household’s prefrences and willingness to pay for

HOUSEHOLDrsquoS PREFRENCES AND WILLINGNESS TO PAY

FOR PESTICIDES FREE FRUIT IN KHYBER

PAKHTUNKHAWA (KP) PAKISTAN

BY

JAHANGIR KHAN

A dissertation submitted to The University of Agriculture Peshawar in Partial

fulfillment of the requirement for the Degree of

DOCTOR OF PHILOSOPHY IN AGRICULTURE

(AGRICULTURAL amp APPLIED ECONOMICS)

DEPARTMENT OF AGRICULTURAL amp APPLIED ECONOMICS

FACULTY OF RURAL SOCIAL SCIENCES

THE UNIVERSITY OF AGRICULTURE

PESHAWAR-PAKISTAN

MAY 2018




BY

JAHANGIR KHAN





Approved by

___________________________ Chairman Supervisory Committee

Prof Dr Abbas Ullah Jan

___________________________ Member (Major Field of study)

Dr Ghaffar Ali

___________________________ Member (Minor Field of study)

Prof Dr Mussawar Shah

___________________________ Chairmanamp Convener Board of Studies

Dr Ghaffar Ali

___________________________ Dean Faculty of Rural Social Sciences

Prof Dr Noor P Khan

___________________________ Director Advanced Studies and Research

Dr Shahid Sattar




PESHAWAR-PAKISTAN

MAY 2018

TABLE OF CONTENTS

S No Title Page No

List of Table i

Acknowledgements ii

Abstract iii

I INTRODUCTION 1

11 Background on Pakistan 2

12 Pesticides-free Food and Products 4

13 Justification of the study 6

14 Purpose and objectives of the study 7

15 Research Questions 8

16 Hypothesis Development 9

161 Hypothesis to be tested 9

17 Contribution of the study 9

18 Organization of thesis 10

II LITERATURE REVIEW 11

21 Illustration of Contingent Valuation Method (CVM) 11

22 Crux of the Double bounded dichotomous choice model premium 13

23 Overview of the Ordered Logit Model 15

24 Factors influencing Householdslsquo Willingness to Pay 19

25 Essence of the Literature Reviewed 27

III MATERIALS AND METHODS 29

31 Khyber Pakhtunkhwa 29

32 Sampling Technique 31

321 Stage 1 _Selection of district Peshawar and Mardan 31

322 Stage 2 _ Selection of Union Councils (UCs) 31

323 Stage 3 _Selection of households from each Union Council 31

33 Allocation of Sample Size for Different Models 32

34 Contingent Valuation Survey Designing 33

35 Householdslsquo Survey 33

36 Conceptual Framework 34

361 Householdlsquos Utility and Willingness to Pay 34

362 WTP and CVM 35

37 Elicitation Techniques 36

371 Bidding Game Approach 37

372 Open-ended Elicitation Method 37

373 Payment Card Approach 37

374 Dichotomous Choice Model 37

38 Empirical Estimation of WTP by Payment Card using Ordered Logit

Model 39

39 Empirical Estimation of WTP using Double Bounded Dichotomous

Choice Model 42

391 Factors which could Influence WTP 43

392 Bids Design 44

310 Empirical Estimation of WTP using Linear Regression Model 44

311 Description of Variables 45

1V RESULTS AND DISCUSSION 46

41 Descriptive Analysis 46

411 Demographic and Socio-economic Characteristics 46

412 Householdlsquos Awareness and Perceptions about Pesticides Application

on Fruit 51

42 Empirical Results of this Research Endeavour 52

421 Distribution of responses on householdslsquo willingness to pay

(WTP) 52

422 Householdlsquos willingness to pay using ordered logit model 53

423 Predicted probabilities and Marginal effects of ordered logit model 56

424 Matrix of Correlation Coefficient 60

43 Householdlsquos willingness to pay using double bounded dichotomous

choice model 63

431 Householdslsquo estimated Mean WTP 65

432 Households Response to First Bid (Amount) 66

44 Post Estimation Diagnostic Test 67

441 Householdslsquo willingness to pay by using linear regression model 68

45 Comparison of elicitation questions formats 70

451 Response rate for zero WTP 71

46 Discussion about Major Findings 72

V SUMMARY CONCLUSION AND RECOMMENDATION 78

51 Summary 78

52 Conclusions 79

53 Recommendations 81

54 Limitation and Suggestion for Future Envisage 82

56 Suggestions 83

LITERATURE CITED 84

Appendix- 1 Questionnaire 96

i

LIST OF TABLE

Table No Title Page No

31 Total population and sampled households from selected UClsquos 32

32 Payment card format 41

33 Bid system for Pesticides free fruits 44

34 Description of explanatory variables 45

41 Age of the householdlsquos head (Years) 47

42 Educational Level of the Householdlsquos Head (Years) 48

43 Householdslsquo size of the Respondents (Member in Number) 48

44 Householdslsquo Income in Pakistanlsquos Rupee (PKR) 49

45 Households expenditure on food (PKR) 50

46 Householdlsquos monthly expenditure share on fresh fruits (PKR) 50

47 Householdlsquos Awareness and Perceptions of Pesticides use on Fruit

Grown 51

48 Factors influencing respondent householdlsquos WTP (Ordered logit model) 55

49 Predicted probabilities and marginal effects from the estimated ordered

logit model 61

410 Matrix of correlation coefficient between explanatory variables 62

411 Factors influencing consumerslsquo WTP (double-bounded dichotomous

choice model) 65

412 Households mean estimated WTP 66

413 Householdslsquo Response to First Bid (Amount) 67

414 Diagnostic test results 68

415 Estimated parameters using liner regression model 70

416 Mean willingness to pay comparison from CV question format 71

417 Comparison of response rates by CV question format 71

ii

ACKNOWLEDGEMENTS

I am grateful to Almighty Allah for blessing me with the potential of seeking

the light of knowledge the taste of gaining knowledge courage and for all the blessings

which enabled me to complete a stage of education

Doing a research is not an individual work Itlsquos indeed the result of efforts by

many people I would like to thanks all people who helped and supported me to

complete this research successfully

My whole hearted and profound thanks to my advisor Dr Abbas Ullah Jan

Department of agricultural amp Applied Economics for his support critical review

valuable suggestions and inspiration to make this research success

My most special thanks to Assistant Prof Dr Syed Attaullah Shah Department

of agricultural amp Applied Economics for his cooperation and valuable suggestions

providing me all facilities during the course of this research

My sincere thanks to Dr Ghaffar Dr Dawood Jan and all faculty members

Department of agricultural amp Applied Economics for their cooperation advices and

back-up to achieve my goals and their encouragement and instrumental support during

the research practical work

I would like to submit my admirations to my friends and foreign research expert

Dr Kar Ho Lim and Dr Aditya Khanal Department of Agricultural amp Environmental

Sciences College of Agriculture Tennessee State University USA for their help

especially in thesis write-up and paper publication

At last but the not least I wish to put across my deep admiration to my parents

friends relatives and family members who support me during my study

Jahangir Khan

iii



PAKHTUNKHAWA PAKISTAN

Jahangir Khan and Abbas Ullah Jan

Department of Agricultural amp Applied Economics

Faculty of Rural Social Sciences

The University of Agriculture

Peshawar-Pakistan

May 2018

ABSTRACT

The over use of fertilizers and pesticides in agriculture are degrading natural ecosystem

and human health The substantial association of health risk with pesticide residues and

its adverse impact on environment has fetched attention of researchers across the globe

In this alarming scenario pesticide free farming is deemed as panacea to

environmental human and animal health friendly production system Pesticide free

fruit are considered to be superior in quality as compared to fruit produced

conventionally and helps in preventing several health and environmental hazards

Therefore the demand for pesticide free fruit is increasing throughout the world Given

this increasing demand for pesticide free fruit this study is designed to measure what

price premium household would be willing to pay (WTP) for fruit free from pesticides

such as apple peach and mango This study also aims to identify factors influencing

householdslsquo WTP decision of pesticide free fruit in Khyber Pakhtunkhwa (KP)

Pakistan The primary data was gleaned from 1000 sampled respondents through face

to face interview from two selected districts namely Peshawar and Mardan KP

Pakistan To elicit householdlsquos WTP information Contingent Valuation Method

(CVM) was employed Contingent valuation is a survey based method used for eliciting

willingness to pay of the householdslsquo for environmental and natural resources

Different elicitation techniques are used to design CV question scenario such as

payment card question double dichotomous choice question and open ended question

Consequently this study used the entire three payment format to elicit householdlsquos

WTP for pesticide free fruit The ordered logit model was employed to appraise the

payment card method However linear regression model was adopted to identify

factors influencing householdlsquos willingness to pay for pesticides free fruit

Nevertheless the double bounded dichotomous choice model was performed to

measure dichotomous choice questions The major results demonstrate that 935 percent

households were willing to pay higher prices for fruit pesticides free in the study area

Estimates remarkably reveal that around 35 percent households were willing to pay 16

to 20 percent higher prices and 24 percent households were willing to pay 6 to 10

percent higher prices for pesticides free fruit than the prevailing prices of conventional

produce It is reported by 61 percent of the households that local farmers use irrational

pesticides on fruit Major findings have also corroborated that 881 percent sampled

household have perceived health concerns over pesticides residues in food Similarly

911 percent of the households have supported the idea that farmer should be engaged

in environmental benign agricultural production practices which have a minimum

adverse impact on health and the environment Socio economic and demographic traits

have confirmed positive significant effects on householdlsquos willingness to pay The

iv

results of householdlsquos head awareness on WTP are according to the prior expectations

that awareness of householdlsquos head has significant contribution in willingness to pay

for pesticides free fruit While householdlsquos size has a significant but inverse effect on

willingness to pay for pesticides free fruit Furthermore householdlsquos perception

regarding health and environment concern has a propensity to positively influence the

willingness to pay for pesticides free fruit It is also depicted by the results that mean

WTP by using double dichotomous payment card and open ended elicitation format

validates consumer demand for pesticide free fruit in the study area Three separate

mean WTP were computed for each double dichotomous choice payment card and

open ended format which were figured as Rs2576 1632 and 1437 respectively

These results reveal market potential for pesticides free fruit in the study area This

research study is expected to contribute in the three different aspects Firstly this study

has figured out the potential for pesticides free markets in Pakistan This study has also

abridged the research gap regarding consumerlsquos preferences and willingness to pay for

pesticides free fruit which can be generalized and replicated to other areas In addition

results have provided insight to fruit producers helping them to strategize production

system decisions Based on the findings from this research government non-

government organization and other stakeholders should formulate policies and would

promote and encourage the production of pesticides free fruit in Pakistan

1

I INTRODUCTION

Pesticides are agrochemical formulated to cope with the severe problems diseases

caused by insects fungi virus and self-grown weeds The term pesticide can be defined

as any chemical or natural substance applied with the objective to repel destroy or

control pests and regulate plant growth (FAO 2002) In modern agriculture arena

pesticides are intensively used on crops before and after harvest The application of

pesticides surged with the passage of time due to an increase in the demand for

agricultural commodities by the burgeoning population of the world The overall

pesticidelsquos consumption across the globe is observed as about 2 million tons per year

While this massive pesticides consumption demonstrates that about 69 percent is used

by European countries and the remaining 31 percent is utilized by the rest of the world

as mentioned by Abhilash and Singh (2009) The more alarming situation is that the

aforementioned magnitude of pesticides consumption is increasing with the every

passing year as reported by FAO (2002)

The green revolution as well as a huge increase in the application of pesticides in the

agriculture realm had enhanced food and non-food crop production Resultantly the

significant surge in the economic growth of several agricultural based economies was

reported over the last few decades as demonstrated by Carvalho (2006) Despite the

substantial contribution of pesticides to diminish the food insecurity societies around

the world are cognizant and concerned about the food sanitation safety and

environmental externalities owing to irrational use of pesticides and other croplsquos input

(Wilson 2000) More categorically the food safety realization in developed countries

has been led to organic agriculture Whereas in many developing countries which

include but not limited to Pakistan the pesticides-free and organic food markets

remained underdeveloped due to several reasons One of the obvious reasons is the

uncertainty among consumerlsquos preference that led to their concern if an organic market

can be self-sustained Similarly a dearth of proper market structures and institutional

support failed to provide environment-friendly agriculture practices in developing

countries (Rehber and Turhan 2002) The current scenario of agriculture sector in

developing countries has raised several considerable questions to acquire the

anticipated implications for this sector However the most relevant query drifted that

2

―Is there sufficient consumerlsquos willingness to pay (WTP) available in a developing

country for grass-roots development of pesticide-free agriculture

11 Background of the Research Endeavor

Agriculture sector is the mainstay of Pakistanlsquos economy which significantly

contributes as 192 percent to overall Gross Domestic Product (GDP) of its economy

(GOP 2016-17) Despite many efforts and policy reforms still this sector is entangled

with insignificant growth momentum

Since the inception of this country in 1947 there wasnlsquot any notable crop and plant

protection policy adopted by concerned policy makers over a long span of time It is

evident from past timeline that ―Grow More slogan was initiated by the government of

Pakistan back in 1970s to address the escalating foodlsquos demand of rapidly increasing

population of Pakistan Subsequently Grow More policy resulted in ever increasing

pest problem which couldnlsquot be controlled with conventional crop management

practices Therefore the government started to provide the direct subsidy to Pesticides

Industry to provide panacea to croplsquos pest problem But unfortunately the colossal

surge in pesticides utilization had not only destroyed the pests but was also found lethal

for the environment benign organisms that include predators birds etc This irrational

use of pesticides and other crop inputs has caused huge economic loses and health

issues among the farming community

Pakistanlsquos agriculture is endowed with 11 (Eleven) different agro-ecological zones

providing the country an incredible exciting arena for experimentation and state of the

art for agriculture as reported by Altaf (2010) This diversified nature of ecological

zones can be utilized in a lucrative way to attain an optimal output The driving forces

of this sector are striving hard to curtail the gaps by ensuring the adequate production

and supplying the food to meet the demand of rapid growing population of the country

However the emerging challenges such as irrational use of croplsquos input and complying

with world trade organization (WTO) obligations are insisting the concerned policy

makers to focus on paradigm shift for significant contribution of agriculture towards

livelihood welfare and prosperity

3

These different agro ecological conditions provide the encouraging and conducive

environment for the production of cereal crops fruits vegetables and even for non-food

crops Fruits and vegetables grown in Pakistan have a wide domestic demand and have

also attracted the international consumer by exporting these edibles in the international

market Pakistan exports mango apple dates oranges guava and dry fruits like pine

nuts to different countries which include but not limited to Afghanistan UAE Saudi

Arabia and Europe (GOP 2014-15)

The relative importance of agricultural sector can be gauged with high growth rate of

exports of fruits and vegetables from Pakistan to different countries mainly South East

and the Middle East (Khalid Mustafa 2003) where low Sanitary and Phytosanitary

(SPS) standards are comply with Yet several more fruit grown in Pakistan have

enormous potential to be exported in the international market Specifically insect pest

infestation during pre- and post- harvest of fruit and vegetables is a significant problem

To protect from those many kinds of pesticides and agro-chemicals are widely used in

Pakistan These include different types of agro-chemicals which consist more than 100

types of insecticides almost 30 types of fungicides and approximately 39 different

types of herbicides (Zia et al 2009Anwar et al 2011) In 1960 the consumption of

chemical pesticides in Pakistan was 7000 tons per year which has risen to 78 232 tons

per year in 2003 (Syed and Malik 2011)With the development of pest resistance to

those chemicals over years each year new chemical compounds in large amount are

used to protect crops Overuse of these agro-chemicals has caused many adverse health

and environmental effects

However significant variation in consumer behavior in the developed countries has

excelled the demand of high quality food which had encouraged the organic

agriculture Thatlsquos why developing countries who have still adopted obsolete strategies

for pest control are out of race for agriculture export and are at venture to be considered

as ―dirty producer in an international market Similarly in Pakistan massive increase

in the pesticidelsquos use has escorted to two major harms to Pakistanlsquos economy Firstly

Pakistan imports a large quantity of pesticides incurring billions of costs on it and

second overuse of pesticides on agricultural commodities has created many health and

environmental hazards in the farming community of Pakistan Several research

endeavors such as Ahmad et al (2004) Rizwan et al (2005) Parveen and Masud

4

(2001) had divulged that individuals working in field under pesticides exposed

environment specifically women who worked long time in the cotton croplsquos field

sustained more health hazards These health hazard underscored skin irritation

headache nausea and gastroenteritis It is also evident that the hazardous chemical

residues of organo-chlorines organophosphate and synthetic pyrethroids pesticides

were found in 85 percent of the blood samples drawn from 75 sampled individuals

(male and female) in Pakistan

12 Pesticides free Food and Products

Pesticides free fruit and vegetable are those edibles that are grown without the use of

pesticides and can be deemed as major component of an organic farming Due to

awareness among people about advantages of Pesticides free fruit and vegetable which

upshot in food safety and benefit environment as well the production and consumption

of such food products is being highly valued With the consumption of food produced

without the use of pesticides can be helpful in the prevention of some of the health

hazards related with the consumption of conventional food (Nouhoheflin et al 2004)

The term ―Pesticides free was introduced for the first time in a book ―Look to the

Land in 1939 by Lord Northbourne The author narrates pesticides free farm as an

organization that making use of environment balance technique by adopting zero

pesticides In early 20th

century pesticides free food ideology was brought forward

while correspondingly there was an immense use of chemical in food products as well

Householdslsquo were having great concern about their health as well as soil condition and

they began to grow such food which was free from chemical residuals In the era of

70s a noteworthy change was reported in escalating the demand of pesticides free food

and pesticides free farming Therefore in year 1972 ―International Federation of

Pesticide free Agriculture Movement was formed In the same era the producers who

were producing pesticides free food individually commenced the certification process

The obvious aim of the process was to develop rules and to underpin the standards of

pesticides free production

In this modern era where food consumers are highly concerned about their health safety

and environment benign practices they prefer to buy pesticides free food products

This is because of their knowledge about the relationships between the production

practices and quality of food produced Consumers are becoming more conscious as

5

they are aware of the harmful effects of food produced with irrational pesticides use on

their health Many research endeavors have corroborated that fresh fruit and vegetables

confers health related benefits and provide protection against the risk associated with

different types of diseases like diabetes stroke and cancer(Van and Pivonka 2000 Stan

Kar Stoner Singh 2008) Likewise the world health organization (WHO) has

revealed in their research carried out in 2002 that the fruits and vegetables

contaminated with pesticides can cause about 31 percent of diseases related to heart and

11 percent stroke in all over the world However if best quality of fruit and vegetable

consumption is adequately increased it is projected that about 27 million of lives can

be protected each year Pesticides free food contains higher level of antioxidants which

fight against various diseases and provide different essential vitamins More

importantly pesticides free food products also aimed to prevent from some allergies

and diseases common in human being It is corroborated by other research studies that

chemical fertilizer free food are beneficial for human health as well as for the animals

wildlife and for the ecosystem To encourage such agricultural management techniques

in developing countries in general and Pakistan in particular still there is long way to

go but such research studies can provide the paved way to open new avenues for the

concerned policy makers and stakeholder in the realm of Agriculture

In addition locally grown pesticide free produce tends to fetch higher prices due to

sanitation concerns of the consumer and improved quality of the product Subsequently

such produce are preferred by the household and they are agree to pay a price premium

for such food produced free from pesticides compared to prevailing regular market

price of conventional food products Thus it is important to measure householdlsquos

willingness to pay for locally produced pesticide free fruit To acquire a good or

service consumerslsquo wants to sacrifice an extra amount of money which show their

willingness to pay Willingness to pay can also be defined more categorically as the

extra amount of money that an individual wants to pay for best quality of food (Lusk

and Hudson 2004) The commonly used model for eliciting householdlsquos willingness to

pay information is Contingent Valuation Method (CVM) Contingent valuation (CV) is

a survey-based method which is used to elicit householdlsquos willingness to pay for

environmental and natural resources

6

12 Justification of the Study

With the every passing year the demand for agriculture products is hiking due to rapid

increase in the worldlsquos population Pakistan being an agrarian country is striving hard

to fulfill the domestic and international demand for agricultural food To overcome the

escalating demand for agricultural product farmers mainly depend on chemical

technologies to manage pests and to provide enough food Besides their benefits now it

is clear that pesticides are negatively influencing human health and also the natural

environment The food that we are eating has gained more discussion in all over the

world including developing countries like Pakistan that whether this food is safer for

human health and for natural environment Consumers are facing with problemslsquo which

food is safe to eat and which is not safe Which food processing is beneficial for human

and environment and which is worse (Bold et al 2015 Chiew Shi Wee et al 2014

Sirieix 2011 and Butt et al 2015) Most of people are turning towards the production

and consumption of pesticides free food to resolve these issues

In developed countries consumers are highly concerned about the excessive use of

chemicals on food and its negative impact on health and natural environment thatlsquos

why the production of food produced without the use of pesticides Large numbers of

studies are conducted on consumerslsquo perception regarding pesticides- free food in

developed countries like Europe Australia United State and New Zealand but in

developing countries very little is known about consumerslsquo perception regarding

pesticides-free food

Despite the fact that food production without pesticides and other chemicals are safe for

health and environment its production and consumption is very low In Pakistan only

few farmers are using chemicals free technology for food production It has only 28

farms producing pesticides-free food which they just growing for their own

consumption not for commercial purpose In Pakistan there is high gape of information

about consumerlsquos perception and awareness regarding pesticides-free food and

consumerslsquo willingness to pay for pesticides-free food (Panhwar 2004)

Keeping in view the human health hazards and environmental vulnerability owing to

irrational use of pesticides alternative farming systems such as pesticides free farming

integrated pest management (IPM) and organic farming is becoming progressively

7

more popular in the global context However in the country like Pakistan where costly

input and lower output agriculture was a historic focus Following the Green

Revolution in 1960s adoption of certified organic production is expected to be fairly

low Nevertheless aforementioned agriculture practices could be an alternative system

in convincing farmers towards safe and sustainable agriculture and to comply with the

strict regulations and mandates of certified organic system and WTO Moreover due to

conducive and diversified weather and climatic condition of the country and relatively

cheaper labor force availability production of such safer food seems feasible

Pesticides free food is supposed to be having high prices however it is important to

examine whether households are willing to pay a higher price for these pesticides free

fruit According to the research study conducted in different countries of the world on

pesticides free food this study also focus to investigate a price premium that

households are willing to pay for pesticides-free fruit and factors influencing their

decision For this purpose Khyber Pakhtunkhwa (KP) is selected as a research area

Khyber Pakhtunkhwa (KP) is blessed with fertile soil and plenty of water for irrigation

and is famous for production of delicious fruit such as peach apple guava plum

mango Pear apricot date and citrus Fruit farming has been an important business of

Khyber Pakhtunkhwa and the total fruit production during 2015-16 was 411448 tons

from 44737 hectare (GOKP 2015-16) Given that the region is one of the important

fruit growing regions with relatively readily available agricultural labor growers has

the potential to produce pesticides free fruit in this region In this direction more

research work is required to estimate a price premium householdslsquo willing to pay for

fruit free of chemicals and pesticides Thatlsquos why this study is designed to measure

what price premium households would be willing to pay for pesticides free fruit and

improvement in apple peach and mango quality produced by farmers

14 Purpose and objectives of the Study

The irrational and overuse of pesticides in agricultural food production causes severe

damages to human as well as animal health and to the environment too Thus a new

production and new system is needed to overcome these problems and to limiting the

use of these hazardous chemicals during production process The risk of harmful effects

on health and environment are generally reduced with pesticides free farming compared

8

to conventional farming methods Hence pesticides-free farming has the potential to

provide a healthy and safer environment The purpose of conducting this study is to

understand the factors that influence householdlsquos behavior in purchasing pesticide free

food and their willingness to pay for such food The main theme to carry out this study

is to discuss on the variables which determines householdlsquos behavior in the buying

pattern of pesticide free food Besides this research also aims to increase the

understanding on householdlsquos awareness attitude and perceptions towards pesticide

free products

The general objective of this study was to investigate what price premium householdslsquo

are willing to pay for pesticides free fruit produced locally

The specific objectives of this research study are mentioned as below

To study socio-economic characteristics of household and their expenditure on

fruit

To investigate householdlsquos perception towards the use of pesticides on fruit

production

To identify factors influencing householdlsquos willingness to pay (WTP) for

pesticides free fruit

To compare householdlsquos willingness to pay across urban and rural regions of

the study area

To examine the effect of different contingent valuation elicitation format on

householdlsquos WTP

15 Research Questions

1 Do householdlsquos willingness to pay a price premium for pesticide free fruit

produced locally is affected by their socio-economic characteristics

2 Do householdslsquo willingness to pay price premium for pesticide free fruit

produced locally are different in rural and urban regions


produced locally are affected by WTP question format

9

16 Hypotheses

Hypothesis is a proper statement that shows the expected association between an

exogenous and endogenous variable (Creswell 1994) Hypothesis is mainly of two

types the null (Ho) and the alternative (H1) hypothesis The null hypothesis is a

statement about the relationship between the dependent and independent variables

while the alternative hypothesis is tested for the acceptance or for the rejection of null

hypothesis through using different test-statistics and usually opposite to the null

hypothesis

161 Hypotheses to be tested

Hypothesis 1

H1 Socioeconomic characteristics have significant effect on householdlsquos WTP

for pesticides free fruit produced locally

Hypothesis 2

H1 Rural and urban locations have significant effect on householdlsquos WTP for

pesticides free fruit produced locally

Hypothesis 3

H1 WTP question format have significant effect on householdlsquos WTP for


17 Contribution of the Study

The major findings of this research endeavor could be lucrative to pesticides-free food

industry players in designing and implementing programs relating to the production

marketing and consumer behavior regarding fruit and vegetable The study is providing

information regarding householdlsquos willingness to pay an extra amount for pesticides

free fruit at market place The identification of factors influencing purchase of

pesticides free food provides valuable information in formulating short and long term

marketing programs Also the outcomes of the study provide benefits to Government

in their policy making towards pesticides-free farming and pesticides free products

Pesticides free fruit could contribute significantly to wealth formation poverty

lessening and can assess to export market Pesticides free fruit provide healthy food and

natural environment to the society

10

18 Organization of thesis

This study is organized into five chapters In the first chapter background of the study

research questions study hypothesis research justification and contribution of this

study is discussed Chapter two is consist of review of literature related to consumerslsquo

perception market potential and market prospects empirical research studies on

consumerlsquos willingness to pay and consumer knowledge about pesticides free food

socio-demographic variables and their effects on willingness to pay price premium are

discussed Chapter three discuss in detail the study area conceptual and empirical

framework on consumerslsquo willingness to pay and contingent valuation methods are

discussed Chapter four presents descriptive analysis and results obtained from

empirical findings and Chapter five provide summary conclusion and recommendation

and future suggestions on the basis of research findings

11

II LITERATURE REVIEW

Literature review is a synthesis of previous study in the content of a thesis In this

chapter different past investigation are reviewed Mostly this chapter concern on the

methods adopted by different researchers while measuring willingness to pay It also

figure-out various explanatory variables which have been found influencing

householdslsquo willingness to pay an extra amount of money for pesticides-free food

Previous researches on perception questions are also discussed

21 Illustration of Contingent Valuation Method (CVM)

A number of research studies are undertaken across globe to investigate about

consumerslsquo WTP for safer foods such as organically produced pesticides free or

naturally grown Most of the WTP studies use contingent valuation methods where

hypothetical market scenario is developed and subjects are asked to name their WTP

price as compared to existing market price Different techniquesquestionnaires are

used in contingent valuation method where respondents are directly asked to state their

maximum amount of money they are willing to pay for specified improvements in

environmental or health quality The methods used in CVM includes personnel

interview mail and survey that elicit consumerlsquos WTP for those goods yet not available

in the market Survey questions include single bounded double bounded dichotomous

choice and open ended or closed ended (Lusk and Hudson 2004)

Misra et al (1991) studied consumer preferences and their willingness to pay for

pesticides free fresh produce by applying contingent valuation method An ordered

probit model was adopted to know householdlsquos stated willingness to pay for products

free from pesticides residual The study also aimed to know the factors affecting the

probability of householdslsquo WTP for a number of alternative price premiums The

results indicated that householdlsquos willingness to pay was different across different

factors The study concluded that testing and certification was the recommendation of

the households Results also showed that consumers in the study area opposed higher

prices for certified-FPR fresh produce

In another study Gil et al (2000) adopted contingent valuation method and studied

consumerslsquo willingness to pay for pesticides free fruit in Spanish regions Results

showed that consumerslsquo concern over health and environment was increased Results

12

also suggested that due to the adverse impact of conventional food on health and

environment demand for pesticides-free food has raised Results of the study also

showed that consumerslsquo were willing to pay more prices for fruits vegetables and

meats which were free of pesticides

Boccaletti and Nardella (2000) used contingent valuation method to assess householdlsquos

willingness to pay for pesticides free fresh fruit and vegetables To know the impacts of

explanatory variables on the probability of householdslsquo willingness to pay different

price premium an ordered logit model was used and results were reported A

significant and positive effect of income on householdlsquos willingness to pay was

observed Results of the study also suggest that householdlsquos education and associated

risk concern has an inverse relation with households WTP

In another study Millock et al (2002) conducted a research study by using contingent

valuation technique to estimate willingness to pay for pesticides free products through

panel data The information collected was based on weekly report of householdslsquo

purchases of 2000 Danish families Questionnaires were sent to households and asked

them to differentiate different food attributes The food product attributes were included

environmental issues animal welfare and food safety The result showed that

household had given high value to food free from pesticideslsquo residues

Similarly in a relevant study Cranfield and Magnussan (2003) studied willingness to

pay of the Canadian householdlsquos for those products which were free from pesticides

residuals by applying an Ordered Probit Analysis model A contingent valuation (CV)

study was attempted to know that if Canadian households would pay a price premium

for pesticides free food products About sixty five (65) percent of the householdlsquos were

willing to pay a 1 to 10 percent extra amount of compared to those products

contaminated with pesticides residuals About five percent of the total respondents were

willing to pay more than 20 percent price premium The main determinants that switch

over the households to pay higher premiums for pesticides free products were

householdslsquo health concern and environmental concern

In a relevant study John and Eric (2004) developed a survey based research to find out

householdlsquos choice of paying an extra amount for fresh and pesticides free products by

using a contingent valuation technique According to their research 65 percent of

13

households were willing to pay one to ten percent extra prices for pesticides-free

products as compare to conventionally produce one five percent respondents willing

to pay more than twenty percent Health and natural environmental issues youth and

grocery stores were the important factors influencing consumers to pay higher prices

Masias et al (2012) carried out a research study in Spain to analyze the level of

knowledge consumption and consumerlsquos willingness to pay for organic vegetables

such as organic tomatoes By using contingent valuation method three distinct

consumerslsquo groups were identified The results showed consumerlsquos lack of knowledge

regarding organic vegetable Result of the study revealed a clear relationship between

level of knowledge and organic food consumption and consumerslsquo potential willingness

to pay

Boys et al (2014) conduct a research study in Dominica to assess willingness of the

consumerslsquo and their opinion for organic or locally grown produce By adopting

contingent valuation method (CVM) maximum likelihood estimation (MLE) procedure

was applied Findings from the study reported that respondents in Dominica were

willing to pay 175 percent for organic and 12 percent price premium for locally

produced food Results of the study showed that consumer response towards

willingness to pay was different across socio-demographic characteristics family health

status and experience regarding adoption of organic food products

22 Crux of the Double bounded dichotomous choice model

Many recent research studies deployed double bounded dichotomous choice model to

study consumerslsquo willingness to pay for pesticides free organic and related food

Owusu (2010) studied and analyzed market possibility for new pesticides free lettuce

and water melon by using a double bounded dichotomous choice contingent valuation

technique in the city of Kumasi in Ghana The information of the respondents was

collected By applying a Tobit model householdslsquo willingness to pay was assessed

More than 50 percent price premium were paid by 71 percent of the respondents for

natural vegetables and 82 were willing to pay 1 to 50 percent higher premiums for

natural fruits Results showed that human capital food qualities and householdlsquos

recognition impact householdlsquos willingness to pay for pesticide free commodities The

14

evaluated market possibility for pesticide free fruits were (GHcent32117113 US$

26453433) for every annum and for naturally produced vegetable was GHcent1991224

(US$1640083) per year suggested an immense market possibility for naturally

produced fruits in Ghana

sum

(

)

(

)

Where

are binary valued (0 or 1) indicators and the formulas

for the corresponding response probabilities are given above The model was estimated

through maximum likelihood estimation method and the results were used to find out

the mean and individual WTP (s) for pesticides free fruits

Where ƒ(WTP) is a function X is a set of socio-economic characteristics are

coefficients and is error term

In another study Cerda et al (2012) investigated different markets regarding

respondentlsquos preferences and willingness pay a price premium for products free from

pesticide in Chile Conjoint analysis was also used to estimate the marginal willingness

to pay of the consumer for pesticide-free apple A total of 400 individuals were

interviewed to know householdlsquos willingness to pay and to determine different

attributes that consumer search when purchasing apple by using a logistic probability

function and single-bound dichotomous elicitation format The output showed sweet

apple lowest price and pesticides free production attributes were preferred by

households Results of the study revealed that consumers in the study area were willing

to pay about 130 Chilean pesos kilogram for pesticide free apple

By using double bounded dichotomous choice approach Minh et al (2013) conducted

a research study on consumption and willingness to pay a price premium for pesticides

free vegetables in Vietnam Under contingent valuation method 185 respondents were

surveyed and analyzed Results showed that about 15 percent of the consumers had

already used pesticides free vegetables and 88 percent sought to try and purchase such

products if available in the market Result revealed that consumerslsquo were willing to pay

15

on average 70 percent more amount for pesticides free vegetable than the convention

price Findings also showed that respondents with more concerned about pesticides free

food and high purchasing power were more likely to pay extra amount of money

Findings of the study showed most of the consumers were still worrying about safe

food because of chemical residues in vegetables Results suggest that control of

pesticides level was difficult for state agencies because of insufficient capabilities

Some recommendations were suggested based on findings of the study such as the

consumers should be informed regarding organic vegetables and information should be

publicized to consumers and to expand organic market share in the future new shops

should be open

Hai et al (2013) conducted a research study on consumption of organic vegetables and

consumer WTP for vegetables produced without the use of pesticides in Vietnam They

reported in their study that most of the consumers were still worrying about safe food

because of chemical residues in vegetables Control of pesticides level was difficult for

state agencies because of insufficient capabilities By using double bounded

dichotomous choice approach under contingent valuation method 185 respondents

were surveyed and analyzed The results showed that about 15 percent of the

consumers had already used pesticides-free vegetables and 88 percent of the total

respondents desired to try and purchase if such pesticides free products were available

in the market On average consumers were willing to pay 70 percent more price than

the convention price Findings of the study also showed that respondents with high

income and more concerned about pesticides-free food were more likely to pay price

premium

23 Overview of the Ordered Logit Model

Regarding discrete nature and ordinal ranking of the WTP variables in payment card

method an ordered logistic regression was applied in many research studies Ordered

logistic regression is the most appropriate choice in studying these issues (Green

2007) Under latent variable framework the willingness to pay model can be written as

follows

16

Where is an unobserved latent variable reflecting the WTP for pesticides-free fruits

for household i expressed in terms of utility to switch from the traditionally grown

fruits consumption to pesticide free fruits is a parameterlsquos vector reflecting the

relationship between WTP captures a set of socioeconomic and demographic

variables influencing WTP and is the unobserved disturbance term reflecting

stochastic differences between households not controlled for The relationship between

the unobserved and the observed outcome for household ( =0 1 2hellipj) can

be summarized as follows

It is presumed that ɛ is normally distributed across observation

With regards to ordered logistic model Valchovska S (2004) investigated Dutch

householdlsquos attitudes and behavioral intentions to purchase pesticides-free olive oil By

applying CVM to assess consumer willingness to pay a price premium for pesticides

free olive oil on the Dutch consumer an ordered logit regression model was used

Results suggested that willingness to pay did not depend on socio-demographic factors

but rather on consumers awareness and experience with the product Results also

showed that experience regarding the product was significantly related to purchase

intention and willingness to pay Most of the consumers considered pesticide-free olive

oil to be too expensive Results suggested high prices appeared the biggest constraint

on consumption Results clearly verified that consumerslsquo familiarity with pesticide-free

olive oil in the Netherlands was low at present This situation may however be

changed by a possible increased availability of the product in the supermarkets

17

Rodriguez et al (2008) carried out a research study to measure consumers WTP for the

available pesticides free products in Argentina domestic market The data was collected

through a survey from the consumers of Buenos Aires city For the analysis of data a

binomial multiple logistic regression model was applied Five different organic

products such as regular milk leafy vegetables whole wheat flour and fresh chicken

and aromatic herbs were selected for the research The method of contingent valuation

(CVM) was adopted to estimate consumerslsquo stated willingness to pay The result

revealed that pesticide free agriculture has undergone momentous expansion and

consumers in the study area were willing to pay a higher amount of money for such

organic products Research results suggest that along with price that play a significant

rule while consuming organic products non availability of stores for organic products

and a reliable regulatory system limits the consumption of pesticides free organic

products in the study area

According to Kalogeras et al (2009) carried out a research study that concentrates on

the identification of Dutch householdslsquo willingness to pay (WTP) for natural olive oil

The study was carried out in 5 biggest Dutch cities in Netherland To evaluate the

impact of explanatory variables on householdslsquo willingness to pay a price premium for

natural produced olive oil an ordered logit regression model was constructed Results

suggest that experience awareness and consumerslsquo personnel satisfaction were the

variables influencing consumerslsquo WTP for natural olive oil

Travis et al (2009) conduct a research on consumer purchasing behavior for pesticides

free fruits and vegetables To identify the impact of socio-economic and socio-

demographic characteristics on the probability of consumers belonging to certain

groups like devoted casual or nonuser an ordered logistic model was used Results

showed that factors like price and income were influencing householdlsquos willingness to

purchase pesticides-free fruits and vegetables to some extent The results also showed

that respondents with a college degree children aged more than six years and aged

above than fifty years were willing to purchase pesticides-free fruits and vegetables

Zeki and Zia (2009) carried out a research study to investigate consumerslsquo stated WTP

for tomatoes produced free from pesticides residues The study also aimed to measure

the impacts of socio-demographic and hazard variables on WTP Ordered Probit model

18

was used to figure out the likelihood of WTP for pesticide free tomatoes The

information was acquired from 666 respondents by survey method in Ankara and Tokat

regions at same occasion The study results revealed that 3423 percent of Turkish

households were not willing to pay 7702 percent willing to pay a 30 percent higher

amount of money and 22 97 percent would be willing to pay more than 30 percent

premium According to the results Turkish households were paying a little price

premium for tomatoes produced free from pesticides Furthermore the important

factors significantly influencing willingness to pay for pesticides free tomatoes were

gender education statue of mother recognizes for ecologic agriculture solid

sustenance and risk

Oyawole et al (2016) conducted a study in Nigeria to asseslsquo consumer awareness

benefits and willingness to pay for organic vegetables Descriptive statistics and logit

model was used for the analysis of data According to the research findings about 70

percent of consumers were aware of the benefits of organic agriculture and hence they

were willing to pay price premium Results showed that factors influencing willingness

to pay positively were higher education and consumer awareness regarding organic

food while age income and gender had no significant influence on consumer

willingness to pay

Hayati et al (2017) conducted a research study in Marand city to identify factors

effecting consumerslsquo WTP for pesticides-free fruits and vegetables To assess

respondentlsquos willingness to pay an ordered logistic regression model was applied By

using Contingent valuation method data was collected from 394 respondents The

results revealed that 33 of the respondents were willing to pay 20 more price

premium 64 showed 5 to 20 more price premium while only a small portion 3

of the total sample of the consumers were not willing to pay more price for pesticides

free fruits and vegetables Findings of the study also revealed that factors such as

income of the respondent environmental and health concern and consumerlsquos

knowledge regarding pesticides free fruits and vegetables were significantly affecting

respondentslsquo willingness to pay for vegetables and fruits free from pesticides residues

19

24 Factors influencing Householdsrsquo Willingness to Pay

Based on the literature review factors influencing households WTP a price premium

are discussed below

WTPj = β0 +β1Agej + β2Genj + β3Eduj+ β4Hsizej + β5Incj + β6Locj + β7Healthconj+

β8Envirconcernj +

Where

WTP = Willingness to pay for pesticides free fruit = Householdslsquo head age in years

= Gender status of the householdslsquo head = Education level of householdslsquo head in

years = Householdslsquo size = Income of the household = Householdslsquo

location = Health concerned = Environment concerned micro=Error term

Govindasamy and Italia (1991) investigated households in different grocery retail

markets in New Jersy to know their different opinion regarding pesticides free

products The main theme of the research study was to know demographic

characteristics that caused the household to pay a price premium for products free from

pesticides residues than the price prevailing in the market The result showed the

influencing factors that caused the individual to pay more price premium for pesticides

free products were demographics characteristics such as females those having higher

income and young individuals The result also showed that number of member in

households had an inverse relation with willingness to pay More individual in a house

were not willing to pay higher prices for pesticides free products

Piyasiri and Ariyawardana (2002) conduct a research study to identify market potential

and consumerslsquo expectations for pesticides free food in Kandy Sri Lanka The study

also aimed to identify factors influencing consumerslsquo willingness to pay price premium

for pesticides-free food Results revealed that most of consumers in the study area were

aware of the use of pesticides free food and this awareness influenced their

consumption of organic food and willingness to pay more for organic food Results

showed that socio-demographic characteristics like income education of the

respondents beside environment knowledge were the important factors influencing

consumerslsquo WTP for pesticides-free food Study suggested that market for organic food

could be enhanced by availability of organic food in easily accessible shops and market

20

should also direct awareness in consumer regarding demand and consumption of

organic food

Qingbin and Junjie (2003) conduct a study to identify market potential for pesticides

free apple and milk by adopting a conjoint analysis technique in Vermont State of

USA Results found that there was a significant niche market for pesticides free apple

and milk The results also suggested that especially those consumers who were

regularly purchased pesticides free products were willing to pay price premium for

apple and milk produced without the use of chemicals and certified by NOFA

Heo and Kim (2004) investigated green marketing strategies and willingness to pay for

environment-friendly agricultural products in the Metropolitan area The results

revealed consumerlsquos WTP for grain vegetables fruit and processed foodstuffs were

206 percent 202 percent 193 percent and 172 percent respectively higher than

agricultural products produced by conventional farming method

Gracia and Magistris (2007) conduct a research study to know consumerslsquo purchasing

behavior regarding pesticide-free food and also factors influencing food purchasing in

Iran A multivariate limited dependent variable model was used Results showed that

households purchasing pattern was more for pesticides free products and they

purchased such safer products in large quantity Findings of the study showed that

purchase of pesticide free products depends on householdlsquos behavior and information

regarding the product Moreover householdlsquos behavior regarding health concern and

environment concerns given by pesticides-free products were the factors that explained

both intension and final decision to purchase pesticide free products Income and

information about pesticide free products had a significant positive influence on the

decision of the consumer to purchase pesticides free products

Kamal et al (2009) studied householdlsquos willingness to pay a higher price for

pesticides-free products in Kathmandu valley About 180 respondents were interviewed

by using well designed questionnaires to find out their perception for pesticide-free

food commodities and asses their willingness to pay The study revealed that almost all

the respondents were willing to pay a higher price for such food but the level of

acceptability varied Up to 58 of the respondents were willing to pay 6- 20 more

price while 13 were willing to pay half premium The average price premium was

21

noted about 30 Over 39 of the respondents suggest the extra price is reasonable for

pesticide-free food while 27 suggest it a really higher price However results showed

that the consumption of pesticide free food had increased

Morteza et al (2009) conducted a study to examine consumerslsquo willingness to pay for

pesticides free fruits and vegetables The results showed that variables such as socio-

demographic characteristics and perception of the respondents regarding environment

and health concern were influencing consumerslsquo WTP for pesticides free food

Environment concern was the important factor of consumer willingness to pay but

results from this study showed that respondents in New Brunswick gave more priority

to health as compare to environment Results also indicated a positive influence of

income and health concern on consumer willingness to pay for organic food

Ghorbani and Harnraz (2009) carried out a research study on factors influencing

consumer WTP for pesticides free products in Iran By applying Tobit model the

results showed that physical look and information of consumerslsquo were the influencing

factors affecting willingness to pay higher price Consumerlsquos concern of chemicals

residues in diets were also positively affecting willingness to pay In demographic

characteristics such as education of the respondents had negative effect on WTP The

study suggested that farmers and consumers should be encouraged to produce and

consume pesticides-free food Study also suggests that marketing strategies should be

encouraged for the marketing of such organic food products

Akgungor et al (2010) carried out a research study to estimate consumerslsquo perception

regarding safe food and the trade-off that urban Turkish consumer made between good

quality and chemicallsquos free fresh fruits and vegetables The date was gathered from a

representative sample of urban consumers The results suggested higher income and

more educated respondents were highly interested and they had more knowledge

regarding organic products Results showed suggested reason for choosing organic

products was consumerslsquo perception regarding organic products of low health risk and

higher nutritional value Results showed 36 percent higher price premium consumers

were willing to pay for organic food that suggests urban Turkish consumerslsquo demand

for organic products

22

Oraman and Unakitan (2010) analyzed factors influencing Turkish consumerslsquo

purchasing decisions for fruits and vegetables The survey conducted in Istanbul by

applying logistic model Results of the survey showed that health and safety concern

were the important factors influencing consumerslsquo preferences regarding organic food

Findings of the study would help organic food producer in targeting factors that were

influencing consumerslsquo decisions to purchase organic food products

Bektas et al (2011) conducted a research study to determine level of consumerslsquo

awareness regarding food safety in Izmir Turkey by applying Probit model Results

revealed that consumerslsquo with high income and more education were more aware

regarding safer food Outcome of the study also identified aged respondents had more

probability for healthy and safe food products Results suggested that awareness for

safer food should be passed through informative campaign targeting especially low and

middle income groups as well as low education level population

Coulibaly et al (2011) studied the health risk caused by using large quantity of

chemicals and pesticides on vegetables By using a hedonic pricing model they

identified the determinants of the householdlsquos WTP for pesticide free products

Information was collected through a well designed questionnaire on householdlsquos

perception awareness and consumerslsquo willingness to pay for pesticide free vegetables

The perception of householdlsquos for good quality vegetables included color freshness no

external damage and firmness The most important factor effecting householdlsquos choice

to pay more for pesticide-free vegetables were awareness about the health hazards

caused by those chemical Households were willing to pay more than fifty percent for

those products free of such pesticides and chemicals

Joyce et al (2011) conduct a survey to examine consumerslsquo perceptions and to assess

their willingness to pay for pesticides-free product They surveyed 100 households in

Morogoro municipal The results presented showed that 78 of the respondents were

willing to pay a higher price for pesticides-free food The results revealed that

environment and health concern were the most important factors effecting householdlsquos

willingness to pay for organic food Results from the survey suggested that

consumption of pesticides free food were increasing but need certification labeling

processing and packaging to boost up the demand

23

Sangkumchaliang and Huang (2012) conducted a survey on consumerslsquo perception and

attitude towards organic food products Results showed that consumers were

purchasing organic food products because of the expectations that organic food is

healthier and safer to the environment Results also revealed that respondents with old

aged and more educated were more willing to purchase organic food products The

study suggested that consumerlsquos information needed to purchases organic food

Owusua and Anifori (2013) analyzed the willingness of householdlsquos to pay an extra

amount of money to watermelon and lettuce produced naturally or free from pesticides

by applying a (CV) contingent valuation information starting with urban Kumasi in

Ghana The impacts of the determinants of the householdlsquos willingness to pay a higher

price were examined with a Bivariate Tobit model Results showed socioeconomic

characteristics as well as freshness and cleanness of products had a great influence on

householdlsquos choice to pay a higher price than they pay for conventional products

While householdslsquo size has a negative impact on consumerslsquo willingness on paying

premium to natural lettuce The estimated mean householdlsquos willingness to pay for

pesticide free watermelon was Ghcent05554 (US$ 0 4575) and for natural lettuce was

GHcent12579 (US$1 0361)

Haghjou (2013) investigated that the demand for those products that was grown without

the use of pesticides has increased amazingly in the recent years The study was carried

out to assess the factors effecting householdlsquos willingness to pay a higher price for

organic products accessible in the Argentinean provincial market The output of the

study reveals that 95 of the respondents were willing to pay a higher price while 10

of the householdlsquos were like to pay about 35 percent higher price than the market

existed price for naturally grown products The results suggested that householdslsquo

income family size ecological problems including respondentslsquo knowledge has

enhanced their desire to pay higher price for pesticide-free products than the

conventional one The result also showed that female as well as house wives were

agreed to pay more price premium

HUI et al (2013) conduct a survey on householdslsquo WTP a price premium for

pesticides-free products in Klang valley The study was based on householdlsquos

purchases by 2012 on their demographic and social-economic characteristics To study

the householdlsquos perception and WTP for pesticide free products 500 households were

24

interviewed by using well designed questionnaires The data collected were analyzed to

find what determined the presence of pesticide-free products The main theme of the

research study was to know the determinants that playing rule in willingness to pay for

products free from pesticides residues The result revealed that majority of the

households were agreed to pay a higher price premium for pesticide free products

Different factors like environment psychology food free from pesticide residuals and

health conscious were related to explain household willingness to pay for organic

products However the result also showed that social demographic and level of

knowledge did not explain the WTP for products free from pesticide

Syed et al (2014) studied different level of pesticides in different vegetables and fruits

in Pakistan The results obtained showed that more than half of the collected samples

were contaminated with organophosphate pyrethroids and more organochlorines

pesticides Numerous research studies found that tomato apple melon mango grapes

and plum among fruits and vegetables has crossed the maximum residual levels of

FAO and World Health Organization (WHO) The comparison with other areas showed

that in 50 of the sample the residual level was above than the stated level but was in

agreement with neighboring countries like china and Bangladesh Higher hazard risk

index (HRI) values were calculated for dieldrin methamidophos op-DDT diazinon

and pp-DDT in apple mango banana melon potato and onion

Vidogbena et al (2015) carried out a research study in major cities in Benin to asseslsquo

consumer perceptions about cabbage produced by a physical barriers method to protect

cabbage from pesticides Results showed that consumers were aware of the impacts of

pesticides on health and environment but they were not able to differentiate between

cabbage produced conventionally and through this net method Results of the study

revealed that consumer were willing to pay higher price for cabbage produced with

minimum application of pesticides as compared to one produced with pesticides

application Consumers were willing to pay 38 more price than the existed market

price Results indicated that females more educated and aged respondents were willing

to pay more prices for better quality cabbage

Safdar et al (2015) studied pesticide free food consumption and consumerslsquo WTP in

the United Arab Emirates To recognize major determinants of respondentlsquos willing to

pay more price for products free from pesticides residues a regression model was used

25

Around 300 hundred respondents were interviewed and information was collected The

results showed that the consumption of such food was increased in the study area This

increment was due to high per person price premium more knowledge about nourished

food products and different household population Consumers were paid price premium

for the food free from pesticides residuals Results showed that majority of the

respondents respond when inquired as to whether they were willing to pay more for

pesticide-free products Age nationality instruction family size and salary were main

factors influencing consumerslsquo to pay higher price for the pesticides-free food products

Hiren et al (2016) carried out a survey in Tennessee State USA The data were

collected on a random sample from grocery shoppers to assess consumer general

knowledge about pesticides-free food and to know their willingness to pay For this

study binary logistic regression model was used The survey showed that most of the

consumer had a fair knowledge about pesticides free food Results indicated that

number of those respondents who had never been used organic food was higher than

those who usually used The results showed that income and environmental concern

were the factors that effectively determine to pay more for pesticides-free food

Aguiar et al (2016) studied factors influencing consumerslsquo purchasing behavior

regarding organic food in Brazil by using structural equation modeling (SEM)

approach Results revealed that most of the consumerslsquo were willing to buy organic

food Respondents were willing to pay 25 percent price premium for organic food as

compared to food produced conventionally Results suggest the main determinants of

consumerslsquo willingness to pay were their beliefs of positive effects of organic food on

health and environment

Mangan et al (2016) studied level of awareness and willingness to pay for organic

vegetables in Sindh province of Pakistan Result of the study reported that majority of

the respondents had knowledge about the beneficial effect of organic vegetables while

less than half of the respondents had never heard about organic vegetables Results also

showed that most of the respondents (82) were not aware of the benefits of organic

vegetables to the environment Majority of the respondents were willing to pay price

for organic vegetables

26

Nandi et al (2016) studied consumer willingness to pay for organic fruits and

vegetables and also factors influencing consumerslsquo WTP in India For the estimation of

respondentlsquos willingness to pay contingent valuation method (CVM) was used For the

data analysis 250 respondents were selected A binomial regression model was used to

know respondents willingness to pay and the factors influencing on WTP Results

revealed that most of the respondents were confronted with environment problem

health related issues and safe environment and food The respondents were increasingly

desired to have more healthier and environmental friendly food To acquire better

quality of fruits and vegetables about 90 percent of consumers were willing to pay a

price premium ranging from 5 percent to 100 percent Factors like income of

respondents householdlsquos size gender and other opinion variables such as pesticides

residues in food taste and environmental concern were significantly influencing

consumer willingness to pay a price premium

Slamet et al (2016) conducted a research study to identify factors influencing

consumerslsquo willingness to purchase pesticides free vegetables in Jabodetabek region

(Jakarta) Data was obtained through a householdlsquos survey Three methods binary logit

model descriptive analysis and factor analysis were used for analysis of data The

results showed that respondents with more income minimum householdlsquos size and

price tolerant were more likely to purchase pesticides-free vegetables The study also

indicated other factors determining consumerlsquos willingness to purchase for pesticides-

free vegetables were positive attitude health concern environment concern as well as

positive belief in pesticides-free vegetables

Gumber and Joyti (2017) conduct a research study in national capital region of India to

find out price premium and factors effecting consumerslsquo WTP for pesticides free food

Results of the study showed that consumerlsquo demographic characteristics like education

income of the respondents environmental concern and health related issues were the

important factors influencing consumers to pay higher price for organic food Besides

other variables like taste physical look certification packaging and promotion were

found to have no influence on consumer willingness to pay for pesticides-free food

Results suggested organic food producer to design communication strategies and

suitable pricing strategies in the study area

27

25 Essence of the Literature Reviewed

The above literature reported that several studies have been conducted on

consumerhouseholds willingness to pay for pesticides-free fruits with contingent

valuation method (Govindasamy and Italia 1999 Krystallis and Chryssohoidis 2005

Quagrainie 2006 Kimenju and De Groote 2008) In this type of models a

hypothetical market scenario is developed in which consumer are asked about their

stated WTP a price premium Misra et al (1991) and Boccaletti and Nardella (2000)

used contingent valuation method and analyzed household willingness to pay for

organic products in Italy and USA Gil et al (2000) also used the contingent valuation

model in Spain and reported that respondents in that study area were willing to pay a

price premium for pesticide-free fruits

Regarding the socio-demographic profile of pesticides-free products the above

underline research study showed that mostly female respondents were willing to pay

price premium more frequently than male respondents Age factors also played an

important role with older consumers observed more WTP due to their health concern

On the other hand income played a vital role while buying safer food Literature also

supported that more educated respondents are willing to pay more price premium for

healthier and environmental friendly food products

The preceding review presents valuable information on contingent valuation method

and consumer willingness to pay price premium for organic foods and environment

resources Since most of the work had done on consumer willingness to pay for

pesticide-free fruits in developed countries but not a few studied paid much attention to

conduct research on householdslsquo willingness to pay for pesticides-free fruits in

developing countries like Pakistan

A few facts emerge the literature review One the coverage of consumerslsquo WTP for

organic and pesticide-free food is rather thin in the literature The lack of this

information could inhibit governmental and developmental agencieslsquo decision Second

the consumer WTP is a factor demographics and consumerslsquo perception This study

uses CVM to explore Pakistani consumer WTP for pesticide-free fruit We found socio-

demographic factors such as age education income householdlsquos size householdlsquos

head education and perception significantly influencing householdslsquo WTP Findings of

28

WTP

Environmental

concern

Socio-demoghr

aphic characte

risitcs

consumer knowledge of PFF

Health

concern

this study almost showed 26 percent price premium that suggest a strong indication of

consumerslsquo demand for pesticide-free fruit This is a convincing message for

agriculture policymakers to encourage and educate farmers for production of pesticide-

free fruits Thus this study is timely relevant and provided additional information on

understanding consumerlsquos attitudinal behavior choice and factors effecting willingness

to pay for pesticide free fruits in Khyber Pakhtunkhwa (Pakistan)

Review of literature highlighted different influencing factors that affect the consumers

willingness to pay for pesticides-free food are shown in figure 1 It shows that

perception of consumers regarding human health and environment and socio-economic

and socio-demographic characteristics have an influential affect on consumer

willingness to pay

Figure 1 Factors effecting consumerrsquos WTP for pesticides free fruits

29

III MATERIALS AND METHODS

This chapter consists of two sections The first section describes the study area while

the second section presents the conceptual frame of the study The second section

provides a detailed discussion about the methodology being employed for the research

In the beginning of this section a brief debates provided on Contingent Valuation

Method (CVM) used to analyze householdslsquo willingness to pay (WTP) and later on

elaborate specification of the empirical models used for capturing the factors

influencing householdlsquos willingness to pay for pesticides-free fruit and vegetables is

given followed by a discussion on how the data was collected in the study area

31 Khyber Pakhtunkhwa

Khyber Pakhtunkhwa (KP) occupies a north-west position in Pakistan with a total area

of about 74521 square km Gilgit-Baltistan is situated on its northeast Punjab on the

southeast and Azad Kashmir on the east A long and narrow piece of land belongs to

the Federally Administered Tribal Areas (FATA) borders situated to its south and

Baluchistan directly below it On its west Federally Administered Tribal Areas are

situated and Afghanistan is situated on its northwest According to census report 1998

the total population of KP was 177 million According to the 2011 Census Bureau of

Pakistan house listing operation the population of KP was estimated to be more

than 268 million There are a total of 26 districts in KP Naturally KP has been

endowed with abundant cultural and tourism friendly environment It has the capability

to become a charming area for the tourist in the world Due to its beautiful and

attractive scenery geographical location climate and God gifted natural resources KP

is exceptionally abundant in terms of multitudes of tourist attraction The core of this

charm is clear from the striking natural picturesque consisting of beautiful rivers

attractive and splendid waterfalls spiral lakes mostly in the hilly areas and ever green

valleylsquos in most parts of the province TCKP (Tourism Corporation Khyber

Pakhtunkhwa(2015)Districts of KP is shown in figure31

30

Figure 31 District Peshawar and Mardan of Khyber Pakhtunkhwa

31

32 Sampling Technique

Three stage stratified sampling technique was used for the collection of data

from study area

321 Stage 1 _Selection of district Peshawar and Mardan

In the first stage as KP is comprised of 26 districts Peshawar and Mardan was

purposively selected The purpose behind this selection was huge population in these

two districts

322 Stage 2 _ Selection of Union Councils (UCs)

In the second stage from each selected district one urban and one rural union

council were randomly selected Thus a total of 4 union councils were taken as a

sample location from both districts

323 Stage 3 _Selection of households from each Union Council

In the third and final stage a list of households was obtained from local union

councillsquos health department (BHU) The following Yamanelsquos (1967) formula was

used to decide sample size of households

Where

- r is the sample size for households

- N is the total households in selected UCs and

- e is the minimum probability of error

The value of ―e was selected at e = 003 with the intension to keep the error at lowest

possible level and select a best representative sample from the given population of

10020 households

The Yamanelsquos formula suggests a sample size of 1000 households from two districts

After deciding sample size households was taken from selected union councils (UCs)

using proportional allocation sampling technique The allocation is said to be

32

proportional when the total sample size n is distributed among the different union

councils in proportion to the size of strata

=

____________________ (2)

Where

- = no of sampled respondents in each stratum

- Ni =population size of ith UCs

- N = the total number of households in selected UCs

- n = total number of households

The number of sampled households selected through proportional allocation method is

given in table 31

Table 31 Total population and sampled households from selected UCrsquos

District Union councils Total households Sampled

households

Mardan Urban 3090 309

Rural 1910 191

Peshawar Urban 3000 300

Rural 2020 202

Total 4UClsquos 10020 1000

Source Local Basic Health Unit (BHU) Peshawar and Mardan

33 Allocation of Sample Size for Different Models

A total of 1000 sampled respondents were selected for this research study from urban

and rural areas of the two districts namely Peshawar and Mardan of Khyber

Pakhtunkhwa Pakistan A sample of 600 respondents was reserved for double

bounded dichotomous choice model For the best estimation of parameters double

bounded model requires large sample size compared to open ended and payment card

model (Calia and Strazzera 2000) Out of total respondents a sample of 400

households were allocated for linear regression model and ordered logit model 200

for each model

33

34Contingent Valuation Survey Designing

CVM produces values contingent upon the description of the resource and the method

of payment The accurate measurement of any resource requires a detailed description

of the resource (Loomis et al 2000) The survey designed for this study started with the

description of the conventional food commodities and uses of different varieties of

chemical pesticides on fruit and vegetables before and after harvest After the

description of pesticides its harmful effects on human being as well as on environment

then pesticide free fruits were discussed with the households After describing the

benefits of pesticides free fruit respondents were asked to rank the relative importance

of each benefit The main reason for asking this question was to reveal householdlsquos

preferences their non-monetary value for use and nonuse benefits and to compare

them with their stated WTP response

Results in CVM are sensitive to the valuation question format and payment mechanism

(Carson and Hanemann 2005) The National Oceanic and Atmospheric Administration

(NOAA) Blue Ribbon Panel recommended the use of single bounded dichotomous

choice CV questions with mandatory payment vehicles (Arrow et al 1993) However

recent studies show that the single bounded dichotomous choice method provides

limited information about householdlsquos WTP and produces higher WTP compared to

open-ended question and payment card method (Zhongmin et al 2006) The single

question dichotomous choice method requires a large number of respondents to obtain

an accurate estimate of WTP (Carson and Hanemann 2005) People in the study area

were not familiar with CV Survey The use of an open-ended question format may

generate high zero WTP responses Consequently this study used the entire three

payment format to elicit householdlsquos WTP for pesticides-free products

35 Householdsrsquo Survey

This research mainly based on primary data The primary data was amassed through

interview schedule On the basis of objectives of the study a well-defined questionnaire

was prepared and was pre-tested in the field A small Pre-test was conducted before the

final data collection About 1000 households from Peshawar and Mardan were face to

face interviewed In contingent valuation studies face to face interview is more reliable

(Carson 2000) Socio-demographic characteristics attitudinal and behavioral

34

information of the households were collected Through this survey the data was

gathered both from rural and urban areas of the selected districts District Peshawar and

urban areas were taken equal to one and district Mardan and rural areas were taken

equal to zero Before asking the respondents for their willingness to pay a price

premium they were briefed about the differences among the conventional and

pesticides free fruit The attitudes of the consumers and knowledge about the minimum

use of pesticides on fruit were also gathered to better know how the respondents relate

different aspects of pesticides free fruit These attitudinal behavior questions were

posed using a modified Likert scale response (where a one equals agree and zero equals

disagree) Different values were assigned to each response according to a well-defined

method in the literature (Cranfield and Magnusson 2003)

36 Conceptual Framework

This section is devoted to the conceptual framework of the study Households utility

and willingness to pay willingness to pay and contingent valuation method and the

estimation of mean WTP are discussed The empirical discussion on the factors

influencing householdlsquos willingness to pay a price premium is also discussed

361 Householdrsquos Utility and Willingness to Pay

Willingness to pay could be analyzed as a householdlsquos choice problem Following

Canfield et al 2003 the study assumes that a household who buys and consumes a

conventionally produced food products encounters the same food products but in

pesticide free form on the market The household who decides to purchase pesticide-

free fruits instead of the conventional one does so because it is assumed that hisher

utility is higher for the pesticide-free food (Magnusson et al 2005) If the utility does

not change then a rational household will not be willing to pay as an increase in the

price results in a lower level of utility compared to the base level of utility Also if the

utility increases then the household may be willing to pay more for pesticides-free

food on the basis that the price increase does not lower the utility beyond the base level

(Cranfield et al 2003) The householdlsquos willingness to pay is therefore a function of

the change in utility arising from the consumption of pesticides-free food Thus

35

Where ∆U is the change in utility

Since the choice of one product over another is a discrete one it is convenient to look at

householdlsquos choice problem in a random utility setting Random utility models have

been used extensively in the valuation literature in the analysis of householdlsquos food

safety valuation and assessment of householdlsquos response to new (or different) products

(Eom 1994 Veeman and Adamowicz 2000 Kuperis et al 1999 Quagrainie et al

1998) Following the random utility framework proposed by Cranfield et al (2003) it

is assumed that a household faces a choice between buying either the conventional or

pesticides-free food variety of the same product The utility derived from consuming a

given product by a household is given as

Where

Where is the utility arising from choosing the ith alternative is the deterministic

component of the utility function is a vector of observable alternative specific

factors that influence utility is a vector of parameters and is the stochastic

component The households choose alternative if and only if for all (or

that without loss of generality

The utility of the household is however not observable What is observed is whether or

not the household chooses to pay a premium for the pesticide free product

362 WTP and CVM

On the basis of stated preferences consumer willingness to pay can be measured by

several methods To extensively elicit consumer preferences for food labels on different

attributes economist and market researchers have used contingent valuation (CV)

choice experiment (CE) and experimental auction (EA) or combination of all the three

methods (Fox et al 1994 Fox 1995 Huffman et al 1996 Hossain et al 2003

Loureiro and Umberger2003 2005) To estimate willingness to pay (WTP) economist

must turn to hypothetical due to unavailability of markets for the good or service

Historically Contingent Valuation Method (CVM) has been used for the evaluation of

consumerlsquos preferences for those goods not available in the market

36

Contingent Valuation Method is a survey based method where respondents are

presented with a hypothetical payment scenario for pesticide free products in this study

pesticides-free fruits Methods used in contingent valuation include face to face

interview surveys and mail to elicit consumerlsquos willingness to pay for organic and

pesticide-free food Contingent valuation method based on a survey approach was

presented by SVCiariacy-Wantrup (1947) however contingent valuation method was

first time empirically used by Davis (1963) Due to its proficiency most of the

researchers and policy makers used this technique to elicit consumerlsquos valuation for

those goods which are not available in the market such as research concerns to

environment health and recreation (Jakobsson ampDragun 1996)

The classification of framework to measure WTP based on the data collection methods

are as presented in Figure 32 We employed contingent valuation method (CVM) to

measure householdslsquo willingness to pay for pesticides-free fruits among the different

available alternative methods in the literature CVM was the most widely used

approach (Hanemann 1984)

Figure 32 Classification framework of methods to measure willingness-to-pay

Source (Breidert Hahsler ampReutterer 2006)

37 Elicitation Techniques

According to Portney(1994)to draw out the value of good and service different

elicitation techniques are used to design CV question scenario It is the important part

37

of any CVM study The elicitation used in contingent valuation methods are of various

types The most popular ones are bidding game approach open ended payment card

and dichotomous choice approach

371 Bidding Game Approach

In this approach a bid is randomly assigned to each respondent from a list of

predetermined bids The assigned bid may be a lower bid or higher bid Respondents

are to answer the bid and the process is continuous until the highest positive response is

recorded (Randall et al 1974 as cited in Venkatachalam 2004) Since this approach

provides market like situation and the respondents can research their preferences so the

results obtained through this approach are quite better

372 Open-ended Elicitation Method

In open ended questions format respondents are asked to identify a single amount

without suggesting them any value Respondents are asked to give their opinion on

―How much they willing to pay for a certain attribute Mitchell and Carson (1989)

found certain drawbacks in using this question format They reported that this method

provides maximum no response no answer and outliers In this method respondents do

not know what value heshe has to select

373 Payment Card Approach

Another technique in contingent valuation method is the payment card approach In this

question format respondents are asked to select an amount in willingness to pay from a

checklist given in absolute value or in percentage of prices (Boccaletti ampNardella

2000 Lacaze Rodriguez and Lupin 2009)This approach is used for small sample

size However it has been noted that the respondents could easily be confused if the

survey is not carefully designed (Wang and Whittington 2005)

374 Dichotomous Choice Model

In this format two choices are provided to respondents ―Yes or ―No This format

resembles the market choice behavior It included single bounded double bounded and

multiple bounded questions format

38

A Single Bounded Method

The single bounded format was first used by (Bishop and Heberlein 1979) The

consumers are asked whether they would be willing to pay a single amount for a certain

goods having an extra quality attribute The answer expected might be ―yes or ―no to

the given amount This format is easy to use but it provides limited information for

willingness to pay amount and the bidding game stop after a single information

provided

Most of the research work done on willingness to pay has suggested that respondents in

contingent valuation methods do not have a single value of price but they might have a

range of economic values in their mind (Cameron ampQiggim 1994 Dobourg Jones-lee

and Loomes 1994)

B Double Bounded Method

In double-bounded questions format respondents are presented with follow-up

questions after asking the first question For example if respondentlsquos answered to the

first question is ―yes willingness to pay a $X the next question might be whether

respondents willing to pay $Y (typically $Y gt $X) On the other hand if respondents

say ―No the first question than heshe might ask whether the respondents willing to

pay $Z (typically $Z lt $X) This questionlsquos approach is also called doubled-bounded

referendum approach (Cameron ampQiggim 1994) In comparison with single bounded

model more statistical efficiency can be seen by estimating doubled-bounded

willingness to pay data with the help of interval based econometric model (Heinemann

et al 1991) Figure 33 shows double bounded choice format

This study used all the three question scenarios to elicit WTP for pesticide free fruits

39

WTP

Yes

wtp

1st bid

yes

wtp 2nd

higher bid

yes No

No

wtp 2nd lower bid

yes No

No

Figure 33 Double Bounded Choice formats

38 Empirical Estimation of WTP by Payment Card using Ordered Logit Model


method an ordered logistic regression was applied as the most appropriate choice in

studying these issues (Green 2007) The WTP model can be written under latent

variable framework as follows



fruits consumption to pesticide free fruits is a vector of parameters reflecting the

relationship between WTP captures a set of socioeconomic and

demographicvariables influencing WTP and is the unobserved disturbance term

reflecting stochastic differences between households not controlled for The

40

relationship between the unobserved and the observedoutcome for household

( =0 12hellipj) can be summarized as follows

It is presumed that ɛ is normally distributed across observation By normalizing the

mean and variance of ɛ to zero and one the following probabilities can be calculated

Where F () indicates distribution function and microlsquos are unknown parameters to be

estimated with β

A natural question arises that when a variable influencing outcome changes than how

this variable influences the probabilities of different outcome For example if age is a

factor which influence consumer willingness to pay different choices then how would a

personlsquos probability of being WTP different choices be effected if heshe was a year

older Aldrich and Nelson stated that the estimated coefficients only determine the

direction of the effect but not the magnitude The magnitude of ordered logit cannot be

simply interpreted but signs and statistical significance agree with linear regression

(Wooldridge 2001) To answer the above question and take the idea marginal effects

can be calculated The marginal effects show that how a change in explanatory

variables affects the probability of willingness to pay that consumers are willing to pay

for different WTP classes In this model the coefficients are not equal to the marginal

41

effects of explanatory variables on probabilities Since the marginal effects can be

calculated by the following equation

There are two broad Cumulative density function (CDF) choices Logistic density

function and standard normal density function The model is said to be ordered logit if

the distribution is cumulative standard logistic (F) and the model is said to be ordered

Probit if the distribution is cumulative standard normal (Φ) Results obtained from

both of these models are same only the difference is in the tail The logistic distribution

has heavier tail than the standard normal distribution As Green (2000) reported ―It is

difficult to justify choice of one distribution over other on theoretical grounds in most

applications it seems not much difference The results obtained from both models

may be quite similar because of the similar distribution However an ordered logit

model is applied in this study

Empirically we estimated ordered logit model where WTPj is an ordered dependent

variable with ten WTP price premium categories

Table 32 Payment card format

Price premium classes (PKR)

WTP

= 0

WTP

1-5

WTP

6-10

WTP

11-15

WTP

16-20

WTP

21-25

WTP

26-30

WTP

31-35

WTP

36-40

Above

40

Source Pre- tested field survey (2017)

42

39 Empirical Estimation of WTP using Double Bounded Dichotomous Choice

Model

For Dichotomous choice question Following Chen et al (2002) and Kimenju et al

(2005) a double bounded dichotomous choice model was used in this study to assess

householdslsquo willingness to pay and the influence of explanatory variables on

householdlsquos WTP a price premium for pesticides-free fruits This model was used

because the dependent variable was double dichotomous whether the respondents

would be willing to pay or not so they provide answer with ―yes or ―no Many

researchers used double-bounded dichotomous choice method in their research such as

(Ara 2002 Rodriguez et al 2007 Abdullah and Jeanty 2011 and Claudy et al

2011)

The double-bounded method confronts each respondent with two dichotomous choice

WTP questions (bids) The 2nd

bid value is contingent on the respondentlsquos reply to 1st

bid If the respondent responds in ―yes to the first bid (B) than the second bid (Bu) is

some amount higher than the first bid (Bu

gt B) If the respondent says ―no to the first

bid the second bid (Bd) is then some lower amount (B

d lt B) Thus there are the

following four possible outcomes for the double-bounded WTP question ―yes-yes

―yes-no ―no-yes and ―no-no

According to Hanemann et al (1991) the probability of answering ―yes-yes (Pryy) is

= )

Where Pryy is the probability of answering ―yes-yes WTP is the respondentlsquos

willingness to pay for the product and F is the cumulative distribution function with

parameter vector Similarly the probability for each of the other three outcome

responses is

]

43

Where and are the probabilities for saying ―yes-no ―no-yes and ―no-

no to the double-bounded question respectively Thus the log-likelihood function for

the ith

respondent can be written as

sum

(

)

(

)

Where






coefficients and is error term The models were estimated using maximum

likelihood estimation method

391 Factors which could Influence WTP

As Kimenju et al (2005) has indicated WTP is influenced by householdlsquos knowledge

and perception in addition to price and socio-economic factors Moreover

householdlsquos WTP may be influenced by individuals tastes and preferences income

and perceptions on the products in addition to household and socio-economic

characteristics (Cranfield and Magnusson 2003)

A number of different explanatory variables were included in the WTP model These

include demographic variables regional variables and perceptional variables The

variables that are included may depend on the manner by which the data is gathered

(ie contingent valuation surveys experimental methods etc) Factors which

influence householdlsquos willingness to pay for pesticides-free fruits are formally specified

as

44

392 Bids Design

In this study hypothetical prices (bids) for double-bounded dichotomous choice model

were designed based on the prices available for conventional fruit in the market On

average (Rs100kg) To minimize starting bids bias bidding system was used in table

31 Respondents were asked different bid

Table33 Bid system for Pesticides free fruits

First bid High bid Low bid

10 20 5

20 30 10

30 40 20

40 Above 30

Source Field Survey (2017)

310Empirical Estimation of WTP using Linear Regression Model

For open ended questions data a linear WTP model was used to estimate WTP and

identified its determinants

sum

Where

= is the WTP of the jth household for Pesticides-free fruits

= Set of socioeconomic characteristics of the jth household

Factors effecting consumerslsquo willingness to pay for pesticides free fruits can be written

as

Willingness to pay is actually represents the demand of the household The difference

in both is only the consumer surplus If we suppose zero consumerslsquo surplus than the

two identities are the same Therefore willingness to pay in the above model showed

percentage of expenditure on pesticides free fruit of the total food expenditure The

explanatory variables included were age gender education householdlsquos size income

45

location health concern environment concern and awareness Since the dependant

variable in the model is continuous so the appropriate method of estimation was

ordinary least square (OLS)

311Description of Variables

Table 34 presents a list of explanatory variables used in estimation of willingness to

pay a price premium for pesticides-free fruits

Table34 Description of explanatory variables

Respondents willingness to pay

WTP ( Price Premium)

0= Not willing to pay

1= Willingness to pay 1-5


3= willingness to pay 11-15






9= willingness to pay above

Age of the householdlsquos head

Age Age of the householdlsquos head measured in years

Gender of respondents (Dummy variable)

Gender 0= Female

1= Male

Householdlsquos head education

Education Education of the householdlsquos head in years

Member in each household

Householdslsquo Size In number including all family members

Households location 0 = Rural households

1= Urban households

Awareness Household knowledge regarding pesticides uses on fruits

where 1 shows aware respondents and 0 shows unaware

respondents

Income Income of the households in Pakistani rupees

Consumer attitude towards impact of pesticides on health

Health concern 1 if respondents concern to health 0 if not concerned

Consumer attitude towards impact of pesticides on environment

Environment concern 1 if respondents concern to environment 0 if not

concerned

46

1V RESULTS AND DISCUSSION

This chapter illustrates the major finding of this research endeavor These findings are

computed in the light of major objectives and hypotheses constructed for this research

The collected primary data was punched into the computer and was estimated

encompassing double bounded dichotomous choice model ordered logit model and

linear regression model in the STATA econometric software This chapter is further

bifurcated into three sections In the first section a descriptive statistics is computed to

elaborate the respondentlsquos traits of the study area that includes socio-economic and

demographic aspects as well Followed by the analysis of major attributes such as

attitudinal behavior perception about pesticides free fruit and householdlsquos consumption

behavior that has attain the specific objectives of this study The empirical results on

willingness to pay are underscored in section two Moreover the three different

questionnaires ie dichotomous choice open ended and payment card are adopted and

their results are discussed and compared with each other in section three

41 Descriptive Analysis

Descriptive analysis is a statistical tool that is used to summarize the collected data in

tabulated form The range of data mean value median standard error and variance

coefficients are highlighted via statistical analysis This helps the researcher and readers

to get understanding about the pattern of data This section consists of the descriptive

part of the analysis Socio-demographic characteristics such as age gender education

and other attributes of the respondents are shown in the tabulated form Moreover

socio-economic portfolio that includes income consumption and certain perception

along their attitudinal trend regarding organic and conventional fruits are given and

discussed

411 Demographic and Socio-economic Characteristics

This section demonstrates the demographic and socio-economic characteristics of the

respondents The information was gathered from 1000 household of the study area

47

Age of the householdrsquos head

Householdslsquo age is an essential demographic characteristic and an important factor that

can influence householdslsquo willingness to pay An average age of the household in

district Peshawar and Mardan is computed and given in Table 41 The computation

depicts that an average age of the respondents in Peshawar is reported around 40 years

while in Mardan an average age is observed as 54 years Result reveals a significant

difference in the mean age of rural and urban location of Peshawar with a probability of

(0001) Whereas no significant difference was found in householdlsquos age in urban and

rural region of district Mardan

Table 41 Age of the householdrsquos head (Years)

District Age of the Respondents

Mean Rural Urban T-test

Peshawar 3997 35382 42333 7217

(0000)

Mardan 5402 53188 55870 1104

(0136)

All 46995 47310 46659

Source Authorrsquos calculation based on Survey Data 2016-17

Educational Level of the Householdrsquos Head

An individual entails modern education about developments in technology science and

an array of other managerial skills that drives consumerlsquos behavior Education can also

play a pivotal role in consumerlsquos awareness while choosing improved quality of food

Therefore education can be considered as an imperative factor influencing consumerlsquos

decision to pay higher price for pesticides free fruit Several research studies carried out

across the globe have corroborated that an educated households with higher

qualification are more conscious while making purchasing decision and prefer to

choose pesticides free fruit

Keeping in view an education as a substantial factor persuading consumer behavior the

householdlsquos head education level was analyzed and is presented in Table 42The

descriptive statistics divulged that the mean educational level was observed as 978 and

1138 years of schooling of the household head in Mardan and Peshawar respectively

Estimates of t-test further depicts a significant difference in educational level in rural

48

and urban region of both districts with a p-value of (0001) and (0000) for Mardan and

Peshawar respectively These findings suggest a higher level of education in urban

households compared to rural households These results are in line with Shah et al

(2016)

Table 42 Educational Level of the Householdrsquos Head (Years)

Districts Educational Level


Mardan 978 8782 12012 3780

(0001)

Peshawar 1138 7735 13257 8016

(0000)

All 1058 8436 12855


Households Size in the Study Area

Householdslsquo size is an important demographic characteristic which shape households

purchasing behavior Large householdslsquo size increases the consumption without taking

quality in consideration The probability of choosing an improved version of fruit

quality decreases with an increase a member in a household Small size households are

more concerned about good quality of fruit

An estimation of household size data illustrates that an average household size in

district Peshawar and district Mardan was reported as 06 and 09 members respectively

The results shown in Table 43 have suggested no significant difference in householdslsquo

size in urban and rural areas of both districts The average householdlsquos size was

computed as 715 members These results are consistent with Shah et al (2016) who

depicted similar findings for household size in KP

Table 43 Householdsrsquo size of the Respondents (Member in Number)

District


Mardan 863 8666 8548 0965

(0400)

Peshawar 567 6029 5484 -2122

(0018)

All 715 7796 6463


49

Income of the Households

The household income level is one of the driving aspects that manipulate the

consumption and saving behavior of an individual Those societies where individuals

earn high income are usually deemed as food secured societies across the globe

however low income group of the poor societies are generally reported as food

insecure It is worth-mentioning that surge in an income can subsequently leads to

choose high quality food (that includes cereals fruits vegetables pulses and their

byproducts) by individuals Likewise householdlsquos income has considered as an

important determinant of willingness to pay for quality attributes such as pesticides

free

An income status of the households in the study area is outlined in Table 44 The mean

income of the Household was calculated as Rs62130 and 42430 in district Mardan and

Peshawar respectively There was a significant difference in the mean income of

respondents from urban and rural areas of both the districts The T-value of Mardan

region was signified as 6018 and had a probability of (0000) while in Peshawar region

was 950 with P-value of (0000)

Table 44 Householdsrsquo Income in Pakistanrsquos Rupee (PKR)

District


Mardan 63130 5489855 8145161 6018

(0000)

Peshawar 42430 2923529 4922727 9504

(0000)

All 52780 4642718 5952577


Householdrsquos Expenditure on Food

Food consumption expenditure is the monetary expense incurred by household to

purchase food items Such food expenditure is the key component of current

expenditure to buy consumable goods The data regarding householdlsquos expenditure on

food is estimated and is shown in Table 45 The mean expenditure incurred on food by

the household in Mardan and Peshawar was determined as Rs 49280 and 34860

respectively A significant difference in rural and urban householdlsquos food expenditure

has been reported The computed t-value observed as 425 and 743 with a p-value

0000 which implies that householdlsquos expenditure in urban region was higher as

compared to rural households

50

Table 45 Households expenditure on food (PKR)

District


Mardan 49280 4511594 5854839 4256

(0000)

Peshawar 34860 2544118 3971212 7435

(0000)

Total 42070 3862136 4573196


Note Values in parenthesis is P-Value

Householdrsquos Monthly Expenditure Share on Fresh Fruit

Expenditure share is an amount of income that is incurred by an individual on certain

goods out of total spending Households in the study area have allocated their income

share to make an expense for fresh fruits which is shown in Table 46 It has been

observed that in districts Mardan an average spending for fresh fruit was computed as

4172 (PKR) per month by the household Whereas expenditure share for fresh fruit by

Peshawarlsquos household was 3800 (PKR) which was less as compared to Mardan The

given t-values of the estimates confirm a significant difference in expenditure share

incurred for fresh fruits by rural and urban region households of both the districts This

significant difference implies that householdlsquos expenditure share for fresh fruit in urban

area is higher as compared to rural households

Table 46 Householdrsquos monthly expenditure share on fresh fruits (PKR)

Respondents


Mardan 4172 3798551 5003226 3055

(0000)

Peshawar 3800 2411765 4515152 5103

(0000)

All 3986 3340777 4671134


51

412 Householdrsquos Awareness and Perceptions about Pesticides Application on

Fruit

This research endeavor was mainly designed to assess the consumer willingness to pay

for pesticides free fruit Therefore it was pertain to glean data about their awareness

about pesticide use on locally produced fruit in the study area These fruit include

Apple Peach and Mango Due to irrational use of pesticides environmental hazards are

also reported by previous research studies therefore there respondents were asked about

their perception about environmental hazards Major findings about the aforementioned

aspects are underscored in Table 47 which reveals that 61 percent of respondents have

a perception that there is an irrational and intensive use of pesticides on fruit by the

local fruitlsquos farmers Around 88 percent of the respondents perceived environmental

and health concerns over pesticides residues in food Similarly 91 percent of the

respondents believed that farmer should engage in environmental friendly agricultural

production practices which have a minimum adverse impact on health and the

environment

However the overall results indicate that sampled households were not entirely

cognizant about an intensive use of pesticide on local fruits however they were

correctly perceived over the impacts of pesticides on human health and environment

Table 47 Householdrsquos Awareness and Perceptions of Pesticides use on Fruit

Grown

Statements Agreed Disagreed

Local farmers are intensively using pesticides on

Apple Peach and Mango fruits

61 39

I feel the use of pesticides in agriculture has

negative effect on the environment

881

119

I am concerned about pesticide residue in our

food supply

876 124

I believe farmer should engage in environmental

friendly agricultural production practices with

minimum impact on human health

901

99


52

42 Empirical Results of this Research Endeavour

The empirical analysis of the gleaned data was made to achieve the major objectives

and to address the research questions of this research endeavor Major estimates on

―willingness to pay for pesticide free fruits have been made and conferred in this

section Different elicitation techniques were employed to assess householdlsquos

willingness to pay price premium These estimation techniques encompassed double

bounded dichotomous choice model ordered logit model and linear regression model to

appraise dichotomous choice payment card and open ended question

421 Distribution of responses on householdsrsquo willingness to pay

(WTP)

Householdlsquos preferences to pay higher prices for pesticides free fruit were investigated

and highlighted in Figure 41 which demonstrates the distribution of response about

WTP price premium for pesticide free fruit in the survey area The households were

asked whether and how much they were willing to pay higher prices for pesticide free

fruit than conventional produced fruit The primary data estimates confirm that about

935 percent of respondents are willing to pay a higher price premium for pesticide free

fruit in the sampled districts These results are similar with the previous research study

undertaken by Hayati et al(2017) in Iran by using contingent valuation method

Furthermore an ordered logistic regression model was employed which depicts that out

of 394 respondents who were interviewed 97 percent of respondents were willing to

pay price premium for pesticides free fruits and vegetables These results are supported

by Nandi et al(2017) who conducted a study in India by using contingent valuation

method and applying binomial logistic regression model Data was obtained from 250

respondents and reported that more than 90 percent of the respondents were willing to

pay higher price for better quality fruits and vegetables Decomposing the responses 35

percent of the households are willing to pay 16 to 20 percent higher prices for

pesticides free fruits than the conventional 24 percent willing to pay 6 to 10 percent

higher price and 65 are not willing to pay higher price A plausible reason for higher

WTP for significant portion of the population is due to awareness As most of the

respondents in the study area were aware they may have some knowledge about

adverse effects of chemical pesticides Therefore they were willing to pay higher prices

for pesticide free fruits if available

53

NotWTP

1_5 6_10 11_15 16_20 21_25 26_30 31_35 36_40 Above40

650 4

24

9

35

6 550 150

550 3

Figure 41 Distribution of willingness to pay responses (Rskg)

422 Householdrsquos willingness to pay using ordered logit model

Estimated parameters and coefficients of ordered logit model are presented in table 48

Model is specified on the bases of R2 estimated from restricted and unrestricted

likelihood function The likelihood ratio test is used to test the null hypothesis that the

overall effect of coefficients is zero The p-value is 0000 shows that the model is

statistically significant at 95 level of significance The estimated model with a scaled

R2

about 022 which is in consist with the generally R2 value mostly observed in cross

sectional data In cross sectional data like the one used for this study the value of

Pseudo R2 is typically low The conventionally computed R

2 is of limited value in those

models having qualitative nature In most cases this value is low and use of coefficient

of determination as a summary statistics should be avoided in those cases where the

response variables are qualitative (Gujrati 1995)This pseudo R2 cannot be interpreted

separately or across the dataset but could be used when evaluating multiple models

which predict the same results on the same set of data It has only meaningful when

compared to some other pseudo R2 in the same data on the same type and predicting

the same results In this case pseudo R2 indicates which model better predict the results

(Bruin J 2006)This value pointed out overall ability of the model for the correct

prediction of willingness to pay of the consumer based on explanatory variables The

null hypothesis that the joint influence of explanatory variables was zero on the bases

of chi-squire value null hypothesis was rejected

Predicted probabilities and marginal effects are calculated separately because of the

non-linear behavior of logit model Most of the coefficients are statistically significant

54

The variables like householdlsquos age education level of the respondents awareness

income and health concern variables and household size are significant at five percent

The negative sign showed that as the size of numbers in a family increased the log

odds for willingness to pay decreased The same was reported in a relevant study by

Govindasamy and Italia 1999 carried out a research study in New Jearsy to provide

opinion on organic produce Objective of the study was to evaluate demographic

characteristics caused consumers to pay higher prices to obtained organic food

products Findings of the study showed female respondents consumer with higher

annual income and younger individual were more likely to pay higher premiums for

organic produce Our finding shows variables gender was not significant because most

of the respondents in the study area were male

Positive sign on income showed that consumer with higher income were more likely be

willing to pay higher prices for pesticides free fruit It has been also noted that with

increased in income purchasing power of the respondents increased that changed the

purchasing pattern of the respondents This was also confirmed by Roitner-

Schobesberger et al(2008) They conduct a study on consumerslsquo perception regarding

organic food in Bangkok and found that more than a third of the 848 respondents

reported having purchased organic fruits or vegetables and the main reason for buying

organic food was the expectation of the consumers that the food are healthier and

environmentally friendly The respondents who purchased organic vegetables were

those having more aged higher income and more education

Findings of our study also showed that respondents with friendly attitude regarding

environment would be willing to pay higher price for such fruit These results were in

line with Haghjou et al (2013) carried out a research study on factors effecting

consumerlsquos potential willingness to pay for organic food in Tabriz Iran By adapting an

ordered logistic regression model results showed that factors like income of the

respondent family dimension environmental concern and wholesome diet besides

consumerslsquo awareness were significantly increases consumerslsquo willingness to pay for

organic food Results revealed that consumers with higher care about their health were

more likely to be willing a higher price for such pesticides free fruit

55

Table 48 Factors influencing respondent householdrsquos WTP (Ordered logit

model)

Variables Estimated

Coefficient

Std Error Z-ratio P-value

Age 00698807 00147356 474 0000

Gender -02469171 08432503 -029 0770

Education 00821316 00223365 368 0000

Household size -00975395 00502583 -194 0052

Location

Urban

02783974 02961745 094 0347

Income 00000277 000000502 551 0000

Health concern 2600153 05346547 486 0000

Environment

concern

03993532 0574947 069 0487

Awareness 09595126 02836742 338 0001


Log likelihood = -29863 Pseudo R-squared = 020 LR chi2 (9) = 15849

Number of observation = 200 Probability gt chi2 = 0000

Note indicate statistical significance at 5

56

423 Predicted probabilities and Marginal effects of ordered logit

model

Predicted probabilities and marginal effects of explanatory variables are underscored in

Table 49 These predicted probabilities indicate a strong likelihood that the average

respondent is willing to pay more prices for pesticides free fruit Producers usually

expect high price for their production so if they sought high premiums than marketing

efforts would be diverted to such fraction of consumer where they would probably

willing to pay high price than the conventional price Alone these predicted

probabilities are not too much informative what is more informative is the impact of a

change in predictors on the predicted probabilities (ie marginal effects)

Due to the non-linear behavior of ordered logit model to measure the impact of a

change in particular independent variable on householdslsquo willingness to pay marginal

effects of explanatory variables are calculated Marginal effects show the change in

predicted probabilities for different class of willingness to pay regarding an average

household concerning the particular variable For qualitative choice model estimated

coefficients affect marginal probabilities These marginal probabilities (probability

derivatives) were calculated from the estimated model They measure the change in the

probabilities of each willingness to pay outcome with respect to change in each

explanatory variable The sum of marginal probability is zero in each row because an

increase of the probability in one category must be set off a decrease in the other

category or categories

For continuous variables the interpretation is simple and straight forward Keeping all

other variables fixed a unit change in explanatory variable will results an increase or

decrease in the predicted probability equal to the degree of marginal effect of the stated

variable However in case of binary variable marginal effects shows change in

predicted probabilities based on whether the respondents falls in that category or not

Our results suggest some meaningful insight into the role of socio-economic and

demographic variables on householdlsquos WTP for pesticides-free fruit

Age has a positive and significant influence on householdlsquos WTP for pesticides free

fruit The results show that with an increase in age WTP also increases This finding is

consistent with other researchers who reported that WTP of organic and healthy food

57

increases with age beyond 30-40 years (Hayati et al 2017 Boccaletti and Nardella

2000 and Zellner and Denger 1989)With increase in age people are more concerned

about their health as they may perceive that they are prompt to low immunity and

higher risk for diseases With realization of aging they are more likely to pay higher

price premium for safer foods Our result suggests that the marginal effects of age is

negative for first three WTP classes (ie Not willing to pay WTP 1-5 percent WTP 6-

10 percent and WTP11-15 percent) while positive for the rest of the four classes in

upper tailsmdashindicating that higher age is associated with higher likelihood of paying

premium on upper tails The highest marginal effect of age 0007 is found for category

16-20 percent higher premium This indicates that an increase in age by one year is

associated with 07 percentage point increase in likelihood of paying 16-20 percent

higher premium for pesticides free fruits over conventional These results are in

contrast with Cranfield and Magnusson (2003) conducted a research study on

consumerlsquos willingness to pay for pesticides free food products in Canada by using

contingent valuation method and reported that younger consumers have the strongest

marginal effects (those consumers had an age less than 35 years younger) followed by

those consumers had an age less than 50 years Results showed younger consumers pay

more for healthy foods as compared to older in case of Canadian consumers However

our results are in consistent with several other studies (Hayati et al 2017 Zellner and

Denger 1989) finding a positive influence of age on consumerlsquos WTP for organic and

healthy foods In another study Boccaletti and Nardella (2000) conducted a study on

consumer willingness to pay for organic produce in Northern Italy By adapting an

ordered logit model the impacts of relevant explanatory variables were reported

Results suggests a positive impact of consumerlsquos age on WTP a price premium

The marginal effects for gender indicate female respondents are less likely to be willing

to pay more prices or likely to pay less amount for pesticides free fruit Female

respondents like to pay a price premium but less as compared to male respondents (no

premium or 1 to 5 percent premium) One can observe that most of the respondents in

the study area were male which support our findings These results are in contrast with

Cranfield and Magnusson (2003) The probability of marginal willingness to pay

decreased by (-0001 percent) for higher amount

58

Another significant variable affecting WTP in our study is the years of education of the

householdlsquos head Our result suggests a positive relationship of education on WTP for

pesticides free fruit Households with more formal education have better understanding

of the adverse effect of consuming fruit contaminated with pesticides So they may

better understand the benefits of pesticides free fruit Marginal effects of education are

positive as WTP progresses for higher classes (categories) beyond 16-20 percent (table

49) Among these the highest effect of education 0020 is shown for WTP category

36-40 percent which implies that an additional year of schooling of the household head

increases likelihood of paying 36-40 percent higher price premium for pesticides free

fruit over conventional by around 2 percentage These results are in line with the

findings of Haghjou et al (2013) who found a positive effect of education on WTP for

organic food products in Iran However these results are in contrast with Boccaletti and

Nardella (2000) who reported an inverse relation of consumer education with WTP a

price premium

We also found a significant effect of the household size and household income on WTP

for pesticides free fruit The effect of household size is negative Marginal effect in

table 49 shows that the highest negative effect of 012 is shown for 16-20 WTP

categories which indicate that an additional household member decreases the likelihood

of paying 16-20 percent higher premium for pesticides free fruits by 12 percent One of

the convincing reasons for this negative effect of household size can be the householdlsquos

budget constraint Budget constraint limits the extent to which consumer pay higher

prices for food products (Cranfield and Magnusson 2003) Our findings are consistent

with previous studies Ariyawardana et al (2009) conduct a study on consumerslsquo

willingness to pay for organic ethnic specialty produce in USA reported that marginal

effect of price premium decreases with an increase in householdslsquo member

In regards to income households with higher income are more willing to pay higher

premiums for pesticides free fruit Income always played a significant role in changing

consumerlsquos behavior to change hisher decision from not willing to pay or less willing

to pay to higher willing to pay for organic products Households in highest income

class showed a strong propensity to pay more prices Marginal effects of income for the

first four classes emerged negative Our results suggest a strong propensity to pay

higher prices as household income increases Our marginal effects of income show a

59

monotonic increase in the income effect as WTP premium level progresses beyond 16-

20 percent It implies that at low level of income households are unwilling to pay more

but with rise in income households are ready to pay higher premium for pesticides free

fruit a significantly higher magnitude is shown for the highest category (010 income

coefficient for more than 40 percent premium) Overall it clearly suggests that

household with higher level of income would pay more prices for pesticides free fruit

These results are in line with Hayati et al (2017) and Cranfield and Magnusson (2003)

who found that an increase in income increases purchasing power of consumer which

results a change in purchasing pattern Boccaletti and Nardella (2000) conducted a

study on consumerslsquo willingness to pay for pesticides free fresh fruits and vegetables in

Italy and found that willingness to pay is significantly and positively related to income

We also included variables indicating health and environmental concern of the

respondent Results indicated that the more the households were concerned about the

impact of pesticides in fruits on health and environment the more the probability of

willingness to pay The marginal effects for health concern is negative for first three

willingness to pay classes (ie not willingness to pay willingness to pay 1_5 wiliness

to pay 6_10 percent) and for environment concern it is negative for first four classes

while for the remaining WTP classes it is positive Strikingly the highest magnitude of

marginal effects up to 041 among all variables is found from the health concern

variable On one hand a significantly positive effect suggests that the health concerned

householdslsquo are more likely to pay higher premium for WTP than those not concerned

A magnitude of higher scale on marginal effect on the other hand strongly supports

the distinct difference in WTP between health concerned and non-concerned

individuals Overall this also highlights the importance of this variable on modeling

WTP for pesticides free fruits For example a 041 marginal effect of health concern

variable on 16-20 premium category of WTP suggest that health concerned individual

are 41 percent more likely to pay 16 to 20 percent higher premium for pesticides free

fruit as compared to non-concerned households The effect of health concern on WTP

is consistent and distinctly higher in magnitude from previous similar studies in other

countries For example Hayati et al (2017) found that health concerned individual were

26 percent more likely to pay 16 to 20 percent in Iran This indicates that health

concern factor is an important motivation to premium price for pesticides free fruits in

Pakistan

60

Finally we found a significant effect of awareness variable Recall that our awareness

variable is represented by dummies Our result suggests that the households in the study

area were aware of the fact that farmers are intensively using pesticides on fruits so

they were willing to pay more price premium for pesticides free fruits Marginal effects

show a negative signs for modest price premiums on WTP categories 1-5 and 6-10

while positive signs for all higher categories 16-20 21-25 26-30 31-35 36-40 and

above 40 This may indicate that households are more aware of the adverse impact of

pesticides on health and environment Probably awareness comes from education as our

results shows that the average years of education is higher in the study area

424 Matrix of Correlation Coefficient

Income is generally related with age and education of the households in the study area

(table 410) This result may indicate that more aged households have higher income

and advanced education Households in high income and more educated class shows

high propensity of willingness to pay for pesticides free fruit As the results indicated

that more aged people do care more about their health and high class income

respondents have more discretionary income to spend on fruit Overall the results show

that explanatory variables are not highly correlated hence no problem of

Multicollinearity was diagnosed in the data

61

Table 49 Predicted probabilities and marginal effects from the estimated ordered logit model

Not WTP

()

WTP 1-5

()

WTP 6-

10 ()

WTP 11-

15 ()

WTP 16-

20 ()

WTP 21-

25 ()

WTP 26-

30 ()

WTP 31-

35 ()

WTP 36-

40 ()

WTP

Above 40

()

Predicted Probabilities

00122 00179 02616 01183 04434 00620 00510 00110 00201 00026

Marginal effects

Age -0000 -0001 -0011 -0002 0007 0003 0003 0006 0001 0001

Gender 00039 00054 00623 0015 -0033 -0019 -0019 -0004 -0008 -0001

Education -0000 -0001 -0013 -0002 0010 0003 0003 0010 0020 0002

Household size 0002 0002 0012 0004 -0012 -0004 -0004 -0001 -0020 -0002

Urban rural -0003 -0004 -0049 -0009 0031 0013 0013 0002 0005 0001

Income -0003 -0004 -0004 -0010 0003 0001 0001 0002 0005 0010

Health concern -0103 -0113 -0372 0030 0410 0100 0100 0014 0030 0003

Environment

concern

-0005 -0007 -0072 -0010 0052 0017 0015 0003 0006 0008

Awareness -0014 -0020 -0120 -0030 0122 0045 0041 0010 0020 0002


62

Table 410 Matrix of correlation coefficient between explanatory variables


Variables Age Gender Education Location Households

size

Income Health

Concern

Environment

Concern

Age 10000

Gender -00193 10000

Education 00872 -00147 10000

Location 00725 00689 01047 10000

Households size -00294 00277 -00161 -01704 10000

Income 04123 -00690 02133 - 00405 01583 10000

Health Concern 01604 00224 02229 00660 - 00422 02102 10000

Environment Concern -00786 00944 -00245 00570 -00059 -00350 00118 10000

63

43 Householdrsquos willingness to pay using double bounded dichotomous

choice model

The double bounded dichotomous choice model was used to find out how much

households are willing to pay a price premium for pesticides free fruit The model has

been proved useful for the determination of the contribution of independent variables in

householdslsquo willingness to pay for pesticides free fruit Mainly those factors that

influenced the householdslsquo willingness to pay are age of the householdlsquos head

householdlsquos size gender awareness income head education and their perceptions

The Likelihood Ratio test statistic the Wald Chi2 value is 27228 with a p-value of lt

0001 confirmed that the model with all the explanatory variables has good prediction

power of householdslsquo choice and WTP for pesticides free fruit (table 411) The

estimated coefficients for most of the explanatory variables are statistically significant

and have signs consistent with prior expectations Headslsquo characteristics such as age

education level and awareness of pesticides use on fruits perception of health and

environmental concerns of pesticides are the most import determinants of the

householdlsquos WTP for pesticides free fruit Householdlsquos income and number of

individuals have significant effect on their price premium for fruits free of pesticide

residue

The coefficient for Age is positive and its value is 0294 which reveals that a one year

increase in headlsquos age would increase householdlsquos willingness to pay a price premium

of 0294 rupees for pesticides free fruit at constant level of other variables This

generally implies that household headed by an old individual has strong preferences

and high WTP for pesticides free fruits as compared to others These results are

supported by Vidogbena et al 2015 reported a positive significant effect of consumerslsquo

age WTP in Benin for minimized pesticides residues Results suggest older households

are more concerned about health benefits associated with fresh pesticides free food

This positive correlation of householdslsquo age and Willingness to pay a high price

premium for pesticides freeorganic food is also in agreement with findings of (Anifori

2013 Haghiri et al 2009 Misra et al 1991) However these findings are in contrast

with (Govindasamy and Italia 1999) carried out a research study on consumerslsquo

willingness to pay for organically produced fresh produce in New Jersey to find

64

opinion on organic produce and found that all the three age category younger people

like to pay a high price premium

Headlsquos education level has a positive significant association with householdlsquos

willingness to pay a price premium for pesticides free fruit A likely explanation is that

education increases consumerslsquo awareness regarding the adverse effect of pesticides on

human health and natural environment Consumerslsquo with a high level of education can

better understand the benefits attached to the consumption of food produced without the

use of pesticides These results are also in line with Vidogbena et al (2015) studied

consumerslsquo willingness to pay for cabbage with minimized pesticides residues in

Southern Benin and reported that consumers with high level of education were

positively affected WTP In some other related studies Darby et al (2008)Liu et al

(2009) and Misra et al(1991) also confirmed positive association of consumerlsquos

education and willingness to pay price premium for pesticides free organic fruits

Headlsquos awareness of pesticides use on local fruits production and their health and

environmental concerns over pesticides use are also the most important determinants of

householdlsquos willingness to pay for pesticides free fruits As discussed in the previous

section householdlsquos awareness and perception of pesticides use on fruits and their

education level are connected and have significant influence for creating market for

pesticides free organic fruits

Householdlsquos demand for best quality fruit is expected to rise with increase in their

income level The estimated coefficient for householdlsquos income is positive which

implies direct association with their price premium for pesticides free fruits and is

consistent with general theory and our prior expectations In future with economic

growth increased in per capita income is expected and this increase in per-capita

income will increase the demand for pesticides free fruits

We found a negative significant effect of the householdlsquos size on WTP for pesticides-

free fruit As the number of members increases household become less likely to pay a

price premium for pesticides free fruit More mouths to feed reduces budget for best

quality fruits as noted previously by (Oyawole et al 2016 Ghorbani and Harnraz

2009) In another study Govindasamy et al (2001) findings suggests that each

member in a lager household has less discretionary income to spend compared to a

65

smaller household and may consider paying a premium for integrated pest management

a luxury

Table 411 Factors influencing consumersrsquo WTP (double-bounded dichotomous

choice model)

Variables Coefficient Std Error z-statistic Pgt|z|

Constant -8614601 3640408 -237 0018

Age 0294755 00638171 462 0000

Gender -0133885 - 4628428 003 0977

Education 04521878 01574002 287 0004

Income 00001208 00000284 426 0000

Householdlsquos

Size

-06690743 2499154 -268 0007

Health concern 6165207 1882292 328 0001

Environment

concern

6739389

2053786 328 0001

Awareness 8194937 1693789 484 0000

Urban Rural 02295739 1339268 017 0864


Log likelihood = -61347 Number of observation = 600

Wald chi2 (9) = 27226 Probabilitygt chi2 = 0000


431 Householdsrsquo estimated Mean WTP

The estimated model was used to derive each householdlsquos willingness to pay price

premium for pesticides free fruits Table 412 and figure 42 presents the summary

statistics for the estimated price premium The Table shows that householdlsquos estimated

mean willingness to pay price premium is around 26 rupees with a standard deviation

of 106 and the estimated minimum and maximum price premium are 0 and 445

rupees respectively These statistics reveals that householdslsquo on average are willing to

pay 26 percent more price premium for pesticide-free fruits than the existed market

producing pesticide free fruits

66

2

125 115

38

325

35

-5

0

5

10

15

20

25

30

35

40

45

0 1-10 11-20 21-30 31-40 gt40

Fre

qu

en

cy o

f th

e h

ou

seh

old

s

WTP bins

Table 412 Households mean estimated WTP

Mean Std Dev Min Max

WTP 25798 10601 0 44511


Figure 42 householdsrsquo estimate WTP bids

432 Households Response to First Bid (Amount)

Table 413 and figure 43 shows households response to first bid of the WTP question

The Table clearly show the sensitivity of a householdlsquos yes - no response to the bid

amount As the bid amount goes up the probability of acceptance is expected to

decrease Results show that higher bids reduced the likelihood of acceptance For

example for a bid amount of Rs10 as price premium for pesticides free fruits 8833

percent of the households are willing to pay while it dropped to 222 percent when the

bid amount is increased to Rs40 which is consistent with the standard theory

67

0

01

02

03

04

05

06

10 20 30 40

Table 413 Householdsrsquo Response to First Bid (Amount)

Households

with YesNo

response

First bid amount (PKR)

10 20 30 40

Households

with No

response

21 (1167) 24 (2581) 141 (5732) 63 (7778)

Households

with Yes

response

159 (8833) 69 (7419) 105 (4268) 18 (2222)

Total

Households

180 93 246 81


Figure 43 Probability of WTP given bids

44 Post Estimation Diagnostic Test

The model was tested against Multicollinearity by using (variance inflating factor

criteria) and for Heteroskedasticty (Breusch-Pagan test) and the results are presented in

table 414 Rule of thumb for VIF is that if the value is ge 10 than the problem of

Multicollinearity is severe According to our findings the mean value of variance

inflating factor is 114 less than the critical value suggests that there is no

Multicollinearity problem in the model Breusch-Pagan test is used for detecting

Heteroskedasticty problem The (χ2) value is 066 and p- value is 041 This p-value

suggests that the probability of rejecting the presence of Heteroskedasticty is 41percent

68

Table 414 Diagnostic test results

Problems Diagnostic Test Mean value P-value

Multicollinearity VIF 112 _

Heteroskedasticty Breusch-Pagan 066 041


441 Householdsrsquo willingness to pay by using linear regression model Results of householdlsquos willingness to pay for pesticides-free fruits using linear

regression model is shown in table 415 Variables such as age education awareness

income householdslsquo size and consumer perceptions regarding health and friendly

environment are significantly influencing consumerslsquo WTP for pesticide-free fruits

Age has a positive and significant influence on willingness to pay ie the result shows

that with an increase in age willingness to pay also increases This result is slightly

different from few findings of other researchers who reported a high WTP in young and

middle age consumerslsquo (30-40) years Govindasamy and Italia (1999) But there are

some logical reasons behind our findings As young people are not so much health

conscious but with getting older and older the disease of aging caught their minds and

they keep more care about their health Another reason with an increase in age

education and experience increases as a result an increase in WTP for pesticides free

fruits These results are supported by Muhammad et al (2015) found a positive and

significant association between age and consumer willingness to pay Their results was

supported by the fact that young individual health consciousness is a rare phenomena

but as the people get older and older many diseases related to health induce them to

pay more attention towards safe and healthy food such as pesticides free organic food

Education and monthly income are the other factors positively and significantly

influencing householdslsquo WTP Households with more formal education have more

concern and better understanding of the risk associated with consuming food

contaminated with pesticides So they better understand that fruits produced without the

use of chemicals pesticides could be beneficial for health Results show that a one year

increase in formal education householdslsquo WTP increases by rupees 025 for pesticides

free fruit as compared to those having no education In regards to income respondents

with higher income are willing to pay more price premium A one rupee increase in

income will increase householdlsquos WTP by 0001 Muhammad et al (2015) reported a

69

significant effect of income and education on householdslsquo stated willingness to pay for

organic food in Arab Emirates consumer

Householdslsquo size is usually reported as negative influence on WTP Findings of our

study show a negative significant influence on householdlsquos willingness to pay This is

likely due to larger households requiring additional funds to satisfy households demand

for pesticides free fruit which may induce households to buy conventional fruit Other

reason may be as with limited resources feeding more mouths is increasingly difficult

These results are in contrast with Muhammad et al (2015) conducted a study on

factors affecting consumerlsquos willingness to pay for certified organic food products in

United Arab Emirates and reported a positive relationship of willingness to pay and

householdlsquos size Usually householdslsquo size is large in Arab Emirates and hence more

earning resources compared to small households which support their findings Our

finding shows a decrease of 085 rupees by an addition of one member in a household

Other important variables are householdslsquo concern regarding health and environment

Results show that respondentslsquo are highly concerned about residual effect of pesticides

on human health and environment Our results support these findings by positive WTP

Table 415 shows householdslsquo concerned regarding health and environment Results

suggest that households with more concerned for health and environment are willing to

pay Rs582 and Rs020 respectively higher prices for pesticides free fruit compared to

those not concerned

Finally we found variable awareness positively and significantly influencing

householdslsquo WTP for pesticides free fruit in survey area The result shows that more

aware households are willing to pay more price premium compared to unaware

households Awareness usually increases with education and age as can be evidence

from our findings a positive and significant influence of education and income on

householdlsquos WTP When households education level and age increases their awareness

regarding pesticidelsquos negative impact on health increase and hence an increase in WTP

for pesticides free fruit

70

Table 415 Estimated parameters using liner regression model

Variables Coefficient Std Error t-Statistics P-value

Constant -6174109 - 4353038 142 0158

Age 02348861 00467651 502 0000

Gender -2828394 3096026 - 091 0362

Education 0243413 00772618 315 0002

Income 00001237 00000157 790 0000

Householdlsquos

size

-03936806 01755667 -224 0026

Health concern 5567941 1465789 380 0000

Environment

concern

02999708 2023651 015 0882

Awareness 3567843 1001883 356 0000

Urban rural 0587075 1047051 056 0576



No of observation = 200 F (9) = 2859 Probgt F = 0000 R-squired adjusted = 055

45 Comparison of elicitation questions formats Mean WTP by using double dichotomous payment card and open ended elicitation

format are reported in table 416The willingness to pay evaluated using average values

for the explanatory variables are Rs2576 for double bounded 1632 is for payment

card and 1437 for linear regression Results indicated that householdslsquo evaluated

through double dichotomous choice payment card scenario and open ended format are

willing to pay 26 16 and 14 more price for pesticides free fruits in the study area

These results are in line with Ngo et al (2013) conducted a study on consumerslsquo

willingness to pay for organic vegetables in Vietnam and found 70 more price

premium Rodriguez et al (2008) carried out a research study in Argentina on

consumerslsquo willingness to pay for organic food products and reported that consumers

were willing to pay a higher premium of 87 for leafy vegetables Mean willingness to

pay for double dichotomous model was calculated by maximum likelihood estimation

mentioned in the model while for payment card and open ended format logit regression

of response on bid amount was used All mean WTP values are significantly different

71

from zero and are different across the three questions format The probability (Plt

0000) between double bounded open ended and payment card method shows a

significant difference in estimated mean values of all the three questions elicitation

formats A t-value of 1483 250 and 1222 means that the mean values calculated

through different methods are significantly different from each other

Table 416 Mean willingness to pay comparison from CV question format

CV questions format Open ended

Mean WTP (1437)

Payment card

Means WTP (1632)

Payment card

Mean WTP (1632)

MD (194)

t-value (250)

P-value (0006)

--------

Double bounded

Mean WTP (2576)

MD (1143)

t-value (1483)

P-value (0000)

MD (949)

t-value (1222)

P-value (0000) Source Authorrsquos calculation based on Survey Data 2016-17

1MD = Mean difference 1US$=105 PKR in 2017

451 Response rate for zero WTP

Table 417 shows householdlsquos response rate to different elicitation formats The

response rate of payment card format is more than both DC and OE questions formats

Results show that 87 of the respondents respond to the willingness to pay question for

payment card method For dichotomous choice the response rate is 58 and for open

ended respondentslsquo response rate is 46 Taken together these results suggest that the

payment card format is easy for valuation task faced by respondents and lead to

efficiency in data collection

Table 417 Comparison of response rates by CV question format

Percent Response

to WTP question

Double dichotomous

choice

Payment card

method

Open ended

method

Yes 5850 87 4650

No 4150 13 5350


72

46 Discussion about Major Findings This study was design to explore householdlsquos preferences and willingness to pay for

pesticides free fruit in Khyber Pakhtunkhwa Pakistan For this study a detailed

questionnaire was designed to obtained information from the households on their socio-

demographic characteristics perception regarding pesticides used on conventional fruit

and their willingness to pay a price premium for pesticides free fruit The overall

objective of the study was to know householdslsquo willingness to pay a price premium for

pesticides free fruit such as Apple Peach and Mango In response to willingness to pay

question 93 percent of the households were willing to pay a price premium while a

negligible portion were unwilling to pay any premium for pesticides free fruit Out of

total WTP 35 percent of the households were willing to pay16-20 percent higher

amount for pesticides free fruit

With regards to gender status of the households findings of the research showed most

of the respondents in the study area were male and a minor portion were female

Variable gender was not significant in this study because of the area structure where

male households are the primary purchaser of householdlsquos food items In this research

we found that majority of the respondents were educated most of them were highly

educated while a negligible portion of the respondents had no formal education The

mean education in Mardan and Peshawar was almost 10 and 12 years of schooling

respectively A significant difference was observed in urban and rural householdslsquo

education level in both the districts

Householdslsquo expenditure on food and fresh fruits were also calculated The mean

expenditure on food in district Mardan was PKR- 49280 and in district Peshawar was

PKR- 34860 Based on t-test a significant difference was observed on the consumption

of fresh fruit in urban and rural areas of the two districts Total expenditure on fresh

fruits in Mardan and Peshawar was 3340 and 4671 respectively Based on findings of

the study it could be concluded that respondents in urban region spent more income on

fresh fruit and consume more fresh fruits compared to rural region

Householdslsquo awareness of pesticides use on locally produced fruit such as Apple

Peach and Mango and their health and environmental concerns over pesticides use

were estimated The results revealed that 61 percent of the respondents were agreed that

local farmers use intensive pesticides on fruit Around 88 percent of the respondents

perceived environmental and health concerns over pesticides residues in food

Similarly 91 percent of the respondents believed that farmer should engage in

73

environmental friendly agricultural production practices which have a minimum

adverse impact on health and the environment These results induced households to pay

higher prices for such pesticides free fruit if available in the market The overall results

indicated that sampled households were not fully aware of the intensive pesticides use

on local fruit however they were correctly perceived over the impacts of pesticides on

human health and environment

The empirical findings of the study revealed socio-demographic characteristics had a

significant influence on householdslsquo willingness to pay a price premium for pesticides

free fruit Results showed more aged householdslsquo head were willing to pay more price

premium This is supported by the fact that older people are more health concern

compared to young individual Householdslsquo head education level also played a positive

and significant role with high education consumers seems slightly more willing to pay

These results are in line with Haghjou et al (2013) Householdlsquos size was negatively

influencing householdlsquos WTP and accord with the expectation Due to income

constraint with increase a member in a household will decrease WTP for pesticides-

free fruit because feeding more mouths with limited resources would be difficult These

results are in line with Oyawole et al 2016 Many Conflicting results are also reported

regarding household size Some studies indicated the presence of more children

positively influencing WTP for organic food while some results reported an inverse

relationship between WTP and householdslsquo size Findings of our research revealed a

negative significant influence on householdslsquo willingness to pay for pesticides free

fruits These results were also according to our expectation With an increase in family

size the households do not care much about quality but mostly quantity

Income of the householdslsquo head was taken as continuous variable in this research study

In most cases especially in willingness to pay research studies a positive association of

income and households WTP was observed Any increase in householdslsquo income leads

to rise in their willingness to pay for safer healthier and pesticides free fruit Despite

high prices for pesticides free food products householdslsquo with high income showed

likelihood to pay a price premium Our findings also showed a positive effect of

income on householdslsquo WTP for pesticides free fruit An increase in income changes

householdslsquo purchasing behavior and choose better quality of food So with an increase

in income households were willing to pay more price premium Same results were

reported by Cranfield and Magnusson 2003

74

Variable awareness played a significant role while consuming better quality of food

Findings of our study also showed a positive and significant influence of variable

awareness on householdslsquo WTP for pesticides free fruit More than half of the

respondents were aware of the intensive use of pesticides on fruit Majority of the

households knew about the risk attached with fruits produced with agrochemicals The

more aware households were willing to pay more price premium for pesticides free

fruit compared to unaware households These results are also supported by Oyawole et

al2016

Moreover results of this study are also consistent with previous studies that health and

environmental concern are the important factors in householdlsquos preferences for

pesticides free food and reduced input food products We also found a positive

significant influence of health concern and environment concern on WTP These results

suggest that respondents in the study area are more conscious about health and

environment They are willing to pay more prices for such fruit free from pesticides

residues Based on above results most of socio-demographic characteristics have

positive influence on householdlsquos willingness to pay for pesticides-free fruit in the

study area On the basis of these findings we reject the null hypothesis and accept the

alternative hypothesis by concluding that socio-demographic characteristics have

influencing behavior on householdslsquo WTP

Willingness to pay across urban and rural regions shows no significant difference The

P-value of 0864 showed that WTP of households in urban regions were not statistically

different from those in rural regions Although we had expected a positive and

significant difference among urban and rural households willingness to pay for

pesticides free fruit and the difference in householdslsquo income education and

expenditure across urban and rural households support our expectation One of the

reasons for no significant difference is the selection of rural union councils which are

nearby urban union councils If the study is spread to more rural union councils than an

expected difference in urban and rural households may be observed Based on these

results the null hypothesis of no significant difference between urban and rural

households is accepted and can be concluded that no significant difference was found

in willingness to pay amount across rural and urban households

75

A Payment Card Approach

In this approach respondents are asked to select their WTP from a payment card given

in absolute value or in percentage of prices (Boccaletti amp Nardella 2000 Lacaze

Rodriguez and Lupin 2009) Payment card requires smaller sample sizes for the

efficient estimation of parameters than the double bounded model A recent research

found that payment card is to be free of range and centering biases when the

willingness to pay values on the payment card is sufficiently large and the respondents

are not constrained (Rowe et al 1996) However choosing an amount from payment

card may be more cognitively burdensome on the respondents and difficult than simply

yes or no response

B Open Ended Approach

In open ended question respondents are asked to state their WTP for a certain attribute

without suggesting them any value This technique does not require an interviewer and

does not result in any starting bias This approach is easy for the respondents to answer

Due to non provision of any value respondents find it difficult to answer and results

large non- response rate

C Double Bounded Approach

The dichotomous choice contingent valuation method is an important method in

contingent valuation surveys Due to simplicity this method is popular and widely used

for data collection Two questions formats are used in this method single bound and

double bounded questions are asked from the respondents For single bound question

format the respondentlsquos only reply in yes or no while in double bounded approach

second question contingent on the first response is asked

Hanemann et al (1991) recommended double bounded dichotomous choice model for

eliciting householdslsquo WTP In the double bounded formate each respondent is

presented with two bids The level of the second bid is contingent upon the response to

the first bid If an individual responds in ― yes to the first bid Bi the second bid (Bu) is

some amount greater than the first bid (Bi lt Bu) is askedIf the respondent responds

―no to the first bid the second bid (Bl) is some amount smaller than the first bid (B

llt

Bi) is asked

76

Henemann et al (1991) and Leon (1995) confirmed that double bounded model is more

effcient than single bound model For the correction of poor choice of the initial vector

double bounded model was suggested Researchers also found that double bounded

method produce more precise point estimates of parameters Double bounded model

requires more sample size due to the statistical inefficiency imposed by the data

compared to payment card and open ended model If sample size is large enough

double bounded model estimates accurate results

Due to its potttential inconsistency with response to the first binary question and larger

scope for biased results double bounded model is contravartial Bateman et al (2001)

concluded that the respondents feel fury and guilt when the second question is asked

making the response of the double bounded internally inconsistence One of the main

disadvantage of double bounded model is that response of the respondents may be

influenced by the first offered amount which is generally called starting point bias

(Flachaire and Hollard 2005)

There are few notable patterens while studying consumerlsquos willingness to pay by using

different elicitation formats Estimated willingess to pay based on double bounded

format and payment card format tend to be large compared to open ended questins

format Furthermore estimated willingness to pay from double bounded model would

be larger than payment card format

Not surprisingly as shown in table 416 the estimated mean willingness to pay for

pesticides free fruit based on the models were significantly different across the three

elicitation format Estimated WTP for double bounded format payment card format

and open ended was 25 percent 16 percent and 14 percent respectively The estimated

mean WTP for double dichotomous model is higher than twice the estimated mean

willingness to pay based on payment card and open ended data

When comparing response rate of households to the willingness to pay questions

format was different across the three elicitation methods In double bounded method

the question was whether the households were willing to pay a specific amount in

payment card method households were asked to select the amount from a specified

values provided on a card whereas in open ended question households were asked to

say how much extra they were willing to pay for pesticides free fruits The difference in

questions leads us to expect that more individual would respond positively to

willingness to pay question in payment card method because in this elicitation format

consumers had to select from payment level The response rate of payment card format

77

is more than both DC and OE questions formats Results show that 87 of the

respondents respond to the willingness to pay question for payment card method For

dichotomous choice the response rate is 58 and for open ended respondentslsquo response

rate is 46 Taken together these results suggest that the payment card format is easy

for valuation task faced by respondents and lead to efficiency in data collection

It has been remained an unresolved issue that which CV questions format is best to use

While the NOAA panel (Federal Register 1993) recommended using double bounded

dichotomous choice model due to its easy use and resemblances in day to day decision

making In this study we found that the response rate in double dichotomous choice

model is lower than payment card format and higher mean willingness to pay than both

open ended and payment card format In contrast payment card format has desirable

response properties

One elicitation format is not clearly better than the others on priority ground The

appropriateness of any elicitation format depends upon the circumstances of the study

For example payment card elicitation format better suits if the sample size is small If

the sample size is large enough double bounded elicitation format is preferred

78

V SUMMARY CONCLUSION AND RECOMMENDATION

This chapter presents findings of the research study as well as policy recommendations

This chapter also outlined limitation in this research and suggestion for further research

in future

51 Summary

Conventional agriculture has gained the power of providing food to majority of the

world population but at the cost of damaging the environment and human health While

pesticides free farming on the other side is environmental and human health friendly

farming that avoids the use of such hazardous chemicals which are harmful for human

plants and animal planet Pesticides free farming system is increasingly becoming

popular in producers as well as in consumer The term pesticides free denote production

of fruit without the use of pesticides and play a vital rule in future agriculture

commodities production It has been observed that fruit produced without the use of

chemicals pesticides are generally higher in prices than the conventional fruit

production in most part of the world However pesticides free farming and pesticides

free food is a relatively new phenomenon and very few people especially in developing

countries are aware about the beneficial impacts of such food on health and

environment Willingness to pay for pesticides free fruit is different from fruits

produced through the use of chemicals pesticides because pesticides free fruits are

relatively expansive

The main theme of this study was to investigate householdslsquo awareness and willingness

to pay for pesticides free fruit and to determine socio-economic and socio-demographic

characteristics in relation to their impact on willingness to pay a price premium This

study was carried out in two districts of Khyber Pakhtunkhwa (Pakistan) namely

Peshawar and Mardan The household level data employed in this study were obtained

from 1000 households through face to face interview by employing pretested

questionnaires Householdslsquo perception and attitude about pesticides free fruit were

also analyzed Three questionnaire elicitation formats ie dichotomous choice payment

card and open ended were used in this study For the estimation of dichotomous choice

data double bounded dichotomous choice model was used An ordered logit model was

used for the estimation of payment card type data and for the estimation of open ended

79

questionnaires linear regression model was used to estimate householdslsquo willingness to

pay price premium for pesticides free fruits

52 Conclusions

Adoption of technological advancement in agriculture has attracted considerable

attention in many developing countries because majority of population in less

developed countries derives its likelihood from agricultural production New

technologies provide farmers an opportunity to increase production and enhance

economic growth (Carvalho 2006) Although the green revolution spread across

developing countries in Asia and resultant in increased food production by adopting

technological inputs like fertilizer and pesticides However the high usage of these

chemicals to bring this spectacular growth in agriculture production is not without its

problems In most countries it has been observed that using commercial agricultural

practices causes many problems like environmental degradation and human health

effects (Wilson 2000) Coordinated efforts are needed to increase food production

with a view to enhance food safety and quality Although chemicals free agriculture is

gaining more and more support for safer food but still not providing enough food to

support need of the population in developing countries

Demand and markets for pesticides free fruit has gained a significant and valuable

interest of research scientist in all over the world Several research studies have been

identified price premium that consumers are willing to pay for pesticides free fruit and

also showed some socio-demographic factors influencing their decision to pay more

price premiums Different approaches are adopted in these studies depending on their

objectives These research studies mainly focused on attitudes and perception towards

these foods and not their actual purchase According to our knowledge studies on

householdlsquos willingness to pay and the most relevant factors influencing their decision

to pay more price premium are limited in developing countries such as Pakistan

The general objective of this survey was to study the socio-demographic and socio-

economic characteristics of the householdslsquo and to investigate factors influencing their

willingness to pay for pesticides free fruit A variety of factors including respondentlsquos

age gender householdlsquos size respondentlsquos income householdlsquos head education

awareness and certain attitudinal questions like health concern and environment

concern appear to influence householdlsquos willingness to pay a price premium Findings

80

of the study suggest health concern and environment concern has significant influence

on householdslsquo willingness to pay Hence it can be concluded that households in the

study area are more concern about their health and surrounding environment Results of

the study also indicated no significant difference in willingness to pay across rural and

urban regions of the study area

Study concluded that the most relevant explanatory variables positively influencing

householdslsquo willingness to pay for pesticides free fruit are age of the householdlsquo head

income of the household headlsquos education householdslsquo awareness health concern and

environmental concern while householdlsquos size is negatively significant which usually

reported that householdslsquo with more members do not care much about quality but more

quantity because feeding more people with limited resources are difficult Majority of

the households are willing to pay price premium for pesticides free fruit especially

those with high level of income household leads to high degree of willingness to pay

Education level also became an important factor in willingness to pay higher price for

pesticides free fruit More aged people have always been concern about their health As

the people get aged more and more the diseases of aging caught their minds so they

like to pay more for safer food While when it become to pay more price variable

gender shows insignificant affect due to the limited availability of female respondents

in the sample data

Results of the households awareness regarding pesticides used on conventional fruit

and its impact on health and natural environment are positive Most of the households

are highly concern about health and environment Results suggest that more than half of

the households are aware of the adverse impact of pesticides on health and

environment Survey suggested that more than half of the households are strongly

agreed that farmers should produce such an agricultural food product which has

minimum adverse impact on human health and natural environment Results of the

study are consistent with other findings conducted on consumerslsquo willingness to pay for

organic food and pesticides free food and reported that health and environmental

concern were the most important factors

Health and environmental concern is an important factor constituted a significant

influence which inclined households towards willingness to pay for pesticides free fruit

Krisoff (1998) reported that consumers perceived pesticides free food as healthier safer

and environmental friendly as compare to food produced by conventional method

81

From this study it is observed that households perceived pesticides free food as

healthier they are willing to pay more price premium

Results obtained from this study concluded that 93 percent of the households are

willing to pay more prices for pesticides free fruit Out of this proportion 35 percent of

households are willing to pay 16 to 20 percent more price above the regular price while

24 percent are willing to pay 6 to 10 percent higher price for pesticides free fruit

Households are willing to pay above than 20 percent comprised of 215 percent of the

sample data Results show that out of total willingness to pay 4 percent of the

households are willing to pay 1 to 5 percent price premium and 9 percent are willing to

pay 11 to 15 percent more price premium Results also show that only a minor portion

65 percent of the sampled respondents is unwilling to pay any more

Householdslsquo willingness to pay was also assessed The study revealed that on average

the respondents are willing to pay 26 percent higher price for pesticides free fruit than

the regular price which concluded that households in the study area are responsive

towards safer food and they like to pay higher premium for such fruit

53 Recommendations

This study is one of the first analytical attempts to measure householdslsquo willingness to

pay for pesticides free fruit in Pakistan Since not much research work is done on

pesticides free fruit in Pakistan so this study would contribute a little for future

researchers Findings of the survey suggest some recommendations for consumers and

producers Researchers may consider this study as basis for further research

An important task is to provide more information to consumers regarding

pesticides free fruit and the perceived benefits by consuming these fruit This

research study also provides information to consumers that how pesticides free

fruit is differ from fruit produced conventionally The sampled studied shows

that there is a potential for market growth of pesticides free fruit To identify

these potential consumers knowledge about their socio-demographic and socio-

economic characteristics is important

With potential demand and high price premium pesticides free fruit production

could be one of the lucrative strategies for producers to earn higher net margin

from their production so like other new technologies management practices

and production system pesticides free fruit production also needs government

82

assistance such as advertisement consumers awareness campaigns financial

aids as well as green subsides and loans to the producers to develop well

established market and efficient supply chain in Pakistan

By adopting new agricultural practices and comply with standards of World

Trade Organization (WTO) this will not only abridge the supply demand gap

for pesticide free fruit sat domestic level but also will boost the economy of the

country due to increase in fruit and vegetables exports

Contribution in the field of pesticides free fruit production from academics

research workers extension graduates scientist and other professionals are

necessary to brief producers as well as consumers about the negative impact of

pesticides due to incorrectly use of these hazardous chemicals on human and

animals health as well as effect on natural environment

Based on the findings from this research government non-government

organization and other stakeholders should formulate policies and would


Demonstration centers should be established within the agriculturist community

for the awareness of farmers regarding the production of pesticides free food

As the results identified householdlsquos willingness to pay is effected by

explanatory variables so more independent variables should be included in the

model to further explain willingness to pay for pesticides free fruit

In addition the area of sampling could be more spread and not be limited to only

two districts of Khyber Pakhtunkhwa If data are collected from different

provinces and districts all over Pakistan the results obtained might be a better

representation of the whole population

As this research study conducted only at few fruit such as Apple Peach and

Mango future research should focus on more fruit as well as on vegetables

54 Limitation and Suggestion for Future Envisage

A couple of limitations were encountered during this research study

This research study has investigated willingness to pay for fruit only due to

time and budget constraint In future a large scale research study should be

carried out both on fruit and vegetable

83

Second since only two districts of Khyber Pakhtunkhwa were examined in

the future such studies should be replicated to other districts and provinces of

Pakistan to determine householdslsquo willingness to pay for pesticides free fruit

Third some variables employed in this study were not statistically significant

presumably due to small sample size To overcome this problem in future

study large sample size should be taken into consideration in order to enhance

the degree of freedom

56 Suggestions

The future of pesticides free agriculture production is very bright To lead a healthy life

human being needs pure food and pollution free environment It has been proved that

pesticides free agriculture is the only solution to provide safe and healthy food to the

world population Chemicals free agricultural system is a natural phenomena and

human being can feel its importance By adopting pesticides free farming soil fertility

can also be maintained Farmers can provide healthy and safer environment by

strengthening the sustainable and pesticides free agriculture Now a daylsquos demand for

pesticides free food is increasing very fast and in the future it would be necessary to get

rid of food produced by using chemical fertilizer and pesticides

To inform consumers long term investment in promotion and education campaigns

would help to develop individual concern regarding the risk associated with pesticides

on food products This concern will translate individual willingness to pay towards a

positive price premium

84

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15(2) 191-202

Haghiri M J E Hobbs and M LMcnamara 2009 Assessing consumer preferences

for organically grown fresh fruits and vegetables in Eastern New Brunswick

International Food and Agribusiness Management Review Volume 12( 4)81

HeoSW and H Kim 2004 Green marketing strategies and willingness to pay for

environment-friendly agricultural products in the metropolitan area Korean

Journal of Organic Agriculture

90

HossainF B Onyango B Schilling W Hallman and AAdelaja2003 Product

attributes consumer benefits and public approval of genetically modified

foods International Journal of Consumer Studies 27(5) 353-365

Hanemann M J Loomis and B Kanninen 1991Statistical efficiency of double-

bounded dichotomous choice contingent valuationAmerican Agricultural

Economics 73(4)1255-1263

HanemannWM 1984Welfare evaluations in contingent valuation experiments with

discrete responses Am J Agric Econ 66(3) 332ndash341

Jakobsson K M and A K Dragun 1996 Contingent valuation and endangered

species methodological issues and applications Edward Elgar Publishing

Khan J M M S Zia and M Qasim 2010 Use of pesticides and their rule in

environmental pollution International Journal of Environmental and Ecological

Engineering4 12-25

KalogerasN S Valchovska G Baourakis and P Kalaitzis2009Dutch householdlsquos

willingness to pay for pesticide free olive oilJournal of International Food amp

Agribusiness Marketing 21(4) 286-311

Kimenju S C and HD Groote 2008 Householdlsquos willingness to pay for genetically

modified food in Kenya Agricultural economics 38(1) 35-46

Krystallis A and G Chryssoidis 2005 Consumers willingness to pay for organic

food Factors that affect it and variation per organic product type British Food

Journal 107(5) 320-343

Kuperis A P M MVeeman and W L Adamowicz 1999 Householdlsquosresponse to

the potential use of Bovine Somatotrophin in Canadian dairy production

Canadian Journal of Agricultural Economics47(2) 151-163

KmentaJ 1997Elements of Econometrics University of Michigan Press Second

edition

91

Lusk JL and Hudson D 2004 Willingness-to-pay estimates and their relevance to

agribusiness decision making Review of Agricultural Economics 26(2) 152-

169

Liu Y Y Zeng and X Yu 2009Consumer willingness to pay for food safety in

Beijing a case study of food additives In Contributed paper prepared for

presentation at the international association of agricultural economists

conference Beijing China (pp 16-22)

Loureiro M L and W J Umberger 2005 Assessing consumer preferences for

country-of-origin labeling Journal of Agricultural and Applied

Economics 37(1) 49-63

Loureiro M L and W JUmberger 2003 Estimating consumer willingness to pay for

country-of-origin labeling Journal of Agricultural and Resource

Economics28(2) 287-301

Loomis J P Kent L Strange K Fausch and A Covich 2000 Measuring the total

economic value of restoring ecosystem services in an impaired river basin

results from a contingent valuation survey Ecological Economics 33(1) 103ndash

117

MuhammadS E Fathelrahman and RUT Ullah 2015 Factors affecting

householdlsquoslsquo willingness to pay for certified pesticide free food products in

United Arab Emirates Journal of Food Distribution Research 46(1)37-45

MagnussonE and J A L Cranfield 2005 Householdlsquos demand for pesticide free food

products in Canada A Probit Analysis Canadian Journal of Agricultural

Economics53(1) 67ndash81

MagnussonK MA Arvola UKKHursti L Aringberg PO Sjoumldeacuten 2003 Choice

oforganic foods is related to perceived consequences for human health and to

environmentallyfriendly behavior Appetite40 (2)109ndash117

92

Millock K H and L G Hansen 2002 Willingness to pay for pesticide-freefoods A

Comparison between Survey Data and Panel Data from Denmark Available at

httpmpraubuni-muenchende47588

Mitchell R C and R T Carson 1989 Using surveys to value public goods the

contingent valuation method Resources for the FutureResources for the Future

Maddala G S 1986 Limited-dependent and qualitative variables in econometrics (No

3)Cambridge university press

Mitchell R C amp Carson R T 1984 A contingent valuation estimate of national

freshwater benefits technical report to the US Environmental Protection

Agency Washington DC Resources for the Future

Nandi R W Bokelmann N VGowdruand G Dias2017 Factors influencing

consumerslsquo willingness to pay for organic fruits and vegetables Empirical

evidence from a consumer survey in India Journal of Food Products

Marketing 23(4) 430-451

Ngo Minh H M Masahiro andF Susumu 2013 Willingness to pay for organic


Kyushu Univ 58(2) 449-458

NouhoheflinT O Coulibaly A J Cherry R A Hassan and PYAdegbola2004

Consumerslsquo perception and willingness to pay for pesticide free vegetable in

Benin and Ghana African Association of Agricultural EconomistsThe role of

social scientistsProceedings of the Inaugural SymposiumGrand Regency

Hotel Nairobi Kenya

Oyawole F P D Akerele and A O Dipeolu 2016 Factors influencing willingness to

pay for organic vegetables among civil servants in a developing

country International Journal of Vegetable Science 22(2) 121-128

OwusuV and M OAnifori2013Consumerwillingness to pay a premium for pesticide

freefruit and vegetable in Ghana International Food and Agribusiness

Management Review16(1)67-86

93

OwusuV and A M Owusu 2010Measuring market potential for fresh pesticide free

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African Association of Agricultural Economists (AAAE) and 48th Agricultural

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South Africa

OramanY and G Unakitan 2010Analysis of factors influencing organic fruit and

vegetable purchasing in Istanbul Turkey Ecology of food and nutrition 49(6)

452-466

PiyasiriAGSA and A Ariyawardan2011 Market potentials and willingness to pay

for selected organic vegetables in Kandy Sri Lankan Journal of Agricultural

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PanhwarF 2004Organic farming in PakistanPublished by City Farmer Canadalsquos

Office of Urban Agriculturehttpwwwcityfarmerorg Pakistan Org

Farminghtml

Portney P R 1994 The contingent valuation debate why economists should care The

Journal of Economic Perspectives 8(4)3ndash 17

httpwwwjstororgstable2138336

Quagrainie K K JUntershultz and M Veeman 1998 Effects of product origin and

selected demographics on householdlsquoschoice of red meats Canadian Journal of

Agricultural Economics46(2)201-216

RodriacuteguezE V Lacaze and B Lupiacuten 2008Contingent valuation of householdslsquo

willingness to pay for pesticide free food in Argentina12th Congress of the

European Association of Agricultural Economists

Roitner-Schobesberger B I Darnhofer SSomsook and C R Vogl2008Consumer

perceptions of organic foods in Bangkok Thailand Food policy33(2) 112-121

Randall A B Ives and C Eastman1974 Bidding games for valuation of

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d Management 1(2)132ndash149

94

Salmet A S A k Nakayasu and H Bai 2016The determinants of organic vegetables

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103390foods5040085

SyedJ H A Alamdar A Muhammad K Ahad Z Shabir HAhmad SM Ali SG

A S Sani HBokhari KDGallagher IAhmad and SA M A SEqani

2014Pesticide residues in fruits and vegetables from Pakistan a review of the

occurrence and associated human health risks Environmental science and

pollution research 21(23)13367-13393

SangkumchaliangP and W C Huang 2012 Consumerslsquo perceptions and attitudes of

organic food products in Northern Thailand International Food and

Agribusiness Management Review 15(1) 87ndash102

Syed J H and R N Malik 2011 Occurrence and source identification of

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Chemical Industries KalashahKaku Pakistan Environmental Earth Science

62(6)1311ndash1321

Smith A T C L Hung and B H Lin 2009 Does Price or Income Affect Organic

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Taiba B M Khan M Nazir M Sajjad D Jan and A U Jan 2011 Estimation of

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contemporary research in business 3(8)688-704

Vidogbena F A Adeacutegbidi R Tossou F A KomlanAnselme T Martin M

Ngouajio S Simon L Parrot and K K Zander 2015Consumerslsquo

Willingness to Pay for Cabbage with minimized pesticide residues in Southern

Benin Environments 2(4) 449-470

Valerian J E Domonko S Mwita and A Shirima 2011Assessment of the

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MunicipalReport of the original work done for Sustainable Agriculture

Tanzania (SAT)

95

Veeman M and W Adamowicz 2000Consumerlsquos perceptions of environmental risks

and the demand for food safety httpsdoiorg107939R3ZS2KG11

Wooldridge J M 2010 Econometric analysis of cross section and panel data MIT

press London

Wang Q and J Sun 2003 Consumer preference and demand for organic food

Evidence from a Vermont survey Paper prepared for American Agricultural

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Zia M S M J Khan M QasimandARehman 2009Pesticide residue in the food

chain and human body inside Pakistan J Chem Soc Pak 31(2) 284ndash291

Zhongmin X U J Loomis Z Zhiqiang and K Hamamura 2006Evaluating the

performance of different willingness to pay question formats for valuing

environmental restoration in rural ChinaEnvironment and Development

Economics 11(5) 585ndash601 httpsdoiorg101017S1355770X06003147

Zellner JA and RL Degner1989Consumer willingness to pay for food safety Paper

presented at the Southern Agricultural Economics Meeting Nashville TN

96

Appendix- 1 Questionnaire

Q1Socio-economic characteristics

1 Location

o Rural

o Urban

2 Name ____________________

3 Age ____________________(years)

4 Gender

o Male

o Female

5 Educational status ______________ Years

6 Household Size_________________ No

7 Monthly income _______________________________Rs

8 Monthly consumption expenditure _________________Rs

9 How much you spend on Fresh Fruits Rs __________month

10 How much you consume the following fruits

Fruits Quantity

Apple

Mango

Peaches

11 Local farmers are intensively using pesticides on Apple Peach and Mango fruits

o Aware

o Not aware

97

12 Attitudinal question responses

Householdrsquos Awareness Perceptions of Pesticides use

Questions Agreed Disagreed



I feel the use of pesticides in agriculture has negative

effect on the environment

I am concerned about pesticide residue in our food

supply




The effect of pesticides residues on human health

The use of pesticides can badly affect the agro-ecological system as well as human

health Human health related problems may vary with the composition of chemicals

The most common problems are skin flue and headache while severe health hazards

include paralysis cancer etc Studies show that globally around 30 lakh people are

poisoned annually from consumption of pesticides contaminated food and 2 lakh of

them die from different heath problems caused by pesticides residues Most of the

pesticides used on agricultural crops are banned by the WHO

13 Householdrsquos willingness to pay for pesticide free fruit

Wording for Dichotomous choice question

Suppose your favorite fruit such as apple mango and peach regularly cost on average

Rs 100kg Assuming no difference in taste and nutritional content would you pay Rs

X more to consume pesticide free version of the same fruits

Yes No

Wording for open ended question


Rs 100kg Assuming no difference in taste and nutritional content how much would

you pay for pesticides-free version of the same fruits

Rs _________

98

Wording for payment card question

Suppose your favorite fruit such as apple mango and peaches regularly costs on

average Rs 100kg you purchase Assuming no difference in taste and nutritional

content would you pay slightly more for a pesticides free version of the same fruits

Yes No

If yes how much would you pay to consume pesticide free version of the same fruit

Select from the given payment card

1 WTP= 0

2 WTP= 1-5

3 WTP= 6-10

4 WTP= 11-15

5 WTP= 16-20

6 WTP= 21-25

7 WTP= 26-30

8 WTP= 31-35

9 WTP= 36-40

10 WTP= Above than 40

If no what are the reasons for not paying price premium for pesticide free

commodities (PFC) Please select the most relevant one

o I canlsquot afford to pay price premium on PFC

o The pesticide have no harmful effect on health

o We do not use fresh fruits

o Other reasons ___________________________

99

PLAGIRIASM UNDERTAKING

It is certified that the research work presented in the Ph D dissertation of Mr Jahangir

Khan C No 45 University Registration No2006-Agr-U-13234 Session 2014-2017

Department of Agricultural amp Applied Economics Faculty of Rural Social Sciences

The University of Agriculture Peshawar under the titled ―HOUSEHOLD

PREFRENCES AND WILLINGNESS TO PAY FOR PESTICIDES FREE FRUIT IN

KHYBER PAKHTUNKHAWA (KP) PAKISTAN was conducted under the

supervision of Dr Abbas Ullah Jan

I understand the zero-tolerance policy of HEC and the University of Agriculture

Peshawar towards plagiarism Therefore I as an author of the above titled research

thesis declared that no portion of my thesis has been plagiarized and the material used

for references is properly cited

I undertake that I found guilty at any time and any statement is found to be incorrect or

plagiarized in the above mentioned titled thesis even after my graduation the

University has the right to withdraw my Ph D degree and the HEC has the right to

publish my name on the HECUniversity website on the list of persons who submitted

plagiarized thesis of guilty under plagiarism policy

Jahangir Khan

100

AUTHORrsquoS DECLARATION

I Mr Jahangir Khan C No 45 Session 2014-2017 hereby stated that my Ph D

dissertation titled ―Household Preferences and Willingness to Pay for Pesticides free

Fruit in Khyber Pakhtunkhwa (KP) Pakistan is my own work and not been submitted

previously by me or anyone else for taking degree from The university of Agriculture

Peshawar or any other University in the country world At any time if any statement

found to be incorrect even after my graduation the university has the right to withdraw

my Ph D Degree

Jahangir khan

Date

101

CERTIFICATE OF APPROVAL


Khan C No 45 University Registration No 2006 -Agr-U-13234 Session 2014-2017






No part of this dissertation has been submitted anywhere else for any degree The

dissertation is submitted for the award of degree of Doctor of Philosophy in the


The University of Agriculture Peshawar

Ph D Scholar Jahangir Khan

APPROVED BY

1 External Examiner _________________ Lal K Almas Ph D

Associate Dean and Regents

Professor Agricultural Business amp

Economics University of West Texas

AampM USA

2 External Examiner ___________________ Prof Dr Harun Ucak

Alanya Alaadin Keykubat

University Turkey

Major Supervisor ___________________ Dr Abbas Ullah Jan

Head of Department ________________

Dr Ghaffar Ali




BY

JAHANGIR KHAN





Approved by

___________________________ Chairman Supervisory Committee

Prof Dr Abbas Ullah Jan

___________________________ Member (Major Field of study)

Dr Ghaffar Ali

___________________________ Member (Minor Field of study)

Prof Dr Mussawar Shah

___________________________ Chairmanamp Convener Board of Studies

Dr Ghaffar Ali

___________________________ Dean Faculty of Rural Social Sciences

Prof Dr Noor P Khan

___________________________ Director Advanced Studies and Research

Dr Shahid Sattar




PESHAWAR-PAKISTAN

MAY 2018

TABLE OF CONTENTS

S No Title Page No

List of Table i

Acknowledgements ii

Abstract iii

I INTRODUCTION 1



























362 WTP and CVM 35







Model 39


Choice Model 42


392 Bids Design 44







on Fruit 51



(WTP) 52





choice model 63









51 Summary 78

52 Conclusions 79



56 Suggestions 83

LITERATURE CITED 84


i

LIST OF TABLE













Grown 51



logit model 61



choice model) 65







ii

ACKNOWLEDGEMENTS























Jahangir Khan

iii








Peshawar-Pakistan

May 2018

ABSTRACT





































iv




















1

I INTRODUCTION































2






























3

































4


































5
































6
































7
































8








free products





fruit


production




the study area


householdlsquos WTP








9

16 Hypotheses







hypothesis


Hypothesis 1



Hypothesis 2



Hypothesis 3















10













11
































12
































13











to pay




















14





sum

(

)

(

)

Where























15










should be open













premium






follows

16






















17
































18










sustenance and risk








willingness to pay












19



are discussed below


β8Envirconcernj +

Where

























20


organic food






























21































22
































23

















GHcent12579 (US$1 0361)
















24

































25































26
































27
































28

WTP

Environmental

concern

Socio-demoghr

aphic characte

risitcs


Health

concern











willingness to pay


29




























30


31



from study area




two districts









Where






10020 households




32



=

____________________ (2)

Where






given in table 31



households


Rural 1910 191


Rural 2020 202











for each model

33
































34






























35











Where








362 WTP and CVM










36





















37





























38







provided




and Loomes 1994)













39

WTP

Yes

wtp

1st bid

yes

wtp 2nd

higher bid

yes No

No

wtp 2nd lower bid

yes No

No













40






estimated with β












41

















WTP

= 0

WTP

1-5

WTP

6-10

WTP

11-15

WTP

16-20

WTP

21-25

WTP

26-30

WTP

31-35

WTP

36-40

Above

40


42


Model









2011)












= )




responses is

]

43



the ith


sum

(

)

(

)

Where



















as

44

392 Bids Design







10 20 5

20 30 10

30 40 20

40 Above 30





sum

Where




as






45























Gender 0= Female

1= Male






1= Urban households



respondents






concerned

46
























discussed




47













Peshawar 3997 35382 42333 7217

(0000)

Mardan 5402 53188 55870 1104

(0136)

All 46995 47310 46659
















48




(2016)




Mardan 978 8782 12012 3780

(0001)

Peshawar 1138 7735 13257 8016

(0000)

All 1058 8436 12855















District


Mardan 863 8666 8548 0965

(0400)

Peshawar 567 6029 5484 -2122

(0018)

All 715 7796 6463


49










free








District


Mardan 63130 5489855 8145161 6018

(0000)

Peshawar 42430 2923529 4922727 9504

(0000)

All 52780 4642718 5952577












50


District


Mardan 49280 4511594 5854839 4256

(0000)

Peshawar 34860 2544118 3971212 7435

(0000)

Total 42070 3862136 4573196















Respondents


Mardan 4172 3798551 5003226 3055

(0000)

Peshawar 3800 2411765 4515152 5103

(0000)

All 3986 3340777 4671134


51


Fruit













environment





Grown




61 39



881

119


food supply

876 124




901

99


52










(WTP)























53

NotWTP

1_5 6_10 11_15 16_20 21_25 26_30 31_35 36_40 Above40

650 4

24

9

35

6 550 150

550 3








R2


















54































55


model)

Variables Estimated

Coefficient


Age 00698807 00147356 474 0000

Gender -02469171 08432503 -029 0770

Education 00821316 00223365 368 0000

Household size -00975395 00502583 -194 0052

Location

Urban

02783974 02961745 094 0347

Income 00000277 000000502 551 0000

Health concern 2600153 05346547 486 0000

Environment

concern

03993532 0574947 069 0487

Awareness 09595126 02836742 338 0001





56


model






























57
































58














price premium



















59

































Pakistan

60



















61


Not WTP

()

WTP 1-5

()

WTP 6-

10 ()

WTP 11-

15 ()

WTP 16-

20 ()

WTP 21-

25 ()

WTP 26-

30 ()

WTP 31-

35 ()

WTP 36-

40 ()

WTP

Above 40

()


00122 00179 02616 01183 04434 00620 00510 00110 00201 00026

Marginal effects

Age -0000 -0001 -0011 -0002 0007 0003 0003 0006 0001 0001

Gender 00039 00054 00623 0015 -0033 -0019 -0019 -0004 -0008 -0001

Education -0000 -0001 -0013 -0002 0010 0003 0003 0010 0020 0002

Household size 0002 0002 0012 0004 -0012 -0004 -0004 -0001 -0020 -0002

Urban rural -0003 -0004 -0049 -0009 0031 0013 0013 0002 0005 0001

Income -0003 -0004 -0004 -0010 0003 0001 0001 0002 0005 0010

Health concern -0103 -0113 -0372 0030 0410 0100 0100 0014 0030 0003

Environment

concern

-0005 -0007 -0072 -0010 0052 0017 0015 0003 0006 0008

Awareness -0014 -0020 -0120 -0030 0122 0045 0041 0010 0020 0002


62




size

Income Health

Concern

Environment

Concern

Age 10000

Gender -00193 10000

Education 00872 -00147 10000

Location 00725 00689 01047 10000

Households size -00294 00277 -00161 -01704 10000

Income 04123 -00690 02133 - 00405 01583 10000

Health Concern 01604 00224 02229 00660 - 00422 02102 10000


63


choice model
















residue














64
































65


a luxury


choice model)


Constant -8614601 3640408 -237 0018

Age 0294755 00638171 462 0000

Gender -0133885 - 4628428 003 0977

Education 04521878 01574002 287 0004

Income 00001208 00000284 426 0000

Householdlsquos

Size

-06690743 2499154 -268 0007

Health concern 6165207 1882292 328 0001

Environment

concern

6739389

2053786 328 0001

Awareness 8194937 1693789 484 0000

Urban Rural 02295739 1339268 017 0864














66

2

125 115

38

325

35

-5

0

5

10

15

20

25

30

35

40

45

0 1-10 11-20 21-30 31-40 gt40

Fre

qu

en

cy o

f th

e h

ou

seh

old

s

WTP bins



WTP 25798 10601 0 44511











67

0

01

02

03

04

05

06

10 20 30 40


Households

with YesNo

response


10 20 30 40

Households

with No

response

21 (1167) 24 (2581) 141 (5732) 63 (7778)

Households

with Yes

response

159 (8833) 69 (7419) 105 (4268) 18 (2222)

Total

Households

180 93 246 81












68
































69




















those not concerned









70



Constant -6174109 - 4353038 142 0158

Age 02348861 00467651 502 0000

Gender -2828394 3096026 - 091 0362

Education 0243413 00772618 315 0002

Income 00001237 00000157 790 0000

Householdlsquos

size

-03936806 01755667 -224 0026

Health concern 5567941 1465789 380 0000

Environment

concern

02999708 2023651 015 0882

Awareness 3567843 1001883 356 0000

Urban rural 0587075 1047051 056 0576


















71








Mean WTP (1437)

Payment card

Means WTP (1632)

Payment card

Mean WTP (1632)

MD (194)

t-value (250)

P-value (0006)

--------

Double bounded

Mean WTP (2576)

MD (1143)

t-value (1483)

P-value (0000)

MD (949)

t-value (1222)












Percent Response

to WTP question

Double dichotomous

choice

Payment card

method

Open ended

method

Yes 5850 87 4650

No 4150 13 5350


72


































73


































74








al2016
























75










yes or no response




















llt

Bi) is asked

76



































77












response properties





78




in future

51 Summary



























79



52 Conclusions






























80



















in the sample data















81
















53 Recommendations

















82
































83








56 Suggestions














84

LITERATURE CITED




Dublin Ireland



economics39(1)47-59











Conference503-511








85




















617





development398-103



86











18(2)277-287



61(5)926-930














87



Economics 32(10)1329-1336
























88





FAO Rome 1ndash279





















89






Research30(2)0044














15(2) 191-202







90






Economics 73(4)1255-1263







Engineering4 12-25








Journal 107(5) 320-343





edition

91



169














117










92














Marketing 23(4) 430-451








Hotel Nairobi Kenya







93





South Africa



452-466






Farminghtml















94



103390foods5040085












62(6)1311ndash1321














Tanzania (SAT)

95




press London












96



1 Location

o Rural

o Urban

2 Name ____________________

3 Age ____________________(years)

4 Gender

o Male

o Female







Fruits Quantity

Apple

Mango

Peaches


o Aware

o Not aware

97









supply

















Yes No





Rs _________

98





Yes No



1 WTP= 0

2 WTP= 1-5

3 WTP= 6-10

4 WTP= 11-15

5 WTP= 16-20

6 WTP= 21-25

7 WTP= 26-30

8 WTP= 31-35

9 WTP= 36-40







o Other reasons ___________________________

99


















Jahangir Khan

100








my Ph D Degree

Jahangir khan

Date

101














APPROVED BY





AampM USA



University Turkey



Dr Ghaffar Ali

TABLE OF CONTENTS

S No Title Page No

List of Table i

Acknowledgements ii

Abstract iii

I INTRODUCTION 1



























362 WTP and CVM 35







Model 39


Choice Model 42


392 Bids Design 44







on Fruit 51



(WTP) 52





choice model 63









51 Summary 78

52 Conclusions 79



56 Suggestions 83

LITERATURE CITED 84


i

LIST OF TABLE













Grown 51



logit model 61



choice model) 65







ii

ACKNOWLEDGEMENTS























Jahangir Khan

iii








Peshawar-Pakistan

May 2018

ABSTRACT





































iv




















1

I INTRODUCTION































2






























3

































4


































5
































6
































7
































8








free products





fruit


production




the study area


householdlsquos WTP








9

16 Hypotheses







hypothesis


Hypothesis 1



Hypothesis 2



Hypothesis 3















10













11
































12
































13











to pay




















14





sum

(

)

(

)

Where























15










should be open













premium






follows

16






















17
































18










sustenance and risk








willingness to pay












19



are discussed below


β8Envirconcernj +

Where

























20


organic food






























21































22
































23

















GHcent12579 (US$1 0361)
















24

































25































26
































27
































28

WTP

Environmental

concern

Socio-demoghr

aphic characte

risitcs


Health

concern











willingness to pay


29




























30


31



from study area




two districts









Where






10020 households




32



=

____________________ (2)

Where






given in table 31



households


Rural 1910 191


Rural 2020 202











for each model

33
































34






























35











Where








362 WTP and CVM










36





















37





























38







provided




and Loomes 1994)













39

WTP

Yes

wtp

1st bid

yes

wtp 2nd

higher bid

yes No

No

wtp 2nd lower bid

yes No

No













40






estimated with β












41

















WTP

= 0

WTP

1-5

WTP

6-10

WTP

11-15

WTP

16-20

WTP

21-25

WTP

26-30

WTP

31-35

WTP

36-40

Above

40


42


Model









2011)












= )




responses is

]

43



the ith


sum

(

)

(

)

Where



















as

44

392 Bids Design







10 20 5

20 30 10

30 40 20

40 Above 30





sum

Where




as






45























Gender 0= Female

1= Male






1= Urban households



respondents






concerned

46
























discussed




47













Peshawar 3997 35382 42333 7217

(0000)

Mardan 5402 53188 55870 1104

(0136)

All 46995 47310 46659
















48




(2016)




Mardan 978 8782 12012 3780

(0001)

Peshawar 1138 7735 13257 8016

(0000)

All 1058 8436 12855















District


Mardan 863 8666 8548 0965

(0400)

Peshawar 567 6029 5484 -2122

(0018)

All 715 7796 6463


49










free








District


Mardan 63130 5489855 8145161 6018

(0000)

Peshawar 42430 2923529 4922727 9504

(0000)

All 52780 4642718 5952577












50


District


Mardan 49280 4511594 5854839 4256

(0000)

Peshawar 34860 2544118 3971212 7435

(0000)

Total 42070 3862136 4573196















Respondents


Mardan 4172 3798551 5003226 3055

(0000)

Peshawar 3800 2411765 4515152 5103

(0000)

All 3986 3340777 4671134


51


Fruit













environment





Grown




61 39



881

119


food supply

876 124




901

99


52










(WTP)























53

NotWTP

1_5 6_10 11_15 16_20 21_25 26_30 31_35 36_40 Above40

650 4

24

9

35

6 550 150

550 3








R2


















54































55


model)

Variables Estimated

Coefficient


Age 00698807 00147356 474 0000

Gender -02469171 08432503 -029 0770

Education 00821316 00223365 368 0000

Household size -00975395 00502583 -194 0052

Location

Urban

02783974 02961745 094 0347

Income 00000277 000000502 551 0000

Health concern 2600153 05346547 486 0000

Environment

concern

03993532 0574947 069 0487

Awareness 09595126 02836742 338 0001





56


model






























57
































58














price premium



















59

































Pakistan

60



















61


Not WTP

()

WTP 1-5

()

WTP 6-

10 ()

WTP 11-

15 ()

WTP 16-

20 ()

WTP 21-

25 ()

WTP 26-

30 ()

WTP 31-

35 ()

WTP 36-

40 ()

WTP

Above 40

()


00122 00179 02616 01183 04434 00620 00510 00110 00201 00026

Marginal effects

Age -0000 -0001 -0011 -0002 0007 0003 0003 0006 0001 0001

Gender 00039 00054 00623 0015 -0033 -0019 -0019 -0004 -0008 -0001

Education -0000 -0001 -0013 -0002 0010 0003 0003 0010 0020 0002

Household size 0002 0002 0012 0004 -0012 -0004 -0004 -0001 -0020 -0002

Urban rural -0003 -0004 -0049 -0009 0031 0013 0013 0002 0005 0001

Income -0003 -0004 -0004 -0010 0003 0001 0001 0002 0005 0010

Health concern -0103 -0113 -0372 0030 0410 0100 0100 0014 0030 0003

Environment

concern

-0005 -0007 -0072 -0010 0052 0017 0015 0003 0006 0008

Awareness -0014 -0020 -0120 -0030 0122 0045 0041 0010 0020 0002


62




size

Income Health

Concern

Environment

Concern

Age 10000

Gender -00193 10000

Education 00872 -00147 10000

Location 00725 00689 01047 10000

Households size -00294 00277 -00161 -01704 10000

Income 04123 -00690 02133 - 00405 01583 10000

Health Concern 01604 00224 02229 00660 - 00422 02102 10000


63


choice model
















residue














64
































65


a luxury


choice model)


Constant -8614601 3640408 -237 0018

Age 0294755 00638171 462 0000

Gender -0133885 - 4628428 003 0977

Education 04521878 01574002 287 0004

Income 00001208 00000284 426 0000

Householdlsquos

Size

-06690743 2499154 -268 0007

Health concern 6165207 1882292 328 0001

Environment

concern

6739389

2053786 328 0001

Awareness 8194937 1693789 484 0000

Urban Rural 02295739 1339268 017 0864














66

2

125 115

38

325

35

-5

0

5

10

15

20

25

30

35

40

45

0 1-10 11-20 21-30 31-40 gt40

Fre

qu

en

cy o

f th

e h

ou

seh

old

s

WTP bins



WTP 25798 10601 0 44511











67

0

01

02

03

04

05

06

10 20 30 40


Households

with YesNo

response


10 20 30 40

Households

with No

response

21 (1167) 24 (2581) 141 (5732) 63 (7778)

Households

with Yes

response

159 (8833) 69 (7419) 105 (4268) 18 (2222)

Total

Households

180 93 246 81












68
































69




















those not concerned









70



Constant -6174109 - 4353038 142 0158

Age 02348861 00467651 502 0000

Gender -2828394 3096026 - 091 0362

Education 0243413 00772618 315 0002

Income 00001237 00000157 790 0000

Householdlsquos

size

-03936806 01755667 -224 0026

Health concern 5567941 1465789 380 0000

Environment

concern

02999708 2023651 015 0882

Awareness 3567843 1001883 356 0000

Urban rural 0587075 1047051 056 0576


















71








Mean WTP (1437)

Payment card

Means WTP (1632)

Payment card

Mean WTP (1632)

MD (194)

t-value (250)

P-value (0006)

--------

Double bounded

Mean WTP (2576)

MD (1143)

t-value (1483)

P-value (0000)

MD (949)

t-value (1222)












Percent Response

to WTP question

Double dichotomous

choice

Payment card

method

Open ended

method

Yes 5850 87 4650

No 4150 13 5350


72


































73


































74








al2016
























75










yes or no response




















llt

Bi) is asked

76



































77












response properties





78




in future

51 Summary



























79



52 Conclusions






























80



















in the sample data















81
















53 Recommendations

















82
































83








56 Suggestions














84

LITERATURE CITED




Dublin Ireland



economics39(1)47-59











Conference503-511








85




















617





development398-103



86











18(2)277-287



61(5)926-930














87



Economics 32(10)1329-1336
























88





FAO Rome 1ndash279





















89






Research30(2)0044














15(2) 191-202







90






Economics 73(4)1255-1263







Engineering4 12-25








Journal 107(5) 320-343





edition

91



169














117










92














Marketing 23(4) 430-451








Hotel Nairobi Kenya







93





South Africa



452-466






Farminghtml















94



103390foods5040085












62(6)1311ndash1321














Tanzania (SAT)

95




press London












96



1 Location

o Rural

o Urban

2 Name ____________________

3 Age ____________________(years)

4 Gender

o Male

o Female







Fruits Quantity

Apple

Mango

Peaches


o Aware

o Not aware

97









supply

















Yes No





Rs _________

98





Yes No



1 WTP= 0

2 WTP= 1-5

3 WTP= 6-10

4 WTP= 11-15

5 WTP= 16-20

6 WTP= 21-25

7 WTP= 26-30

8 WTP= 31-35

9 WTP= 36-40







o Other reasons ___________________________

99


















Jahangir Khan

100








my Ph D Degree

Jahangir khan

Date

101














APPROVED BY





AampM USA



University Turkey



Dr Ghaffar Ali

362 WTP and CVM 35







Model 39


Choice Model 42


392 Bids Design 44







on Fruit 51



(WTP) 52





choice model 63









51 Summary 78

52 Conclusions 79



56 Suggestions 83

LITERATURE CITED 84


i

LIST OF TABLE













Grown 51



logit model 61



choice model) 65







ii

ACKNOWLEDGEMENTS























Jahangir Khan

iii








Peshawar-Pakistan

May 2018

ABSTRACT





































iv




















1

I INTRODUCTION































2






























3

































4


































5
































6
































7
































8








free products





fruit


production




the study area


householdlsquos WTP








9

16 Hypotheses







hypothesis


Hypothesis 1



Hypothesis 2



Hypothesis 3















10













11
































12
































13











to pay




















14





sum

(

)

(

)

Where























15










should be open













premium






follows

16






















17
































18










sustenance and risk








willingness to pay












19



are discussed below


β8Envirconcernj +

Where

























20


organic food






























21































22
































23

















GHcent12579 (US$1 0361)
















24

































25































26
































27
































28

WTP

Environmental

concern

Socio-demoghr

aphic characte

risitcs


Health

concern











willingness to pay


29




























30


31



from study area




two districts









Where






10020 households




32



=

____________________ (2)

Where






given in table 31



households


Rural 1910 191


Rural 2020 202











for each model

33
































34






























35











Where








362 WTP and CVM










36





















37





























38







provided




and Loomes 1994)













39

WTP

Yes

wtp

1st bid

yes

wtp 2nd

higher bid

yes No

No

wtp 2nd lower bid

yes No

No













40






estimated with β












41

















WTP

= 0

WTP

1-5

WTP

6-10

WTP

11-15

WTP

16-20

WTP

21-25

WTP

26-30

WTP

31-35

WTP

36-40

Above

40


42


Model









2011)












= )




responses is

]

43



the ith


sum

(

)

(

)

Where



















as

44

392 Bids Design







10 20 5

20 30 10

30 40 20

40 Above 30





sum

Where




as






45























Gender 0= Female

1= Male






1= Urban households



respondents






concerned

46
























discussed




47













Peshawar 3997 35382 42333 7217

(0000)

Mardan 5402 53188 55870 1104

(0136)

All 46995 47310 46659
















48




(2016)




Mardan 978 8782 12012 3780

(0001)

Peshawar 1138 7735 13257 8016

(0000)

All 1058 8436 12855















District


Mardan 863 8666 8548 0965

(0400)

Peshawar 567 6029 5484 -2122

(0018)

All 715 7796 6463


49










free








District


Mardan 63130 5489855 8145161 6018

(0000)

Peshawar 42430 2923529 4922727 9504

(0000)

All 52780 4642718 5952577












50


District


Mardan 49280 4511594 5854839 4256

(0000)

Peshawar 34860 2544118 3971212 7435

(0000)

Total 42070 3862136 4573196















Respondents


Mardan 4172 3798551 5003226 3055

(0000)

Peshawar 3800 2411765 4515152 5103

(0000)

All 3986 3340777 4671134


51


Fruit













environment





Grown




61 39



881

119


food supply

876 124




901

99


52










(WTP)























53

NotWTP

1_5 6_10 11_15 16_20 21_25 26_30 31_35 36_40 Above40

650 4

24

9

35

6 550 150

550 3








R2


















54































55


model)

Variables Estimated

Coefficient


Age 00698807 00147356 474 0000

Gender -02469171 08432503 -029 0770

Education 00821316 00223365 368 0000

Household size -00975395 00502583 -194 0052

Location

Urban

02783974 02961745 094 0347

Income 00000277 000000502 551 0000

Health concern 2600153 05346547 486 0000

Environment

concern

03993532 0574947 069 0487

Awareness 09595126 02836742 338 0001





56


model






























57
































58














price premium



















59

































Pakistan

60



















61


Not WTP

()

WTP 1-5

()

WTP 6-

10 ()

WTP 11-

15 ()

WTP 16-

20 ()

WTP 21-

25 ()

WTP 26-

30 ()

WTP 31-

35 ()

WTP 36-

40 ()

WTP

Above 40

()


00122 00179 02616 01183 04434 00620 00510 00110 00201 00026

Marginal effects

Age -0000 -0001 -0011 -0002 0007 0003 0003 0006 0001 0001

Gender 00039 00054 00623 0015 -0033 -0019 -0019 -0004 -0008 -0001

Education -0000 -0001 -0013 -0002 0010 0003 0003 0010 0020 0002

Household size 0002 0002 0012 0004 -0012 -0004 -0004 -0001 -0020 -0002

Urban rural -0003 -0004 -0049 -0009 0031 0013 0013 0002 0005 0001

Income -0003 -0004 -0004 -0010 0003 0001 0001 0002 0005 0010

Health concern -0103 -0113 -0372 0030 0410 0100 0100 0014 0030 0003

Environment

concern

-0005 -0007 -0072 -0010 0052 0017 0015 0003 0006 0008

Awareness -0014 -0020 -0120 -0030 0122 0045 0041 0010 0020 0002


62




size

Income Health

Concern

Environment

Concern

Age 10000

Gender -00193 10000

Education 00872 -00147 10000

Location 00725 00689 01047 10000

Households size -00294 00277 -00161 -01704 10000

Income 04123 -00690 02133 - 00405 01583 10000

Health Concern 01604 00224 02229 00660 - 00422 02102 10000


63


choice model
















residue














64
































65


a luxury


choice model)


Constant -8614601 3640408 -237 0018

Age 0294755 00638171 462 0000

Gender -0133885 - 4628428 003 0977

Education 04521878 01574002 287 0004

Income 00001208 00000284 426 0000

Householdlsquos

Size

-06690743 2499154 -268 0007

Health concern 6165207 1882292 328 0001

Environment

concern

6739389

2053786 328 0001

Awareness 8194937 1693789 484 0000

Urban Rural 02295739 1339268 017 0864














66

2

125 115

38

325

35

-5

0

5

10

15

20

25

30

35

40

45

0 1-10 11-20 21-30 31-40 gt40

Fre

qu

en

cy o

f th

e h

ou

seh

old

s

WTP bins



WTP 25798 10601 0 44511











67

0

01

02

03

04

05

06

10 20 30 40


Households

with YesNo

response


10 20 30 40

Households

with No

response

21 (1167) 24 (2581) 141 (5732) 63 (7778)

Households

with Yes

response

159 (8833) 69 (7419) 105 (4268) 18 (2222)

Total

Households

180 93 246 81












68
































69




















those not concerned









70



Constant -6174109 - 4353038 142 0158

Age 02348861 00467651 502 0000

Gender -2828394 3096026 - 091 0362

Education 0243413 00772618 315 0002

Income 00001237 00000157 790 0000

Householdlsquos

size

-03936806 01755667 -224 0026

Health concern 5567941 1465789 380 0000

Environment

concern

02999708 2023651 015 0882

Awareness 3567843 1001883 356 0000

Urban rural 0587075 1047051 056 0576


















71








Mean WTP (1437)

Payment card

Means WTP (1632)

Payment card

Mean WTP (1632)

MD (194)

t-value (250)

P-value (0006)

--------

Double bounded

Mean WTP (2576)

MD (1143)

t-value (1483)

P-value (0000)

MD (949)

t-value (1222)












Percent Response

to WTP question

Double dichotomous

choice

Payment card

method

Open ended

method

Yes 5850 87 4650

No 4150 13 5350


72


































73


































74








al2016
























75










yes or no response




















llt

Bi) is asked

76



































77












response properties





78




in future

51 Summary



























79



52 Conclusions






























80



















in the sample data















81
















53 Recommendations

















82
































83








56 Suggestions














84

LITERATURE CITED




Dublin Ireland



economics39(1)47-59











Conference503-511








85




















617





development398-103



86











18(2)277-287



61(5)926-930














87



Economics 32(10)1329-1336
























88





FAO Rome 1ndash279





















89






Research30(2)0044














15(2) 191-202







90






Economics 73(4)1255-1263







Engineering4 12-25








Journal 107(5) 320-343





edition

91



169














117










92














Marketing 23(4) 430-451








Hotel Nairobi Kenya







93





South Africa



452-466






Farminghtml















94



103390foods5040085












62(6)1311ndash1321














Tanzania (SAT)

95




press London












96



1 Location

o Rural

o Urban

2 Name ____________________

3 Age ____________________(years)

4 Gender

o Male

o Female







Fruits Quantity

Apple

Mango

Peaches


o Aware

o Not aware

97









supply

















Yes No





Rs _________

98





Yes No



1 WTP= 0

2 WTP= 1-5

3 WTP= 6-10

4 WTP= 11-15

5 WTP= 16-20

6 WTP= 21-25

7 WTP= 26-30

8 WTP= 31-35

9 WTP= 36-40







o Other reasons ___________________________

99


















Jahangir Khan

100








my Ph D Degree

Jahangir khan

Date

101














APPROVED BY





AampM USA



University Turkey



Dr Ghaffar Ali


51 Summary 78

52 Conclusions 79



56 Suggestions 83

LITERATURE CITED 84


i

LIST OF TABLE













Grown 51



logit model 61



choice model) 65







ii

ACKNOWLEDGEMENTS























Jahangir Khan

iii








Peshawar-Pakistan

May 2018

ABSTRACT





































iv




















1

I INTRODUCTION































2






























3

































4


































5
































6
































7
































8








free products





fruit


production




the study area


householdlsquos WTP








9

16 Hypotheses







hypothesis


Hypothesis 1



Hypothesis 2



Hypothesis 3















10













11
































12
































13











to pay




















14





sum

(

)

(

)

Where























15










should be open













premium






follows

16






















17
































18










sustenance and risk








willingness to pay












19



are discussed below


β8Envirconcernj +

Where

























20


organic food






























21































22
































23

















GHcent12579 (US$1 0361)
















24

































25































26
































27
































28

WTP

Environmental

concern

Socio-demoghr

aphic characte

risitcs


Health

concern











willingness to pay


29




























30


31



from study area




two districts









Where






10020 households




32



=

____________________ (2)

Where






given in table 31



households


Rural 1910 191


Rural 2020 202











for each model

33
































34






























35











Where








362 WTP and CVM










36





















37





























38







provided




and Loomes 1994)













39

WTP

Yes

wtp

1st bid

yes

wtp 2nd

higher bid

yes No

No

wtp 2nd lower bid

yes No

No













40






estimated with β












41

















WTP

= 0

WTP

1-5

WTP

6-10

WTP

11-15

WTP

16-20

WTP

21-25

WTP

26-30

WTP

31-35

WTP

36-40

Above

40


42


Model









2011)












= )




responses is

]

43



the ith


sum

(

)

(

)

Where



















as

44

392 Bids Design







10 20 5

20 30 10

30 40 20

40 Above 30





sum

Where




as






45























Gender 0= Female

1= Male






1= Urban households



respondents






concerned

46
























discussed




47













Peshawar 3997 35382 42333 7217

(0000)

Mardan 5402 53188 55870 1104

(0136)

All 46995 47310 46659
















48




(2016)




Mardan 978 8782 12012 3780

(0001)

Peshawar 1138 7735 13257 8016

(0000)

All 1058 8436 12855















District


Mardan 863 8666 8548 0965

(0400)

Peshawar 567 6029 5484 -2122

(0018)

All 715 7796 6463


49










free








District


Mardan 63130 5489855 8145161 6018

(0000)

Peshawar 42430 2923529 4922727 9504

(0000)

All 52780 4642718 5952577












50


District


Mardan 49280 4511594 5854839 4256

(0000)

Peshawar 34860 2544118 3971212 7435

(0000)

Total 42070 3862136 4573196















Respondents


Mardan 4172 3798551 5003226 3055

(0000)

Peshawar 3800 2411765 4515152 5103

(0000)

All 3986 3340777 4671134


51


Fruit













environment





Grown




61 39



881

119


food supply

876 124




901

99


52










(WTP)























53

NotWTP

1_5 6_10 11_15 16_20 21_25 26_30 31_35 36_40 Above40

650 4

24

9

35

6 550 150

550 3








R2


















54































55


model)

Variables Estimated

Coefficient


Age 00698807 00147356 474 0000

Gender -02469171 08432503 -029 0770

Education 00821316 00223365 368 0000

Household size -00975395 00502583 -194 0052

Location

Urban

02783974 02961745 094 0347

Income 00000277 000000502 551 0000

Health concern 2600153 05346547 486 0000

Environment

concern

03993532 0574947 069 0487

Awareness 09595126 02836742 338 0001





56


model






























57
































58














price premium



















59

































Pakistan

60



















61


Not WTP

()

WTP 1-5

()

WTP 6-

10 ()

WTP 11-

15 ()

WTP 16-

20 ()

WTP 21-

25 ()

WTP 26-

30 ()

WTP 31-

35 ()

WTP 36-

40 ()

WTP

Above 40

()


00122 00179 02616 01183 04434 00620 00510 00110 00201 00026

Marginal effects

Age -0000 -0001 -0011 -0002 0007 0003 0003 0006 0001 0001

Gender 00039 00054 00623 0015 -0033 -0019 -0019 -0004 -0008 -0001

Education -0000 -0001 -0013 -0002 0010 0003 0003 0010 0020 0002

Household size 0002 0002 0012 0004 -0012 -0004 -0004 -0001 -0020 -0002

Urban rural -0003 -0004 -0049 -0009 0031 0013 0013 0002 0005 0001

Income -0003 -0004 -0004 -0010 0003 0001 0001 0002 0005 0010

Health concern -0103 -0113 -0372 0030 0410 0100 0100 0014 0030 0003

Environment

concern

-0005 -0007 -0072 -0010 0052 0017 0015 0003 0006 0008

Awareness -0014 -0020 -0120 -0030 0122 0045 0041 0010 0020 0002


62




size

Income Health

Concern

Environment

Concern

Age 10000

Gender -00193 10000

Education 00872 -00147 10000

Location 00725 00689 01047 10000

Households size -00294 00277 -00161 -01704 10000

Income 04123 -00690 02133 - 00405 01583 10000

Health Concern 01604 00224 02229 00660 - 00422 02102 10000


63


choice model
















residue














64
































65


a luxury


choice model)


Constant -8614601 3640408 -237 0018

Age 0294755 00638171 462 0000

Gender -0133885 - 4628428 003 0977

Education 04521878 01574002 287 0004

Income 00001208 00000284 426 0000

Householdlsquos

Size

-06690743 2499154 -268 0007

Health concern 6165207 1882292 328 0001

Environment

concern

6739389

2053786 328 0001

Awareness 8194937 1693789 484 0000

Urban Rural 02295739 1339268 017 0864














66

2

125 115

38

325

35

-5

0

5

10

15

20

25

30

35

40

45

0 1-10 11-20 21-30 31-40 gt40

Fre

qu

en

cy o

f th

e h

ou

seh

old

s

WTP bins



WTP 25798 10601 0 44511











67

0

01

02

03

04

05

06

10 20 30 40


Households

with YesNo

response


10 20 30 40

Households

with No

response

21 (1167) 24 (2581) 141 (5732) 63 (7778)

Households

with Yes

response

159 (8833) 69 (7419) 105 (4268) 18 (2222)

Total

Households

180 93 246 81












68
































69




















those not concerned









70



Constant -6174109 - 4353038 142 0158

Age 02348861 00467651 502 0000

Gender -2828394 3096026 - 091 0362

Education 0243413 00772618 315 0002

Income 00001237 00000157 790 0000

Householdlsquos

size

-03936806 01755667 -224 0026

Health concern 5567941 1465789 380 0000

Environment

concern

02999708 2023651 015 0882

Awareness 3567843 1001883 356 0000

Urban rural 0587075 1047051 056 0576


















71








Mean WTP (1437)

Payment card

Means WTP (1632)

Payment card

Mean WTP (1632)

MD (194)

t-value (250)

P-value (0006)

--------

Double bounded

Mean WTP (2576)

MD (1143)

t-value (1483)

P-value (0000)

MD (949)

t-value (1222)












Percent Response

to WTP question

Double dichotomous

choice

Payment card

method

Open ended

method

Yes 5850 87 4650

No 4150 13 5350


72


































73


































74








al2016
























75










yes or no response




















llt

Bi) is asked

76



































77












response properties





78




in future

51 Summary



























79



52 Conclusions






























80



















in the sample data















81
















53 Recommendations

















82
































83








56 Suggestions














84

LITERATURE CITED




Dublin Ireland



economics39(1)47-59











Conference503-511








85




















617





development398-103



86











18(2)277-287



61(5)926-930














87



Economics 32(10)1329-1336
























88





FAO Rome 1ndash279





















89






Research30(2)0044














15(2) 191-202







90






Economics 73(4)1255-1263







Engineering4 12-25








Journal 107(5) 320-343





edition

91



169














117










92














Marketing 23(4) 430-451








Hotel Nairobi Kenya







93





South Africa



452-466






Farminghtml















94



103390foods5040085












62(6)1311ndash1321














Tanzania (SAT)

95




press London












96



1 Location

o Rural

o Urban

2 Name ____________________

3 Age ____________________(years)

4 Gender

o Male

o Female







Fruits Quantity

Apple

Mango

Peaches


o Aware

o Not aware

97









supply

















Yes No





Rs _________

98





Yes No



1 WTP= 0

2 WTP= 1-5

3 WTP= 6-10

4 WTP= 11-15

5 WTP= 16-20

6 WTP= 21-25

7 WTP= 26-30

8 WTP= 31-35

9 WTP= 36-40







o Other reasons ___________________________

99


















Jahangir Khan

100








my Ph D Degree

Jahangir khan

Date

101














APPROVED BY





AampM USA



University Turkey



Dr Ghaffar Ali

i

LIST OF TABLE













Grown 51



logit model 61



choice model) 65







ii

ACKNOWLEDGEMENTS























Jahangir Khan

iii








Peshawar-Pakistan

May 2018

ABSTRACT





































iv




















1

I INTRODUCTION































2






























3

































4


































5
































6
































7
































8








free products





fruit


production




the study area


householdlsquos WTP








9

16 Hypotheses







hypothesis


Hypothesis 1



Hypothesis 2



Hypothesis 3















10













11
































12
































13











to pay




















14





sum

(

)

(

)

Where























15










should be open













premium






follows

16






















17
































18










sustenance and risk








willingness to pay












19



are discussed below


β8Envirconcernj +

Where

























20


organic food






























21































22
































23

















GHcent12579 (US$1 0361)
















24

































25































26
































27
































28

WTP

Environmental

concern

Socio-demoghr

aphic characte

risitcs


Health

concern











willingness to pay


29




























30


31



from study area




two districts









Where






10020 households




32



=

____________________ (2)

Where






given in table 31



households


Rural 1910 191


Rural 2020 202











for each model

33
































34






























35











Where








362 WTP and CVM










36





















37





























38







provided




and Loomes 1994)













39

WTP

Yes

wtp

1st bid

yes

wtp 2nd

higher bid

yes No

No

wtp 2nd lower bid

yes No

No













40






estimated with β












41

















WTP

= 0

WTP

1-5

WTP

6-10

WTP

11-15

WTP

16-20

WTP

21-25

WTP

26-30

WTP

31-35

WTP

36-40

Above

40


42


Model









2011)












= )




responses is

]

43



the ith


sum

(

)

(

)

Where



















as

44

392 Bids Design







10 20 5

20 30 10

30 40 20

40 Above 30





sum

Where




as






45























Gender 0= Female

1= Male






1= Urban households



respondents






concerned

46
























discussed




47













Peshawar 3997 35382 42333 7217

(0000)

Mardan 5402 53188 55870 1104

(0136)

All 46995 47310 46659
















48




(2016)




Mardan 978 8782 12012 3780

(0001)

Peshawar 1138 7735 13257 8016

(0000)

All 1058 8436 12855















District


Mardan 863 8666 8548 0965

(0400)

Peshawar 567 6029 5484 -2122

(0018)

All 715 7796 6463


49










free








District


Mardan 63130 5489855 8145161 6018

(0000)

Peshawar 42430 2923529 4922727 9504

(0000)

All 52780 4642718 5952577












50


District


Mardan 49280 4511594 5854839 4256

(0000)

Peshawar 34860 2544118 3971212 7435

(0000)

Total 42070 3862136 4573196















Respondents


Mardan 4172 3798551 5003226 3055

(0000)

Peshawar 3800 2411765 4515152 5103

(0000)

All 3986 3340777 4671134


51


Fruit













environment





Grown




61 39



881

119


food supply

876 124




901

99


52










(WTP)























53

NotWTP

1_5 6_10 11_15 16_20 21_25 26_30 31_35 36_40 Above40

650 4

24

9

35

6 550 150

550 3








R2


















54































55


model)

Variables Estimated

Coefficient


Age 00698807 00147356 474 0000

Gender -02469171 08432503 -029 0770

Education 00821316 00223365 368 0000

Household size -00975395 00502583 -194 0052

Location

Urban

02783974 02961745 094 0347

Income 00000277 000000502 551 0000

Health concern 2600153 05346547 486 0000

Environment

concern

03993532 0574947 069 0487

Awareness 09595126 02836742 338 0001





56


model






























57
































58














price premium



















59

































Pakistan

60



















61


Not WTP

()

WTP 1-5

()

WTP 6-

10 ()

WTP 11-

15 ()

WTP 16-

20 ()

WTP 21-

25 ()

WTP 26-

30 ()

WTP 31-

35 ()

WTP 36-

40 ()

WTP

Above 40

()


00122 00179 02616 01183 04434 00620 00510 00110 00201 00026

Marginal effects

Age -0000 -0001 -0011 -0002 0007 0003 0003 0006 0001 0001

Gender 00039 00054 00623 0015 -0033 -0019 -0019 -0004 -0008 -0001

Education -0000 -0001 -0013 -0002 0010 0003 0003 0010 0020 0002

Household size 0002 0002 0012 0004 -0012 -0004 -0004 -0001 -0020 -0002

Urban rural -0003 -0004 -0049 -0009 0031 0013 0013 0002 0005 0001

Income -0003 -0004 -0004 -0010 0003 0001 0001 0002 0005 0010

Health concern -0103 -0113 -0372 0030 0410 0100 0100 0014 0030 0003

Environment

concern

-0005 -0007 -0072 -0010 0052 0017 0015 0003 0006 0008

Awareness -0014 -0020 -0120 -0030 0122 0045 0041 0010 0020 0002


62




size

Income Health

Concern

Environment

Concern

Age 10000

Gender -00193 10000

Education 00872 -00147 10000

Location 00725 00689 01047 10000

Households size -00294 00277 -00161 -01704 10000

Income 04123 -00690 02133 - 00405 01583 10000

Health Concern 01604 00224 02229 00660 - 00422 02102 10000


63


choice model
















residue














64
































65


a luxury


choice model)


Constant -8614601 3640408 -237 0018

Age 0294755 00638171 462 0000

Gender -0133885 - 4628428 003 0977

Education 04521878 01574002 287 0004

Income 00001208 00000284 426 0000

Householdlsquos

Size

-06690743 2499154 -268 0007

Health concern 6165207 1882292 328 0001

Environment

concern

6739389

2053786 328 0001

Awareness 8194937 1693789 484 0000

Urban Rural 02295739 1339268 017 0864














66

2

125 115

38

325

35

-5

0

5

10

15

20

25

30

35

40

45

0 1-10 11-20 21-30 31-40 gt40

Fre

qu

en

cy o

f th

e h

ou

seh

old

s

WTP bins



WTP 25798 10601 0 44511











67

0

01

02

03

04

05

06

10 20 30 40


Households

with YesNo

response


10 20 30 40

Households

with No

response

21 (1167) 24 (2581) 141 (5732) 63 (7778)

Households

with Yes

response

159 (8833) 69 (7419) 105 (4268) 18 (2222)

Total

Households

180 93 246 81












68
































69




















those not concerned









70



Constant -6174109 - 4353038 142 0158

Age 02348861 00467651 502 0000

Gender -2828394 3096026 - 091 0362

Education 0243413 00772618 315 0002

Income 00001237 00000157 790 0000

Householdlsquos

size

-03936806 01755667 -224 0026

Health concern 5567941 1465789 380 0000

Environment

concern

02999708 2023651 015 0882

Awareness 3567843 1001883 356 0000

Urban rural 0587075 1047051 056 0576


















71








Mean WTP (1437)

Payment card

Means WTP (1632)

Payment card

Mean WTP (1632)

MD (194)

t-value (250)

P-value (0006)

--------

Double bounded

Mean WTP (2576)

MD (1143)

t-value (1483)

P-value (0000)

MD (949)

t-value (1222)












Percent Response

to WTP question

Double dichotomous

choice

Payment card

method

Open ended

method

Yes 5850 87 4650

No 4150 13 5350


72


































73


































74








al2016
























75










yes or no response




















llt

Bi) is asked

76



































77












response properties





78




in future

51 Summary



























79



52 Conclusions






























80



















in the sample data















81
















53 Recommendations

















82
































83








56 Suggestions














84

LITERATURE CITED




Dublin Ireland



economics39(1)47-59











Conference503-511








85




















617





development398-103



86











18(2)277-287



61(5)926-930














87



Economics 32(10)1329-1336
























88





FAO Rome 1ndash279





















89






Research30(2)0044














15(2) 191-202







90






Economics 73(4)1255-1263







Engineering4 12-25








Journal 107(5) 320-343





edition

91



169














117










92














Marketing 23(4) 430-451








Hotel Nairobi Kenya







93





South Africa



452-466






Farminghtml















94



103390foods5040085












62(6)1311ndash1321














Tanzania (SAT)

95




press London












96



1 Location

o Rural

o Urban

2 Name ____________________

3 Age ____________________(years)

4 Gender

o Male

o Female







Fruits Quantity

Apple

Mango

Peaches


o Aware

o Not aware

97









supply

















Yes No





Rs _________

98





Yes No



1 WTP= 0

2 WTP= 1-5

3 WTP= 6-10

4 WTP= 11-15

5 WTP= 16-20

6 WTP= 21-25

7 WTP= 26-30

8 WTP= 31-35

9 WTP= 36-40







o Other reasons ___________________________

99


















Jahangir Khan

100








my Ph D Degree

Jahangir khan

Date

101














APPROVED BY





AampM USA



University Turkey



Dr Ghaffar Ali

ii

ACKNOWLEDGEMENTS























Jahangir Khan

iii








Peshawar-Pakistan

May 2018

ABSTRACT





































iv




















1

I INTRODUCTION































2






























3

































4


































5
































6
































7
































8








free products





fruit


production




the study area


householdlsquos WTP








9

16 Hypotheses







hypothesis


Hypothesis 1



Hypothesis 2



Hypothesis 3















10













11
































12
































13











to pay




















14





sum

(

)

(

)

Where























15










should be open













premium






follows

16






















17
































18










sustenance and risk








willingness to pay












19



are discussed below


β8Envirconcernj +

Where

























20


organic food






























21































22
































23

















GHcent12579 (US$1 0361)
















24

































25































26
































27
































28

WTP

Environmental

concern

Socio-demoghr

aphic characte

risitcs


Health

concern











willingness to pay


29




























30


31



from study area




two districts









Where






10020 households




32



=

____________________ (2)

Where






given in table 31



households


Rural 1910 191


Rural 2020 202











for each model

33
































34






























35











Where








362 WTP and CVM










36





















37





























38







provided




and Loomes 1994)













39

WTP

Yes

wtp

1st bid

yes

wtp 2nd

higher bid

yes No

No

wtp 2nd lower bid

yes No

No













40






estimated with β












41

















WTP

= 0

WTP

1-5

WTP

6-10

WTP

11-15

WTP

16-20

WTP

21-25

WTP

26-30

WTP

31-35

WTP

36-40

Above

40


42


Model









2011)












= )




responses is

]

43



the ith


sum

(

)

(

)

Where



















as

44

392 Bids Design







10 20 5

20 30 10

30 40 20

40 Above 30





sum

Where




as






45























Gender 0= Female

1= Male






1= Urban households



respondents






concerned

46
























discussed




47













Peshawar 3997 35382 42333 7217

(0000)

Mardan 5402 53188 55870 1104

(0136)

All 46995 47310 46659
















48




(2016)




Mardan 978 8782 12012 3780

(0001)

Peshawar 1138 7735 13257 8016

(0000)

All 1058 8436 12855















District


Mardan 863 8666 8548 0965

(0400)

Peshawar 567 6029 5484 -2122

(0018)

All 715 7796 6463


49










free








District


Mardan 63130 5489855 8145161 6018

(0000)

Peshawar 42430 2923529 4922727 9504

(0000)

All 52780 4642718 5952577












50


District


Mardan 49280 4511594 5854839 4256

(0000)

Peshawar 34860 2544118 3971212 7435

(0000)

Total 42070 3862136 4573196















Respondents


Mardan 4172 3798551 5003226 3055

(0000)

Peshawar 3800 2411765 4515152 5103

(0000)

All 3986 3340777 4671134


51


Fruit













environment





Grown




61 39



881

119


food supply

876 124




901

99


52










(WTP)























53

NotWTP

1_5 6_10 11_15 16_20 21_25 26_30 31_35 36_40 Above40

650 4

24

9

35

6 550 150

550 3








R2


















54































55


model)

Variables Estimated

Coefficient


Age 00698807 00147356 474 0000

Gender -02469171 08432503 -029 0770

Education 00821316 00223365 368 0000

Household size -00975395 00502583 -194 0052

Location

Urban

02783974 02961745 094 0347

Income 00000277 000000502 551 0000

Health concern 2600153 05346547 486 0000

Environment

concern

03993532 0574947 069 0487

Awareness 09595126 02836742 338 0001





56


model






























57
































58














price premium



















59

































Pakistan

60



















61


Not WTP

()

WTP 1-5

()

WTP 6-

10 ()

WTP 11-

15 ()

WTP 16-

20 ()

WTP 21-

25 ()

WTP 26-

30 ()

WTP 31-

35 ()

WTP 36-

40 ()

WTP

Above 40

()


00122 00179 02616 01183 04434 00620 00510 00110 00201 00026

Marginal effects

Age -0000 -0001 -0011 -0002 0007 0003 0003 0006 0001 0001

Gender 00039 00054 00623 0015 -0033 -0019 -0019 -0004 -0008 -0001

Education -0000 -0001 -0013 -0002 0010 0003 0003 0010 0020 0002

Household size 0002 0002 0012 0004 -0012 -0004 -0004 -0001 -0020 -0002

Urban rural -0003 -0004 -0049 -0009 0031 0013 0013 0002 0005 0001

Income -0003 -0004 -0004 -0010 0003 0001 0001 0002 0005 0010

Health concern -0103 -0113 -0372 0030 0410 0100 0100 0014 0030 0003

Environment

concern

-0005 -0007 -0072 -0010 0052 0017 0015 0003 0006 0008

Awareness -0014 -0020 -0120 -0030 0122 0045 0041 0010 0020 0002


62




size

Income Health

Concern

Environment

Concern

Age 10000

Gender -00193 10000

Education 00872 -00147 10000

Location 00725 00689 01047 10000

Households size -00294 00277 -00161 -01704 10000

Income 04123 -00690 02133 - 00405 01583 10000

Health Concern 01604 00224 02229 00660 - 00422 02102 10000


63


choice model
















residue














64
































65


a luxury


choice model)


Constant -8614601 3640408 -237 0018

Age 0294755 00638171 462 0000

Gender -0133885 - 4628428 003 0977

Education 04521878 01574002 287 0004

Income 00001208 00000284 426 0000

Householdlsquos

Size

-06690743 2499154 -268 0007

Health concern 6165207 1882292 328 0001

Environment

concern

6739389

2053786 328 0001

Awareness 8194937 1693789 484 0000

Urban Rural 02295739 1339268 017 0864














66

2

125 115

38

325

35

-5

0

5

10

15

20

25

30

35

40

45

0 1-10 11-20 21-30 31-40 gt40

Fre

qu

en

cy o

f th

e h

ou

seh

old

s

WTP bins



WTP 25798 10601 0 44511











67

0

01

02

03

04

05

06

10 20 30 40


Households

with YesNo

response


10 20 30 40

Households

with No

response

21 (1167) 24 (2581) 141 (5732) 63 (7778)

Households

with Yes

response

159 (8833) 69 (7419) 105 (4268) 18 (2222)

Total

Households

180 93 246 81












68
































69




















those not concerned









70



Constant -6174109 - 4353038 142 0158

Age 02348861 00467651 502 0000

Gender -2828394 3096026 - 091 0362

Education 0243413 00772618 315 0002

Income 00001237 00000157 790 0000

Householdlsquos

size

-03936806 01755667 -224 0026

Health concern 5567941 1465789 380 0000

Environment

concern

02999708 2023651 015 0882

Awareness 3567843 1001883 356 0000

Urban rural 0587075 1047051 056 0576


















71








Mean WTP (1437)

Payment card

Means WTP (1632)

Payment card

Mean WTP (1632)

MD (194)

t-value (250)

P-value (0006)

--------

Double bounded

Mean WTP (2576)

MD (1143)

t-value (1483)

P-value (0000)

MD (949)

t-value (1222)












Percent Response

to WTP question

Double dichotomous

choice

Payment card

method

Open ended

method

Yes 5850 87 4650

No 4150 13 5350


72


































73


































74








al2016
























75










yes or no response




















llt

Bi) is asked

76



































77












response properties





78




in future

51 Summary



























79



52 Conclusions






























80



















in the sample data















81
















53 Recommendations

















82
































83








56 Suggestions














84

LITERATURE CITED




Dublin Ireland



economics39(1)47-59











Conference503-511








85




















617





development398-103



86











18(2)277-287



61(5)926-930














87



Economics 32(10)1329-1336
























88





FAO Rome 1ndash279





















89






Research30(2)0044














15(2) 191-202







90






Economics 73(4)1255-1263







Engineering4 12-25








Journal 107(5) 320-343





edition

91



169














117










92














Marketing 23(4) 430-451








Hotel Nairobi Kenya







93





South Africa



452-466






Farminghtml















94



103390foods5040085












62(6)1311ndash1321














Tanzania (SAT)

95




press London












96



1 Location

o Rural

o Urban

2 Name ____________________

3 Age ____________________(years)

4 Gender

o Male

o Female







Fruits Quantity

Apple

Mango

Peaches


o Aware

o Not aware

97









supply

















Yes No





Rs _________

98





Yes No



1 WTP= 0

2 WTP= 1-5

3 WTP= 6-10

4 WTP= 11-15

5 WTP= 16-20

6 WTP= 21-25

7 WTP= 26-30

8 WTP= 31-35

9 WTP= 36-40







o Other reasons ___________________________

99


















Jahangir Khan

100








my Ph D Degree

Jahangir khan

Date

101














APPROVED BY





AampM USA



University Turkey



Dr Ghaffar Ali

iii








Peshawar-Pakistan

May 2018

ABSTRACT





































iv




















1

I INTRODUCTION































2






























3

































4


































5
































6
































7
































8








free products





fruit


production




the study area


householdlsquos WTP








9

16 Hypotheses







hypothesis


Hypothesis 1



Hypothesis 2



Hypothesis 3















10













11
































12
































13











to pay




















14





sum

(

)

(

)

Where























15










should be open













premium






follows

16






















17
































18










sustenance and risk








willingness to pay












19



are discussed below


β8Envirconcernj +

Where

























20


organic food






























21































22
































23

















GHcent12579 (US$1 0361)
















24

































25































26
































27
































28

WTP

Environmental

concern

Socio-demoghr

aphic characte

risitcs


Health

concern











willingness to pay


29




























30


31



from study area




two districts









Where






10020 households




32



=

____________________ (2)

Where






given in table 31



households


Rural 1910 191


Rural 2020 202











for each model

33
































34






























35











Where








362 WTP and CVM










36





















37





























38







provided




and Loomes 1994)













39

WTP

Yes

wtp

1st bid

yes

wtp 2nd

higher bid

yes No

No

wtp 2nd lower bid

yes No

No













40






estimated with β












41

















WTP

= 0

WTP

1-5

WTP

6-10

WTP

11-15

WTP

16-20

WTP

21-25

WTP

26-30

WTP

31-35

WTP

36-40

Above

40


42


Model









2011)












= )




responses is

]

43



the ith


sum

(

)

(

)

Where



















as

44

392 Bids Design







10 20 5

20 30 10

30 40 20

40 Above 30





sum

Where




as






45























Gender 0= Female

1= Male






1= Urban households



respondents






concerned

46
























discussed




47













Peshawar 3997 35382 42333 7217

(0000)

Mardan 5402 53188 55870 1104

(0136)

All 46995 47310 46659
















48




(2016)




Mardan 978 8782 12012 3780

(0001)

Peshawar 1138 7735 13257 8016

(0000)

All 1058 8436 12855















District


Mardan 863 8666 8548 0965

(0400)

Peshawar 567 6029 5484 -2122

(0018)

All 715 7796 6463


49










free








District


Mardan 63130 5489855 8145161 6018

(0000)

Peshawar 42430 2923529 4922727 9504

(0000)

All 52780 4642718 5952577












50


District


Mardan 49280 4511594 5854839 4256

(0000)

Peshawar 34860 2544118 3971212 7435

(0000)

Total 42070 3862136 4573196















Respondents


Mardan 4172 3798551 5003226 3055

(0000)

Peshawar 3800 2411765 4515152 5103

(0000)

All 3986 3340777 4671134


51


Fruit













environment





Grown




61 39



881

119


food supply

876 124




901

99


52










(WTP)























53

NotWTP

1_5 6_10 11_15 16_20 21_25 26_30 31_35 36_40 Above40

650 4

24

9

35

6 550 150

550 3








R2


















54































55


model)

Variables Estimated

Coefficient


Age 00698807 00147356 474 0000

Gender -02469171 08432503 -029 0770

Education 00821316 00223365 368 0000

Household size -00975395 00502583 -194 0052

Location

Urban

02783974 02961745 094 0347

Income 00000277 000000502 551 0000

Health concern 2600153 05346547 486 0000

Environment

concern

03993532 0574947 069 0487

Awareness 09595126 02836742 338 0001





56


model






























57
































58














price premium



















59

































Pakistan

60



















61


Not WTP

()

WTP 1-5

()

WTP 6-

10 ()

WTP 11-

15 ()

WTP 16-

20 ()

WTP 21-

25 ()

WTP 26-

30 ()

WTP 31-

35 ()

WTP 36-

40 ()

WTP

Above 40

()


00122 00179 02616 01183 04434 00620 00510 00110 00201 00026

Marginal effects

Age -0000 -0001 -0011 -0002 0007 0003 0003 0006 0001 0001

Gender 00039 00054 00623 0015 -0033 -0019 -0019 -0004 -0008 -0001

Education -0000 -0001 -0013 -0002 0010 0003 0003 0010 0020 0002

Household size 0002 0002 0012 0004 -0012 -0004 -0004 -0001 -0020 -0002

Urban rural -0003 -0004 -0049 -0009 0031 0013 0013 0002 0005 0001

Income -0003 -0004 -0004 -0010 0003 0001 0001 0002 0005 0010

Health concern -0103 -0113 -0372 0030 0410 0100 0100 0014 0030 0003

Environment

concern

-0005 -0007 -0072 -0010 0052 0017 0015 0003 0006 0008

Awareness -0014 -0020 -0120 -0030 0122 0045 0041 0010 0020 0002


62




size

Income Health

Concern

Environment

Concern

Age 10000

Gender -00193 10000

Education 00872 -00147 10000

Location 00725 00689 01047 10000

Households size -00294 00277 -00161 -01704 10000

Income 04123 -00690 02133 - 00405 01583 10000

Health Concern 01604 00224 02229 00660 - 00422 02102 10000


63


choice model
















residue














64
































65


a luxury


choice model)


Constant -8614601 3640408 -237 0018

Age 0294755 00638171 462 0000

Gender -0133885 - 4628428 003 0977

Education 04521878 01574002 287 0004

Income 00001208 00000284 426 0000

Householdlsquos

Size

-06690743 2499154 -268 0007

Health concern 6165207 1882292 328 0001

Environment

concern

6739389

2053786 328 0001

Awareness 8194937 1693789 484 0000

Urban Rural 02295739 1339268 017 0864














66

2

125 115

38

325

35

-5

0

5

10

15

20

25

30

35

40

45

0 1-10 11-20 21-30 31-40 gt40

Fre

qu

en

cy o

f th

e h

ou

seh

old

s

WTP bins



WTP 25798 10601 0 44511











67

0

01

02

03

04

05

06

10 20 30 40


Households

with YesNo

response


10 20 30 40

Households

with No

response

21 (1167) 24 (2581) 141 (5732) 63 (7778)

Households

with Yes

response

159 (8833) 69 (7419) 105 (4268) 18 (2222)

Total

Households

180 93 246 81












68
































69




















those not concerned









70



Constant -6174109 - 4353038 142 0158

Age 02348861 00467651 502 0000

Gender -2828394 3096026 - 091 0362

Education 0243413 00772618 315 0002

Income 00001237 00000157 790 0000

Householdlsquos

size

-03936806 01755667 -224 0026

Health concern 5567941 1465789 380 0000

Environment

concern

02999708 2023651 015 0882

Awareness 3567843 1001883 356 0000

Urban rural 0587075 1047051 056 0576


















71








Mean WTP (1437)

Payment card

Means WTP (1632)

Payment card

Mean WTP (1632)

MD (194)

t-value (250)

P-value (0006)

--------

Double bounded

Mean WTP (2576)

MD (1143)

t-value (1483)

P-value (0000)

MD (949)

t-value (1222)












Percent Response

to WTP question

Double dichotomous

choice

Payment card

method

Open ended

method

Yes 5850 87 4650

No 4150 13 5350


72


































73


































74








al2016
























75










yes or no response




















llt

Bi) is asked

76



































77












response properties





78




in future

51 Summary



























79



52 Conclusions






























80



















in the sample data















81
















53 Recommendations

















82
































83








56 Suggestions














84

LITERATURE CITED




Dublin Ireland



economics39(1)47-59











Conference503-511








85




















617





development398-103



86











18(2)277-287



61(5)926-930














87



Economics 32(10)1329-1336
























88





FAO Rome 1ndash279





















89






Research30(2)0044














15(2) 191-202







90






Economics 73(4)1255-1263







Engineering4 12-25








Journal 107(5) 320-343





edition

91



169














117










92














Marketing 23(4) 430-451








Hotel Nairobi Kenya







93





South Africa



452-466






Farminghtml















94



103390foods5040085












62(6)1311ndash1321














Tanzania (SAT)

95




press London












96



1 Location

o Rural

o Urban

2 Name ____________________

3 Age ____________________(years)

4 Gender

o Male

o Female







Fruits Quantity

Apple

Mango

Peaches


o Aware

o Not aware

97









supply

















Yes No





Rs _________

98





Yes No



1 WTP= 0

2 WTP= 1-5

3 WTP= 6-10

4 WTP= 11-15

5 WTP= 16-20

6 WTP= 21-25

7 WTP= 26-30

8 WTP= 31-35

9 WTP= 36-40







o Other reasons ___________________________

99


















Jahangir Khan

100








my Ph D Degree

Jahangir khan

Date

101














APPROVED BY





AampM USA



University Turkey



Dr Ghaffar Ali

iv




















1

I INTRODUCTION































2






























3

































4


































5
































6
































7
































8








free products





fruit


production




the study area


householdlsquos WTP








9

16 Hypotheses







hypothesis


Hypothesis 1



Hypothesis 2



Hypothesis 3















10













11
































12
































13











to pay




















14





sum

(

)

(

)

Where























15










should be open













premium






follows

16






















17
































18










sustenance and risk








willingness to pay












19



are discussed below


β8Envirconcernj +

Where

























20


organic food






























21































22
































23

















GHcent12579 (US$1 0361)
















24

































25































26
































27
































28

WTP

Environmental

concern

Socio-demoghr

aphic characte

risitcs


Health

concern











willingness to pay


29




























30


31



from study area




two districts









Where






10020 households




32



=

____________________ (2)

Where






given in table 31



households


Rural 1910 191


Rural 2020 202











for each model

33
































34






























35











Where








362 WTP and CVM










36





















37





























38







provided




and Loomes 1994)













39

WTP

Yes

wtp

1st bid

yes

wtp 2nd

higher bid

yes No

No

wtp 2nd lower bid

yes No

No













40






estimated with β












41

















WTP

= 0

WTP

1-5

WTP

6-10

WTP

11-15

WTP

16-20

WTP

21-25

WTP

26-30

WTP

31-35

WTP

36-40

Above

40


42


Model









2011)












= )




responses is

]

43



the ith


sum

(

)

(

)

Where



















as

44

392 Bids Design







10 20 5

20 30 10

30 40 20

40 Above 30





sum

Where




as






45























Gender 0= Female

1= Male






1= Urban households



respondents






concerned

46
























discussed




47













Peshawar 3997 35382 42333 7217

(0000)

Mardan 5402 53188 55870 1104

(0136)

All 46995 47310 46659
















48




(2016)




Mardan 978 8782 12012 3780

(0001)

Peshawar 1138 7735 13257 8016

(0000)

All 1058 8436 12855















District


Mardan 863 8666 8548 0965

(0400)

Peshawar 567 6029 5484 -2122

(0018)

All 715 7796 6463


49










free








District


Mardan 63130 5489855 8145161 6018

(0000)

Peshawar 42430 2923529 4922727 9504

(0000)

All 52780 4642718 5952577












50


District


Mardan 49280 4511594 5854839 4256

(0000)

Peshawar 34860 2544118 3971212 7435

(0000)

Total 42070 3862136 4573196















Respondents


Mardan 4172 3798551 5003226 3055

(0000)

Peshawar 3800 2411765 4515152 5103

(0000)

All 3986 3340777 4671134


51


Fruit













environment





Grown




61 39



881

119


food supply

876 124




901

99


52










(WTP)























53

NotWTP

1_5 6_10 11_15 16_20 21_25 26_30 31_35 36_40 Above40

650 4

24

9

35

6 550 150

550 3








R2


















54































55


model)

Variables Estimated

Coefficient


Age 00698807 00147356 474 0000

Gender -02469171 08432503 -029 0770

Education 00821316 00223365 368 0000

Household size -00975395 00502583 -194 0052

Location

Urban

02783974 02961745 094 0347

Income 00000277 000000502 551 0000

Health concern 2600153 05346547 486 0000

Environment

concern

03993532 0574947 069 0487

Awareness 09595126 02836742 338 0001





56


model






























57
































58














price premium



















59

































Pakistan

60



















61


Not WTP

()

WTP 1-5

()

WTP 6-

10 ()

WTP 11-

15 ()

WTP 16-

20 ()

WTP 21-

25 ()

WTP 26-

30 ()

WTP 31-

35 ()

WTP 36-

40 ()

WTP

Above 40

()


00122 00179 02616 01183 04434 00620 00510 00110 00201 00026

Marginal effects

Age -0000 -0001 -0011 -0002 0007 0003 0003 0006 0001 0001

Gender 00039 00054 00623 0015 -0033 -0019 -0019 -0004 -0008 -0001

Education -0000 -0001 -0013 -0002 0010 0003 0003 0010 0020 0002

Household size 0002 0002 0012 0004 -0012 -0004 -0004 -0001 -0020 -0002

Urban rural -0003 -0004 -0049 -0009 0031 0013 0013 0002 0005 0001

Income -0003 -0004 -0004 -0010 0003 0001 0001 0002 0005 0010

Health concern -0103 -0113 -0372 0030 0410 0100 0100 0014 0030 0003

Environment

concern

-0005 -0007 -0072 -0010 0052 0017 0015 0003 0006 0008

Awareness -0014 -0020 -0120 -0030 0122 0045 0041 0010 0020 0002


62




size

Income Health

Concern

Environment

Concern

Age 10000

Gender -00193 10000

Education 00872 -00147 10000

Location 00725 00689 01047 10000

Households size -00294 00277 -00161 -01704 10000

Income 04123 -00690 02133 - 00405 01583 10000

Health Concern 01604 00224 02229 00660 - 00422 02102 10000


63


choice model
















residue














64
































65


a luxury


choice model)


Constant -8614601 3640408 -237 0018

Age 0294755 00638171 462 0000

Gender -0133885 - 4628428 003 0977

Education 04521878 01574002 287 0004

Income 00001208 00000284 426 0000

Householdlsquos

Size

-06690743 2499154 -268 0007

Health concern 6165207 1882292 328 0001

Environment

concern

6739389

2053786 328 0001

Awareness 8194937 1693789 484 0000

Urban Rural 02295739 1339268 017 0864














66

2

125 115

38

325

35

-5

0

5

10

15

20

25

30

35

40

45

0 1-10 11-20 21-30 31-40 gt40

Fre

qu

en

cy o

f th

e h

ou

seh

old

s

WTP bins



WTP 25798 10601 0 44511











67

0

01

02

03

04

05

06

10 20 30 40


Households

with YesNo

response


10 20 30 40

Households

with No

response

21 (1167) 24 (2581) 141 (5732) 63 (7778)

Households

with Yes

response

159 (8833) 69 (7419) 105 (4268) 18 (2222)

Total

Households

180 93 246 81












68
































69




















those not concerned









70



Constant -6174109 - 4353038 142 0158

Age 02348861 00467651 502 0000

Gender -2828394 3096026 - 091 0362

Education 0243413 00772618 315 0002

Income 00001237 00000157 790 0000

Householdlsquos

size

-03936806 01755667 -224 0026

Health concern 5567941 1465789 380 0000

Environment

concern

02999708 2023651 015 0882

Awareness 3567843 1001883 356 0000

Urban rural 0587075 1047051 056 0576


















71








Mean WTP (1437)

Payment card

Means WTP (1632)

Payment card

Mean WTP (1632)

MD (194)

t-value (250)

P-value (0006)

--------

Double bounded

Mean WTP (2576)

MD (1143)

t-value (1483)

P-value (0000)

MD (949)

t-value (1222)












Percent Response

to WTP question

Double dichotomous

choice

Payment card

method

Open ended

method

Yes 5850 87 4650

No 4150 13 5350


72


































73


































74








al2016
























75










yes or no response




















llt

Bi) is asked

76



































77












response properties





78




in future

51 Summary



























79



52 Conclusions






























80



















in the sample data















81
















53 Recommendations

















82
































83








56 Suggestions














84

LITERATURE CITED




Dublin Ireland



economics39(1)47-59











Conference503-511








85




















617





development398-103



86











18(2)277-287



61(5)926-930














87



Economics 32(10)1329-1336
























88





FAO Rome 1ndash279





















89






Research30(2)0044














15(2) 191-202







90






Economics 73(4)1255-1263







Engineering4 12-25








Journal 107(5) 320-343





edition

91



169














117










92














Marketing 23(4) 430-451








Hotel Nairobi Kenya







93





South Africa



452-466






Farminghtml















94



103390foods5040085












62(6)1311ndash1321














Tanzania (SAT)

95




press London












96



1 Location

o Rural

o Urban

2 Name ____________________

3 Age ____________________(years)

4 Gender

o Male

o Female







Fruits Quantity

Apple

Mango

Peaches


o Aware

o Not aware

97









supply

















Yes No





Rs _________

98





Yes No



1 WTP= 0

2 WTP= 1-5

3 WTP= 6-10

4 WTP= 11-15

5 WTP= 16-20

6 WTP= 21-25

7 WTP= 26-30

8 WTP= 31-35

9 WTP= 36-40







o Other reasons ___________________________

99


















Jahangir Khan

100








my Ph D Degree

Jahangir khan

Date

101














APPROVED BY





AampM USA



University Turkey



Dr Ghaffar Ali

household’s prefrences and willingness to pay for

Documents