Economics Working Paper Series

RE Centre for Training and Research in

Public Finance and Policy

Does inequality affect the consumption patterns of the poor? The role of “status

seeking” behaviour

Sugata Marjit Sattwik Santra

Koushik Kumar Hati

WP NO 4

CENTRE FOR TRAINING AND RESEARCH IN PUBLIC FINANCE AND POLICY WEBSITE: WWW.CTRPFP.AC.IN

Centre for Studies in Social Sciences,

Calcutta

Reserve Bank of India, Industrial Economics

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Does inequality affect the consumption patterns of the poor?

The role of “status seeking” behaviour

Sugata Marjit

Centre for Studies in Social Sciences, Calcutta

and Indian Statistical Institute, Kolkata

Sattwik Santra

Centre for Studies in Social Sciences, Calcutta

Koushik Kumar Hati

Centre for Studies in Social Sciences, Calcutta

Abstract

We consider a situation where the relatively ‘poor’ are concerned about their relative income

status with respect to a relevant reference group. Such a concern is explicitly introduced in a

utility function to study the consequences of societal status on the consumption behavior of the

poor. The theoretical model points toward a possible conflict between income based and

nutrition-based measure of poverty. Our theoretical model point toward a direct and negative

relationship between inequality and share of nutritional consumption as reflected in the

consumption of food. Finally the paper looks at the empirical relationship between inequality

and consumption across districts within states of India. The hypotheses that inequality impacts

consumption patterns via status effect turns out to be statistically significant for almost all the

Indian states.

Keywords: Status; Consumption pattern; Inequality; Poverty;

JEL Classification: D01, O40, D12, C13, C14, C51

This paper has benefitted from seminars delivered at the Indian Institute of Management, Ahmedabad, Indian

Statistical Institute, Delhi, Asian Development Bank, Manila, Indian Association for Cultivation of Science,

Calcutta, Institute for Fiscal Studies, UK, and Delhi School of Economics. We are indebted to Richard Blundell,

Giacomo Corneo, Krishnendu Ghosh Dastidar and Abhirup Sarkar for extensive discussions. Financial support

from RBI Endowment and CTRPFP at CSSSC is gratefully acknowledged. The usual disclaimer applies.

I. Introduction

A fundamental query involving the preference pattern of any individual in a society, has to deal

with the influence of the society on the consumption behavior of the individual. The idea of

conspicuous consumption and the so-called Veblen effect are quite well known in economics.

Very recently, Sivanathan and Petit (2010) have confirmed the fact that individuals are quite

sensitive to their relative status in the society and would like to ‘mend’ their ‘self’, under

constant attack from various social pressures, by taking recourse to status-signaling consumption

behaviour. A series of experiments confirms such a pattern of human behaviour. This is one of

the building blocks of the utility function that we use in the subsequent analysis. Early literature

includes Frank (1985) who talks about context dependent preferences and the concern for status

as we discuss in this paper, is an issue related to a particular social context. More recently,

Mujcic and Frijters (2013) have explicitly and convincingly demonstrated a method for

measuring the willingness to pay to move up the status ladder.The paper starts off by

highlighting a well-observed empirical phenomenon, discussed extensively in the literature on

poverty in India. Patnaik (2007) and Deaton and Dreze (2009) have dealt with the conflict

between income-based measure and nutrition-based measures of poverty. In India people moving

above the poverty line with greater monthly expenditure on overall consumption demonstrate

lower nutritional intake. Thus Patnaik (2007) asserts that actual poverty estimate is far greater

than the optimistic figure provided by the government. While Deaton and Dreze (2009) analyze

various reasons for such a behaviour, not much emphasis is given to the role of a status-driven

consumption pattern, although they do not altogether ignore such a possibility. That social

inequality can influence individuals’ consumption and induce greater consumption of the so-

called status good, becomes quite relevant for such analysis. Thematically this is undermined and

under-explored in the poverty literature. We will eventually demonstrate why preexisting social

inequality can lead to the conflicting measures of poverty and provide empirical evidences to

justify our standpoint.

II. Literature Review

There are a number of works that highlight the conflict between income-based measure and

nutrition-based measure of poverty and offer some reasonable explanations. Patnaik (2007)’s

analysis shows that the official level of poverty (which has been very optimistic of lately) has

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been highly underestimating the true scenario. The paper further focuses on the contradictory

empirical finding that states having higher value in poverty index using income-based measure

may have higher calorie intakes and the vice-versa. Such contradictions in results with the two

different measures have been found for states in India like Gujarat and Bihar, Orissa and Andhra

Pradesh. The paper also highlights the fact that calorie intake alone, cannot measure poverty to

its maximum precision. There are many cases where high income groups consume lower levels

of calories in comparison to their age and sex. This might be due to their job requirements, or

their amount of physical labour might be low and due to certain health conditions.

Deaton and Dreze (2009) analyse the reason behind the discrepancies in the results of the two

measures of poverty. They observe that nutritional intake, proxied by calorie intake, has been

declining with rising incomes as a result of change in activity structure affecting the food intake

pattern in both rural and urban societies. Though they emphasize that calorie intake in itself

cannot measure the well-being of the society as other nutrients are also equally important. There

is also an indication to the possibility of a squeeze in the food budget of poor household for

increase in non-food expenses like schooling and other social necessities.

A paper by Radhakrishna and Ravi (2004) explores an empirical relationship between

malnutrition and poverty for the rural India, along with a logit regression using maximum

likelihood method to identify the determinants of rural malnutrition. Their findings suggest that

even though there is some achievement in poverty reduction, India has not been very successful

in reducing malnutrition. In a working paper by Mukherjee, Rajaraman, and Swaminathan

(2010), they have modeled both under nutrition and over nutrition in India along with which they

have discussed the role of different forms of economic inequality, and various behavioral

variable (such as diet and activity) that affect nutrition. Analysis of under and over weight in

India using data from 1998-1999 have found individual socioeconomic status to be an important

predictor of being overweight [Griffiths and Bentley (2001)]. Peter Svedberg (2008) addressed

the question as to why high overall economic growth in India has failed to alleviate child

malnutrition. This paper tries to provide firm empirical and quantitative evidence of female

subjugation relative to poverty income as a reason for stunted growth in nutritional status.

Nevertheless, not much focus has been given in India on the role of status affecting the

consumption pattern of the poor people. Most of the explanations regarding falling nutrition

levels, provided till date, have been related to stagnation in agricultural production with more

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than 50% of the population being employed in agriculture. But the last few decades have seen a

large shift in the sectorial composition of employment structure as well and so there is a need to

explore further avenues to explain the contradictory results with the two measures of poverty. In

general there is a need to understand the impact of status on consumption patterns of individuals

for tax and welfare related policies in general.

One issue that is empirically relevant for research on poverty and nutrition, has to do with the

causal relationship between inequality and poverty. The conventional wisdom that poverty

causes inequality needs to be reexamined if the status effect is important. Faster growth rates do

not mean that the increment is equally shared by various income classes. Rising inequality

accentuates status effect and compels people toward status-based consumption pattern and may

adversely affect poverty in terms of nutritional measure. Social perception about status might be

related to the information about global consumption standard as projected through electronic

media. These effects must be seriously looked into.

A voluminous literature discusses the impact of social status, relative income and relative

rewards on productivity such as Hopkins and Kornienko (2010), Ku and Salmon (2009), on

optimal taxation such as Beath and Fitzroy (2010), Kanbur and Tuomala (2010) and on networks

such as Ghiglino and Goyal (2008). There is also a huge literature that has empirically examined

the relationship between relative societal position and well-being. The papers by Easterlin

[(1974), (1995) and (2001)] note that income and self-reported happiness are positively

correlated across individuals within a country. The author interprets these findings as evidence

that relative income rather than absolute income matters for well-being. Using European micro

data, Van de Stadt, Kapteyn, and Van de Geer (1985), Clark and Oswald (1996), Senik (2004),

and Ferrer-i-Carbonell (2005) find that well-being is partly driven by relative position, where

reference groups are defined by demographic characteristics. Using U. S. data, McBride (2001)

finds evidence that relative income affects subjective well-being, but they caution about the

statistical reliability of their findings. Also, the paper by Luttmer (2005) using NSFH data finds

that, controlling for an individual’s own income, higher earnings of neighbors are associated

with lower levels of self-reported happiness and that increased neighbors’ earnings have the

strongest negative effect on happiness for those who socialize more in their neighborhood.

However, these papers do not deal with the issues we are discussing in this paper.

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Status led consumption can hurt the level of intergenerational bequests and increase the

probability of a poverty trap with imperfect credit markets as demonstrated in Moav and Neeman

(2012). Status seeking behavior may impact risk-taking attitude of individuals with interesting

consequences. Such issues have been discussed by Robson (1992) and Ray and Robson (2012).

Concern for relative income status may affect the pattern of trade of a poor economy. These

have been dealt with, in Marjit and Roychowdhury (2012).

We felt the importance of introducing the concept of status in a simple utility function that can

capture the essence of the issue and then try to assess its implications. In the first phase of the

paper we precisely do that and build up a case that increasing absolute level of purchasing power

may actually decrease nutritional measure of poverty, where food effectively turns out to be an

“inferior” good if the status-concerned consumer internalizes the distributional implication of an

overall change in income. This result is generated through a direct impact of inequality on

consumption, in particular on food to non-food consumption. Then we proceed to test this

hypothesis in terms of the most widely used data set in India, the National Sample Survey

Organization data on household level consumption with the latest two rounds of data across

Indian states for the rural and urban sectors. Another motivation for using a large sample is that

in earlier works, experiments, anecdotal observations, case studies (see Luttmer (2005),

Fafchamps and Shilpi (2008), Banerjee and Duflo (2011), etc.) do point toward such behavior.

Natural question is whether large data set and wider variations accommodate such claim.

The paper is structured as follows. The second section develops a basic theoretical model, one

that explains the conflict between income and nutrition-based measures of poverty. The third

section deals with the empirical evidence on inequality and poverty using the National Sample

Survey data for Indian states and districts. The last section concludes.

III. A Theoretical Model

We start with two axioms on how perceived social inequality affects the individual welfare.

Axiom 1: Being down the societal ladder hurts.

This implies that individuals’ perception about their societal position, positively affect their

individual utilities. This prompts individuals down the societal ladder to revive some of their

societal image by engaging in the consumption of certain conspicuous “status goods” which

leads us to:

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Axiom 2: A lower relative societal position increases the value the representative individual

confers to the status good relative to the non-status good.

The above axiom is modeled as the property of the utility function where, a rise (fall) in the

perceived status of the representative individual decreases (increases) the ratio of the marginal

utility of the status good relative to the non-status good. That is if the utility U is represented by:

𝑈 = 𝑈(𝑛, 𝑠,Φ), then axiom 2 implies: 𝜕𝜕Φ�𝜕𝑈𝜕𝑠

𝜕𝑈𝜕𝑛� � > 0

or, along with the usual assumptions of positive marginal utilities associated with the

consumption of both the status and non-status goods: 𝑈𝑠Φ𝑈𝑛Φ

> 𝑈𝑠𝑈𝑛

where n denotes the consumption of the non-status good, s denotes the consumption of the status

good, Φ is a measure of the perceived status of the representative individual and the subscripts

attached to the function U denotes the partial derivatives with respect to the respective variables.

The above axiom is directly drawn from experimental psychology literature where intensity of

desire to consume the status good seems to be greater among those who are affected by social

inequality. Maximization of the utility function subject to the budget constraint:

𝑝𝑠𝑠 + 𝑛 = 𝐼 (M1)

which supposes the non-status good to be the numéraire yields the first order condition: 𝑈𝑠𝑈𝑛

= 𝑝𝑠 (M2)

where ps denotes the price of the status good and I denotes income. In order to study the impact

of axiom 2 on the consumption of the goods at optimal, we differentiate equations (M1) and

(M2) to obtain:

𝑝𝑠𝑑𝑠∗ + 𝑑𝑛∗ = 𝑑𝐼 (M3)

𝑈𝑠𝑠∗ 𝑑𝑠∗ + 𝑈𝑠𝑛∗ 𝑑𝑛∗ + 𝑈𝑠Φ∗ 𝑑Φ = 𝑝𝑠(𝑈𝑛𝑠∗ 𝑑𝑠∗ + 𝑈𝑛𝑛∗ 𝑑𝑛∗ + 𝑈𝑛Φ∗ 𝑑Φ) (M4)

using a star as a superscript to indicate quantities evaluated at the optimal. Manipulating (M3)

and (M4), we arrive at (note 𝑈𝑠𝑛∗ = 𝑈𝑛𝑠∗ ):

𝑑𝑠∗ = (𝑈𝑠𝑛∗ −𝑈𝑛𝑛∗ )𝑑𝐼+(𝑈𝑠Φ∗ −𝑈𝑛Φ

∗ 𝑝𝑠)𝑑Φ−�𝑈𝑠𝑠∗ −2𝑝𝑠𝑈𝑠𝑛∗ +𝑝𝑠2𝑈𝑛𝑛∗ �

(M5)

𝑑𝑛∗ = (𝑈𝑠𝑛∗ 𝑝𝑠−𝑈𝑠𝑠∗ )𝑑𝐼+(𝑈𝑛Φ∗ 𝑝𝑠−𝑈𝑠Φ

∗ )𝑝𝑠𝑑Φ−�𝑈𝑠𝑠∗ −2𝑝𝑠𝑈𝑠𝑛∗ +𝑝𝑠2𝑈𝑛𝑛∗ �

(M6)

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In the above equations, the denominator takes up a positive sign assuming the second order

sufficient conditions for the utility maximization problem to hold. Also axiom 2 and equation

(M2) along with positive marginal utilities of status and non-status commodities implies that the

expression: 𝑈𝑠Φ∗ − 𝑈𝑛Φ∗ 𝑝𝑠 remains strictly positive. Our assumption will be that individuals’

status perception is based on their level of incomes relative to the society’s average income level

such that being above average does not matter, but being below definitely hurts. This asymmetry

is deliberate to highlight the implications of belonging to the downside of inequality. This

implies:

Φ = Φ�𝐼𝐼�̅ �= 1 for 𝐼 ≥ 𝐼 ̅

< 1 for 𝐼 < 𝐼�̅ together with Φ′ �= 0 for 𝐼 ≥ 𝐼 ̅

> 0 for 𝐼 < 𝐼.̅

Thus from the equations (M5) and (M6) and along with the usual assumptions of diminishing

marginal utilities of both the consumables and non-negative cross partial derivatives of the utility

function, we may conclude that:

i. 𝜕𝑠∗

𝜕𝐼> 0 unambiguously and

ii. 𝜕𝑛∗

𝜕𝐼⋚ 0 according to as Φ′ ⋛ (𝑈𝑠𝑛∗ 𝑝𝑠−𝑈𝑠𝑠∗ )

(𝑈𝑠Φ∗ −𝑈𝑛Φ∗ 𝑝𝑠)𝑝𝑠.

The last relationship also implies that 𝜕𝑛∗

𝜕𝐼> 0 if Φ′ = 0 i.e. when status consciousness is absent.

It may also be noted that:

𝜕𝑈∗

𝜕𝐼=

−(𝑈𝑛∗𝑈𝑠𝑠∗ −2𝑈𝑠∗𝑈𝑠𝑛∗ +𝑈𝑠∗𝑈𝑛𝑛∗ )−�𝑈𝑠𝑠∗ −2𝑈𝑠∗

𝑈𝑛∗𝑈𝑠𝑛∗ +�𝑈𝑠

∗

𝑈𝑛∗�2𝑈𝑛𝑛∗ �𝑈Φ

∗

−�𝑈𝑠𝑠∗ −2𝑝𝑠𝑈𝑠𝑛∗ +𝑝𝑠2𝑈𝑛𝑛∗ � is unambiguously positive.

The above properties of the optimal consumption and utility thus culminates in:

Proposition 1: A growth in income may reduce consumption of non-status goods such as

food and hence nutritional intake if it is accompanied by a worsening of income

distribution. Thus non-status good will look to be an “inferior” good implying that income

based and nutritional-based measures of poverty will not match. If income distribution

remains unchanged, there will be no such conflict.

Proof: See the discussion above. Q.E.D.

IV. Empirical Analysis:

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Given the massive impact that distribution of income has on one’s perception of her status in the

society and thus her consumption decisions, it becomes vital at this stage to see the impact of

such perceptions on one’s decision making process, empirically. As the theory has already

established that status concerns have an adverse effect on the nutritional state of the people, even

in the face of rising incomes, here we exemplify the existence of such a phenomenon

empirically. For our purpose, we take up India, as a prospective candidate and look for the

prevalence of status, affecting the relative consumptions of commodities.

In India, it is often observed that higher levels of overall consumption expenditure (which is

approximated as a proxy for income levels) among the poor do not imply higher nutritional

intake which is quiet contrary to general perception. To present some anecdotal evidences along

these lines, we consider the degree of poverty (measured by percentage of population lying

below the poverty line) and child malnourishment (measured by percentage of children suffering

from malnourishment) for the states of India. Figure F1 plots those two variables against the

states’ per capita gross state domestic product (taken in log). From the figure, we can clearly

appreciate that although with a rise in the gross state domestic product (hereafter referred to as

GSDP) as a proportion of total population there is an appreciable decline in poverty, no such

trends is observed for child malnourishment. For example states like Andhra Pradesh, Gujrat,

Haryana, Himachal Pradesh, Karnataka, Punjab and Tamil Nadu although having a respectable

amount of per capita GSDP, still register a high degree of child malnutrition compared to the

states having relatively lower amount of per capita GSDP like Chhattisgarh, Jharkhand, Madhya

Pradesh, Orissa and Rajasthan, Uttar Pradesh and West Bengal. But if we consider poverty, we

can see that changes in poverty figures of the states are more amenable to the respective per

capita GSDP figures.

Insert Figure F1 about here

World Bank Data reveals, in the past decade, India has seen high annual growth rates from about

4 percent to an average of 8 percent peaking to about 10 percent in 2011. Also the poverty levels

(according to World Bank data) have reduced over years. But the nutritional status of many

states of the country does not show respectable levels of improvement. Svedberg (2008) found

that between 1993 and 2006, net state domestic product per capita grew by about 4.5% per year

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on an average, nearly a doubling of real income, while the prevalence of child stunting and

underweight reduced by a meagre 23 percent to 12 percent over the past 13 years. Whereas in

China, child stunting fell from 33 to 10 percent during 1992-2005 and child underweight was

practically eliminated. Also prevalence of under nutrition in adult women in 2005-2006 was

33%, down only by 3 percentage points from 36 percent in 1998-19991. All these facts and

figures indicate that not only does one may obtain different conclusions if one takes a nutrition

based approach of poverty, rather than an income based approach but in addition, changes in per

capita GSDP which may result from certain policy prescriptions may have different impacts as

judged by these two measures of poverty.

One possible candidate that can generate such a non-trivial observation, have been attributed in

our paper to the persistence of status effect (the inherent tendency to consume status goods rather

than nutritious goods to conform to societal status) prevailing among the population which

interacts with the income effect and determines the overall relative consumption patterns and

might be important from the view point of formulating economic policies. In many middle

income countries it has been observed that as the income levels of the people rises, with a rise in

income inequality, the low income people try to mimic the consumption pattern of higher income

class, thereby bringing a shift in their expenditure structure toward luxury goods and thus

affecting their nutritional status. This would imply another aspect of income inequality – that

income inequality distorts consumption and expenditure patterns among the poor. In accordance

with the theory developed so far, we consider a situation where the poor people are concerned

about their relative social status. In a society with unequal distribution of income, to keep up with

the standards of the high income class, low income people try to spend more on luxury goods so

as to retain their relative status. In other words, income inequality in a society has an impact on

the tendency to retain relative social status among the poor. This can be quantified by the

spending on non-food luxury items in comparison to food items. In the ensuing sections we

develop an empirical model to validate the widespread prevalence of status consciousness in the

Indian society.

V. Data and Methodology

1International Institute of Population Sciences, Research Brief, No. 2, (2007).

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The entire empirical analysis is entirely based on the extensive datasets provided by the National

Sample Survey Organization of India viz. the NSS 66th and 68th round all India unit level

survey on consumption expenditure (Schedule1.0, Type 1 and 2). For both these rounds of NSSO

data, the first stage sampling unit (hereafter referred to as FSU) is the 2001 census village for

rural India and Urban Frame Survey blocks for urban India. For the urban sector, the Urban

Frame Survey blocks are formed from towns/cities which are divided into aerial compact blocks

with clear cut identifiable boundaries and permanent land marks. The ultimate stage units are the

households and the datasets comprise of observations on various characteristics specific to the

households and the individuals belonging to the households. Apart from this, data is also

provided on the households’ localization, such as the sector (Rural or Urban), district and state.

The total number of household level observations in our analysis is 201649 for the 66th round

and 203313 observations for the 68th round. The data spans thirty five states and union territories

(henceforth, the union territories will be referred to as states). The total number of districts in our

analysis is 612 for the 66th round and 625 for the 68th round.

Tables 1a and 1b summarize some of the key statistics related to the principal variables of our

analysis namely the monthly per capita total expenditure and the monthly per capita expenditures

on food commodities. Information is also provided for some subsidiary variables which are of

interest such as the household size, the number of females in the household, the total land

possessed and the amount of land cultivated by the household and the median age of the

household. The statistics are reported for both the rounds and are categorized according to rural

and urban sectors of the individual states as well as for the country as a whole.

In addition to the variables provided in the surveys, we construct a suitable inflator to account for

the effect of price variations across the different administrative and economic agglomerations.

More specifically, for each round, we calculate a state-district-sector specific price index that

measures the amount of expenditure that is required to be made by a household living in that

particular state, district and sector to attain the all-India median level of consumption of each of

the essential non-durables2.

As discussed in the introduction, we are chiefly concerned with the impact of status on the food

expenditures of the relatively poor people of the society and thus, we first identify the ‘poor’

2 These constitutes the various food items, energy (for household use), clothing and bedding.

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households. For our purpose, a household is defined to be “poor” if the monthly per-capita

consumption expenditure of the household (which serves as a proxy to the respective

household’s per capita income) falls short of the median monthly per-capita consumption

expenditure of the particular FSU in which the household is located. This particular way of

defining the poor households assumes the FSU specific per capita consumption expenditure level

as our FSU specific poverty line. Note that this measure is able to account for the differences in

the living standards across the different socio-economic agglomerations of the country as far as

the data allows us to do so.

To motivate our empirical model, we present some preliminary observations from the data. For

the same, we restrict our attention to those poor households belonging to a particular sector

(rural/urban) whose monthly per-capita consumption expenditures, suitably deflated by the

constructed price index, lie within a range of 10 percent above or below the Indian lowest

quintile (i.e., 25th percentile) monthly per-capita consumption expenditure for that sector. Note

that the deflated lowest quintile monthly per-capita consumption expenditure for rural Indian is

Rs. 491 and Rs. 693 for 66th and 68th rounds respectively while the same for urban Indian is

respectively Rs. 780 and Rs. 1069. Restricting ourselves to these households, we compute their

FSU specific median food expenditure share and compare it against the respective FSU’s highest

quintile (i.e., 75th percentile) deflated per capita consumption expenditure. We do this exercise

separately for both the NSSO rounds. The plots from this exercise for both rounds of data are

depicted in figure – F2. We find that each of the scatterplots depicts a negative relationship

between the FSU’s median food expenditure ratios of the selected households and the FSU’s

highest quintile per capita consumption expenditure irrespective of the sector and the rounds. To

illustrate this clearly, we have superimposed a linear trend line to each of the scatterplots. The

idea behind this exercise is that, if status consciousness is prevalent among the poor households

then it would imply that these households living in a relatively affluent locality should spend

relatively less on food items compared to those living in a relatively poor locality even if they

have the same level of total expenditure. Thus the plots depicted, are in line with our conjecture

and bears out the fact that relatively poor individuals belonging to a particular class of income

(here proxied by total consumption expenditure), do tend to “mend their self” by revising their

consumption patterns in a way that mimics the consumption patterns of the relatively richer

sections in their societies.

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Insert Figure: F2 about here

With this initial result in hand, we move on develop a detailed and robust statistical framework

in the subsequent paragraphs to study the nature and significance of the role of status in shaping

individuals’ food consumption patterns.

For our formal empirical model, we need to identify a variable that quantifies the influences that

promotes the status responsiveness of the poor households. In order to do so, we take up each

FSU and define the logarithm of the FSU’s highest quintile (i.e., 75th percentile) per capita

consumption expenditure as the status variable of all the prospective households belonging to

that particular FSU. The status variable constructed thus has the advantage that it makes our

analysis robust to specification biases. This follows since the manner in which the status variable

of a household is defined makes it irresponsive to the household’s income up to a certain extent

thus guarantying that this variable truly represents the households’ responsiveness to its societal

position rather than capturing certain nonlinearity of the households’ income.

To test for the presence of status concern among the poor households, we look at the statistical

significance of the association of the status variable with the expenditure share of food while

allowing for the influences of total expenditure and a host of other covariates. For our underlying

empirical model, we assume that the expenditure share of food is related to the relevant

explanatory variables according to the relationship:

𝑆 = 𝐹1(𝑝) + 𝐹2(𝑀) + 𝐹3(𝐷) + 𝐹4(𝑍) + 𝜀

In the above relation, S represents the total share of expenditure on food, p denotes the vector of

prices of the consumables, 𝐹𝑖(∙)∀𝑖 = 1 to 4 are arbitrary functions, M, D denote income and the

status variable respectively, Z represents a vector of other control variables and 𝜀 represents the

statistical error component. We estimate the above relationship with some additional structure

particularly on the functional forms of 𝐹𝑖(∙)′𝑠 as well as on the error term. Since we are

essentially estimating an Engel relationship, we take up the functional form suggested by Lesser

(1963) (a rank three model) and estimate the relationship:

ln 𝑆𝑖𝑗𝑘𝑙 = 𝛼 + 𝛽 ln𝑀𝑖𝑗𝑘𝑙 + 𝛾 1𝑀𝑖𝑗𝑘𝑙

+ 𝜃𝐷𝑖𝑗𝑘 + 𝜋𝑍𝑖𝑗𝑘𝑙ℎ + 𝜌𝑍𝑖𝑗𝑠𝑠𝑑 + 𝜀𝑖𝑗𝑘𝑙 … (E1)

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where 𝜀𝑖𝑗𝑘𝑙~𝑁�0,𝜎𝑖𝑗2� , the subscript ‘i’ indexes the possible combinations of states and sector,

‘j’ indexes the districts, ‘k’ indexes the FSU’s belonging to the particular combination of state,

district and sector and ‘l’ indexes the households belonging to the region identified by the indices

‘ijk’. Note that in the above relationship, we have partitioned the vector of control variables Z

into a vector of household specific variates Zh and a vector of variates specific to the respective

state sector and district Zssd (and hence the form of the subscripts associated with these

variables). For the household specific controls, we incorporate a number of household

characteristics that comprises of the household size (in logs), the maximum level of education3,

the median age, the squared median age, the number of females (in logs), the principal

occupation class and indicators for the social group4. On the other hand, for the state-sector-

district specific controls, we consider the price index (construction is detailed earlier), the overall

per-capita consumption expenditure (in logs), the total amount of land cultivated (in logs) and

the fraction of the population who are skilled5 for the corresponding combination of state, sector

and district. These later controls serve as the broad indicators of the cost of living, development

and factor abundance of the respective state sector and district. We also generalize the above

model and allow for the status variable to incorporate the large amount of cultural and social

diversity of the country. We thus investigate an alternative formulation of equation (E1) given

by:

ln 𝑆𝑖𝑗𝑘𝑙 = 𝛼 + 𝛽 ln𝑀𝑖𝑗𝑘𝑙 + 𝛾 1𝑀𝑖𝑗𝑘𝑙

+ 𝜃𝑖𝐷𝑖𝑗𝑘 + 𝜋𝑍𝑖𝑗ℎ + 𝜌𝑍𝑖𝑗𝑘𝑙𝑠𝑠𝑑 + 𝜀𝑖𝑗𝑘𝑙 … (E2)

Note that in the above equation, the coefficients associated with the status variable are allowed to

vary across the states and sectors and thus it differs from the previous specification. The above

systems are estimated using least squares techniques and the results of this empirical exercises

are elucidated next.

VI. Results and Discussion

3 The general educational level of an individual is indicated by numbers where, not literate: 0, literate without

formal schooling: 1, literate with formal schooling below primary: 2, primary: 3, middle: 4, secondary: 5, higher

secondary: 6, diploma/certificate course: 7, graduate: 8, postgraduate and above: 9. 4 The social groups are: Scheduled Tribes: 1, Scheduled Castes: 2, Other Backward Classes: 3 and the rest: 9. 5 Skilled individuals are defined as those who have received at least secondary level of education.

12

If poor people are indeed concerned about their relative standing in the society then it must get

reflected in our empirical exercise as a significant 𝜃/𝜃𝑖: the coefficient associated with the log of

the variable indicating status effect. If 𝜃/𝜃𝑖 is significantly negative, it indicates that overall or

for the particular state and sector indexed by ‘i’, a rise in income inequality coerces the

individuals who are relatively poor, to consume food commodities in relatively lesser quantities

compared to other non-food items.

The results for the model estimated for the NSSO 66th round data reveals that overall, for the

whole country, status effect among the poor (i.e. 𝜃) significantly lowers their relative food

consumption [Refer Table: 2a] and this results continue to hold good even if we allow the status

variable to vary across the states and sectors [Refer Table: 2b]. When the status variable is

allowed to vary across the states and sectors, we can see that the coefficients assume negative

values for all the combinations of states and sectors and are significant for almost all these states

and sectors except for rural Andaman and Nicobar Islands, rural Lakshadweep, and rural Assam

[Refer Table: 2b]. The results for the NSSO 68th round does not vary much in terms of the sign

and the significance of the coefficients associated with the status variable. Thus yet again, we

find that overall, for India, the coefficient of the status variable (i.e. 𝜃) is negative and significant

[Refer Table: 3a] whereas when the status variable is allowed to vary across the states and

sectors, the coefficients assume negative values for all the combinations of states and sectors and

are significant for almost all these states and sectors except for rural Lakshadweep for which the

status coefficient assumes an insignificant positive value [Refer Table: 3b].

The literature on the empirical testing of status consciousness voices some concerns about the

estimation of models as depicted by equations E1 and E2. Firstly there is the intuitive problem

that since the various components of total expenditure are jointly determined by a household, the

total expenditure is likely to be endogenous for the model discussed above. Secondly, there is

also the common statistical concern that the measurement errors in the components of total

consumption, of which food items is one, is related to the measurement error in total

expenditures. Given these concerns, we re-estimate our generalized model (i.e. equation E2) and

instrument for the log of total expenditure using the total land possessed by the respective

households, taken in logarithms. We report the results of the hypothesis test that whether the

suspect endogenous regressor: total expenditure, can be treated as exogenous. We also test for

any “weak instrument” concerns associated with the suggested instrument. The results from both

13

of these exercises [Refer Table – 4] reveal that both of the concerns discussed above are not

relevant for our problem and guarantees the continued validity of the results forwarded in the

previous tables.

If we summarize the results obtained from the above regressions, we show that the coefficient of

log status is indeed negative and significant for the country as a whole and even for almost all the

states and sectors. This empirically affirms our assumption regarding individuals’ status

consciousness and its impact on the individuals’ consumption of certain “non-status” goods

particularly food.

VIII. Conclusion

In this paper we wanted to focus on the impact of relative status on the consumption behaviour

of the poor who might feel relatively deprived in a society with highly unequal income

distribution. We have demonstrated that concern for social status in a situation where a rise

individual income is also accompanied by a worsening of income distribution, people may spend

less on food and more on status good. Thus income based and nutrition-based measures of

poverty will give qualitatively different result and income growth will be consistent with

malnutrition. After theoretical demonstration we test our results in terms of the NSSO 66th and

68th round datasets across Indian states and estimation through various methodologies strongly

corroborate our claim. In many states we cannot rule out the negative impact of inequality, which

is the key force behind the concern for status, on relative consumption of food. Future work will

try to explore the implication of such concern for status on health, education and gender related

issues.

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17

Figure: F1 A comparison of poverty and child malnourishment in the Indian states with per-capita gross

state domestic product.

Source: Per Capita GSDP for the year 2011-12 is obtained from the Ministry of Statistics and

Programme Implementation, Government of India, poverty percentage is obtained from the press note on poverty estimates, 2011-12 by Planning Commission, Government of India, child malnourishment percentage figures is obtained from the Ministry of Health and Family Welfare, Government of India.

Figure: E2 Status effect: some preliminary observation from the data

Source: Based on authors’ calculations from data.

Table 1a: Descriptive statistics of important variables for the 66th round.

Monthly per-capita consumption expenditure Monthly per-capita food expenditure Household size Number

of females

Land possessed in hectares Land cultivated in hectares Median age

State Sector Mean Median SD Min Max Mean Median SD Min Max Mean Max Mean Mean Median SD Max Mean Median SD Max Mean Median SD Jammu & Kashmir Rural 1362.3896 1203.6145 693.0399 322.6367 1.65e+04 732.9030 658.6000 298.9507 204.8750 3845.9045 5.2955 25.0000 2.5598 0.5343 0.4000 0.5304 6.0000 0.4876 0.3540 0.4875 9.0000 25.7959 24.0000 12.5438 Jammu & Kashmir Urban 2302.1224 1874.2196 1817.3171 452.1689 3.08e+04 895.3167 793.7500 424.4530 239.0000 7730.0000 4.7952 16.0000 2.2960 0.1389 0.0200 0.3140 3.0360 0.4281 0.2750 0.5619 7.0000 28.7357 27.0000 11.8903

Himachal Pradesh Rural 1680.2692 1352.7319 1263.9772 284.3021 2.67e+04 810.1229 700.9429 427.0145 168.1667 7038.7144 4.3963 19.0000 2.2256 0.5514 0.3200 1.1113 74.4000 0.3921 0.2600 0.4579 7.2870 31.1001 28.0000 14.8790

Himachal Pradesh Urban 3424.8008 2767.9480 3599.8169 424.8000 6.46e+04 1218.7541 1058.9524 854.5211 194.6000 9869.2861 3.3983 18.0000 1.6607 0.1256 0.0070 0.4625 8.0000 0.4937 0.2120 0.9791 8.0000 29.1890 26.5000 13.1129

Punjab Rural 1751.4918 1395.9673 1555.8492 284.5531 3.32e+04 803.8595 704.8979 372.0106 202.8750 7170.3999 4.8675 21.0000 2.2960 0.7957 0.0150 2.1451 101.1750 2.5117 1.6180 3.1936 97.5330 28.6769 25.5000 13.8761

Punjab Urban 2688.5316 2113.3835 2071.3220 302.6370 1.92e+04 966.3746 840.0000 516.0335 211.0000 6921.4287 4.2783 24.0000 1.9519 0.1463 0.0070 0.9098 20.4350 2.7536 2.0200 2.5997 12.1410 29.5602 27.5000 13.0577

Chandigarh Rural 2691.7606 2162.4858 1533.1864 745.2485 8755.7295 1037.5412 897.2500 457.9251 361.2000 2803.8572 2.9078 12.0000 1.0219 0.0917 0.0050 0.4262 4.6470 0.9843 0.4040 1.3402 4.3470 24.1719 25.0000 9.2927

Chandigarh Urban 5284.2473 4183.0674 4390.1795 473.9076 3.06e+04 1506.1749 1175.0000 1126.8482 270.7500 1.22e+04 3.3063 11.0000 1.5293 0.2022 0.0040 0.8392 8.1440 3.3647 2.8320 2.4159 8.0940 29.7663 26.0000 13.8947

Uttaranchal Rural 3355.4430 1296.2275 3988.3262 301.1693 1.34e+04 1132.2190 698.7143 909.7914 198.5000 4765.5000 3.8234 27.0000 1.7815 0.3625 0.1600 0.7825 25.2300 0.4409 0.2200 0.8670 25.2000 26.6682 22.0000 14.5746

Uttaranchal Urban 2407.3700 1933.9315 1597.4983 337.8755 1.61e+04 877.2340 779.0000 430.8543 150.0000 4050.1428 4.5352 19.0000 2.1291 0.0338 0.0060 0.2089 6.0040 0.3549 0.0600 0.7799 5.8000 26.4137 24.0000 12.8593

Haryana Rural 1543.3842 1302.0724 940.2314 301.7363 1.66e+04 801.4947 730.2321 425.4056 149.3214 8611.3926 5.1190 30.0000 2.4196 0.9124 0.0210 2.1514 51.8930 2.1120 1.4000 2.8900 48.0000 25.3185 23.0000 12.6420

Haryana Urban 2935.5979 2018.4374 2896.2793 366.1866 2.87e+04 996.0188 855.5714 628.5407 190.4000 6414.5718 4.4303 21.0000 2.0994 0.1659 0.0080 1.0709 26.4060 2.5169 1.2140 3.6922 26.4000 26.5026 24.0000 12.5132

Delhi Rural 2181.3442 2076.3149 1205.3392 727.2192 7625.2310 1166.0629 984.6667 840.7632 362.8000 5644.2856 2.7595 12.0000 1.0785 0.0064 0.0010 0.0130 0.4000 0.0167 0.0160 0.0090 0.0260 26.9983 24.0000 11.7147

Delhi Urban 3746.3057 2760.2876 2972.3198 456.8853 2.50e+04 1154.6985 1046.1428 613.7545 200.6250 8993.0000 3.6840 15.0000 1.5711 0.0046 0.0020 0.0323 2.0000 0.2187 0.0000 0.4825 1.5000 26.9702 25.0000 11.7670

Rajasthan Rural 1196.3873 1024.8611 957.7786 242.1204 1.98e+04 639.3392 578.1905 384.8109 119.6429 1.35e+04 5.2769 30.0000 2.5327 1.7931 0.8750 2.8154 60.0000 2.1763 1.2500 2.7081 50.6000 23.9295 21.0000 13.5006

Rajasthan Urban 2298.9792 1759.4071 1808.8947 340.6082 2.13e+04 854.3326 736.3333 517.6811 163.8333 1.06e+04 4.9027 33.0000 2.3791 0.3178 0.0040 2.1057 50.6570 2.7972 1.0000 4.0063 25.3000 25.4454 23.0000 12.7460

Uttar Pradesh Rural 939.2199 805.0366 575.3915 159.7123 2.21e+04 526.5634 467.1714 294.6266 42.8571 1.43e+04 5.5268 34.0000 2.7081 0.6387 0.2880 1.0568 40.6000 0.8454 0.5020 1.1254 40.4700 24.0035 20.0000 14.6866

Uttar Pradesh Urban 2545.0870 1534.6810 3161.2037 285.2466 2.26e+04 838.0306 638.2500 637.0249 136.6667 1.29e+04 4.8910 23.0000 2.3138 0.1400 0.0080 0.7863 20.5080 1.0601 0.5060 2.0915 20.5000 25.2321 23.0000 12.5332

Bihar Rural 797.2713 712.7292 371.0808 154.5744 9659.1729 495.0195 453.2727 212.5169 110.4000 3007.5000 5.2175 21.0000 2.4479 0.4129 0.0400 0.9287 25.1650 0.7271 0.4000 1.0625 25.0090 22.1022 19.0000 13.1656

Bihar Urban 1602.3617 1257.4961 1183.4919 158.2123 1.12e+04 699.3577 579.3214 404.7920 98.6667 3985.0000 4.7972 22.0000 2.2720 0.1583 0.0120 0.6003 11.2150 0.7780 0.4050 1.1225 10.0360 23.7990 21.0000 12.2737

Sikkim Rural 1609.1404 1165.5206 1440.5055 425.1308 1.82e+04 789.4375 635.8333 613.3556 267.6286 1.71e+04 4.0023 12.0000 1.9207 0.3983 0.2800 0.4868 6.2000 0.4156 0.3500 0.4126 6.1800 26.1632 24.5000 10.9527

Sikkim Urban 2741.3477 2384.8425 1691.1751 576.5753 1.81e+04 1182.3274 1015.2500 574.5399 393.6000 2950.0000 3.2394 16.0000 1.4954 0.0136 0.0030 0.0594 0.5030 0.0016 0.0000 0.0218 0.3000 27.8586 26.0000 11.0466 Arunachal Pradesh Rural 1591.3043 1231.4110 1134.7652 297.7973 1.18e+04 860.5166 678.9286 640.9535 173.0000 8471.5361 4.9239 16.0000 2.3243 2.8821 2.0000 4.8251 100.0000 1.8109 1.2000 2.8454 90.0000 24.0524 22.0000 11.5498 Arunachal Pradesh Urban 2001.2649 1649.8484 1374.5476 228.3105 1.51e+04 946.8739 793.1429 631.6078 134.0000 7208.4287 4.0811 15.0000 1.8690 0.7851 0.2000 2.0018 40.0000 1.0359 0.5000 1.8964 16.1880 23.2532 21.5000 10.1729

Nagaland Rural 1491.4782 1357.0593 601.8869 592.1592 7612.2876 826.0288 771.2571 281.5772 397.5714 6000.0000 5.1008 9.0000 2.5302 1.7188 1.2000 1.7124 15.5000 0.9416 0.8000 0.9479 9.0000 22.9739 20.5000 9.9184

Nagaland Urban 2148.8579 1930.9484 1054.1023 781.6130 1.32e+04 904.8238 801.7143 384.8495 353.8571 2828.5715 4.7535 9.0000 2.3221 1.0254 0.8000 1.1390 12.0000 0.4354 0.2000 0.6710 5.0000 23.0755 21.0000 10.1303

Manipur Rural 1011.9581 937.2466 361.0962 436.6446 6081.1372 589.3497 560.1667 160.9309 233.0000 2124.7144 5.1784 15.0000 2.4938 0.6880 0.5620 0.8678 52.0000 0.7526 0.6000 0.7031 9.0600 25.1094 24.0000 10.8292

Manipur Urban 1404.2124 1183.9049 750.9621 520.0106 1.21e+04 609.9689 552.2500 328.3592 231.1250 1.16e+04 4.8517 28.0000 2.3924 0.2765 0.0600 0.4101 3.3640 0.4355 0.4040 0.4207 3.0000 25.4050 25.0000 10.9265

Mizoram Rural 1239.6161 1110.1119 567.3801 394.6931 5785.7104 706.4235 655.0476 288.2805 219.2500 2933.2856 4.8596 14.0000 2.3565 0.6694 0.6070 0.5756 8.1170 0.6288 0.6000 0.4092 4.0460 24.7096 22.5000 12.3234

Mizoram Urban 2229.5775 2048.2212 1068.3173 470.2082 1.32e+04 972.7754 898.0000 437.1347 174.2000 4120.3335 4.9818 13.0000 2.4789 0.3183 0.0150 0.6466 8.0100 0.7744 0.6070 0.8006 8.0000 25.2613 23.5000 11.1488

Tripura Rural 1132.3449 1021.0206 526.6854 340.9139 7181.1094 700.9773 638.0000 281.0407 192.4000 3379.7144 4.2375 15.0000 2.0627 0.3360 0.1240 0.5139 14.4000 0.4704 0.4800 0.3460 10.4000 28.1819 25.5000 12.5980

Tripura Urban 2205.5321 1841.2936 1473.5148 409.1507 1.13e+04 997.2024 895.6428 486.9140 182.5000 3817.7144 3.5570 15.0000 1.7674 0.0520 0.0180 0.1422 3.0000 0.2773 0.1650 0.4376 2.9520 32.0696 29.5000 12.8008

Meghalaya Rural 1121.6950 998.6693 470.5018 392.1811 7131.5356 606.5406 545.0357 233.6059 201.0000 3713.1428 5.1010 14.0000 2.5694 0.5597 0.1440 1.1572 20.2350 0.5864 0.2200 0.9731 17.5350 21.7256 20.5000 10.2969

Meghalaya Urban 1980.2963 1716.8995 1112.0813 498.8995 1.25e+04 744.4296 654.4000 332.0241 235.0357 4031.0000 4.7038 16.0000 2.4101 0.0687 0.0130 0.2820 4.0000 0.2271 0.0480 0.3881 3.0800 23.3802 21.0000 10.4236

Assam Rural 975.4923 862.5362 461.7016 309.9486 7842.8101 625.0082 574.4081 254.3916 154.2500 3103.6785 5.1071 16.0000 2.4289 0.9917 0.6920 1.1577 30.0000 1.1240 0.8750 0.9895 28.7000 24.5381 24.0000 10.3470

Assam Urban 2140.4827 1790.3069 1485.0025 391.9699 3.50e+04 954.9719 822.0000 510.6677 200.0000 3387.0000 4.1754 13.0000 1.9126 0.1407 0.0270 0.4693 11.9080 0.5923 0.1600 0.9614 11.7740 27.6135 26.0000 11.0185

West Bengal Rural 962.1634 859.2707 509.6894 232.0959 2.62e+04 581.8862 534.9429 266.6622 105.4000 1.27e+04 1.0000 22.0000 14.0000 0.1858 0.0260 0.0000 10.7040 0.3578 0.2000 0.0000 19.0000 28.1428 25.5000 94.0000

West Bengal Urban 2562.6131 1806.6849 2501.5267 108.2818 3.21e+04 925.5439 784.5000 578.9654 74.3571 1.36e+04 1.0000 19.0000 10.0000 0.0284 0.0100 0.0000 2.7800 0.1191 0.0000 0.0000 2.5600 34.0784 32.0000 93.0000

Jharkhand Rural 821.4512 721.1924 373.1480 182.4384 1.13e+04 485.4108 436.7500 211.7506 106.8571 2900.7856 4.8609 19.0000 2.2952 0.5687 0.2480 1.3392 60.7050 0.5746 0.4000 0.8565 20.2350 23.9136 21.5000 12.7444

Jharkhand Urban 1915.0998 1440.0822 1610.7068 277.0255 1.45e+04 831.4848 675.8095 554.7258 154.7143 7021.5713 4.6987 21.0000 2.1926 0.0896 0.0070 0.5248 10.0060 0.1958 0.0520 0.3266 3.0000 25.4493 23.5000 11.8868

Orissa Rural 821.7712 699.6678 497.5350 87.5616 2.41e+04 494.6487 432.1429 280.0689 20.0000 3440.0476 4.2504 21.0000 2.0961 0.6133 0.3200 0.8798 13.0000 0.8350 0.6080 0.8875 12.8500 28.7500 26.0000 14.2342

Orissa Urban 2062.4503 1497.7916 1992.3824 271.0455 2.10e+04 803.5914 666.2857 527.2601 31.4000 4951.0000 4.0077 17.0000 1.9660 0.1640 0.0090 0.5485 13.7860 0.6616 0.4040 1.0054 10.0000 28.3587 26.5000 11.7576

Chhattisgarh Rural 786.3967 670.6986 442.2205 151.4286 5970.5400 431.3263 389.6000 219.3563 20.0000 2849.1428 4.5679 24.0000 2.2286 1.0049 0.8090 1.2942 20.8140 1.2092 0.8090 1.3183 22.0000 26.5456 24.0000 13.6934

Chhattisgarh Urban 1951.6392 1550.7704 1523.9112 207.1918 2.19e+04 702.2330 641.3143 377.8328 65.7500 7350.0000 4.6884 21.0000 2.2768 0.1432 0.0060 0.7966 20.0000 1.9403 1.4160 2.4370 19.4100 27.0202 25.5000 12.5319

Madhya Pradesh Rural 917.3286 755.8699 621.6084 165.3892 1.95e+04 491.8507 423.0286 290.2208 59.3333 3336.0000 4.8256 29.0000 2.2878 1.4739 0.8090 2.3157 80.8500 1.9419 1.2140 2.3464 50.4900 25.3631 22.0000 14.1598

Madhya Pradesh Urban 2299.1804 1593.4064 2170.4445 305.4521 2.33e+04 747.9272 617.9841 511.8811 129.6000 9047.1426 4.6433 24.0000 2.1862 0.3479 0.0050 1.8549 40.4900 1.4763 0.0000 3.6458 40.4700 26.7515 24.0000 13.0314

Gujarat Rural 1178.1724 1003.9612 909.0963 273.5993 4.08e+04 643.5385 583.5000 263.8387 159.7500 2647.0000 4.9837 23.0000 2.4076 0.9505 0.2410 1.9356 36.0120 1.5918 0.9200 2.1952 36.0000 28.0804 25.0000 14.4567

Gujarat Urban 2685.5598 2129.6172 2147.5203 340.5320 3.24e+04 928.3275 851.3333 481.6480 118.0000 7152.7500 4.3957 17.0000 2.0368 0.1633 0.0040 0.8622 16.0200 1.9519 1.1450 2.4135 16.0000 29.8069 27.0000 13.6047

Daman & Diu Rural 1774.6891 1665.1541 862.2904 413.1678 7396.4473 806.1663 814.9286 292.0942 214.8750 2128.6667 4.5263 12.0000 2.2153 0.0911 0.0040 0.3364 4.0000 1.3192 0.4500 2.5961 9.5500 28.4332 29.0000 6.9464

Daman & Diu Urban 2561.3653 1913.1370 1620.9765 730.1849 9243.1934 928.5345 792.5000 441.5240 313.8571 2730.7144 4.7516 24.0000 2.3772 0.2616 0.0050 0.8737 4.0470 2.8586 2.7500 1.0463 4.0000 27.9735 28.0000 10.2606

D & N Haveli Rural 934.8202 768.7531 470.8660 410.3151 3032.9119 579.8487 534.1667 218.1349 228.3333 1707.2856 5.8502 13.0000 2.8463 0.5070 0.0610 0.6389 3.0040 1.1352 1.1330 0.3971 2.8330 20.4701 17.0000 11.5832

D & N Haveli Urban 2156.6404 1819.9257 1236.5166 783.9095 8155.1997 865.6344 780.6285 344.8528 422.5000 2368.5000 4.4560 15.0000 1.8961 0.0387 0.0080 0.0886 0.8420 0.3692 0.4000 0.1216 0.7500 22.0712 23.0000 9.4810

Maharashtra Rural 1173.6228 1040.1403 663.9337 95.5890 2.93e+04 612.5145 566.1786 273.3141 92.9643 1.26e+04 4.5047 33.0000 2.1994 0.9895 0.2090 2.0645 121.4160 1.5946 1.0000 2.3595 121.4100 30.1330 26.5000 15.5760

Maharashtra Urban 3655.8211 2347.9993 4454.1023 268.0240 8.93e+04 1063.7189 884.5000 665.3053 160.3750 8101.7144 4.1594 33.0000 1.9679 0.1388 0.0020 0.9232 24.3140 1.4409 0.5260 2.4720 24.2820 29.7420 27.0000 12.8223

Andhra Pradesh Rural 1316.3192 1046.5068 1065.8675 42.1507 2.71e+04 725.2746 602.1429 487.5470 8.0000 5677.1431 3.6857 30.0000 1.8226 0.5289 0.0160 1.1554 80.3530 1.2201 0.8090 1.4465 23.8770 31.1634 27.0000 15.6216

Andhra Pradesh Urban 2765.1931 2066.7837 2364.0831 287.1233 2.75e+04 1054.0457 846.6786 877.8003 30.0000 1.77e+04 3.5931 19.0000 1.7614 0.0807 0.0050 0.4256 8.0940 1.2392 0.9000 1.2783 8.0940 29.1065 26.0000 13.6188

Karnataka Rural 1017.5907 874.0068 568.3782 275.2913 9250.5381 559.8203 502.7857 250.7264 124.1333 4129.5000 4.4515 35.0000 2.2461 0.8044 0.1610 1.5792 60.7050 1.3493 0.8090 1.8084 60.6050 30.0455 27.5000 13.3844

Karnataka Urban 2864.2363 2121.6958 2843.9239 298.9589 4.55e+04 948.4206 824.2449 533.5428 15.0000 5991.4282 3.8694 20.0000 1.8672 0.1654 0.0060 1.3720 60.7050 0.6541 0.0000 2.5995 50.0000 29.3492 26.0000 13.1253

Goa Rural 2029.3129 1817.7313 958.2671 657.2945 1.80e+04 1036.2843 960.6667 409.1132 373.8571 3934.0000 4.4257 14.0000 2.1608 0.3532 0.0310 0.7204 8.1000 0.4744 0.2300 0.8347 8.0940 31.6270 28.0000 14.2029

Goa Urban 3452.8100 2914.9932 2027.3963 598.6370 1.59e+04 1194.9146 1049.3334 654.9139 292.7857 5962.5000 4.0535 15.0000 2.0552 0.0862 0.0090 0.8832 15.0090 0.3423 0.0000 1.9087 15.0000 32.3748 30.0000 13.7464

Lakshadweep Rural 2209.2076 1673.5526 1985.0220 612.6787 1.64e+04 1154.9788 958.1429 602.0364 399.4667 3458.5713 5.1633 15.0000 2.6600 0.0394 0.0250 0.0468 0.3310 0.0219 0.0150 0.0234 0.1010 29.3355 26.0000 14.7804

Lakshadweep Urban 2998.6173 2413.1462 1849.0722 671.7417 1.46e+04 1352.9410 1140.0000 696.0636 363.8095 4500.0000 5.4787 20.0000 2.9006 0.0615 0.0400 0.0769 0.4600 0.0706 0.0400 0.0758 0.4400 27.2929 27.0000 11.0429

Kerala Rural 2035.6700 1520.7261 2086.2458 156.7397 8.30e+04 862.0216 732.3571 571.2995 55.0000 1.26e+04 4.0546 15.0000 2.1284 0.2217 0.0600 0.6724 40.4700 0.2543 0.0640 0.7140 32.3760 34.0968 31.5000 14.9306

Kerala Urban 3328.5001 2366.4912 4062.3144 217.4794 1.86e+05 1036.2137 868.4286 798.5854 30.0000 1.00e+04 3.9526 24.0000 2.0585 0.0835 0.0280 0.2796 6.4800 0.1106 0.0200 0.3786 6.0710 34.7461 32.0000 14.5396

Tamil Nadu Rural 1187.5031 983.9374 860.1510 12.7740 1.47e+04 614.5293 552.7500 305.3833 38.0000 4506.3335 3.6414 15.0000 1.8206 0.2444 0.0120 0.6622 44.8000 0.7143 0.4070 0.9061 41.3000 33.5969 30.0000 16.0262

Tamil Nadu Urban 2347.0638 1818.4110 1853.4659 323.2479 3.77e+04 881.7344 754.2857 508.3953 40.0000 6771.4287 3.4684 15.0000 1.7297 0.0686 0.0060 0.3804 27.2200 0.5086 0.2000 0.9740 27.2100 32.8148 29.0000 14.8037

Pondicherry Rural 1697.4281 1477.9281 855.3396 495.8734 1.01e+04 860.6832 774.0000 319.7012 270.4898 3101.5715 4.2663 10.0000 2.1577 0.2543 0.0040 0.9251 7.6580 0.6646 0.0000 1.4067 7.6500 30.3113 26.5000 15.2304

Pondicherry Urban 3939.0903 2605.3904 9326.4904 499.4109 1.09e+05 1210.1323 1072.2382 633.0971 235.3571 5283.7144 3.7268 15.0000 1.9046 0.0709 0.0040 0.6797 20.2350 0.1837 0.0000 1.0507 10.1180 32.9818 29.5000 15.0252

A & N Islands Rural 2225.6818 1663.5231 2715.1385 619.6674 3.01e+04 1120.6943 999.5000 601.1774 398.5714 8738.5713 4.0525 16.0000 1.9225 0.5523 0.0400 1.1324 12.1410 0.8600 0.8000 0.7994 8.0000 28.0236 27.0000 11.5805

A & N Islands Urban 3484.7452 2841.7178 2640.8275 927.8184 2.83e+04 1341.7317 1208.5714 631.4319 325.8571 1.14e+04 3.8331 12.0000 1.7974 0.0513 0.0100 0.4044 10.0020 0.2626 0.0000 0.5423 2.0030 30.1077 28.0000 11.5796

Overall

1601.8975 1066.0712 1943.2166 12.7740 1.86e+05 702.7717 582.4000 477.7525 8.0000 1.77e+04 4.5112 35.0000 2.1798 0.5430 0.0200 1.4088 121.4160 1.1029 0.6070 1.7582 121.4100 27.8506 25.0000 14.3268

Table 1b: Descriptive statistics of important variables for the 68th round.

Monthly per-capita consumption expenditure Monthly per-capita food expenditure Household size Number of females Land possessed in hectares Land cultivated in hectares Median age

State Sector Mean Median SD Min Max Mean Median SD Min Max Mean Max Mean Mean Median SD Max Mean Median SD Max Mean Median SD

Jammu & Kashmir Rural 2190.0586 1920.4144 1202.2317 462.5255 3.39e+04 1191.6718 1093.2000 538.6518 255.2222 1.17e+04 5.2091 20.0000 2.5403 0.4773 0.3290 0.6183 15.0000 0.4685 0.3530 0.5509 14.5000 25.5219 24.0000 11.7647

Jammu & Kashmir Urban 3927.6200 3307.0630 2529.3265 629.3151 3.07e+04 1540.1778 1378.1714 725.6981 349.5000 5786.4287 4.6768 19.0000 2.2286 0.1037 0.0200 0.2883 4.7970 0.3007 0.2000 0.4315 4.0470 28.1307 27.0000 11.7191

Himachal Pradesh Rural 2599.6425 2139.7842 1905.9752 705.9602 3.63e+04 1235.2977 1058.5000 885.9075 251.0000 2.50e+04 4.3723 18.0000 2.2351 0.4602 0.2400 0.7300 9.5750 0.3385 0.2200 0.4478 8.0430 31.5037 28.5000 14.8137

Himachal Pradesh Urban 4899.5116 4121.5928 3152.0123 661.8239 6.08e+04 1917.6442 1694.7500 987.1502 260.4000 1.47e+04 3.1284 13.0000 1.4543 0.1255 0.0040 0.6248 12.2560 0.4042 0.1520 0.9903 12.0640 29.5436 26.0000 12.7709

Punjab Rural 2906.5183 2436.0410 1803.5584 699.6689 2.70e+04 1292.9449 1165.7500 616.4730 368.4000 1.50e+04 4.7293 18.0000 2.2634 0.7090 0.0150 1.9563 44.5170 2.4037 1.6180 2.9234 28.3290 29.2965 26.5000 13.7489

Punjab Urban 4279.4867 3461.2200 3184.6493 773.1644 5.28e+04 1547.4702 1352.2500 828.5415 327.6286 1.22e+04 4.0957 20.0000 1.9294 0.1199 0.0080 0.7759 16.1880 2.7485 2.0220 2.8793 15.6830 29.5145 27.5000 12.6804

Chandigarh Rural 3502.8492 2892.9910 1856.3049 1090.2416 9641.6504 1552.9182 1236.6666 903.4825 566.1818 5681.7144 3.8348 15.0000 1.6637 0.0385 0.0040 0.3159 4.5320 1.4075 0.8090 1.5677 4.4520 27.7256 26.5000 13.7169

Chandigarh Urban 4814.7189 3823.6814 3729.3763 671.5851 3.30e+04 1675.8912 1315.2858 1153.6166 361.9048 1.04e+04 4.1830 13.0000 1.8462 0.0238 0.0050 0.0787 3.2320 . . . . 26.8409 25.0000 11.8104

Uttaranchal Rural 2163.7040 1837.6849 1253.7042 616.3014 2.96e+04 1118.2924 1005.3143 494.8844 382.0000 6380.0000 4.4953 20.0000 2.2217 0.3199 0.1300 0.6383 10.4200 0.4413 0.2400 0.7067 10.0000 28.4191 25.0000 14.9760

Uttaranchal Urban 3875.1159 3099.1919 2934.8587 597.9467 3.11e+04 1526.5889 1261.4642 905.2604 365.6143 8992.5000 4.3923 14.0000 2.0568 0.0615 0.0050 0.5853 20.5000 0.9944 0.1600 2.5095 20.0000 27.2648 24.5000 12.7748

Haryana Rural 2663.5295 2344.3357 1421.6059 542.2685 3.32e+04 1426.9227 1249.6000 759.5164 248.0000 2.65e+04 4.9149 20.0000 2.2711 0.8097 0.0180 1.6393 24.2580 1.9369 1.4160 2.0218 24.2400 26.4991 24.5000 12.1839

Haryana Urban 5568.0080 3916.3455 4956.1437 691.7291 5.86e+04 1942.9774 1589.5143 1714.6389 207.0130 5.54e+04 4.1846 16.0000 1.9387 0.0883 0.0080 0.5865 20.4370 1.3993 0.8090 1.9658 20.0320 28.4872 26.0000 12.4877

Delhi Rural 3635.6449 3146.6248 1610.2142 871.6473 1.18e+04 1541.9888 1424.4000 664.8495 360.0000 5354.6431 4.4805 14.0000 1.9985 0.0744 0.0040 0.3376 4.0120 0.8340 0.3230 0.9327 4.0470 26.6724 25.5000 9.2469

Delhi Urban 5626.6841 3912.6895 6570.6003 857.5284 1.20e+05 1791.5148 1536.3572 1026.8234 337.1429 1.20e+04 4.0501 18.0000 1.8160 0.0270 0.0020 0.5089 30.0010 0.4243 0.0000 1.7462 20.0000 28.3856 26.0000 12.4610

Rajasthan Rural 1962.1184 1745.6484 1668.5358 461.8063 7.05e+04 1010.3592 910.2500 868.1061 156.2000 3.73e+04 4.9651 22.0000 2.3916 1.6095 0.7680 2.3906 50.7050 1.9229 1.1000 2.3379 50.0000 25.4088 22.0000 14.4935

Rajasthan Urban 3966.7236 3010.5652 3052.7673 551.9413 5.67e+04 1524.0106 1204.6906 1247.1993 280.5143 2.20e+04 4.5997 22.0000 2.1454 0.2628 0.0050 1.2557 37.9730 2.1910 1.2500 3.1884 37.9350 25.8514 23.0000 12.6877

Uttar Pradesh Rural 1502.0065 1281.1240 1019.3023 158.7557 1.08e+05 809.6091 707.5000 495.9016 42.8571 3.15e+04 5.4842 39.0000 2.6713 0.5668 0.2510 1.0107 35.7500 0.7672 0.4600 1.1151 35.7050 23.6140 20.0000 14.3032

Uttar Pradesh Urban 3277.9141 2205.1616 3205.3903 465.3510 7.15e+04 1259.9786 1006.3928 816.5240 75.0000 1.26e+04 4.9230 32.0000 2.3229 0.1228 0.0060 0.6358 24.3040 0.9027 0.4570 1.5940 24.3000 25.3394 23.0000 12.9969

Bihar Rural 1402.0557 1267.3914 629.3847 338.7241 1.17e+04 817.9953 754.0714 355.4214 189.5000 5668.6855 5.1554 23.0000 2.4197 0.4182 0.0700 0.8647 44.0700 0.6123 0.2800 0.9161 38.4250 23.7638 21.5000 13.3131

Bihar Urban 2330.6799 1932.9707 1393.3744 474.0417 1.83e+04 1026.7235 914.7500 512.2029 246.0000 6043.8569 5.0359 22.0000 2.3249 0.1494 0.0100 0.5416 11.9430 0.9109 0.3800 1.4481 11.9000 23.9172 22.0000 11.7759

Sikkim Rural 2048.1426 1773.0182 902.9665 864.2951 8740.9336 1089.8449 981.5000 424.6195 488.7143 5956.1426 3.9991 13.0000 1.9653 0.6299 0.6000 0.5722 14.1640 0.6529 0.5600 0.5027 14.1000 28.4631 27.0000 12.6245

Sikkim Urban 3826.2882 3374.8684 1855.6333 1018.1187 1.55e+04 1647.6241 1541.0477 655.2973 534.0000 5306.8574 2.9584 10.0000 1.4568 0.0236 0.0020 0.1107 1.0100 0.3916 0.4000 0.2481 0.9150 28.9894 28.0000 12.1229

Arunachal Pradesh Rural 2303.5430 1774.8174 1732.1051 438.8767 1.84e+04 1142.5955 867.0000 932.0414 155.0000 1.31e+04 4.6925 18.0000 2.2301 2.4741 2.0000 2.8482 35.0000 1.5619 1.0000 1.7526 20.0000 23.9903 22.0000 11.2077

Arunachal Pradesh Urban 3258.2424 2644.9590 2283.8829 413.4301 2.37e+04 1413.8219 1169.0000 997.8499 147.6000 1.05e+04 4.1412 14.0000 2.0124 0.4290 0.0400 1.1302 20.0000 0.7636 0.5000 1.2314 10.0000 23.2796 22.0000 9.7839

Nagaland Rural 2346.2972 2132.5386 951.6115 697.1165 1.22e+04 1269.2811 1172.3334 527.0881 467.3333 6443.5356 5.2674 10.0000 2.5634 2.5131 2.0000 1.8027 14.5000 1.0876 0.9000 0.9625 8.5000 23.2183 21.0000 10.3987

Nagaland Urban 3242.2614 3013.3770 1344.7792 1254.3090 1.37e+04 1427.9230 1334.8000 564.6728 526.5000 5488.0000 4.9017 9.0000 2.3134 1.5153 0.9000 1.6915 13.0000 0.4985 0.3000 0.7850 9.5000 23.0705 22.0000 8.9968

Manipur Rural 1784.8750 1589.8494 753.8082 660.8849 9077.1230 938.9255 820.4524 428.7358 265.3571 6061.8413 5.1731 14.0000 2.4987 0.6463 0.5080 0.8978 30.0000 0.7271 0.5500 0.6649 13.9000 25.1773 24.0000 10.3817

Manipur Urban 2333.0536 2049.3123 1133.1307 817.9425 1.43e+04 947.4560 851.1667 405.0659 274.0000 3636.7144 4.9078 15.0000 2.3996 0.2471 0.0500 0.4999 10.0250 0.4756 0.4600 0.5735 8.0970 26.9465 26.5000 11.7407

Mizoram Rural 1989.1226 1752.2008 956.8441 498.5945 1.04e+04 1199.0990 1058.7142 594.5622 299.0000 8834.6426 4.7800 13.0000 2.3979 0.6907 0.5130 0.7304 13.9050 0.7472 0.7000 0.5808 13.8680 25.1224 23.5000 12.5145

Mizoram Urban 3461.1184 3148.8491 1547.9781 903.3065 1.45e+04 1675.3340 1562.7500 693.9161 466.4000 8061.5713 4.9360 14.0000 2.4915 0.1794 0.0150 0.4686 10.0120 0.4937 0.4050 0.4204 3.3050 25.1623 24.0000 10.8159

Tripura Rural 1643.0003 1449.8164 764.4507 499.8239 1.40e+04 1002.8115 914.3928 419.3956 314.5000 4749.2144 4.0915 21.0000 1.9566 0.2942 0.1600 0.3949 7.0130 0.3975 0.3300 0.3450 6.6000 29.0004 26.5000 13.1436

Tripura Urban 3172.3025 2766.6621 1806.4800 551.0359 1.40e+04 1458.1379 1308.6964 691.0411 267.0000 5451.5713 3.5256 17.0000 1.7500 0.0363 0.0180 0.0866 2.8050 0.0986 0.0000 0.2139 2.4750 31.9328 30.0000 12.8010

Meghalaya Rural 1799.4774 1648.2941 711.5345 697.6139 5.47e+04 1032.8547 943.6667 448.5800 357.8333 5.19e+04 5.1563 14.0000 2.5803 0.7075 0.5400 0.8452 13.1340 0.6276 0.4380 0.6448 6.0460 21.7153 20.0000 10.8720

Meghalaya Urban 3411.0884 2930.5769 1646.1288 849.3536 1.45e+04 1426.2775 1294.6666 656.8494 319.7143 7398.4287 4.8886 14.0000 2.5549 0.0921 0.0220 0.3615 10.0040 0.3858 0.1750 0.6151 4.0000 24.0896 22.0000 10.6495

Assam Rural 1505.8557 1325.7371 741.7792 453.0297 1.69e+04 928.7436 819.7959 444.4295 205.0000 7907.0000 4.9014 19.0000 2.2448 0.8611 0.5000 1.4093 120.6660 1.0257 0.6690 1.4485 120.0000 25.4026 24.0000 11.0866

Assam Urban 3254.9961 2680.6492 2207.7110 637.6794 1.64e+04 1393.1063 1200.8857 805.2967 342.2500 7385.5356 4.1009 18.0000 1.9745 0.1156 0.0270 0.5628 12.3580 0.3056 0.0000 1.1363 7.3480 29.4513 28.0000 11.5411

West Bengal Rural 1624.5831 1431.6781 949.0727 270.0753 3.90e+04 952.6155 857.7500 610.7333 34.2143 3.53e+04 4.1281 22.0000 2.0454 0.1826 0.0260 0.3903 9.2800 0.3882 0.2560 0.4978 9.2460 29.0852 26.5000 13.7527

West Bengal Urban 4091.0557 3023.3052 3703.1903 457.6343 6.94e+04 1574.2088 1371.9387 995.9990 203.0000 2.22e+04 3.7463 16.0000 1.8027 0.0369 0.0090 0.3251 21.0450 0.5623 0.2000 1.5458 20.0330 34.4520 32.0000 14.0135

Jharkhand Rural 1295.0806 1146.9150 651.6202 328.4460 1.65e+04 739.1463 662.2143 353.2042 133.5556 5391.1431 4.8880 24.0000 2.3843 0.4711 0.2140 0.8008 16.1880 0.5044 0.3080 0.7269 36.4230 24.0651 21.5000 13.4685

Jharkhand Urban 3035.9014 2555.1672 2097.0598 498.2986 2.44e+04 1287.0751 1133.9048 695.6529 242.6667 1.17e+04 4.3549 25.0000 2.0128 0.1266 0.0090 0.5365 12.1500 0.3925 0.1940 1.0184 12.1100 26.6359 25.0000 12.1902

Orissa Rural 1291.3983 1143.0083 660.4074 153.1370 2.47e+04 728.3728 660.3333 340.3912 120.0000 6518.0000 4.2411 18.0000 2.0855 0.5610 0.3040 0.7684 18.2110 0.8042 0.6070 0.7827 16.9970 30.1410 27.5000 14.2125

Orissa Urban 2873.8540 2290.9863 2010.2755 395.9178 2.32e+04 1201.7971 1041.5000 675.5565 108.0000 8142.8574 3.7264 14.0000 1.7872 0.1244 0.0080 0.4264 11.5310 0.8425 0.6060 0.8201 6.0700 29.5441 27.0000 13.3023

Chattisgarh Rural 1297.8907 1148.2798 698.7049 236.4521 1.52e+04 694.4235 624.5476 311.4925 94.0000 3720.5715 4.7368 21.0000 2.2998 1.0688 0.8140 1.3387 28.3270 1.2733 1.0000 1.3138 24.2820 27.9626 25.0000 14.5618

Chattisgarh Urban 2822.9467 2066.2056 2482.1496 271.6575 2.57e+04 1085.4562 911.2500 707.3755 102.7143 8880.7139 4.4479 18.0000 2.1522 0.3164 0.0120 1.2577 60.8130 1.4270 0.8090 2.5186 60.7000 26.0584 24.5000 12.1407

Madhya Pradesh Rural 1465.1128 1231.7474 981.8186 266.7251 4.71e+04 773.3753 683.0000 441.6930 130.6667 2.44e+04 4.6185 25.0000 2.1646 1.2560 0.6290 2.8540 163.9800 1.9803 1.2600 3.3956 161.9400 26.1915 22.5000 14.5759

Madhya Pradesh Urban 3148.8073 2295.4556 2688.5271 521.4983 3.41e+04 1171.5832 946.7857 827.1782 116.6667 1.36e+04 4.5004 22.0000 2.1064 0.2840 0.0060 1.2218 20.2000 2.3438 1.6180 2.5931 20.0000 27.4685 25.0000 12.9767

Gujarat Rural 1994.6125 1735.0514 1098.6626 52.1096 2.20e+04 1114.0962 1023.0000 448.7569 32.0000 6753.0000 4.8162 17.0000 2.3155 0.8606 0.1300 1.7204 40.0500 1.6304 1.0000 2.0931 40.0000 28.8376 26.5000 13.8278

Gujarat Urban 3867.8287 3316.1260 2524.2577 592.7551 5.14e+04 1625.2833 1530.0000 722.2982 171.4286 4.69e+04 3.8773 21.0000 1.7749 0.1477 0.0030 1.2178 20.2440 2.5842 1.2000 4.2746 20.2350 30.5454 28.0000 12.4904

Daman & Diu Rural 3423.5281 3042.3423 1276.3194 1387.3185 6511.2241 1850.7447 1643.4286 903.7382 830.0000 4502.8569 2.2359 14.0000 0.9161 0.0578 0.0010 0.1825 1.8160 0.2874 0.2100 0.2705 1.8000 27.3862 28.0000 9.8259

Daman & Diu Urban 3364.1701 2950.7939 1509.5059 1005.1945 1.01e+04 1494.9118 1381.2571 608.5918 517.6000 2908.7144 3.8421 31.0000 1.8410 0.0375 0.0050 0.2209 2.0220 1.3651 2.0000 1.1070 2.0000 29.2868 27.5000 12.3587

D & N Haveli Rural 1577.0199 1180.1062 1037.0307 443.7933 5868.2236 830.4057 658.2429 479.5405 277.5454 2685.1428 4.4317 16.0000 2.1011 0.4363 0.4040 0.5065 5.2520 0.5542 0.4040 0.3919 4.8480 21.9603 20.0000 11.2382

D & N Haveli Urban 3948.0359 2958.8164 2195.7626 1095.4648 8607.9180 1805.1607 1358.3469 1201.4247 484.2381 4774.2856 3.6784 16.0000 1.6886 0.0673 0.0020 0.2701 2.1850 0.6566 0.4050 0.6565 2.1820 25.3257 24.5000 8.5229

Maharastra Rural 2047.4956 1728.9424 1626.1098 314.0023 4.56e+04 1068.9645 945.6000 879.7720 78.0000 3.98e+04 4.2586 26.0000 2.0535 0.8812 0.1200 1.6291 36.4430 1.6154 1.2000 1.8362 32.3760 30.4752 27.5000 14.9899

Maharastra Urban 5092.7823 3626.2373 5469.4602 478.8196 1.30e+05 1806.0427 1467.1666 1324.9216 264.1667 1.75e+04 4.0777 21.0000 1.9213 0.1280 0.0020 0.8173 42.0700 2.0253 1.2140 2.6028 40.0000 29.6479 27.0000 12.7719

Andhra Pradesh Rural 2112.1357 1833.6005 1490.1070 176.4569 5.16e+04 1110.1440 985.1428 854.6605 64.2857 3.96e+04 3.5940 21.0000 1.7718 0.5501 0.0160 1.1545 92.9800 1.1896 0.8090 1.4079 92.9400 32.7799 28.0000 15.9310

Andhra Pradesh Urban 3681.4345 3078.6394 2504.4931 503.0000 5.32e+04 1454.5401 1286.7500 770.6344 53.0000 1.04e+04 3.4854 27.0000 1.7142 0.0812 0.0060 0.6214 28.4090 1.1597 0.4040 2.2237 28.3290 29.0832 26.0000 13.3770

Karnataka Rural 1920.1436 1623.1644 1240.9459 438.0240 3.28e+04 1008.8583 891.4000 511.1483 181.5000 8509.0713 4.4847 24.0000 2.2150 1.0446 0.4080 2.3218 93.4850 1.6284 0.8380 2.7216 92.6760 30.6775 28.0000 13.5975

Karnataka Urban 4767.1327 3255.9634 4817.2589 533.2358 7.15e+04 1658.9095 1285.0000 1339.7708 220.2000 4.33e+04 3.8372 21.0000 1.8473 0.2151 0.0060 1.5085 46.0000 2.3015 1.0110 4.4131 45.0000 29.3491 27.0000 12.3485

Goa Rural 3234.1700 2854.7463 1741.0901 926.2720 1.11e+04 1563.2212 1386.6666 820.3851 411.8810 5175.4287 3.9670 11.0000 2.0257 0.0691 0.0200 0.4307 6.0900 0.2280 0.0400 0.7928 5.8090 30.3848 29.0000 13.0533

Goa Urban 5104.5267 4354.3252 3087.1061 1035.7427 2.14e+04 1813.4803 1608.0000 894.7038 462.5000 8010.1426 3.7391 14.0000 1.8123 0.0575 0.0100 0.5875 10.2400 1.3677 0.0600 3.1733 9.5000 33.1053 31.0000 13.5607

Lakshadweep Rural 3772.5244 3239.6230 2102.0801 1278.5822 1.89e+04 2205.6162 2072.4285 875.7042 809.8000 6144.0000 5.0684 14.0000 2.4704 0.0847 0.0490 0.1208 0.6700 0.0755 0.0320 0.1767 4.0470 30.2869 27.0000 12.3535

Lakshadweep Urban 4563.6913 3662.6575 3297.3136 1017.1644 2.59e+04 2194.6095 1820.0000 1385.8478 441.6667 1.39e+04 5.1925 16.0000 2.8161 0.0508 0.0400 0.0881 0.9040 0.0411 0.0200 0.0929 0.8000 30.0116 28.5000 10.6613

Kerala Rural 3322.0009 2452.3425 4816.6637 494.7221 1.69e+05 1470.6336 1226.2858 3118.5244 37.0000 1.61e+05 4.0844 17.0000 2.1579 0.1850 0.0570 0.4633 16.9880 0.1872 0.0400 0.4817 16.1880 34.7522 32.0000 14.9749

Kerala Urban 5171.1398 3686.7915 5685.8023 387.7808 9.62e+04 1692.0812 1416.0000 1216.3709 33.0000 2.91e+04 3.8003 23.0000 1.9778 0.0812 0.0320 0.2590 4.8890 0.0928 0.0160 0.3583 10.0480 35.7282 33.0000 14.6400

Tamil Nadu Rural 2083.2448 1778.6849 1301.1647 382.0959 3.97e+04 1084.6925 958.4000 586.8455 42.8571 2.62e+04 3.6603 14.0000 1.8679 0.2641 0.0120 0.9391 80.9400 0.8460 0.6000 1.3494 60.7050 34.2762 30.0000 16.0923

Tamil Nadu Urban 3684.0187 2877.1462 2945.9131 363.7671 5.60e+04 1437.9842 1248.2858 828.3680 180.0000 1.80e+04 3.4533 17.0000 1.7289 0.0782 0.0060 0.6038 27.1810 0.8253 0.4040 1.1408 6.0710 32.8415 29.5000 14.5322

Pondicherry Rural 2858.7566 2561.8289 1569.3875 714.4521 1.79e+04 1476.1786 1270.1715 681.7483 171.4286 4686.4287 3.4730 11.0000 1.7861 0.1160 0.0060 0.3858 11.0000 1.0381 1.2140 0.6098 3.0200 32.9132 28.0000 16.2252

Pondicherry Urban 4364.9715 3711.4917 2805.8185 542.1507 3.91e+04 1763.9557 1607.2858 858.3702 278.5714 1.41e+04 3.4135 15.0000 1.7092 0.0288 0.0060 0.2674 14.0000 0.3346 0.0080 0.8615 3.6420 32.7011 29.5000 14.0186

A & N Islands Rural 3715.6069 2937.3589 2704.1332 960.0275 4.46e+04 1956.2357 1701.5000 970.9929 487.8000 7230.0000 4.1094 17.0000 1.9869 0.5127 0.0300 0.9711 5.9940 4.8312 0.8400 136.2978 4975.0000 29.0338 27.0000 12.4882

A & N Islands Urban 6405.2515 4836.5688 4828.7770 1657.7671 5.14e+04 2528.9939 2200.9048 1212.7157 500.0000 1.06e+04 3.5261 11.0000 1.7925 0.0223 0.0100 0.0871 2.2600 0.0543 0.0000 0.1559 0.8000 30.3204 28.0000 11.4725

Overall

2522.7007 1801.1750 2747.0752 52.1096 1.69e+05 1143.8230 952.2000 943.1646 32.0000 1.61e+05 4.4242 39.0000 2.1366 0.4995 0.0200 1.3549 163.9800 1.0821 0.6070 2.6852 4975.0000 28.4874 25.5000 14.3527

Table 2a: Estimation Results for 66th Round for equation 25

Regression 1 2 3 Variables Status -0.0442*** -0.0276*** -0.0212***

(0.0031) (0.0030) (0.0028)

MPCE (log) -0.1539*** -0.1558*** -0.1557***

(0.0073) (0.0056) (0.0056)

MPCE (Inverse) -77.9270*** -78.7518*** -82.7492***

(6.3254) (5.3367) (5.0329)

Household size (log) 0.0079** 0.0036 0.0047

(0.0034) (0.0033) (0.0033)

Max education -0.0072*** -0.0051*** -0.0056***

(0.0005) (0.0004) (0.0004)

Median age 0.0001 0.0002 0.0001

(0.0002) (0.0002) (0.0002)

Median age (squared) -0.0000 -0.0000 -0.0000

(0.0000) (0.0000) (0.0000)

No of females (log) 0.0039** 0.0047*** 0.0049***

(0.0018) (0.0017) (0.0017)

NCO Code 0.0023*** 0.0019*** 0.0020***

(0.0003) (0.0003) (0.0003)

Social group: 1 -0.0154*** -0.0161*** -0.0166***

(0.0043) (0.0041) (0.0041)

2 -0.0119*** -0.0108*** -0.0105***

(0.0026) (0.0023) (0.0023)

3 -0.0128*** -0.0113*** -0.0119***

(0.0028) (0.0023) (0.0023)

MPCE (state-district-sector aggregate) (log)

-0.0359***

(0.0076)

Per-capita land cultivated (state-district-sector aggregate) (log)

-0.0055*** -0.0065***

(0.0019) (0.0017)

Price index (log) (state-district-sector) -0.0771*** -0.0106 0.0213

(0.0195) (0.0173) (0.0168)

Educated fraction (state-district-sector aggregate)

-0.2156*** -0.1532***

(0.0159) (0.0221)

Constant 2.0598*** 1.9918*** 2.1817***

(0.0575) (0.0467) (0.0591)

No of Observations 78560 78169 78169 R Squared 0.4524 0.4671 0.4698

Note: The figures in the parenthesis indicate standard errors of the coefficients and *, **, *** denote significance of the coefficients at 10, 5, 1 per cent respectively.

Table 2b: Estimation Results for 68th Round for equation 25

Regression 1 2 3 Variables Status -0.0392*** -0.0272*** -0.0215***

(0.0030) (0.0030) (0.0028)

MPCE (log) -0.1308*** -0.1319*** -0.1304***

(0.0062) (0.0069) (0.0072)

MPCE (Inverse) -120.6895*** -121.2165*** -123.6256***

(8.5100) (9.0609) (9.3511)

Household size (log) 0.0144*** 0.0132*** 0.0134***

(0.0031) (0.0030) (0.0030)

Max education -0.0063*** -0.0047*** -0.0050***

(0.0005) (0.0004) (0.0004)

Median age 0.0002 0.0002 0.0002

(0.0002) (0.0002) (0.0002)

Median age (squared) -0.0000 -0.0000 -0.0000

(0.0000) (0.0000) (0.0000)

No of females (log) 0.0013 0.0009 0.0014

(0.0017) (0.0017) (0.0016)

NCO Code 0.0031*** 0.0027*** 0.0028***

(0.0003) (0.0003) (0.0003)

Social group: 1 -0.0165*** -0.0159*** -0.0170***

(0.0045) (0.0044) (0.0044)

2 -0.0150*** -0.0135*** -0.0127***

(0.0026) (0.0024) (0.0024)

3 -0.0140*** -0.0114*** -0.0114***

(0.0026) (0.0022) (0.0023)

MPCE (state-district-sector aggregate) (log)

-0.0350***

(0.0082)

Per-capita land cultivated (state-district-sector aggregate) (log)

-0.0061*** -0.0063***

(0.0020) (0.0020)

Price index (log) (state-district-sector) -0.0581*** 0.0116 0.0702***

(0.0145) (0.0207) (0.0260)

Educated fraction (state-district-sector aggregate)

-0.1790*** -0.1397***

(0.0158) (0.0199)

Constant 1.9132*** 1.8512*** 2.0210***

(0.0477) (0.0534) (0.0727)

No of Observations 80398 80030 80030 R Squared 0.3453 0.3602 0.3624

Note: The figures in the parenthesis indicate standard errors of the coefficients and *, **, *** denote significance of the coefficients at 10, 5, 1 per cent respectively.

Table 3a: Estimation Results for 66th for equation 26

Note: The figures in the parenthesis indicate robust standard errors of the coefficients and *, **, *** denote significance of the coefficients at 10, 5, 1 per cent respectively.

Regression 1 2 3 Regression 1 2 3 Regression 1 2 3

Variables Variables Variables

Status (Jammu & Kashmir Rural) -0.0136*** -0.0135*** -0.0135*** Status (West Bengal Rural) -0.0078*** -0.0079*** -0.0079*** MPCE (log) -0.1365*** -0.1363*** -0.1363***

(0.0027) (0.0027) (0.0027) (0.0025) (0.0026) (0.0025) (0.0051) (0.0053) (0.0053)

Status (Jammu & Kashmir Urban) -0.0218*** -0.0217*** -0.0217*** Status (West Bengal Urban) -0.0196*** -0.0196*** -0.0196*** MPCE (Inverse) -65.7143*** -65.5589*** -65.5763***

(0.0025) (0.0026) (0.0026) (0.0024) (0.0025) (0.0025) (4.9787) (5.0690) (5.0608)

Status (Himachal Pradesh Rural) -0.0141*** -0.0140*** -0.0140*** Status (Jharkhand Rural) -0.0143*** -0.0143*** -0.0143*** Household size (log) 0.0122*** 0.0121*** 0.0121***

(0.0026) (0.0027) (0.0027) (0.0026) (0.0026) (0.0026) (0.0029) (0.0029) (0.0029)

Status (Himachal Pradesh Urban) -0.0210*** -0.0208*** -0.0207*** Status (Jharkhand Urban) -0.0195*** -0.0194*** -0.0194*** Max education -0.0060*** -0.0060*** -0.0060***

(0.0028) (0.0030) (0.0030) (0.0024) (0.0025) (0.0025) (0.0004) (0.0004) (0.0004)

Status (Punjab Rural) -0.0152*** -0.0151*** -0.0150*** Status (Orissa Rural) -0.0116*** -0.0115*** -0.0115*** Median age -0.0004** -0.0004** -0.0004**

(0.0025) (0.0025) (0.0026) (0.0026) (0.0027) (0.0027) (0.0002) (0.0002) (0.0002)

Status (Punjab Urban) -0.0225*** -0.0223*** -0.0223*** Status (Orissa Urban) -0.0206*** -0.0204*** -0.0204*** Median age (squared) 0.0000 0.0000 0.0000

(0.0026) (0.0027) (0.0027) (0.0024) (0.0025) (0.0025) (0.0000) (0.0000) (0.0000)

Status (Chandigarh Rural) -0.0239*** -0.0239*** -0.0238*** Status (Chhattisgarh Rural) -0.0192*** -0.0190*** -0.0190*** No of females (log) 0.0036** 0.0037** 0.0037**

(0.0024) (0.0024) (0.0025) (0.0031) (0.0031) (0.0031) (0.0016) (0.0016) (0.0016)

Status (Chandigarh Urban) -0.0227*** -0.0226*** -0.0225*** Status (Chhattisgarh Urban) -0.0288*** -0.0286*** -0.0285*** NCO Code 0.0011*** 0.0011*** 0.0011***

(0.0023) (0.0025) (0.0025) (0.0024) (0.0026) (0.0025) (0.0003) (0.0003) (0.0003)

Status (Uttaranchal Rural) -0.0132*** -0.0132*** -0.0132*** Status (Madhya Pradesh Rural) -0.0195*** -0.0194*** -0.0194*** Social group: 1 -0.0059 -0.0060 -0.0060

(0.0025) (0.0026) (0.0026) (0.0025) (0.0025) (0.0025) (0.0037) (0.0037) (0.0038)

Status (Uttaranchal Urban) -0.0233*** -0.0232*** -0.0231*** Status (Madhya Pradesh Urban) -0.0288*** -0.0286*** -0.0286*** 2 -0.0051*** -0.0051*** -0.0051***

(0.0024) (0.0025) (0.0024) (0.0025) (0.0026) (0.0026) (0.0019) (0.0019) (0.0019)

Status (Haryana Rural) -0.0133*** -0.0132*** -0.0132*** Status (Gujarat Rural) -0.0112*** -0.0111*** -0.0111*** 3 -0.0024 -0.0026 -0.0026

(0.0025) (0.0026) (0.0026) (0.0025) (0.0025) (0.0025) (0.0018) (0.0018) (0.0018)

Status (Haryana Urban) -0.0240*** -0.0239*** -0.0238*** Status (Gujarat Urban) -0.0225*** -0.0223*** -0.0223*** MPCE (state-district-sector aggregate) (log) -0.0002

(0.0025) (0.0026) (0.0026) (0.0024) (0.0025) (0.0025) (0.0071)

Status (Delhi Rural) -0.0182*** -0.0220*** -0.0220*** Status (Daman & Diu Rural) -0.0145*** -0.0143*** -0.0143*** Per-capita land cultivated (state-district-sector aggregate) (log) -0.0006 -0.0006

(0.0033) (0.0028) (0.0027) (0.0024) (0.0026) (0.0025) (0.0011) (0.0011)

Status (Delhi Urban) -0.0262*** -0.0268*** -0.0267*** Status (Daman & Diu Urban) -0.0243*** -0.0263*** -0.0263*** Price index (log) (state-district-sector) -0.0224* -0.0215 -0.0214

(0.0025) (0.0027) (0.0027) (0.0031) (0.0025) (0.0025) (0.0124) (0.0144) (0.0160)

Status (Rajasthan Rural) -0.0155*** -0.0154*** -0.0154*** Status (D & N Haveli Rural) -0.0052** -0.0052** -0.0052** Educated fraction (state-district-sector aggregate) -0.0049 -0.0046

(0.0025) (0.0025) (0.0026) (0.0025) (0.0025) (0.0025) (0.0176) (0.0216)

Status (Rajasthan Urban) -0.0253*** -0.0251*** -0.0250*** Status (D & N Haveli Urban) -0.0225*** -0.0224*** -0.0224*** Constant 1.6963*** 1.6975*** 1.6989***

(0.0024) (0.0025) (0.0025) (0.0024) (0.0025) (0.0024) (0.0390) (0.0418) (0.0592)

Status (Uttar Pradesh Rural) -0.0145*** -0.0144*** -0.0144*** Status (Maharashtra Rural) -0.0157*** -0.0155*** -0.0155*** No of Observations 78560 78169 78169

(0.0025) (0.0025) (0.0025) (0.0025) (0.0026) (0.0025) R Squared 0.5310 0.5241 0.5241

Status (Uttar Pradesh Urban) -0.0245*** -0.0244*** -0.0244*** Status (Maharashtra Urban) -0.0234*** -0.0234*** -0.0233***

(0.0023) (0.0024) (0.0024) (0.0024) (0.0025) (0.0025)

Status (Bihar Rural) -0.0090*** -0.0090*** -0.0090*** Status (Andhra Pradesh Rural) -0.0110*** -0.0110*** -0.0109***

(0.0025) (0.0026) (0.0025) (0.0025) (0.0026) (0.0026)

Status (Bihar Urban) -0.0213*** -0.0212*** -0.0211*** Status (Andhra Pradesh Urban) -0.0213*** -0.0212*** -0.0212***

(0.0025) (0.0026) (0.0025) (0.0024) (0.0025) (0.0025)

Status (Sikkim Rural) -0.0147*** -0.0146*** -0.0146*** Status (Karnataka Rural) -0.0155*** -0.0154*** -0.0154***

(0.0024) (0.0025) (0.0025) (0.0026) (0.0026) (0.0026)

Status (Sikkim Urban) -0.0181*** -0.0180*** -0.0180*** Status (Karnataka Urban) -0.0240*** -0.0239*** -0.0239***

(0.0024) (0.0024) (0.0025) (0.0023) (0.0025) (0.0025)

Status (Arunachal Pradesh Rural) -0.0143*** -0.0141*** -0.0141*** Status (Goa Rural) -0.0129*** -0.0129*** -0.0128***

(0.0028) (0.0029) (0.0029) (0.0026) (0.0027) (0.0027)

Status (Arunachal Pradesh Urban) -0.0170*** -0.0167*** -0.0167*** Status (Goa Urban) -0.0236*** -0.0234*** -0.0234***

(0.0027) (0.0028) (0.0028) (0.0027) (0.0028) (0.0028)

Status (Nagaland Rural) -0.0077** -0.0075** -0.0075** Status (Lakshadweep Rural) 0.0013 0.0011 0.0012

(0.0032) (0.0033) (0.0032) (0.0024) (0.0025) (0.0025)

Status (Nagaland Urban) -0.0184*** -0.0182*** -0.0181*** Status (Lakshadweep Urban) -0.0114*** -0.0116*** -0.0115***

(0.0031) (0.0032) (0.0032) (0.0024) (0.0025) (0.0025)

Status (Manipur Rural) -0.0083** -0.0081** -0.0081** Status (Kerala Rural) -0.0160*** -0.0160*** -0.0160***

(0.0032) (0.0033) (0.0033) (0.0025) (0.0026) (0.0026)

Status (Manipur Urban) -0.0224*** -0.0221*** -0.0221*** Status (Kerala Urban) -0.0244*** -0.0243*** -0.0243***

(0.0032) (0.0033) (0.0033) (0.0026) (0.0027) (0.0027)

Status (Mizoram Rural) -0.0112*** -0.0112*** -0.0112*** Status (Tamil Nadu Rural) -0.0147*** -0.0147*** -0.0147***

(0.0032) (0.0032) (0.0032) (0.0025) (0.0026) (0.0025)

Status (Mizoram Urban) -0.0199*** -0.0197*** -0.0197*** Status (Tamil Nadu Urban) -0.0233*** -0.0228*** -0.0227***

(0.0026) (0.0027) (0.0027) (0.0024) (0.0025) (0.0025)

Status (Tripura Rural) -0.0061** -0.0062** -0.0062** Status (Pondicherry Rural) -0.0110*** -0.0110*** -0.0110***

(0.0026) (0.0027) (0.0027) (0.0030) (0.0030) (0.0030)

Status (Tripura Urban) -0.0121*** -0.0121*** -0.0120*** Status (Pondicherry Urban) -0.0178*** -0.0177*** -0.0177***

(0.0024) (0.0025) (0.0025) (0.0023) (0.0025) (0.0025)

Status (Meghalaya Rural) -0.0173*** -0.0173*** -0.0173*** Status (A & N Islands Rural) -0.0005 -0.0005 -0.0005

(0.0031) (0.0031) (0.0031) (0.0027) (0.0027) (0.0028)

Status (Meghalaya Urban) -0.0260*** -0.0259*** -0.0259*** Status (A & N Islands Urban) -0.0151*** -0.0151*** -0.0151***

(0.0027) (0.0028) (0.0028) (0.0024) (0.0025) (0.0025) Status (Assam Rural) -0.0033 -0.0033 -0.0032 (0.0027) (0.0027) (0.0027) Status (Assam Urban) -0.0134*** -0.0132*** -0.0132*** (0.0032) (0.0033) (0.0033)

Continued on the right…

Table 3b: Estimation Results for 68th Round for equation 26

Note: The figures in the parenthesis indicate robust standard errors of the coefficients and *, **, *** denote significance of the coefficients at 10, 5, 1 per cent respectively.

Regression 1 2 3 Regression 1 2 3 Regression 1 2 3

Variables Variables Variables

Status (Jammu & Kashmir Rural) -0.0126*** -0.0125*** -0.0131*** Status (West Bengal Rural) -0.0093*** -0.0089*** -0.0096*** MPCE (log) -0.1116*** -0.1098*** -0.1101***

(0.0028) (0.0028) (0.0027) (0.0027) (0.0027) (0.0026) (0.0062) (0.0063) (0.0063)

Status (Jammu & Kashmir Urban) -0.0213*** -0.0210*** -0.0219*** Status (West Bengal Urban) -0.0193*** -0.0188*** -0.0196*** MPCE (Inverse) -96.8536*** -94.8599*** -94.5506***

(0.0025) (0.0025) (0.0024) (0.0025) (0.0025) (0.0024) (8.2142) (8.2798) (8.2051)

Status (Himachal Pradesh Rural) -0.0178*** -0.0174*** -0.0181*** Status (Jharkhand Rural) -0.0158*** -0.0155*** -0.0160*** Household size (log) 0.0206*** 0.0211*** 0.0210***

(0.0026) (0.0027) (0.0025) (0.0029) (0.0029) (0.0028) (0.0031) (0.0031) (0.0031)

Status (Himachal Pradesh Urban) -0.0214*** -0.0211*** -0.0220*** Status (Jharkhand Urban) -0.0222*** -0.0217*** -0.0224*** Max education -0.0056*** -0.0056*** -0.0056***

(0.0027) (0.0028) (0.0026) (0.0026) (0.0026) (0.0025) (0.0004) (0.0004) (0.0004)

Status (Punjab Rural) -0.0195*** -0.0195*** -0.0203*** Status (Orissa Rural) -0.0138*** -0.0136*** -0.0141*** Median age -0.0006*** -0.0005*** -0.0005***

(0.0026) (0.0026) (0.0025) (0.0028) (0.0028) (0.0026) (0.0002) (0.0002) (0.0002)

Status (Punjab Urban) -0.0247*** -0.0246*** -0.0254*** Status (Orissa Urban) -0.0232*** -0.0229*** -0.0237*** Median age (squared) 0.0000 0.0000 0.0000

(0.0026) (0.0026) (0.0025) (0.0027) (0.0026) (0.0025) (0.0000) (0.0000) (0.0000)

Status (Chandigarh Rural) -0.0222*** -0.0214*** -0.0218*** Status (Chhattisgarh Rural) -0.0187*** -0.0186*** -0.0192*** No of females (log) -0.0006 -0.0006 -0.0006

(0.0026) (0.0026) (0.0025) (0.0029) (0.0029) (0.0028) (0.0016) (0.0016) (0.0016)

Status (Chandigarh Urban) -0.0245*** -0.0235*** -0.0242*** Status (Chhattisgarh Urban) -0.0271*** -0.0271*** -0.0279*** NCO Code 0.0018*** 0.0018*** 0.0018***

(0.0026) (0.0026) (0.0025) (0.0027) (0.0027) (0.0026) (0.0002) (0.0003) (0.0003)

Status (Uttaranchal Rural) -0.0138*** -0.0134*** -0.0141*** Status (Madhya Pradesh Rural) -0.0183*** -0.0182*** -0.0189*** Social group: 1 -0.0100*** -0.0098*** -0.0096***

(0.0029) (0.0029) (0.0028) (0.0028) (0.0028) (0.0026) (0.0035) (0.0034) (0.0034)

Status (Uttaranchal Urban) -0.0230*** -0.0227*** -0.0235*** Status (Madhya Pradesh Urban) -0.0275*** -0.0274*** -0.0282*** 2 -0.0069*** -0.0069*** -0.0070***

(0.0026) (0.0026) (0.0025) (0.0026) (0.0026) (0.0024) (0.0020) (0.0020) (0.0020)

Status (Haryana Rural) -0.0142*** -0.0141*** -0.0148*** Status (Gujarat Rural) -0.0105*** -0.0106*** -0.0112*** 3 -0.0034** -0.0032* -0.0033*

(0.0026) (0.0026) (0.0025) (0.0027) (0.0027) (0.0026) (0.0017) (0.0017) (0.0017)

Status (Haryana Urban) -0.0236*** -0.0235*** -0.0244*** Status (Gujarat Urban) -0.0197*** -0.0197*** -0.0205*** MPCE (state-district-sector aggregate) (log) 0.0073

(0.0027) (0.0027) (0.0026) (0.0027) (0.0027) (0.0026) (0.0082)

Status (Delhi Rural) -0.0192*** -0.0185*** -0.0192*** Status (Daman & Diu Rural) -0.0136*** -0.0132*** -0.0139*** Per-capita land cultivated (state-district-sector aggregate) (log) 0.0018 0.0018

(0.0031) (0.0031) (0.0031) (0.0026) (0.0027) (0.0025) (0.0014) (0.0014)

Status (Delhi Urban) -0.0248*** -0.0241*** -0.0249*** Status (Daman & Diu Urban) -0.0204*** -0.0198*** -0.0205*** Price index (log) (state-district-sector) 0.0218 0.0371** 0.0248

(0.0027) (0.0026) (0.0025) (0.0027) (0.0027) (0.0026) (0.0145) (0.0189) (0.0246)

Status (Rajasthan Rural) -0.0186*** -0.0188*** -0.0195*** Status (D & N Haveli Rural) -0.0176*** -0.0176*** -0.0181*** Educated fraction (state-district-sector aggregate) -0.0112 -0.0171

(0.0028) (0.0029) (0.0028) (0.0028) (0.0028) (0.0026) (0.0161) (0.0180)

Status (Rajasthan Urban) -0.0264*** -0.0265*** -0.0273*** Status (D & N Haveli Urban) -0.0238*** -0.0237*** -0.0243*** Constant 1.5405*** 1.5091*** 1.4696***

(0.0026) (0.0026) (0.0025) (0.0026) (0.0026) (0.0025) (0.0469) (0.0511) (0.0676)

Status (Uttar Pradesh Rural) -0.0158*** -0.0154*** -0.0161*** Status (Maharashtra Rural) -0.0158*** -0.0157*** -0.0163*** No of Observations 80398 80030 80030

(0.0026) (0.0026) (0.0025) (0.0027) (0.0026) (0.0025) R Squared 0.4206 0.4164 0.4165

Status (Uttar Pradesh Urban) -0.0231*** -0.0229*** -0.0237*** Status (Maharashtra Urban) -0.0237*** -0.0235*** -0.0242***

(0.0026) (0.0026) (0.0024) (0.0026) (0.0026) (0.0025)

Status (Bihar Rural) -0.0141*** -0.0139*** -0.0144*** Status (Andhra Pradesh Rural) -0.0151*** -0.0151*** -0.0158***

(0.0028) (0.0028) (0.0027) (0.0026) (0.0026) (0.0025)

Status (Bihar Urban) -0.0233*** -0.0229*** -0.0235*** Status (Andhra Pradesh Urban) -0.0237*** -0.0235*** -0.0242***

(0.0027) (0.0027) (0.0026) (0.0026) (0.0026) (0.0024)

Status (Sikkim Rural) -0.0153*** -0.0156*** -0.0161*** Status (Karnataka Rural) -0.0144*** -0.0143*** -0.0150***

(0.0027) (0.0027) (0.0026) (0.0027) (0.0027) (0.0026)

Status (Sikkim Urban) -0.0203*** -0.0202*** -0.0210*** Status (Karnataka Urban) -0.0242*** -0.0239*** -0.0248***

(0.0026) (0.0026) (0.0024) (0.0026) (0.0026) (0.0025)

Status (Arunachal Pradesh Rural) -0.0224*** -0.0227*** -0.0232*** Status (Goa Rural) -0.0168*** -0.0162*** -0.0168***

(0.0029) (0.0029) (0.0028) (0.0031) (0.0031) (0.0030)

Status (Arunachal Pradesh Urban) -0.0246*** -0.0248*** -0.0253*** Status (Goa Urban) -0.0237*** -0.0231*** -0.0239***

(0.0030) (0.0030) (0.0029) (0.0027) (0.0027) (0.0026)

Status (Nagaland Rural) -0.0131*** -0.0131*** -0.0136*** Status (Lakshadweep Rural) 0.0006 0.0009 0.0002

(0.0029) (0.0029) (0.0028) (0.0026) (0.0026) (0.0024)

Status (Nagaland Urban) -0.0210*** -0.0208*** -0.0214*** Status (Lakshadweep Urban) -0.0103*** -0.0099*** -0.0108***

(0.0026) (0.0026) (0.0025) (0.0025) (0.0025) (0.0024)

Status (Manipur Rural) -0.0190*** -0.0189*** -0.0192*** Status (Kerala Rural) -0.0148*** -0.0144*** -0.0152***

(0.0029) (0.0029) (0.0028) (0.0027) (0.0027) (0.0026)

Status (Manipur Urban) -0.0284*** -0.0284*** -0.0286*** Status (Kerala Urban) -0.0234*** -0.0231*** -0.0240***

(0.0028) (0.0028) (0.0027) (0.0026) (0.0026) (0.0025)

Status (Mizoram Rural) -0.0097*** -0.0101*** -0.0105*** Status (Tamil Nadu Rural) -0.0143*** -0.0140*** -0.0146***

(0.0031) (0.0031) (0.0030) (0.0027) (0.0027) (0.0026)

Status (Mizoram Urban) -0.0165*** -0.0167*** -0.0173*** Status (Tamil Nadu Urban) -0.0221*** -0.0213*** -0.0221***

(0.0028) (0.0027) (0.0026) (0.0026) (0.0026) (0.0025)

Status (Tripura Rural) -0.0072*** -0.0068** -0.0075*** Status (Pondicherry Rural) -0.0135*** -0.0129*** -0.0136***

(0.0027) (0.0028) (0.0027) (0.0031) (0.0031) (0.0031)

Status (Tripura Urban) -0.0148*** -0.0144*** -0.0152*** Status (Pondicherry Urban) -0.0201*** -0.0196*** -0.0205***

(0.0025) (0.0025) (0.0024) (0.0026) (0.0026) (0.0025)

Status (Meghalaya Rural) -0.0134*** -0.0135*** -0.0140*** Status (A & N Islands Rural) -0.0067** -0.0072*** -0.0079***

(0.0039) (0.0039) (0.0038) (0.0027) (0.0027) (0.0026)

Status (Meghalaya Urban) -0.0219*** -0.0218*** -0.0223*** Status (A & N Islands Urban) -0.0161*** -0.0161*** -0.0170***

(0.0029) (0.0029) (0.0028) (0.0026) (0.0026) (0.0025)

Status (Assam Rural) -0.0089*** -0.0089*** -0.0094*** (0.0027) (0.0027) (0.0026) Status (Assam Urban) -0.0196*** -0.0195*** -0.0201*** (0.0027) (0.0027) (0.0025)

Continued on the right…

Table 4: Results from endogeneity tests

66th round (Table 3a) 68th round (Table 3b)

Endogeneity test of endogenous regressors test statistic 0.1000 1.1500 Chi squared(1) P-Value 0.7523 0.2836

Weak identification test (Kleibergen-Paap rk Wald F statistic) 10.6070 20.4220