food security monitoring report malawi

Food Security Monitoring Report

Malawi June 2005

MALAWI Vulnerability

Assessment Committee

VAC

SADC FANR Vulnerability

Assessment Committee

VAC

Malawi Vulnerability Assessment Committee

In collaboration with

The SADC-FANRRegional

Vulnerability Assessment Committee

LA

KE

MA

LA

WI

Mzimba

Kasungu

Lilongwe

Rumphi

Dedza

DowaMchinji

Machinga

Zomba

Mulanje

Mangochi

Chitipa

Chikwawa

Ntcheu

Karonga

Nkhotakota

Nkhata Bay

Salima

Balaka

Mwanza

Nsanje

Thyolo

Ntchisi

Blantyre PhalombeChiradzulu

LAKECHILWA

LAKEMALOMBE

LAKECHIUTA

Missing Food Entitlements(% Min Energy Requirements,Per Capita)

>30%21-30%11-20%1-10%Not At Significant Risk

Legend

Country

Districts

Lakes

Parks

Cities

Areas at Risk: April 2005 – March 2006 Based on the price of maize increasing year-on-year at a rateequal to the present inflation rate (Scenario 1).

World Food Programme Government of the Republic of Malawi

Malawi VAC Food Security Monitoring Report June 2005 Inside Cover

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Acknowledgements

The Malawi Vulnerability Assessment Committee (MVAC) would like to thank the following participants and their organisations, who contributed either directly or indirectly to researching, analysing, writing up and presenting the information in this report:

• Walusungu Kayira (Ministry of Economic Planning and Development)

• Moses Kachale (Ministry of Economic Planning and Development)

• Martha Khungwa (Ministry of Economic Planning and Development)

• Charles Rethman (Ministry of Economic Planning and Development/Save the Children US)

• Fiskani Nkana (Ministry of Agriculture) • Pepani Bakali (Ministry of Agriculture) • Kettie Msukwa (Ministry of Finance) • Philemon Siwinda (National Statistics Office) • Simon Mulungu (Department of Poverty and

Disaster Management Affairs) • Gift Mafuleka (Department of Poverty and Disaster

Management Affairs) • Sam Chimwaza (FEWS-NET) • Evance Chapasuka (FEWS-NET)

• Tesfai Ghermazien (Food and Agriculture Organization)

• Caesar Kachale (Food and Agriculture Organization)

• Susanne Wiebe (United Nations Development Programme)

• Masozi Kachale (World Food Programme) • Sarah Kaphamtengo (World Food Programme) • Mervyn Chiumia (World Food Programme) • Duncan Ndhlovu (World Food Programme) • Smart Masamba (Action Against Hunger) • Commodious Nyirenda (Action Against Hunger) • Roslyn Harper (Concern Worldwide) • Vincent Gondwe (Concern Worldwide) • Norias Kayira (Catholic Relief Services) • James Bwirani (Oxfam) • Peace Mthekana (Save US)

In addition, the following agencies assisted the Malawi Vulnerability Assessment Committee by providing the data that much of this analysis is based upon:

• The National Statistics Office

• The Ministry of Agriculture

• The Department of Poverty and Disaster Management Affairs

• The Ministry of Health

• Action Against Hunger

• World Food Programme

• Food and Agriculture Organization (Crop and Food Supply Assessment Mission)

• FEWS-NET

• SADC Regional Remote Sensing Unit

• National Meteorological Centre

The Malawi Vulnerability Assessment Committee thanks all partners who have generously contributed funding towards this report: DFID, the European Union, World Food Programme and FEWS-NET.

This document contains the views and findings of the MVAC but does not necessarily reflect the views of the Government ofMalawi, any single member of the MVAC or any of the donors or funding agencies.

Malawi VAC Food Security Monitoring Report June 2005 Executive Summary

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Executive Summary

The Malawi Vulnerability Assessment Committee (MVAC) is a multi-agency body that studies the relationships between socio-economic conditions and people’s livelihoods to gain a better understanding of where, why and for how long people are vulnerable. One of the activities associated with this is to conduct regular monitoring assessments which are aimed at obtaining an early warning forecast for vulnerability to food insecurity in Malawi for the remainder of the agricultural consumption year (April to March).

Malawians continue to be unacceptably vulnerable to food insecurity, much of it chronic and much of it attributed to the high levels of poverty in the country. This year, a short but critical failure in the summer rains, coupled with a lack of inputs during the important planting and growing period, led to the lowest cereal production since 1994. The MVAC carried out a field exercise in April, which looked at the impact of this poor harvest and the prevailing economic conditions on poor households, using a modelling technique that is built on a ‘baseline’ description of how households normally survive and make their ends meet.

There are two basic questions being asked in a year of crop shortages. The first question is, “how much food is to be imported?” The answer to this lies in a food balance sheet, as the question centres around food availability. However, food in the country does not necessarily automatically translate into food at home or in bellies. People may be so poor that they are unable to secure food offered up in the markets. In this case, the second question that arises is, “what is the humanitarian need?” This report is largely concerned with answering this question1.

The MVAC has developed a series of livelihood profiles that describe how households go about getting their primary food requirements; these profiles are called baselines and they depict the sources of food and income, as well as the expenditure patterns that households incur to survive. When these baselines are combined with monitoring information that describes changes in terms of these elements, the result can be put in food terms. In other words, it is possible to describe how households’ access to food changes with changes in important components of their livelihoods, such as food crop production, cash crop production, ganyu availability and payment rates or staple prices. These livelihood profiles are applicable to carefully constructed livelihood zones (spatial areas of reasonably homogenous livelihood systems), as well as the different wealth groups within each zone. The profiles therefore differentiate households geographically and by the resources they command.

In April, MVAC members conducted a rapid survey (not sampled) of all of the areas identified as having had problems during the preceding season. Most of these were in the south of the country. The exercise was really conducted to verify the secondary data sources (such as production estimates or price changes) and elaborate on some others. Results and data were then combined and used to project scenarios based on assumptions that are built on the experience of previous years.

The MVAC recognises that many factors contribute to vulnerability, including HIV/AIDS, chronic and deep poverty and gender issues. However, the focus was kept on a ‘problem specification’ defined by the cropping season because the chief interest was in deciding how this season’s output affects short-term food security; other, longer-term issues will be investigated later.

Since it is extremely difficult to predict the future maize price2, two possible scenarios were chosen to describe this variable. Scenario 1 assumes that the maize price during the purchasing period (December to March) will rise to a level that reflects previous years with an adjustment made according to the current rate of inflation while scenario 2 assumes that maize is landed in Blantyre at $220/MT and then sold at cost parity, after adding storage and distribution charges as well as a small contingency.

In each affected part of a livelihood zone, the MVAC calculates a missing food entitlement3 (see Box 1), which is expressed as a

1 It must be noted that even in a good production year when there is an overall national surplus, some people may still not be able to access sufficient food and may therefore require humanitarian assistance. 2 A number of factors influence the maize price, many of which are equally difficult to predict 3 For simplicity, this analysis concentrates on one nutrient only: food energy. All food energy sources are included in the analysis, though, including foodstuffs such as dairy, meat (for the lucky few that have it), root crops and fruits such as mangoes and bananas,

Box 1: What are ‘Missing Food Entitlements’?

The term ‘missing food entitlement’ is usedrather than ‘deficit’ because the latter term isusually associated with the shortfall inproduction only. The shortfall in productionactually tells us how much food needs to beimported in order to meet local averageconsumption but it does not tell us whetherpeople will be able to get their hands on thatfood. The missing food entitlement is thesum of all the food that is missing athousehold level, after households haveexhausted all the options they have forobtaining it. It therefore represents the totalmissing calories from people’s intake orconsumption, rather than from theirproduction.


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percentage of the minimum per capita average energy requirement, or a percentage of 2100 kcal per person per day. Figure 1 shows the geographical areas as classified by the MVAC in terms of entitlement risk. This information can be converted into a single food commodity4 and summed over the population who are at risk of missing this entitlement. If maize is chosen as the commodity, the result is a total maize equivalent of the missing food entitlement. The maize equivalent of the missing food entitlement is an approximation of the total amount of cereal (maize) that is needed to ensure that households are able to meet their minimum food energy requirements.

What is striking in the MVAC’s baselines is that household incomes are very low for a great many Malawians. Baseline annual income figures (when the season and economic conditions are ‘normal’) range from around MWK 9,000 to MWK 30,0005 (US$ 70 to US$ 240) per household for the poorest third of most communities. At current prices, if all the income of a household from the lower end of the above range is put into staple purchase only, the household will get only 45% of its needs. Clearly, many households do not have the means to purchase their way out of any production failure –even for a short period. In addition, this drastically reduces the choices many households can make in terms of their basic needs, especially choices in the quality of food. Shortages of cash also force households to have make uneconomic choices, such

as selling productive assets or selling produce required by the household at harvest-time for a low price and then, when they obtain a little money later on, purchasing it back again later on in the year at a high price.

The total missing food entitlements for each scenario and the cash required to replace them are given in Table I. Notice that the cash equivalent has a much higher elasticity to staple price than the maize equivalent; if staple prices increase from scenario 1 by 71% to scenario 2, the cash equivalent to the missing food entitlement increases by an extra 198% (almost three times the value), whereas the maize equivalent only increases by 54%. The implications of this are that prices need to be reasonably stable if cash-transfer programmes are to be effective in meeting food needs.

Based on population breakdowns, the population at risk in scenario 1 of 4.2 million people represents approximately 2.9 million children under eighteen at risk and 750,000 children under five at risk.

The information in this report should inform the design of indicators for regularly monitoring food security; the scenarios can be tested and variations used to change the projections –something the MVAC also intends to do later in the year, based on the availability of reliable data. The areas at risk of large missing food entitlements should also be given priority for nutritional screening and it would be informative to compare children’s nutritional status with household wealth status.

The MVAC also intends to investigate chronic vulnerability issues by moving into deeper layers of analysis with the Integrated Household Survey (IHS) data or by conducting in-depth studies at specifically focused areas of interest.

many of which are rich in other nutrients. However, resource and time constraints do preclude analysis on needed nutrients such as proteins, micronutrients, etc. This statement in no way implies that these needs are not also important. 4 Use of a single food commodity is for comparison reasons only. It in no way implies that people should only eat a single commodity. 5 Previous reports had these figures at MWK 8,000 – 25,000. They have been adjusted upwards to compensate for inflation.

Table I – Total Missing Food Entitlements and Cash Requirements

Scenario 1 Scenario 2

Maize Purchase Price Increase from Feb 2005-Feb 2006

+13% (MWK 19-23/kg)

+93% (MWK 32-40/kg)

Change in price from scenario 1 to scenario 2 +71%

Overall Population Affected 4,224,400 4,612,200

Missing Food Entitlements 269,600 MT 414,400 MT

Change in food from scenario 1 to scenario 2 +54%

Cash Requirements MWK 6.04 billion, US$ 48.7 million

MWK 18.02 billion, US$ 145.3 million

Change in cash from scenario 1 to scenario 2 +198%

Box 2: Total Missing Food Entitlements (in cash or in maize equivalents)

The MFE totals in Table I are meant as overallplanning figures, they are not meant to be usedto determine precise targeting at sub-districtlevels. Rather, selective targeting should bebased on the criteria for the wealth groups,presented in Table XI in the Appendix. Thesewealth descriptions can be combined with othercharacteristics, such as dependency ratios,degrees of loss or failure, etc. to obtain precisetargeting criteria.


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Figure 1 - Maps Showing the Areas at Risk of Food Insecurity for the Agricultural Consumption Year April2005 to March 2006

LA

KE

MA

LA

WI

Mzimba

Kasungu

Lilongwe

Rumphi

Dedza

DowaMchinji

Machinga

Zomba

Mulanje

Mangochi

Chitipa

Chikwawa

Ntcheu

Karonga

Nkhotakota

Nkhata Bay

Salima

Balaka

Mwanza

Nsanje

Thyolo

Ntchisi


LAKECHILWA

LAKEMALOMBE

LAKECHIUTA

LA

KE

MA

LA

WI

Mzimba

Kasungu

Lilongwe

Rumphi

Dedza

DowaMchinji

Machinga

Zomba

Mulanje

Mangochi

Chitipa

Chikwawa

Ntcheu

Karonga

Nkhotakota

Nkhata Bay

Salima

Balaka

Mwanza

Nsanje

Thyolo

Ntchisi


LAKECHILWA

LAKEMALOMBE

LAKECHIUTA

«

Scenario 1: Maize prices adjusted at currentaverage inflation rates

K19-K23/kg

Scenario 2: Maize landed in Blantyre at $220/MT, consumer price adjusted for storage, distribution

and 5% mark upK32-K40/kg

Missing Food Entitlements(% Min Energy Requirements,Per Capita)

>30%21-30%11-20%1-10%Not At Significant Risk

Legend

Country

Districts

Lakes

Parks

Cities

Malawi VAC Food Security Monitoring Report June 2005 Contents

6

Contents Acknowledgements ........................................................................................................................................................Page 2

Executive Summary .......................................................................................................................................................Page 3

Glossary of Abbreviations Used in this Document .......................................................................................................Page 7

NATIONAL OVERVIEW

Introduction ....................................................................................................................................................................Page 8

The Methodology and the Areas Covered by this Assessment.....................................................................................Page 9

Current Hazards (Changes) ......................................................................................................................................... Page 12

Response Strategies..................................................................................................................................................... Page 16

Outcome....................................................................................................................................................................... Page 17

Conclusion and Implications....................................................................................................................................... Page 24

FINDINGS BY LIVELIHOOD ZONE

Chitipa District, Chitipa Maize and Millet Livelihood Zone...................................................................................... Page 25

Karonga District, Central Karonga Livelihood Zone................................................................................................. Page 27

Karonga and Nkhotakota Districts, Nkhata Bay Cassava Livelihood Zone .............................................................. Page 29

Rumphi District, Western Rumphi and Mzimba Livelihood Zone ............................................................................. Page 31

Nkhotakota District, Northern Lakeshore Livelihood Zone ....................................................................................... Page 32

Kasungu, Ntchisi, Dowa, Mchinji, Lilongwe and Dedza Districts, Kasungu Lilongwe Plain Livelihood Zone ...... Page 34

Nkhotakota, Salima, Dedza, Ntcheu and Mwanza Districts, Rift Valley Escarpment Livelihood Zone ................... Page 36

Salima, Dedza and Mangochi Districts, Southern Lakeshore Livelihood Zone ........................................................ Page 39

Mangochi, Zomba, Chiradzulu, Blantyre and Thyolo Districts, Shire Highlands Livelihood Zone......................... Page 41

Mangochi District, Phirilongwe Hills Livelihood Zone ............................................................................................. Page 44

Balaka, Machinga, Zomba, Mwanza and Neno Districts, Middle shire Livelihood Zone......................................... Page 46

Machinga, Zomba, Phalombe, Mulanje, and Chiradzulu Districts,

Lake Chilwa and Phalombe Plain Livelihood Zone ......................................... Page 48

Thyolo and Mulanje Districts, Thyolo-Mulanje Tea Estates Livelihood Zone.......................................................... Page 51

Chikwawa and Nsanje Districts, Lower Shire Livelihood Zone................................................................................. Page 53

APPENDICES

Common Hazards ........................................................................................................................................................ Page 56

Table Detailing the Criteria for Defining the Wealth Groups in Each Livelihood Zone .......................................... Page 58

Map of the Livelihood Zones in Malawi .................................................................................................................... Page 59

Malawi VAC Food Security Monitoring Report June 2005 Glossary of Abbreviations Used in this Document

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Glossary of Abbreviations Used in this Document

AAH – Action Against Hunger ACY – Agricultural Consumption Year –the year over which farming households normally consume their annual

production. This normally begins in April (as the harvest starts to be gathered) and ends in March (just before the next harvest. It is sometimes referred to as the Agricultural Marketing Year.

ADD – Agricultural Development Division – Spatial unit used by the Ministry of Agriculture, Irrigation and Food Security. It usually comprises two or three districts but is smaller than a region

CFSAM – Crop and Food Supply Assessment Mission DoPDMA – Department of Poverty and Disaster Management Affairs EPA – Extension Planning Area – sub-district spatial unit used by the Ministry of Agriculture, Irrigation and

Food Security FAO – Food and Agriculture Organization FEWS NET – Famine Early Warning System Network Ganyu – Casual labour or piecework IHS – Integrated Household Survey LBVA – Livelihoods-based vulnerability analysis LZ – Livelihood Zone MEP&D – Ministry of Economic Planning and Development MFE – Missing Food Entitlement MWK – Malawi Kwacha, the local currency in Malawi. At the time of writing US$1 = MWK 107 and € 1 =

MWK 127 MoA – Ministry of Agriculture MVAC – Malawi Vulnerability Assessment Committee NSO – National Statistics Office RDP – Rural Development Programme, a spatial unit used by the Ministry of Agriculture, Irrigation and Food

Security. RDPs are now equivalent to districts. RVAC – Regional Vulnerability Assessment Committee SC-US – Save the Children (United States) TA – Traditional Authority, a sub-district administrative spatial unit. UNDP – United Nations Development Programme UNICEF – United Nations Children’s Fund VAC – Vulnerability Assessment Committee (see also MVAC, RVAC) WFP – World Food Programme WVI – World Vision International

Malawi VAC Food Security Monitoring Report June 2005 National Overview

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Food Security Monitoring Report – June 2005 National Overview Introduction

The Malawi Vulnerability Assessment Committee (MVAC) is a consortium of organisations working to assess and reduce vulnerability in Malawi; it includes Government, UN Agencies and NGO’s. The Ministry of Economic Planning and Development in the Government of Malawi chairs the MVAC.

Malawians continue to experience unacceptably high levels of vulnerability and food insecurity, much of it chronic. Economic changes such as worsened terms of trade for primary commodities, lost employment opportunities and a depreciating local currency, coupled with degraded soils, shrinking land holdings6 and HIV and AIDS have fuelled growing poverty, which has been exacerbated by a succession of unfavourable climatic conditions. These conditions have reduced the ability of ‘poor’ households to secure sufficient income and food.

The livelihoods-based approach adopted by the MVAC provides relevant information and analysis on food access and livelihoods to various Government ministries, international organisations and civil society; in so doing it aims to inform early warning of pending disasters, to guide rural development strategies, poverty reduction and safety nets programming and to assist food security policy formulation.

The Overall Aim of this Assessment

This assessment is an important part an annual exercise conducted by the MVAC to present early warning information to relevant stakeholders, based on the main harvest that begins in April and is normally concluded in July. As such, the stated objective of the assessment was “to obtain a forecast for vulnerability to food insecurity in Malawi for the coming agricultural consumption year (i.e., April 2005 to March 2006)”.

There are two basic questions being asked in a year of crop shortages. The first question is, “how much food is to be imported?” The answer to this lies in a food balance sheet, as the question centres on food availability. However, food in the country does not necessarily automatically translate into food at home or in bellies. People may be so poor that they are unable to secure food offered up in the markets. In this case, the second question arises, which is, “what is the humanitarian need?” This is a question about people’s basic right to enough food, the food they need to stay alive, or their food entitlements. Food entitlements are not as straight forward as food being around; they are determined as much by people’s exchange options as their productive options. This report is largely concerned with answering this second question.

The MVAC does recognise that the high levels of both acute and chronic vulnerability in Malawi go far beyond changes in climatic conditions from one year to another. For this reason the MVAC uses a livelihoods-based vulnerability analysis (LBVA) in its approach. The MVAC is intending to move towards a deeper understanding of the causes behind both chronic and transient vulnerability, issues which will begin to be examined on pages 21 to 24.

In 2003 and 2004, the MVAC conducted livelihood-zoning exercises, completing the Household Economy Approach (HEA)7 baseline surveys in all 18 rural livelihood zones in Malawi. This report uses these baseline data in combination with information from the April/May 2005 MVAC assessment and secondary sources (principally the MoA Second Round Crop Estimates and price data) to develop projections of food security for various parts of the country between now and the next harvest at the end of March 2005.

This Report

The first section of this report, pages 1 to 7, consists of the cover, executive summary, table of contents and glossary of abbreviations. The next section, pages 8 to 24, contains the national overview for the country. The next fourteen

6 This includes the tillage of unsuitable or marginal land for the preferred agriculture. 7The household economy approach is also widely known as the “Food Economy Approach”. The word “food” was dropped by Save the Children to emphasise that the approach sought to understand how households’ go about their economic activities in order to meet their basic needs, rather than purely to determine food aid needs.


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sections (pages 25 to 55) detail the expected conditions in each affected livelihood zone. The last section (from page 56) is an appendix with some tables that detail the missing food entitlements and income requirements for each zone.

Except where cited, the MVAC produced the information in this document and any quotation from it should be credited to the MVAC. However, total cash requirements, food gaps, and numbers of affected populations are based on the official population projections provided by the National Statistics Office (NSO).

The Methodology8 and the Areas Covered by this Assessment

The Household Economy Approach Baselines

The basic principle underlying the household economy approach5, is that analysing local livelihoods is essential for a proper understanding of the impact —at the household level— of shocks or hazards such as drought, conflict or market dislocation. Crop failure may, for example, leave one group of households destitute because the failed crop is their only source of staple food, while another group may be able to cope because they have alternative food and income sources that can make up the production shortfall, such as livestock. The household economy baseline captures this essential information on local livelihoods and coping strategies, making it available for analysing the impacts of a given hazard.

Livelihood patterns vary from one area to another, according to many local geographical factors including climate, soil, and access to markets. The first step in a food economy analysis is therefore to prepare a livelihood zone map; that is, a map delineating geographical areas within which people share basically the same patterns of access to food, including crops and livestock and have the same access to markets. The livelihood zone map for Malawi is shown in the Appendix, “Map of the Livelihood Zones in Malawi”, page 59. This map also shows the spatial relationships between these zones, the districts and the Ministry of Agriculture’s extension planning areas (EPAs).

The location of a household is one important factor that helps to determine its options for obtaining food and generating income. A household’s asset holdings, or wealth, are also other contributing factors, since these determine access to the means of production or income generation. Wealth groups are typically distinguished from one another by differences in land holding, livestock holding, capital, education, skills, labour availability or social capital (kinship ties, education and training or skills level). Defining the different wealth groups in each zone is the second step in a food economy analysis, the output from which is a wealth breakdown.

Having grouped households according to where they live and their wealth, the next step is to generate household economy baseline information for typical households in each group for a defined reference or baseline year. Food access is determined by investigating the sum of the ways households obtain food —what food they grow, gather or receive as gifts, how much food they buy, how much cash income is earned in a year, and what other essential needs must be met with income earned. Once this baseline is established, an analysis can be made of the likely impact of a shock or hazard in a bad year. This involves assessing how food access will be affected by the shock, what other food sources can be added or expanded to make up initial shortages, and what final deficits emerge.

Outcome Analysis

The objective is to investigate and to derive an outcome that describes the effects of a hazard9 on future access to food and income, so decisions can be taken about the most appropriate interventions. The rationale behind the approach is that a good understanding of how people have survived in the past provides a sound basis for projecting into the future. Three types of information are combined; information on baseline access, information on hazard (i.e. factors affecting access to food/income, such as crop production or market prices) and information on response strategies (i.e. the sources of food and income that people turn to when exposed to a hazard). The approach can be summarised as follows:

Outcome is a function of the Baseline, the Hazard and the Response

OR

Outcome = f (Baseline, Hazard, Response)

8 See the following documents VAC for more detailed descriptions of the methodology and for conducting baseline assessments: MVAC, “Baseline Profiles for Malawi” and Lawrence, M, “Food Economy Scenario Analysis – a Guide for the Malawi VAC” FEWS-NET and MVAC, 2004. For a full description of the approach and methodology, see Seaman, J et al “The Household Economy Approach: A Resource Manual for Practitioners”, Save the Children UK, London (2000) 9 A hazard may be defined as any event or factor, be it environmental, economic or social conditions that is likely to affect access to food or income at household level (see the section ‘Current Hazards (Changes)’ on pages 12. The change may occur very rapidly or its onset may be slow and less immediately noticeable.


10

The hazard is defined by a ‘problem specification’ that is essentially a comparison between conditions this year and those in the baseline. An added advantage of this type of analysis is that by looking at year-on-year changes, small errors in the source data do significantly alter the outcome10.

The outcomes are normally expressed as numbers of people at risk and as missing food entitlements11. 'Missing food entitlements' refer to the food that households need to survive but which they cannot, in any reasonable way, get their hands on. This is a very different measure from the amount of food households may be storing, for example, because while a household may have no stocks, it may also have money or some item that it can easily exchange for food (including the labour of the household members). Missing food entitlements also differ from the ‘national deficit’, the latter being associated with the shortfall in production or supply. The shortfall in production actually tells us how much food needs to be imported in order to meet local average consumption but it still does not tell us whether people will be able to get their hands on that food. The missing food entitlements are the food that is missing at household level, after households have exhausted all the options they have for obtaining it. In this analysis, it represents the total missing food calories from people’s intake or consumption, rather than from their production.

Missing food entitlements are expressed in three different ways in this analysis:

1. As a percentage of an individual’s minimum average daily energy requirements, or 2100 kcal per person per day. For example, if each member in a household were missing 210 kcal per day then the missing food entitlement would be 10 percent.

2. As the amount of cash that the household would need in order to purchase sufficient food to cover the missing energy from their minimum needs with the most affordable commodity available. This is called the ‘cash equivalent’. In MVAC calculations, sufficient cash is also ‘set aside’ for the household to purchase its other minimum non-staple needs (including other foodstuffs) –this applies to all missing food entitlement representations. The cash equivalent is normally given in local currency units.

3. As the amount of a particular food commodity that the household would need to consume to cover the missing food from their minimum needs. This is normally given in terms of kg of maize, and is called the ‘maize equivalent’. Like the cash equivalent, the maize equivalent is derived from a missing food entitlement that takes into account other non-staple minimum needs.

Other Analyses

Many factors contribute to vulnerability, including HIV and AIDS, chronic and deep poverty and gender issues. Much of this assessment’s focus was kept on defining the problem specification, based on the recently completed cropping season12 because the chief interest was in deciding how this season’s output affects short-term food security. Nevertheless, it is understood that chronic and longer-term issues play a significant role in households’ livelihoods and therefore underlie much of the acute, shorter-term vulnerability presented in this report. There is therefore a strong case for further investigation into these factors and for exploring their links with poverty and households’ resilience. The section “Chronic and Transient Vulnerability” touches on this subject, although the MVAC intends to explore the subject further with:

• Investigations into linking the data from the Integrated Household Survey into MVAC analysis, and;

• The possibility of local in-depth studies that provide details on the linkages between the different measures of socio-economic status (for example, wealth, dependency ratios, illness prevalence, orphans, etc.)

10 For example, a small error in crop production (say 10%) would do little to the problem specification calculation but such an error may have serious consequences on other analyses, such as the national food balance sheet. 11 More precisely, this should be referred to as the ‘missing food energy entitlement’, as the calculations have been based on energy calculations. While it is theoretically possible to factor in the other important components of diet (such as protein, fats, micronutrients) into the calculations, the added complexities make it difficult to find the time and resources required to solve them. 12 This is what calling the activity a ‘monitoring assessment’ means.

Box 2 – Vulnerability not covered but forwhich there is still concern

The MVAC recognises that there are small areas, communities, and households whose livelihoods and food security are of concern, even though they are outside of this assessment. In particular, there are many people who face hunger and vulnerability everyyear, regardless of whether the season was good orbad. While not wishing to condone this undesirable level of chronic vulnerability, this report seeks tounderstand and report on the larger and more acute levels of vulnerability resulting from the previousseason’s crop failures.

This analysis is also based on projections, assumptions and scenarios; if reliable monitoring information arises that challenges these assumptions, then the MVAC will review its calculations and outcomes.


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Assessment Activities

The VAC assessment and analysis methodology involves triangulating diverse information and data sources, as shown in Figure 2.

Secondary source information provided the basis for identifying the worst affected districts for field visits and where complete and disaggregated data sets are available, for compiling the initial problem specifications.

VAC members from MEP&D, MoA, MoF, DoPDMA, NSO, SC-USA, Concern Worldwide, AAH, Oxfam, CRS, FEWS-NET, WFP, UNDP and FAO13 then spent at least ten days in the field with the objective of verifying the data on the changes over the last season and those expected in the coming year. To do this, they had to verify the second-round crop estimate figures14 and decide how the crop figure for the district should be broken down into livelihood units so that a comparison can be made between different years. They did this by visiting villages and conducting semi-structured focus group interviews with farmers from different wealth groups. The results were assimilated at the end of the day. It is important to note that the interviews followed a basic structure but not a questionnaire-type format. This is because the interviews were carried out in a way that encourages a probing enquiry; information was analysed, crosschecked and confirmed by interviewers as they went along. Any interesting developments were explored as well. This methodology was adopted to save on resources of people and time, promoting affordability and sustainability. This also meant that it was not possible to conduct any kind of standard

13 The VAC members were grouped together into four teams that were allocated groups of areas to study. There were 3-5 people in each team. 14 The MVAC deliberately waited for the second-round crop estimate figures to become available as the first-round figures were collected before the effects of the dry-spell had become apparent. The estimates used were aggregated to EPA level and these were grouped to obtain information on livelihood zones or affected parts of livelihood zones (in most case, EPAs fit wholly into livelihood zones).

Table II – Areas visited by the MVAC field teams

District EPA No. of villages

Chitipa Chisenga, Kavukuku 4 Karonga Lupembe, Vinthukutu 3 Rumphi Bolero, Katowo & Muhuju 3 Mzimba Visited district authorities only Nkhata Bay Visited district authorities only Likoma Not visited Nkhotakota Nkhunga, Linga, Mwansambo & Zidyana 6 Kasungu Chamama, Nkhamenya 2 Ntchisi Kalila, Chipuka 2 Dowa Chivala, Bowe 2 Mchinji Mkanda, Mikundi 2 Salima Chinguluwe, Khombedza, Tembwe, Chipoka 6 Lilongwe Mpingu, Chileka, Ming’ongo, Chitekwele, Chiwamba, Ukwe 6 Mangochi Nasenga, Mbwadzulu, Lungwena, Ntiya, Masuku 9 Dedza Mayani, Lobi, Linthipe, Mtakataka & Golomoti 5 Ntcheu Njolemole, Kandeu 2 Machinga Ntubwi, Nampeya 3 Balaka Utale, Phalula 3 Zomba Chingale, Thondwe, Ngwerero, Malosa, Mpokwe 6 Phalombe Mpinda, Kasongo, Naminjiwa 3 Neno Neno, Lisungwi 2 Blantyre Ntonda, Lirangwe, Kunthembwe & Chipande 2 Chiradzulu Mombezi, Thumbwe 2 Mwanza Mwanza, Thambani 2 Mulanje Thuchila, Msikawanjala, Mulanje Boma, Milonde 6 Thyolo Matapwata, Masambanjati, Thyolo Boma 4 Chikwawa Kalambo, Mikalango 4 Nsanje Makhanga, Mpatsa 4 TOTAL 93

Satellite imagery, remote sensing, rainfall data, and

other monitoring data

VAC Baseline Livelihood Profiles, field observations, focus group interviews, and

market visits.

NSO and MOAIFS crop estimates, price records, population estimates, and

other assessments.

Figure 2 - VAC Assessment Process - Triangulation


12

sampling procedure. It is an attempt to maximise the use of existing information and survey data (instead of replicating it), while ensuring that this data reflects the situation on the ground and is internally consistent.15

Field and secondary source data were then organised into comparisons; an element for this year was compared with that in the baseline and expressed as a percentage change16. The percentage change in food and income sources from the baseline represents the “problem specifications” that were used to calculate deficits and the lack of food entitlements.

Areas Covered

The field teams visited all districts (except for Likoma), RDP and EPA offices. In the fourteen livelihood zones that were found to have significant numbers of households that will be affected by poor crop production, the teams also visited villages (usually one per EPA) and met with elders and community leaders, as well as focus groups from each of the main wealth groups.

Current Hazards (Changes)

In the context of the current analyses, a hazard is any event or factor that is likely to affect access to food or income at household level17. For the hazard to be incorporated into the analysis, it has to be expressed in quantitative terms, e.g. a 50% reduction in maize production, a 20% increase in maize purchase prices, etc18. Some common hazard definitions or problem specifications are given in Table VII in the Appendix. Specific details of the hazards incorporated into the current analyses are given for each livelihood zone in later sections of this report. Three general hazards are considered in this section.

Crop Production Failure

Rural livelihoods still in Malawi, for all wealth groups, depend to a significant degree on the production and direct consumption of crops. In addition, many households, including the ‘poor’, also derive important income from the growing and selling of cash crops, as well as the sale of food crops.

For overall national production, there were problems during the season with inputs and especially fertiliser supply, which was coupled with an untimely break in the rainy season. The failure in the availability of inputs has been attributed to policy failure, as well as difficulties in procurement, transport and delivery. Policy failure came about because signals from Government as to whether or not they would subsidise were unclear, discouraging commercial traders from bringing in the necessary commodities early enough. When it became clear that Government would not provide a general subsidy, the private sector was unable to raise the quantities required quickly enough, while Government deliveries (intended only for the poorest and most vulnerable farmers19) were held up with supply bottlenecks, being distributed in late December into January.

15 It is important to note that the MVAC carried out this assessment without resorting to expensive external consultants, using the considerable capacity that has been built among members’ staff. 16 For ease of calculation, the VAC expresses its percentage changes as a ratio, not as a difference ratio; for example, if this year’s production is eight instead of ten units, the percentage change is expressed as 8/10 or 80%, rather than –20%. 17 See page 6, footnote 5. 18 See page 7, footnote 9. 19 Under the Targeted Inputs Programme, or TIP, as it is well known.

Figure 3 - Normalised rainfall image derived fromremote-sensing data (Source: Regional Remote SensingUnit, Gaborone)


13

In terms of rainfall, the 2004/2005 cropping season began quite well, although at the time there was some confusion as to when the season actually began. Farmers may also have gambled on the rains lasting long enough for them to delay planting until they had secured the necessary inputs they required. Whatever the reason, some farmers planted quite late—in December—which placed them at a severe disadvantage later on as their crops were beginning tasselling when the late-season dry spell began.

These problems became severe when the rainy season virtually ceased in early February, catching most plants at their critical stages. It is important to note that in much of the highland and central plains areas, the few farmers who had access to inputs were able to secure a harvest, even if it was not optimal. Those without—the overwhelming majority—were condemned to the lowest yields since 199420.

Notwithstanding the lack of inputs, in many parts of the country’s Southern Region, the dry spells were so severe that even copious inputs would have done little to lessen the failure. Some EPAs within the lowlands of the Central and Northern Regions were also in this category and all these are highlighted in the individual livelihood zones.

Cereals Crops: According to the second round crop estimates produced by the Ministry of Agriculture, the national production of cereals21 is the lowest since 1995.

Figure 4 is a time-series of national production over the last twenty-two years. It is interesting to note that, (with the exception of the high production harvests in 1999 and 2000 when large amounts of fertilisers were made available through a general subsidy) long-term cereal production has only increased very slightly and has definitely not kept pace with population increases. Also, it is apparent that since the early 1990s, there has been a lot more fluctuation in cereal production –this may be attributed to an increase in adverse weather events but may also reflect a more dynamic and unpredictable trade and policy environment.

Balaka, Salima and southern Nkhotakota, the lowland parts of Blantyre, Mwanza, Neno and Dedza districts, together with Lower Shire (Shire Valley ADD), were the worst hit in terms of cereal production. These areas all experienced around 20-40% of their baseline production. These are marginal growing areas for rain fed maize and households in these areas also grow significant amounts of sorghum and millet, both of which appear to have done as badly as maize22.

Most of the other areas identified in this assessment as having suffered poor production, achieved around 45-60% of baseline this year. In Dedza, Lilongwe, Kasungu, Mchinji, Dowa and Ntchisi, the of EPAs with failed cereal crops follow a much more patchy pattern, attributed more to the lack of inputs than the rains on their own.

The lowland areas of Lower Shire, the plain from Phalombe up to and around Lake Chilwa and the flatlands at the foot of the escarpments from Salima to Mangochi also depend on rice, which is grown for consumption and for sale. This crop did very badly this year in these areas, either failing outright or producing very little (0-10% of baseline).

Cassava, sweet potatoes and other root crops: Over the last two years, there has been a drive by both Government and international agencies to diversify the foodstuffs available to Malawians and this has included projects that distribute of cassava and sweet potato cuttings to farmers. Consequently, there has been an increase in cultivation of the crop, especially in the north of the country. However, from the perspective of risk of food insecurity over the coming year, it

20 See the FEWS-NET report, March 2004 21 Maize, sorghum, millet, wheat and rice 22 See Balaka, Mwanza, Zomba and Blantyre Districts, Middle Shire LZ on page 46 and Chikwawa and Nsanje Districts, Lower Shire LZ on page 53.

Figure 4 - Total National Production of the main cereal crops in Malawi1983-2005 (Source: Ministry of Agriculture and FEWS-NET)

0

400,000

800,000

1,200,000

1,600,000

2,000,000

2,400,000

2,800,000

Cropping Season

M aize Rice

Wheat Sorghum

M illet Average All Cereals (1983-2004)


14

is important to note that the plantings tend to be one-year varieties and in the worst hit areas these were planted just as the dry spells occurred, stifling their establishment and undermining forthcoming yields.

There is also the fear that households that have no other options will resort to early consumption of the smaller tubers.

Although national sweet potato and cassava production may well appear to cover lost maize, it is important to bear in mind they do not store, sell or travel well. Cassava flour can be expected to keep around three months and market systems presently convey it up to 50-100 km from its point of origin. Sweet potatoes can be stored for even shorter periods. This means that surpluses in Nkhata Bay and the North are not presently assisting food supplies in Southern Region.

Finally, there are many doubts over the tubers crop estimate figures, more so than any other crop. Tubers such as cassava is quite a lot more difficult than measuring cereals and this must be born in mind when comparing production figures.

Other food crops: Production in pulses and groundnuts has also increased significantly in the 1990’s but now seems to be levelling out. These crops are grown for sale as much as for own consumption, due to the relatively high value they have when compared with cereals. The most affected areas as far as crop production is concerned also lost most of their legumes this year.

Cash Crops: Last year, Malawi had one of its highest tobacco production figures of all time. The earnings from this crop were instrumental in paying for the imports of food crops into the country, especially that which entered informally from Mozambique. However, tobacco production is known to have reduced this year and quality is expected to be lower as well, resulting in considerably less income, especially for poorer farmers.

In response to the expectation of good prices and the provision of inputs on credit (to be repaid from production), farmers have, over the last three years, increased their areas cultivated under cotton. However, this year prices will fall compared with last year, from MWK25/kg to MWK18/kg. In the Lower Shire and in the Middle Shire livelihood zones, cotton production is expected to be affected by dry spells that have harmed flowering; this will affect yields and grading –the latter will also influence prices paid to farmers.

Maize purchase price

Since this monitoring analysis has been carried out as an early warning function to project possible food security outcomes that are based on the main 2004-05 agricultural season, purchase prices should reflect the period during the consumption year (in this case from April 2005 to March 2006) when most purchases are made. During the whole of this year, the period of most purchase is likely to be from October 2005 to March 2006, although the most vulnerable groups will begin purchasing as early as June, if they can find money.

0

40,000

80,000

120,000

160,000

200,000

240,000

280,000

320,000

360,000

Cropping SeasonGroundnuts Other PulsesGroundnuts Average (1983-2004) Pulses Average (1983-2004)

Figure 6 – Total national production of the main legume crops in Malawi1983-2005 (source: Ministry of Agriculture and FEWS-NET)

0

20,000

40,000

60,000

80,000

100,000

120,000

Cropping Season

Tobacco CottonTobacco Average (1983-2004) Cotton Average (1983-2004)

Figure 5 – Total national production of tobacco and cotton in Malawi1983-2005 (source: Ministry of Agriculture and FEWS-NET)


15

Scenarios have to be made to allow comparison of the period under review with the baseline. This year, the Ministry of Agriculture (MoA) posted a national deficit of 482,608 MT23. This figure did not include the provision of food aid or planned but it did include a projection for informal cereal imports.

Given that there is most likely some national deficit, there are two likely scenarios that could evolve:

• Informal cross-border trade could expand beyond what it was last year and coupled with food aid and other commercial imports (whether by the public or private sectors) market supply could be such that prices remain stable when compared with previous years. Any rise would be well within current inflation rates.

• Informal cross-border trade and food aid are insufficient to cover consumption requirements. In this case food will need to be imported and if it is not subsidised, the retail price is likely going to be influenced by various components such as the cost of purchase, the cost of transport, storage and distribution as well as supply and demand forces.

The VAC therefore decided to use two scenarios: Scenario 1 places the maize purchase price at a level in line with present inflation rates and scenario 2 is based on a resale price at purchase parity derived from a landed price in Blantyre of $220/MT. The assumptions used for the two chosen scenarios are explained in Box 3, point 3.

23 The FAO-led Crop and Food Supply Assessment Mission (the CFSAM) estimated a national shortfall of 434,000 MT.

Box 3 – Assumptions and Scenarios

The deficits and resulting food gaps reported in this document are based on scenariosfor the coming year, which are subject to many assumptions. The assumptions werederived from projections that the team considered likely but which may actually end up being quite different. It would be useful for those agencies that regularly monitor specific sites (for example, on a monthly basis) to pitch their questions at testing theseassumptions. Findings that are at variance with the chosen scenarios can then beincorporated into the analysis and the results amended.

1. The analysis here has considered that the exchange rate will remain ‘reasonably’stable. From the point of view of vulnerability to food insecurity, the importantthing is the ratio between what a household can earn against what it needs to spend on essential services and food. Therefore, a sudden devaluation occurring betweenthe main crop-selling period (June to September) and the food-purchasing period (December to March) will drive up food prices (as food will likely be imported)and severely disenfranchise households. This may lead to a reaction of hoarding (asthe ‘better-off’ fear that they will not be able to afford their needs), undermining the poor’s ability to access food or income through ganyu or kinship ties.

2. It is assumed that prices for most commodities will continue to rise at the currentprevailing inflation rate. This is 35% more than the price in the baseline marketingyear, i.e. the agricultural marketing year April 2002 to March 2003. There are afew exceptions to this, notably the price of cotton. Prices offered at the start of the season are substantially above those in the baseline (roughly 1.8 times the baseline,or 80% more than baseline). Assumptions on prices are easily monitored andadjusted as the situation develops.

3. Instability in the national supply of cereals can seriously affect staple prices andthis year there are fears that national requirements will not be met without importsor domestic purchases at an end price that exceeds normal inflation-adjusted levels. To allow for this possibility, two scenarios for the staple price have been created:

• Scenario 1 allows for a staple price at the end of the consumption year that is aprojection of current year-on-year inflation rates (i.e. around MWK 19-23 per kg)

• Scenario 2 is based on maize being landed in Blantyre at $220/MT and thensold at cost parity. Adding further storage and distribution costs as well as a 5%contingency will place the staple (maize) price well above current inflation-based projections (i.e. around MWK 31-40 per kg).

4. It is assumed that households will maximise their opportunities to obtain income orfood in order to meet their minimum requirements, i.e. they will not reduce intakeinstead or engage in risky or destructive practices to obtain food or cash. In reality, these ‘coping’ strategies are regularly adopted and will be manifest with greaterasset depletion and increased malnutrition.

5. Opportunities for labour (ganyu) in neighbouring countries are normal and therewill not be excessive emigration. This assumption will be revised according to developments that take place in the areas where cross-border movement is more likely.

6. The coming summer agricultural season, starting in October 2005, will be normaland on time.

7. The analysis also excludes interventions, such as public works programmes, wide-scale income transfer projects or food aid. This is because it seeks to inform theseinterventions.

8. Maize remains the preferred source of energy for households in the affected areas,although Government and other organisations are endeavouring to diversify thefood basket.


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Ganyu availability and payment rates

Ganyu, or casual labour (piecework), has evolved to become the dominant source of food for most of the country’s ‘poor’, being paid directly in maize or through cash. Ganyu has grown in importance as poorer households find it more and more difficult to invest in their farming and easier to work for those who have the necessary capital to ensure a reasonable harvest. Those with the necessary resources and capital can afford to spread their risk (diversify), purchase inputs24, plant on time, weed on time and quickly harvest their more abundant produce. Those without these resources quickly deplete their own production (often as early as July –normally) and look for ganyu.

Ganyu payment rates are known to fall at times of food shortage. Providing ganyu is a social obligation for wealthier households in the community but the system is informal and depends as much on what employers can afford as on needs. In general, ‘poor’ households prefer to receive their payment for agricultural ganyu in food when there are food shortages because cash pay rates seldom keep pace with staple price rises. Conversely, local community agricultural employers prefer to pay in cash during times food availability is low. In practice, employers will set aside as much food as they can afford to release for ganyu, after which they insist on providing cash.

The fall in both availability and payment rates will depend on the timing and performance of the coming 2005/06 cropping season, as well as resources remaining from the 2004/05 season. Good crop prospects (both in terms of favourable weather and market conditions) will influence the investment that households who provide ganyu opportunities make. The assumption is that the coming season will be normal and on time (see Box 3, item 6).

In most areas, the availability of ganyu-for-food is linked to the access that richer employer-farmers have for their local staples (cereals and root crops). Even though many of the affected areas identified in this report have very low staple productions, this does not mean that richer households cannot source food using their more considerable cash and asset bases. In all, most households will have access this year to between three-quarters and the entire amount of ganyu-for-food normally available in the baseline.

Ganyu-for-cash is pegged at a higher rate (usually 100 percent, or normal), since this depends more on the employers’ basic resources (income and capital) than on production of the payment commodity.

The assumption is made that ganyu cash pay-rates will not keep pace with inflation; rather they will increase but at a lower rate than those in the baselines. Despite this many parts of the country and especially those near to the border, experienced higher-than-usual pay rates during the 2004/05 season. Nevertheless, it is thought by members and by the villagers themselves that the increased labour supply caused by more households seeking work to overcome their production losses will keep labour rates only slightly up from baseline but still below inflation (i.e., around 110%).

Other changes. In areas that have suffered consecutive failures, such as Lower Shire (the Shire Valley ADD), households have been selling livestock each year at unsustainable rates. This means that household animal holdings have been reduced, affecting this source of income.

While there are long-term threats to fishing in Lake Malawi, the other lakes and rivers, on a year-to-year basis there is no evidence of a substantial decline. Therefore, for those whose livelihoods depend on fishing or on fishing ganyu, fish availability is taken to be the same as baseline this year.

Response Strategies

A relatively limited number of strategies will still be available to rural Malawian households to respond to common food security threats. The resilience of ‘poor’ households to shocks is constrained by four important factors in many parts of Malawi:

• Their dependence upon relatively concentrated livelihood and cropping patterns, especially their high dependence on casual labour combined with domestic maize production

• The very limited ability of local agricultural labour markets to meet the additional supply of labour in bad years • The low asset levels of most households. • The very low levels of income that households normally derive from their livelihood activities; this means that they

are unable to easily compensate for lost food and nor are they able to accumulate resources that can be used to mitigate against shocks

Further notes on the strategies incorporated into the current analysis are provided in the table below, and additional details can be found in the document ‘Malawi Baseline Livelihood Profiles’, available from the MVAC.

24 Especially fertiliser for what are often described as “tired soils”.


17

Table III - Response Strategies in Malawi Response Strategy

Notes

Livestock sales To supplement income, households that own livestock may sell additional animals, as they did to cope with high maize prices during the 2001-02 marketing year. This is an important strategy for ‘middle’ and ‘better-off’ households, but is less of an option for the ‘poor’, since few ‘poor’ households own significant numbers of animals. In this year's worst hit areas of crop production, particularly Lower Shire, Middle Shire and the Phalombe Plain, households have been unable to recover their asset holdings due to successive bad years.

Casual labour (Ganyu)

Attempting to expand ganyu is one of the main response strategies pursued by both ‘poor’ and ‘middle’ households in times of crisis. The effectiveness of the strategy may be questioned, however, since there is little evidence that local work opportunities increase significantly in a bad year, while labour rates most definitely fall when food is scarce. Out-migration in search of labour does occur (to towns and to neighbouring districts or countries). This was noted in 2001-02, but is probably not always an option that can be pursued by many of the ‘poor’ or ‘middle’ households. Many in the Lower and Middle Shire Valleys and on the Lake Chilwa and Phalombe Plain will likely seek employment in Mozambique; however, it is difficult to estimate the extent of coming opportunities. Casual labour could also be a mitigating factor in Lupembe EPA in Karonga district because of ganyu availability in neighbouring EPAs where production was good this year.

Changes in the balance between the sale and consumption of food crops.

This is potentially quite an important strategy in zones where ‘poor’ households sell rather than consume a proportion of their food crops. This is especially the case where the crop is sold post-harvest at a relatively low price. For the purposes of the current analysis, it has been assumed that in a bad year all types of household will to some extent switch from selling to consuming staple food crops that are sold in years that are more ‘normal’.

Increased cassava consumption

Cassava is an important reserve crop in a number of zones, especially in the north of the country. However, as with other crops, the ‘poor’ tend to plant smaller areas of cassava than either the ‘middle’ or the ‘better-off’ and may therefore have little reserve to fall back on in a bad year. The ‘poor’ may switch from purchasing maize to purchasing cassava, which, although requiring more preparation, is cheaper. If the production estimates are trusted, it will be plentiful in the north but the inability of cassava (even dried cassava) to ‘travel’ will limit this option in the south.

Switching expenditure from non-food items to staple foods.

Again, this is potentially quite an important strategy, especially in areas where the ‘poor’ cultivate tobacco and have a significant net income from this source. The approach in this case has been to define a minimum basket of non-staple food expenditure (soap, salt, dry fish, etc.) and to calculate potential purchasing power on the basis that any additional income over and above this can be spent on purchasing staple foods. The value of this minimum basket (MWK 3,540 per household per year) has been defined on the basis of observed patterns of expenditure by the ‘poor’ who live in the lower income zones in the country. As such, it reflects the actual expenditure minimising strategies employed by vulnerable households in Malawi.

Wild foods Access to wild foods that yield significant amounts of food energy, such as wild grains or wild roots and tubers is severely limited in Malawi. This limits the effectiveness of wild food consumption as a response to crisis.

Outcome

The Projected Missing Food Entitlements and the Numbers of People Affected.

Missing food Entitlements25 in this report refer to the missing intake of the annual energy needs for an average household. The energy needs are based on an average minimum requirement of 2100 kcal per person per day. Therefore, if a household is expected to face a food deficit of 33%, the household is missing one-third of its total minimum annual food needs –a very serious situation.

The analysis shows that, for scenario 1, the ‘better-off’ households in all areas of the country do not appear to be facing missing food entitlements in the coming agricultural year (April 2004 to March 2005). However, the ‘better-off’ in the Rift Valley Escarpment livelihood zone in Nkhotakota, Salima, Dedza and Neno (Group A on page 36) are at risk of a small lack of entitlements in scenario 2. The ‘middle’ wealth group are at risk of missing entitlements in the same parts of the Rift Valley livelihood zone, as well as in the Lake Chilwa-Phalombe Plain, Middle Shire, Thyolo-Mulanje Tea Estates and Lower Shire in both scenarios. The ‘middle’ wealth group will also be at risk of missing food entitlements

25 See the section “Outcome Analysis” on page 9 for a more complete explanation.


18

in the part of the Shire Highlands livelihood zone for scenario 2. The ‘poor’ face missing food entitlements in all the affected areas in both scenarios, but to different degrees.

Table IV below shows the household deficits for both scenarios. What is clear is that for those households with large missing food entitlements (>20%), staple price increases that are substantially above the inflation rate do not drive up these deficits by much26. This is explained by the fact that households with large deficits have low incomes; these households are unable to purchase grain at any price and so are not as affected by staple purchase-price changes as others are. This has implications for the viability and effectiveness of subsidies on the food price. Unless prices can be kept below MWK 4/kg (which is unrealistic), they will not remove the missing entitlements.

On the other hand, households that are just able to meet their needs (borderline cases) and those that are facing low deficits will experience a larger increase food shortage when prices increase. These households have greater incomes than those with the high deficits; however, this income is only useful when prices are stable.

Table IV – Individual Missing Food Entitlements by Districts, EPAs and Livelihood Zones for Each Scenario Affected Area Defici ts (Percentage of 2100 kcal) P o p u l a t i o n A t R i s k


District EPAs Livelihood Zone ‘Poor’ ‘Middle’ ‘Poor’ ‘Middle’ ‘Better-off’ ‘Poor’ ‘Middle’ ‘Better-

Off’

Balaka Bazale, Mpilisi, Phalula, Rivirivi,Ulongwe, Utale Middle Shire Valley 50-65%20-35% 60-70% 35-45% 152,500 95,000

Chipande, Kunthembwe, Lirangwe Middle Shire Valley 50-65%20-35% 60-70% 35-45% 117,800 73,400

Blantyre Chipande, Ntonda Shire highlands 15-25% 30-40% 45,100

Dolo, Kalambo, Livunzu Lower Shire Valley 55-65%50-60% >80% >80% Chikwawa

Mbewe, Mikalango, Mitole Lower Shire Valley 50-60%30-45% 65-75% 50-65% 159,400 188,800

Mbulumbudzi, Mombezi, Thumbwe Shire highlands 30-40% 45-55% 5-15% 66,400 96,600

Chiradzulu Thumbwe Lake Chilwa & Phalombe Plain 55-70%15-30% 60-70% 30-45% 23,300 38,800

Chitipa Chisenga, Kavukuku Chitipa Maize & Millet 25-35% 25-40% 12,300

Golomoti, Mtakataka Rift Valley Escarpment 15-30%10-25% 35-45% 30-40% 10-20% 15,700 19,000

Golomoti, Mtakataka Southern Lakeshore 10-20% 35-45% 20,200

Linthipe, Lobi Kasungu Lilongwe Plain 15-30% 20-35% 31,900 Dedza

Mayani Kasungu Lilongwe Plain 5-15% 10-25% 17,000

Bowe, Chivala, Mvera, Chinguluwe Kasungu Lilongwe Plain 5-15% 10-25% 29,000

Dowa Mponela Kasungu Lilongwe Plain 15-30% 20-35% 19,400

Lupembe Central Karonga 20-35% 40-50% 0-5% 3,500 4,200 Karonga

Vinthukutu Nkhata Bay Cassava 0-10% 5-15% 13,200

Chamama, Nkhamenya Kasungu Lilongwe Plain 15-30% 20-35% 63,000 Kasungu

Chulu, Santhe Kasungu Lilongwe Plain 5-15% 10-25% 35,500

Chilaza, Chileka, Malingunde, Ming’ongo, Ukwe Kasungu Lilongwe Plain 15-30% 20-35% 75,800

Lilongwe Chitekwele, Chiwamba, Mng’wangwa, Mpenu, Mpingu Kasungu Lilongwe Plain 5-15% 10-25% 94,600

26 With a price hike, deficits will rise a little but not as much as one might intuitively expect.

Box 4 – A Note about Numbers

The figures below exclude households in unaffected areasthat nevertheless may have some characteristic that wouldmake them vulnerable, for example, extreme poverty or animpoverished household whose productive members alsosuffer from a chronic, disabling disease such asHIV/AIDS.

Total missing food entitlements and numbers of people atrisk are provided to assist agencies in determining theoverall scale of vulnerability. They should not form thebasis of precise targeting. They are based on population projections calculated by the NSO, following the 1998 National Census. The MoA’s EPA population tables arealso used. These may or may not reflect the actual numbersof people on the ground in 2005-2006.

All figures reported here are only approximations and maybe subject to revision at any time at the discretion of theMalawi VAC.


19

Affected Area Defici ts (Percentage of 2100 kcal) P o p u l a t i o n A t R i s k


District EPAs Livelihood Zone ‘Poor’ ‘Middle’ ‘Poor’ ‘Middle’ ‘Better-off’ ‘Poor’ ‘Middle’ ‘Better-

Off’

Chikweo, Nampeya, Nanyumbu, Nsanama, Ntubwi Lake Chilwa & Phalombe Plain 55-70%15-30% 60-70% 30-45% 57,800 96,400

Domasi Middle Shire Valley 50-65%20-35% 60-70% 35-45% 9,900 6,200

Domasi, Mbonechera Shire Highlands 30-40% 40-55% 5-15% 32,900 47,800 Machinga

Nyambi Shire Highlands 15-25% 30-40% 12,500

Chilipa, Mbwadzulu, Mthilamanja, Namkumba, Nasenga

Phirilongwe Hills 10-20% 25-35% 55,300

Katuli, Lungwena, Maiwa, Masuku, Ntiya Shire highlands 15-25% 30-40% 99,600 Mangochi

Lungwena, Mbwadzulu, Namkumba, Nasenga Southern Lakeshore 10-20% 35-45% 66,400

Chioshya Kasungu Lilongwe Plain 5-15% 10-25% 16,400 Mchinji

Mikundi, Mkanda Kasungu Lilongwe Plain 15-30% 20-35% 39,100

Kamwendo, Msikawanjala, Thuchila Lake Chilwa & Phalombe Plain 55-70%15-30% 60-70% 30-45% 107,400 178,900

Mulanje Milonde, Mulanje Boma Thyolo Mulanje Tea Estates 10-20%5-10% 25-35% 20-35% 59,800 52,400

Mwanza Middle Shire Valley 50-65%20-35% 60-70% 35-45% 14,100 8,800 Mwanza

Thambani Rift Valley Escarpment 15-30%10-25% 35-45% 30-40% 10-20% 20,700 25,000 7,400

Neno Rift Valley Escarpment 15-30%10-25% 35-45% 30-40% 10-20% 20,400 24,700 7,300 Neno

Lisungwi Middle Shire Valley 50-65%20-35% 60-70% 35-45% 13,600 8,500

Linga, Nkhunga, Zidyana Northern Lakeshore 5-10% 20-30% 49,800

Mwansambo, Zidyana Rift Valley Escarpment 15-30%10-25% 35-45% 30-40% 10-20% 32,800 39,500 11,800 Nkhotakota

Nkhunga Nkhata Bay Cassava 0-10% 5-15% 8,200

Makhanga, Mpatsa Lower Shire Valley 55-65%50-60% >80% >80% 29,200 34,600 Nsanje

Mogoti, Nyachilenda, Zunde Lower Shire Valley 50-60%30-45% 65-75% 50-65% 55,700 66,000

Ntcheu Bilira, Kandeu, Manjawira, Nsipe, Sharpevale Rift Valley Escarpment 5-15% 0-5% 25-35% 15-25% 132,700 159,900

Ntchisi Chipuka, Kalira, Malomo Kasungu Lilongwe Plain 5-15% 10-25% 47,200

Phalombe Kosongo, Mpinda, Naminjiwa, Tamani, Waruma Lake Chilwa & Phalombe Plain 55-70%15-30% 60-70% 30-45% 63,900 106,600

Rumphi Bolero, part of Muhuju Western Rumphi & Mzimba 15-25% 30-45% 21,600

Chinguluwe, Chipoka, Kamuona, Thembwe Rift Valley Escarpment 15-30%10-25% 35-45% 30-40% 10-20% 63,900 77,000 22,900

Salima Chipoka, Kamuona, Thembwe Southern Lakeshore 10-20% 35-45% 62,300

Dwale, Khonjeni, Masambanjati, Thekerani, Thyolo Central

Thyolo Mulanje Tea Estates 10-20% 5-10% 25-35% 20-35% 208,200 182,100 Thyolo

Matapwata Shire highlands 30-40% 40-55% 5-15% 6,300 9,200

Chingale Middle Shire 50-65%20-35% 60-70% 35-45% 25,000 15,600

Chingale, Dzaone, Malosa, Thondwe Shire highlands 30-40% 40-55% 5-15% 120,200 174,800 Zomba

Likangala, Mpokwe, Msondole, Ngwerero Lake Chilwa & Phalombe Plain 55-70%15-30% 60-70% 30-45% 66,000 110,000

Since the calculations on deficits include incomes and expenditure in determining food entitlements, it should be possible to calculate the amount of money a household from a particular wealth group will need to overcome their missing food entitlements. This can be called the ‘cash equivalent’. In general, the larger the missing entitlement, the larger the cash equivalent will be. Table X in the Appendix shows the cash equivalents both scenarios in each of the affected parts of livelihood zones presented in Table IV.

The deficits can be combined with population figures to obtain a total ‘missing food entitlement’ for particular administrative areas or the nation as a whole. This has been done and is presented in Table V, while detailed breakdowns are available in the Appendix in Table IX on page 57.


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Based on MVAC data, UNICEF have calculated that of the 4.2 million people at risk, 2.2 million are children under 18 years of age and 750 000 are children under five.27

The total missing food entitlements are not a ‘food-aid need’, rather they are an indication of amount of food required to replace the deficits in all the identified households. Food-aid needs will depend on many other factors as well, including (but not limited to):

• The actual populations residing in the assessed areas (the figures given here are based on projections). Table xx in the Appendix contains basic descriptions of each of the wealth categories and these descriptions should form the basis of targeting, not the numbers provided in Table IV on page 18 and Table V.

• The amount of cash (income) households receive from other interventions

• The ‘off-take’ between the planned food rations and the actual food intake by the beneficiaries (including misdirected food)

• The food requirements for other chronically vulnerable households. Population figures and the percentages affected in each zone are listed in each Livelihood Zone Profile in pages 25 to 55 of this document.

Table V - Table of Main Food Security Outcomes: Missing Food Entitlements and Cash Requirements Scenario 1 Scenario 2 Remarks

MWK 19-23/kg MWK 32-40/kg Staple Price on which the scenario is based +71% Total Population affected TOTAL 4,224,400 4,612,200

Missing Food Entitlements (MT) TOTAL 269,600 414,400

Change in MFE Maize Equivalent from Scenario 1 to Scenario 2 +54%

Malawi Kwacha (K) 6,042,000,000 18,017,000,000

US Dollar ($) 48,728,000 145,300,000 Assumes an exchange rate of MWK 124 to $1.00 Euro (€)

40,282,000 120,114,000 Assumes an exchange rate of MWK 150 to €1.00

Cash needed to Overcome Missing Food Entitlements

Pound Sterling (₤) 26,736,000 79,722,000 Assumes an exchange rate of MWK 226 to ₤1.00

Change in Money Requirement from Scenario 1 to Scenario 2 +198%

The missing food entitlements will increase as the agricultural marketing year (April 2004 – March 2005) goes on. Table VI shows a breakdown of this missing food entitlement over three quarterly periods. In the extreme cases,

notably those of the affected parts of Lower Shire, Lake Chilwa–Phalombe Plain, Middle Shire, part of the Rift Valley Escarpment and Central Karonga livelihood zones, there is a small missing food entitlement from April to June. This is summarised in Table VI and in Figure 7. Details are shown in Table IX in the Appendix.

As with the missing food entitlements, the total cash required to replace the food gaps can be calculated. This

27 According to the MDHS Table 2.1, household population by age, sex and residence, on average 53% of household members are aged 0-18. (In the last 15-19 years age group the number was divided by 5 and multiplied by 3 to get the number for 15-17) In an average household of 5.5 members there will be therefore be an average of 2.9 children under 18 years of age. The number of children under five, according to the same table, is 17.9% or, for an average household size of 5.5 members there will be an average of 0.98 children under five.

Table VI - Progression by season of the missing food entitlements

Season Populations affected

Missing Food Entitlements

maize equivalent(MT)

April 2005 – June 2005 1,571,600 21,100 July 2005 – September 2005 2,883,500 46,400 October 2005 – December 2005 3,993,300 76,000 January 2006 – March 2006 4,224,400 126,100 Total 4,224,400 269,600

Figure 7 – Progression of Missing Food Entitlements over the year

Apr-JunJul-Sep

Oct-DecJan-M ar

126,100

76,000

46,400

21,1000

20000

40000

60000

80000

100000

120000

140000

MT

Season


21

Figure 8 – Graph showing the maize and cash equivalents’ elasticity against the staple purchasing prices for Scenario 1 and Scenario 2

0

50,000100,000

150,000200,000

250,000300,000

350,000400,000

450,000


2,5005,000

7,50010,000

12,50015,000

17,50020,000

22,500

M FE as Total: M aize Eq.M FE as Total: cash Eq.Change from Scenario 1 to Scenario 2: CashChange from Scenario 1 to Scenario 2: M aize

is shown in Table V and Table X for each livelihood zone.

Notice that the missing food entitlement (in MT) is 54% higher in scenario 2 than it is in scenario 1 but the cash needed to overcome that lack of entitlement is 198% higher (almost three times as much). This means that the cash equivalent has a far higher elasticity to price change than the maize equivalent. The consequences of this are that if food entitlements are to be assured with a cash or income intervention, prices must be kept reasonably stable –which can only be done with adequate supplies28.

‘Chronic’ and ‘Transient’ Vulnerability

As stated in the introduction, the overall purpose of this report is to provide an ‘early warning’ product about acute vulnerability in Malawi, especially in light of the poor 2004-2005 farming season. However, there is a growing appreciation that the unacceptably high levels of vulnerability experienced by many in Malawi is as much due to structural conditions as it is due to ‘shocks’ or ‘hazards’. Even where hazards are prevalent, questions arise as to whether these hazards are really as bad as the effects on vulnerability that they spawn, or whether these effects are not greatly exacerbated by the high degrees of prevailing poverty (including disease prevalence such as HIV and AIDS, malnutrition and many other manifestations and causes of poverty). Understanding which interventions will have the greatest effect on reducing vulnerability hinges around making sense of the degree to which hazard exposure or prevailing poverty are actually behind households’ vulnerability. Although somewhat crude, this section aims to begin to examine these issues and seek out solutions to our understanding.

Much confusion exists over what are being termed as ‘chronic’ and ‘transient’ vulnerability. The terms ‘chronic’ and ‘transient’ are about the duration of affectedness, not about the degree. It is therefore technically incorrect to refer to high-vulnerability cases as ‘transient’ and low-vulnerability cases as ‘chronic’. In spite of this, however, we know that people are capable of withstanding high degrees of vulnerability if only for a short period, while others may bear a low degree of vulnerability for a much longer duration. For this reason, ‘transient’ vulnerability is often equated with ‘acute’ vulnerability, which may be defined as vulnerability that is of short duration but is intense or deep enough to be life threatening.

For the sake of clarity, in this text the term ‘transient vulnerability’ refers to a state of vulnerability that occurs within a single agricultural consumption year, usually concentrated during particular seasons, while ‘chronic’ vulnerability is taken to be vulnerability that repeats itself every year, even if only for a part of that year; for example, during the ‘hunger season’.

Vulnerability is often expressed as the being a condition that is determined by households’ lack of ability to cope, or their lack of resilience, combined with their exposure to some sort of hazard. In other words:

Vulnerability is a function of a households’ lack of resilience and its exposure to hazard

OR

Vulnerability = f (Lack of resilience, Exposure to Hazard)

This expression tells us that there are two dimensions to vulnerability, and therefore mapping the degree to which people are vulnerable must take both dimensions into account.

Hence, when we talk of households being chronically vulnerable, we essentially mean these households are either subjected to frequent or severe and regular hazards or households that have a low resilience (or a high lack of resilience) or both.

Figure 9 is a sketch that shows how these two dimensions may contribute to chronic vulnerability, with some examples from different parts of the country. Note that the examples are not dimensioned and this figure is not meant to be a basis for comparing the different examples. In future it is hoped that numbers can be assigned to each of the two dimensions

28 This statement in no way implies that the supplies have to be provided by the Government, just that there have to be adequate supplies.


22

for many different areas, so that the scale and the nature of chronic vulnerability can be mapped this way and better understood.

Point (1) on Figure 9 represents a location that experiences few external shocks and when it does, these shocks tend to be of lower severity than elsewhere. In addition, households there have resilient livelihood systems. Hence, the total vulnerability, as represented by the length of the arrow from the origin of the axes to the point, is quite low. A possible example of such a point in Malawi is the area around of Mzimba.

Point (2), as indicated by the length of the arrow, has a much higher degree of vulnerability than point (1), although this vulnerability is attributed mostly to the frequency and severity of the hazards faced by households in the area represented by this point, rather than their lack of resilience or ability to cope. An example of this in Malawi could be Lower Shire livelihood zone (Shire Valley ADD, or Chikwawa and Nsanje districts), where households have more assets, higher incomes and a much wider array of options for coping with adversity29 than elsewhere but where there are frequent droughts or floods that undermine what are actually more robust livelihoods30. Logically, it would make sense to programme efforts to mitigate against the twin threats of drought and floods (with irrigation from the Shire River and well-designed flood control systems), rather than tackling poverty on its own in an area such as this31.

Point (3) has more-or-less the opposite situation to that of Point (2). Examples of households experiencing conditions represented by this point are the ‘poor’ found in the Southern Highlands, some of the highland areas of Ntcheu and Dedza districts and some parts of Lilongwe Rural district. These households (by virtue of the physical geography of where they live) are not subjected to extreme environmental events very often and when they are, these are often of a lower magnitude than elsewhere. However, the ‘poor’ households in these places have very weak livelihoods –they have few assets, have few options for economic productivity (and consequently low incomes) and have weak coping strategies. Their vulnerability is invariably a result of deep poverty and this explains why these areas have many of the manifestation of food insecurity and vulnerability even in good years32. Strategies for reducing vulnerability should therefore aim at strengthening livelihoods and tackling the deep poverty by increasing annual income and assisting in the accumulation of assets.

29 In Lower Shire, households normally grow a large variety of crops, including sorghum, millet and maize as cereals, sweet potatoes and a little cassava as root crops, vegetables (largely for sale) and cotton (with a little bit of sugar) as a cash crop. They also keep more livestock than many other parts of the country, they fish and are able to engage in petty trading or to seek ganyu over the border in Mozambique. In the 1997/98 IHS, the TAs in Lower Shire scored better than most in Southern Region in the poverty headcounts and the depth of poverty (see “The 1998 Integrated Household Survey” and “Malawi – an Atlas of Social Statistics”). 30 Since 2000, the area has experienced the following calamities: 2001 –flood 2002 –drought 2003 –flood 2004 –drought 2005 –drought 31 It may be that repeated hazards afflicting this area have undermined livelihoods to the extent that Households’ ability to cope has weakened over the years –this would be represented by the point moving vertically upwards in Figure 9. 32 Many of these areas show up with indicators of high food insecurity, even in good agricultural production years. See AAH Surveillance Bulletin, January 2005 data

Figure 9 – Sketch Showing the Dynamics of the Two MainDimensions of Vulnerability (Not To Scale).

Degree of Exposure to Hazard (Frequency and Severity of Hazards)

Deg

ree

of L

ack

of R

esilie

nce

(ess

entia

lly a

fu

nctio

n of

pov

erty

)

E.g. Much of MzimbaSelf-sufficient LZ

E.g. Lower Shire LZ (Chikwawa and Nsanje Districts)

E.g. Much of Phalombe Plain LZ (especially Phalombe District)

E.g. much of the Shire Highlands LZ and the Rift Valley Escarpment LZ, parts of Lilongwe Rural.

12

4

3


23

Lastly, point (4) shows an area of chronic vulnerability with a mixture of both lack of resilience and frequent or severe hazards. An example of such an area could be most of Phalombe district (except Nkhulambe EPA on the east side of Mount Mulanje). Households represented by this point will need a mixture of interventions –partly to dampen the effect of hazards and partly to reduce poverty.

The horizontal values for each point in Figure 9 could be measured by multiplying both the frequency of hazards and the severity of each of them. The vertical values in Figure 9 are best measured by looking at the depth of poverty figures from the Integrated Household Survey (IHS) and by comparing these with data from the HEA baselines.

Linking the IHS and Households’ Resilience33

In 1997-98, which was also a normal production year in most parts of the country, the NSO and the then National Economic Council (now the MEP&D) undertook a national Integrated Household Survey (IHS), which identified relationships between household characteristics and households’ welfare levels. The IHS data was collected over a twelve-month period and although the data, containing detailed information on household consumption and expenditure as well as a host of household demographic and other characteristics, was rich, it was nevertheless a sample, which at best provides data aggregated at district level.

About the same time, the NSO undertook the 1998 Malawi Population and Housing Census. While collecting simple information, the census was universal in coverage and the data can therefore be highly disaggregated.

The poverty mapping in Malawi – an Atlas of Social Statistics takes advantage of both datasets, modelling household welfare and producing an indicator for each household in the census with similar characteristics. From this, poverty levels can be assigned to Traditional Authorities (TAs) or EPAs. One such poverty level that is comparable to that in the MVAC analysis is the Depth of Poverty, or the average level of consumption below the poverty line34.

Three poverty lines were developed in the IHS for each of the three regions (Northern, Central and Southern) and one was developed for the urban centres. The poverty lines were based on the cost of the minimum recommended daily per capita energy requirements plus some basic non-food items. The weighted mean for the nation was then MWK10.47 or about $0.41 (MWK 44.41

33 Much of the descriptions here are taken from “Malawi – an Atlas of Social Statistics” (National Statistics Office and the International Food Policy Research Institute), T. Benson, J. Kaphuka, S. Kanyanda and R. Chinula. Data and explanations provided in Malawi – an Atlas of Social Statistics were used to write this section. 34 See “Malawi – an Atlas of Social Statistics”, page 27 and 32.

Figure 10 - Depth of Poverty (source: NSO and IFPRI)

Map obtained from “Malawi –An Atlas of Social Statistics”,NSO and IFPRI, Bennet,Kaphuka, Kanyanda & Chinula


24

now, or about $0.35). Those households whose daily per capita consumption fell below this amount were classified as poor. The percentage of poor households in a given spatial unit is called the poverty headcount. However, it is difficult to relate the poverty headcount to the MVAC livelihood data as it does not say how poor the poor actually are.

The ‘poverty gap’ is the difference between individual consumption levels in households and the poverty line (individuals in non-poor households have a poverty gap of zero). The Depth of Poverty figure for each spatial unit (in this case for each TA) is calculated as the mean poverty gap for the whole population, divided by the poverty line35.

Areas where the depth of poverty exceeds 0.282, the national rate, are also likely to be areas with high chronic vulnerability (areas that are shaded brown on the map in Figure 10). This depth of poverty data can potentially be used to disaggregate income levels within livelihood zones, and so create a “spatial problem specification”, the analysis of which can then be compared with the temporal outcomes presented in the section “The Projected Missing Food Entitlements and the Numbers of People Affected.” Areas where the two lots of missing food entitlements are of similar values are likely to be areas where the present vulnerability is actually a more chronic phenomenon and is due to poverty, not climatic change. The union between these and other areas of high poverty will need to be considered for longer-term action against chronic vulnerability.

This analysis will require time and resources to be carried out but could prove very useful, not only in informing policy for safety nets and social protection measures but in maximising the use of existing information and information systems.

Conclusion and Implications

The outcomes presented above seek to show what will happen if most variables that determine food entitlements develop in a manner that is consistent with previous years. More extreme variations than what are presented here will trigger a deeper and more widespread crises, dragging more households from the ‘middle’ and even ‘better-off’ wealth groups into food deficit.

Household incomes for the ‘poor’ are very low in Malawi. Baseline data suggests that the ‘poor’ earn between MWK 9,000 and MWK 30,00036 per household per annum (depending on their livelihood zone). Those in zones with incomes close to the lower figure are only able to purchase around 45% of their needs in a normal year, assuming that they put all their income into staple cereal food purchase. These low incomes mean that households have virtually no cash to fall back on in the event of a production failure. It also means that they are very severely limited in terms of the choices they can make for their basic needs. Since they need to purchase items other than staples, they will seek cash whenever they can and are forced to sell some of their crop at harvest-time, when prices are low. Later on, when prices have risen, they will be forced to buy back again. This becomes a vicious circle, reinforcing their poverty.

The missing food entitlements can be alleviated through food aid (or ‘direct food-entitlement support’) or they can be replaced with cash. The figures given in this document for cash requirements can be used to design cash transfer programmes; for example, given a certain statutory wage rate, the number of days a cash-for-work programme should go on for in a particular area can be calculated. Presently, Malawi has two major cash-based programmes, although they have not until now been targeting emergency needs. Food aid has so far been used to do this.

The analysis in this report is not the last word on food security in Malawi for 2005-2006. The scenarios chosen and the assumptions underlying each of the predicted variables need to be tested and revisions can and must be made. Support must continue for regular monitoring of several of the variables, including prices, availability of ganyu and collection or self-employment activities by household members. This document also serves as a blueprint for designing indicators for monitoring food security throughout the year. Details of crisis indicators are available in each of the forthcoming livelihood zone sections. As was done at the end of 2004, widespread nutritional screening exercises will be useful in comparing nutritional outcomes with vulnerability forecasts.

Finally, in order to understand clearly the important factors associated with vulnerability in Malawi, the MVAC needs to undertake deeper layers of analysis into poverty and the cause behind chronic vulnerability; this could take the form of further analysis on the IHS data as well as in-depth localised studies on population samples.

35 The Depth of Poverty map appears on page 32 of Malawi – an Atlas of Social Statistics. 36 This is adjusted up from MWK 8,000 to MWK 25,000 in the baselines because of inflation.

Malawi VAC Food Security Monitoring Report June 2005 Chitipa District, Chitipa Maize and Millet Livelihood Zone

Food Security Monitoring Report – June 2005 Chitipa District Chitipa Maize and Millet Livelihood ZoneMain Conclusions and Implications

The dry spell, which occurred from mid-January 2005 to mid-February, resulted in a reduction in crop production for this livelihood zone. Chisenga and Kavukuku EPAs were the worst affected. If the price of staple increases by 35% over the baseline price (13% up on last year), the sum of all the missing food entitlements in maize equivalent 980 MT or MWK 21.5 million. If the staple prices rise by 110% more than baseline (75% up on last year), then the sum of the missing food entitlements will be 1,120 MT and MWK 47.8 million, for maize and cash equivalents respectively.

Zone Description

The Chitipa Maize and Millet livelihood zone consists of five EPAs in Chitipa RDP (all EPAs, except for Misuku). Major crops grown in the zone include maize, sweet potatoes, tobacco, cassava, groundnuts, beans and finger millet. Millet is grown using the slash and burn system, a system that is being discouraged by government and has resulted in the crop becoming no longer the second largest in the food basket.

Households also keep chickens, guinea fowl, goats and, for the ‘middle’ and ‘better-off’ only, cattle. Many ‘poor’ households do not have goats.

Current Hazards

The dry spell has reduced the crop production substantially. It resulted in stunted growth in tobacco, abortive cobs in maize and the suspension of planting for roots and tuber crops. Although maize yields per hectare are estimated to be much lower because the dry spell occurred during tasselling stage, the total production is estimated to be only 10% lower than last year’s, due to the increase in area planted.

Two EPAs, Chisenga and Kavukuku, have been worst affected in terms of food production. Apart from maize, Food crops most affected are cassava and sweet potato (due to poor uptake and reduced area planted), groundnuts (due to late planting) and millet (reduced area planted).

Affected EPAs & Populations District EPAs Population

Chisenga 15,600 Chitipa Kavukuku 24,500 Total 40,100 Scenario 1 & 2 % ‘Poor’ 30-45%

Assumptions for this Projection % Of baseline

Crop production*

Maize S. Potatoes Cassava Millet

85-95% 15-25% 65-75% 10-25%

Ganyu for food 120-140% Ganyu for cash Availability 90-110% Payment 65-75% Scenario 1 market purchase price for maize† MWK 19-23/kg

Scenario 2 market purchase price for maize†

MWK 32-40/kg

Cost of basic non-food items† 130-140% Inputs 190-210% *Baseline = Production for 2002 †Baseline = average price 2002-03 ACY

Scenario 1 (Staple Price to be Approximately MWK19-26/kg) Food, Income and Expenditure Graphs for ‘Poor’ Households in Chisenga and Kavukuku EPAs

Sources of Food Sources of Cash Expenditure

0%

20%

40%

60%

80%

100%

120%

Baseline 2005-06

Cereal Crop Root CropsPulse & Gnuts Other CropsPurchase Ganyu

0%

20%

40%

60%

80%

100%

120%

Baseline 2005-06min.non-staple desirable

staple discretionaryexp. deficit

0%

20%

40%

60%

80%

100%

120%

Baseline 2005-06Self-EmploymentGanyuLivestock SalesCash Crop SalesOther Food Crop SalesCereal Crop Sales

Malawi VAC Food Security Monitoring Report June 2005 Chitipa District, Chitipa Maize and Millet Livelihood Zone

26

Outcome

The general reduction in food crop production means that ’poor’ households will not be able to sell these crops. This leaves ganyu for cash, the sale of firewood and a small amount of sale of livestock as the main alternative sources of income. However, pay rates of ganyu are expected to go down in tandem with the increased number of seekers, as the demand for it by employers is not likely to rise more than the normal opportunities that exist within in the communities. Much of the ‘poor’s food needs will have to be met with increased ganyu, which could go up by 27%, although pay rates are expected to decline by 30%.

This reduction has resulted in an initial food entitlement deficit of 25-35% for a population of 40,100 in scenario 1. The food entitlement deficit will go up to 25-40% for scenario 2.

Crisis Warning Indicators

Households from all the wealth groups are expected to migrate to the neighbouring Zambia in search for ganyu; this will have to be watched. Large amounts of food entering from Zambia is a good sign but if people are returning empty-handed then supplies over the border are drying up.

Sharp decreases in prices for products that are gathered or made from the bush, such as firewood, charcoal and grass articles, indicate an oversupply in these items. This represents a point where livelihoods and coping are beginning to fail.

An early rise in the main staple and root crop prices are an important indicator of pending failure.

Malawi VAC Food Security Monitoring Report June 2005 Karonga District, Central Karonga Livelihood Zone

Food Security Monitoring Report – June 2005 Karonga District Central Karonga Livelihood ZoneMain Conclusions and Implications

Karonga RDP has reported significant crop production losses particularly in Lupembe EPA, which is part of the Karonga Central Livelihood Zone. Root and tuber crops that would normally contribute significantly to food needs of the ‘poor’ have also not done well. This has resulted in a total missing food entitlement in maize and cash equivalents of 310 MT and MWK 6.4 million respectively if the price of staple increases by 35% above baseline (or 13% up on last year). If the price of the staple goes up by 110% from baseline (75% up on last year), as is envisaged if food is imported and sold at cost parity, then the missing food entitlement in maize and cash equivalents would go up to 350 MT and MWK 14.5 million respectively. Normally, local ganyu contributes only 1-10% of food needs but this year it is projected rise to 10-20%.

Zone Description

Central Karonga livelihood zone has two extension planning areas (EPAs), Lupembe and Mpata. It is a relatively productive maize and cassava zone that attracts migrant labour from other parts of the country in most years. It is less dependent on maize than other northern zones. Livestock holdings, especially of cattle, are high by national standards. Cash incomes are low, however, since tobacco is not grown and the zone is remote from the country’s larger urban markets. Most ‘middle’ and ‘better-off’ income is earned from the sale of food crops and livestock (cattle and pigs), while the ‘poor’ depend upon ganyu and self-employment (firewood, mat-making etc.).

Cotton (no baseline) is a new cash crop in the area starting two seasons ago because of the better prices. Production has been reduced to only 96% of last year’s, as the crop is drought tolerant. Income from cotton is expected to buy food for those households that grew it (not for the ‘poor’). However, a problem is that this season’s selling price is expected to be lower than last year.

Current Hazards

Data at the RDP indicate that maize production has gone down to 45%. Of the two EPAs, Lupembe is more severely affected by the prolonged dry spell that extended for three weeks from the second week of January. This was preceded by floods that occurred in December 2004.

Maize production has been affected by the dry spell as it occurred during the critical period when the maize was at its tasselling stage. Similarly, cassava, though drought tolerant, did poorly because of reduced area and poor uptake of the

Affected EPAs & Populations District EPAs Population Karonga Lupembe 9,600 Total 9,600 Scenario 1 & 2 % ‘Poor’ 30-40% Scenario 2 % ‘Middle’ 40-50%


Crop production (based upon RDP-level information)*

Maize Groundnuts S. Potatoes Cassava

40-50% 35-50% 20-30% 35-45%

Ganyu for food 140-160% Availability 90-110% Ganyu for cash Payment 70-80%


MWK 19-23/kg


MWK 32-40/kg

Cost of basic non-food items† 130-140% Inputs 190-210% *Baseline = average production 1998-2002 †Baseline = average price 2002-03 ACY

Scenario 1 (Staple Price to be Approximately MWK19-26/kg) Food, Income and ExpenditureGraphs for ‘Poor’ Households in Lupembe EPA


0%

20%

40%

60%

80%

100%

120%

Baseline 2005-06

Cereal Crop Root Crops

Pulse & Gnuts Other Crops

Purchase Ganyu

0%

20%

40%

60%

80%

100%

120%

Baseline 2005-06

Self-EmploymentGanyuLivestock SalesOther Food Crop SalesRoot Crop SalesCereal Crop Sales

0%

20%

40%

60%

80%

100%

120%

Baseline 2005-06

exp. deficitdiscretionarystapledesirablemin.non-staple

Malawi VAC Food Security Monitoring Report June 2005 Karonga District, Central Karonga Livelihood Zone

28

newly planted crop due to the dry spell. Crop performance this year is generally worse than last year, but better than the in 2002.

The crop failure will definitely result in low incomes for most farmers in the affected EPAs. This will in turn affect the prospects for ganyu for cash for the ‘poor’ households who derive their incomes from sale of their labour.

Outcome

Focus group discussions with farmers in Lupembe revealed that the ‘middle’ and ‘better-off’ would have adequate food for the next three months: April – June 2005. Thereafter they may resort to early harvesting of the cassava. Maize shortages are likely to push the maize prices up and the ganyu prices down.

Reduced maize production, reduced ganyu payments and reductions in purchasing power are expected to result in a 20-35% missing food entitlement for ‘poor’ households in the affected EPAs. Income from cotton sales could be used for food purchases, but this may not suffice due to the reduced yield and price uncertainties. Consequently, the contribution to food needs from food purchases or exchanges would decline from the normal 20-25% to 10-20%. The ‘poor’ would rely on ganyu which is expected to increase in it contribution to minimum food needs from 1-10% to 10-20%.


Increased demand for maize in local markets, coupled with higher prices in neighbouring Tanzania could drive up food prices. Consequently, prices for rice and other food crops grown on either side of zone could rise as well. If substantial formal inputs of maize are needed, prices may go as high as MWK 35/kg.

The ‘poor’ will start seeking ganyu locally and in more distant areas which are more diversified in crop production. They may increase their sales of firewood. As for the ‘middle’ and the ‘better-off’, a crisis warning may be the increased sales of livestock, although distress selling is not expected.

Malawi VAC Food Security Monitoring Report June 2005 Karonga and Nkhotakota Districts, Nkhata Bay Cassava Livelihood Zone

Food Security Monitoring Report – June 2005 Karonga and Nkhotakota Districts Nkhata Bay Cassava Livelihood ZoneMain Conclusions and Implications

The dry spell, which occurred from mid January 2005 to mid February 2005, also affected production in this largely food secure livelihood zone.

This reduction will likely result in total food entitlement deficit of 180 MT maize equivalent or MWK 3.8 million cash equivalent, assuming the price for staple stands at 35% above the baseline price (or 13% up on last year). If the price of cereal increases by 110% above baseline (75% up on last year) then the missing food entitlements are likely to be 550 MT or MWK 22.5 million in maize and cash equivalents, respectively. Much of the minimum food needs will have to be contributed by increased purchases and ganyu, which are likely to change from 10-20% to 20-30% and 1-10% to 5-15%, respectively.

Zone Description

The whole zone runs from Karonga South and a part of Rumphi, through Nkhata Bay, to northern Nkhotakota. With high rainfall but poor soils, cassava is the dominant crop in this zone. The zone is normally characterised as ‘food-rich’ but ‘cash-poor’, since there are few sources of income available besides the sale of crops, and there is only a limited market for the bitter variety of cassava grown in the zone. Maize, rice and bananas are grown in addition to cassava, and the sale of these contributes significantly to local incomes. Given its drought resistance, cassava plays a key role in ensuring food security, with the zone attracting migrant labour from other zones when these are affected by food shortages. Most households in the ‘middle’ and ‘better-off’ category indicated that they will have enough food for the next six months. In addition to crop sales, people also fish in order to boost their incomes. Fish are a source of food to the zone as well.

Current Hazards

The dry spell reduced the crop production. It resulted in stunted growth in tobacco, abortive cobs in early-planted maize and the suspension of planting of root and other crops. Although the yields in maize were reduced, production (for the ‘middle’ and ‘better-off’ was raised due to increased area planted.

Outcome

The reduction in crop production means lost income from the sale of


Vinthukutu Nkhata-Bay Nyungwe 39,900

Nkhotakota Nkhunga 24,900 Total 64,800 Scenario 1 & 2 % ‘Poor’ 25-40%


Crop production*

Maize Groundnuts S. Potatoes Cassava

55-65% 20-30% 35-45% 80-90%

Availability 90-110% Ganyu Wage 100-120% Scenario 1 market purchase price for maize† MWK 19-23/kg

Scenario 2 market purchase price for maize† MWK 32-40/kg

Cost of basic non-food items 130-140% Inputs 190-210% *Baseline = average production 1998-2002 †Baseline = average price 2002-03 ACY

Scenario 1 (Staple Price to be Approximately MWK19-26/kg) Food, Income and ExpenditureGraphs for ‘Poor’ Households in Vinthukutu and Nkhunga EPAs


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min.non-staple desirablestaple discretionaryexp. deficit

Malawi VAC Food Security Monitoring Report June 2005 Karonga and Nkhotakota Districts, Nkhata Bay Cassava Livelihood Zone

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crops. Ganyu for cash and the sale of firewood are the main alternative sources of income. However, the ganyu wage rate is expected to remain constant, as the demand by employers will not increase substantially.

In scenario 1, ‘poor’ households are likely to lack 0-10% of their minimum food energy requirements, while in scenario 2, ‘poor’ households are likely to lack 5-15% of their minimum food energy requirements.


Early searching for ganyu by the ‘Poor’ and early rise in the main staple crop prices are the most important set of indicators.

Malawi VAC Food Security Monitoring Report June 2005 Rumphi District, Western Rumphi and Mzimba Livelihood Zone

Food Security Monitoring Report – June 2005 Rumphi District Western Rumphi and Mzimba Livelihood ZoneMain Conclusions and Implications

The zone experienced a significant drop in maize and tobacco production due to the fertiliser shortages and the prolonged dry spell which lasted for over a month from the second week of January 2005. If the staple price goes 35% above the baseline price (or 13% up on last year), the total missing food entitlement is likely to be 1,000 MT in maize or MWK 21.1 million in cash equivalents. If the price rises by 110% above baseline (75% up on last year), the total entitlement deficit will increase to 1,830 MT or MWK 75.3 million in maize or cash equivalents, respectively.

Zone Description

Western Rumphi and Mzimba Livelihood Zone is generally productive and self sufficient in food. Households rely mainly on maize and groundnuts for food and tobacco for cash, and there is little diversification to other crops. Tobacco is heavily produced in Bolero and parts of Muhuju EPA, and Rumphi is referred to as the ‘Kasungu of the North’ because of these two areas.

Current Hazards

The dry spell hit the district for a period of six weeks, affecting maize, tobacco and other crops. Bolero, Katowo, Chiweta and parts of Muhuju EPAs were the most affected. Yields for maize were 778kg/ha for Muhuju and 907kg/ha for Bolero from the second round crop estimates. The drop in burley tobacco production is exacerbated for smallholders due to their inaccessibility to fertilizer.

Outcome

Most households sold their tobacco to intermediaries, so they can get basic necessities, thinking it was unnecessary waiting for the auction floors just to sell less than half a bale.

Field data indicates that this year’s missing entitlements are likened to those of 2001-2002. In scenario 1, the poorest households are expected face missing entitlements of 15-25% and in scenario 2 they are expected to miss 30-45% of their minimum food energy needs.


The ‘poor’ are expected to resort early to searching for ganyu in the nearby tobacco estates for survival. This and an early rise in the main staple crop prices are the main indicators.


Bolero Katowo

58,500

Rumphi Muhuju

Only households residing in the area near Rumphi Town, number unknown

Total 58,500 Scenario 1 & 2 % ‘Poor’ 30-45%


Crop production*

Maize Groundnuts S. Potatoes Tobacco

35-45% 35-50%

0% 70-80%

Tobacco sales† Price 120-130% Ganyu for food 65-75%

Availability 90-110% Ganyu for cash Payment 100-120% Scenario 1 market purchase price for maize† MWK 19-23/kg


Cost of basic non-food items 130-140% Inputs 190-210% *Baseline = average production 1998-2002 †Baseline = average price 2002-03 ACY

Scenario 1 (Staple Price to be Approximately MWK19-26/kg) Food, Income and Expenditure Graphs for ‘Poor’ Households in Bolero, Katowo and parts of Muhuju EPAs


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Baseline 2005-06

Livestock SalesCash CropsOther Food Crop SalesRoot Crop Sales

Malawi VAC Food Security Monitoring Report June 2005 Nkhotakota District, Northern Lakeshore Livelihood Zone

Food Security Monitoring Report – June 2005 Nkhotakota District Northern Lakeshore Livelihood ZoneMain Conclusions and Implications

The three to four week dry spell reduced production of maize, rice and cassava. Contributions to food requirements from purchases will have to increase form 25-35% to 50-60% and 25-40% to 45-60%, for the ‘Poor’ and the ‘Middle’ respectively. In order to maximise their food, the ‘Poor’ households will have to increase expenditure on staple from MWK 8,200 to MWK 18,600. They will rely on fishing or fishing ganyu to pay for this. A large proportion of the income for both the ‘Poor’ and the ‘Middle’ will also come from self-employment and petty trade. The total missing food entitlement is expected to be 870 MT in maize or MWK 25.0 million in cash, assuming an increase in the price of the staple of 35% over and above the baseline price (or 13% up on last year). This will go up to 2,800 MT in maize equivalent or MWK 157.9 million in cash equivalent if the price increases by 110% over and above baseline (75% up on last year).

Zone Description

The zone covers a thin strip of land with a width of approximately 5-6 km, extending from the lakeshores of Nkhata Bay Boma to the Nkhotakota-Salima boundary. Cassava, maize and rice are the major food crops in the zone. The zone also grows quite a lot of bananas, which are mostly for sale. However, the bunchy top disease has in recent years almost wiped out the banana crop in the zone.

Selling paddy and fishing are the main economic activities in the area. ‘Poor’ households earn income from fishing ganyu for the ‘middle’ or ‘better-off’. Normally, cassava and maize complement each other, with maize providing food for the first three months after harvest.

Current Hazards

The dry spell started from half way in the rainy season for three to four weeks, greatly affecting maize, rice and cassava production. The maize crop was at tasselling and cobbing stages and the RDP estimates its production going down by 36% since last year. The new cassava crop failed to establish. Rice, the main source of income, has significantly been affected and it is estimated that the production will go down by 31% for the RDP since last year. This is due to late transplanting after the seedlings had overgrown in the field followed by a short-lived resumption of rains. Winter cropping, which would normally provide extra maize, is unlikely due to low underground water tables. Hippos threaten people entering the lake and growing rice in the fields along the lake.


Nkhunga 24,900Linga 94,000Nkhotakota Zidyana 31,900

Total 150,800Scenario 1& 2 % ‘Poor’ 25-40%


Crop production* Maize Cassava Rice

45-55% 70-80% 10-15%

Rice sales price† 110-130% Availability 80-100% Ganyu Payment 100-120%



Cost of basic non-food items† 130-140% Inputs 190-210% *Baseline = average production 1998-2002 †Baseline = average price 2002-03 ACY

Scenario 1 (Staple Price to be Approximately MWK19-26/kg) Food, Income and ExpenditureGraphs for ‘Poor’ Households in Nkhunga, Linga and Zidyana EPAs


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Malawi VAC Food Security Monitoring Report June 2005 Nkhotakota District, Northern Lakeshore Livelihood Zone

33

Outcome

‘Poor’ households are most likely to experience missing entitlements this year; this will kick in during the last three months of the year.

People have adequate cassava up to June for the ‘poor’, August and September for the ‘middle’ and ‘better-off’, successively. They will then resort to the immature cassava crop and ganyu for survival. Since ganyu will be difficult to find within the communities, migration to places that may have food is likely to take place.

Missing food entitlements for ‘poor’ households are expected to be 5-10% of their minimum food energy requirements in scenario 1, rising to 20-30% of their minimum requirements in scenario 2.


Early searching for ganyu by the ‘Poor’ and early rise in the main staple crop prices are the best warning for a pending crisis.

Malawi VAC Food Security Monitoring Report June 2005 Kasungu, Ntchisi, Dowa, Mchinji, Lilongwe and Dedza Districts, Kasungu Lilongwe Plain Livelihood Zone

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Food Security Monitoring Report – June 2005 Kasungu, Ntchisi, Dowa, Mchinji, Lilongwe and Dedza Districts Kasungu Lilongwe Plain Livelihood ZoneMain Conclusions and Implications

All the RDPs in the Lilongwe-Kasungu Plain livelihood zone experienced reductions in the yield and production of the three major crops: tobacco, maize and groundnuts. The lost crop production will have an effect on the availability of ganyu, an important source of food and cash for the ‘poor’.

The problem was caused by the lack of availability and high prices for inputs, especially fertilizer. This was compounded by an erratic rainfall pattern that ended in prolonged dry spells. For analysis, the zone was divided into two groups: Group A and Group B, each containing EPAs with roughly the same magnitude of problem. If staple purchasing prices continue to rise at present inflation rates (a price of MWK 19-23 per kilogram), the total missing food entitlement is likely to be 11,110 MT in maize equivalent or MWK 198.8 million in cash equivalent for the EPAs in Group A, and 5,430 MT or MWK 97.2 million for EPAs in Group B, respectively. If staple purchase prices are based on import parity (MWK 32-40 per kilogram), as in Scenario 2, then the total missing food entitlement for EPAs in Group A is likely to become 14,420 MT or MWK 505.0 million in maize and cash equivalents, respectively. Those in Group B will be 9,210 MT and MWK 322.6 million, respectively.

Zone Description

With the exception of Mayani EPA in Dedza and Chipuka EPA in Ntchisi where a significant percentage of additional income is generated from onions and garlic respectively, the zone is otherwise uniform in its main sources of food and income. ‘Better-off’ and ‘middle’ households rely almost exclusively on local crop production and, to a very limited extent, on local livestock production. Most of the income in this zone comes from the sale of tobacco. In a ‘normal’ year, when there is surplus maize, other income sources are maize, groundnuts and Soya sales. However, almost the entire surplus is generated by the ‘better-off’, whereas the poorest 25% of household are perpetually in food production deficit and rely on ganyu for a better part of the year. Almost everyone grows tobacco, although the level of production differs according to wealth. Tobacco accounts for 65-85% income for all wealth groups.

Current Hazards

EPA-level crop data shows that maize production, when compared with baseline, for Group A was worse (35-50%) than Group B (60-70%). There is also an expected decline in

Affected EPAs & Populations Group District EPAs Population

Ming’ongo 72,900 Ukwe 68,200 Chileka 95,700

Lilongwe

Malingunde 66,400 Chamama 110,500

Kasungu Kaluluma 141,500 Mikundi 66,900

Mchinji Mkanda 89,500 Lobi 62,400

Dedza Linthipe 65,100 Chivala 48,500

Dowa Mponela 77,600

Total 965,200

A

Scenario 1 & 2 % ‘Poor’ 20-30% Mpingu 71,300 Mng’wangwa 64,900 Mpenu 75,100 Chitekwele 92,900

Lilongwe

Chiwamba 74,100 Dedza Mayani 67,900

Kalira 137,000 Chipuka 20,900 Ntchisi Malomo 31,000 Mvera 8,700

Dowa Bowe 59,000

Mchinji Chioshya 65,600 Total 768,400

B

Scenario 1 & 2 % ‘Poor’ 20-30%

Assumptions for this Projection % Of Baseline – Group A

% Of Baseline – Group B

Crop production (based upon district-level information)

Maize* Groundnuts* Tobacco* Other crops*

35-50% 40-55% 70-80% 85-100%

60-70% 110-120% 70-80% 55-65%

Tobacco sales price 120-130% 120-130% Availability 75-85% 75-85%

Ganyu Payment 90-105% 90-105%

Other sources of food and income 90-105% 90-105% Scenario 1: Market purchase price for maize† MWK 19-23/kg

Scenario 2: Market purchase price for maize† MWK 32-40/kg

Cost of basic non-food items† 130-140% 130-140% Other prices 130-140% 130-140% *Baseline = average production 1998-2002 †Baseline = average price 2002-03 ACY

Malawi VAC Food Security Monitoring Report June 2005 Kasungu, Ntchisi, Dowa, Mchinji, Lilongwe and Dedza Districts, Kasungu Lilongwe Plain Livelihood Zone

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tobacco production (roughly, by a quarter) in EPAs within both groups. Group A also experienced a decline in groundnut production (40-55%), while Group B got more than the baseline this year (110-120%).

Other crops such as sweet potatoes have also been affected due to lack of moisture in the soil and prospects for any winter harvest look bleak due to the reduction in moisture levels in the Dambo soils.

Ganyu for food is expected to be more scarce because the ‘middle’ and ‘better-off’ do not have enough of their own maize. It is also expected that because of shortfalls the demand for ganyu will be higher, putting pressure on pay rates, which are not expected to keep up with inflation.

Livestock levels in this zone have declined over the years especially for the ‘poor’ Households. Hence, very few ‘poor’ households have any livestock like chickens or goats which they can sell and use the income to offset the deficit.

The reduction in the major crops, coupled with the scarcity of ganyu and the expected reduction in ganyu pay rates will hit the ‘poor’; in the EPAs in Group A they are expected to lack 15-30% of their food energy entitlements, while group B are expected to lose 5-15%.

If we assume that the price of maize increases to a price based on import parity (scenario 2,), then the ‘poor’ in the EPAs in Group A will have a deficit of 20-35% and those in Group B will face a deficit of 10-25%. Thus, the change in of price from scenario 1 to scenario 2 will increase the missing entitlements of the ‘poor’ of Group B more than those of Group A. Both scenarios will not affect the ‘middle’ and ‘better-off’ wealth groups’ in EPAs of either Group A or Group B.


An unusual migration of people in search of ganyu is an early indicator of an impending crisis. However, care needs to be exercised in interpreting migration data as seeking labour quite far (and over international borders) from households’ home villages can be quite normal and may be triggered not by hunger but rather by more attractive pay rates. The majority of the ‘poor’ households in this zone have already started engaging in ganyu but it was indicated that ganyu availability has declined. This is the case even in those EPAs close to the Zambian border. It was indicated that similar conditions of food insecurity prevail in Zambia close to the Malawian border. Migration to urban centres may start happening sometime during the year if opportunities for ganyu are exhausted in rural areas.

A significant increase in grain prices beyond the inflation-adjusted level, as indicated in scenario 2, will have an immediate impact on household food security.

Livestock distress sales (unsustainable selling or selling that would constrain recovery) also indicates a looming crisis. Although livestock selling is only an option for the ‘middle’ and ‘better-off’ households, the fact that they are doing it would indicate their lack of resources for employing and supporting the ‘poor’. Consideration does, however, need to be given to the fact that there may be a surge of selling as the ‘better-off’ and ‘middle’ invest in the forthcoming cropping season.

MFEs as Percent Energy Requirement MFE for the ‘poor’ Scenario 1 Scenario 2 Group A 15-30% 20-35% Group B 5-15% 10-25%

Outcome

Scenario 1 (Staple Price to be Approximately MWK19-26/kg) Food, Income and Expenditure Graphs for ‘Poor’ Households in Ming’ongo, Ukwe, Chileka, Malingunde, Chamama, Kaluluma,Mikundi, Mkanda, Lobi, Linthipe, Chivala and Mponela EPAs


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Malawi VAC Food Security Monitoring Report June 2005 Nkhotakota, Salima, Dedza, Ntcheu and Mwanza Districts, Rift Valley Escarpment Livelihood Zone

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Food Security Monitoring Report – June 2005 Nkhotakota, Salima, Dedza, Ntcheu and Mwanza Districts Rift Valley Escarpment Livelihood ZoneMain Conclusions and Implications

The early cessation of rains that adversely affected the cereal crops did not spare cotton either, the zone’s main cash crop. The zone was divided into two based on the severity of the impact of the early tailing off the rainfall. Group A covers the western (inland) part of Zidyana and Mwansambo EPAs in Nkhotakota district, Chinguluwe and parts of Khombedza, Tembwe and Chipoka EPAs in Salima district, parts of Mtakataka and Golomoti in Dedza district and Neno EPA in Neno district. Group B includes Sharpevale, Kandeu, Bilira, Nsipe and Manjawira EPAs in Ntcheu district. Group A is the worst affected in the zone where the ‘poor’ households only managed to produce about 20-30% of their normal maize production and are expected to attain half of their baseline cotton production while in the ‘poor’ in Group B managed to produce about 55-65% of their normal maize production.

These factors will adversely affect household incomes and their ability to buy food. If maize prices increase at the average inflation rate (or 35% higher than baseline price) to MWK 19-23/kg during the period of December 2005 to February 2006 when most households tend to buy maize, the total missing food entitlements are expected to be 15,180 MT in maize equivalent or, MWK 348.0 million in cash equivalent for Group A. The total missing entitlements for Group B would be 4,450 MT and MWK 101.9 million in maize and cash equivalents, respectively. Assuming that the maize is imported at cost parity, the price would to MWK 32-40/kg (or 110% higher than baseline), then EPAs in Group A would have a total missing food entitlement of 30,350 MT or MWK 1,367.2 million in maize and cash equivalents, respectively. EPAs in Group B would be missing 16,140 MT or MWK 724.5 million, respectively.

Zone Description

This zone stretches along the slopes and foot of the western rift escarpment from south-east Nkhotakota district through Dedza and Ntcheu in Central Region down to Neno district in Southern Region. It is a relatively low-lying area characterised by high temperatures, especially during the summer months of August to September. Cotton is the main cash crop in the area. The area is generally food secure with the ‘poor’ households being able to meet almost all (97%) their minimum food requirements with ‘middle’ and ‘better-off’ wealth getting above their minimum food requirements during normal years. Livestock, mainly goats, play a very important role as a source of income for buying food. Cattle are also important but are mainly confined to the ‘better-off’ households. The ‘poor’ households also depend heavily on ganyu to obtain cash to buy food.


Zidyana 31,900 Nkhotakota Mwansambo 52,200 Khombedza 62,500 Tembwe 24,200 Chinguluwe 39,200 Salima

Chipoka 37,900 Mtakataka 24,100 Dedza Golomoti 16,200

Neno Neno 52,500 Total 340,700 Scenario 1 & 2 % ‘Poor’ 35-45% Scenario 1 & 2 % ‘Middle’ 40-55%

A

Scenario 2 % ‘better-off’ 10-20% Bilira 59,700 Manjawira 92,400 Nsipe 101,000 Kandeu 16,100

Ntcheu

Sharpevale 71,100 Total 340,300 Scenario 1 & 2 % ‘Poor’ 35-45%

B

Scenario 1 & 2 % ‘Middle’ 40-55%

Assumptions for this Forecast % of baseline – Group A

% of Baseline – Group B

Crop production*

Maize Groundnuts S. Potatoes Cassava Rice Cotton

20-30% 15-30% 10-25% 15-25% 0-10%

45-55%

26%1

23% 17% 20% 6% 66%

Cotton sales price† 110-130% Ganyu for food 60-70% Ganyu for cash Availability 90-110% Payment 100-120% Other sources of food and income 100%



Cost of basic non-food items† 130-140% Inputs† 190-210% *Baseline = average production 1998-2002 †Baseline = average price 2002-03 ACY


37

Current Hazards

The most important factor that will affect household food security in the zone is the drop in crop production as a result unfavourable weather conditions and all crops suffered the effects of the abrupt end of the rainfall season. Shortages in fertilisers did not help either, although the rainfall failure was so abrupt and complete that in this case good input availability would not have been sufficient.

Encouraged by favourable prices last season, many households in the area increased their cotton cultivation this season. Since most of them depend on cotton for income to buy food when their own-produced food runs out, threats to cotton production could make the households much more vulnerable to food insecurity. Although the cotton price is above baseline, it fetches MWK 18/kg this season compared with MWK 25/kg last year (a drop of 28%). This has frustrated cotton farmers, some of whom have indicated that they will not grow the crop again next season if the price does not improve.

Despite increased sales, income from livestock is expected to drop as prices decrease when households sell their animals to obtain cash for buying food. There will also be an increase in the supply of ganyu as poorer households quickly finish their own produced food this season.

Outcome

All these factors culminate in increased household vulnerability to food insecurity in the area. For those that have, income from increased livestock sales (mainly goats) will not be enough to offset the deficits for the ‘poor’ and ‘middle’ wealth group because of the expected huge drops in livestock prices and the expected maize price increase. Although households will probably do more ganyu to obtain cash to buy food, this will be compromised by the drop in ganyu rates due to increased labour supply because of the increased number of households seeking work.

Households in the ‘poor’ and ‘middle’ wealth groups in Group A EPAs are expected to experience missing food entitlements of 15-30% and 10-25% of their minimum energy needs, respectively, in scenario 1. The

Scenario 1 (Staple price approximately MWK19-23/kg) graphs for ‘Poor’ households in Zidyana, Mwansambo, Khombedza, Tembwe, Chinguluwe, Chipoka, Mtakataka, Golomoti andNeno EPAs (Group A)

Sources of Food Expenditure

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Baseline 2005-06min.non-staple desirablestaple discretionaryexp. deficit

Scenario 1 (Staple price approximately MWK19-23/kg) graphs for ‘Middle’ households in Zidyana, Mwansambo, Khombedza, Tembwe, Chinguluwe, Chipoka, Mtakataka, Golomoti andNeno EPAs (Group A)


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min.non-staple stapledesirable discretionaryexp. deficit


38

‘better-off’ will be able to meet their minimum food energy requirements by increasing their food purchases. In EPAs in Group B, households are expected to experience lower missing entitlements with ‘poor’ households missing 5-15% and the ‘middle’ wealth group missing 0-5%. The ‘better-off’ households will again be able to meet their minimum food requirement.

Under scenario 2, the missing entitlements will increase to 35-45% for ‘poor’ and 30-40% for ‘middle’ households in EPAs in Group A. Even the ‘better-off’ will also experience a food intake deficit of 10-20%. In EPAs in Group B, the ‘better-off’ households will not face a food intake deficit but ‘poor’ and ‘middle’ households are expected to experience missing entitlements of about 25-35% and 15-25%, respectively.


Increased demand in both local and ADMARC markets. Long queues of people waiting to buy in ADMARC markets are signs of serious food security problems. There will be rapid increases in maize prices in the local markets.

An increase in the number of people looking for ganyu and reduced ganyu rates are all signs of food security problems as are increased livestock sales and reduced livestock prices.

MFEs as Percent Energy Requirement Scenario 1 Scenario 2 MFE

‘Poor’ ‘Middle’ ‘Poor’ ‘Middle’ ‘Better-Off’ Group A 15-30% 10-25% 35-45% 30-40% 10-20% Group B 5-15% 0-5% 25-35% 15-25%

Malawi VAC Food Security Monitoring Report June 2005 Salima, Dedza and Mangochi Districts, Southern Lakeshore Livelihood Zone

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Food Security Monitoring Report – June 2005 Salima, Dedza and Mangochi Districts Southern Lakeshore Livelihood ZoneMain Conclusions and Implications

The early cessation of rains in the area adversely affected crop production thereby negatively affecting household food security in the area. This is generally a food production deficit area and households in the ‘poor’ and the ‘middle’ wealth groups are unable to meet their food requirements in a normal year and have to supplement it with purchases, which they fund through money earned from fishing or fishing ganyu. Even the well-off households have to supplement their food production with about 9% of food purchases to meet their food requirements in a normal year. This year, ‘poor’ households will not be able to purchase enough food to offset the deficit created by the drop in crop production and their total missing food entitlements will be 5,090 MT in maize or MWK 136.7 million in cash equivalent, provided that maize prices rise at parity with current average inflation rates (a price of MWK 19-23/kg). If maize is sold at import parity (a price of MWK 32-40/kg), the total missing entitlement will be 13,040 MT or MWK 609.0 million in maize and cash equivalents, respectively. The ‘middle’ and ‘better-off’ households are expected to meet their minimum food requirements because of higher income levels.

Zone Description

The Southern Lakeshore zone is a narrow strip about five kilometres wide surrounding the southern end part of Lake Malawi. The zone starts in areas bordering the lake in Salima district and stretches through Dedza and Mangochi districts. This area also covers the principal fishing area of the lake, which is at its shallowest. Consequently, households are highly dependent on fishing for their incomes. The ‘poor’ and ‘middle’ wealth group households obtain their cash through provision of various types of fishing labour or ganyu while the ‘better-off’ households obtain their cash from the fish sales (the ‘better-off’ own boats and equipment). Since this is a crop production deficit area, fishing income is used to buy food, including staple. Efficient operation of food markets is therefore crucial in the zone and household income levels and food prices play an important role in determining of household food security. Various crops are grown including maize, rice, groundnuts, cassava, sweet potatoes, etc.

Current Hazards

The abrupt cessation of the rains towards the end of January happened when most of the crops were at the critical development stage such as maize tasselling, transplanting of rice, uptake of cassava and sweet potatoes, pegging in groundnuts, which is why production was so severely affected. Shortages in inputs did not help either, although the dry spells were such that there lack of availability did not make that much difference. Hence, many households in the area will depend on the market for food and if supplies in the markets are reduced, prices will rise.

Baseline average prices used in the analysis is for the period December 2002 to February 2003. Agricultural ganyu rates are expected to drop due to excess labour supply, as many households will be looking for ganyu to obtain cash to buy food. Livestock prices are also expected to drop as households become forced to sell their livestock to obtain cash to buy food. However, fishing income is expected to remain fairly stable although there are concerns that fish stocks are slowly dwindling in the lake which poses a long-term threat.


Kombedza 62,500 Tembwe 24,200 Salima Chipoka 37,900 Mbwadzulu 25,800 Nasenga 52,000 Namkumba 23,000 Mangochi

Lungwena 31,900 Mtakataka 24,100 Dedza Golomoti 16,200

Total 297,600 Scenario 1 & 2 % ‘Poor’ 45-55%



Maize Groundnuts S. Potatoes Rice Cassava

25-45%

10-15% 10-15% 0-10%

45-55% Ganyu for food 40-50%

Availability 140-160% Agricultural ganyu Payment 55-65% Fishing ganyu Availability 95-105% Payment 95-105% Other sources of food and income 95-105% Scenario 1 market purchase price for maize† MWK 19-23/kg


Cost of basic non-food items† 130-140% Other prices† 190-210% *Baseline = average production 1998-2002 †Baseline = average price 2002-03 ACY

Malawi VAC Food Security Monitoring Report June 2005 Salima, Dedza and Mangochi Districts, Southern Lakeshore Livelihood Zone

40

Outcome

Although the zone is generally a deficit area in terms of crop production, households are able to significantly boost their food access from maize purchases using off-farm income, especially fishing. This is why that despite the area experiencing significant drops in crop production; only ‘poor’ households are expected to suffer missing entitlements under scenario 1, of 10-25%. Even with the price increase in scenario 2, the ‘middle’ and ‘better-off’ households still will not lack entitlements, as they are able to meet their requirements from increased maize purchases using income generated from fishing. However, the missing food for the ‘poor’ households is expected to increase to 35-45%.


The most important indicator of impending food crisis will be a rapid increase in staple food price which hinders the ability of the households to buy food.

Increase in livestock sales coupled with huge drops in livestock prices are often an indicator of food crisis in the zone. Livestock prices tend to drop when households become forced to sell their livestock to obtain cash to buy food.

Another indicator is the increase in the number of people looking for ganyu, very often much earlier than usual. This in turn forces ganyu rates to go down, thereby affecting household incomes and consequently their ability to buy food.

Scenario 1 (Staple price approximately MWK19-23/kg) graphs for ‘Poor’ households in Kombedza, Tembwe, Chipoka, Mbwadzulu, Nasenga, Namkumba, Lungwena, Mtakataka andGolomoti EPAs


0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Baseline 2005-06Cereal Crops Root CropsPulse & Gnuts PurchaseGanyu

0%

20%

40%

60%

80%

100%

120%

Baseline 2005-06Self-EmploymentGanyuLivestock SalesOther Food Crop SalesRoot Crop SalesCereal Crops

0%

20%

40%

60%

80%

100%

120%

Baseline 2005-06


Malawi VAC Food Security Monitoring Report June 2005 Mangochi, Zomba, Chiradzulu, Blantyre and Thyolo Districts, Shire Highlands Livelihood Zone

41

Food Security Monitoring Report – June 2005 Mangochi, Zomba, Chiradzulu, Blantyre and Thyolo Districts Shire Highlands Livelihood ZoneMain Conclusions and Implications

The EPAs in the zone are divided into two groups, each of which is equally affected. Group A comprises Ntonda and part of Chipande EPAs in Blantyre, Lungwena, Ntiya, Katuli, Masuku and Maiwa EPAs in Mangochi and Nyambi EPA in Machinga. Group B comprises Mbonechera and Domasi EPAs in Machinga, Malosa, Dzaone, Thondwe and Chingale EPAs in Zomba, Mombezi, Mbulumbudzi and Thumbwe EPAs in Chiradzulu, Chipande EPA in Blantyre and Matapwata EPA in Thyolo. Almost all areas in the zone experienced heavy rains during the first half of the season followed by the prolonged dry spell from late January to February 2005. This poor rainfall distribution pattern was made worse by shortages in inputs, especially fertiliser, needed to combat soil leeching that occurred in the first half of the season due to heavy rainfall. The EPAs in Group A have, however, received some showers up to early March 2005.

Consequently, the ‘poor’ and ‘middle’ groups in the zone have experienced significant reductions in crop production. If, as in scenario 1, maize purchasing prices rise at a rate equal to the current average inflation rate (the price would be MWK 19-23/kg), then the total missing food entitlement in the EPAs in Group A is 7,170 MT in maize equivalent or MWK 170.9 million in cash equivalent. In Group B it is 18,040 MT or MWK 430.4 million for maize and cash equivalents, respectively.

If future maize purchasing prices are based on import cost parity (prices of MWK 32-40/kg) or as in scenario 2, then the total missing entitlements in EPAs in Group A would be 12,137 MT or MWK 566.9 million in maize and cash equivalents, respectively. The maize and cash equivalents in the EPAs of Group B would be 30,700 MT or MWK 1,433.7 million, for maize and cash equivalents, respectively.

Zone Description

This is a large zone covering one of the most densely populated portions of the country. This zone averages about 1,200 – 1,400 metres in elevation and mean annual precipitation ranges from 1,000 – 1,400 mm. Land holding size is a significant constraint to agricultural production and livestock holdings are relatively low. For the ‘better-off’ and ‘middle’, the primary source of food is own production, accounting for up to 40-85% of annual food needs. The ‘poor’, however, obtain just over 20% of their annual food needs from their own crops.


Lungwena 31,900 Ntiya 72,100 Katuli 54,800 Masuku 60,000

Mangochi

Maiwa 83,000 Machinga Nyambi 38,000 Blantyre Ntonda 93,800 Total 433,600

A

Scenarios 1 & 2 % ‘Poor’ 25-40% Mbonechera 42,900

Machinga Domasi 37,400 Malosa 56,700 Dzaone 145,300 Thondwe 115,000

Zomba

Chingale 47,200 Mombezi Mbulumbudzi

123,700 Chiradzulu

Thumbwe 77,600 Blantyre Chipande 42,800 Thyolo Matapwata 19,100 Total 707,700 Scenarios 1 & 2 % ‘Poor’ 25-40%

B

Scenario 2 % ‘Middle’ 40-55%

Assumptions for this Projection

% of Baseline (Group A)

% of Baseline (Group B)


Maize Groundnuts S. Potatoes Cassava Pulses

55-65% 50-60% 40-55% 50-65% 50-60%

35-45%

25-35% 15-30% 50-60% 35-45%

Ganyu for food 75-85% 75-85% Ganyu for cash Availability 95-105% 65-75% Payment 80 – 100% 105-115% Other sources of food and income 95-105%

Scenario 1: market purchase price for maize† MWK 19-23/kg




42

Purchase is the largest source of food for the ‘poor’. Their main source of income is agricultural employment (Ganyu), whereas for the ‘better-off’ it is crop sales.

Current Hazards

Like elsewhere, this livelihood zone experienced heavy rains during the first half of the season and a prolonged dry spell from late January to February 2005. The ‘poor’ and ‘middle’ groups in the zone lost significant crop production. Some of the factors contributing to the reduction include delayed planting time, access to fertilizer and fertilizer availability, soil leeching due to heavy rainfall in the first half of the season and moisture stress due to prolonged dry spell. The fertilizer scarcity and high fertilizer prices exacerbated the climatic and environmental shocks, accentuating leeching during the heavy rains, and slowing growth so that plants were harder struck by the dry spells.

The dry spells hit the maize crop at the cobbing and tasselling stages while groundnuts were at their flowering stage. Even drought tolerant crops such as sorghum and pigeon peas were affected by moisture stress. Roots and tubers were also affected; the cassava planted last year did not develop good tubers due to moisture stress and the newly planted crop dried up –particularly in the uplands. Sweet potato was planted at very small scale due to the prolonged dry spell which occurred during the planting period. The ‘poor’ are expected to produce only 40-60% of their baseline maize production, sweet potatoes 20-50%, cassava 50-65%, groundnuts 30-55%, and pulses around 40%.

Ganyu is expected to decrease by 20% for food and 30% for cash, compared with baseline. This is due to the ‘better-off’ and ‘middle’ households lacking resources to afford the extra employment created by the ‘poor’ households seeking more work.

Outcome

The above hazards will particularly reduce household food accessibility for the ‘poor’.

In Scenario 1, the ‘poor’ households are expected to experience missing food entitlements of 15-25% and 30-40% for EPAs in Group A and Group B, respectively. The missing entitlements are caused by the drop in the contribution made by crops to food intake from approximately 55% to 30% for Group A EPAs and from approximately 55% to 23% for Group B to energy requirements, which households are unable to make up with increased purchases due to their very low income and asset bases. However, for Group A, the ‘poor’ can expand on ganyu since they are either closer to Blantyre City or the Mozambique border.

In scenario 1 the ‘middle’ households will not experience a deficit due to their high purchasing power mainly derived from greater asset holdings and from petty trading.

In Scenario 2, the missing entitlements for the ‘poor’ will increase to 30-40% for EPAs in Group A and to 40-55% for those in Group B. The ‘middle’ in Group B are also expected to miss 5-10% of their entitlements in scenario 2, due to higher staple food purchase prices which reduce their food access.


It is expected that many households will run out of food much earlier this season than they normally do.

Scenario 1 (Staple price approximately MWK19-23/kg) graphs for ‘Poor’ households in Mbonechera, Domasi, Malosa, Dzaone, Nasenga, Thondwe, Chingale, Mombezi, Mbulumbudzi, Thumbwe, Chipande and Matapwata EPAs (Group B)


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120%

Baseline 2005-06


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100%

120%

140%

Baseline Response


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20%

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80%

100%

120%

140%

Baseline 2005-06

Self-EmploymentGanyuLivestock SalesOther Food Crop SalesRoot Crop Sales


43

Winter production, which does not normally contribute significantly to food access, will not be expandable due to moisture stress.

Early rises in food prices are an important indicator to watch for impending crisis.

There is an expected increase in the number of people looking for ganyu both locally for cash and across the border in Mozambique in search of ganyu for food. It is also very likely that there will be labour migration from the zone to other zones within the country particularly to the tobacco estates. A low ganyu payment rate is important to monitor.

Livestock prices could go down significantly later in the year, which must be monitored.

Malawi VAC Food Security Monitoring Report June 2005 Mangochi District, Phirilongwe Hills Livelihood Zone

44

Food Security Monitoring Report – June 2005 Mangochi District Phirilongwe Hills Livelihood Zone

Main Conclusions and Implications

Most EPAs in this livelihood zone experienced significant reductions in maize and cash crop harvests. This was, in a large part, due to the dry spell that affected the entire district at a critical stage in crop development. As a result, there are concerns that the poor within the zone will face food shortages, especially in Nasenga, Mthilamanja, Chilipa, Namkumba and Mbwadzulu EPAs. In addition, winter crop production is threatened by inadequate residual moisture; consequently, harvests during this season are unlikely to be substantial. This will also reduce the availability of ganyu, which is an important source of both food and income for the ‘poor’.

The production of tobacco was also severely affected due to low input uptake and the effect of the dry spell. This reduces incomes for ‘middle’ and ‘better off’ households, which again links to low availability of local cash-ganyu thus negatively affecting incomes for ‘poor’ households in the coming months.

If the staple purchase price keeps pace with inflation (a value of MWK 19-23/kg) then the total missing food entitlement is expected to be 1,710 MT in maize equivalent or MWK 46.4 million in cash equivalent. If the staple purchase price increase to import parity (a value of MWK 32-40/kg) then the total missing entitlement is likely to rise to 3,790 MT or MWK 201.2 million in maize and cash equivalents, respectively.

Zone Description

The Phirilongwe Zone covers most of the upland areas of the western half of Mangochi district, the EPAs of Chilipa, Mthilamanja, Mbwadzulu, Nasenga and Namkumba. Normally, the zone receives significant amounts of rainfall, 800mm to 1000mm, which frequently causes water logging and flooding problems in some years in the low-lying areas. Maize is the main staple grown while tobacco and cotton are important cash crops for the area. Groundnuts are also grown for cash, especially for ‘poor’ households, whose ability to grow tobacco is limited by their lack access to inputs, especially fertilizer. Winter crop production is not very significant in the zone.

In ‘normal’ years, the ‘poor’ and ‘middle’ wealth groups obtain 50-55% and 70%, respectively, of their annual food energy requirements from their own crop production. The rest of their needs are acquired through purchases and, for the ‘poor’, through ganyu. The ‘better-off’ households in the zone are able to exceed their food requirements through their own production in ‘normal’ years.

Current Hazards

During the 2004/05 growing season, the entire livelihood zone experienced a prolonged dry spell starting during the last week of January. This occurred at the critical tasselling stage for maize development, causing significant reductions in production from the baseline year. Other crops were also affected by the dry spell, including cotton, the main cash crop37. Maize production is down 50% from baseline in Nasenga, Mbwadzulu, Mthilamanja and Namkumba EPAs. Other crops showing an even poorer performance were groundnuts, cassava, and pulses, which indicated a production

37 Due to low tobacco prices last year, many farmers switched from tobacco to cotton this year.


Chilipa 47,200 Mthilamanja 56,700 Nasenga 52,000 Mbwadzulu 25,800

Mangochi

Namkumba 23,000 Total 204,700 Scenario 1 & 2 % ‘Poor’ 20-35%

Assumptions for this Projection % of Baseline

Crop production*

Maize Groundnuts Cassava Pulses Cotton

45-55%

15-25% 15-25% 5-15%

45-55% Cotton sales price† 120-130%

Ganyu Availability 85% (food), 100% (cash)

Payment 105-115% Other sources of food and income 95-105% Scenario 1: market purchase price for maize† MWK 19-23/kg



Malawi VAC Food Security Monitoring Report June 2005 Mangochi District, Phirilongwe Hills Livelihood Zone

45

loss of 80-40% from baseline. Cash crops also suffered. Cotton was a popular crop this year, as farmers were encouraged by good prices last year and subsidised inputs, increasing their area under cultivation. However, production was also affected by the dry spell and is expected to be only 50% of baseline. The other main cash crop, tobacco, performed slightly better, with the ‘poor’ getting approximately 65-70% of the baseline harvest this year. The price offered to cotton growers this year is also expected to be lower than last year. Income sources from cotton represent an important contribution to all households’ income and cotton prices will have a considerable impact on income sources for all wealth groups.

The resulting maize shortages are expected to reduce ganyu payments and ganyu availability (ganyu for food), as more people will be seeking and fewer people providing. Income from self-employment activities is expected to increase slightly as people will put extra effort into producing and selling of grass, firewood, etc. The resulting increased supply of these goods is likely to reduce prices. This will affect ‘poor’ households and reduce access due to the higher prices and declining incomes.

Outcome

The level of harvest indicates that most ‘poor’ households will consume their own production up by July or August. This reduction in their own-produced maize and other crops, coupled with expected reduction in ganyu payments will mean that they will have reduced purchasing power; is likely to result in the ‘poor’ missing 10-20% of their entitlements for the conditions in scenario 1. For the conditions in scenario 2, this is likely to rise to 25-35% of their entitlements.


The timing and performance of the coming season will affect crucial sources of food and income in the coming year, especially ganyu (for both food and cash).

Other warning indicators include rapid increases in staple prices beginning as early as August/September, increased number of people looking for ganyu at reduced rates, increased sales of livestock at low prices during the hunger season (December to February).

Scenario 1 (Staple price approximately MWK19-23/kg) graphs for ‘Poor’ households in Chilipa, Mthilamanja, Nasenga, Mbwadzulu and Namkumba EPAs


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60%

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100%

120%

Baseline 2005-06


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120%

Baseline 2005-06


0%

20%

40%

60%

80%

100%

120%

Baseline 2005-06

Self-EmploymentGanyuLivestock SalesCash CropsOther Food Crop SalesRoot Crop SalesCereal Crop Sales

Malawi VAC Food Security Monitoring Report June 2005 Balaka, Machinga, Zomba, Mwanza and Neno Districts, Middle shire Livelihood Zone

46

Food Security Monitoring Report – June 2005 Balaka, Machinga, Zomba, Mwanza and Neno Districts Middle shire Livelihood ZoneMain Conclusions and Implications

All the EPAs in this zone have been affected similarly by the prolonged dry spell, which translated into severe drops in crop production during the 2004/05 agriculture season. In particular, maize, the main staple for this zone, was heavily affected as the dry spell occurred during the critical tasselling stage. In addition to this, limited availability and access to agricultural inputs aggravated the production failure, and as a result, both ‘middle’ and the ‘poor’ wealth groups lost approximately 40% of their food needs, which usually gained from their own production.

Cotton production in this livelihood zone was also affected and this will have a cause income decline. Income has especially reduced for the ‘middle’ and the ‘better-off’ households and this will have affect potential hiring of local ganyu, hitting incomes for the ‘poor’ households in the months ahead as well.

If staple prices remain within current average inflation rates ( a price of MWK 19-23/kg), then the total missing food entitlement is likely to be 54,250 MT in maize equivalent or MWK 1,294.1 million in cash equivalent. If staple prices rise to import parity (a value of MWK 32-40/kg) then the total missing entitlement is likely to be 66,070 MT or MWK 3,086.0 million for maize and cash equivalents, respectively.

Zone Description

The Middle Shire livelihood zone includes parts of Mwanza, Balaka, Blantyre, Machinga and Zomba districts and extends from the southern end of Lake Malombe in the north to the Mpatamanga gorge in the south. The zone has a relatively dry climate with a mean annual precipitation ranging from 200-1000 millimetres. The zone is characterised by near-subsistence farming, with fishing on a small scale taking place amongst those living close to the shire river. Being a dry area, crop production is relatively low but those along the river can rely on winter cropping. People in the area have no trouble accessing markets for their produce, although farmers in remote parts of the zone sometimes have to walk long distances. Prices of the main cash crop in the zone (cotton) tend to fluctuate and many farmers have, over the years, stopped growing the crop. However, there is renewed interest because of recent price incentives and subsidies on inputs offered by the Cotton Development association.

Current Hazards

The onset of rains this season came on time for the zone. However, due to the prolonged dry spell and the early termination of the rains, most crops were very poor this season. This has even affected the production of drought resistant crops such as cassava, and sweet potatoes because the rains stopped during the planting period for these crops. Sorghum was also hit; the dry spell affected the process of pudding.

Crop production was also affected due to the late distribution of Targeted Input Programme, the lack and the high cost of inputs.

Crop losses are expected to reduce the payment of ganyu for food. Incomes that are realised from activities like ganyu, sales of crops like cotton, rice, fruits, etc. will go down as well.


Phalula Utale Rivirivi

51,800

Ulongwe 65,600 Balaka

Bazale 122,000 Machinga Domasi (Ntubwi) 18,700 Zomba Chingale 47,200 Mwanza Thambani 26,600 Neno Lisungwi 25,600 Total 357,500 Scenario 1 & 2 % ‘poor’ 45-60% Scenario 1 & 2 % ‘Middle’ 25-40%

Assumptions for this Projection % of baseline


Maize Groundnuts Sweet potatoes Sorghum, millet Cotton Pulses

25-40% 45-55%

0% 0%

35-45% 15-25%

Cotton sales price† 115-125% Ganyu for food 60-70% Ganyu for cash Availability 95-105% Payment 105-115% Other sources of food and income 95-105% Scenario 1 market purchase price for maize†

MWK 19-23/kg


MWK 32-40/kg


Malawi VAC Food Security Monitoring Report June 2005 Balaka, Machinga, Zomba, Mwanza and Neno Districts, Middle shire Livelihood Zone

47

Outcome

Households in all the wealth groups will have a reduction in their access to food this zone in the livelihood zone. In scenario 1, the ‘poor’ are likely to miss 50-65% of their food energy entitlements, while the ‘middle’ are likely to miss 20-35% of their entitlements. In scenario 2, the missing food entitlement for the ‘poor’ will rise to 60-70% of their needs and that of the ‘middle’ will rise to 35-45% of their needs.


Reliance on ganyu for the ‘poor’ and the ‘middle’ wealth groups will be high this season although there will be pressure on pay rates since labour supply will be higher than demand. It will be important to monitor both price and availability.

The sale of livestock such as goats is likely to increase as households seek money for purchasing maize. With a fairly static demand, there will be pressure on prices.

They may also attempt to increase their incomes through an increase in firewood sales, marked increases need to be watched.

Scenario 1 (Staple price approximately MWK19-23/kg) graphs for ‘Poor’ households in Phalula, Utale, Rivirivi, Ulongwe, Bazale, Domasi, Chingale, Thambani & Lisungwi EPAs


0%

20%

40%

60%

80%

100%

120%

Baseline 2005-06

Cereal Crops Root CropsPulse & Gnuts Other CropsPurchase Ganyu

0%

20%

40%

60%

80%

100%

120%

Baseline 2005-06

Self-EmploymentGanyuLivestock SalesCash CropsOther Food Crop SalesRoot Crop SalesCereal Crop Sales

0%

20%

40%

60%

80%

100%

120%

Baseline 2005-06


Malawi VAC Food Security Monitoring Report June 2005 Machinga, Zomba, Phalombe, Mulanje, and Chiradzulu Districts, Lake Chilwa and Phalombe Plain Livelihood Zone

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Food Security Monitoring Report – June 2005 Machinga, Zomba, Phalombe, Mulanje, and Chiradzulu Districts Lake Chilwa and Phalombe Plain Livelihood ZoneMain Conclusions and Implications

All the EPAs in this zone were affected; they experienced heavy rains during the first half of the season and prolonged dry spell from late January to February 2005.

Like elsewhere, this caused significant reductions in crop production. Other factors that compounded the reduction include delayed planting time, access to fertilizer and fertilizer availability and soil leeching due to heavy rainfall in the first half of the season.

The ‘poor’ in the zone are particularly at risk due to limited options for earning cash. The fishing ganyu which is one of the sources of income has also been affected as a result of low fish production resulting from the prolonged dry spell.

If prices rise at a rate similar to current average inflation (a price of MWK 19-23/kg), the zone is likely to miss 69,970 MT in maize equivalent or MWK 1,669.2 million in cash equivalent of its food entitlement for the period April 2005 through March 2006. If prices rise to import parity (a price of MWK 32-40/kg), then the total missing food entitlement will become 90,070 MT or MWK 4,206.6 million in maize or cash equivalents, respectively.

Zone Description

As its name suggests, this zone includes areas surrounding Lake Chilwa and Lake Chiuta in Machinga and Zomba districts, extending south to the highland plain in Phalombe district and parts of Mulanje, Thyolo and Chiradzulu districts in the southern region. It generally receives an annual rainfall of 700-1000 mm, which is adequate for production of various crops. The main crops grown for food are maize, cassava, sorghum and rice. Tobacco and sunflower are cash crops but a minority of households grow them. Most of the households depend on their food crops for cash as well; rice being the most important cash crop for the households close to Lake Chilwa. Some of the cash obtained from selling rice is used to purchase maize, the main staple. Both the ‘poor’ and ‘middle’ households supplement their food access by doing ganyu in exchange of food in normal years.

Livestock (mainly goats and chickens) production is very insignificant as a source of food but it serves as a reliable source of cash during the hard times, mainly for ‘middle’ and ‘better-off’ households. Small-scale businesses and fishing are other economic activities from which households in the zone may derive their livelihoods. In summary, most of the households in the zone are subsistence farmers who sell part of their produce in order to access other basic needs, including food.

In ‘normal’ years, neither the ‘poor nor the ‘middle’ households are able to meet their food intake requirements. Just over half of the food requirements for the ‘poor’ and two-thirds of that of the ‘middle’ comes from their own crops. Purchases make up a third for the ‘poor’ and a quarter for the ‘middle’ and food from ganyu contributes 5-15% for the ‘poor’ and 1-10% for the ‘middle’. In a ‘normal’ year, a ‘poor’ households’ income purchases less than half of its food needs –this greatly restricts their capacity to cope with production shocks. Only ‘better-off’ households are able to meet their food intake requirement of which own crop production contributes 70-80% of their food intake while purchase make up the rest.

Current Hazards

Despite good early planting rains in the first half of the season, the zone experienced a prolonged dry spell from late January through February 200, quickly ending the rainy season. Coupled with fertilizer scarcity and high prices, households have experienced significant reductions in crop production although there are some variations within the


Chikweo 44,800Nampeya 36,500Nanyumbu 56,800Nsanama 36,500

Machinga

Ntubwi 18,200Msondole 80,400Mpokwe Likangala

124,300Zomba

Ngwerero 15,300Kosongo 37,700Tamani 41,400Mpinda 32,300Naminjiwa 47,800

Phalombe

Waruma 53,900Kamwendo Thuchila

208,300Mulanje

Msikawanjala 149,600Chiradzulu Thumbwe 77,600Total 1,061,400Scenario 1 & 2 % ‘Poor’ 25-35% Scenario 1 & 2 % ‘Middle’ 45-55%


49

zone depending on the time of planting, availability of and access to fertilizer, location of land (upland or low land) and degree of moisture stress. The very few who planted earlier harvested more than the others but still less when compared with baseline.

The Maize crop was affected at cobbing and tasselling stage while groundnuts were caught at their flowering stage. Even drought tolerant crops such as sorghum and pigeon peas were also affected, mainly by moisture stress. The production of roots and tubers has also been affected. Cassava planted last year has not developed good tubers due to moisture stress and the newly planted crop has dried up particularly in the upland. Sweet potato was planted in the wet lands only due to the prolonged dry spell experienced during the planting period. The ‘poor’ are expected to produce 35% less than their baseline maize production, 33% less than baseline for cassava and very small amounts of rice, sweet potatoes, groundnuts and pulses (pigeon peas).

Ganyu for food is assumed to drop by 20% and that for cash by 40%, when compared with baseline. The ‘poor’ will have to go to Mozambique in addition to local casual labour and the activities include harvesting, land clearing, ridging, and weeding. On the other hand, cash ganyu, which is local, will drop by 40% due to the ‘middle’ and ‘better-off’ losing income from failed cash crops and reduced fish production and expected low livestock prices.

Winter farming, which is normally practised by the 'better-off' and provides some employment opportunities, will be very low due to moisture stress.

Outcome

The above hazards will place the ‘poor’ and ‘middle’ households at risk of food insecurity, the degree to which will depend on the two staple price scenarios.

In Scenario 1, ‘poor’ households are likely to miss 55-70%% of their food energy entitlements, while ‘middle’ households are likely to miss 15-30% of their entitlements. There are two reasons for this: first, for both wealth groups, there is the drop in the contribution made by own crops to food intake and second, for the ‘poor’ only, there is a drop in the contribution of purchased food (mainly maize). This is due to lost crop production and reduced income, coupled with higher purchase prices. With such a low income base and few assets or opportunities for expansion, the ‘poor’ and ‘middle’ are not be able to purchase the food they need to make up their lost production. Unlike the ‘poor’, the ‘middle’ have a more assets and are also able to engage in petty trading.

Assumptions for this Projection % Of Baseline


Maize Rice Groundnuts S. Potatoes Pulses Cassava Sorghum Tobacco

60-70% 0-5%

0-10% 0-10% 0-2%

70-85% 0%

35-45% Tobacco sales price† 55-65% Agricultural Ganyu availability

Cash Food

55-65% 75-85%

Payment 135-145%

Fishing Ganyu Availability pay

75-85% 95-105%

Self-employment Availability pay

65-75% 95-105%

Petty Trade Availability pay

40-55% 95-105%

Scenario 1 market purchase price for maize† 22.95 MWK/kg

Scenario 2 market purchase price for maize† 35.00 MWK/kg

Cost of basic non-food items† 130-140% Cost of inputs† 190-210% *Baseline = average production 1998-2002 †Baseline = average price 2002-03 ACY

Scenario 1 (Staple price approximately MWK19-23/kg) graphs for ‘Poor’ households in Chikweo, Nampeya, Nanyumbu, Nsanama, Ntubwi, Msondole, Mpokwe, Likangala, Ngwerero,Kosongo, Mpinda, Tamani, Naminjiwa, Waruma, Kamwendo, Thuchila Msikawanjala andThumbwe EPAs


0%

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Baseline 2005-06


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Baseline 2005-06



50

In Scenario 2, the deficits for the ‘poor’ will increase slightly to 60-70%. Their small income prevents the poor from purchasing grain at all but ridiculously low prices, and so they are not directly affected by changes. The same is not so true of the ‘middle’, however. Their missing entitlements will rise to 30-45% of their minimum energy needs.


It is anticipated that many households will run out of food in June, which is much earlier than normal (November/December).

Food prices, especially of maize and other staples, will need to be watched and compared with previous seasons.

There will be an increase in the number of people from Phalombe, Zomba, Machinga and Mangochi districts, crossing the border into Mozambique in search of ganyu for food. There is also likely to be labour migration from the zone to other zones within the country and particularly to the tobacco estates. The number of people seeking ganyu and the low ganyu payment rate will be an important indicator of stressed food insecurity situation.

Another indicator is the price at which different livestock types (chickens, turkeys, and then goats) will be sold. These are expected to go down with increased sales.

Scenario 1 (Staple price approximately MWK19-23/kg) graphs for ‘Middle’ households in Chikweo, Nampeya, Nanyumbu, Nsanama, Ntubwi, Msondole, Mpokwe, Likangala, Ngwerero,Kosongo, Mpinda, Tamani, Naminjiwa, Waruma, Kamwendo, Thuchila Msikawanjala and Thumbwe EPAs


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Baseline 2005-06

min.non-staple stapledesirable discretionaryexp. deficit

Malawi VAC Food Security Monitoring Report June 2005 Thyolo and Mulanje Districts, Thyolo-Mulanje Tea Estates Livelihood Zone

51

Food Security Monitoring Report – June 2005 Thyolo and Mulanje Districts Thyolo-Mulanje Tea Estates Livelihood ZoneMain Conclusions and Implications

Own production of most crops for households is these two districts are down due to the lack of fertiliser and poor rainfall. Maize production is expected to be 35-45% of what is normally produced and other crops that provide either food or cash have also been affected. This will force households to increase the use of the alternative sources, such as purchases or ganyu in exchange for food.

These shocks will result in missing entitlements in the 2005-06 agricultural consumption year for the ‘poor’ and ‘middle’ households in both parts of the zone. The lost entitlements depend on households’ ability to purchase food and therefore staple prices are important. Scenario 1 assumes that purchase prices of maize increase at the average rate of inflation (about 13%) making the total missing food entitlement as a maize equivalent to be 11,310 MT or MWK 208.5 million in cash equivalent. Scenario 2 assumes a maize price increase to a higher level, based on import cost parity, of 93% more than 2004-2005. This results in the total missing entitlements increasing to 32,422 MT or MWK 1009.6 million for maize and cash equivalents, respectively.

Zone Description

The zone covers parts of Mulanje and Thyolo districts in the south-eastern part of Malawi. It is characterised by large tea estates that leave very little remaining land for cultivation by smallholder farmers. Consequently, land holdings are small, averaging less than one acre and are the main determining factor for crop production. Land holding sizes increase with wealth group category. Many households do not grow enough food to last them the whole year so they depend on markets for food, with much of the income coming from working on the tea estates. The zone also borders Mozambique so much of the food on the market—especially maize—comes from across the border. Close to 40% of the food energy intake by ‘poor’ and ‘middle’ households comes from purchases. The ‘better-off’ households are less dependent on purchases (around 15% of their needs) as they are able to produce more from larger pieces of land.

The zone generally experiences cool temperatures and high rainfall (900-2000mm), both of which are extended over a long period. It receives light rains or showers long after the main rainfall season is over in the rest of the country making weather conditions favourable for the production of the tea and fruits such as bananas, pineapples, avocado pears and citrus. Many households obtain income from working in the tea estates and selling fruits; this helps them withstand maize production shocks, yet it also makes them dependent on maize purchase prices. Livestock holdings are insignificant since grazing land is limited because most of the land is under tea cultivation.

Current Hazards

In general, the rains this last season started towards the end of October 2004. The planting rains were received in early November and there was an even distribution, which facilitated planting and transplanting of different crops in good time. Germination was above 95% and all transplanted and supplied crops picked up well. The two districts then received heavy rains in December, which did damage some crops such as maize by leaching nutrients, causing yellowing. Scanty rains were received in the month of


Mulanje Mulanje Boma Milonde

149,600

Thyolo Masambanjati Thekerani

265,200

Thyolo Central Dwale Khonjeni

255,100

Total 669,900Scenario 1 & 2 % ‘Poor’ 25-35%

Assumptions for this Projection % Of Baseline


Maize Rice S. Potatoes Pulses Cassava Bananas

35-45% 0%

5-15% 45-55% 55-65% 75-85%

Banana price† 95-105% Ganyu (food) 45-55%

Availability 95-105% Ganyu (smallholder)

Payment 95-105% Availability 70-80%

Ganyu (estates) Payment 95-105%

Self-employment and petty trading 0% Scenario 1 market purchase price for maize† MWK 19-23/kg


Cost of basic non-food items† 130-140%2 Inputs† 190-210% *Baseline = average production 1998-2002 †Baseline = average price 2002-03 ACY

Malawi VAC Food Security Monitoring Report June 2005 Thyolo and Mulanje Districts, Thyolo-Mulanje Tea Estates Livelihood Zone

52

January and the situation worsened in February 2005 with the dry spell that also afflicted other parts of the country. However, the areas in the Thyolo and Mulanje Tea estates livelihood zone were still receiving occasional showers when the former were completely dry. Although the rainfall received was lower than expected, some crops survived.

The concern is that the dry spells will affect the availability of local agricultural labour or ganyu –an important source of food and income for the ‘poor’ –particularly that which is paid in food. Tea may be affected, which could reduce income for ‘poor’ and ‘middle’ households and would then lead to lost income, both on the estates and with smallholder cash ganyu. Without accurate forecasts, the availability of work in the estates is estimated to be around 75% and the wage rate, currently at MWK 60/day, is assumed to remain the same.

Income from self-employment could also decrease as people lack the resources to run personal businesses and markets diminish as resources are diverted to purchasing food. Production of fruits and vegetables are also expected to drop slightly due to the dry spells.

Outcome

Own crops are expected to cover 15-25% of the minimum energy requirements for ‘poor’ households this year, with ganyu (paid in food) contributing 10-20% and purchases, 40-50%. Income is also expected to fall to 55-70% of baseline this year. Using scenario 1, the above hazards would have caused more losses in entitlements were it not for households’ ability to increase staple purchases, which will account for just over 40-50% of the food calorie, up from 35-45% in the baseline. All the discretionary expenditure will be switched to the staple food and maintaining minimum non-staple purchases. Based on the NSO population projections, the estimated missing entitlement is 10-20% for the ‘poor’ and 0-10% for the ‘middle’.

Assuming scenario 2, the food intake deficit faced by ‘poor’ households will increase to 25-35%. The ‘middle’ households are also expected to face a significantly higher deficit of 20-35%. This substantial increase is due to the ‘poor’ and ‘middle’ households in this zone being highly dependent on food purchases and are therefore sensitive to staple food price changes. Based on these deficits and the total population of the affected EPAs, the same population at risk has a total maize equivalent to their missing food entitlements of about 32,420 MT.


Any changes in staple prices will dramatically change food security; this needs to be monitored carefully.

As ‘Middle’ and ‘better-off’ households are able to sell livestock, extra sales being recorder with reduced prices will indicate a worsening situation.

There will be more people looking for work in the estates, many of whom will not be successful. As wage rates fixed, excess labour (people hanging around looking for work) will provide an early indication of acute food insecurity.

If tea is equally affected by the dry spells, there will be many people laid off from the estates.

The timing and performance of the coming season will be an important determinant for factors such as ganyu availability.

Scenario 1 (Staple price approximately MWK19-23/kg) graphs for ‘Poor’ households in Mulanje Boma Milonde Masambanjati Thekerani Thyolo Central Dwale, and Khonjeni EPAs


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Malawi VAC Food Security Monitoring Report June 2005 Chikwawa and Nsanje Districts, Lower Shire Livelihood Zone

53

Food Security Monitoring Report – June 2005 Chikwawa and Nsanje Districts Lower Shire Livelihood Zone

Main Conclusions and Implications

The prolonged dry spells experienced in this zone significantly affected crop production across the whole zone but some areas were more severely affected than others and to analyse this, the zone was divided into two groups, each group comprising EPAs that are affected to roughly the same degree. Group A comprises Makhanga and Mpatsa EPAs in Nsanje district and Mitole, Mbewe and Mikalango EPAs in Chikwawa district. Group B consists of all the rest. Both groups are expected to face serious food deficits this season.

The onset of last season’s planting rains was timely, but it became erratic with prolonged dry spells. Coupled with the probability of lost income through reduced ganyu from agricultural activities, ‘poor’ households from group A are expected to lose more of their entitlements than Group B.

If prices increase beyond inflation (13% more than last year or 35% more than inflation, a value of MWK 19-23/kg), the total missing food entitlement for the EPAs in Group 1 is expected to be 30,710 MT maize equivalent or MWK 610.5 million cash equivalent. The EPAs in Group B are expected to miss in 30,070 MT in maize equivalent or MWK 652.1 million in cash equivalent of their entitlement.

If maize prices will rise during December 2005 and March 2006 to MWK 32-40/kg, the total maize equivalent of the missing food entitlements in the EPAs in Group A could rise to 48,100 MT and the cash equivalent to MWK 1,913.9 million. In this scenario the EPAs in Group B are expected to have missing food entitlements totalling 41,290 MT or MWK 1,753.1 million maize and cash equivalents, respectively.

Zone Description

This hot dry lowland zone is nonetheless relatively productive by the standards of southern Malawi. This is because a variety of crops are grown during both the main and winter seasons, with winter crops cultivated in wetlands beside the Shire River. Cotton is the zone’s major cash crop, which has grown in popularity recently with better markets and support for inputs form the buying companies. Cattle holdings are significant, although concentrated in the hands of the ‘better-off’. Overall, very roughly one third of the total income in the zone comes from the sale of food crops, one third from the sale of cotton and the other third from the sale of livestock (mainly cattle and goats). The zone benefits from good access to neighbouring Mozambique, a source of relatively cheap maize in both good and bad years.

There are significant variations in winter production between different parts of the zone. For the roughly 20% of the population living in the west of the zone, away from the river, there are, of course, other local variations, with winter production more important in some villages than others.

Current Hazards

The planting rains started very well, but


Chikwawa Mitole Mbewe Mikalango

209,800

Makhanga 53,800 Nsanje Mpatsa 23,100 Total 286,700 Scenario 1 & 2 % ‘Poor’ 30-45%

A


Chikwawa Kalambo Livunzu Dolo

209,800

Mogoti 33,000 Nsanje Nyachilenda 70,700 Zunde 42,900 Total 356,400 Scenario 1 & 2 % ‘Poor’ 30-45%

B


Assumptions for this Projection % Of Baseline – Group A

% Of Baseline – Group B

Crop production (based upon district-level information)*

Maize Rice Sorghum Millet Groundnuts Pulses Cotton Sweet Potatoes

15-25% 0%

0-10% 5-15%

0% 0%

15-25% 0%

40-55% 0%

5-15% 5-15%

0% 0%

35-45% 0%

Cotton sales price 115-125% Availability 90-110% Cattle Payment 90-110%

Scenario 1: Market purchase price for maize MWK 19-23/kg

Scenario 2: Market purchase price for maize MWK 32-40/kg

Cost of basic non-food items† 130-140% Fertilisers and inputs 190-210% *Baseline = average production 1998-2002 †Baseline = average price 2002-03 ACY


54

stopped earlier than expected. The rains were then erratic with prolonged dry spells starting in late January, which affected the growth of all plants and caused them to wilt. All the cereals (local maize, millet and sorghum) dried up completely as the dry spell hit at a time when most of the crops were at reproductive stage. It also affected the growth of cotton and rice production in both parts of the zone. Overgrown rice seedlings were not transplanted in the main field in most areas due to inadequate water.

Dambo areas were also affected by the drought as they became dry earlier, curtailing winter cultivation, as the area available will be far smaller. Winter production normally helps in improving the food security situation in the zone, which is not the case this consumption year.

Cotton buds were observed bursting prematurely with very poor quality lint, so in addition to low food crop production, the main cash crop is equally reduced. This will reduce income from cotton sales (usually by ‘middle’ and ‘better-off’ households) or ganyu in cotton picking and grading (by the ‘poor’).

Livestock numbers have reduced because households have had to sell them off every year due to the succession of bad years. However, it is expected that livestock prices will be most affected due to increased selling this year.

Outcome

As a result of reduced incomes from agricultural activities, the ‘poor’ will find it difficult to purchase maize and rice.

In scenario 1, lower incomes realised from ganyu coupled with poor cereal production are expected to create a significant missing food entitlements. The ‘poor’ in Group A are expected to miss of 55-65% of their food needs, while the ‘middle’ are expected to miss 50-60%. The ‘poor’ in Group B are expected to be without 50-65% of their entitlements and the ‘middle’, 20-35%.

In scenario 2, the missing entitlement goes above 80% for both the ‘poor’ and ‘middle’ in Group A EPAs. The missing entitlement for the ‘poor’ in Group B becomes 65-75% and for the ‘middle’, 50-65%.

Scenario 1 Scenario 2 MFE ‘Poor’ ‘Middle’ ‘Poor’ ‘Middle’

Group A 55-65% 50-60% >80% >80% Group B 50-60% 30-45% 65-75% 50-65%

Scenario 1 (Staple price approximately MWK19-23/kg) graphs for ‘Poor’ households in Mitole, Mbewe, Mikalango, Makhanga and Mpatsa EPAs (Group A)


Scenario 1 (Staple price approximately MWK19-23/kg) graphs for ‘Middle’ households in Mitole, Mbewe, Mikalango, Makhanga and Mpatsa EPAs (Group A)


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Baseline 2005-06


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55


‘Poor’ households are expected to seek additional ganyu, both locally and in more distant parts of Mozambique, which are more diversified in crop production. These movements need to be monitored.

The actual prices received by farmers for their cotton will be important for overall incomes; these should be monitored, as should final cotton production.

The performance of the winter season will be all-important this year as it can make up some of the losses for food crops during the summer season. This includes sweet potatoes, a more drought resistant crop than maize.

The timing and performance of the coming agricultural season will also be key to providing opportunities for cash and food. If it is delayed, low food reserves will be stretched further. If performance is poor, then agricultural ganyu availability for the ‘poor’ will be more constrained. This should be monitored at the end of the year.

Staple prices do significantly affect households in this livelihood zone, due to their earnings from cotton and rice sales. Maize prices will be instrumental in food security later on in the year, such that a sharp rise in staple price will lead to rapidly deteriorating food security. These should be monitored as they will cause further and wider food insecurity if they rise beyond inflation-adjusted levels.

Finally, households from all wealth groups may try selling livestock (distress sales); increases in this activity (and correspondingly large drops in local prices) would indicate a growing crisis.

Malawi VAC Food Security Monitoring Report June 2005 Appendix

56

Food Security Monitoring Report – June 2005 Appendix

Common Hazards

Table VII – Some common hazard definitions used throughout the country (other hazard definitions vary from one place to another and are detailed in each of the LZ sections) Item Problem Specification Kwacha Prices of Most Commodities (Inflation over two years – at current rates) 135% Kwacha Labour (for Cash) Pay Rates 110% Kwacha Cotton Prices 180% Tobacco Prices 125% Fishing Availability 100% Self-Employment Opportunities 100% Self-Employment prices 135%

Missing Food Entitlements and Cash Requirements by Livelihood Zone

Table VIII - Cash Requirements to Alleviate Deficits Household Yearly Incomes ( M W K )

Required to Overcome Deficit Scenario 1 Scenario 2

Affected Parts of Livelihood Zone

‘Poor’ ‘Middle’ ‘Poor’ ‘Middle’ ‘Better-off’ Central Karonga - Lupembe EPA 10,223 18,134 205 Chitipa Maize & Millet - Kavukuku and Chisenga EPAs 7,751 13,691 Kasungu-Lilongwe Plain - Ming'ongo, Chileka, Ukwe, Mikundi, Linthipe, Chamama, Lobi,Mkanda, Chivala, Mponela, Kaluluma & Malingunde EPAs 4,770 9,629

Kasungu-Lilongwe Plain - Mpingu, Mng’wangwa, Mpenu, Chiwamba, Chitekwele,Mayani, Bowe, Mvera, Kalira, Chipuka, Malomo & Chioshya EPAs 2,230 5,882

Lake Chilwa & Phalombe Plain - Machinga, Zomba, Mulanje Districts; Kosongo, Mpinda,Tamani Waruma, Naminjiwa & Thumbwe EPAs 18,211 6,372 29,514 16,929

Lower Shire - Kalambo, Livunzu, Nyachilenda, Mogoti, Dolo & Zunde 14,555 10,074 28,630 23,598 Lower Shire - Makhanga, Mpatsa, Mitole, Mbewe & Mikalango EPAs 14,729 13,595 36,621 33,922 Middle Shire - Lisungwi, Thambani, Mwanza, Phalula, Utale, Chingale & Ntubwi EPAs 16,562 7,736 29,136 18,261 Nkhata Bay Cassava - Vinthukutu & Nkhunga EPAs 971 4,593 Northern Lakeshore - Nkhunga, Linga and Zidyana EPAs 2,761 13,865 Phirilongwe Hills - Mbwadzulu, Mthilamanja, Nasenga & Namkumba EPAs 4,616 15,903 Rift Valley Escarpment - Sharpevale, Kandeu, Bilira, Nsipe, Manjawira EPAs 3,077 952 12,734 9,227 Rift Valley Escarpment - Zidyana, Mwansambo, Khombedza, Chinguluwe, Tembwe,Chipoka, Mtakataka, Golomoti, Mwanza & Neno EPAs 6,456 4,982 17,990 15,461 6,342

Shire highlands - Mbonechera, Thondwe, Malosa, Thumbwe, Dzaone, Mombezi, Chingale, Ntubwi & Matapwata EPAs 10,483 21,548 4,261

Shire highlands - Ntonda, Ntiya, Lungwena, Katuli, Masuku, Nyambi & Maiwa EPAs 5,979 15,754 Southern Lakeshore - Chipoka, Tembwe, Mtakataka, Golomoti, Namkumba Mbwadzulu,Nasenga & Lungwena EPAs 5,051 17,884

Thyolo Mulanje Tea Estates - Msikawanjala, Mulanje Boma, Khonjeni & Thekerani EPAs 2,858 1,622 9,418 8,050 Western Rumphi - Bolero and Parts of Muhuju EPA 5,367 15,222


57

Table IX - Missing food entitlements over the whole year for each affected part of each livelihood zone for Scenario 1

Table X – Missing food entitlements and cash requirements and for the affected parts of each livelihood zone Affected Parts of Livelihood Zone MFE: Maize Equivalent

(MT) MFE: Cash Eq. (Malawi

K million)

Scenario 1 Scenario 2 Scenario 1 Scenario 2

Central Karonga - Lupembe EPA 310 350 6.42 14.54Chitipa Maize & Millet - Kavukuku and Chisenga EPAs 980 1,120 21.49 47.78Kasungu-Lilongwe Plain - Ming'ongo, Chileka, Ukwe, Mikundi, Linthipe, Chamama, Lobi, Mkanda, Chivala, Mponela, Kaluluma & Malingunde EPAs 11,110 14,420 198.77 505.00

Kasungu-Lilongwe Plain - Mpingu, Mng’wangwa, Mpenu, Chiwamba, Chitekwele, Mayani, Bowe, Mvera, Kalira, Chipuka, Malomo & Chioshya EPAs 5,430 9,210 97.19 322.63

Lake Chilwa & Phalombe Plain - Machinga, Zomba, Mulanje Districts; Kosongo, Mpinda, Tamani Waruma, Naminjiwa & Thumbwe EPAs 69,970 90,070 1,669.21 4,206.55

Lower Shire - Kalambo, Livunzu, Nyachilenda, Mogoti, Dolo & Zunde 30,070 41,290 652.05 1,753.05Lower Shire - Makhanga, Mpatsa, Mitole, Mbewe & Mikalango EPAs 30,710 48,100 610.48 1,913.89Middle Shire - Lisungwi, Thambani, Mwanza, Phalula, Utale, Chingale & Ntubwi EPAs 54,250 66,070 1,294.13 3,086.00Nkhata Bay Cassava - Vinthukutu & Nkhunga EPAs 180 550 3.78 22.49Northern Lakeshore - Nkhunga, Linga and Zidyana EPAs 870 2,800 24.99 157.92

Affected Parts of Livelihood Zone Missing Food Entitlements (MT)*

Apr-Jun Jul-Sep Oct-Dec Jan-Mar

Total Affected

Pop. ‘Poor’ ‘Middle’TOTAL ‘Poor’ ‘Middle’TOTAL ‘Poor’ ‘Middle TOTAL ‘Poor’ ‘Middle’ TOTAL Central Karonga - Lupembe EPA 3,500 50 50 60 60 70 70 120 120Chitipa Maize & Millet - Kavukuku and Chisenga EPAs 15,300 70 70 160 160 200 200 480 480Kasungu-Lilongwe Plain - Ming'ongo, Chileka, Ukwe, Mikundi, Linthipe, Chamama, Lobi, Mkanda, Chivala, Mponela, Kaluluma & Malingunde EPAs

229,200 1,530 1,530 3,650 3,650 5,960 5,960

Kasungu-Lilongwe Plain - Mpingu, Mng’wangwa, Mpenu, Chiwamba, Chitekwele, Mayani, Bowe, Mvera, Kalira, Chipuka, Malomo & Chioshya EPAs

239,700 1,130 1,130 4,340 4,340

Lake Chilwa & Phalombe Plain - Machinga, Zomba, Mulanje Districts; Kosongo, Mpinda, Tamani Waruma, Naminjiwa & Thumbwe EPAs

849,100 6,240 6,240 12,570 12,570 12,580 6,530 19,110 12,720 19,180 31,900

Lower Shire - Kalambo, Livunzu, Nyachilenda, Mogoti, Dolo & Zunde 295,800 1,670 1,670 3,010 1,160 4,170 5,090 4,770 9,860 6,500 7,420 13,920Lower Shire - Makhanga, Mpatsa, Mitole, Mbewe & Mikalango EPAs 237,900 2,340 1,600 3,940 3,100 3,490 6,590 4,150 4,910 9,060 5,090 6,030 11,120Middle Shire - Lisungwi, Thambani, Mwanza, Phalula, Utale, Chingale & Ntubwi EPAs

540,200 4,430 4,430 9,170 1,430 10,600 13,200 3,080 16,280 15,220 7,710 22,930

Nkhata Bay Cassava - Vinthukutu & Nkhunga EPAs 21,400 190 190Northern Lakeshore - Nkhunga, Linga and Zidyana EPAs 49,800 660 660Phirilongwe Hills - Mbwadzulu, Mthilamanja, Nasenga & Namkumba EPAs

55,300 290 290 510 510 940 940

Rift Valley Escarpment - Sharpevale, Kandeu, Bilira, Nsipe, Manjawira EPAs 292,700 810 810 2,470 1,240 3,710Rift Valley Escarpment - Zidyana, Mwansambo, Khombedza, Chinguluwe, Tembwe, Chipoka, Mtakataka, Golomoti, Mwanza & Neno EPAs

338,700 670 670 1,120 1,120 1,550 2,360 3,910 4,520 5,000 9,520

Shire highlands - Mbonechera, Thondwe, Malosa, Thumbwe, Dzaone, Mombezi, Chingale, Ntubwi & Matapwata EPAs

225,800 3,110 3,110 4,570 4,570 4,610 4,610 5,750 5,750

Shire highlands - Ntonda, Ntiya, Lungwena, Katuli, Masuku, Nyambi & Maiwa EPAs

157,200 960 960 2,190 2,190 4,080 4,080

Southern Lakeshore - Chipoka, Tembwe, Mtakataka, Golomoti, Namkumba Mbwadzulu, Nasenga & Lungwena EPAs

148,800 900 900 1,100 1,100 1,400 1,400 1,740 1,740

Thyolo Mulanje Tea Estates - Msikawanjala, Mulanje Boma, Khonjeni & Thekerani EPAs

502,500 2,360 220 2,580 2,120 570 2,690 4,450 3,490 7,940

Western Rumphi - Bolero and Parts of Muhuju EPA 21,600 360 360 650 650

TOTAL 4,224,400 19,480 1,600 21,090 40,010 6,297 46,311 53,610 24,591 75,837 75,884 55,067 125,952* the error difference in the totals of the MFEs across the seasons and the total for the average MFEs for whole year are due to rounding when in disaggregating the data into seasons. The average for the whole year should be taken as the more correct figure.


58

Affected Parts of Livelihood Zone MFE: Maize Equivalent (MT)

MFE: Cash Eq. (Malawi K million)

Scenario 1 Scenario 2 Scenario 1 Scenario 2Phirilongwe Hills - Mbwadzulu, Mthilamanja, Nasenga & Namkumba EPAs 1,710 3,790 46.40 201.18Rift Valley Escarpment - Sharpevale, Kandeu, Bilira, Nsipe, Manjawira EPAs 4,450 16,140 101.94 724.45Rift Valley Escarpment - Zidyana, Mwansambo, Khombedza, Chinguluwe, Tembwe, Chipoka, Mtakataka, Golomoti, Mwanza & Neno EPAs 15,180 30,350 347.97 1,367.23

Shire highlands - Mbonechera, Thondwe, Malosa, Thumbwe, Dzaone, Mombezi, Chingale, Ntubwi & Matapwata EPAs 18,040 30,700 430.39 1,433.69

Shire highlands - Ntonda, Ntiya, Lungwena, Katuli, Masuku, Nyambi & Maiwa EPAs 7,170 12,140 170.94 566.89Southern Lakeshore - Chipoka, Tembwe, Mtakataka, Golomoti, Namkumba Mbwadzulu, Nasenga & Lungwena EPAs 5,090 13,040 136.65 608.96

Thyolo Mulanje Tea Estates - Msikawanjala, Mulanje Boma, Khonjeni & Thekerani EPAs 13,100 32,420 208.42 1,009.56Western Rumphi - Bolero and Parts of Muhuju EPA 1,000 1,830 21.11 75.34

TOTAL 269,610 414,380 6,042.31 18,017.14Change in Value from Scenario 1 to Scenario 2 +54% +198%

Table Detailing the Criteria for Defining the Wealth Groups in Each Livelihood Zone

Table XI - 'Poor' and ‘Middle’ Wealth Groups Household Characteristics

Livelihood Zone

Land holding (acres)

Land cultivated(acres) Livestock38 Approx. Hh yearly

cash income39 Other

‘Poor’ ‘Middle’ ‘Poor’ ‘Middle’ ‘Poor’ ‘Middle’ ‘Poor’ ‘Middle’

Chitipa maize and millet 1-2 2-4 0.25-1 1-2 G: 0-2

C: 2-4 G: 2-5 C: 4-10

B:10300 N:7720

B:46100 N:45750

The poor normally depletes own production by July. -The poor lack inputs

Central Karonga 0.5-1 1.5-3 0.5-1 1.2-2 G: 0

C: 1-10 P: 0-3

T: 2-5 C: 10-20

P: 2-5

B: 8550 N: 8890

B:11100 N:20830

-‘Poor’ normally consumes own production up to December. -Livestock sales expands income

Western Rumphi 1-3 2-3 1-1.5 2-3 G: 0

C: 7-10 P: 0-3

G: 5 C: 10-15

P: 0-5

B:18300 N:17150

B: 41230 N: 36940

-The poor normally consumes own production up to October.

Nkhata Bay Cassava 0.5-1.5 1.5-3 0.5-1.5 1.5-2 G: 0

C: 2-5 G: 0-5 C: 5-7

B: 9620 N: 10570

B: 14200 N: 13910

-The poor normally consumes own production up to December.

Northern Lakeshore B: 17530

N: 22000 B: 35380 N: 44750

Kasungu-Lilongwe plain 1.5-2.5 2-3 1.5-2.5 2-3 G: 0-5

C: 5-15

T: 0-3 G: 0-6

C: 10-20

B: 9140 N: 8840

B: 31250 N: 28200

-The poor normally consumes own production up to November.

Rift Valley escarpment 3-4 3-4 2-3 2-5

G: 0-3 C: 4-6 P: 0-3

G: 4-7 C:8-10 P: 3-5

B: 19870 N: 19100

B: 26780 N: 18720

Southern Lakeshore 2 3 1.5 3 G: 0-2

C: 5 G: 5 C: 15

B: 25070 N: 22830

B: 75510 N: 73720

-The poor normally finish own production by July. The poor lack farm inputs.

Shire Highlands 0.5-0.75 0.5-1.5 0.5-0.75 1-1.5 G: 0-5 C: 0-3

G: 3-5 C: 8-10

B: 12380 N: 16390

B: 26400 N: 28700

-The poor normally depletes own production by August. -The poor do not use inputs. -The poor cultivate marginal land.

Phirilongwe Hills B: 26430 N: 20610

B: 53400 N: 37390

Middle Shire 2 3 1.5 3 G: 0-2 C: 4

G: 6 C: 10

B: 14720 N: 10940

B: 20760 N: 15990

-Labour shortages for the poor. -The poor normally consumes own production up to September.

Lake Chilwa and Phalombe Plain 1-2.5 2-4 G: 0-2

C: 4-6 G: 1-4 C: 6-8

B: 12800 N: 6910

B: 41100 N: 18150

-The poor normally consumes own production up to July.

Thyolo Mulanje tea estates 1-1.5 1.5-2 0.5-1 1-1.5 G: 0

C: 4-5 G: 0

C: 6-10 B: 21930 N: 15030

B: 23610 N: 16320

-The poor normally consumes own production up to September.

Lower Shire 3-4 3-4 1-1.5 2-3 T: 0

G: 0-4 C: 4-7

T: 3-4 G: 5-8 C: 4-8

B: 11430 N: 10600

B: 24550 N: 11960

-Lack of farm inputs for the poor. -The poor normally consumes own production up to August.

38 C – Chickens, G – Goats, P – Pigs, T – Cattle 39 B – Baseline, N – this year; Income denominated in Malawi Kwacha, for the whole household


59

Map of the Livelihood Zones in Malawi

Figure 11 - Livelihood Zones, EPAs and Districts in Malawi

LA

KE

MA

LA

WI

Mzimba

Kasungu

Lilongwe

Rumphi

Dedza

Chitipa

Dowa

Chikwawa

Mchinji

Machinga

Zomba

MulanjeThyolo

Ntchisi

Mangochi

Ntcheu

Karonga

Nkhotakota

Nkhata Bay

Salima

Balaka

Mwanza

Nsanje


EMFENI

MBAWA

KAVU

KUKU

CHAMAMA

EUTHINI

MASUKU

LIRANGW

E

NKHUNGA

MKANDA

CHINTH

ECHE

NENO

NTUBWI

BOLERO

LISASADZI

KALULU

MA

ZOMBWE

CH

IKW

INA

ES

WA

ZINI

CH

ITH

EKA

BULALA

SAN

THE

MPHEREMBE

LING

A

MIT

OLE

BWEN

GU

CH

ULU

MW

AN

ZA

CHILIPA

DOLO

NTIYA

MANYAMULA

LOBI

MPILIPILI

CHISENGA

PHALULA

ULONGWE

MAD

ISI

MA

NJA

WIR

A

NAS

EN

GA

KARONGA SOUTH

KATULI

UKW

EMSITU

LIVUN

ZU

BOW

E

CH

AMP

HIR

A

MAY

ANI LU

NG

WE

NA

BEMBEKE

KALULU

ZID

YAN

A

KAND

EU

MVERAC

HILA

ZA

MJI

NG

E

NYAMBI

CHINGALE

CHIKWEO

CHITE

KWEL

E

KHOMBEDZA

CHIOSHYA

TSA

NG

AN

O

KALIRA

SHAR

PEVALE

CHISEPO

CH

IPOKA

NSANJE

MPH

OM

PHA

MALOSA

MLOMBA

MAGOTI

MW

AN

SA

MB

O

SINYALA

LUFITA

TEMBWE

LISUNGWI

KARONGA CENTRAL

NTONDA

NSIPE

KANYAMA

MALOMO

MISUKU

MPAMBA

KALAMBO

MPILISI

MULANJE SOUTH

MIKUNDI

NAMPEYA

KASUNGU CHIPALA

MIKALANGO

MULANJE WEST

NACHISAKA

MOMBEZI

THYOLO BOMA

BAZALE

MPOKWE

MPINDA

MWAMKUMBWA

NAMKUMBA

MPATSA

MPENU

MBEWE

MLONYENI

MUHUJU

NANYUMBU

CHIPUKA

NSANAMA

MAIWA

CHIWAMBADEMELA

NTHONDO

MASAMBANJATI

BILIRA

MBWADZULU

MSONDOLE

MPINGUMING'ONGO

TAMANI

GOLOMOTI

MATAPWATA

THONDWE

MAKHANGA

NTCHISI BOMA

LINTHIPE

NJOLOMOLE

MBONECHERA

DZAONE

CHIVALACHINGULUWE

THUMBWE

NTCHENACHENA

MTHIRAMANJA

MTAKATAKA

KAPORO SOUTH

MNDOLERA

KAPORO NORTH

MPONELA

KABWAZI

NKHATABAY BOMA

NYANJA

NYACHILENDA

CHIGONTHIM'NGWANGWA

KASONGO

KAPHUKACHITSIME

WARUMA

CHAFUMBA

KHOSOLO

KAMBANIZITHE

NAMINJIWA

MAIWA

NKHULAMBE

CHAFUMBA

MSONDOLE

LAKE CHILWA

LAKE MALOMBE

LAKE CHIUTA

NAKACHOKA

MAYAKA NGWERERO

33°0'0"E

33°0'0"E

34°0'0"E

34°0'0"E

35°0'0"E

35°0'0"E

36°0'0"E

36°0'0"E

17°0'0"S 17°0'0"S

16°0'0"S 16°0'0"S

15°0'0"S 15°0'0"S

14°0'0"S 14°0'0"S

13°0'0"S 13°0'0"S

12°0'0"S 12°0'0"S

11°0'0"S 11°0'0"S

10°0'0"S 10°0'0"SLivelihood Zones

Border Productive Veg

Central Karonga

Chitipa Millet & Maize

Kasungu Lilongwe Plain

Lake Chilwa - Phalombe Plain

Lower Shire

Middle Shire Valley

Misuku Hills

Mzimba Self Sufficient

Nkhata Bay Cassava

Northern Karonga

Northern Lakeshore

Phirilongwe Hills

Rift Valley Escarpment

Shire Highlands

Southern Lakeshore

Thyolo Mulunje Tea Estates

Western Rumphi & Mzimba

EPAs

0 40 80 120 16020Kilometers

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