Costing and Analysis of Transfer Levels for The Malawi Social Cash Transfer Programme

Transcription

1 ` Costing and Analysis of Transfer Levels for The Malawi Social Cash Transfer Programme Ronald Mangani Robert White April 2012

2 Acknowledgements This study was conducted for the Government of Malawi with financial support from UNICEF Malawi. The authors sincerely appreciate the close guidance and support provided by Harry Mwamlima (Director, Division of Poverty Reduction and Social Protection, in the Ministry of Economic Planning and Development) and Maki Kato, Chief of Social Police at UNICEF Malawi. The technical guidance provided by staff of the Division (especially Tom Mtenje and Imran Nedi) as well as staff at UNICEF Malawi (especially Sophie Shawa and Tayllor Renee Spadafora) is gratefully acknowledged. The authors would like to extend their thanks to all individuals and organisations consulted during the course of the study. A full list of the people consulted is provided in Annexes to the report. The views expressed in this report are those of the authors and do not necessarily represent the views of the Government of Malawi or UNICEF Malawi

3 Acronyms and Abbreviations AIDS - Acquired Immuno Deficiency Syndrome CCT - Conditional Cash Transfers CRC - Convention on the Rights of the Child CSSC - Community Social Support Committee EU - European Union FGD - Focus Group Discussions FISP - Farm Input Subsidy Programme GDP - Gross Domestic Product GMI - Guaranteed Minimum Income GoM - Government of Malawi HIV - Human Immune Virus IHS - Integrated Household Survey K - Malawi kwacha KII - Key Informant Interviews KfW - Kreditanstalt für Wiederaufbau (Reconstruction Credit Institute of Germany) MASAF - Malawi Social Action Fund MDG - Millennium Development Goals MGDS - Malawi Growth and Development Strategy MK - Malawi Kwacha MPVA - Malawi Poverty and Vulnerability Assessment NAC - National AIDS Commission NSNP - National Safety Net Programme NSSP - National Social Support Programme PN - Perceived Needs PPP - Purchasing Power Parity PRSP - Poverty Reduction Strategy Paper PWP - Public Works Programme SB - Subsistence Basket SCT - Social Cash Transfer SCTP - Social Cash Transfer Programme $ - United States dollar UNICEF - United Nations Children Education Fund USD - United States Dollars WFP - World Food Programme WMS - Welfare Monitoring Survey 1

4 Contents Acknowledgements... Acronyms and Abbreviations... 1 Contents... 2 Executive Summary Introduction Background Purpose and Scope of the Study Methodologies Study Limitations Organisation of the Report A Contextual Background of the Malawi SCTP Poverty and Vulnerabilities in Malawi Consequences and Impacts of Poverty Interventions and Intervention Linkages The Policy and Regulatory Environment National Poverty Profile and SCTP Beneficiary Targeting Measures of Poverty in Malawi Beneficiary Targeting in the SCTP Determination of Target Beneficiary Households Determination of Cash Transfer Levels The Literature Appraisal of the determination of the current SCTP transfer levels Alternative Transfer Level Determination Procedures Comparisons and Propositions Revision of Transfer Levels Cost Implications Introduction Assumptions Costing Outcomes Conclusion

5 Tables Table 1: SCTP Beneficiary Chart August Table 2: Gender Categories for Key Informants 9 Table 3: Age Categories of the Beneficiary Key Informants 9 Table 4: Incidence of Poverty in Malawi ( ) 15 Table 5: Estimates of Beneficiary Households Per District 18 Table 6: Calculating Malawi SCTP Generosity in Terms of the Ultra-Poverty Line 20 Table 7: Transfers Levels Proposed by the GoM (2010) 22 Table 8: US Dollar-Stable Transfers 23 Table 9: US Dollar-Stable Transfers after Devaluation 24 Table 10: Inflation-Adjusted Transfers 24 Table 11: IHS Ultra-Poverty Gap Transfer Levels 24 Table 12: Cost of the Monthly Subsistence Basket at 2012 Prices 26 Table13: Cost of Perceived Needs per Month 26 Table 14: Desired Transfer Levels by Current Beneficiaries 27 Table 15: Convergence between Large and Small Transfers 29 Table 16: Transfer Levels Proposed by the IHS Ultra-poverty Gap Plus 10% Methodology 30 Table 17: Summary of Costing Outcomes 34 Figures Figure 1: Derived Monthly Transfer Levels for the Largest Household 28 Figure 2: The Proposed Transfer Level Determination Tool 31 Figure 3: Cash Transfer Costs in 12 Countries 35 Boxes Box 1: Data Improvements and SCTP Beneficiary Targeting 18 Box 2: Education-Related Expenses in Public Schools 30 Annexes Annex 1: References 37 Annex 2: List of National Level Key Informants 39 Annex 3: List of Key Informants at District Level 40 Annex 4: List of FGD Participants 41 Annex 5: Guiding Questions for National Level Consultations 42 Annex 6: Questionnaire for Beneficiaries Field Work 44 Annex 7: Guiding Questions for FGD 47 Annex 8: Incidence of Poverty by District (% of population) 49 Annex 9: Targeting Methods 50 Annex 10: Monthly Cost Implications of Transfer Level Determination Approaches (kwacha) 51 Annex 11: Annual Cost Implications of Transfer Level Determination Approaches (kwacha) 55 Annex 12: Annual Cost Implications of Transfer Level Determination Approaches (kwacha) 60 3

6 Executive Summary This study on the costing and analysis of transfer levels for the Malawi Social Cash Transfer Programme (SCTP) was commissioned by UNICEF Malawi on behalf of the Government of Malawi. The study accomplishes three main things summarised in this report, as follows. First, it formalises the framework for determining the target number of beneficiary household of the SCTP, and presents such estimated for Second, it explores and appraises the various methodologies for determining transfer levels, and recommends an appropriate tool for revising the transfer levels in the programme which is easy, flexible and relatively prudent in terms of its demand on public resources. Finally, the study estimates the monthly and annual direct costs implied by the various transfer level determination frameworks. The main recommendations and implications of this analysis are as follows: I. The determination of target beneficiary households in each district should be based on the following general procedure: a. Calculate the intercensal ( ) annual growth rate in the number of households for each district by iteratively solving for r in: P P98 1 r where P 08 = number of households in the district in 2008 P 98 = number of households in the district in b. Compound the total number of households per district in 2008 at the rate of r, to obtain an estimate of the number of households per district in c. Sum up the numbers of households per district to obtain the estimated total number of households in Malawi in d. Calculate the estimated total number of beneficiary households in 2012 as 10% of the estimated total number of households in Malawi in 2012, in line with the SCTP design. e. Calculate the number of ultra-poor households per district by multiplying each district s ultrapoverty headcount ratio by the estimated number of households in the district. f. Sum up the numbers of ultra-poor households in all districts to obtain the total number of ultra-poor households in Malawi. g. Obtain each district s share of ultra-poor households by dividing each district s number of ultrapoor households by the national number of ultra-poor households. h. Obtain the number of beneficiary households per district by multiplying each district s share of ultra-poor households by the total number of beneficiaries in Malawi. In order to improve the framework for determining beneficiary households, it is recommended that the National Statistical Office should readily supply the following data in standard reports: a. intercensal growth in the numbers of households per district, b. ultra-poverty headcount ratios per district per annum, and c. labour-constrained and non-labour-constrained ultra-poor households per district per annum. 4

7 II. The revision of cash transfer levels should be based on the IHS ultra-poverty gap approach. The following transfer level determination tool should be used: a. Step 1: Determine the ultra-poverty gap. This is the difference between the nominal ultra-poverty line for the poorest household of a given size, and the average expenditure by the poorest segment of the population. b. Step 2: Adjust the ultra-poverty gap for inflation. The rural annual headline inflation rates for the period between the latest IHS period and the current period should be applied. Previous year inflation should be used to adjust the previous year ultra-poverty gap to obtain the current year s ultra-poverty gap. c. Step 3: Increase the inflation-adjusted ultra-poverty gap by a basic non-food expenditures inflator of 10%. The result obtained at this stage becomes the transfer level payable to the largest household of at least four members. d. Step 4: Adjust other transfer levels based on household size by pre-determined growth rates: Assuming that the transfer to the largest household increased g kwacha between two periods, adjust transfer levels due to smaller households by the following constants (rounded up accordingly): One-person household: increase by (g 0.7) kwacha Two-person household: increase by (g 0.8 ) kwacha Three-person household: increase by (g 0.9) kwacha Four-person plus household: increase by g kwacha e. Step 5: Set the primary school bonus. This should be equal to one-third of the new transfer level payable to the one-person household. f. Step 6: Set the secondary school bonus. This should be equal to double the primary school bonus. Based on this procedure, the recommended revised transfer levels are as presented in Table A. Table A: Transfer Levels Proposed by the IHS Ultra-poverty Gap Plus 10% Methodology Household Size Current Proposed (K) $ K $ Increase (%) School Bonus Primary Secondary Note: The exchange rate used is K = $1.00 as at April 2012 The application of the proposed tool would be enhanced by the availability of more recent poverty data, and the results reported herein may require revision as soon as IHS 3 data become available in In addition, the procedure would be enriched by addressing the following data needs: a. Reporting adequate details on the socio-economic characteristics of the non-poor, the poor and the ultra-poor, including their average expenditures and household sizes. b. Reporting poverty and expenditure data at the decile rather than quintile level. c. Reporting data on education expenditure by income group. 5

8 III. Conduct annual reviews of transfer levels. Apart from ensuring responsiveness to changes, annual reviews have the advantage that costs are likely to adjust slowly from year to year, especially when rural inflation remains low. If the application of the adjustment tool in a given review period results in an adjustment of less than 5% to the prevailing transfer due the largest household, it is our view that the transfer levels need not be revised in that period. IV. The direct cost implications of these recommendations as at April 2012 are as follows: a. A national programme roll-out based on the current transfer levels would cost K million ($3.82 million) per month, or K7.66 billion ($45.9 million) per annum in direct costs. b. A national programme roll-out based on the proposed ultra-poverty gap plus 10% approach would cost K million ($5.16 million) per month, and K10.34 billion ($61.91 million) per annum in direct costs. c. Therefore, implementation of the proposed transfer level determination tool would cost 35% more than the current framework at today s prices. Given the objectives and design of the SCTP, this is appears to be the most cost-effective of the procedures explored in the study. d. Additionally, the direct costs due to the proposed approach would be 3.45% of the current Malawi Government Budget, and 1.04% of GDP. These are lower than figures reported for other developing countries, notwithstanding that the SCTP is only one of several other public social security programmes being implemented in Malawi. 6

9 1. Introduction 1.1 Background The Malawi Social Cash Transfer Programme (SCTP) was initiated with the objectives of reducing poverty, hunger and starvation and increasing child school enrolment, health and nutrition among vulnerable households. The programme was piloted in Mchinji District from 2006, and is currently being implemented in 7 districts of the country reaching about 25,000 ultra-poor and labour-constrained households as of August, 2011 (Table 1). The total number of beneficiary households was estimated at 29,925 in November The programme is implemented for the Government of Malawi (GoM) by the SCTP Secretariat of the Ministry of Gender, Children and Community Development, while policy direction is provided by the GoM s Division of Poverty Reduction and Social Protection in the Ministry of Economic Planning and Development. Until end 2011, transfer funding has been largely provided by the Global Fund to Fight Malaria, AIDS and Tuberculosis through the National AIDS Commission (NAC). Additional transfer funding has also been provided by Irish Aid. From, January 2012 funding amounting to 13 million will be provided by the German Government through Kreditanstalt für Wiederaufbau (KfW). The United Nations Children Fund (UNICEF) Malawi provides technical assistance and capacity strengthening to the programme. The SCTP targets ultra-poor and labour-constrained households in Malawi. These are defined as follows: 1 : Ultra poor households: A household is ultra poor if it is in the lowest expenditure quintile and under the national ultra poverty line (only able to afford one meal per day; not able to purchase essential non-food items such as soap, clothing, school material; are begging; and have no valuable assets) Labour constrained households: A household is considered labour constrained if it has no ablebodied adult fit for work or a dependency ratio of more than 3. These households are not able to access or benefit sufficiently from labour based interventions such as public works or casual labour (ganyu). The Government of Malawi has developed the following criteria for labour constrained households: A household with high dependency ratio, identified as one whose household head is between the ages of who may or may not be fit for work, but must care for more than 3 dependants. A person who is not fit for work, including a child who is under the age of 18; a person who is elderly (above 60 years of old); a person who is between the ages of 19-59, but is chronically ill or disabled; or a school going person, up to the age of 25. The SCTP monthly cash transfer levels vary according to family size as follows: 2 K600 ($3.60) for a one-person household K1000 ($6.00) for a two-person household K1,400 ($8.40) for a three-person household K1,800 ($10.75) for a household of four or more members. 1 see 2 Unless otherwise stated, United States dollar ($) values are obtained using the exchange rate of K = $

10 Monthly bonuses of MK200 ($1.20) and MK400 ($2.40) are additionally provided for each primary school and secondary school child, respectively. Table 1 shows the coverage of the SCTP as at 30 August, Table 1: SCTP Beneficiary Chart August 2011 District Mchinji Likoma Machinga Salima Mangochi Chitipa Phalombe Total Total households Elderly headed Female headed Child headed Total Individual Children Orphans Elders Disabled Source: SCTP Secretariat, Ministry of Gender, Children and Community Development 1.2 Purpose and Scope of the Study This study was commissioned by UNICEF Malawi for the GoM. The purpose of the study was to propose a set of indicators and methodologies that may be used to recalculate the amount of cash transfer payments to households made through the SCTP, which would ensure that the objectives of the programme are continuously met. The study assesses the various options that may be used in the recalculation of cash transfer payments to beneficiary households, and estimates their cost implications. The identification, assessment and costing of the various options is aimed at indexing the transfers levels so that the programme is able to meet its intended objectives of reducing poverty and hunger, improving health and nutrition, and increasing school enrolment of children in ultra poor and labour constrained households, while remaining financially feasible. 1.3 Methodologies The study used a combination of methodologies that included extensive desk research, interviews with stakeholders and key informants, as well as focus group discussions. More specifically, the study conducted a review of key papers, reports and other documents related to social cash transfer programmes at national, continental and global levels, in order to understand the study context and to learn from experiences generated elsewhere. This review also assisted in defining the scope of interviews with key informants and focus group discussions. Annex 1 is a list of the documents reviewed. The study used two approaches to primary data collection, namely key informant interviews (KIIs) and focus group discussions (FGDs) in which both qualitative and quantitative responses were captured and analysed. A total of 19 KIIs with officials from Government, development partners and civil society organizations were conducted. In addition, a total of 79 beneficiary households were interviewed on a oneto-one basis as key informants in Mchinji and Machinga districts, and 3 FGDs were also conducted in the two districts. Two FGDs were undertaken in Mchinji district, one with a group of beneficiaries and another one with a group of non-beneficiaries. An FGD was also conducted with a mixed group of beneficiaries and non-beneficiaries in Machinga district. Annexes 2 and 3 present lists of the key informants that were consulted at both the national and district levels. Annex 4 is a list of FGD participants. Table 2 gives a breakdown of the gender representation of the key informants for the one- on-one interviews at national and district levels, while Table 3 presents their age details. 8

11 Table 2: Gender Categories for Key Informants Location Gender Men Women Lilongwe (National Level) 11 8 Mchinji 8 30 Machinga 5 36 Total Table 3: Age Categories of the Beneficiary Key Informants Age Group Location Mchinji Machinga Elderly (65+ yrs) Middle Age (26-64 yrs) Youth (15-25 yrs) 1 3 Children (0-14 yrs) 0 0 Total For the FGDs, a total of 23 individuals were consulted (8 men and 13 women) in both Mchinji and Machinga districts. The various questionnaires and guiding questions for the KIIs and FGDs are presented as Annexes 5, 6 and 7, respectively. 1.4 Study Limitations The results of the analysis summarised in this report could have been improved in several ways. First, the poverty analysis in the report is largely based on the second Integrated Household Survey of 2004, published in 2005 (hereafter IHS, 2005 or IHS 2). Supplemental poverty data are based on the annual Welfare Monitoring Surveys (WMSs), especially WMS (2007) which is the last WMS to report districtspecific poverty profiles. It is important to state that the WMS (2007) poverty profiles are themselves based on IHS (2005) output. Apart from being relatively old, both the IHS (2005) and WMS (2007) reports do not present adequate details about the poor and ultra-poor, as highlighted in the analytical sections of this report. The GoM conducted another IHS in 2011, the results of which had not yet been published at the time of finalising this report. It is highly likely that the results of this analysis could have significantly benefited from the availability of more recent poverty data. Second, as presented in Section 1.3, the primary data analysis conducted in this study was based on small samples collected only from 2 of the 7 districts in which the SCTP is currently being implemented. As such, generalisations of the findings can only be made with great caution in view of the potentially nonrepresentative nature of the respondent beneficiaries. Additionally, the study converts Malawi kwacha (K) values into their United States dollar ($) equivalents using the official exchange rate of K = $1.00. Current foreign exchange market trends suggest that the kwacha is extremely over-valued, and parallel market rates in the region of K = $1.00 prevail in some parts of the country. As such, the conversion in this paper may not reflect the market conditions, notwithstanding that the analysis endeavours to examine the cost implications of a major devaluation of the domestic currency in the SCTP. 1.5 Organisation of the Report This report has been organized as follows. The next section presents a contextual analysis of the Malawi SCTP. It gives the poverty and social security situation, the interventions that have been put in place, the policy and regulatory environment and the financing of the SCTP. Section 3 describes the determination of the national poverty profile and the targeting of SCTP beneficiaries, drawing from the existing literature. It also presents a discussion of some of the guiding principles of the SCTP. Section 4 presents the determination of the cash transfer levels. It appraises the determination process for the current cash transfer levels, analyses alternative approaches to determining the levels, and proposes a tool for the determination of the cash transfer levels. Section 5 analyses the cost implications of using the level determination procedures explored in the report, and Section 6 presents the recommendations and conclusion. 9

12 2. A Contextual Background of the Malawi SCTP 2.1 Poverty and Vulnerabilities in Malawi The WMS (2009), the Malawi Poverty and Vulnerability Assessment (2007) and the IHS (2005) are the most recent sources of information on the poverty levels in the country. The WMS and the IHS define a household as poor if its annual per capita consumption expenditure is below a threshold or a poverty line. The poverty line is a subsistence minimum expressed in Malawi kwacha based on a cost of basic needs methodology which has two parts: (a) minimum food expenditure based on the food requirements of an individual, and (b) critical non-food consumption. Individuals or households whose consumption is lower than the total poverty line are defined as poor, while those whose total expenditure falls short of that necessary to meet the minimum food requirements are categorized as ultra-poor. This process provides an absolute measure of poverty where the poverty and ultra-poverty lines were respectively established as K16,165 and K10,029 per person per year in 2004 (IHS, 2005). According to the WMS (2009), the proportion of the population living below the poverty line in Malawi fell from 52.4% in 2004 (IHS, 2005) to about 39% in The ultra-poor and moderately poor proportions were estimated at 15% and 25% respectively in The proportion of the ultra-poor in Malawi declined in the period from 22% (IHS, 2005) to 15% (WMS, 2009). Poverty is dynamic, with individuals and households shifting frequently from one category to another. This could be due to a harvest shock which can tip large numbers of the non-poor into poverty. In order to understand poverty in Malawi, it is also important to understand how vulnerability has contributed to the poverty dynamics. Vulnerability is defined as the inability of households to deal with shocks to their livelihoods. The following are the key vulnerabilities affecting Malawians at national level: 1. Agricultural vulnerabilities that are caused by erratic rainfall, shortage of land for agricultural production, limited access to farm inputs and credit, and lack of livestock as assets. 2. Economic shocks and processes resulting from undiversified livelihoods, weak markets, interaction between transitory shocks and chronic poverty. 3. Demographic vulnerabilities due to high population growth, increasing number of households headed by women, children and the elderly. 4. Health and nutrition risks including HIV and AIDS According to the GoM (2011), there are two main causes of poverty in Malawi, namely: Limited livelihood sources where most households earn their livelihood only from their household farm and fishing. However, the average household farm sizes are declining with population increase and with declining agricultural productivity caused by deteriorating soil fertility, among other factors. In addition, over-fishing is causing declining catches and affecting the earnings from the fish. Seasonality in time use is another factor that is contributing to poor livelihood because of the substantial underemployment of the people for most of the year. Poor infrastructure is another factor that is adversely affecting access to centres of economic activities such as markets hence leading to limited livelihood sources. Pervasive risks and high vulnerability to shocks which include rainfall and food price variability and volatility in space and time, illnesses and deaths. Frequent and widespread existence of shocks results into large movements into and out of poverty in Malawi. Most households have limited ex ante strategies to mitigate risks due to lack of access to financial services and poorly functioning food markets which place a premium on staple production. Households are therefore forced to 10

13 resort to ex-post coping mechanisms which often deplete household assets and entail permanent damage to the household s ability to engage in productive activities. In addition to the above two factors, overdependence on rain fed agriculture and limited access to farm inputs and produce markets have compounded the poverty situation in the country. The Malawi Poverty and Vulnerability Assessment (GoM/World Bank, 2007) reported that poverty in Malawi manifests itself through the following: high mortality rates; low life expectancy; and malnutrition. Low school attainment and poor health and nutritional status during childhood are other major causes of poverty in Malawi. Although poverty is widespread in Malawi, it is more concentrated in the rural areas and in the southern region of the country. 2.2 Consequences and Impacts of Poverty Individuals and households caught up in poverty often face a multitude of problems which have dire consequences on their livelihoods. Often times the consequences of poverty are pervasive and mutually reinforcing in that the many effects of poverty lead into its persistence. In Malawi, the poor lack and have limited access to social and economic services such as health, education, water and sanitation, and food security. They face high disease burden due to common illnesses such as malaria, diarrhoea, as well as HIV and AIDS related illnesses. This leads to loss of wellbeing due to loss of productivity from the illnesses and/or from taking care of the sick. The resultant deaths cause loss of human capital. Children from poor households tend to have no or limited access to education, which affects their future development and the earning potential of the households, leading to a vicious cycle of intergenerational poverty. The level of poverty influences the nutritional status of individuals and households. Extremely poor households are more likely to suffer from chronic and acute malnutrition due to constant exposure to hunger and food insecurity. Malnutrition leads to reduced immunity, resulting into increased risk of morbidity and mortality. Malnutrition also leads to reduced mental and physical development of children, resulting in poor performance in schools and, therefore, low academic and professional achievements. It is estimated that productivity losses due to disease, death and reduced earnings potential caused by low academic achievement will cost Malawi about $446 million between 2006 and 2015 (GoM, 2011). In Malawi, most poor households earn their livelihoods from on-farm employment. However, with limited access to land, declining productivity of the land, effects of climate change and environmental degradation, as well as depressed crop prices and substantial underemployment due to seasonality of the agricultural sector, there is a substantial proportion of the population which still remains cut off from major economic activity and livelihood opportunities. From desperation and lack of viable sources of livelihoods, people that are trapped in poverty engage in coping strategies that are further destructive and harmful to their livelihoods and the external environment such as selling productive assets, violent crime, prostitution, burning charcoal, brewing illicit alcoholic beverages and child labour - strategies that exacerbate poverty in the long term. 2.3 Interventions and Intervention Linkages Social protection in Malawi is defined in the context of social support which includes all public and private initiatives that provide income or consumption transfers to the poor, protect the vulnerable against livelihood risks, and enhance social status and rights of the marginalized. The overall objective is to reduce ultra-poverty as well as the economic and social vulnerability of poor and marginalized groups (GoM, 2009). The social protection instruments in Malawi are categorized into the following: direct welfare instruments, productivity enhancing instruments, market interventions and transformative policy changes (Chirwa, 2010). These can be looked at as a package that is used to target the poor and ultra poor individuals and households, in order to address their livelihood needs. 11

14 2.3.1 Direct Welfare Programmes Direct welfare instruments in Malawi include both conditional and unconditional cash transfers, supplementary feeding programmes and food aid. There are currently two direct welfare schemes in Malawi at various levels, as follows: The SCTP implemented by the GoM at local council levels as described in Section 1 of this report. The Supplementary Feeding Programmes, particularly the school feeding programmes implemented in various districts of the country by the Ministry of Education with support from the World Food Programme (WFP), Mary Meals, Millennium Village Project Zomba and Land O Lakes. These are aimed at improving school enrolment, attendance, retention and the nutrition status of children of school going age. The WFP s School Meals Programme started in 1999 as a pilot in one district and is currently being implemented in thirteen districts in the southern and central regions of the country. Mary Meals School Feeding Programme started in 2000 and it targets districts that are not targeted by the WFP s School Feeding Programme Productivity Enhancing Programmes These are Public Works Programmes (PWPs) and Agricultural Subsidy Programmes implemented by the GoM with support from development partners. Examples of the Productivity Enhancing Programmes in Malawi include the following: Public Works Programmes where individuals and households with labor are engaged in various public works initiatives, and earn income for their labor. An example is the Local Development Fund Public Works programme (formerly known as MASAF PWP) implemented through local councils with support from the World Bank. This is a safety net for poor households as a cash transfer strategy through labor intensive public works that create employment. The main activities include rehabilitation and construction of economic infrastructures. Another example is the Income Generating Public Works Programme supported by the European Union, whose main aim is to achieve durable poverty alleviation and food security by improving the overall socio-economic status of households through such initiatives as addressing lack of accessibility to rural areas; developing sustainable fuel wood and timber supplies; improving dry season gardening and providing an alternative to the distribution of food to needy communities and to replace these food handouts with projects and activities that enable communities to achieve longer term food security (Chirwa, 2010). Farm Input Subsidy Programme (FISP) which aims at promoting access to and use of farm inputs (mostly fertilizers and improved seed) among smallholder farmers, in order to increase agricultural productivity. The FISP is largely financed by the GoM with support from development partners especially through the purchase of improved seed, and the main objective of FISP is to achieve household food self sufficiency and increased income through increased food and cash crop production. 2.4 The Policy and Regulatory Environment The GoM, with support from development partners, developed the National Safety Net Strategy in 2000 and the National Safety Nets Programme (NSNP) in 2001 within the context of the Vision 2020 and the Poverty Reduction Strategy Paper (PRSP) developed in 2002 to address chronic poverty and vulnerability. The key objective of the NSNP was to reduce poverty and vulnerability of the poor and most vulnerable sections of the Malawi society, and it comprised the following sub programmes: Public Works Programme, Targeted Nutrition Programme, Targeted Inputs Programme, and Direct Welfare Transfer Programme (GoM, 2011). Implementation of the NSNP faced a number of challenges including poor coordination, 12

15 inadequate funding, programme design and capacity limitations, and lack of policy guidelines for implementation of interventions. Given these challenges, the GoM, in consultation with stakeholders, shifted focus from addressing poverty and vulnerabilities through safety nets to the social support approach. This change culminated into the inclusion of the Social Protection and Disaster Risk Reduction theme into the first Malawi Growth and Development Strategy (MGDS I), a second generation PRSP which was formulated for the period The GoM is also in the process of finalizing the National Social Support Policy whose aim is to facilitate the implementation of public and private programmes that will provide income or consumption transfers, protect against vulnerability and enhance the social status and rights of the ultra-poor and the moderately poor. The policy is yet to be adopted for implementation by Cabinet. In order to support the implementation of the National Social Protection Policy, the GoM developed the National Social Support Programme (NSSP) in The NSSP has the purpose of guiding all social support stakeholders, including Government, civil society and faith based organizations, the private sector as well as development partners in championing government priorities on social support. Specifically, the NSSP is aimed at achieving the following: Defining key strategies to improve the socio-economic status of the poor and vulnerable. Providing reference guidelines to all stakeholders in the design, implementation and monitoring of social support programmes. Providing guidelines for cost effective, predictable and sustainable interventions to the benefit of beneficiaries, implementers and financiers. Establishing an institutional framework with the mandate to initiate, coordinate, implement, monitor and evaluate social support programmes. The development and envisaged implementation of the NSSP has strong linkages with other national economic and social policies and with disaster risk reduction strategies, including the following: the revised National HIV and AIDS Policy; The National Youth Policy; the Agriculture and Food Security Policy; The National Gender Policy; the National Policy on Orphans and Vulnerable Children; the Sexual and Reproductive Health Policy; Early Childhood Care and Development Policy; the National Environment Policy; the National Land Policy; the Equalisation of Opportunities (Disability) Policy; the Decentralization Policy; the National Nutrition Policy and Strategy; and other relevant programmes in agriculture, education, health and labour. It is expected that through synergies with these policies, the NSSP will contribute to asset creation and protection, income generation; strengthen human capital and stimulate economic activities; promote social empowerment, reduce income inequality and break intergenerational cycle of poverty; and ensure social and political stability and fulfilment of human rights and freedoms (GoM, 2011). The NSSP also recognises the existence of global and regional development frameworks such as the Millennium Development Goals (MDGs), the Universal Declaration on Human Rights, the Convention on the Rights of the Child (CRC), and the Convention on the Elimination of all forms of Discrimination against Women. In the MGDS II which succeeded the MGDS I, Government has also included a theme on Social Support and Disaster Risk Management. The interventions on poverty and vulnerabilities in the MGDS are closely related to the interventions under other themes, especially on Sustainable Economic Growth, Social Development and cross cutting issues. There is concern among stakeholders, however, that extended delays in the adoption of the National Social Protection Policy reflect the GoM s lack of commitment to social protection. It is speculated that the adoption of the policy could unlock resources into social protection. 13

16 3. National Poverty Profile and SCTP Beneficiary Targeting 3.1 Measures of Poverty in Malawi Malawi principally uses a national measure of poverty and equality that compares the income measure of an individual s consumption-related expenditure with a cost-of-basic-needs threshold. This is a common procedure adopted by the World Bank for developing countries. In practice, this poverty assessment procedure uses a household welfare indicator defined as the total annual per capita consumption expenditure (including implicit expenditure of own production) reported by a household. This is expressed in Malawi kwacha, deflated to February/March 2004 prices 3. Second, a threshold level of welfare that distinguishes between poor and non-poor households is established, and defines the poverty line. The poverty line is technically a subsistence minimum based on the cost-of-basic-needs methodology, and comprises two parts as already described in Section 2.1 above: (a) minimum food expenditure based on the food requirements of an individual, tied to the recommended daily calorie requirement - which defines the ultra-poverty line; and (b) critical non-food consumption, estimated based on the expenditure patterns of households whose total expenditure is close the minimum food expenditure. The sum of the minimum food and non-food expenditures define the poverty line. Individuals or households whose consumption is lower than the poverty line are poor, while those whose total expenditure falls short of that necessary to meet the minimum food requirements are ultra-poor. This process provides an absolute measure of poverty. The poverty and ultra-poverty lines were established as K16,165 and K10,029 per person per year in 2004 (IHS, 2005). The poverty gap 4 in Malawi was estimated at 17.8% overall and 5.3% among the ultra poor. This meant that the poor on average were subsisting on 17.8% less than the poverty line, and the ultra poor on average survived on 5.3% less than the ultra-poverty line. The poverty line of K16,165 was equal to K44.3 or US$0.5 per person per day, and the ultra-poor were subsisting on less than K26.40 per person per day. As an alternative, the World Bank commonly measures national poverty in terms of the ability of a person to live on at least the local currency equivalent of $1.25 per day at 2005 international prices (i.e., adjusted for purchasing power parity (PPP) at the dollar value in 2005). Using the latest available PPP conversion factor of K = $1.00, the implied poverty line for Malawi is K19,468 per person per annum. It is clear that this measure is in respect of poverty per se, and cannot be compared with the ultra-poverty measure that is most relevant in the context of the SCTP. A poverty headcount ratio measures the proportion of the population that lives below the defined poverty line. Based on IHS (2005) computations and subsequent data annually generated through the WMSs, the National Statistical Office releases poverty headcount ratios for Malawi. The available headcount ratio based on the $1.25/day measure is for The ratios based on IHS and WMS are also available by region and rural-urban split up to 2009, and by district up to Table 4 shows the available published ratios for Malawi. Significant progress was made in reducing poverty between 2004 and 2006, but this slowed down thereafter. Most of the poor live in rural areas, but a possible increase in urban poverty is discernible. Since the poverty line based on the $1.25/person/day measure is generally higher, this measure tends to report higher poverty incidence than the national measure. Moreover, because the post-2004 poverty statistics are based on IHS (2005), their reliability tends to decline over time. It is anticipated that the latest IHS conducted in 2011, whose outcomes have not yet been published, will provide a better picture of the status of poverty in Malawi. Table 4 also shows that the incidence of poverty has a geographical perspective in Malawi. More specifically, Annex 8 shows the poverty incidence by district in The southern region has a greater share of the poor with poverty and ultra-poverty incidences being higher than anywhere else in the country. 3 The IHS (2005) upon which the calculations are based was conducted in this period. 4 The poverty gap is defined in terms of how far below the poverty line households are found, on average, expressed as a percentage of the poverty line. Those households that are close to the poverty line could be improved out of poverty with less effort than those that are far below the line 14

17 The poorest three districts in Malawi were all in the Southern Region (Machinga, Mulanje, Zomba), and the least poor rural districts in Malawi were all in the Central Region (Ntchisi, Kasungu, Lilongwe). The poorest urban area was Zomba City and the richest was Blantyre City. According to the Malawi Poverty and Vulnerability Assessment (2007), the prevalence of ultra-poverty in Malawi is higher in the following categories: female headed households; households headed by very young or old persons; households located in the rural areas of the South and Central regions; larger households especially households with more young children and dependents; and households with low levels of education, limited economic opportunities, limited involvement in cash crops, and small landholdings. A more recent presentation of this information which is key for the transfer level costing procedures developed in this study is unavailable. Table 4: Incidence of Poverty in Malawi ( ) Poverty Measure Poor IHS (2005) Malawi Urban Rural Ultra-Poor (IHS (2005) Malawi Urban Rural IHS Poor ($1.25/person/day Malawi WMS Headcount (% of population) WMS WMS WMS WMS Beneficiary Targeting in the SCTP The SCTP in Malawi qualifies as what is called a needs-based social assistance programme. Typically, such programmes provide a monthly cash transfer to the poorest households based on a needs assessment. Apart from Eastern Europe and the former Soviet Union where these programmes are common, such last resort programmes have also been implemented in African countries such as Mozambique, South Africa, Kenya, Tanzania, Senegal, Cameroon and Zambia (Arnold et al., 2011; Slater et al., 2010; ADB, 2006; Gassmann & Behrendt, 2006; Devereux et al., 2005; Schubert, 2005). Several methods are used in the identification of the target groups in social security programmes in general, as summarised in Annex 9. In terms of needsbased programmes such as the SCTP, beneficiaries are usually identified based on a means test, a proxy means test, or a combination of the two (Grosh, 2009). In Mozambique and Zambia, the combination approach was adopted. It is a general rule to keep the design of these programmes simpler in low-income, low capacity countries, and more sophisticated in middle income countries. The targeting of beneficiaries is known to be problematic when a significant proportion of the population is poor and income differences in the bottom deciles are marginal (Ellis, 2009; Slater et al., 2010). A fundamental point in the identification of the target group is the determination of the population that should be targeted. In most middle income countries, such programmes have tended to target between 3% and 10% poorest proportion of the population. The eligible target groups nationally comprise 10% of the population in Zambia and Malawi, and 19% in Kenya (Slater et al., 2010). This determination requires a national process for assessing the poverty profile of the country s population, hence the determination of the poor and non-poor. The Malawi SCTP is designed to target the poorest 10% of the population, categorised as ultra-poor and labour-constrained. The ultra-poor constituted 15% of the population during the period , such that the SCTP target group coincidentally constituted two-thirds of the ultra-poor in that period 5. By these criteria, it was officially estimated that there were about 300,000 eligible households in Malawi, based on IHS (2005) (see GoM, 2010). 5 However, the ultra-poor constituted 22% of the population in 2006, such that the 10% programme target represented less than one half of the ultra-poor. 15

18 As reported by Miller et al. (2008), the SCTP in Malawi uses a community based, multi-stage participatory targeting process. Community volunteers determine the eligible households in their villages, guided by the programme s Manual of Operations which provides proxies of poverty for community members to consider (e.g., the poorest households eat only one meal per day). The procedure involves household interviews conducted by the Community Social Support Committee (CSSC) trained by the district SCT secretariat; verification of the interview results by a community meeting at which eligible households are identified; verification of the eligibility of households by extension workers; and consideration and approval of the proposed list of eligible households by a district-level Social Support Committee. Ideally, this process aims at selecting the neediest households up to a cut-off point, which currently ought to be twothirds of the ultra-poverty incidence for the district in order to ensure that the poorest and labourconstrained 10% of the population is targeted. Miller (2009) notes that proxy means testing is somewhat used in the Malawi SCTP, but there is need to ensure that the proxy is appropriate, well-understood, easy to identify and field-tested. The GoM (2010) also proposes that the targeting process should be formally verified by a proper proxy means test, in order to increase objectivity. Evidence on the ground suggests that the Malawi SCTP targeting process simply seeks to identify the poorest 10% of the population in each district, without regard for the district s poverty profile in relation to other districts in the country. This suggests that the programme may not be targeting the poorest households when the national picture is considered. Additionally, while the normal procedure is to start with programme implementation among the poorest individuals, households and geographical areas (Arnold, 2011, Samson et al., 2006), it is the case that the project was initially piloted in Mchinji which had only the ninth highest incidence of ultra-poverty in 2004 and the sixth lowest incidence in Apart from Machinga (highest incidence in 2007), the inclusion of the ultra-poorest districts in the piloting phase has not been high. It is understood that, among other considerations, Mchinji was chosen in order to facilitate the administration of the piloting phase, because it was then the poorest among districts that are close to Lilongwe. 3.3 Determination of Target Beneficiary Households This study estimates the total number of eligible beneficiary households for 2012 using the following procedure. Let i denote a specific district and t denote the current period (year). Recognise that, currently, the published census data do not report the annual intercensal growth rates in the number of households per district, and that these are inherently different from the annual intercensal growth rates in the population per district. Then: a. The annual growth rate in the number of households for each district i is calculated by iteratively solving for the district-specific compound rate ( r i ) in the compounding formula: where P r i P r 10 i, 08 i,98 1 i i,08 = annual intercensal growth rate in the number of households for district i P = number of households in district i in 2008 P i,98 = number of households in district i in 1998 National Census data are used to obtain P i, 08 and P i, 98 b. The total number of households per district in 2008 obtained from the 2008 Population and Housing Census is compounded at the rate of r i as calculated above, to obtain an estimate of the number of households per district in 2012, say hh i, 12. For Neno, Balaka and the four cities, where necessary, data splitting is accomplished in relation to Mwanza, Machinga and the corresponding host districts for the cities respectively, by assuming constant population proportions. 16