Malawi - Human resources and poverty : profile and priorities for action

Report No. 15437-MAI Malawi Human Resources and Poverty Profile and Priorities for Action March 19, 1996 Human Resources Division Southern Africa Department Africa Region Document of the World Bank   * 0 0 0 0 0 0 0 e e 0 0 0 0 0 0 0 0 0 0 0 a 0 0- 0 a e e a IM a Ia v im Human Resources and Poverty Profile and Priorities for Action November 1995 This report was prepared for the Government of Malawi by a team from the Human Resources Division, Southern I w The World Bank Africa Department of the World Bank. l Southern Africa Department  ACKNOWLEDGMENTS This report has been prepared at the request of the Government of Malawi as the World Bank's input for their Poverty Alleviation Program. The analysis builds on the existing literature and on the insights of many people with whom the Bank has had extensive con- sultations during various visits to Malawi since October 1994. The report is based on data sets made available by the National Statistical Office in Malawi to the World Bank team in October 1994. The scope of the report was reviewed by both government personnel and the research community in Malawi. An earlier draft of the report was presented at several workshops with policy makers, researchers and donors in Malawi in July 1995. This report was written by a team including Helena Ribe (team leader), Ingeborg Astrid Kleppe, Jeff Alwang and Trina Haque. Jeff Alwang conducted the analysis on rural smallholders and Florencia Castro-Leal conducted the analysis on education. Additional work was prepared by Ingeborg A. Kleppe and Venanzio Vetla (human resources, popula- tion, and nutrition), and by Jeff Alwang, Trina Haque, and Paul Siegel (poverty measure- ment, rural poverty and literature review). Trina Haque and Meera Venkataraman devel- oped the statistical methodology for analyzing the HESSEA data. Jeff Alwang and William S. Brown developed the statistical methodology for analyzing the NSSA data. Fiona Macintosh and Leo Demesmaker edited the report. Vinnette Gordon provided secretarial support. The team thanks: S. Kakhobwe (PAP); A. Gomani, M. Kutengule B. Lodh, A. Chulu (EP&D); W Chilowa, S. Khaila (CSR); C. Mataya, M. Zeller (Bunda College); L.F. Golosi, T. Konyani, C. Machinjili (NSO); R. Ayoade (MoAG); E. Chisala, N. Hahn (UNICEF); P. Peters (HIID); and representatives from Chancellors College and FEWS for their valu- able comments. The team also received useful comments from the following World Bank staff: D. Bruns, R. Grawe, B. Kafka, K. Kostermans, H. Schaeffer, M. Salim, and G. Tidrick. The peer reviewers were: K. Krumm, J. van Holst Pellekaan, and P. Lanjouw. Maps appearing in this report are for the convenience of readers. The denominations used and boundaries shown do not imply any judgement on the legal status of any territory or any endorsement or acceptance of such boundaries. A summarized version of this report may be obtained from: Internal Documents Unit HB1-151 Ext. 34641  GLOSSARY ADD Agricultural Development Division ADMARC Agricultural Development and Marketing Corporation AE Adult Equivalent AIDS Acquired Immune Deficiency Syndrome COL Cost of Living Index CPIs Consumer Price Index CSR Centre for Social Research DHS Demographic and Health Survey EA Enumeration Area EP&D Ministry of Economic Planning and Development FEWS Famine Early Warning System GDP Gross Domestic Product GNP Gross National Product HA Hectare HESSEA Household Expenditure and Small-Scale Economic Activities HIID Harvard Institute for Inrernational Development HIV Human Immunodeficiencv Virus IMF International Monetary Fund Kg Kilograms LC Lower Cutoff Line MCH Maternal and Child Health MDHS Malawi Demographic and Health Survey MK Malawiani Kwacha MoAG Ministry of Agriculture MOE Ministry of Educationi NSO National Statistical Office NSSA National Sample Survey of Agriculture PAP Poverty Alleviation Program RDP Rural Development Project SDA Social Dimensionis of Adjustment UC Upper Cutoff Line UNICEF United Nations Children's Fund  m ~~~~~~~~Malawi * Profile and Priorities for Action Priority Indicators of Poverty Population Total population ..................... 11 million Health Population growth rate .... 3.3% annually Mortality rates Population share: Rural .................... 90% Urban ...........8% Infant mortality rate 1988-1992 ... 134.3 BOMAs .. 2% 1978-1982 ... 136.4 (Sources: HESSEA 1990/1991, WDR) Child mortality rate 1988-1992 ... 114.9 1978-1982 ... 140.8 Population Classified Maternal mortality rate 1986-1992 ... 620.0 as "Poor" Infant mortality number of cnidren dying before their Percent, By Rural Development Project Area first year per 1.000 live oirths (Incomes below 40th percentile) Child mortality = number of ch dren dying between 12 and 59 months per 1,000 livF. births Maternal mortn itv y maternal morta ity rate d vided by general ferti ty rate per 100.000 live births. Nutritional status of children under 5 years old Stunted growth ........... 49% 4-25% Underweight ........... 27% 26-35% (Source: MDHS 1992) 36-45% 46-60% F.4 Missing or incomplete data (Source: NSSA 1992/1993)  Indicators Education Enrollment Net primary Quality of primary education enrollment rate for girls 50 Students/ 'Net enrollment is defined as the official number of primary permanent classroom ratio ................... 422 school-age pupils laken as a percentage of total school- age population. Students/ qualified teacher ratio .................... 131 (Source: MOE 1994/1995) Public spending on primary education Unit costs: universily student/primary student ........ 103/1 (Source: HESSEA 1990/17991) Poverty and Inequality Distribution of Incomes Income for rural smailholders for rural smaliholders (annual per capita) 7 Malawi Kwacha 80% below .......... 241 40% below .......... 117 CD 20% below ..... ..... 54 (Source: NSSA 1992/17993) 0-I , 0 300 800 4600 Landholding size Income (MK/AE/Year) for rural smaliholders Source: (NSSA 1992/1993) Less than 0.5 Ha .......... 41% 0.05-1.0 Ha ........... 31% Gini-coefficients Less than 1.0 Ha .......... 72% All Malawi ............ 62 (Source: NSSA 1992/1993) Rural smallholders ............ 57  i | ~~~~~~~~~~~~~~~~~~Malawi - Profile and Priorities for Action Contents Introduction ....................................................................1 1.1 Review of literature .............................................................. 1 1.2 Content and structure .............................................................. 2 Data sources .............................................................. 2 Profile of Human Resources for Malawi ................................................................... 5 2.1 A very young population .............................................................. 5 Population doubled in thirty years .................................... .......................... 5 Half the population is under 15 years old .............................................................. 5 Rural households have more children per adult ................................................... .... 6 2.2 Poor health and malnutrition .............................................................. 7 Child malnutrition is widespread ................................. ............................. 7 lnfant and child mortality are high .............................................................. 7 Child mortality is more prevalent in the Central region ................... ....................... 8 Maternal mortality is high .............................................................. 8 HIV and AIDS are spreading ...................... ........................................ 8 Sanitation is poor and there is little infrastructure ................................. .................. 8 2.3 An overstretched educational system ................................. ............................. 10 School enrollment .............................................................. 10 Important gains in school attendance .............................................................. 10 Enrollment rates are low and the poorest children are least likely to be in school ... 11 The poorest girls are least likely to go to school ......................................11............... 1 Enrollment rates are higher in the Northern region ............................................... 12 There is considerable age/grade mismatch ............................................................. 12 Most primary graduates never attend higher education .................. ....................... 13 Recent changes in enrollment .............................................................. 13 Important inequities remain in primary education ........................... ..................... 13 Public spending on education .................... .......................................... 14 Public spending on primary education increased, but bias against primary education persists ......................... ..................................... 15 Public spending in education has become more pro-poor ...................................... 16 Services and quality have deteriorated as enrollments have surged ........... .............. 17 2.4 Human resources development in an international context ................. ....................... 18 Living conditions are among the poorest in the world although public spending is high .............................................................. 18 2.5 The state of human resources .............................................................. 20 Profile of Poverty for Malawi ................................................................... 23 3.1 Identifying the poor ................................................................... 23 Establishing a meaningful poverty line .................................................................. 23 The household is the unit of analysis ................................................................... 25 3.2 The countrywide picture of poverty ................................................................... 26 Incomes and expenditures suggest widespread deprivation .............. ...................... 26 Most of the poor live in rural areas ................................................................... 26  Contents I ii Poverty is most prevalent and severe in rural areas ............................ ..................... 27 The prevalence of poverty varies across and within regions ............... ..................... 27 Major cities have less poverty ......................... ..................................... 28 Poverty prevalence in BOMAs is closer to rural than city levels ........... ............... 28 3.3 Characteristics of poor households .............................................................. 29 No education among household heads is mainly a rural problem ........... ............... 29 Poor households have the highest dependency ratios ............................................. 29 Although most poorer households are male-headed, female-headed households are more likely to be poor ........................................ 30 Most female heads of households are divorced, widowed or single ........... .............. 31 Female-headed households who receive regular cash remittances are poorer .......... 32 3.4 The geography of rural poverty .............................................................. 32 The most populated ADDs in the Southern and Central regions have the most severe poverty .............................................................. 32 Mzuzu is poorer than other ADDs in the North .................................. ................. 33 Smallholders in Kasungu are much better-off than other smallholders in Malawi .............................................................. 34 The highest severity and densities of poor households are at the Mozambique border .................... .......................................... 35 There are poverty pockets in the North .............................................................. 36 Scope for geographical targeting .............................................................. 36 3.5 Main factors associated with poverty in rural Malawi ............................ ..................... 36 Landholdings and assets .............................................................. 37 Poorer households have least access to land under cultivation ............. ................... 37 Poverty prevalence and cultivated landholdings show the same geographic pattern .............................................................. 37 Households with more members have less land per person ............... ..................... 38 Female-headed households are more likely to farm small areas ............ .................. 38 Cultivated land size alone does not predict household income .............................. 38 Poorer smallholders use few inputs and lack assets ................................................. 39 Female-headed poorer households have the fewest productive assets ...................... 41 Crop profile .............................................................. 41 Local maize is the main crop for the poorest smallholders ..................................... 41 Poorest smallholders do not farm burley tobacco ................................................... 43 Poorer households are net purchasers of maize ........................................... ........... 43 3.6 Limited income from off-farm sources .............................................................. 43 Off-farm employment .............................................................. 44 Smaliholders earn little off-farm income .............................................................. 44 Off-farm employment provides a higher share of income for poorer households ... 44 Sources of income vary across regions .............................................................. 45 Female household heads have less off-farm employment than male heads ............. 46 Medium-sized farmers are a mixed group .............................................................. 47 Livestock .............................................................. 47 Livestock ownership is positively related to income ............................................... 47 Livestock ownership varies by geography and income ........................................... 47 3.7 Main poverty determinants in Malawi .............................................................. 48 Landholding size and location and smallholder incomes ....................................... 48 3.8 The state of poverty in Malawi .............................................................. 49  iii | Malawi - Profile and Priorities for Action Implementing a Strategy to Reduce Poverty in Malawi ......................................... 55 Setting priorities .............................................................. 55 4.1 Developing human resources .............................................................. 56 Expanding access and reducing inequities in the social sectors ............. .................. 56 Increasing effectiveness and quality of social services ...................... ....................... 56 4.2 Improving rural livelihoods ............................................................... 57 Ongoing reforms are necessary but insufficient for the poorest .............................. 57 Economic reforms should be broadened to reach more smallholders .......... ........... 58 Examining land policies ............................................................... 58 Increasing off-farm incomes ...................... ........................................ 59 4.3 Safety net interventions for the poorest .............................................................. 59 Supporting transfer programs for the poorest ........................................................ 59 Distributing free inputs ............................................................... 60 Improving poverty monitoring for better targeting ................................................ 60 4.4 Agenda for further study .............................................................. 60 Methodological Notes .............................................................. 63 Tables for Chapter 2: Profile of Human Resouces for Malawi ........................................................ 71 Tables and Figures for Chapter 3: A Poverty Profile for Malawi ..................................................... 73 References .............................................................. 87 Tables Table 1.1 Review of literature: Summary of findings and questions for further study .3 Table 2.1 Household size and relationship structure by location .6 Table 2.2 Malnutrition indicators in Malawi and neighboring countries .7 Table 2.3 Child mortality and life expectancy for selected African countries .8 Table 2.4 Infant and child mortality in Malawi: the past 15 years .9 Table 2.5 Regional variation in child mortality .9 Table 2.6 Water source, sanitation and flooring for rural and urban households .9 Table 2.7 Gross enrollment rates by quintiles and gender, 1990/199 1.1. Table 2.8 Gross enrollment rates in primary school by region and residence, 1990/1991 .12 Table 2.9 School enrollment: age/grade matching, 1990/1991 .12 Table 2.10 Gross primary enrollment rates by quintiles and gender, 1990/1991 and 1994/1995. 13 Table 2.11 Cross-country comparisons of education financing per student .15 Table 2.12 Public education spending on poorest and richest quintiles .16 Table 2.13 Quality indicators in primary schools, 1992/1993 and 1994/1995 .17 Table 2.14 Aggregate statiscics for Malawi compared to similar groups of countries .19  iv Contents I i Table 3.1 Poverty prevalence for rural smallholders according to different poverty lines .......................... 25 Table 3.2 Households by national and rural-urban location ............................................................... 26 Table 3.3 Poverty indices by location, using upper cutoff, percentages .................................................... 27 Table 3.4 Educational status of household head by gender and location, percentages .............................. 29 Table 3.5 Dependency ratio by income group ............................................................... 30 Table 3.6 Household composition by gender of household head ............................................................. 30 Table 3.7 Poverty prevalence among male- and female-headed households ............................................. 31 Table 3.8 Poverty in female-headed households by marital status of household head ............. .................. 3 1 Table 3.9 Dependency ratio for female-headed households by marital status ........................................... 3 1 Table 3.10 Percentage of poor female-headed households receiving cash allowanices by marital status ....... 32 Table 3.11 Percentage distribution of income group and ADD ............................................................... 33 Table 3.12 Poverty indices by ADD using the 40th percentile income cutoff ............................. .............. 33 Table 3.13 Percentage distribution of cultivated areas by poverty group ................................................... 37 Table 3.14 Percentage of households in each ADD in each cultivated area class ........................................ 38 Table 3.15 Distribution of cultivated areas and income deciles ............................................................... 38 Table 3.16 Proportion of smallholder households using purchased inputs by income groups .................... 39 Table 3.17 Percentage of households with access to credit by area cultivated, income group and ADD ..... 40 Table 3.18 Percentage of ownership of productive assets by cultivated area and income group .................. 40 Table 3.19 Farm characteristics by gender of household head ............................................................... 41 Table 3.20 Percentage of area under cultivation with different crops by size of cultivated area .......... ......... 4 1 Table 3.21 Percentage shares of total cultivated area allocated to crops by poverty group .......................... 42 Table 3.22 Shares of household maize requirements met by own production ............................................ 4'2 Table 3.23 Percentage of smallholder household income from different sources by income group ......... .... 44 Table 3.24 Shares of income received from different sources by ADD ....................................................... 45 Table 3.25 Percentage distribution of income sources by headship and income group ............................... 46 Table 3. 26 Regression analysis: Determinants of smallholder incomes in rural Malawi ............................. 48 Table Al. I Sample by stratum, number of households, and sampling weights ........................................... 65 Table A 1.2 Items included in computing the cost of living indices ............................................................ 65 Table Al.3 Head and spouse earnings and wages from SDA Module A ..................................................... 68 Table Al.4 Coding and mean wages from SDA Module A ..................................................... .......... 69 Table A2.1 Comparisons of fertility indicators between Malawi and neighboring countries .......................71 Table A2.2 Net and gross enrollment rates in primary education, 1990/1991, by quintiles and gender ..... 71 Table A2.3 Net enrollment rates in primary education 1990/1991. by region, residence, and gender ........ 72 Table A2.4 Net enrollment rates in secondary education 1990/1991. by quintile and gender .................... 72 Table A2.5 Gross enrollment rates in primary education, 1990/1991 and 1994/1995, by region and residence ..................................................... 72 Table A3.1 Educational status of household heads by gender and cutoff line, rural Malawi ....................... 73 Table A3.2 Smallholder pover ry by c haracteristic of head ...................................................... 74 Table A3.3 Percentage of households by gender of household head ...................................................... 74 Table A3.4 Percentage of households below the two expenditure cutoff lines by gender of household head ............................................................... 74 Table A3.5 Distribution of female-headed households across regions ......................................................... 75 Table A3.6 Marital status of head of the household by gender ............................................................... 75 Table A3.7 Female-headed households below the 40 percent cutoff line by age group and marital status.. 75 Table A3.8 Areas cultivated by income decile ................................................................ 75 Table A3.9 Farm size by gender of household head ............................................................... 75 Table A3.10 Poverty indices, in percents by ADD, different cutoffs ........................................................... 76 Table A 3.11 Average livestock owned by income decile .76 Table A3.12 Average livestock ownership by poverty cutoff and ADD ....................................... 77  v | Malawi * Profile and Priorities for Action Figures Figure 2.1 Distribution of population across age groups ..................................................................6 Figure 2.2 Education level attained by adults in two age groups, 1990/1991 ............................................ 10 Figure 2.3 Growth in primary enrollments from 1992/1993 to 1994/1995 by region .............................. 14 Figure 3.1 Cumulative smallholder income distribution ................................................................. 24 Figure 3.2 Distribution of incomes for rural smaliholders, per capita ....................................................... 25 Figure 3.3 Lorenz curve for national distribution of expenditures ............................................................. 26 Figure 3.4 Distribution of total household population and poor households by region ............................. 27 Figure 3.5 Percentages of households below 20th and 40th percentiles in BOMAs/Cities ........................ 28 Figure 3.6 Mean annual household incomes and Gini-coefficients for rural smallholders by ADD ........... 33 Figure 3.7 Population classified "poor" below 20th income percentile by rural development project ........ 34 Figure 3.8 Poverty gap 40th percentile by rural development project ........................................................ 35 Figure A2.1 Rural primary enrollments in 1992/1993 and 1994/1995 by regions ...................................... 72 Figure A3.1 Cumulative distribution of smallholder income ................................................................. 77 Figure A3.2 Population classified "poorest" below 20th income percentile by Rural Development Project.. 78 Figure A3.3 Area planted per adult equivalent in household by Rural Development Project ....................... 79 Figure A3.4 Hybrid maize yields by Rural Development Project ................................................................. 80 Figure A3.5 Fertizer usage by Rural Development Project ................................................................. 81 Figure A3.6 Share of hybrid maize in total area planted by Rural Development Project .............................. 82 Figure A3.7 Share of burley tobacco in total area planted by Rural Development Project ............................ 83 Figure A3.8 Persons per hospital by administrative division ................................................................. 84 Figure A3.9 Persons per well by administrative division ................................................................. 85 Figure A3. 10 Number of students per teacher by administrative division .86 Text Boxes Box 3.1 Food security and landholding size ...................................................... 43 Box 3.2 Socioeconomic classification of the population ...................................................... 51 Box Al.l Primary-level enrollment algorithm, by socioeconomic groups, in 1994/1995 ......................... 64  Introduction Introduction Reducing poverty is a central policy objective of the new The economy is overwhelmingly agricultural. Three Government of Malawi which initiated the Poverty Al- broad categories of the population are engaged in agri- leviation Programme. This created a new imperative to culture-owners of large farms (the estate sector), increase understanding of the magnitude and of the mul- smallholders (people who own their own small farms) tiple dimensions of poverty in the country. And this is and agricultural laborers (who work mainly on estates or the objective of the Profile of Human Resources and Pov- on the more prosperous smallholdings). Approximately erty presented in this report. Such knowledge can help 90 percent of the inhabitants of rural Malawi are to guide policy and investment priorities and inform the smallholders, and their main income comes from their design of programs intended to improve living condi- landholdings. tions and increase incomes of the people in Malawi. A Studies focusing on human resources agree that the greater understanding of the magnitude and the profile need for extensive investments in the social sectors is of poverty will also make it easier to implement a moni- urgent. Health and social indicators are among the poor- roringsystem to evaluate the effects of programs and track est in Africa, and Malawi has one of the lowest life ex- the progress of key indicators of poverty. pectancies in the world. Child and maternal health are documented at a critically low level. Education is scarce and most adult Malawians are illiterate. Therefore pro- vision of priority human development services such as primary health care, basic education, nutrition, water and 1.1 Review of literature sanitation is viewed as one of the most cost-effective ways of reducing poverty. A number of studies conducted since the late 1980s There is consensus that past policies have conI- have examined human resources and poverty in strained productivity of the huge rural smallholder Malawi.' A summary of the key findings of these stud- sector and resulted in very low incomes and food in- ies and of issues that need to be addressed is shown in security for these households. The policies of the pre- Table 1.1. The summary also uses inputs from policy- vious government created a dual economy by trans- makers and from the research community in Malawi. ferring customary land to the estate owners and by The studies document the main patterns of human giving them the sole right to grow burley tobacco, resources development and poverty . Their main short- Malawi's most profitable crop. This left most coming is that they cannot draw on a country-wide smallholder families with plots of land too small to data set providing information on household expen- support families and forced them to sell their labor diture and incomes. to the estates.  2 | Malawi * Profile and Priorities for Action Efforts to provide smaliholders with improved Data sources agricultural technologies and to persuade them to di- versify their crops have largely failed. Most This report uses data from three household surveys smallholders continued to grow only local maize and, conducted in the early 1990s: the HESSEA (1990/ as their agricultural productrivitty stagnated, subsis- 1991), the NSSA (1992/1993), and the DHS (1992). tence households were forced to buy more food. There The analysis presented in this report is the first at- is little off-farm work in rural areas and real wages for tempt to analyze poverty in Malawi using nationwide unskilled workers have not risen. Men had to seek data on household expenditures and income. The work elsewhere, sending remittances to support their main sources are: families. * The 1990-1991 Household Expenditure and Small-Scale The findings from this profile should provide EconomicActivities Surve (HESSEA) conducted by the greater detail about the characteristics of the poor and National Statistical Office of Malawi, is used to create a about the main factors associated with poverty, thus abLtt hnnfoaoameasure of household expenditures for Malawi on a na- answering some of the questions presented in Table tional basis. The sample consists of 6,000 households. 1. 1. In doing so these findings should guide policy TheHESSEA-the onlysource of informationoncon- and investment priorities to reduce poverty. The re- sumtio -ba e ousehol re withonational cov- sumption-based household welfare with national cover- port is also uiarended Lo identifv tOpICS for further port~~~~~~~~~~ isas neddt2dnif oisfrfrhr ae-makes it possible to analyze both urban and rural study by Malawian researchers and thus help define are-as es it also ntains iormation on surce * ~~~~~~~~~~~~~~areas. The HESSEA also contains information on sources the policy agenda for povertv reduction. ... of income, demographics, economic activities, and some social indicators. The 1992/1993 National Sample Survey ofAgriculture (NSSA), conducted by the National Statistical Office 1.2 Content and structure of Malawi, is used to create a measure of household income for rural smallholders, who are by far the larg- The report starts with a profile of human resources est group of poor people in Malawi. The NSSA sample and comparisons between aggregate social and eco- consists of observations from some 12,000 nomic indicators for Malawi and those for other simi- smallholders and includes information on household lar groups of countries. Second, household survey data characteristics, demographics, labor supply, farm la- are used to build the poverty profile to assess the preva- bor demand, agricultural practices, and livestock own- lence, depth, and severity of poverty across urban and ership and on changes in stocks, asset ownership, and rural areas and to show the extent of income inequal- the earnings of the household head and spouse. A itv. Third, household survey data are used to show shortcoming of the NSSA in analyzing rural poverty the relationship between poverty and geographic lo- is that the sample frame does not include estate ten- cation, household demograplhics, asset ownership, ants or estate owners.2 access to infrastructure and public goods, linkages to markets, sources of income, and other factors. Finally, * The 1992 Demographic and Health Survey (DHS) was the summarized findings and messages of the report carried out by Macro International Inc., in collabora- are used to develop priorities for a poverty reduction tion with the National Statistical Office of Malawi, strategy in Malawi. on a nationwide sample of 5,300 households. Very similar DHS surveys were carried out in several coun- tries in Sub-Saharan Africa in the late 1980s and early 1990s. These have made it possible to make compari- sons across countries. The DHS contains informa- tion on household demographics, assets, sanitation, and child and maternal health.  Introduction 3 Table 1.1 Review of llterature: Summary of findings and questions for further study Topic Findings Questions for further study Human resources Health Infant and child mortality rates are -How is access to and use of health facilities among the highest in the world distributed across regions? Women suffer more than men from -How are differences in health outcomes across (seasonal) malnutrition regions explained? Education Malawi has worse education indicators - What is the variation in enrollment rates across than the average for Sub-Saharan Africa gender, ages, regions, and rural/urban location? Education among the poor is much - What is the composition, incidence, and higher in urban than in rural areas efficiency of public spending in the education sector? - What are the determinants of the household demand for education and health for their members? Household characteristics Female-headed households are more - What is the relationship between poverty and likely to be poor than male-headed the characteristics of the household head? households - Do female-headed households engage in Female-headed households have less different types of income-earning activities than resources to earn off-farm incomes and male-headed households, and to what extent is are more dependent on remittances this related to poverty? Large family size and high dependency Is gender of the household head useful for ratios are associated with poverty targeting purposes? Regional and urban poverty Poverty is most prevalent in the Southern -Are there important differences in poverty Region among regions. ADDs and RDPs? Urban poverty is characterized by sub- -What are the extent and characteristics of urban standard housing, low levels of poverty? education, and limited employment opportunities Rural poverty Agricultural production Higher yield practices have not been - How much can agricultural intensification adopted by the poorest farmers reduce poverty? Maize is the predominant crop among - How important to smaliholders are the prices of smaliholders and access to purchased inputs? Expansion in the estate sector has - How will changes in the relative prices of inputs caused increased deprivation among and outputs affect the poor? smaliholders - How has the smaliholder burley program affected the poor? - How to put in place drought mitigation programs? Landholding size Landholding size is an important but not - What is the relationship between household size, perfect indicator of poverty landholding size, and the poverty status of the Most farmers cultivate very small land household? plots - What is the relative importance of land and labor constraints to smaliholder producers? - What is the relationship between land tenure status and nutrition in the households? Income sources Poor households receive higher - Do non-agricultural income-earning proportions of their income from off-farm opportunities contribute to the incomes of poor sources households? Self-employment income has decreased - How do household income patterns vary among the poorest in recent years across geographical areas and sociological characteristics (such as gender), and the poverty status of the household? - Do remittances bring households out of poverty?  4 | Malawi * Profile and Priorities for Action Chapter 1 Notes I These include Malawi: Growthl Through Poverty Reduction, World Bank (1990); Situation Analysis ofPoverty in Malawi, Government of Malawi and United Nations (1993); Poverty in Malawi: A Review ofLiterature, Centre for Social Research (1994); Poverty Profile of Rural Households in Malawi: A Summary of Recent Findings, Simler and Quisumbing included in the Agricultural Sector Memorandum, World Bank (1994); Beyond Hunger. Ignorance, and Disease: A Poverty Impact Assessmentfor Malawi, M. Kostner, et al. (1994); Policy Reform and Poverty in Malawi. A Survey ofa Decade ofExperience, Sahn et al. 1989; studies on urban poverty at the Centre for Social Research. and studies on food security in rural Malawi by Pauline Peters. 2 Estate tenants and their dependents numbered 586,000 (in 1989), or roughly 7 percent of Malawi's total population (Jaffee, Mkandawire, and Bertoli, 1989). Casual workers on estates are included, however, as these workers are technically considered to be smallholders. The families of permanent estate workers may be included, depending largely on whether they reside on the estate.  Profile of Human Resources for Malawi 1 5 Profile of Human Resources for Malawi People in Malawi face more difficult circumstances than stress on scarce land resources. The population den- people in most countries. Malawi does not have adequate sity at the time of the 1987 census was estimated to resources to secure minimum standards of health, edu- be 85 people per square km-and it has increased by cation, and nutrition for its rapidly growing population. about 15 people during the past 8 years. This situa- This section analyzes human resources in Malawi in- tion is certainly worse for the poor - land is distrib- cluding such indicators as demography, health, nutri- uted very unequally. tion, and education. Half the population is under 15 years old 2.1 A very young population The shape of the population pyramid for Malawi shows a very large proportion of children. Almost half (47 percent) of the population are under 15 years of Population doubled in thirty years age. Figure 2.1 shows the population age profile and illustrates the large number of young children rela- Between 1964, the year of the country's independence, tive to the adult population. The age structure of the and 1994, Malawi's population increased from 4 mil- population in Malawi indicates that institutions pro- lion to about 11 million. If population growth re- viding nutrition, health and education face an over- mains at the present level (3.3 percent per annum), whelming task. the population in Malawi will double in the next 20 The population dependency ratio is very high and years. The average woman bears almost seven chil- increasing. l The 1977 census shows 97 dependants dren in her lifetime. Access to and the use of modern for every 100 adults of working age, the 1987 census contraceptive methods is very low, which makes it diffi- shows 101 dependants, and the 1992 MDHS shows cult for Malawian women to control their fertility even a dependency ratio of 1.06, meaning that Malawi now though there is evidence that their desired fertility level has 106 dependants per 100 adults of working age. It is lower than the actual (Annex 2: Table A2.1). is therefore common for Malawian children to be The worst impact of the rapid population growth working before the age of 15 thereby reducing the is likely to be felt by the poorest households since actual dependency ratio. However, economic activi- they tend to live far away from social services and ties compete with school attendance and probably are they are the last to be reached if services are not ex- related to the high drop-out rates for primary educa- panded. The high population growth places great tion in Malawi.  61 6 ~~~~~~~~~~~~~~~~~~~~Malawi * Profile and Priorities for Action Rural households have more children per adult The most common relationship structure is tvo re- lated adults: a man and a woman. Only one adult Table 2.1 resident is more frequent in rural households, while Household size and relationship urban households have a higher proportion of adult structure by location residents. Urban households also tend to have more memnbers than rural households, but the dependency Rural Urban Total ratio in urban households is lower than in rural house- Percent of household holds, 0.90 compared to 1.08 (Table 2.1). One fac- population 92 8 100 Mean household size tot contributing to this may be that fertility rates are (Number of persons) 4.4 4.8 4.5 lower in urban areas. Foster children are also more Percentage of prevalent in urban households. Another factor could households with: be the presence of rural migrants who have joined One adult 19 13 18 the households of relatives in urban areas. Two related adults: Consequently, the average urban household has -of opposite sex 45 42 44 -of same sex 4 5 4 more potential providers than the average rural house- Three or more hold. Urban households may therefore be less likely related adults 28 32 29 to be poor since there are more people to provide for With foster children 19 24 20 dependent household members. On the other hand, Other 4 9 5 in poor urban households, the large number of adults Source: MDHS 992 may mean that housing is overcrowded. Figure 2.1 Distribution of population across age groups Age Age 80+ EN 80+ 75-79 II 75-79 70-74 Males EU Females 70-74 65-69 EZi 65-69 60-64 60-64 55-59 r _ 55-59 50-54 L111_50-54 45-49 45-49 40-44 I 40-44 35-39 E 35-39 30-34 30-3d 25-29 25-29 20-24 20-24 15-19 15-19 10-14 10-14 5-9 _ _:: _ 5-9 0-4 0-4 10 8 6 4 2 0 2 4 6 8 10 Percentage of population in each age cohort Source: MDHS 1992  Profile of Human Resources for Malawi 2.2 Poor health and to the continuing poor living conditions and the perma- nence of the risk factors that cause mortality during preg- malnutrition nanic and the first vear of life. The reductionl in child mortalitv is probably related Malawi has a very high tinder-five mortality rate. Al- to the high vaccination rate, which has prevented though the rate declined durinig the last decade, it is the immunizable diseases suchi as measles. According to DHS Worst amongy the COun1tries iln Eastern and Southern Af- the vacciniationl coverage for childrell tinder the age of rica for which data are available. l ife expectancy is among two in 9 9)2 was: 88 percent vaccinatced against measles, the lowest ini the world. 'This is due to illiteracy precari- 88 pci-ceit received all rhree doses of polio vaccine, and otis living conditionis such as food insecurity', and limited percenit received a BCG vaccination. Nevertheless, access to saniration, health care and other social seirvices. even wirh this very high immunnization coverage, almost one in evel-V four Malawian children dies before reach- Child malnutrition is widespread ing the fiftlh birthday. These exceptionally high rates of intf'ant and child mortality are caused by high rates of Malnitr-ition, a major problem in Malawi, is caused by malniLtrition, infectiouis diseases, and malaria. The poor diets, short birth intervals, and inappropriate feed- MDHSi reported a prevalence' of acute respiratory in- ing practices. StuLnting, which is an indicaror- of long- fectiois, fever, and diarrhea among children tinder the terml malnutrition, is more prevalent among childrenl in age of five of aboLit 1 5 percent. 40 percent, and 22 per- Malawi than in neighboring countries (Table 2.2). Nearly cent respectively. one in every two childrei tinder five is short for his/her Mother's edLication is strongly associaced with un- age and onie in four is uinderweighlt. der-five mor-tality. Childreni born to mothers whio had ilo educatiCon were twvice as likely to die before their fifth Infant and child birthday compared with children born to mothiers who mortality are high had been educated to the secondary, level (DHS, 1992). Risk factors associated with under-Five mortality included Although during the last decade there has been a decline having a mothel- who was very young or very old; birth in child mortality (childrell who die betweeni one and intervals shorter than 24 months; birth order, with the five years of age), infant mortality (children who die firstborn child more likely to die than children fourth or during: thieir first vear of age) has remainied high (Tables later in the birth order; small size at birth; and little uti- 2.3 and 2.4). The high infant mortality is probablv due lizationi of health services by the mother during preg- Table 2.2 Malnutrition indicators in Malawi and neighboring countries Malawi Zambia Zimbabwe Tanzania Kenya Namibia Indicators 1992 1992 1994 1992 1993 1992 Percentage of children under 5 -Underweight 27 25 16 29 22 26 -Stunted 49 40 21 47 33 28 Underweight =Proportion of children <-2 Standard Deviations from the median standard Weight for Age Stunting= Proportion of children <-2 Standard Deviations from the median standard Height for Age Sources. The Demographic and Heath Survey Reports for the individaLc countries by Macro InternationaL Inc.  8~~~~~~~~ MaOi*Poie and Priorities for Action nancy' and delivery' 620 maternal deaths per 100(00() births. The high fertil- In the context of neighboring countries, the mortal- itr rate and the tendeicy tfor short inter-vals between births itv' rates for Mialawi aire startling. The infant morrality do niot allowx wvomien in Malawi to recover betwveen births, rare is 30 percent highier- thani in neighboring Zambia whichi increases the risk for complicated preginanicies. A which also has a relatively high int- int mortality rate. high prevalence of malnlutrition amiong Malawianwomen Malawi lias the lowest lif expecrancy-44 vears-of the of childbearing age is an additrional factor affecting couLitries in the region for whitch data are available, materinal mortalitY rates. Child mortality is more HIV and AIDS are spreading prevalent in the Central region The 225,000 estiiated cases of AID)S pUt a heavy bur- \Within Malawi child mortality rate is highest in the den on the already very poor Malawi. T Fllifetimile hos- Central region-50 percent higher than in the other re- pital cost of between X2(00 to $90() eqtials I to 4 years of gions (ETable 2.5). Tle reasons for til's are probably the wages. Homle-based cart, a chcaper alternative to hospi- higher prevalence of riskl factors in this region, including ral care, is an ordeal for imany families because of the short birth intervals, low birth weight and lower utilizationi lack of potable water and latrines. Bv the year 2000, an of MCH services. Feer ominti in thet Central regioll used esritimated 2 million people will be infected with HIIV anteniatal and deliveryv care, andl this cotld also be a proxy and about 355,000 children will he orphianed. This will for low utilization of MCIH scivices after birth. Women in impose high costs o1 hotuseholds and on1 society ill gen- the Central iregion also had miore short-spaced pregnan- eral. In tirban areas, the prevalence of the virlius asnion cies, which are associated with a higher risk for child woImlenl attending antenatal care clinics is cuIrenitly esti- mortality, mated to bec at .0 percenit. Tihe Spread of thIe VilrIS is caIsingll, increalses in borh chil3d and adult mor-taliry rates. Maternal mortality is high Sanitation is poor and TIhe i low utilization of healthi ser-vices duiring chilld deliv- there is little infrastructure ery (Annex 2: Table A2- 1) anid the poor conditions dur- ing preg natncy are the main CaUsCS of the high maternal Over half oft'rhe population obtain their water fronm mortality rate, which was estimated by the MDHIS to be unsafe sources (Table 2.6). A large majority of hotise- Table 2.3 Child mortality and life expectancy for selected African countries Malawi Zambia Zimbabwe Tanzania Kenya Botswana Namibia Indicators 1992 DHS 1992 DHS 1994 DHS 1992 DHS 1993 DHS 1988 DHS 1992 DHS Infant mortality 134.3 107.2 52.8 91.6 61.7 37.4 56.6 Child mortality 114.9 93.6 25.8 54.6 36.7 16.0 28 1 Under-5 mortality 233.8 190.7 77.2 141.2 96.1 52.7 83.2 Life expectancy 44 48 60 51 59 68 59 Infant Mortality Rate= Nurnber of children dying before their first year per 1,000 live births Child Mortality Rate= Number of children dying aged between 12 and 59 months per 1,000 live births Under-five Mortality Rate=Number of children dying aged under 5 years per 1,000 live births Sources: Life expectoncy dota are for 1992. The Africa Development Indicators 1994-95 The World Bank 1995. Other indicators are from the Demographic and Hea/th Survey Reports. from Macro Internationai. Inc.  Profile of Human Resources for Malawi 9 holds live in dwellings with floors made of packed no sanitation facility. This increases the spread of in- earth. Electricity is practically noni-existent in rural fections. especially in crowded households. In 34 per- areas, and even in urbani areas only 20 percent of cent of households, three to four people sleep in the houselholds have access to electricity. same room: about 10 percent of households have five While almost everybody in urban areas has ac- or more people per sleeping room. cess co a latrinie, one-tlird of rural households have Table 2.4 Infant and child mortality in Malawi: the past 15 years Infant Child Under-five Period mortality mortality mortality 1988-92 134.3 114.9 233.8 1983-87 137.5 126.1 246.3 1978-82 136.4 140.8 258.0 Source: 1992 MDHS Table 2.5 Regional variation in child mortality Percent of children Prevalence of Prevalence of born with a antenatal care deliveries Infant Child Under-five birth interval from health in health Region _ mortality mortality mortality below 24 months personnel facilities Northern 120.7 92.3 201.9 16.6 92.9 67.5 Central 130.2 151 0 261.6 24.0 86.3 51.2 Southern 144.3 100.1 230.0 19.2 92.0 56.3 Malawi 135.7 120.1 239.5 21.0 89.7 55.5 Source: MDHS 1992, Macro International, Inc. Table 2.6 Water source, sanitation and flooring for rural and urban households Percentage of households: Rural Urban Total -using an unsafe source for drinking water 58 9 53 -with no sanifation facility 31 3 28 -with mud flooring 93 44 87 Source: MDHS 1992  1 0 Malawi * Profile and Priorities for Action . nche analvsis in this section focuises mainl1 on pri- educational overshe m nmarv education as this educational level is most relevanlt educational system for sedticinig poverty. The analysis dr;ws oni thc ]990/ 1991 1 E SSEA data and is tipdated uising the most re- alawi's CdUtcatiorn system is hampered by problemils of cent available data firomii the MN'inistrV of Education.' por access, hill repetition and drop-out rates, poor inlfaStrturIeLIC , and inequality. lo redr-ess this sitiatil School enrollment Ilbc nicwv ( overnincit of NIalavwi made eduIcation par- rictclarkl primary edLiCatio1, its top prior0ity. In 1994 Important gains in school aftendance school ees fol- Pmill-larV educLation weir eliminiiated and public spending on1 eduication1 was inicreased sharpiv 'There has been a substalnial increase in the slhare of mainlIV O filnalnce the wenLty thOuLsISand ceachers who were yoIng adLJlts receiving soime pri mary edtLctLion, co(in- rc(ruLited to mIeeIt the expected surge in enirollmeit. picinig primilar school, and eveni attaiinigi higher levels .Malavian houiosehlolds responded to this new priorirv and of eductionl compared to the share of ot(ld-e adults wlho the nunmbebr of children en rolled at the primiarv level reached those levels in the past. Tlbe noinmther of jumniped byN 61 percenit froni 1 .8 million to near three Malawviars whio have never attenided school has beein sig- uillion students for the 1 994/1995 school year. 'ificain tlv redLuced AboLut one in thitee MaNlaiaw S cur- Detspite the recenlt impr(ovements. there are still se- rently aged betweeen 16 and 35 Cears old have necver- at- riotis problems and severe iCneqLialties in pulblic pri imar tenided school, compared to one in two oftthose ated i5 edlcta1ti011. TIheret is a dearthi of eveni miilinial essnttial years or older. The sharc of the populartioll aged betWeenv1 teachirig materials and hulmliani resouL-ces necessary to 1( and(t 35 years old whio have attained all educational edtrcate childi-n [Ithere are significant disparities ill par- level of at least Standards V to VIlil has doubIed conii- tiipantion and achilevemlielit a;inI ng socroeconolilic pared to that for the popuLatioll over 35 years of age. groups arid regionts and by genider. The qualitv of edu- It is also clear from compar-ing these tLwo age tgrotips cation, already severely comproniised by large class sizes that disparities between 111en1 ard women ill educational even befoere therecelt surge in primary enrollment, has attainmenit have declited, althouglh the pcenteIt;lgv of detetriorated t'lurtile.- women who have nevei- attenided school remains higher thaln the comparable perceiltage of miieni. Ariioiig iiiales, the share of those wlho have never attenided school has declinted fromi onie in three for Figure 2.2 the older group tO one in five for the Education level attained by adults vouLiger group (FiguL )' 2_2) Amrnong f'e- in two age groups, 1990/1991 niales this share has declined from tv( in three for the oldker gl-OlIp to Ies.s than, Onle h{' * alVE 3s Inarb m m 16-3s APalS U1 two for the von nlger group. hbus, genl- der disparities are still substantial among aduilts aged 16 to 35, but inequities be- tween males and females are declininig over :3 1)- _ time. Thle largest Increase over' ti1ine In school attenldanice in Standards V to VIII was among woisv t'r . Onie out of every L -Ci -3 - Sd. I _ I | fotir womilenl ill thel Voting1. ' tO tlF -,:,Stla I IV S'c VV S-cnnt-lrs Ed-[oll Sld l-IV 51C1 FVVI- Sreached at least Standardks \' to V 11 Males Females whichi is three times thlC nlulimber of tlc - older- grotp of femalets (otel 9 percenit) Source: HESSEA (1990/19 91) r s. __ __ _ ~~~~~~~~~~~~~~~~~wlio reachled t1hlS level prCVIOlY.si  Profile of Human Resources for Malawi I 11 Enrollment rates are low and the among the poorest children: two in three drop out poorest children are least compared to less thani one in two among the richest likely to be in school children. Thus the poor are less likely to enroll in Stan- Only about half of all children six to thirteen years of dards V to VIII (Table 2.7). age were enrolled in primary schools in 1990/1991 and childreni in the lower expenditure quintiles are The poorest girls are munc less likely to be in school. Net primary enroll- least likely to go to school ment rates are more than 40 percentage points lower in the poorest quintile than in the richest (Aninex 2: Gender disparities in net enrollmelit rates at the pri- Table A2.2). mary' level do not appcar to be signiflicant (Anilex 2 The gross primary enrollment rate is substantially 'lable A2.3), but the gross rate is systematically lowelr higher thani the net rate arid this difference is more for girls than for boys across all the expenditUle marked for the poorest than for the richest quintile. quiitiles. This is an indication that girls aged 13 or Gross enrollment rates in primary school for the two older (captired in the gross rate) are more likely to poorest quintiles are about double the net enrollment dr-op out of primarv school than boys aged 1 3 or older rates for the same groups, confirming that late entry (Table 2.7). Thus it is crucial to put in place incci- and repetition occur particularly amonig lower-income tives for eariv enroililenti antd reteitioni of girls in groups. Thus, the poor are more li kely to dr-op out or priniar' education. to leave and returi repeatedly, decreasing their chanices Genider disparities in gross enrollmenit rates for of completing the primary cycle. primarv education are considerably hilgher in the Gross enrollment rates are much lower for Stan- South than in the North or( Cential re^,ions (Annie7x dards V to Vill than for Standards I to [V. The de- 2 T'able A1.3). Box's in the rulal Southi hiave anl over- cline in gross enrollietili rates betweeni the first- aild 111 gross e2nrollmnent ratc about 25 percetit higlher than the second-half of primary educationi is sharpest the rare for girls, xvhile in the rural North and Ceii- Table 2.7 Gross enrollment rates by quintiles and gender, 1990/1991 Household Gross Enrollment Rates Gross Enrollment Rates Expenditure Standards I to IV Standards V to VilI Quintile _ Boys Girls National Boys Girls National I - Poorest 96 70 82 36 27 32 11 1108 98 104 53 38 45 Ill 116 116 116 55 42 48 IV 132 115 123 76 58 68 V - Richest 133 151 142 88 68 77 All 1114 102 108 56 43 50 Primary education in Malawi takes a minimum of 8 years and it goes from Standard I to Standard VIII Gross enrollment rate in Standards I to IV All children enrolled in Standards I to IV as % of 6-9 year old population, Gross enrollment rate In Standards V to VIII. All children enrolled In Standards V to VIII as s/c of 10-13 year old ocoulation, Income quintiles are created by classifving every individual from the poorest to the richest and then dividing the population ins groups containing 20 percent of all individuals The poorest quintile represents the poorest 20 percent of the population Source. HESSEA 1990/199/  1 2 | Malawi * Profile and Priorities for Action tral regions, the gross rates are about the same for There is considerable boys and girls. age/grade mismatch Enrollment rates are higher in the Late entry is very common, and older students are Northern region more likely to be enrolled at every educational level than are students of the correct age group. The age/ Children in the Northern region are the most likely grade matching analysis shows that repetition is also to be, and to remain, enrolled throughout all years of widespread. primary school (Table 2.8). Children in the rural About66percentofallstudentsenrolledinStan- Center have higher gross enrollment rates in Stan- dards l-IV are older than nine years ofage, and arouLnd dards I to IV than children in the rural South. 75 percent of all students enrolled in Standards V- However, enrollment rates in Standards V to VIII VIII are older than 14 years of age (Table 2.9). In are the same for children in the two regions. This in- Forms I-IV in secondary school, 75 percent of all stu- dicates that in both areas many children do not en- dents enrolled are older than 18 vears of age. A re- roll in school after Standard 1V Educational programs cent study found that the average age in Standard I is for the rural Center and the rtural South ought to ap- 10 vears of age and in Standard VIII. it is 22 years of proach two different sources of low completion. Pri- age." The main disadvantage of attending primary mary schools in the rural Center need to increase their school at an older age is that these children are often ability to retain children in school. In the rural South, needed to help to support the household. This be- enrollnients in primary schools need to increase alto- comes a disincentive for them to complete that level gether. Table 2.8 Gross enrollment rates in primary school by region and residence, 1990/1991 Household Gross Enrollment Rates Gross Enrollment Rates Expenditure Standards I to IV Standards V to VIII Quintile Rural Urban Total Rural Urban Total North 139 150 140 94 106 95 Center 103 138 107 38 85 44 South 98 146 103 38 86 44 Ali 104 143 108 45 87 50 Source: HESSEA (1990/1991) Table 2.9 School enrollment: age/grade matching, 1990/1991 Age group Students Percentage of total enrolled in level Level enrolled 5 or less 6-9 10-13 14-15 16-17 18 or over Total Standard I-IV 993,377 2 34 44 12 5 4 100 Standard V-VIII 407,305 0 2 25 25 24 25 100 Forms l-IlV 41,876 0 0 4 9 18 69 100 Forms III-IV* 17,839 0 0 0 2 8 89 100 Forms V-VI 145 0 0 0 13 11 76 100 Tertiary- 6,991 0 0 0 0 0 100 100 Includes M.C.D.E. (Malawi College of Distance Education) students. Tertiary = Primary Teacher Training, Technical Training and University. Source: HESSEA (7990/1991)  Profile of Human Resources for Malawi 1 3 of education and then proceed to higher educational level students in Malawi, includini, studenits attend- levels. ing Primilary Teachcr Trainiiig. Technical Training, and Universitv. In 1994/1995, these enrollments repre- Most primary graduates never se nt a iere 0.3 percent of the total number of enr-oll- attend higher education minits at all levels of eduIcation. The niumber of students conmpletling each cycle anld Recent changes in enrollment enrolling in the next is extremely low. In 1990/1 991, only 18 percent of the children enrolled in primiary The responsc from houiseholds and students itn Malawi school completed the full eight years of primary edu- to the elimination of school fees and the ipriority giVen cation. In addition, since secondary schools offer only by the new government to prim1ary educationi has been a limited number of places, most childreni never at- overwhelming. This section analyzes the distribLution tend secondary school. Only one out of every 100 of the increase in enrollmenit across incomc groups, children entering the primary cycle is admitted to the gender and reg0ions using recenit data from the Minis- secondary cycle. The overall net enrollmelit rate in try of Education. secondary schools is 2.2 percent, and the gross rate is about 10 percent. Given the recent surge in enroll- Important inequities remain in ments and the deterioration in the quality of primary primary education schools, it is possible that a proportionally smaller number of children who complete primary schiooling Estimated gross primarv enrollimenit rates by income wiI attend secondary school in the near future. groups indicate that the same clhildren who were identi- Practically no children from the two poorest fied as beiing disadvantaged in 1990/1991 are llkely to quiintiles attend secondary school (Annex 2: fable remain disadvantaged in 1994/1995 (Table 2.10). Ma- A2.4). Even in the highest expenditure quintile, only jor increases in gross eniroililmeit rates occurred in the 8 percent of children aged 14 to 17 years old are en- 1994/1995 school year at everv incomile lcvel; however, rolled in secondary school. half as mianiy childreni fromil the poorest quiltiile are eu- It is also very rare for Malawians to attend ter- rolled in pirimary school as from the richest quiltile. The tiary education. There are only about 7,500 tertiary- gross enirollmenit rate foir the poorest quiltile is 74 per- Table 2.10 Gross primary enrollment rates by quintiles and gender, 1990/1991 and 1994/1995 Household 1990/1991 1994/1995' expenditure quintiles Boys Girls National Boys Girls National I - Poorest 65 51 58 100 69 74 11 83 69 76 117 88 102 Ill 88 83 86 118 98 114 IV 104 89 97 134 104 131 V - Richest 113 106 110 134 120 133 All 86 75 81 121 96 108 The numerator for the gross enrollment rates in primary education by quintiles in 1994/5 s total enrollrents estimated on tne loasis of 1994/5 regional enrollrnents provided by MOE (1995) and taking the HESSEA survey (1 9Q0/1) as our baseline. This computation involves using a simple mathematical algorithm in which total primary enrollments in each quintile In 1994/1995 are obtained yv applying toe regional rate ot growth in primary enrollments between 1990/1991 anc 19Q4/1995 to the regional composition of prirriary enrollments in trhat same quintile in 1900/19Q1 For further information see Annex 1. The dencronator for tne gross enrollment rates ri primary education by quinties in 19Q4/1995 uses a 3.3'. population growth rate for the6to 13 year-nd poplat on group. taking tne HESSEA suivey- (990/1991)as our baseline. Sources HESSEA (1990/1991). MOE (1993)g MOE (1995)  14 | Malawi * Profile and Priorities forAction cent, while it is 133 percent for the richest quintile. rates in the rural Center and rural South are around 100 Gender disparities in gross enrollment rates have percent, while the rate in the urban North is much increased for all income groups-girls in the poorest higher-I67 percent (Annex 2: Table A2.5). quintile have a gross enrollment rate of only 69 percent. 'The surge in primary enrollments in 1994/1995 has almost one-third lo-,ver than boys. put tremendous stress on schools where classrooms are Estimated gross primary enrollment rates by region badly equipped and where educational materials are indicate that, although the regional disparities are nar- scarce. The quality of primary education is more likely rowing, the same regions thar were relatively disadvan- to have deteriorated in the rural Central and Southern taged in 1990/1991 are still disadvantaged in 1994/1995. regions which are disproportionately affected by the lack Growth rates in primary school enrollments have been of education resources. Since the rural Central and South- highest in those regions that had lagged behind in net ern regions contain the majority of poor students, these enrollment rates in 1 990/1991. Between 1 992/1993 and should become the priority areas for allocating public 1994/1995, primary enrollment in the rural Central re- education spending as this should improve the access to gion increased by 70 percent, and in the rural Southern primary schooling for the poor. region, by 80 percent (Figure 2.3). By contrast, enroll- ments in the rest of the country increased by less than Public spending on education 30 percent. Enrollments in the rural Center and South increased The recent increase in the budget share allocated to pri- most in 1994/1995. In the rural South, enrollments mar' education is a very positive development in the surged from 700,000 to 1.2 million (Figure 2.3). Al- process of increasing investments in humiian capital and though regional disparities have narrowed with the re- improving equity. Tfhe priority now is to restructre the cent rise in enrollments, the rural Center and rural South composition of budgetary allocations within the sector still lag behind in primary enrollments, which are par- to continue improving equity, and to raise the qualit of ticularly low in these regions. Gross primary enrollment service delivery. Figure 2.3 Growth in primary enrollments from 19921993 to 1994/1995 by region Rate 90 80 70 60 50 40 30 20 10 0 North Center South All North Center South RAl Urban Rural Urban Rural Source: MOE (1993); MOE (1995)1  Profile of Human Resources for Malawi I 1 5 Public spending on primary education This situation has improved considerably, but re- increased, but bias against primary mains inequitable. At present, the cost of one sec- education persists ondary-level student in Malawi could finance four Because of the policy shift in 1994/1995. public recur- students at the primary-level, while the cost of one rent spending on educationi has more than tripled in real tertiary-level student is IIow 71 times more than the terms between the 1990/1991 and 1994/1995 fiscal cost of one primary-level student (Table 2.11). Uni- years, from NMK 267.5 million in 1990/1991 to MK versity education is still very costly otn a per stLident 899.7 million in 1994/1995, expressed in constant 1995 basis: a university student in Malawi is 103 times more Kwachas.l Primary-level spending has increased even costly thatn a primary-level student. The much greater more: it surged by 4.3 times in real terms during the cost per student of higher and university education same period and its share hias increased from 45 percent in Malawi is largely because there are very few stmt- to 71 percent of total spending on education. As a re- dents at this level. Progression rates from one educa- suit, public spending per studenta ar the primary level tional level to the next are extremely low, so that verv more than doubled in real terms between the 1990/1991 few students are admitted into tertiary education. and 1994/1995 school years, even after the sharp increase International comparisons of education statistics in enrollment. Per student spending in 1990/1991 was illustrate the relatively small numbers ofstudents go- MK85, and this increased to MK220 in 1994/1995. ex- ing beyond primary education in Malawi although a pressed in constant 1995 Kwachas.' large share of GDP is dedicated to the education sec- The bias against primarv education in the alloca- tor as a whole. In Madagascar and Lao P.D.R., coun- tion of resources within the sector as a whole is demon- tries of comparable income levels, a secondary stl- strated by estimating how many primlarv students could dent is four times as expensive as a primary student, be financed by the cost of one studetnt in either second- the same as for Mlalawi in 1994/1995 (Table 2.11). 1 ary or tertiary education. In 1990/1991, a secondary- However, the contrast at the tertiary level is striking. level student in Malawi was seven titnes as expensive as a In Malawi, tertiary students are about 70 times as primary-tevel stLdent, a tertiary-level studenlt was 97 expensive as primary students, while in Madagascar times as expensive, and a universiry studenit was 165 times and Lao P.D.R., they' are only about 20 times as costly. as expensive. ' In Kenya and Guinea, countries with a higher per Table 2.11 Cross-country comparisons of education financing per student Primary student equivalent cost' GNP/capita Education Country (1992 US$) Primary Secondary Tertiary University (%GDP) Malawi (1994/1995) 220 1 4 71 103 7.5 Madagascar (1993/1994) 230 1 4 22 22 2.6 Lao PD.R. (1992/1993) 230 1 4 24 - 3.6 Kenya (1992/1993) 310 1 3 41 41 9.2 Guinea (1994/1995) 510 1 2 35 58 2.0 South Afnca (1993/1994) 2,670 1 2 5 5 7.3 Mexico (1992/1993) 2,976 1 2 5 5 4.5 t The primary student equivalent cost (subsidy) expresses the number of primary school students that could be financed per student in higher levels. Sources: Castro-Leal (1995a, 1995b, 1994); Castro-Le1o and Dayton (1994); Doyton (1995a. 1995b)  16 Malawi * Profile and Priorities for Action capita income than Malawi, tertiary-level students are Public spending in education has about 40 timiies as expensivc as primarv students. In become more pro-poor South Africa and Mexico. COtiitlries witih a larger num- ber of studenits going bevond primary iand a much The edtication sector in Malawi in 1990/1991 had one higher per capita incomrie lvel, secondary educationi of the worst distributions of public education subsidies per student is onl' tw ice as expernsive as primaryv while in Sub-Saharani Africa. But because of the recent surge tertiary studenits are only five times as costly. in primary enrollments, the increase in government These results indicate that cven though a larger spending on the primary education sector, and the bud- share of puiblic money is being spent per student on getary reallocations within the education sector, the distri- the early levels of edLIcationi in Malawi. completion bution of public education spending across income groups and progression rates rem;ain low at this level. Pri- has improved considerably. mary students receive loxv qual i ty services even thoughI The share of public education resources received by Malawi allocates 70( percelmt of public educationi re- the poor increased substantially berween 1990/1991 and soLirces to this level and a larger share of its GDP goes 1994/1995. In 1994/1995, the poorest income quintile to the educaltion sector thani in some other cO11ntries. received 16 percent of all public education spending com- In 1994/1 995. Malawi spenlt 7.5 percent of its GDP) pared to 10 percentin 1990/1991 (Table 2.12).Theshare on educaItion, while Madagascar spent 3.6 percenit. going to the richest income quintile in 1994/1995 was Lao P.D.R. spent 3.6 percent aind Guinea spent onlv' only 25 percent compared to 38 percent in 1990/1991. 2 percent. The Malawi example shows that an effective way to in- Table 2.12 Public education spending on poorest and richest quintiles Education spending benefiting: the poorest 20% the richest 20% of the population of the population Country Year (percentage share) (percentage share) Malawi 1994/1995' 16 25 1990/1991 10 38 Cote d'lvoire 1993 10 38 Ghana 1992 16 21 Kenya 1992/1993 17 21 Madagascar 1993 9 44 South Afrca 1993 14 40 Tarnzani 1993 13 23 The distributon of all Qublic eoucation spend ng by quintiles in 1994/5 involves estimating total enrollments in 1994/5 by quintiles and by educational leve At the pr mary level total enrollrnents in 1994/5 by quintiles are derived by using a simple mathematical algorithm by app ying the regional rate of growth in primary enro Iments between 1990/1 and 1994/5 to the regional composition ot primary enrollments in that same quintile in 1990/1. The same distr bution of enroilments across quintiles at the secondary and tertiary levels observed in 1990/1 is maintained in 1994/5. For furtner information see Annex 1. Note: It public education spending was equally aistributed across popu ation quintiles, tne poorest and richest quintiles (every number in the table) would receive a 20 percentage share of spending Sources: Dayton (1995); Demery (1995); Bernier. Chao, and Demery (1994), Castro-Leol (1995a, 1995b); Demery and Verghis (1994); World Bank (1995).  Profile of Human Resources for Malawi I ~~ 17 crease the equity of public spending in education is to inl- schools, few new classr<ooms have been built aind only crease the percentage of total education spending allocated a verv small share of public education resources has to primary education. been spent on non-salary quality items. Despite the recent progress in 1994/5, disparities in The bulk of the increase in spending has benii public eduication spending were still considerable at the Lised to finance the salaries of the ncwNlv recruitCed secondary and tertiary levels compared with the primary teachers. Recurrent spending on salaries has ConsuLIIe(f level. In primary education, 19 percent of public spend- 97 percent of all 1994/95 primairy recurCrent expendi- ing went to the poorest quintile of the populaltion, while tures, meaning that only US$0.30 per- studcnt was 16 percent went to the richest quintilc. The poorest allocated to non-salary items during this school vear. quintile received a 9 percent share of secondary educa- In 1992/3, it was estiniated that there were 78 chil- tion expenditures and only a 1 percent share of tertiary dren per qualified teacher (Table 2.13) taklin inr t education subsidies, while in contrast, the richcst quintile acCount that 13 percent of priliary school teachcrs inI received a 39 perccnt share of secondary, and a 58 per- Mlalawi are considered to be uLiqualificd. In thie same cent share of tertiary education subsidies. year, there were 18 children per desk, 32 childire:n per chair, and 102- students per classroom (MOE Basic Stl- Services and quality tistics. 1 993). After the increase in primary enrollments. have deteriorated as qLualitv inidicators deterioratced eveni furtder. 1Ihe nim- enrollments have surged ber of children per qualified reachler, per desk, pe r chaiar . aind per classroom all nearly doubled. Estimates for 1994/95 show that the substantial in- Thus children in NMalawi attend schools in wlicih crease in public spending has not been suIfficient to the most basic pre-conditionis for creating a positive avoid a decline in conditions in p-rimar-y schools. Be- learningt environment are missing. Together xvith high cause of many years of undcr-ftunding for infrastruc- rates of childl malnutrition and limircd access to pri- tmre and supplies, Malawi's public primary schools mary schools (most childrern have to walk distances arc amonig the most poorly-equipped in Africa. Even of uLp to six kilometers) this helps to explaini the after the recent increases in speendinig in primary couLntryIs high repetition ajni drop-oLir rates. Table 2.13 Quality indicators in primary schools, 1992M1993 and 1994A1995 Pupils per: ____ _ 1992/93_ 1994/95 Teacher n a. 77.0 Qualified teacher 78.0 131.0 Textbook/basic subjects n.a. 7.1 Permanent classroom 102.0 422.0 Chair 32.0 56.0 Desk 18.0 31.0 Repetition rates 18% 21%' Drop-out rates n.a. 12%* tMost recent estimates available at MOE. Sources: MOE (1993). National PrimarY Nutrition ond Health Assessment (1995): Robinson eta/ (7094). MOE (1995)  1 8 IMalawi * Profile and Priorities for Action weighited averages. The Malawian economy is similar development Hum n rs to the economies of the countries in both groups, al- development 1n an thoughI there is slightly less dependence on agricul- international context ture in Malawi than its GNP per capita might sug- gest. Statistics for the GNP per capita group are in- The poor achievement on humani resources development fluenced by the inclusion of Bangladesh with its rela- documented in this profile suggests that poverty, how- tively large population; when Bangladesh is removed ever it is defined, is pervasive in Malawi. Although there fronm the group, average annLial GNP growth during have been some improvemenits over time and althoLigh the period was 0.7 percent. the new government has given priority to improvincg the Health and education indicators are low in living conditions of the poor, most Malawianis still suf- Malawi relative to countries with similar income lev- fer deeper deprivation than people in most other coLin- els. Infanit mortality rates are well above (and life ex- tries. This situation has arisen despite high aggregate levels pectancy falls well below) those in both reference of spending on the social sectors. These findings under- groups. That population per physician, access to safe score the urgent need to invest more in basic social ser- water, and immunizationi coverage are mostly better than vices and, even more importantly, to improve the qual- average does nor seem to have much impact on the out- itv and equity of these expenditures. coImle of health indicators. The alarmingiv high infant and child mortality rates indicate structural deficiencies Living conditions are among consistent with extreme deprivationi and poverty. the poorest in the world although P'rimary school net enrollment rates are much public spending is high lower in Malawi than in the coutirries in either refer- ence group, while pupil/teacher ratios are consider- Raniked on the basis of GNP per capita, Malawi is ably higher. Primary school gross enrollment rates in the ninthl poorest coulitry in the world. Despite this Malawi are well below those of each reference group. low ranking, during the 1970s and 1980s economic Gross enrollment rates at the secondary-school level growth in Malawi was relatively high and in recent are substantially lower than those reported for the years Malawi has experienced slightly less economic refer-enice groups. \'omeii in Malawi consistently have decline than the average for the region. However, this less access than men to every educational level, and has nor been reflected in improved living conditions. they also have lower literacy rates than men. This is illustrated by comparing Malawian indicators Yet the total government spending in Malawi has with two reference groups: those for Malawi's neigh- beeni about a third of GNP. well above the levels of boring countries and those for couLntries with a simi- spending in the countries in both reference groups. lar per capita income level. In 1993, for example, total GoM expenditures were The regional referenice group in Table 2.14 in- about US$58 per person comnpared to an average cludes: Angola, Botsxvana. Madagascar, Namibia, US$4 1 in the GNI' refcrence group. Despite this rela- Mozambique. Tanzania, Zaire. Zambia, and Zimba- tively high total spending, social sector outcomes are bwe. The GNP per capita reference group represents; very poor. From a poverty perspective, it is disturb- Nepal, Chad, Bhulain. Sierra Leone, Bangladesh, ing that wlile Malawi's public spendinig is so high its Burunidi, Lao PDR, Uganda, Madagascar, and performance on social indicators is so bad. This indi- Rwanda. These are the five counitries ranked above cates that the allocation of public spending has not and below Malawi in terimis of GNP per capita. The been directed to the basic social services and that the figures for the reference grOups are popuIlation- resources have not been used effectively.  Profile of Human Resources for Mailawi 19 Table 2.14 Aggregate statistics for Malawi compared to similar groups of countries Neighboring Countries with Malawi countries similar GNP/capita Basic indicators GNP per capita (S) 1992 200.0 262.1 210.8 GNP per capita: average annual growth rate (%) 1980-93 -1.2 -1.3 1.1 Average annual population growth (%Y) 1980-92 3.3 3.0 2.4 Growth and structure of production Distribution of GDP (% agriculture) 1970 44.0 25.3 54.2 Distribution of GDP (% agriculture) 1993 39.0 33.7 36.0 GDP: average annual growth rate (%) 1980-93 3.0 2.1 3.9 GDP; agriculture; average annual growth rate (%) 1980-93 2.1 2.5 2.7 Agriculture and food Average index of food production per capita (1979-81=100) 1988-90 83.0 90.7 96.4 Daily calorie supply (per capita); 1989 2,139 2,190 2,062 Central government expenditure % of total expenditure; education; 1980 9 0 13.6 12.3 %of total expenditure; education; 1993 8.8 9.0 13.8 % of total expenditure; health; 1980 5.5 4.3 5.8 % of total expenditure; health; 1993 7.4 4.2 4.8 % of total expenditure; economic services; 1980 43.7 27.7 44.4 % of total expenditure; economic services; 1993 35.0 26.0 31.8 Total expenditure (% of GNP); 1980 37.6 24.0 12.2 Total expenditure (% of GNP); 1993 29.2 19.6 19.3 Education indicators Primary net enrollment (%); 1992 48.0 55.7 66.2 Primary pupil-teacher ratio; 1992 68.0 37.5 56.5 Primary gross enrollment (% of age group) total; 1992 66.0 81.0 78.7 Primary gross enrollment (%/c, of age group) female; 1992 60.0 56.4 72.4 Secondary gross enrollment (% of age group) total; 1992 4.0 24.8 18.9 Secondary gross enrollment (% of age group) female; 1992 3.0 19.8 15.0 Illiteracy rate, total (% pop age 15+) 1990 58.81 36.4 60.0 Illiteracy rate, female (% of lemales oge 15+) 1990 69.2' 46.6 63.5 Health indicators Population per physician; 1984 11,340 15,008 12,178 Access to safe water, total (% of population) 1991 53.0 39.2 59.3 The figures in the regional and GNP per capita groups are population-weighted averages. 'Data reported from the World Development Report 1995; Malawian education statistics report the following adult literacy rates (18 years and older) males 48 percent, females 29 percent Sources: World Development Report 1995; Malawi data are drawn from various sources including Social Indicators of Development, 1994 (some source as the World Development Report); Demographic Heolth Survey (1992); World Bank Country Economic Memorandum (Volume I, November 1989); S/tuatiorn Analysis of Poverty in Malowi (1993); Molowi Education Overview (1994)  20--- 20 -~~~~~~~ Malawi * Profile and Priorities for Action 2.5 The state of human The educational system is ianipeed by problems of poor access, high r-epetition and drop-out rates, resources poor infrastructure, and inequality. The Government of Malawi recently dramatically increased public Livin;g conditions in iMvlalawi are among the worst in the spending ofi primary educationi and, as a result, pri- world. Social indicators are very poor, even compared miary schiool enrollmenits have increased significantly. witih othier Siub-Saharan African countries. If the popu- Never[heless, the primary enrollment rate remains low lation growth contintues at the presenit rare, Malawi will compared to other coLintries in the region or to coun- ha.ve to support close to 20 million people by the year tries with equivalent per capita income levels, and 20 1 4. Nea-lv ialf ilit population is uLider 15 years old: most childrenl never attend secondary school. The hoLuseholds containi more children thani adult providers, boom in enrolltimenits has meant that the quality of Population density is amiong the highest in Africa, and the system-low in the first place-has deteriorated. this is pUtting pressUre on scarce land resources, causing There is a dearth of even the most essential teaching soil eosioni and decreasing land productivity. This makes materials and human resources necessary to educate it difficult both for houselholds to provide eniough food children. and carX ftor all their members and for institutiolis to Three patrcrns of ineqtity emerge from the analy- prov"ide social services to a \'OUIng, and quickly growing sis of human resources; across regions, income groups, population, and gender. In both the health and education sectors 'I'he healtih and nUtirinon indicators of the poptla- there are significant regional variiatiois. The Central tiOn t'iVC grounds for seriotis concern, particularly re- region has mucih higiler child mortality rates and gardingl the welfare of childreni. Child maliutritioni is much lower maternal health care attendance than the widespread. caused by poor diets, short intervals between Souther-n and Northern regions. The Northern region births, and inappropriate feeding practices. In addition, and urbani areas have much higher school attendance both infant and child mfortalilty are high. Almost one in thani the Central and Southerni regions. The variation in every foir Malawian children will die before reaching enrollmcnt rates across income groups is strikitig, and his/her fifth birthday, and Malawi has the higlhest un- the girls are the most likely to drop out at any level. (icr-hvye mortality rate among the I I African counitries The evidence presents us with a puzzle-social [or whichi we have data. indicators in Malawi are among the worst in the world The matelrlnl mor-tality rate is also high, due to despite above average levels ofptiblic expeniditure. The mothers making little or nco use of health services key to solving this puzzle is to improve the intra- durin,g the pregnancy and the birth, rhe highi fertilitv sectoral balance and the income and regional equity rate, the short intte-vals betweeni birtis, and the high of these expenditures. prevalence of mIalilntr-itioni amiong wo nele of To analyze living conditions in Malawi further, childbearing age. HIV and AIDS are spreading and the next section tises hoLIsehold survev data to iden- are imposing high costs on households and on soci- tifv the poor and to define the characteristics associ- etv in gtncral. Sanitation is poor and there is little ated with houselholds with low income and expendi- othei- infrastrUCtUrC, such1 as electricity or rtiral roads, tore levels in Malawi.  Profile of Human Resources for Malawi | 21 Chapter 2 Notes This is the ratio between the population aged 15 to 65 years and the population utnder 15 and over 64 years of age. 2 The mothers were asked whether their children under five had suffered anlV of the three discascs in the two weeks before the survey 3 (MDHS 1992, Macro International. Inc., Table 3.7, page 73) Mother's education Under-five mortality No education 254.9 Secondary education 27.3 Information based on World Bank draft: Southern Africa - [)evelopment and the Aids Challenigc. AV i, October 1995. The school enrollment information for 1990/1 comes from the HESSEA. This is the only daraset available in Malawi that can be used to analyze education indicators linked to household income and expeniditure characteristics. Enrollments by educational levels for 1992/3 and 1994/5, as well as sectoral public spendinig information, were provided by the Ministry of Education (MOE). HESSEA and MOE data were used to compute per capita public education spending by quintiles and by regions in 1990/1 and 1994/5. Hyde et al. 1994. These numbers were adjusted using the 1990/1 and the 1994/5 national consumer price index for non- food items (1990= 100) provided by the Malawi National Statistical Office (1995). The nLimnbers are 102 and 222.5 respectively. Similar estimates are obtained by using the G[)P deflator (1988=1(00) for 1990)/ I and 1994/5 provided for the IMF Database for Malawi (1995). The GDP deflator in 1990/1 is 143.9 and 318.1. in 1994/5. 8 Part of the significant increase in real education spending could be the result of relative movements of wages and prices. This should be the focus of further analysis. Tertiary education in Malawi includes Primary Teacher Training, Vocational Training and ULniversity. IS Primary student equivalent costs are computed for each countrv in the local currency, and all educational levels beyond primary are expressed in terms of the number of primary students that could be finaniced by the actual cost incurred in subsidizing a studenc at higher levels.  22 -1 Malawi * Profile and Priorities for Action  Profile of Poverty for Malawi 1 23 Profile of Poverty for Malawi The aggregate social indicators presented in the previ- comparisons with other countries. ous section suggest that deprivation in Malawi is wide- Choosing a standard of consumption that meets spread. This section uses primary household informa- minimum needs depends on country-specific circum- tion from the HESSEA and the NSSA surVeys to assess stances and requires a consensus among policymnakers the magnitude of poverty in Malawi and to describe the and other relevant parties. It has not been possible to characteristics of poorer households. The section con- calculate a minimum consumption basket for this re- tains the first quantification of urban/rural differentials port because of time and data limiration.s. An abso- using nationally representative data. Iute poverty line for Malawi should be constructed after discussion and consultation with government and other parties. An alternative method of identifying the poor is to identify those households that are relatively worse- 3.1 Identifying the poor off. Relative cutoff points, such as the 40,h or 20' percentile of the household distributions of expendi- Establishing a trUe or income, are commonlyv used in poverty pro- meaningful poverty line files and are the cutoff lines chosen for this report. Those households whose incomes or expenditures fall One method commonly used to identify the poor is below these relative lines are considered to be poor. It to establish a level of expenditures or incomes below is then possible to provide information about the geo- which households are considered to have less than a graphical location, the social and demographic char- minimum or reasonable standard of living. This level, acteristics, and the economic activities of these poor usually termed the poverty line, can be chosen in a households. This information is vital for formulating number of ways. One option is to identify a mini- policies and programs that will have the maximum mum consumption basket of goods appropriate for impact in reducing poverty. Malawi and to value it. Households that do not reach In the analysis that follows, the term poorer this absolute minimum level of consumption are then refers to those households that are below the 40th considered to be poor. Such an absolute poverty line percentile of national expenditures or incomes, and is needed to measure the total number of poor people the term poorest refers to households below the in a country. An absolute line is useful as a baseline 20th percentile. Given that poverty is so severe in for making time-series comparisons or for making Malawi, this terminology does not imply that a  24 Malawi * Profile and Priorities for Action houselhold with expenditures or incomes above ei- in the Malawian context (Figure 3.1). The 40'" percen- ther cutoff is not poor. tile cutoff is slightly below the basic needs line (which is To determine whether these two relative cutoffs are at the 43rd percentile) and about 48 percent of meaiaiiigfiul in the Malawian context, wve compare them smallholder households have incomes below the 1990 with three illustrative poverty lines based on simple as- reference line. The 20'" percentile cutoff falls well below sumptionis to approximate minimum expenditure re- the calorie needs line (which is around the 30,h percen- quirements. The calorie needs line is based on the con- tile), indicating that households that fall below the 20th sumer price of 200 kg of mnaize and approximates the percentile are extremely poor. amounllt hat an adult would need to spend on maize to Most people in rural Malawi have very low incomes meet his/hier calorie needs if all these were to be met (Table 3.1). In 1992 eighty percent of people in rural from earing maize. The basic needs line is based on the smallholder households had incomes below MK 241 per value of 200 kg of maize plus a minimal amount to cover year-about US$ 55. Forty-three percent of people did otlher basic needs such as shelter and clothing. The 1990 not have enough income to acquire their most basic needs reference line was used in the World Bank report and 30 percent had insufficient income to meet their "Malawi-Growth Thlrough Poverrv Reduction" to ap- calorie needs. proximate a poverty line for Malawi at US$40 per per- Moreover the distribution of incomes for rural small son per year. All these lines are used in the current con- holders is very skewed, and most variability of income oc- text to examinae the relevance of the relative cutoffs. curs at the lowest income levels (Figure 3.2) The estimates Using the NSSA data to compare the two relative of the number of poor are fairly insensitive to the choice of cutoffs with the three illustrative poverty lines, we see income cutoff (or poverty line). This is shown by the cu- that the 40"' and 2001 percentile cutoffs are appropriate mulative income distribution in Figure 3.1. Around the Figure 3.1 Cumulative smaliholder income distribution 100- Illustrative poverty lines 90- The Calorie Needs Line approximates the minimum amount that an adult Malawian would need to 80/ spend on maize to meet his/her calorie needs if all these needs had to be met from eating maize 70/ (equal to 200kg). This line can be considered to 70- / be an extreme poverty line. It implies an annual t' 60- income per adult equivalent of MK 98.' = 60-- /The Basic Needs Line takes the minimum calorie needs intake from maize (200 kg) and inflates it to 2 50- approximate the value of the minimum amount a) / zof food plus other essentials, such as clothing and > 40- . shelter, needed to sustain an adult Malawian at a MK 172/year basic level. This line implies an annual income per E 80- adult equivalent of MK 151.* j MK 151/year The 1990 Reference Line was used in the World 20-_ . .. .. . . ,/ . Bank report 'Malawi-Growth Through Poverty .7. MK 98 /year Reduction" (1990) and implies an annual income 10 per adult equivalent of MK 172 (US$40). X-axis is on a log scale____ 0- x *MK are for the year of the NSSA survey, 1992/ o- I 1' I I I 1993 10 20 50 100 200 500 1000 _- Income (MK /Adult Equivalent / Year) Source: NSSA (I 992/1993)  Profile of Poverty for Maai}25 range of the illustrative poverty lines defined, there is low priate as almost all the determinants of poverty affect the variability in household incomes. Thus, a change in the entire household. To make comparisons across households, value of the cutoff leads to a less than proportional change taking into account variations in their composition among in the measured prevalence of poverry.' age groups, incomes and expenditures were converted us- ing adult equivalency scales to produce a figure calculated The household is the unit of analysis at per adult basis. Tro compare across houiseholds with different incomes In the analyses presented here, incomes (using the NSSA and costs of living in different areas ofthe country, incomes data) and expenditures (using the HESSE-A data) are com- and expendituLres were adjusted to include estimates of own- puted and presented at the level of the household rather account productioni and consumption and of imputed ex- than the individual. The methodological details are pre- penditures on rental housing and to accotint for cost-of- sented in Annex 1. The focus on the household is appro- living differenices between areas. Table 3.1 Poverty prevalence for rural smallholders according to different poverty lines Percent of Annual income population per capita Poverty line -Percentile 80 % below ..... .. MK 241 60 % below .................... MK 213 1990 Reference Line ..... 54' percentile 50% below.................MK 158 --- Basic Needs Line . 43d percentile 40% below ....MK 1 17 Calorie Needs Line ...... 30th, percentile 20% below ....... MK 54 Source; NSSA 1992/1993 Figure 3.2 Distribution of incomes for rural smallholders, per capita 7- 0 300 800 4600 Income (MK/AE/Year) Source: NSSA 1992/1993  26 Malawi * Profile and Priorities for Action 3.2 The ounie piturebution of expenditures shows high inequality (Figure 3.3), 3.2oThe povertrywede pectureas does the Gini coefficient which is 0.62-the highest of poverty level of inequality for any of the 13 African countries for whiclh data are available.' Incomes and expenditures A similar pattern is observed for rural smaliholders. suggest widespread deprivation Their mean annual household incomes were 312 MK/ AE (US$66) and the median was 188 MK (US$39). The Incomes and expenditures in Malawi are both very low, bottom half of the distribuition of smaliholder house- and are distributed very unequally.) The national mean holds received 1 5 percent of the income, while the top expenditure level per household was US$189 and the 10 percent received 35 percent of the income. Eighty median (50h percentile) expenditure level was US$104 percent of smallholder households have incomes lower (at 1990-91 exchange rates). The large difference between than 500 MKlAE/year. about US$ 1 00/AE/year at July the mean and the median indicates a skewed distribu- 1993 exchange rates." The Gini coefficient for rural tio. T ioal Lorenz curve for the naional distri- smiallholder incomes is 0.57, which is also extremely high. These data confirimi that rural poverty is deeper and more severe than aggregate GNP figures indicate. Figure 3.3 Lorenz curve for national Most of the poor live in rural areas distribution of expenditures 1.0 - Poverty in Malawi is predominantly rural. Roughly 90 0.9 - percenit of the Malawian people live in rural areas, and W 0.8 - / / their share of the poor is slightly larger than their share of the poptilation-94 percent of the households with ~ 0.7 /expenditLres belov the 40"1 percentile live in rural areas J 06 - / (Table 3.2). 0.s - By contrast. urban households are under-repre- @ 0.4 - / / sented amonig thie poor.' Only 4 percent of the house-