Report No: AUS0000426 . Afghanistan Poverty in Afghanistan Results based on ALCS 2016-17 . July 2018 . POV . . Document of the World Bank . © 2017 The World Bank 1818 H Street NW, Washington DC 20433 Telephone: 202-473-1000; Internet: www.worldbank.org Some rights reserved This work is a product of the staff of The World Bank. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of the Executive Directors of The World Bank or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Rights and Permissions The material in this work is subject to copyright. Because The World Bank encourages dissemination of its knowledge, this work may be reproduced, in whole or in part, for noncommercial purposes as long as full attribution to this work is given. Attribution—Please cite the work as follows: “World Bank. 2018. Poverty in Afghanistan: Results based on ALCS 2016-17. © World Bank.” All queries on rights and licenses, including subsidiary rights, should be addressed to World Bank Publications, The World Bank Group, 1818 H Street NW, Washington, DC 20433, USA; fax: 202-522-2625; e-mail: pubrights@worldbank.org. 2 POVERTY IN AFGHANISTAN 1 One of the main objectives of the Afghanistan Living Conditions Surveys (ALCS, formerly the National Risk and Vulnerability Assessment or NRVA) is to provide information on welfare and living standards, on their evolution over time, and their distribution over households. Of particular importance is the measurement and tracking of welfare amongst the poorest segments of the population, and ALCS survey data provide the principal means for estimating the extent and severity of poverty in Afghanistan. MEASURING POVERTY IN AFGHANISTAN: THE COST OF BASIC NEEDS APPROACH The measure of welfare adopted to assess population living standards is based on household expenditures. An individual is considered as poor if their level of consumption expenditures is not sufficient to satisfy basic needs, or in other words, if their consumption expenditure falls below the minimum threshold identified by the poverty line. In line with international standards, the official absolute poverty line for Afghanistan is estimated following the Cost of Basic Needs (CBN) approach and it was set using the NRVA 2007-08. The CBN absolute poverty line represents the level of per capita consumption at which the members of a household can be expected to meet their “basic needs” in terms of both food and non-food consumption.2 To assess the evolution of wellbeing over time, the 2007-08 poverty line was updated to 2011-12 and 2016- 17 prices for each of the survey years to reflect changes in the cost of living. Figure 1 below briefly describes the data sources and the estimation methodology3. It is important to note that the detailed consumption expenditure module, which allows for direct estimation of poverty, was not included in the ALCS 2013-14. Rather, survey-to-survey imputation techniques were used to predict poverty rates for this survey year. The 2016-17 estimates introduced improvements in the methodology, which have been consistently taken backwards to 2011-12 and 2007-08 (survey to survey imputation estimates for 2013-14 have not yet been revised). These comprise of three important changes: (i) In the interest of increased transparency, and in line with international good practice, non-food thresholds are inflated from their 2007-08 benchmark levels using non-food inflation rates as measured by the official CPI; (ii) Improvements and changes in the survey questionnaire have required small changes in the definition of the welfare measure, which have been consistently revised for all survey years; and (iii) CSO has made the decision in the interest of transparency to include all provinces in national estimates; while indicating clearly provinces for which estimates are 1 This report was prepared by a team from the Poverty and Equity Global Practice of the World Bank and included Nandini Krishnan (Senior Economist), Christina Wieser (Economist), and Zihao (Tobias) Wang (Consultant). 2 More specifically, the food component of the poverty line captures the cost of consuming 2,100 Kcal per day following the typical food consumption patterns of the relatively poor; the non-food component of the poverty line is estimated as the median non-food expenditure of individuals with food consumption around the food poverty line. For more details, please refer to: http://documents.worldbank.org/curated/en/665241533556485812/Poverty- measurement-methodology-using-ALCS-2016-17 3 For a more in-depth description of the methodology, please refer to: http://documents.worldbank.org/curated/en/665241533556485812/Poverty-measurement-methodology-using- ALCS-2016-17 3 deemed to be of inadequate quality due to the security situation or concerns about data quality. These revisions imply that current estimates may differ from previously released numbers. Figure 1: Data sources for poverty measurement and methodology 2007-08 NRVA: 2013-14 ALCS: 2011-12 NRVA: 2016-17 ALCS: BENCHMARK IMPUTATION OF POVERTY ESTIMATES POVERTY ESTIMATES POVERTY ESTIMATES POVERTY ESTIMATES •Define welfare •Food poverty threshold •Survey did not include •Food poverty threshold aggregate priced 2007 food bundle the detailed prices 2007 food bundle •Define reference at 2011 prices expenditure modules at 2016-17 prices population (2nd-5th •Non-food poverty • Survey to survey •Change: Non-food decile) threshold was re- imputation methods thresholds calculated •Define reference estimated based on were used to estimate based on inflating 2007 quantity bundle 2011 food thresholds poverty non-food threshold •Food threshold: Cost of • Helmand and Khost using non-food inflation purchasing 2100 dropped as measured by CPI kilocalories per capita •Comparable poverty •Consistency: Welfare per day following the trends (32 provinces) aggregate and poverty same consumption line made consistent to pattern as the reference reflect improvements in bundle questionnaire •Non-food threshold: • Coverage: All provinces Average non-food to be included in expenditures of national estimates, with households whose per data quality capita food expenditure assessments is close to the food threshold •Define poverty line Source: CSO and World Bank. POVERTY LINES Poverty lines in Afghanistan are estimated at the regional-urban/rural strata level, and the national poverty line is the population weighted average of these regional-strata lines. The classification of provinces into regions for this purpose is shown in Table 1 below. These 8 regions, when split into urban-rural strata, yield 14 region-strata classifications (some regions do not have urban strata), and therefore 14 poverty lines. Table 1: Regions and provinces West Central South East Northeast North West Southwest Central Kabul Ghazni Kunarha Badakshan Balkh Badghis Helmand Bamyan Kapisa Khost Laghman Baghlan Faryab Farah Kandahar Daykundi Logar Paktika Nangarhar Kunduz Jawzjan Herat Nimroz Ghor Panjsher Paktya Nooristan Takhar Samangan Urozgan Parwan Sar-e-Pul Zabul Wardak 4 Figure 2 shows the revised poverty lines for Afghanistan after implementing the methodological changes described above. In 2007-08, the national average threshold for the cost of covering basic needs, the poverty line was 1,261 Afs per person per month. This threshold, consistently defined and valued at 2016- 17 survey prices, increases to 2,056 Afs per person per month. Relative to 2007, this represents a 64% increase in the cost of basic needs, comprised of a 68% increase in the cost of the basic food bundle (benchmarked at 2,100 Kcalories per person per day), and a 58% increase in the cost of non-food necessities. Figure 2: Poverty lines (weighted national Figure 3: Implied average inflation (relative to average), 2007 to 2017 2007=100) based on poverty lines Food Non-food Total Food Non food Total Afs per person per month 168.43 163.69 2,056 157.67 1,758 146.37 1,261 139.16 1,188 1,034 130.01 868 706 724 555 100.00 2007-08 2011-12 2016-17 2007-08 2011-12 2016-17 Source: CSO, World Bank staff estimates, NRVA 2007, Source: CSO, World Bank staff estimates, NRVA 2007, 2011 and ALCS 2016 2011 and ALCS 2016 The rest of this chapter is organized as follows. The next section briefly describes the country context in which the revised poverty trends are situated, followed by a description of the trends in welfare between 2007 and 2017. These trends are analyzed at the national, urban-rural and regional level. The chapter concludes with a profile of Afghanistan’s poor, highlighting key correlates of welfare. CONTEXT, 2007-2017: DECLINE IN ECONOMIC GROWTH AND A DETERIORATING SECURITY SITUATION The overall macro-economic and security context in the country since 2007 can be broken into two distinct phases, pre- and post- the 2014 security transition. While the pre-transition phase was characterized by higher economic growth and a relatively stable security situation, since 2014, growth has stagnated, and the security situation continues to deteriorate. In this context, the 2016-17 poverty estimates are the first direct estimates of welfare since the security transition in 2014. 5 Figure 4 plots per capita GDP and annual GDP growth between 2007 and 2016.4 Between 2007 and 2012, GDP per capita increased from $381 to $691, with economic growth averaging 11.2 percent per year. In contrast, the Afghan economy has grown at an average of 2.1 percent between 2013 and 2016, and GDP per capita in 2016 remains $100 below its 2012 levels. This economic slowdown has been accompanied by a deterioration in security since 2014 and economic activity (as measured by new firm registrations, Figure 5) has been adversely affected. Figure 4: Economic growth and per capita GDP has Figure 5: The deterioration in the security declined since 2012 situation has adversely affected economic activity GDP per capita ($) Battle-related deaths Real GDP growth, annual (%) New firm registrations 800 25 20000 700 18000 20 16000 600 GDP per capita ($) 14000 % growth GDP 500 15 12000 400 10000 300 10 8000 6000 200 5 4000 100 2000 0 0 0 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Source: World Bank, ADU, November 2017 Source: World Bank, ADU, November 2017; UNAMA The deteriorating security situation has led to large-scale population displacements (Figure 6), and has coincided with the return of more than a million Afghans. Since 2007, the number of injuries and deaths has increased five-fold, and in 2016, more than 650,000 Afghans were internally displaced due to conflict. At the same time, 2016 witnessed the return of more than a million documented and undocumented Afghan refugees, primarily from Pakistan and Iran. Internal displacement and large scale return within a difficult economic and security context pose risks to welfare, not only for the displaced, but also for the population at large, putting pressure on service delivery systems and increasing competition for already scarce economic opportunities. 4 Afghanistan’s economic growth is projected to increase slightly to 2.6 percent in 2017, and assuming no further deterioration in security, to 3.2 percent in 2018. World Bank, 2017. Afghanistan Development Update, November 2017. 6 Figure 6: More than 650,000 Afghans were internally Figure 7: More than a million Afghans returned displaced by conflict in 2016 in 2016 alone Injuries+Deaths Conflict-induced IDPs Undocumented returns 800,000 140,000 Documented returns 700,000 120,000 600,000 100,000 Injuries+Deaths 500,000 80,000 IDPs 400,000 691,581 60,000 300,000 40,000 200,000 663,295 100,000 20,000 461,028 372,577 0 0 58,460 56,839 2015 2016 2017* Source: UNOCHA, UNAMA * As of November, 2017; Source: UNHCR, IOM Sector specific trends in growth suggest further causes for concern. While agriculture’s contribution to GDP has declined steadily from around 30 percent in 2007 to 22 percent in 2016, it remains an important sector as a source of livelihoods for the rural poor, in influencing the affordability of basic food items for the population, and its significant inputs into the manufacturing sector. Significant annual fluctuations notwithstanding, the agricultural sector grew, on average, 8 percent per year between 2007 and 2012. Since then, its annual growth rate has fallen sharply to 0.1 percent on average. Potentially related, the ALCS 2016-17 survey period coincided with an increase in food price inflation, which climbed to 10.7 percent year-on-year in May 2017 (World Bank, ADU, November 2017). Figure 11: Annual growth rates by sector (%) Agriculture Industry Services 50.0 40.0 30.0 20.0 10.0 0.0 -10.0 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 -20.0 Source: World Bank staff estimates for ADU, November 2017 7 TRENDS IN POVERTY, 2007-2017 Afghanistan has experienced a sharp increase in poverty since 2011-12. Figure 12 plots the national, urban and rural poverty headcount rates based on the new series and using the three surveys where direct estimation of poverty is possible.5 Poverty headcount rates measure the share of the population whose monthly per capita expenditure falls below the poverty line. At the national level, these headcount rates increased from 34 percent in 2007-08 to 38 percent in 2011-12, followed by a sharp rise to 54.5 percent in 2016-17. Rural poverty remains consistently higher than urban poverty, although the deterioration in welfare has become more widespread. While the increase in poverty in the first period, 2007-2011, was driven by an increase in rural poverty, in the second period, both urban and rural poverty rates have increased substantially. These trends are consistent with the large economic contraction the country has experienced since 2012. The period 2007 to 2011 was characterized by a large increase in GDP per capita (which grew 63 percent relative to its 2011 value), whereas during the latter period, 2012 to 2016, GDP per capita actually fell (Figure 13). Figure 12: Trends in poverty (Headcount rate), 2007-2017 Figure 13: GDP Per capita (% change) 70.0 70.0 63.3 % OF POPULATION BELOW THE 60.0 60.0 50.0 POVERTY LINE 50.0 40.0 40.0 30.0 20.0 30.0 10.0 20.0 0.0 10.0 2007-08 2011-12 2016-17 National 33.7 38.3 54.5 0.0 Urban 25.71 24.64 41.60 2007-2011 2011-2016 Rural 35.72 42.33 58.55 -10.0 -5.0 Source: CSO, World Bank staff estimates, NRVA 2007, 2011 and Source: CSO, World Bank staff estimates ALCS 2016 As economic growth has lagged behind population growth (as measured by CSO’s population estimates, which, according to most recent estimates has underestimated true population growth), not to mention 5 These trends take into account methodological improvements defined consistently over time, and therefore differ from previously released estimates. Table: Comparable poverty trend series (Old and revised) 2007-08 2011-12 2013-14* 2016-17 Old series, excluding Helmand and Khost 36 36 39 Revised series, all provinces 34 38 55 Source: CSO, World Bank staff estimates, NRVA 2007, 2011 and ALCS 2016; *Imputation estimates 8 the additional 2.3 million Afghan returnees since 2015, the country has experienced a large increase in the number of poor people (Figure 14). In 2016-17, almost 13 million rural Afghans lived below the poverty line. At the same time, urban poverty has become more widespread, with the number of urban poor more than doubling since 2007, and consequently, 18 percent of Afghanistan’s poor now live in urban areas (Figure 15). The increase in urban poverty since 2011 was concentrated in Kandahar, Kabul, Herat, Balkh and Kunduz. In 2016-17, these provinces together accounted for 80 percent of the urban poor, with Kabul alone accounting for about half of all the urban poor. In part, this trend may be driven by IDPs and returnees turning to urban centers in search of security, jobs and services. If this trend continues, the pressure on urban centers will likely increase. Figure 14: Estimated number of poor people Figure 15: Share of the poor living in urban and rural areas Urban Rural Urban Rural 12,979,997 84.82 85.38 81.82 8,815,166 7,129,355 2,883,535 15.18 14.62 18.18 1,275,920 1,509,359 2007-08 2011-12 2016-17 2007-08 2011-12 2016-17 Source: CSO, World Bank staff estimates, NRVA 2007, Source: CSO, World Bank staff estimates, NRVA 2007, 2011 and ALCS 2016 2011 and ALCS 2016 DISTRIBUTIONAL CHANGES IN WELFARE This deterioration in welfare was experienced across the distribution, among the poorest households, as well as among the most-well off. Figure 16.1 plots the average per capita expenditures in 2016-17 prices by quintiles (dividing the expenditure distribution into five equally sized groups, sorted in ascending order of per capita expenditures), and shows that each quintile, even the richest 20 percent, experienced a decline in welfare. On average, per capita expenditure fell by 18 percent across the distribution between 2011-12 and 2016-17, and fell by 11 percent among the poorest 20 percent. Between 2007-08 and 2011- 12, instead, the richest 20 percent was the only group to experience an improvement in welfare. Average per capita expenditures increased slightly by 3 percent during this period, driven by this welfare improvement among the well-off, among the poorest 20 percent, expenditures fell by 10 percent. For the 2011-12 to 2016-17 period, these trends were largely explained by trends in per capita food expenditures, which fell by 21 percent on average, with each quintile experiencing a decline, and with the poorest 20 9 percent experiencing a 14 percent fall (Figure 16.2). Note that per capita expenditures fell while food prices were increasing, implying a decline in the quantity of food items consumed. The fall in non-food expenditures was more muted, except among the top 20 percent of the distribution. Figure 16.1: Trends in total per Figure 16.2: Trends in total per Figure 16.3: Trends in total per capita expenditure (2016 capita food expenditure (2016 capita non-food expenditure (2016 prices)6 prices)7 prices)8 2007-08 total exp (in 2016 prices) 2007-08 food exp (in 2016 prices) 2007-08 nf exp (in 2016 prices) 2011-12 total exp (in 2016 prices) 2011-12 food exp (in 2016 prices) 2011-12 nf exp (in 2016 prices) 2016-17 total exp 2016-17 food exp 2016-17 nf exp 6,000 3,000 3,000 5,000 2,500 2,500 4,000 2,000 2,000 3,000 1,500 1,500 2,000 1,000 1,000 1,000 500 500 0 0 0 Bottom 20% 2 3 4 Top 20% Bottom 20% 2 3 4 Top 20% Bottom 20% 2 3 4 Top 20% Source: CSO, World Bank staff Source: CSO, World Bank staff Source: CSO, World Bank staff estimates, NRVA 2007, 2011 and estimates, NRVA 2007, 2011 and estimates, NRVA 2007, 2011 and ALCS ALCS 2016 ALCS 2016 2016 These distributional changes imply that while the intensity of poverty has increased between 2011-12 and 2016-17 (Figure 17), inequality has declined (Figure 18), as the welfare loss among the top of the distribution has been relatively larger than that at the bottom of the distribution (albeit from very different baseline levels). The poverty gap index measures the extent of poverty as the average distance between the per capita expenditure levels of the population and the poverty line, assuming the non-poor have a zero shortfall, and is expressed as a proportion of the poverty line. As Figure 17, shows, the intensity of poverty has doubled at the national, urban and rural level since 2007. On average, the gap between per capita expenditures and the poverty line was 0.15 times the poverty line (calculated across the population).9 Another interpretation of the poverty gap index is that it provides a measure of the aggregate 6 Implicit inflation adjustment based on total poverty line 7 Implicit inflation adjustment based on food threshold 8 Implicit inflation adjustment based on non-food threshold 9 Among the poor, this gap is larger, on average 27 percent of the poverty line. 10 size of the monetary transfer required to bring the poor out of poverty, assuming perfect targeting were possible. Assuming a national population of 29 million in 2016-17 and using the poverty line of 2,056 Afs per capita per month, a poverty gap index of 0.15 or 15 percent of the poverty line, implies an average transfer of 310 Afs per person per month would be needed to eliminate poverty (and the total budget needed would be 131 million US$ per month, targeted to the poor). Figure 17: Trends in the intensity of poverty Figure 18: Trends in expenditure inequality (Gini (Poverty gap index) coefficient) National Urban Rural National Urban Rural 0.16 0.33 0.15 0.31 0.30 0.29 0.29 0.11 0.29 0.10 0.10 0.28 0.08 0.07 0.25 0.25 0.05 0.05 2007-08 2011-12 2016-17 2007-08 2011-12 2016-17 Source: CSO, World Bank staff estimates, NRVA 2007, Source: CSO, World Bank staff estimates, NRVA 2007, 2011 and ALCS 2016 2011 and ALCS 2016 Figure 18 plots the trends in expenditure inequality as measured by the Gini coefficient. The Gini index measures the extent to which the distribution of consumption among individuals or households differs from a perfectly equal one. A value of 0 represents absolute equality with everybody consuming the same amount, a value of 1 absolute inequality, where all consumption is concentrated in one person. The welfare decline experienced across the distribution (shown in Figure 16.1-16.3) is reflected here as a decline in the Gini index in 2016-17 relative to 2011-12, driven by the decline in rural inequality, stemming from a compression of living standards. To what extent was the increase in poverty between 2011-12 and 2016-17 driven by these distributional changes (which compressed the welfare distribution) relative to the overall decline in per capita expenditures (or in other words, the negative rate of growth of welfare)? Poverty reduction can take place without growth in average per capita expenditures if it is accompanied by relatively higher growth in the expenditures of the poor (a solely distributional effect). Alternatively, if the distribution remains 11 Figure 19: Growth-inequality decomposition of unchanged, or each individual’s per capita change in poverty rates between 2011-12 and 2016- consumption growth is equal to the average, 17 then the change in poverty stems solely from the Redistribution growth effect. Between 2011-12 and 2016-17, Growth Change in poverty 2011-16 the overall increase in poverty was 16.2 20 percentage points. This increase was almost 16.2 15 entirely due to a lack in growth in per capita 10 expenditures across the distribution. In fact, had 17.3 5 there been no (favorable) change in the 0 distribution of expenditures in 2016-17 relative -1.1 to 2011-12, national poverty rates would have -5 increased by 17.3 percentage points. The Source: CSO, World Bank staff estimates, NRVA 2011 and ALCS 2016 redistribution effect was able to slightly counter the rise in poverty as poorer households did slightly better than richer households in 2016 compared to 2011, although everyone lost. REGIONAL TRENDS Poverty headcount rates increased in every region between 2011-12 and 2016-17 (Figure 20). Even in the South, where regional estimates appear to have remained unchanged, the exclusion of a province where field operations were limited to the first two quarters of the survey year results in a regional poverty estimate of 46 percent in 2016-17. Regional disparities in welfare levels have also become more marked over time. The largest increases in poverty between 2011-12 and 2016-17 were in the Central, East, North and North-East regions, between 17 and 20 percentage points. The South West region recorded the highest poverty rate in 2016-17, and even if estimates for provinces where fieldwork was affected by security or of inadequate quality are excluded, while the region estimate is lower at 72 percent, it is still the highest in the country. Figure 20: Trends in regional poverty 2007-08 2011-12 2016-17 80.40 69.01 66.63 62.76 57.95 57.52 53.11 48.86 43.94 43.57 43.09 43.08 41.61 41.39 40.22 39.71 37.02 36.34 34.03 33.12 29.39 26.45 22.79 22.41 WEST SOUTH SOUTHWEST WESTCENTRAL CENTRAL NORTHEAST EAST NORTH Source: CSO, World Bank staff estimates, NRVA 2007, 2011 and ALCS 2016 12 As previously noted, a distinct feature of the increase in poverty between 2011 and 2016 has been the shift in the distribution of the poor towards urban areas. Nevertheless, four out of every five poor Afghans continues to live in rural areas. Figure 21 further breaks down the distribution of the urban and rural poor across regions in 2016-17. The Central region, including Kabul, alone accounts for a half of all urban poor, while the North, North East and South West regions account for another third. The rural poor are more dispersed throughout the county. The North East and South West regions each account for 17 percent of the rural poor, followed by the North region, with 15 percent. The distribution of the poor across regions has also changed over time (Figure 22). The South rural and East rural regions have experienced a steady decline in their share of the poor since 2007. The South West rural region’s share of the poor also fell from 17 percent in 2011-12 to 14 percent in 2016-17. In contrast, North rural and Central Urban now account for a larger share of the poor relative to 2011. Figure 21: Share of urban and rural poor by region, 2016-17 Central East North Northeast South Southwest West West-central URBAN 51.1 3.7 13.0 10.9 0.6 13.8 6.7 RURAL 10.4 11.5 15.3 17.0 9.1 16.7 11.1 8.8 Source: CSO, World Bank staff estimates, ALCS 2016 Figure 22: Changes in the regional distribution of the poor (excludes regions with <5% of the poor) NE Rural SW Rural North Rural West Rural East Rural Central Urban Central Rural South Rural W Central Rural 2016-17 13.93 13.8 12.35 9.39 9.28 9.18 8.33 7.51 7.37 2011-12 13.1 17.03 9.21 9.24 10.26 7.5 7.05 11.88 7.88 2007-08 14.18 6.31 11.81 8.61 12.13 7.56 10.36 13.73 7.69 Source: CSO, World Bank staff estimates, ALCS 2016 13 SEASONAL WARIATION IN WELFARE Poverty has always had a seasonal character in Afghanistan, with winter months being characterized by a deterioration in welfare. While the methodology for poverty measurement divides the survey period into quarters, these quarters closely track seasons in the country, with quarter 1 roughly coinciding with Spring, and quarter 4 with Winter. Figure 23 and 24 show the relation between seasonal and quarterly estimates of poverty in 2016-17, and trends in quarterly poverty rates from 2007 to 2017 respectively. Two patterns become evident here: the first, that there was a sharp increase in poverty in quarter 3 and 4 in 2016-17; and the second, that this increase was the largest in 2016-17 relative to other survey years. In part, these trends are driven by increases in prices, particularly food prices, over the survey period, peaking in quarter 4 (Figure 25 and 26). They may also be explained by a decline in income-generating opportunities from agriculture; and by a decline in the local availability of food items in the market during the winter months. Figure 23: Seasonal vs. quarterly poverty rates in Figure 24: Trends in quarterly poverty rates 2016-17 Quarter Season Q1 Q2 Q3 Q4 65.9% 62.7% 67.5% 65.9% 62.7% 55.7% 48.2% 46.8% 46.6% 45.2% 48.7% 48.2% 42.2% 46.3% 45.2% 39.5% 35.9% 30.3% 24.0% 21.0% Q1, Q2, Q3, Q4, 2007-08 2011-12 2016-17 SPRING SUMMER AUTUMN WINTER Source: CSO, World Bank staff estimates, ALCS 2016 Source: CSO, World Bank staff estimates, NRVA 2007, 2011 and ALCS 2016 14 Figure 25: Quarterly food and non-food price Figure 26: Quarterly average inflation, as inflation, survey + Nonfood CPI, 2016-17 measured by CPI, 2016-17 (Base Q1=100) Survey food price index Overall CPI Food CPI Non-food price index 110.0 100.06 108.0 100.04 106.0 100.02 104.0 100.00 102.0 99.98 100.0 99.96 98.0 99.94 96.0 1 2 3 4 Q1 Q2 Q3 Q4 Source: CSO, World Bank staff estimates, ALCS 2016 Source: CSO, World Bank staff estimates WHO ARE AFGHANISTAN’ S POOR? Household and individual demographic and socio-economic characteristics are important correlates of poverty. This section provides some descriptive statistics on the key correlates of poverty in Afghanistan, while describing the prevalence of these characteristics among the poor and the population as a whole. DEMOGRAPHIC CHARACTE RISTICS Consistent with past NRVA surveys, demographic characteristics are strongly correlated with poverty headcount rates. First, poverty rates increase steadily with household size (Figure 27). While a third of households with 1 to 5 members live below the poverty line, roughly 60 percent of households with 8 members or more are poor. However, smaller households with 1 to 5 members make up only 13 percent of the total population, whereas households with 8 or more members make up more than 60 percent of the population (Figure 28). Households of larger size therefore, are both more prevalent and face a higher poverty rate. Poverty also rises with increasing dependency. Figure 29 plots the share of the population living below the poverty line by child dependency and total dependency ratios. Given the demographic distribution of the country, with roughly 40 percent of the population below the age of 14, the bulk of dependency is accounted for by children, and as a result, the prevalence of poverty is very similar when comparing child dependency or total dependency. As with household size, households with very high dependency, for instance, 3 or more dependents to each working age household member, face rates of poverty as high as 70 percent. 15 Figure 27: Poverty rates by household size, 2016- Figure 28: Population share and poor population 17 by household size, 2016-17 Poverty rate Poor population by HH size Population share by HH size 62.1% 61.5% 58.2% 50.1% 5,000,000 30.0% 4,000,000 25.0% 34.6% 20.0% 3,000,000 15.0% 2,000,000 10.0% 1,000,000 5.0% 0 0.0% 10-12 members 1-5 members 6-7 members 8-9 members 13 or more members 1-5 MEMBERS 6-7 MEMBERS 8-9 MEMBERS 10-12 MEMBERS 13 OR MORE MEMBERS Source: CSO, World Bank staff estimates, ALCS 2016 Source: CSO, World Bank staff estimates, ALCS 2016 Figure 29: Poverty headcount rates, by dependency ratios, 2016-17 71.4% 71.3% 61.9% 61.1% 59.9% 59.2% POVERTY RATES (%) 44.1% 43.6% BELOW 1 1-1.9 2-1.9 3 OR ABOVE By child dependency ratios By total dependency ratios Source: CSO, World Bank staff estimates, ALCS 2016 Note: The child dependency ratio is defined as the number of children aged 0-14 over the population in the most productive ages (15-64). The total dependency ratio is defined as the number of children aged 0-14 and elderly aged 65 and above over the population in the most productive ages (15-64) 16 EDUCATION AND LABOR MARKET OUTCOMES Education (or the lack thereof) is another important correlate of poverty in Afghanistan. With only 36 percent of household heads being literate, the low levels of educational attainment are pervasive. Households with illiterate heads account for 74 percent of the population, facing poverty rates of 63 percent on average, compared with headcount rates of 40 percent among households with literate heads. Breaking it down further, it becomes evident that the lack of education is both highly correlated with poverty as well as highly prevalent. Approximately 73 percent of the population belongs to households where the head of household has no education (Figure 30). These households account for 82 percent of the poor, facing a poverty rate of 61 percent on average. While poverty does fall with increasing education of the head of household, households where heads have more than secondary education account for only 5 percent of the population. Finally, having an educated household head does not eliminate the risk of poverty. Figure 30: Poverty rates and share in population, by education level of head of household, 2016-17 Poverty rate Share of poor population Share of population 82 73 61 45 43 39 31 19 9 9 7 5 4 3 3 2 2 1 NO COMPLETED COMPLETED COMPLETED COMPLETED COMPLETED EDUCATION PRIMARY LOWER UPPER TEACHER UNIVERSITY SCHOOL SECONDARY SECONDARY COLLEGE OR SCHOOL SCHOOL TECHNICAL COLLEGE EDUCATIONAL ATTAINMENT OF HOUSEHOLD HEAD Source: CSO, World Bank staff estimates, ALCS 2016 The lack of a strong link between higher education and lower poverty likely reflects the pervasive lack of productive employment opportunities. Overall, 38 percent of the population belongs to households whose heads are either unemployed, under-employed or inactive (Table 2). About 42 percent of the poor population belongs to these types of households. In other words, the employment status of the head of the household does not sharply differentiate poor households from non-poor households. While poverty rates are highest among households with heads who are unemployed (68 percent), they remain high irrespective of the employment status of the head. 17 Table 2: Poverty rates, share in population, by employment status of head of household, 2016-17 Employment status of head of Share of poor Share of total household Poverty rate population population Employed 51.1 57.6 61.4 Underemployed 63.0 17.6 15.2 Unemployed 58.8 13.9 12.9 Inactive 57.2 10.8 10.3 Source: CSO, World Bank staff estimates, ALCS 2016 To understand why the poverty rate among households with employed heads is more than 50 percent, we must understand the quality of employment. Figure 31 plots poverty rates, share of the poor population and share of the total population by the type of job held by employed household heads. Approximately 59 percent of the population belongs to households where the head of household holds vulnerable employment, or in other words, is self-employed or works on own-account, is a day laborer or is an unpaid worker. Only 17 percent of the population belongs to households where heads hold salaried employment or work as employers. As Figure 31 shows, only having a salaried job (15 percent of the population) brings poverty rates below 50 percent. In contrast, 56 percent of the population belongs to households with heads who are self-employed or day laborers, whose poverty rates are as high as 53 and 66 percent respectively. Figure 31: Poverty rates, share in population, by type of job, employed head of household, 2016-17 Poverty rates Share of poor population Share of total population 66 57 57 53 45 43 42 40 16 13 10 7 5 4 3 3 2 2 SELF- DAY SALARIED SALARIED UNPAID EMPLOYER EMPLOYED LABOURER WORKER, WORKER, FAMILY PUBLIC PRIVATE WORKER SECTOR SECTOR TYPE OF JOB, EMPLOYED HEADS OF HOUSEHOLD Source: CSO, World Bank staff estimates, ALCS 2016 While employment of the household head in agriculture continues to be associated with higher poverty rates (63 percent), and accounts for a third of the poor population (and 29 percent of the total population) with employed heads, other sectors are also characterized by high poverty rates. Industry accounts for 11 percent of the poor (and total) population with employed heads of household, with a poverty rate of 58 percent; and the services sector, with 29 percent of the poor (and 35 percent of the total) population with employed heads, has poverty rates of 45 percent. Figure 32 breaks these patterns down into the major 18 sectors of employment (2-digit codes), highlighting the vulnerability of non-agricultural employment in the construction sector in particular. Figure 32: Poverty rates, share in population, by sector of employment, employed head of household, 2016-17 Poverty rates Share of poor population Share of total population 63 62 47 46 45 37 34 29 17 14 11 9 9 8 6 4 2 2 AGRICULTURE MANUFACTURING PERSONAL SERVICES AND INFORMATION CONSTRUCTION RESTAURANTS AND RETAIL TRADE AND COMMUNICATION WHOLESALE AND TRANSPORT, COMMUNITY, SOCIAL AND STORAGE, HOTELS SECTOR OF EMPLOYMENT, EMPLOYED HEAD OF HOUSEHOLD Source: CSO, World Bank staff estimates, ALCS 2016 CONCLUSION A severe slow-down in Afghanistan’s economic growth characterized the period between 2012 and 2016. This sharp deceleration can be attributed to the combined effects of the drawdown of international military forces and a sharp fall in associated international spending, reduction of aid, and increasing conflict and political instability. These trends are reflected in the increasing vulnerability of the Afghan population, as widespread deteriorations in welfare are evidenced in the sharp increase in poverty rates to 55 percent in 2016-17. Many inequalities persist in Afghanistan, between regions, cities and rural areas, and rich and poor Afghans. Poverty headcount rates increased in every region between 2011-12 and 2016-17 and the deterioration in welfare was experienced across the distribution, among the poorest households, as well as among the most-well off. These distributional changes imply that while the intensity of poverty has increased between 2011-12 and 2016-17, inequality has declined, as the welfare loss among the top of the distribution has been relatively larger than that at the bottom of the distribution. Demographic characteristics remain are strongly correlated with poverty headcount rates. Poverty rates increase steadily with household size and households of larger size are both more prevalent and face a higher poverty rate. Education (or the lack thereof) is another important correlate of poverty in Afghanistan. Low levels of educational attainment are pervasive and households with illiterate heads account for 74 percent of the population, facing poverty rates of 63 percent on average, compared with 19 headcount rates of 40 percent among households with literate heads. While unemployment of the head of household is correlated with higher poverty, employment is no guarantee against poverty. Roughly half the population belonging to households with employed heads lives in poverty. Few have access to productive or remunerative employment. Afghans living in households where the household head is employed in agriculture are likely to face higher poverty rates (63 percent) and account for a third of the poor population. More broadly, almost 60 percent of the population belongs to households where the head of household holds vulnerable employment, or in other words, is self-employed or works on own-account, is a day laborer or is an unpaid worker. 20