Some aspects of poverty in Sri Lanka : 1985-90

_ _ _ __ _ _ _ _ v P S r\ 3 % POLICY RESEARCH WORKING PAPER 173 8 Some Aspects of Poverty Poverty in Sri Lanka is still largely a rural phenormenon. in Sri Lanka: 1985-90 Between l986and 1991, national poveeiy rates. Gaurav Datt dedinct ;nodestiy. alrnnst Dileni Gunewardena enrre,y because of a decline in rural poverty During the sarrme period, urb.in poverty increased. PcG et households tend to h-ave higher dep:r) iMdorcy ti. fe\ver year. of schooling, lovler pairtii ipawitlon iF e la! <-. force>, arndi signic antlv higher U rienl2 lovyiient The World Bank Policy Research Department Poverty and Human Resources Division  POLICY RESEARCH WORKING PAPER 173b Summary findings Datt and Gunewardena characterize pove:rty in Sri But poverty in Sri Lanka is still largely a rural Lanka, using data from two recent household surveys phenomenon. Nearly half the poor depend on (for 1985-86 and 1990-91). Poverty rates in 1990-91 agriculture for livelihood. Another 30 percent depend on were highest in the rural sector and lowest in the estate other rural nonagricultural activities. sector, with the urban sector in betveen. Regional variations in poverty are fairly limited. Between 1985-86 and 1990-91, national poverty Female-headed households are associated with greater declined modestly, almrost entirely because of a fall in poverty only in the urban sector. Poorer households tend rural poverty (although poverty in the estate sectom also to have higher dependency ratios, fewer years of declined). Agriculture, forestry, and fishing accounted schooling, lower rates of participation in the labor force, for about 80 percent of the decline in national poverty. and significantly higher rates of unemployment. Favorable redistribution and growth in ruiral mean Direct transfer benefits from the Food Stamp Program consumption accounted about equally for the decline in are progressive and have a greater impact on poverty rural poverty. than uniform allocations from the same budget. During the same period, urban poverty increased. Economic growth could reduce poverty considerably. This paper-a product of the Poverty and Humarn Resources Division, Policy Research Department - is a revised version of a background paper for the Sri Lanka Poverty Assessment. Copies of this paper are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Patricia Sader, room N8-040, telephone extension 202-473- 3902, fax 202-522-1153, Internet address psader@worldbank.org or Andrea Ramirez, room N8-036, telephone 202-458- 5734. March 1997. (62 pages) The Policy Research Wlorking Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, in terpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent. Produced by the Policy Research Dissemination Center  Some Aspects of Poverty in Sri Lanka: 1985-90 * Gaurav Dart and Dileni Gunewardena * This is a revised version of a background paper in support of the Sri Lanka Poverty Assessment which was written by the authors at the Poverty and Human Resources Division, Policy Research Department, World Bank. We are grateful to the Department of Census and Statistics, Ministry of Policy Planning and Implementation, Colombo, Sri Lanka, who provided us with the data as well as prompt answers to our subsequent queries. We have benefited from the commnents of Hugo Diaz at various stages of the work. We would also like to thank Benu Bidani, Emmanuel Jimenez and Martin Ravallion for useful suggestions and comments.   1 Introduction Sri Lanka's record as a relatively poor country with excellent social indicators has held an imnportant place in policy discussions on poverty and human development. Its experience has often been considered an eminent example of "support-led" as distinguished from "growth-mediated" strategy to improvement in basic capabilities (Dreze and Sen, 1989), though this view has not gone uncontested. In particular, there has been much debate on the relative importance of growth in average incomes and social sector spending for improvements in basic social indicators such as life expectancy and under-5 mortality.' This debate has however remained largely uninformed by how the country has fared in terms of income or consumption poverty. This is for good reason: despite the apparently large poverty-oriented literature, there remain large gaps in what we know about income or consumption poverty in Sri Lanka. For example, poverty estimates for Sri Lanka have seldom gone beyond the disaggregation for rural, urban and estate sectors, and there does not seem to exist any consistent regional poverty profile for the country. We also do not know how levels of poverty vary by socio-economic characteristics such as the sector of employment, gender of the head of the household, or ethnic groups. Similarly, little is known about tlhe relationship between consumption poverty and other household attributes such as educational attainment, labor force participation or employment status. Also, we do not know much about recent changes in poverty and what the proximate determinants of those changes may have been. This paper attempts to fill some of these holes in our knowledge of consumption poverty in Sri Lanka. The paper is based on an analysis of data from two recent household surveys in Sri Lanka, viz., the Labor Force and Socio-economic Survey (LFSS) of 1985-86 and the Household Income and Expenditure Survey (HIES) of 1990-91 conducted by the Department of Census and Statistics (DCS). The DCS surveys have been the basis of several previous estimates of poverty, but have remained under-utilized for a detailed characterization of poverty in Sri Lanka. The paper is organized as follows. We first discuss the data and methodological issues related to The many contributions in this debate include Isenman (1980), Sen (1981, 1988), Bhalla and Glewwe (1985, 1986), Ravallion (1987), Bhalla (1988a,b), Anand and Kanbur (1991), Kakwani (1993), Aturupane, Glewwe and Isemnan (1994).  poverty measurement in section 2. Section 3 deals with the construction of spatial and temporal cost of living indices, an issue which has been largely ignored in the empirical poverty literature on Sri Lanka. The detailed results are presented in sections 4-6. Section 4 presents our estimates of absolute poverty for 1985-86 and 1990-91 at the national and sectoral level, and examines the robustness of the observed changes in poverty over a range of poverty measures and poverty lines. It also presents results on the proximate sources of changes in poverty using some simple decompositions. In section 5, we present a detailed regional and socio-economic poverty profile. In section 6, we use the data to examine the targeting performance of the Food Stamp Program which has been a key anti-poverty program in the country. We also look at the implications of the poverty profile for targeting resources and development programs, and the potential effect of economic growth on future poverty reduction. The final section concludes with a brief summary of the main findings. 2 Data and methodology 2.1 The standard of living indicator Unlike a lot of recent work on poverty in Sri Lanka, we will be concerned with consumption poverty. In particular, we use per capita consumption expenditure (excluding expenditure on durables) as the preferred indicator of individual standard of living.2 A number of recent studies have used calorie intake or food expenditure per capita (or per adult equivalent) as the poverty indicator. Examples of the former are Sahn (1987), and Rouse (1990); examples of the latter include Anand and Harris (1985), and Edirisinghe (1990). Partly, the motivationfor this has been the non-availabilityof a suitable cost-of-living index; using calorie consumption or food expenditure linked with some caloric intake obviates the need for a cost-of-living index. But this is achieved at some expense; what these studies measure is the extent of under-nutrition or food poverty. While this is an important dimension of poverty, the poor, by most definitions, devote a significant part of their expenditure to non-food items. For instance, for 1985-86 2 See Deaton (1995) for a discussion of the relative merits of using per capita consumption as the individual welfare indicator for developing countries. 2  Rouse (1990) reported the average share of food expenditure for the poor (defined in terms of calorie consumption per adult equivalent) to be only about 61 per cent. Arguably, an important dimension of poverty is potentially lost by ignoring non-food expenditures altogether. And there may also be considerable re-ranking of households when per capita food, rather than total, expenditure is used as the welfare indicator (see Glewwe and van der Gaag 1990, Chaudhuri and Ravallion 1994, Lanjouw and Lanjouw 1996). Total (all-commodity) consumption expenditure is also better grounded in consumer theory as a money metric of welfare, while the same cannot be said of food expenditure. Total consumiption expenditure is thus preferred as an indicator of the standard of living and poverty as it allows us to construct a more generalized measure of deprivation. The lack of suitable inter-regional or inter- temporal price indices for Sri Lanka is, however, a serious problem. How this may be addressed using the LFSS and HIES data is discussed further below. 2.2 Coverage and Comparability The 1985-86 Labor Force and Socio-economic Survey (LFSS) and the 1990-91 Household Income and Expenditure Survey (HIES) are broadly comparable in design and methodology, though the 1990-91 survey, as its changed title suggests, is narrower in scope and has only limited information on household employment and earnings. An important limitation of the survey data we are using should be noted at the outset: they do not have full national coverage. The 1990-91 HIES could not be conducted in 8 of the Northern and Eastern districts due to the prevailing conditions of political unrest. These districts were only partially covered in the 1985-86 HIES. To maintain comparability, we decided not to use the available 1985-86 data for these districts. The 8 excluded districts - Jaffna, Kilinochchi, Mannar, Vavuniya, Mullaitivu, Batticaloa, Amparai, Trincomalee - accounted for about 15 % of Sri Lanka's population in 1990 (DCS 1991).A Also, data from only the first three (of the 12 monthly) rounds of the 1990-91 HIES were available 3 All references to "Sri Lanka" and "national" in various Tables and the text should be taken to imply the whole country except the 8 Northern and Eastern districts. 3  to us at the time of this work. Again, in order to maintain comparability with the 1985-86 HIES, we only used data from the corresponding three rounds (i.e., pertaining to the same calendar months) of the 1985- 86 survey. The three rounds are for the months of June, July and August. 2.3 Poverty measures We will use poverty measures within the Foster, Greer, Thorbecke (FGT) class (Foster et. al 1984). The FGT class of poverty measures encompasses many of the well-known measures, and can be generally written as P = f [LS .x)dx M where x is per capita consumption expenditure,f(x) is its density, z denotes the poverty line, and a is a non- negative parameter. Higher values of the parameter a indicate greater sensitivity of the poverty measure to inequality amongst the poor. We will generally work with poverty measures Pa for a = 0, 1, 2 which respectively define the headcount index, the poverty gap index and the (distributionally sensitive) squared poverty gap index. 2.4 Reference poverty line Our starting point here is a reference food poverty line. This is derived from Nanayakkara and Premaratne (1987). Using LFSS data for 1985-86, they estimated a food poverty line at a monthly per capita food expenditure of Rs 202.49 at 1985-86 prices, corresponding to a normative threshold of 2500 calories and 53 grams of protein per adult (age 20-39 years) male equivalent. We round this off to Rs. 200 (at 1985-86 prices), and that defines our reference food poverty line. Allowing for basic non-food expenditure estimated from national Engel functions for 1985-86 (see discussion below), this yielded a national reference poverty line of Rs 242.06 of monthly per capita expenditure (on all items except consumer durables) at 1985-86 prices. Most of our poverty estimates are anchored on this poverty line; 4  often we will also use a more generous poverty line that is 20 per cent higher than the reference line.4 How does this reference poverty line compare with some others in the literature? As mentioned above, a good part of the literature on poverty in Sri Lanka does not use expenditure poverty lines at all as it performs all calculations in terms of calories. In recent work, there are only a few instances of the use of expenditurepoverty lines. Notable among these is the poverty line by Gunaratne (1985), also used by Anand and Harris (1985), and Bhalla and Glewwe (1985). This is a food poverty line defined by a food expenditure of approximately Rs. 70 per capita per month at 1978-79 prices, or about Rs. 173 at 1985-86 prices when up-dated by the Colombo Consumer Price Index (CPI) for Food. This is about 13 per cent lower than the reference food poverty line we use. A comparison can also be made with the a-dollar-a-day (per person at 1985 purchasing power parity) poverty line used in some recent estimates of poverty for the developing world (see, for example, Chen, Datt and Ravallion, 1993). In Sri Lankan currency, this translates into a per capita expenditure of about Rs 252 per month, or about 4 per cent higher than our reference poverty line. In some of the following analysis, we will focus on robust ordinal comparisons of poverty, for instance, when looking at whether poverty has decreased or increased between 1985-86 and 1990-91. In these cases, we will not use any specific poverty measures or poverty lines, but instead draw upon the dominance approach following Atkinson (1987), which allows us to make robust poverty comparisons for a broad class of poverty measures and for a range of poverty lines up to some quantifiable maximum. 2.5 Regional disaggregation The level of regional disaggregationof the poverty profile is constrainedby the overall sample size. Since we are using only 3 rounds of the surveys, our effective samples are relatively small: 4847 households for 1985-86 and 4650 for 1990-91. It will thus not be possible to construct poverty profiles for each of the 17 districts covered in the two surveys with any reasonable degree of precision. But we 4 In some of the tables below where we use both poverty lines, we designate the population below the higher line as poor, and those below the reference line as ultra poor. 5  do introduce a limited disaggregation broadly at the provincial and sectoral level. We distinguish the following five regions: (i) Western (districts: Colombo, Gampaha, Kalutara), (ii) Central (districts: Kandy, Matale, Nuwara Eliya), (iii) Southern (districts: Galle, Matara, Hambantota), (iv) North western and north central (districts: Kurunegala, Puttalam, Anuradhapura, Polonnaruwa), and (v) South central (districts: Badulla, Monaragala, Kegalle, Ratnapura). For each region, we further distinguish between the rural and urban sectors. Given the relatively small number of observations for the estate sector, we subsume it under the rural sector. For the estimates constructed at the national level though, we will separate out the estate sector. 3 Spatial and temporal price indices For Sri Lanka, there do not exist any suitable price indices to control for (a) regional differences in the cost of living, and (b) temporal changes in the cost of living within regions or sectors. The only established consumer price index (CPI) is the Colombo CPI, which of course is a temporal price index for the city of Colombo only. The DCS also publishes urban retail prices of some food items by district. But no indices or price data are available for the rural sector. The first part of our work is therefore devoted to the construction of spatial and temporal price indices for rural and urban sectors of the five regions introduced above, using the LFSS/HIES data. This is done in two steps. First, we construct spatial price indices separately for 1985-86 and 1990-91; for either survey year, these indices link regional cost of living to national (average) cost of living in the same year. The procedure for constructing spatial price indices is the same for both 1985-86 and 1990-91. We then construct a temporal price index to link national cost of living in 1985-86 with that in 1990-91. Together this yields a full set of price relativities across all regions and over the two survey periods. The details of our methodology are set out below. 3.1 Spatial price indices The LFSS/HIES provide data on the quantities and values of over 200 food items for the sampled households, using which one can construct unit values. For most non-food items, however, such unit 6  values cannot be constructed because either we do not have data on the quantities consumed for these items, or the non-food item is intrinsically too heterogenous for a unit value to be meaningful. Thus, we begin by first constructing a spatial food price index. Spatial cost of living differences for non-food items will be estimated separately by estimating Engel functions for non-food consumption (discussed later). Our methodology for the construction of the spatial food price index for a given survey year is as follows. (i) The entire (national) sample is ranked by nominal per capita expenditure (net of expenditure on durables), and a sub-sample of the bottom 40% of the population is identified as the reference group of households. Data from this sub-sample only are used for the construction of the food price index. (ii) The selected sub-sample is allocated to the rural and urban sectors of the five regions, which defines the reference group of households for each region-sector. (iii) The over-200 food items are aggregated into 38 expenditure categories, comprising 36 food categories, and kerosene and firewood. The aggregation seemed desirable for mitigating the problem of the unit values for some food items being based on very few observations for the reference group of households. An attempt has however been made to ensure that the categories consist of relatively homogenous items for both surveys. For convenience, we will refer to these 38 categories as "food", and all other items of consumption as "non-food", even though "food" includes two non-food items (kerosene and firewood), "non-food" includes some of the highly heterogenous food items. A list of the expenditure categories is given in Annex 1. (iv) Next, we construct regional and national unit values for the 38 food categories. For region R, the unit value for category j is defined as R R - R p.v./lq. where vjR is the average value and q-R is the average quantity of category j consumed by the reference group of households in region R. Similarly, the national unit value for category j is defined 7  pi v.l- where iV and q-j are averages for the national reference group of households. I I (v) The food price index in region R relative to the nation as a whole is then defined as p R- = ____ w~R. j P, (1) where wj's are the expenditure shares of different food categories for the national reference group of households, and are defined as w.= v.a t v, There are two reasons why we base the food price index on data pertaining to the bottom 40 per cent reference group of households only. The first reason has to do with the fact that unit values are not prices. The most important problem in using unit values to construct cost of living indices is that they are often positively correlated with the level of living, reflecting the use of better quality products by richer groups. By constructing unit values only for the bottom quantiles in different regions (as determined by the bottom 40 % of the national sample), we mitigate the problem of standard-of-living-related quality variation. The second reason is that since the spatial price indices are to be used for poverty analysis, we would like the quantity weights for different expenditure categories to reflect the expenditure pattern of the poor rather than the whole population. In estimating spatial price differences for non-food items using Engel functions, we broadly follow the approach discussed in Ravallion and Bidani (1994), and Ravallion (1994). We first define a food poverty line, denoted ZF, as the minimum level of per capita food expenditure required to meet some nutritional threshold. As discussed above (section 2.4), this is taken to be a per capita food expenditure of Rs. 200 per month at 1985-86 national prices. The nominal food poverty line at 1990-91 prices is derived using the temporal food price index (discussed in the following sub-section). 8  For any survey year, given a zF defined at national prices, the food poverty line for region R (denoted ZFI) is obtained as ZFR = PF9. Z4. Next, we define basic non-food expenditure for region R (denoted zN') as the typical non-food expenditure (per capita) of a household in region R whose total expenditure (per capita) is just equal to the food poverty line. The poverty line for region R, zR, is then obtained as the sum of ZF and ZNR. Basic non-food expenditure is determined by estimating a region-specific food-share equation, as below. w R R + aR hR + aR c + f31n(xiz R/ + ER (2) Fl 0 Il1 2 i i F where xi' is per capita (total) expenditure of household i in region R, wFR is the share of food in the household's expenditure, hiR is household size and ciR is the number of children in the household under 10 years of age. I On writing R R R R R-R a =a + a h + a c 0 1 2 we can interpret the parameter a' (evaluated at regional mean values) as the typical food share of a household in region R whose total expenditure is just equal to the food poverty line. The poverty line for region R can then be written zR zR (2 a-) (3) A national poverty line z can be derived analogously. Hence, the spatial cost-of-living index for region R relative to the nation as a whole can be derived p R = ZRIZ = PR(2 - R)/(2 -a') (4) There is of course no a priori reason why the national poverty line thus evaluated should coincide with the 5 Thie parameter estimates for the food Engel functions for 1985-86 and 1990-91 are available not shown here but from the authors upon request. 9  population-weighted average of regional poverty lines; however, with our data they virtually do, both for 1985-86 and 1990-9 1. 6 3.2 The temporal price index The methodology for constructing an index of change in the cost of living between the two survey dates is analogous to that for the spatial index. We will first define a temporal food price index between 1985-86 and 1990-91; this is defined in terms of national prices. Generalizing equation (1) above, we can write a Fisher's type food price index as p9/5= 1