Vulnerability and Poverty in Bangladesh *

Transcription

1 ASARC Working Paper 2009/02 Vulnerability and Poverty in Banglades * Md. Safiul Azam Economics, Scool of Social Sciences, University of Mancester, UK & Katsusi S. Imai Economics, Scool of Social Sciences, University of Mancester, UK 24 April 2009 Abstract Tis study estimates ex ante poverty and vulnerability of ouseolds in Banglades using Houseold Income and Expenditure Survey (HIES) data in Our results sow tat poverty is not same as vulnerability as a substantial sare of tose currently above te poverty line is igly vulnerable to poverty in te future. Te study finds tat tose witout education or agricultural ouseolds are likely to be te most vulnerable. Te geograpical diversity of vulnerability is considerable, for example, vulnerability in coastal division, i.e., Cittagoan Division is almost double to tat of Daka and almost four times iger tan Kulna Division. It is suggested tat ex ante measures to prevent ouseolds from becoming poor as well as ex post measures to alleviate tose already in poverty sould be combined in evaluating poverty. For te cronic poor wo lack economic assets, priority sould be given to reduction of consumption fluctuations and building up assets troug a combination of protective and promotional programmes. Access to financial services, for example, toug micro credit programmes, migt elp poor ouseolds build up assets as it smootes income and consumption, enables te purcase of inputs and productive assets, and provides protection against crises. Key words: poverty, vulnerability, risks, poverty dynamics, Banglades JEL codes: C21, C25, I32 * Te autors are grateful to te financial support from DFID and Cronic Poverty Researc Centre at te University of Mancester in te UK. Te autors benefited from te advice from Armando Barrientos, Ragav Gaia, and Ragbendra Ja. Te views expressed are tose of te autors and do not necessarily represent tose of te organisation to wic tey are affiliated.

2 Vulnerability and Poverty in Banglades I. Introduction Te concept of risk and its contribution to poverty dynamics is gaining increasing importance in poverty literature. It is now evident tat te dynamic conceptualization of poverty is important from bot teoretical and policy perspectives in designing and implementing anti-poverty policies. Teoretically, te presence of risks can potentially influence ouseold decision making, for example, on weter to adopt a new agricultural tecnology or weter to ave more cildren in an effort to mitigate future income generation risks. An adequate understating of risk-poverty linkage is also beneficial in identifying some of te key micro-level binding constraints to poverty reduction: identifying wo are te most vulnerable, as well as wat caracteristics are correlated wit movements in and out of poverty, can yield critical insigts for policy makers (Ajay and Rana, 2005). Tus, to address poverty reduction as a goal, public policies sould not only igligt poverty alleviation interventions to support tose wo are identified as te poor ex post, but also te poverty prevention interventions to elp tose wo are poor ex ante, tat is, prevent tose wo are vulnerable to socks not to fall into poverty. Te latter was empasised by te World Bank s Social Risk Management framework wic igligts tree types of risk management strategies: prevention, mitigation and coping (Holzmann and Jørgensen, 2000). An assessment of ouseold s vulnerability to poverty is more tan justified to figure out wo is likely to be poor, ow poor are tey likely to be, and wy tey are vulnerable to poverty. Economic growt in Banglades in te last one and a alf decades or so as no doubt improved te living standard of te population across te country. Analysis of poverty trends as sowed a consistent decline in poverty incidence, especially in rural areas (see Table 1). Banglades as enjoyed a credible record of sustained growt witin a stable macroeconomic framework in recent years. At a comparatively low level of development, it as also earned te distinctions of a major decline in population growt rate and of graduating to te medium uman development group of countries by UNDP s ranking. Cild mortality was alved during te 1990 s, life expectancy as increased from 45 in 1972 to 64 years in 2005, net primary enrolment ASARC WP 2009/02 1

3 Md. Safiul Azam & Katsusi S. Imai Vulnerability and Poverty in Banglades went up significantly as did women s economic participation, gender parity as been acieved in primary and secondary education tanks mainly to scool stipend or food for education programme (e.g. 978 female students per 1000 male students). Notwitstanding specific areas of progress, aggregate poverty rates remain dauntingly ig. Pockets of extreme poverty persist and inequality is rising. Estimates based on te Houseold Income and Expenditure Surveys (HIES) of te Banglades Bureau of Statistics sow poverty declines from 58.8 in 1991/92 to 48.9 per cent in 2000 and it furter declines to 40.0 per cent in So poverty as declined sligtly more tan one percentage point a year since 1990s. Te observed improvement also olds true for te distributionally sensitive poverty measures te poverty gap ratio declined from 17.2 to 12.9 per cent and te squared poverty gap ratio declined from 6.8 to 4.6 per cent- indicating tat te situation of te poorest also improved during tis period. Despite tis improvement, te proportion of te poorest remained worryingly ig at around 25 per cent of te population in Tere is considerable interface between te poverty dynamics and unfavourable agro-ecological and climatic environment (e.g. soil salinity, flood, cyclone, river erosion, draugt etc.). Oter factors contributing to tis interface include low uman capital accumulation, unregulated and igly informal labour market, ealt azards and illness, arvest and social risks like weak rule of law resulting in crime, violence and insecurity, political unrest and corruption. Tere are indications tat a large number of ouseolds over around te poverty line, wic implies tat ig ratio of ouseolds can potentially fall back into poverty. According to Ajay and Rana (2005) recent growt experience in Asia -despite aving led to dramatic declines in US$1-aday poverty- is less rosy wen more generous US$2-a-day poverty line is used. Staggeringly large numbers are at te margin, indicating potential vulnerabilities to myriad socks for large proportion of population. Banglades alone as almost 68 million individuals in tis range. A dynamic forward looking analysis of poverty would lead us to understand te causes of poverty persistence and tereby elp bring sarper pro-poor orientation of te growt process were an inclusive social protection mecanism could play a central role. Taking into account te dynamic dimensions of poverty, te present study estimates te ex ante welfare of ouseolds as opposed to te traditional poverty ASARC WP 2009/02 2

4 Md. Safiul Azam & Katsusi S. Imai Vulnerability and Poverty in Banglades assessments, wic can only present a static and ex post picture of ouseolds welfare. We estimate ex ante bot te expected mean and as well as variability of consumption, wit te later being determined by idiosyncratic and covariate socks. A number of approaces ave been proposed to assess and estimate vulnerability to poverty. First, vulnerability can be seen as a probability of falling into poverty in near future (Cauduri, 2003; Cauduri et al., 2002; Cristaensen and Subbarao, 2001). Te oter way of measuring vulnerability considers it as low expected utility (Ligon and Scecter, 2003). Bot of tese measures ave teir advantages and disadvantages. 1 In eiter cases te underlying idea is to construct appropriate probability distribution of consumption expenditures conditional on ouseold caracteristics and subject to idiosyncratic/or covariate socks. Tis probability distribution function is ten used to estimate vulnerability indicators tat are similar to te family of FGT indices of poverty (Foster et al., 1984). Ideally, vulnerability measurement would require te long panel data. However, for many developing countries, reliable panel data are scarce and only cross-sectional survey data are available. Furtermore, most ouseold surveys are not designed to provide a full account of te impact of socks. Information on idiosyncratic and covariate socks is terefore eiter completely missing or very limited in most of te ouseold survey data. Banglades is no exception in tis regard. Altoug tere ave been regular rounds of Houseold Income and Expenditure surveys in every five year intervals, any nationally representative ouseold panel survey is yet to be available. Te absence of nationally representative panel data obliges us, in our assessment of vulnerability to poverty in Banglades, to adopt te approac proposed by Cauduri (2003) wic is particularly designed for cross-section data. Poverty reduction as been, and will remain te principal objective of development policy of Banglades for some foreseeable future to come. Altoug Banglades as experienced a moderate growt rate wit sustained macro-economic stability, it as one of te most adverse agro-ecological and climatic interfaces. Natural disaster, suc as, flood, cyclone, salinity, draugt, is fairly common events in te everyday life of Bangladesis. In addition to te unfriendly eco-climatic conditions, poor economic and social infrastructure contributes to te prevalence of 1 For a detailed survey of literature, refer to Hoddinott and Quisumbing (2003), Hoogeveen (2001) and Ligon and Scecter (2004). ASARC WP 2009/02 3

5 Md. Safiul Azam & Katsusi S. Imai Vulnerability and Poverty in Banglades ever present risks tat ouseolds need to cope wit. Te principal motivation of te present analysis is tus to explore te following questions: i) Wo is vulnerable to poverty and wat are te caracteristics of ouseolds wit vulnerability in Banglades?; ii) Do te caracteristics featuring ouseolds wit poverty and ouseolds wit vulnerability differ?; and iii) Wo are more likely to fall into transient poverty or cronic poverty and wat are te major caracteristics of ouseolds in transient and cronic poverty, respectively in Banglades? Te core objectives of tis study include measuring poverty and vulnerability to poverty in Banglades and suggesting some policy options for government to adopt for reducing poverty and vulnerability. Despite te abundant literature and discourse of poverty in Banglades, te rigorous quantitative studies to address te risks and poverty are scarce. Tis paper is to fill te gap by examining quantitatively te linkage between risks and movement in and out of poverty using nationally representative crosssection data. Te rest of te paper is structured as follows. Section II provides a brief overview of te current state of Banglades economy along wit te poverty situations and discourses. Section III outlines te details of te metodology, including te one to decompose poverty and vulnerability. Section IV gives a brief description about te data. Te econometric and oter relevant results are presented in Section V. Section VI concludes te study igligting some of te policy issues for reducing poverty and vulnerability to poverty in Banglades. II. Poverty and Vulnerability in Banglades Banglades as long been seen as te arcetypal teatre of poverty. Altoug te istory of poverty in te region goes back to te Britis colonial period (Siddiqui, 1982), te actual surge of interests on poverty among academics and researcers began after te independence of te country in 1971 especially against te backdrop of painful and devastating famine of 1974 and te following decades saw a stream of studies generating te uge literature on poverty issues of Banglades. Most of te studies during te 1970s and 80s were ex post static analysis and focused mainly on counting te poor. However, te statistics on poverty are generally problematic due mainly to te quality of te data and te use of multiple sources in estimating poverty. Te later alf of te 1990s witnessed a sift from static to dynamic analysis of ASARC WP 2009/02 4

6 Md. Safiul Azam & Katsusi S. Imai Vulnerability and Poverty in Banglades poverty. A number of studies investigating te dynamic aspects of poverty in Banglades are available now and notable contributions are made by Raman (1996) and Sen (2003). Below is presented a summary of poverty trends and poverty dynamics in Banglades. Table 1: Poverty Trends in Banglades 1983 to 2005 Year National Urban Rural Poverty Gap Squared Poverty Gap 1983/ / / / Source: Sen 2003 and te figure for 2005 is taken from Banglades Bureau of statistics 2005 Tere is little agreement between researcers and academics about te poverty figures over time due mainly to different metods and multiple sources of data used in estimating poverty during te 1970s and 1980s. Te official figure for te estimated level of poverty of te country immediately after independence stood as ig as 82.9 per cent in Te later alf of te 1970s marked te beginning of a rapid decline of poverty followed by a iatus during te 1980s, poverty continued to decline during te 90s and te pace of reduction got even faster during te fast alf of te 2000s as can be seen in Table 1. Poverty as declined from over 80 per cent in te early 1970s to around 40 per cent in People living below te poverty line ave declined almost 1.5 percentage point a year since 1990s wic is quite impressive. More importantly, analysis based on te distributionally sensitive poverty measures indicates tat tere as been a substantial improvement in te living standards of te poorer section of te population during te period as revealed by a greater decline in te dept and severity of poverty in rural areas tan in te urban areas. 2 Overtime comparability of poverty estimates are difficult due mainly to canges in te metodology of data collection and poverty estimation. It is convenient to consider te period between 1995/ wen te Houseold Income and Expenditure Survey (HIES) began to use consistent data collection and poverty estimation metodologies. For details around tese issues please see Amed (2000). ASARC WP 2009/02 5

7 Md. Safiul Azam & Katsusi S. Imai Vulnerability and Poverty in Banglades Noneteless, te impressive poverty reduction record is a little comfort as te callenges aead are quite enormous. First, poverty still remains at a very ig level and te number of people living below poverty line remains almost te same as it was in (about 60million). Te most startling consequence of widespread poverty is tat a quarter of te country s population -36 million people cannot afford an adequate diet, according to te 2005 estimates of food poverty or extreme poverty (BBS, 2006). Cronically underfed and igly vulnerable, tey remain largely witout assets (oter tan teir own labour power) to cusion lean-season unger or te crusing blows of illness, flooding, and oter calamities (Quisumbing, 2007). Second, faster poverty reduction during te 1990s was also accompanied by rising inequality measured by private consumption expenditure distribution wic is a major concern for policy makers. During te period , te level of consumption inequality increased from 31.9 to 37.9 per cent in urban areas and from 25.5 to 29.7 per cent in rural areas. Rising inequality as te potential to dampen te pace of economic growt as well as te poverty reduction outcomes (Sen, 2003). Tird, tere are significant regional variations of poverty. Poverty is more pronounced in some areas and regions of te country, wic suffer from flooding, river erosion, mono cropping and similar disadvantages. Poverty is igest in te western region of te country (Rajsai Division) followed by Kulna and Cittagong. Finally, wile tese static point-in-time poverty estimates are useful to ave a snapsot of poverty situation, tey are not muc useful to explain te gross movement of ouseolds in and out of poverty. Empirical evidence suggests tat te gross movements in and out of poverty are muc larger tan te net aggregate poverty outcomes indicated by static estimates. To ave a proper grip on policy perspectives, it is necessary to understand te underlying dynamism tat propels ouseolds in and out of poverty. Tere are a number of studies (e.g. Raman, 1996, 2002; Sen 1996, 2003) tat incorporate te notion of risks and vulnerability in understanding te dynamics of poverty particularly in rural areas of Banglades. Te panel study of 62 villages by ASARC WP 2009/02 6

8 Md. Safiul Azam & Katsusi S. Imai Vulnerability and Poverty in Banglades BIDS (Banglades Institute of Development Studies) and Power and Participation Researc Centre (PPRC) was one of te earliest of tis nature. It as been found tat te poor are not just a simple omogenous population tat can be neatly categorized into one or two groups. Tere are considerable variations and mobility among te poor. Apart from te limited asset base and adverse socio-political environment, te poor and te vulnerable are subject to periodic socks suc as natural disasters, illness and insecurity wic often result in fluctuating economic fortunes. Tere are also factors tat elp tem move out of poverty. Using a two period panel (1987/88 and 2000) consisting of 379 ouseolds from 21 villages, Sen (2003) as made similar attempts to explore te dynamics of poverty in rural areas. He adopts te rural liveliood framework coined by Ellis (2000) to analyse (te lack of) mobility of ouseolds in and out of poverty and identifies four groups: i) te always poor wo remained poor in bot periods and constitutes 31 per cent of te sampled ouseolds; ii) te never poor wo stayed out of poverty in bot te periods wit te sare of 25 per cent; iii) te ascending ouseolds, te ones wo escaped from poverty and represents 26 per cent of te ouseolds; and iv) te descending ouseolds wo descended from te non-poor into poverty wit te sare of 18 per cent. Te difference between te sare of te ascending and te descending ouseolds, 8 per cent is te net cange in poverty during tis period. Te study again confirms tat te mobility among te poor and vulnerable is far greater tan wat we observe net aggregate poverty canges at national level. More recently, Quisumbing (2007) reports similar movements of ouseolds in and out of poverty. All tese studies, owever, are based on te ex post analysis. Te present study attempts to complement te earlier studies by using te measures of ex ante analysis of poverty. III. Metodology In tis section we delineate te detailed estimation procedure of te analysis of vulnerability to poverty in Banglades. First, using record level ouseold data, FGT measures of ead-count poverty (Foster et al, 1984) will be calculated. Ten ouseold s expected consumption will be calculated using Feasible Generalized Least Square (FGLS) estimation procedure. Te expected consumption ten will be used to estimate ouseold s vulnerability to poverty. ASARC WP 2009/02 7

9 Md. Safiul Azam & Katsusi S. Imai Vulnerability and Poverty in Banglades (1) Measuring Vulnerability Te principal aim of a forward looking vulnerability to poverty estimation is to ave an estimate of ouseold s over time mean and variance of consumption expenditures. Ideally, tis requires panel data collected over a sufficiently long period. However, as noted by Jalan and Ravallion (2001), most of te available standard data sources are based on a single visit (cross section) ouseold survey and cannot be used for tis purpose. In tis study, we use te vulnerability to poverty measure proposed by Cauduri (2003), Cauduri et al. (2002) and Suryaadi and Sumarto (2003) developed particularly for cross-section data. Vulnerability in tis context is defined as expected poverty, or in oter words as te probability tat a ouseold s consumption will lie below te predetermined poverty line in te near future. Following Cauduri (2003), for a given ouseold, te vulnerability is defined as te probability of its consumption being below poverty line at time t+1: V ( ln c ln c) t = Pr, t+ 1 < were V t is vulnerability of ouseold at time t, c, t+ 1 denote te consumption of ouseold at time t+1 and c stands for te poverty line of ouseold consumption. Assuming tat for ouseold te data generation process for consumption is captured by te following equation: were ln c = β + ε (1) X c stands for per capita consumption expenditure for ouseold, represents a vector of observable ouseold caracteristics (containing bot idiosyncratic and community elements), β is a vector of parameters, and ε is a mean-zero disturbance term tat captures ouseold s idiosyncratic factors (socks) contributing to differential level of per capita consumption for ouseolds tat sare te same caracteristics. Consumption expenditures, c is assumed to be log-normally distributed and as suc te disturbance term, ε will be distributed normally. Te vulnerability to poverty of ouseold, wit caracteristics coefficient estimates of te equation (1) in te following manner: X X can now be calculated using te ASARC WP 2009/02 8

10 Md. Safiul Azam & Katsusi S. Imai Vulnerability and Poverty in Banglades ^ V ln c X = Pr(ln c < ln c X ) = Φ σ β (2) were V denotes vulnerability to poverty, tat is te probability tat te per capita consumption level ( c ) will be lower tan te poverty line ( c ) conditional on ouseold caracteristics X. Meanwile, Φ (.) denotes te cumulative density of te standard normal distribution and σ is te standard error of te equation (1). Houseolds future consumption is furter assumed to be dependent upon uncertainty about some idiosyncratic and community caracteristics. To ave consistent estimate of parameters, it is necessary to allow eteroskedasticity, tat is, variances of te disturbance term to vary. Tis can take te following functional form: i j σ 2, = Z θ = X X θ + η (3) e i j i ij A tree-step Feasible Generalised Least Squares (FGLS) procedure can be used to estimate te parameter,θ. Equation (1) is first estimated using an ordinary least squares (OLS) procedure. Ten, te estimated residuals from te equation (1) are used to estimate te following equation, again by OLS: 2 e OLS i j, = Z θ + η = X X θ + η (4) i j i Te estimate from above is ten used to transform te equation (4) into te following: ij 2 Z e OLS, θ OLS Z = Z θ OLS η θ + Z θ OLS (5) Tis transformed equation is estimated using OLS to obtain an asymptotically efficient FGLS estimate, θ FGLS. Z 2 θ FGLS is a consistent estimate ofσ, wic is te variance of te idiosyncratic component of ouseold consumption. Tis is ten used to transform te equation (1) into: e, Z ln c θ FGLS = Z X θ FGLS β + Z e θ FGLS (6) ASARC WP 2009/02 9

11 Md. Safiul Azam & Katsusi S. Imai Vulnerability and Poverty in Banglades OLS estimation of te equation (6) yields a consistent and asymptotically efficient estimate of β. Te standard error of te estimated coefficient, β FGLS, can be obtained by dividing te reported standard error by te standard error of te regression. Finally, te estimates of β and θ obtained troug tis FGLS metod can be used to estimate te vulnerability to poverty of ouseold troug te following generalisation of te equation (2): V = Φ ln c X i j X X i j i β θ ij (7) Clearly, estimation of vulnerability to poverty depends on te following elements: te distributional assumption of normality of log consumption, te coice of poverty line c, te expected level of log consumption and te expected variability of log consumption. Te iger te level of expected consumption and expected consumption variability te lower is te vulnerability. As noted earlier, a merit of tis vulnerability measure is tat it can be estimated wit cross section data. However, te measure correctly reflects a ouseolds vulnerability only if te distribution of consumption across ouseolds, given te ouseold caracteristics at time t represents time-series variation of ouseold consumption. Hence tis measure requires a large sample in wic some ouseolds experience good times and oters suffer from some kind of negative socks. Also te measure is unlikely to reflect large unexpected socks, if we use te cross-section data for a normal year. (2) Determinants of vulnerability It is evident from te literature and te empirical studies tat vulnerability is a closely related but distinct concept from poverty on a number of counts. First vulnerability is a dynamic concept as opposed to poverty wic is essentially a stock concept. Te model below is used to examine te determinants of vulnerability to poverty in Banglades. Tis is implemented using te following regression model: V^ t = X ψ + μ (8) ASARC WP 2009/02 10

12 Md. Safiul Azam & Katsusi S. Imai Vulnerability and Poverty in Banglades Were V^ t is te estimated vulnerability by (7), X is te vector of ouseold idiosyncratic caracteristics, ψ is vector of coefficients and μ te error term. (3) Decomposing Poverty and Vulnerability Te objectives of te present study include creating ouseold s current poverty and vulnerability to poverty profiles and tereby figuring out prospective course of poverty in Banglades. In doing so, ouseolds will be disaggregated first by location namely -urban and rural and ten by various ouseold caracteristics tat distinguises between groups, for example- size of land olding in rural areas and educational level of te ead of te ouseold in urban area. Head Count Poverty index is calculated using te poverty lines suggested by Banglades Bureau of Statistics (BBS). BBS used two poverty lines for its poverty estimates. One is called te lower poverty line wic is equal to only te food poverty line 3 and ouseolds wose total expenditures are equal to te food poverty line are called te extreme poor. Te oter one is te upper poverty line wic is equal to food plus non-food poverty line 4 and te corresponding ouseolds are termed as moderate poor ouseolds. Tese two poverty lines -lower and upper- are available for te entire 16 stratum of te HIES However, in tis study we ave used only te upper poverty lines for te entire 16 stratum as it includes bot te food consumption expenditures and te cost of non-food items. People living below te upper poverty line are generally considered as poor. Wereas lower poverty line only considers te food consumption expenditure and te people living below te lower poverty line is categorized as extreme poor. Any operationally useful assessment of ouseolds vulnerability status depends essentially on two important factors: first, te coice of a vulnerability tresold, tat is, a minimum level of vulnerability above wic all ouseolds are defined to be vulnerable and second, specifying te time orizon over wic ouseolds vulnerability is to be assessed. Tere is, owever, a certain degree of arbitrariness involved in making suc decisions. 3 Food poverty line is defined as te cost of acquiring a food basket containing te nutritional requirement of 2122 k.cal. per person per day. 4 A non-food poverty line is calculated by estimating te cost of consuming non-food goods by te ouseolds close to food poverty line. ASARC WP 2009/02 11

13 Md. Safiul Azam & Katsusi S. Imai Vulnerability and Poverty in Banglades Te most preferred and natural candidate for te vulnerability tresold is 0.5. Tis midway dividing point as tree attractive features (Suryaadi and Sumarto, 2003). Firstly, tis is te point in te equation (7) were te expected log consumption coincides wit te log of te poverty line. Secondly, it makes intuitive sense to say a ouseold is vulnerable if it faces a 50 per cent or iger probability of falling into poverty in te near future. Tirdly, if a ouseold is just at te poverty line and faces a mean zero sock, ten tis ouseold as a one period aead vulnerability of 0.5. Tis implies tat, in te limit, as te time orizon goes to zero, ten being currently in poverty and being currently vulnerable to poverty coincide (Pritcett et al., 2000). Anoter tresold tat makes sense is te observed eadcount ratio. Te underlying logic is tat because te observed poverty rate represents te mean vulnerability level in te population, anyone wose vulnerability level lies above tis tresold faces a risk of poverty tat is greater tan te average risk in te population and ence can be legitimately included among te vulnerable Cauduri (2003, P11). In practice, owever, most of te empirical studies adopted te vulnerability tresold of 0.5. Te oter but not less important aspect of an operationally useful vulnerability index is to decide on a time orizon over wic ouseolds vulnerability is to be assessed. Te existing literature again is of little elp in tis regard. In most of te cases time orizon is defined troug some arbitrary expression like probability of falling into poverty in te near future providing indication tat tere is no obvious coice. Recognizing tat certain degree of arbitrariness is needed, Cauduri (2003) proposed two possible cases -a time orizon of one year, wic can be tougt of in terms of te likeliood of poverty in te sort run, and a time orizon of tree years wic rougly corresponds to te likeliood of poverty in te medium-term. In te later case all ouseolds experience poverty spell at least once in te next tree years are categorised as vulnerable. Wit a vulnerability tresold V = 0. 5 indicting te probability of falling into n poverty at least once in te next n years, te probability of falling into poverty in te subsequent years, i.e., one, two or tree years can be calculated using te following equation: * V = 1 n 1 V n ASARC WP 2009/02 12

14 Md. Safiul Azam & Katsusi S. Imai Vulnerability and Poverty in Banglades Table 2 sows te different vulnerability tresold for tree different years. Table 2: Te Relationsip of Time Horizon and Vulnerability Tresold Time orizon Vulnerability tresold Vn=0.50 One year Two year Tree year Once decisions about vulnerability tresold and time orizon are taken, using a combination of ouseold poverty and vulnerability to poverty status based on current consumption, te estimated degree of vulnerability to poverty, and te estimated expected consumption, ouseolds can now be grouped into several poverty and vulnerability categories as in Table 3 5. Table 3 Poverty and Vulnerability Categories Current Consumption (c) Vulnerability to poverty v 0.5 c < c c c A D E [ c] v < 0.5 C F B E E [ c] < c c Expected consumption (E[c]) Poor = A + B + C Cronic Poor = A Transient Poor = B + C Non-poor = D + E + F Hig Vulnerability Non-poor = D + E Low Vulnerability Non-poor = F Hig Vulnerability Group = A + B + D + E Low Level of Consumption = A + D Hig Variability of Consumption = B + E Low Vulnerability Group = C + F Total Vulnerable Group = A + B + C + D + E Here, c is te poverty line consumption. 5 Te categorization of poverty and vulnerability to poverty of ouseolds is based on Suryaadi and Sumarto (2003). ASARC WP 2009/02 13

15 Md. Safiul Azam & Katsusi S. Imai Vulnerability and Poverty in Banglades Te above categorization process tus would result in a number of overlapping groups of ouseolds. First, te population is divided into two distinct groups using te poverty line consumption tresold: te poor and te non-poor. Tose wo ave average consumption equal to or below te poverty lines are generally termed as te poor and te rest is non-poor. Te poor ten are decomposed into two distinct groups: te cronic poor and te transient poor. Te cronic poor are te ones wo are currently poor and also ave expected consumption levels below te poverty line. Tese ouseold are most likely to remain poor in future. Te transient poor, on te oter and, are tose wo are also currently poor but teir expected consumption levels are above te poverty line. Some of te transient poor ave low vulnerability, but some of tem ave ig vulnerability. As a result of tis process, a total of five groups of ouseolds will emerge: te poor, te non-poor, te ig vulnerability group, te low vulnerability group, and te total vulnerable group. As can be seen from te taxonomy above, te caracteristic feature of te ig vulnerable ouseold group are low level of expected consumption and ig variability of consumption. Similarly, te non-poor can also be partitioned into two separate groups te vulnerable non-poor and te non-vulnerable non-poor depending on teir degree of vulnerability, expected level of consumption and te initial poverty status. Te constituents of te total vulnerable group are ten te ouseolds associated wit ig vulnerability group and tose are currently poor. Tis kind of categorization is important from bot teoretical and practical point of views. First, it supports te idea tat te poor and te vulnerable are not te same tey are distinct groups even toug tey may not be mutually exclusive. Te total vulnerable group tus includes all tose wo are currently poor plus tose people wo are currently non-poor but wo ave a relatively strong cance of falling into poverty in te near future. As Suryardi and Sumarto (2003, p.7) noted: wile vulnerability to poverty is defined as te risk or probability of falling below te poverty line, te definition of te total vulnerability group is based on bot tis risk as well as initial poverty status. Tis is to categorize a ouseold as vulnerable it is necessary to combine te probability of bad outcomes as well as some measure of teir badness according to a given social welfare function. ASARC WP 2009/02 14

16 Md. Safiul Azam & Katsusi S. Imai Vulnerability and Poverty in Banglades Tere are obvious advantages in furter disaggregation of poverty categories as in Table 3, rater tan simply dividing ouseolds into te poor and te non-poor. Tis disaggregation clearly demonstrates tat te poor and te vulnerable are eterogeneous rater tan static omogenous groups. It will facilitate advocacy, allow monitoring of progress in reducing vulnerability. In addition, eac one of tese groups is likely to respond differently to particular policies aimed at reducing poverty and vulnerability and as suc, it migt be necessary to devise different policies for different groups (Jalan and Ravallion, 2000). IV. Data For measuring poverty and vulnerability and investigating te relationsip between te two, detailed information are required on caracteristics of ouseolds suc as ouseold size, demograpics and resource endowments, and teir income and consumption expenditure. Net income refers to te ouseold s income in cas and in kind after deducting all costs and taxes. Consumption expenditure is te expenditure on food and non-food items suc as cloting, ousing, ealt, education, transport and communication, recreation and entertainment. Tis study uses te Houseold Income and Expenditure Survey (HIES)-2005 collected by te Banglades Bureau of Statistics (BBS). It was conducted during January 2005 to December Tere are 10 different modules containing a wide range of individual and ouseold level information. It as specific modules for general ouseold caracteristics as well as modules on ealt, education, activities, employment and labour force participation, assets and income, prices, consumption expenditures of all kinds, social safety net programmes etc. HIES-2005 is a nationally representative ouseold survey, covering all areas of te country. A total of 10,080 ouseold were interviewed of wic 6,400 is rural and te rest 3,680 is urban. A two stage stratified random sampling tecnique was followed in drawing sample for HIES 2005 under te framework of Integrated Multipurpose Sample (IMPS) design developed on te basis of Population and Housing Census Tere are 320 rural and 184 urban PSUs in te sample. HIES-2005 collected some selected community/village level information as well. However, community information was collected only from te rural areas. Te community information includes principal economic activities of te village, pysical ASARC WP 2009/02 15

17 Md. Safiul Azam & Katsusi S. Imai Vulnerability and Poverty in Banglades and oter social infrastructure, availability of oter facilities like marketing, banks, and te information on impact of natural disasters. V. Econometric Results Te results of te regression equation are given in Table 4. It sows te regression results for te equation (7) wereby log of per capita consumption in 2005 is estimated by ouseold idiosyncratic caracteristics and oter determinants. Te summary statistics of variables included in te model are given in te Appendix. Te variables size of te ouseolds, age of ead of te ouseolds and te size of land olding by ouseolds along wit teir squares are included in te model because of te possible non-linearity of te relationsip between log consumption per capita and tese variables. Oter variables reflecting ouseold s idiosyncratic caracteristics are dependency ratio, ygienic conditions, weter a ouseold as electricity, telepone connection or not, and weter ouseolds do participate in social safety net programmes or not. Houseold s ygienic condition is defined as bad if a ouseold does not ave sanitary latrine and safe drinking water. Oter important inclusions are ousing condition, educational level acieved by te ead of te ouseold, activity status of te ead of te ouseold, and weter ead of te ouseold suffered any cronic or serious illness over te past twelve monts. Wile te variables oter tan te ousing condition seem to be natural candidates for inclusion in te regression (Suryaadi and Sumarto, 2003), ousing condition defined by te type of te construction materials used in building ouses, is included in te model as tis is tougt to be a major and quite regular source of socks for Bangladesi ouseolds. Even wit moderate rainfall and normal flooding conditions, wic is fairly common in Banglades, ouseolds particularly in rural areas need to spend significant amount of resources for repair and reconstruction of teir ouses. So ouses constructed by mud brick, emp/ay/bamboo are considered to be poor wile brick/tiles/ C. I. seet/wood ouses are considered to be good ouses. Activity of te ead of te ouseold is categorized into tree categories: ouseold ead wit no activity meaning eiter tey are retired or unemployed, ouseold-eads engaged in agricultural activities, and ouseold eads working in non-agricultural sector. Similarly, ouseolds are categorized into four distinct groups in accordance wit te educational level acieved by te ead of te ouseolds as can be seen in te Appendix. ASARC WP 2009/02 16

18 Md. Safiul Azam & Katsusi S. Imai Vulnerability and Poverty in Banglades Table 4: Estimates of Expected log Consumption Variable labels Age of ead of ouseolds Age-square of ead of ouseold Size of ouseold Size-square of ouseold Total land olding of ouseold Square of total land olding Dependency ratio in te ouseold Dummy of gender of ead of ouseold Dummy of participating in safety net programme Dummy of illness of ead of ouseold Dummy of aving electricity connection Dummy of aving telepone line Dummy of ygienic condition Dummy of ousing condition Dummy of ead of ouseold agricultural activity Dummy of ead of ouseold non-agricultural activity Dummy of up to secondary education Dummy of up to iger secondary education Dummy of tertiary or iger education Dummy of Barisal region Dummy of Cittagoan region Dummy of Daka region Dummy of Kulna region Dummy of Rajsai reg Constant Log consumption Coefficients (robust t statistic).017 (10.41) (-9.22) ( ).005 (10.16).098 (20.85) (-7.56) (-15.76) (1.02).091 (8.78) (-3.34).172 ( 20.37).415 (26.99).110 (13.09).105 (13.89) (-7.36) (-3.34).158 (19.86).298 (13.31).450 (21.08) (-12.36) (-1.33).114 (-7.17) (-19.24) (-20.57) 6.63 (153.99) Vulnerability Coefficients (robust t statistics) (-14.26).000 (11.86).142 (26.86) -006 (-16.92) (-22.55).003 (9.71).406 (25.04).023 (2.03) (-9 76).022 (3.38) (-30.22) (-2.15) (-16.03) (-25.32).096 (8.24).049 (4.62) (-32.64) (-14.71) (-15.01).344 (20.61).079 (5.43).109 (7.74).224 (14.81).252 (17.69).453 (13.16) ASARC WP 2009/02 17

19 Md. Safiul Azam & Katsusi S. Imai Vulnerability and Poverty in Banglades Te non-linearity is confirmed in te relationsip between log consumption per capita and te size of te ouseold, age of ouseold ead, and size of total land olding and teir squared terms as teir coefficient estimates are statistically significant. Te coefficient for age of ouseold ead is positive and igly significant. Its square is ten negative and statistically significant. Similarly, size of te total land olding seems to affect consumption positively as expected but its square is negative and igly significant. As expected, te size of ouseold as a negative influence on consumption, tat is, te larger te ouseolds te lower tends to be te per capita consumption. Its square again is of opposite sign indicating te non-linearity of relationsip wit log of consumption per capita. Not surprisingly, te variables- ousing condition, electricity connection, telepone connection, and ygienic condition all ave sizeable positive effect on per capita consumption and te coefficients are also igly statistically significant. Compared to te base category illiterate ead of ouseold, te rest of dummies on education are found to affect consumption per capita positively. Te relevant coefficients are all statistically significant as well. Tis basically conforms to oter studies concluding tat literacy and education attainment decrease poverty (e.g. World Bank, 2002). Te coefficient for dependency ratio is negative and statistically significant indicating tat ouseolds wit larger number of younger people tend to ave lower level of per capita consumption. Te relatively larger coefficient for nonagricultural activity dummy indicates tat te non-agricultural activity is more rewarding tan agricultural activities in terms of per capita consumption. Table 5 provides estimates for national level poverty and vulnerability to poverty categories. Te decomposition of poverty and vulnerability to poverty sows tat total vulnerability to poverty at national level is muc iger tan te point-in-time estimates of poverty, wic signifies te importance of forward looking poverty analysis. Arguably, tis indicates tat te current poverty estimates migt be underestimated. Te transient poor is estimated to be per cent as opposed to te 9.25 per cent ig vulnerable non-poor group people wo are currently non-poor but ave te potential to become poor some time in future. Te ig percentage (i.e., 23.55) of cronic poor wic is also referred to as structural poverty is in line wit BBS s official estimates for extreme poverty rate of around 25 per cent in Low level of endowments, poor economic infrastructure, and limited opportunities for ASARC WP 2009/02 18

20 Md. Safiul Azam & Katsusi S. Imai Vulnerability and Poverty in Banglades employment among oters migt explain te prevalence of suc uge numbers of cronic poor. Table5: Poverty and Vulnerability to Poverty Categories, 2005 Poverty and Vulnerability Category (%) Poor: A Cronic poor (CP) B +C Transient Poor (TP) A+B+C Total poor D+E Hig Vulnerable Non-poor (HVNP) 9.25 A +B+C+D+E Total Vulnerability to Poverty (TVP) Table 6 sows te distribution of population by poverty and vulnerability to poverty categories diaggregated by location namely, urban and rural in Te poverty figures for rural areas indicate tat despite increasing efforts for poverty reduction over te years, poverty remains a pervasive factor in rural Banglades. Around per cent rural population stays below te poverty line wile per cent of tem probably will remain tere for a few more years to come. About 16 per cent of te rural ouseolds are identified as transient poor some of wom may escape poverty in future wile per cent rural non-poor are living under te treat of becoming poor in future. Te urban area recorded more impressive poverty reduction in recent years tan te rural areas as revealed by te corresponding figures in te above table. However, te proportion of transient poor in urban areas as compared wit te cronic poor is iger tan wat it is for rural areas. Te ig vulnerable non-poor group in urban area represents a sizeable proportion of urban population as well. Almost per cent of te urban population is involved in movement in and out of poverty indicating tat urban poverty migt sot up if appropriate risk mitigating policies along wit usual poverty reduction strategies are not in place. Table 6: Poverty and Vulnerability Categories by Location Poverty and Vulnerability Categories Urban Rural Poor: A Cronic poor B +C Transient Poor A+B+C Total poor D+E Hig Vulnerable Non-poor A +B+C+D+E Total Vulnerability to Poverty ASARC WP 2009/02 19

21 Md. Safiul Azam & Katsusi S. Imai Vulnerability and Poverty in Banglades As sown in Table 7, tere is a considerable variation in te poverty and vulnerability to poverty rates among te six administrative divisions of te country. Te poverty rate is te igest in te soutern and nortern part of te country wile te central part as te lowest poverty rate. In Barisal Division poverty is as ig as per cent and te total vulnerability figure is above sixty per cent. Looking at te composition of poverty and vulnerability to poverty categories, variation in rates are quite discernible. Wile cronic poverty is igest in Barisal closely followed by Cittagaon Division, Kulna as te lowest rate of cronic poverty followed by Daka Division. Noneteless, Kulna sares te igest rate of transient poverty. Cittagaon and Sylet Division ave te igest sare of ig vulnerable-non-poor population. All tese figures again justify te forward looking poverty analysis as it unveils different dimensions of poverty prevalence enabling policy makers to ave a deeper understanding of poverty dynamics in te country. Table 7: Poverty and Vulnerability Category by Administrative Divisions and by Houseold Caracteristics Name of Division CP TP Total Poor HVNP Total VP Barisal Cittagoan Daka Kulna Rajsai Sylet Illiterate ead of ouseold Head of ouseold aving up to secondary education Head of ouseold aving iger secondary education Head of ouseold aving tertiary level or iger education No activity ead of Houseolds Agricultural Non-agricultural ASARC WP 2009/02 20

22 Md. Safiul Azam & Katsusi S. Imai Vulnerability and Poverty in Banglades Tere is virtually no disagreement among economists on te prominent role of education in poverty reduction. Education can affect people s standard of living troug a number of cannels: it elps skill formation resulting in iger marginal productivity of labour tat eventually enables people to engage in more remunerative jobs. Hence it is expected tat education is positively correlated wit consumption levels of ouseolds, tat is, te iger te level of education, te iger te ouseolds tend to consume and te lower te level of poverty. Te regression result reported earlier also confirms tis for Banglades. Te distribution of ouseolds belonging to different categories differentiated by te level of education acieved by te ead of ouseolds across different poverty and vulnerability to poverty groups sows tat poverty is most concentrated in ouseolds eaded by people wo do not ave any formal education. Tey are also te most vulnerable in terms of estimated total vulnerability to poverty wic is over 60.0 per cent. Poverty and vulnerability get lower and lower as te level of education of ouseold eads get iger and iger. According to tis estimate among people wo ave tertiary or more education, cronic poverty is totally absent and tis group of people ave better coping abilities against future odds as revealed by te absence of future treat of becoming poor. A meagre 4.24 per cent of igly educated people are transient poor. Te incidence of poverty and vulnerability to poverty across broad sectors: agricultural and non-agricultural. Tere seems to be a group of ouseolds wit ead of ouseold belonging to neiter of te above groups. Tese are probably te ouseold were ead of te ouseold eiter retired from jobs or ouseolds eaded by ousewives receiving remittances and not involved in any economic activity. Poverty is less prevalent in tis group wile ouseolds wit ead of ouseolds working in agriculture sare te majority of poor. Cronic poverty in ouseolds wit eads working in agriculture is widespread. Te ig vulnerable non-poor population also constitutes a significant proportion of tese ouseolds. On te oter and, nonagricultural activities are seen to be more remunerative in terms of reducing poverty as is te case wit most oter developing countries. Noneteless, more tan 35 per cent of non-agricultural ouseolds are cronically poor wile almost 9 per cent of te non-poor non-agricultural ouseold are at risk of poverty. ASARC WP 2009/02 21

23 Md. Safiul Azam & Katsusi S. Imai Vulnerability and Poverty in Banglades VI. Concluding Observations As as been te case for many oter similar studies, particularly for Indonesia, and Cina, vulnerable population in Banglades is also found to be significantly larger tan te number of currently poor. Total vulnerability is found to be as opposed to te current poverty of around 39 per cent. Vulnerability in rural areas is even iger wic is estimated to be per cent. Te categorization of poverty into transient and cronic poverty is even more insigtful. Regional dimension of poverty and vulnerability to poverty clearly sows te justification for tis kind of analysis and certainly calls for differential treatment of poverty reduction efforts in different administrative regions. Vulnerability in coastal division, i.e., Cittagoan Division is almost double to tat of Daka and almost 4 times iger tan Kulna Division. Education is found to be a key element in reducing poverty. Poverty and vulnerability to poverty are te igest among ouseolds eaded by illiterate person; were as ouseolds eaded by person aving more tan iger secondary level education are significantly better poised to cope wit risk and uncertainty. So investment in uman capital along wit oter means of social protection and promotion could be instrumental for poverty reduction in Banglades. Agricultural ouseolds again are more vulnerable tan non-agricultural ouseolds, wic underscores te need for more protection of te agricultural community. Tere are reservations among economists about using a single cross-section to estimate standard deviation of consumption and to assume tat cross sectional variability proxies inter-temporal variation in consumption (e.g. Hoddinott and Quisumbing, 2003). Noneteless, te results of tis study provide meaningful insigts into poverty and vulnerability at ouseold levels in case were only cross-sectional data are available. A sizeable portion of ouseolds tat are now non-poor are certainly vulnerable to falling into poverty in future. Tis as policy implications and terefore suc results sould be taken into account, particularly wen policy makers design social policy. Ex ante measures sould be enanced to prevent as many ouseolds as possible from becoming poor, so sould be ex post measures to alleviate tose already in poverty. As noted earlier, te expansion of te concept of poverty does not alter te basic tenets of te usual poverty reduction strategies. Te significance of governance, uman capital and infrastructure as key drivers of growt, employment generation, and poverty reduction will remain. Te only issues tat it ASARC WP 2009/02 22