Anirudh Krishna


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Anirudh Krishna

Sanford Institute of Public Policy

Box 90245

Duke University

Durham, NC 27708 - 0245

(919) 613-7337 (Office)

(919) 960-4658 (Home)

(919) 681-8288 (Fax)


Poverty is inherently dynamic: large numbers of people are escaping from poverty at any given time, but large numbers are also falling into poverty simultaneously. Achieving faster poverty reduction requires speeding up the pace of escapes while concurrently slowing down the rate of descents into poverty. Studies undertaken over the past five years in India, Kenya, Peru and Uganda, considering 223 villages and over 25,000 households, show that escapes and descents are not symmetric in terms of reasons. While one set of reasons is related to escaping poverty, another set of reasons is associated with falling into poverty. Targeting both sets of reasons is required for reducing poverty faster; targeting people alone will not help. Descents into poverty cannot be controlled when resources are targeted toward those who are already poor. Even in terms of facilitating escapes from poverty, universalistic responses targeting reasons are better than those targeted toward specific individuals. Targeting reasons before targeting people will be critical for reducing poverty faster in the future. Since reasons for escape and descent are quite context-specific, more variegated responses will be required.

Keywords: poverty, targeting, health, Stages-of-Progress methodology

Word Count: 9,533
Author’s Acknowledgements
Adam Hosmer-Henner provided excellent research assistance. Christopher Barrett, Harry Blair, Thomas Carter, Alan Fowler, Ruth Meinzen-Dick, Mick Moore, Diwesh Sharan, Ole Therkildsen, and two anonymous reviewers commented on earlier drafts. The usual disclaimers apply.


Targeting is an important concern of international development assistance, and it is imperative that valuable resources are appropriately directed and effectively utilized. The central motivation for targeting is to improve the efficiency of poverty reduction programs. By disproportionately distributing program benefits to those who are actually poor, finer targeting theoretically allows for the same amount of poverty reduction with fewer resources. Targeting appeals to policymakers and economists because of this implicit efficiency and quantitative objectivity. Additionally, donors can evaluate grant requests, comparing the extent to which funds actually reach the poor.

However, the major focus so far has been whom to target and not so much on what to target, which is a mistake. When the objective of the aid effort is to reduce poverty sustainably, three steps need to be taken in order. First, actionable reasons for poverty must be identified. Second, programs must be devised that target these particular reasons. Third, efforts must be made to direct these programs toward the people who most need this support. The first and the second steps of this process have been mostly neglected so far1 – and the third and subsequent step has received the most attention. This paper is intended to help rectify this unfortunate imbalance.

Targeting reasons – for escaping poverty or for falling into poverty – must form a central part of the aid effort. As discussed below, targeting people is likely to be of little consequence unless reasons are simultaneously targeted through appropriate policy measures.

Targeting as presently practiced is based on the premise that there is a given stock of the poor who can be identified reasonably accurately and affordably. There are two parts to this premise: first, there is a conception, rather an image, of a fixed stock of the poor; second, there is the belief that this stock can be marked off using methods that are reliable and also cost-effective.

Both parts of the premise suffer from significant shortcomings. Identification has been neither reasonably accurate nor affordable. Programs that have employed some form of targeting have achieved very mixed results, as discussed in Section 2.

The first part of the premise, related to a fixed stock of poverty, is even more troublesome. Section 3 reviews evidence from recent studies which show that poverty is fundamentally dynamic: instead of a fixed stock of the poor there is a changing cast of characters. Large numbers of those who were poor previously have escaped out of poverty. Conversely, large numbers who are poor at the present time have newly fallen into poverty.2

Controlling the generation of new poverty is – or should be – an equally important objective of poverty reduction. It seems more fruitful to prevent the creation of poverty in the first instance than to provide assistance only after someone has fallen into poverty. However, targeting “the poor” tends to preclude this consideration. By focusing resources upon those who are already poor, it directs attention away from others who are falling into poverty.

Targeting can at best help resolve only one part of the problem: it can help direct resources toward those who are presently poor and – if beneficiary rolls are updated regularly, which seldom happens – it can also steer resources toward the newly impoverished, albeit after (and not before) they have fallen into poverty. However, what effect these resources will have by way of poverty reduction is not altogether clear. Even in terms of raising the existing poor out of poverty, targeting beneficiaries provides only one part of the solution. Unless pathways out of poverty have been reasonably well charted, i.e., unless it is known what factors will help to take poor people out of poverty in a particular context, and unless programs are designed that directly target these specific pathways, program resources may amount to no more than temporary relief. Their impact on poverty reduction can be muted and marginal.

Knowing and operating upon context-specific reasons for escape and descent is an essential prerequisite for successful poverty reduction. Section 4 reviews evidence showing how reasons for escape and descent are not just different from each other; both sets of reasons are also different in different contexts. Section 5 concludes with some recommendations for targeting in future.

Factors related to administrative cost, perverse incentive effects, and political viability have tended to bedevil the practice of targeting beneficiaries. Because information about the poor is imperfect and not costless to obtain, programs are never perfectly targeted in practice. Some of the deserving are unwittingly excluded while some of the non-poor are almost invariably included. Errors of inclusion and exclusion can be quite considerable, and reducing the extent of these errors can result in a huge and unacceptable burden of administrative, social and political costs (Baker and Grosh 1994; Cornia and Stewart 1995; Gaiha, Imai and Kaushik 2001; Ravallion and Datt 1995; van de Walle 1995).

Programs have generally targeted beneficiaries through four types of mechanisms: indicator targeting, geographical targeting, community-based targeting, and self-targeting. The choice of appropriate methods depends upon the quality of information available about the poor, the level of geographic heterogeneity, administrative costs, and political viability (Neto 2001).

Indicator targeting is a commonly used approach, and it encompasses a broad range of alternative methodologies. A verified means test is the most sought after technique, but lack of reliable information on incomes has prompted users to rely upon some other indicators, including age, acreage, asset holdings, education, employment, gender, and place of residence. The costs of assembling even these alternative bits of information reliably can overwhelm program administrators. Keeping this information current over successive years is a more forbidding task. Many beneficiaries remain on the rolls even after their earnings increase beyond the eligibility cut-off (Besley and Kanbur 1993). Incentives for cheating and corruption are especially likely in situations where incomes are variable, undocumented, and not directly verifiable – conditions that characterize the situations of most poor people.

Targeting programs through fixed indicators can also run up against political viability considerations. Because there are fewer stakeholders in a narrowly targeted program as opposed to a universal one, opposition to programs narrowly targeted to particular groups can overwhelm the political will for going forward with such a program (Gelbach and Pritchett 2002; Gutner, Gomaa and Nasser 1999). During episodes of recession, budget cuts are deepest in programs that are narrowly targeted toward a particular group (Ravallion 1999; 2004). An intention to target program benefits narrowly is quite often compromised, therefore, because of a need to muster broader political support for the program (Pritchett 2005). In such situations, “attempts to achieve ‘more for the poor’ through the use of indicator targeting may in fact mean less for the poor” as program budgets get squeezed (Gelbach and Pritchett 2002: 42).

The second method, geographical targeting, is more attractive when poverty in a country is concentrated within particular areas. This method is less useful in large parts of the world where high levels of income diversity exist within regions and even within communities (Bardhan and Mookherjee 1999; Coady and Harris 2001; Elbers et al. 2004; Nhate and Simler 2003). Poverty mapping based on small-area estimation can help improve coverage and reduce leakages by lowering the population of targeted units (Bigman and Srinivasan 2002; Elbers et al. 2003), but it can be very costly to implement.

Geographical targeting is more viable when the geography itself contributes to poverty and when migration is not a feasible option (Ravallion and Wodon 1999). And it can also be applied more effectively when ethnic, historical and location-based disadvantages overlap, as they do in some Latin American contexts (Schady 2002). Geographic targeting in such situations can help deal with large concentrations of the poor – but it does not help by itself to determine the reasons that cause the poverty of these people and other reasons that promote their escapes out of poverty. As discussed in the next section, any program based on targeting beneficiaries (or geographic regions) remains seriously incomplete when reasons for escape and descent are not simultaneously targeted.

The third set of targeting methods, community-based targeting, is based on the undeniable fact that there is richer and more accurate knowledge about poverty at the local level (Esman and Uphoff 1984; Uphoff et al. 1998). The danger is that this knowledge may not be appropriately utilized; in fact, inequality within a village may actually worsen if local elites capture processes of decision making and benefit allocation (Galasso and Ravallion 2002; Conning and Kevane 2002; Pender and Ruben 2004; Platteau and Abraham 2002). Inequalities in the exercise of power may never be entirely smoothed out, but they can be ameliorated if the investments choices are publicly justified on the basis of transparent analysis and do not remain purely an exercise of arbitrary power. I will discuss in the concluding section how a process of analysis and choice can be set in place within community groups, nested within a polycentric response directed toward reasons for escape and reasons for descent.

The fourth targeting method, self-targeting, is employed in programs that are open to all but which are designed in such a way as to be more appealing to poor people and less appealing to others. Usually, there is some sort of work requirement. In other cases involving food aid, certain types of cereals have been provided that poorer people will most likely consume because they lack other options, but which richer people will avoid.3

Self-targeting can assist the poor who are aware of such a program and who are physically able to complete the work requirement. However, considerable costs are entailed for those who participate by way of queuing, foregoing other income-earning opportunities, acquiring the required certification, etc. (Ravallion and Datt 1995). In addition, self-targeting can work poorly amid conditions of imperfectly working factor markets. As Barrett and Clay (2003: 176) conclude after reviewing evidence about self-targeting schemes from Ethiopia, “it may be hardest to reach the truly needy where the need is greatest.” Finally – and most important – if the cause (and not the manifestation) of poverty is not lack of food or lack of makeshift employment, self-targeted schemes may end up providing little more than temporary income infusions. They can help poor people survive another day or week or month – which is important – but which hardly suffices to help people make an escape out of poverty.4

Combinations of targeting methods have been found more accurate and useful in some circumstances, for instance, a combination of geographical and community-based targeting has been suggested, particularly for communities where poorer sections are better organized (UNDP 2000). On the whole, however, targeting has had very mixed results.5 While a few programs have successfully targeted groups in extreme poverty (Matin and Hulme 2003; Yunus 1997), evaluations of targeted programs have been generally quite unflattering.

A recent comprehensive analysis of targeted programs found that compared to untargeted or universal assistance targeting has not consistently worked better in terms of reaching the poor. While in the median targeted program the poor received 25 percent more resources than they would have received in an untargeted program, in another 25 percent of targeted programs these benefits were actually regressive, leaving the poor worse off than in universal programs (Coady, Grosh and Hoddinott 2004). No single method of targeting was universally best: targeting mechanisms that had high median scores also had higher variability in terms of their ability to reach the intended beneficiaries.

Other evaluations of targeted programs in developing and industrialized countries have concluded similarly, that their benefits are at best no more progressive than would be a uniform transfer to all citizens (Gelbach and Pritchett 2002). In addition, targeting can have quite perverse effects, including stigmatization of the intended beneficiaries.6

Targeting beneficiaries has been relatively more useful for relief programs and programs that act as social safety nets (Coady, Grosh and Hoddinott 2004) or which can help correct gender imbalances (Appleton and Collier 1995). But in most other cases it has not helped reduce the incidence of poverty. “Policies that attempt to identify the poor and target benefits to them can serve important redistributive and safety net roles… The risk is when targeted instruments are seen as the main instrument for poverty reduction” (van de Walle 1995: 606).

Far from being the main instrument, targeting beneficiaries constitutes at best only a part of the strategy for poverty reduction. Who to target is only one part of the puzzle; what to target is an essential, but relatively ignored, second part.

One possible explanation for this disparity in knowledge and practice has to do with the dominance of a macroeconomic view of poverty where growth is regarded as the engine of poverty reduction. With this mindset, social safety nets are put in place as a compassionate supplement to the destabilizations of macroeconomic policy; all that is necessary to smooth the economic transition. However, identifying and assisting the poor does little to reduce the vulnerability of the non-poor to shocks (Baulch and Hoddinott 2000; Carter and Barrett 2006).

Thus even in the best of targeting worlds, a critical constituency – those at the risk of falling into poverty – is neglected. Further, when the microeconomic reasons for escaping poverty are also ignored, what types of assistance to provide is also quite often based upon nothing more than hunches or hypotheses.


Poverty is not a static phenomenon; identifiable causes help regenerate poverty. Concentrating not just on who is poor at a given moment in time but on why they are poor can lead to better designed and in fact better “targeted” policies.

Table 1 presents illustrative results from a diverse selection of studies that have examined poverty in dynamic context. Considering different countries and different time periods, and employing different methods and even different definitions of poverty, these studies nevertheless arrived at a common conclusion: new poverty is being created even as some old poverty is destroyed. The stock of poverty is dynamic, changing significantly over time.

-- Table 1 about here --
The first row of this table shows that of a random sample of 379 households in two Bangladesh villages studied by Sen (2003), 26 percent of households escaped from poverty over the 13-year period, 1987 to 2000. These households formed part of the stock of poverty in 1987, but they were no longer poor in 2000. Movements in the reverse direction were also large: during the same 13-year period, another 18 percent of households fell into poverty.

Other studies also show that a falling tide operates alongside a rising tide in all parts of the world. Six percent of a sample of households in Egypt, studied by Haddad and Ahmed (2003), came out of poverty between 1997 and 1999, but another 14 percent fell into poverty. Fourteen percent of a random sample of rural Indian households escaped from poverty between 1970 and 1982, but another 13 percent of households fell into poverty during the same time period (Bhide and Mehta 2004). In 20 communities in Western Kenya, 18 percent of households came out of poverty over the past two decades, but another 19 percent fell into poverty concurrently. Net change in poverty in these Kenyan communities was minus one percent, but a total of 37 percent of households experienced a change in poverty status (Krishna et al. 2004).

A glacial pace of poverty reduction is simply a resultant of two offsetting trends. What is depleted by the flow of people out of poverty is concurrently replenished by a large inward flow.7

The first point to note in the context of targeting is that the set of beneficiaries changes considerably over time. Who is poor today is not the same as who was poor some years ago. Unless eligibility rolls are continuously updated, errors of exclusion will grow significantly over time. Updating these lists entails considerable expenses, however, and while adding new names may be politically rewarding, removing names from the eligibility roster can be politically costly and hard to accomplish. Out-dated and over-lengthy lists of beneficiaries are thus quite common to find.

The second and equally important point is that formerly non-poor people are falling into poverty in all contexts studied. Fresh poverty is being created constantly, but with some rare exceptions, discussed later, hardly any assistance is provided that can help households stave off poverty. For instance, Bhide and Mehta (2004) estimated that an additional 13 percent of all rural Indian households fell into poverty between 1970 and 1982. These households were not poor in the initial period, 1970, thus they were not eligible for receiving assistance from targeted programs. By 1982, these households had fallen into poverty. They were now eligible for assistance – but to get assisted, they first had to fall into poverty.

This is a critical failing of targeted programs: they do not help households and individuals deflect or avert poverty in the first place. They come into play only after a fall has been suffered. As a result, poverty creation has gone mostly unattended and unchecked.

An accumulating mass of studies show that large numbers of households fall into poverty – and it is not only borderline households who are affected by descents. Among 2,631 households in 36 Ugandan communities, a total of 325 households fell into poverty over the past ten years (Krishna et al. 2006a). As many as 24 percent of these newly impoverished households can no longer afford food and clothes, and another 29 percent have pulled their children out of school. Several formerly well-to-do households are included within this number. They have fallen so deeply into poverty that coming back out is a remote possibility. Fully one-quarter of all households that fell into poverty in 36 Andhra Pradesh villages were relatively rich 25 years ago: they owned cattle and jewelry in addition to land and a pukka (brick) house, but they are now reduced to working as day laborers on other people’s fields (Krishna 2006). The probability of becoming poor is larger for households that subsist closer to the poverty line, but the danger of falling into poverty is also clear and present for other, better-off households.

A poverty trap, corresponding to a low-level equilibrium, tends to ensnare freshly impoverished people (Carter and Barrett 2006). Many households that fall into poverty tend to remain poor for long periods of time. For instance, only one-third of households that fell into poverty in these Ugandan communities during the 15-year period, 1979-1994, were able to make an escape out of poverty over the next ten years. The remaining two-thirds of newly impoverished households continued to remain poor even ten years later. A similar story was repeated in 40 communities of Peru. Less than half of all households that fell into poverty over a 15-year period were able to climb out of poverty during the next ten years. The other half have been persistently poor for ten years and longer (Krishna et al. 2006b). In other contexts as well, many who fall into poverty tend to remain poor over long periods of time.

Falling into poverty is frequent, traumatic, frequently irreversible, and therefore serious enough to merit separate policy attention. Another look at Table 1 shows that the numbers in the last column are large in every case. In some cases, e.g., those examined by the Kenyan and South African studies, people who fell into poverty outnumber the people who escaped. Yet, most present-day targeting strategies do not help slow down the pace of new poverty creation. It is also far from obvious that these strategies have helped raise many poor people out of poverty.

How can a better targeted strategy be developed? Targeting reasons before targeting people is suggested below as the better way forward.


“Targeting is a means toward the end, which is poverty reduction” (Coady, Grosh and Hoddinott 2004:83). Reducing poverty through targeted efforts will be assisted by knowing the reasons that assist escapes out of poverty and other reasons that are responsible for descents into poverty. Once these reasons are better known, they can be addressed through suitable programs.

Studies show that escaping poverty and falling into poverty are not symmetric in terms of reasons. Poor people escape from poverty as a result of one set of reasons, but people fall into poverty on account of a different set of reasons. Targeting both sets of reasons simultaneously is necessary; the growth of the problem will have to be contained even as the size of the problem is reduced.

Two different sets of policies are required, therefore: one set to prevent people from falling into poverty, and another and parallel set of policies to promote escapes out of poverty.8 Both sets of policies need to be in force simultaneously. Those in danger of becoming poor will be assisted by the first set of policies, while those who are presently poor will be assisted by the second set. Knowing the separate reasons for escape and descent that operate within any given context will help fashion such a two-track approach.

Between 2001 and 2005, a series of studies were undertaken spanning 223 villages and 25,866 households in diverse areas of Kenya, Uganda, Peru and India, using the Stages-of-Progress methodology, which allows us to understand poverty dynamics from the perspective of the communities surveyed. The Stages-of-Progress method provides a useful methodological device, a benchmark or yardstick, for assessing how high up the ladder of material prosperity a particular household has climbed (or how far down it has descended) over some specific period of time. Compiling these trajectories of stability and change for all households within the communities studied helped us to assess the overall situation of poverty over time. More important, learning about the reasons for change in each individual case helped to identify chains of events associated, respectively, with escaping poverty and falling into poverty.

I review below, first, the reasons for descent that we observed in the different regions we studied. Next, I discuss reasons for escape. Finally, I examine how both sets of reasons vary – not just across countries but also across regions within countries, indicating that policy responses need to be variegated by context.

(a) Reasons for descent

Descents into poverty generally occur gradually and cumulatively and not from one moment to the next. No single reason is usually associated with falling into poverty; multiple linked factors propel most descents. Tackling these major factors can lead to large reductions in the incidence and probability of descent. Important factors of descent identified in each of the regions studied are presented in Table 2.

-- Table 2 about here --
In communities of Kenya, Uganda, India and Peru ill health and high healthcare costs constitute overwhelmingly the most important reason for households’ descents into poverty. Ill health and health-related expenses were associated with nearly 60 percent of all descents recorded in villages of Rajasthan, India, 74 percent of all descents examined in Andhra Pradesh, India, and as many as 88 percent of all descents studied in villages of Gujarat, India. In communities of Uganda and Peru that we studied, respectively, 71 percent and 67 percent of all descents were associated with ill-health and health-related expenses.

Not only does ill-health reduce the earning capacity of a household’s members; in the absence of affordable and easy-to-access healthcare facilities, it also adds considerably to the household’s burden of expenditure, thereby striking a double blow, which quite often results in tragedy. The resulting dependence of survivors, including orphans, upon other households contributed further to descent in many cases. Evidence from many other countries, including Cambodia, China, Ethiopia, Haiti, Kenya, Peru, Sierra Leone, Senegal, and Vietnam, points unambiguously to the deleterious effects of healthcare costs upon households’ welfare (Asfaw and von Braun 2004; Barrett et al. 2001; Deolalikar 2002; Fabricant et al. 1999, Farmer 1999; Krishna 2004; Krishna et al. 2006b; Strauss and Thomas 1998; Xu et al. 2003; Yao 2005). More than half of all personal bankruptcies in America are attributable to medical costs (Himmelstein et al. 2005).

Social and customary expenses on marriages and funerals constitute another set of factors often associated with descent. Funeral expenses were associated with a considerable proportion of descents in many but not all regions studied, including Kenya (64 percent of all descents), Rajasthan (34 percent), Gujarat (49 percent), Andhra Pradesh (28 percent), and Peru (11 percent). Marriage-related expenses were very important in all three states studied in India. They were also an important factor in communities of Peru, affecting younger couples in particular. Over a 25-year period ending in 2004, marriage expenses (together with expenses associated with setting up a new household) were associated with 29 percent of all cases of households falling into poverty.

Land-related factors, including crop disease, land exhaustion, drought and irrigation failure, were also associated with a significant number of descents. Particularly in some regions, these factors had considerable significance. In communities of Western and Central Uganda this set of factors was associated with 39 percent of all observed descents and in communities of Western Kenya with 38 percent of all descents.

Other reasons for descent included the loss of a job resulting from retrenchment, sacking or retirement. Drunkenness and laziness, sometimes thought to be important causes of poverty among the poor, were found to be relatively insignificant reasons. In all the communities investigated, these factors were associated with no more than five percent of all descents.9

High-interest private debt is highly prevalent as a factor contributing to descents in the three Indian states. Villagers deal with high healthcare expenses and expenses on marriages and deaths by taking out high-interest loans from private moneylenders. No institutional sources are usually tapped for such loans. Even in villages of Andhra Pradesh, where self-help groups and rotating savings and credit associations have spread rapidly in the last decade, hardly any villager has been able to avert descent through taking loans from such institutions. Private sources are most often drawn upon for such purposes, and private rates of interest – often as high as ten percent per month – are paid. The high burden of debt that results helps push households downward into poverty.10

Drought and irrigation failure constituted another important reason for descent. However, the effect of this factor, as of many other factors reviewed above, varies considerably across different parts of a region or state. These inter-regional differences are reviewed later in this section.

(b) Reasons for escape

Income diversification – through the cultivation of a new source of income – has been the most important pathway out of poverty in all areas studied (Table 3), as has also been found in other contexts (e.g., Eder 1999; Ellis 2000). Poor rural households have diversified their livelihood and income sources through two different types of strategies. On-farm strategies include pursuing new crops, new techniques, and new methods of livestock husbandry. Diversification into non-traditional export crops (e.g., vanilla and coffee) was quite important in both regions of Uganda. Cash crop diversification was also important in western Kenya and in the Cajamarca region of Peru. Off-farm strategies have included local petty trade, small businesses, and most important, casual or temporary employment within the informal sector in a city. Diversification of income sources was related to 70 percent of all escapes observed in communities of Rajasthan, India, 78 percent of those observed in communities of Western Kenya, 69 percent in Peru, and 54 percent in Uganda.
-- Table 3 about here --
Government and private sector jobs constituted the second most significant pathway out of poverty. This pathway was taken up by 15 percent of households escaping poverty in communities of Uganda and a smaller proportion of escaping households in communities of Peru.

In general, growth of private sector employment has not been the principal or even a very prominent reason for escaping poverty. Even in Gujarat, India, where economic growth rates have averaged eight to nine percent over many years, only about one-third of those who escaped from poverty could do so on account of acquiring a regular job in the private sector.

Another sobering lesson from these studies is that both government and non-governmental assistance and programs are not contributing substantially to households’ movements out of poverty. In all cases, less than 10 percent of escaping households’ pathways included any component of assistance from government or NGO programs. While such programs may have helped make the conditions of poverty more tolerable, few among them have actively assisted escapes out of poverty. Not targeting context-specific reasons for escape is an important reason for this unfortunate (and avoidable) result.

Irrigation and land improvement have been important reasons for escape in several other cases. Over one-quarter of all escaping households in communities studied within each of the three Indian states benefited from large-scale irrigation schemes or from small-scale irrigation activities on their lands.

One encouraging finding is that most children are going to school, many more than did a generation ago. Yet, education has hardly always amounted to an escape out of poverty. Information and connections matter in addition to education, and the lucky few who have found jobs have been greatly assisted by having a helpful contact in some city, usually an uncle or a cousin who was already employed in some formal or informal sector position. Education is often emphasized by static studies as a reliable pathway out of poverty, but a more dynamic analysis of reasons shows that education combined with social networks is more often associated with actual escapes.

(c) Inter-region and intra-region differences

Several examples from these studies show that even within the same country and region, significantly different reasons for escape/descent are in operation. While diversification of income sources has been the most important reason associated with escaping poverty in all regions studied, different sets of activities have been relatively more important in different regions. In villages of Rajasthan, India, for example, some people escaping poverty have taken up additional activities within their village, including rearing goats, making charcoal, and hiring out for labor in mining, transportation and agricultural activities. But many more villagers have sought new sources of livelihood in cities.

Diversification of income sources has involved a different set of activities in villages of Andhra Pradesh, India, and different activities have been taken up in different parts of this state. Broadly, two types of activities are involved. First, some households have set up tiny businesses of their own, or as in the case of Rajasthan, they have sent one of their members to work in the informal sector in some city. These types of activities have been more frequent in villages of Nalgonda and Khammam districts. Other households have diversified into non-traditional crops, while still holding on to a mainly agricultural lifestyle. The second type of diversification (within agriculture) has been more important in villages of East Godavari district. In villages of Gujarat, India diversification has involved a proportionately larger component of income from dairy activities. Different types of support will need to be targeted, thus, in order to promote escape through diversification in different regions of India.11

A second example concerns irrigation. Irrigation failure is an important reason associated with large numbers of descent in villages of Andhra Pradesh, but the effects of this reason vary considerably across different parts of this state. In villages of Nalgonda district, irrigation failure was much more frequently a reason for descent than in villages of the other two districts, Khammam and East Godavari, indicating that the same reason can have significantly different effects even within the same state.

Similarly, in both regions, Puno and Cajamarca, which we studied in Peru, social and customary expenses on marriages and funerals are important for descent. However, while marriage expenses were associated with 32 percent of all descents in communities of Cajamarca, they were involved with only 19 percent of descents observed in Puno communities. Funeral expenses were associated with 17 percent of descents in Cajamarca communities, but such expenses were much less significant for descent in the Puno region.

In Uganda, similarly, average trends for all 36 villages studied conceal the very substantial differences that exist from village to village. Overall, poverty has fallen from 45 percent to 35 percent, but in as many as 16 of the 36 villages that we studied net poverty increased over the 25-year period. Factors of escape and descent were studied across two separate Ugandan regions, Central and Western, and also for two separate time periods, a first period (1980-1994) and a second period (1994-2004). None of three factors – ill health, healthcare expenses, and death of major income earner – was significant for descent in Western villages during the first period, and only one of these factors, healthcare expenses, was significant in Central villages. During the second period, however, all three factors were significantly implicated in descents observed in both regions of this country. Thus, descents have accelerated during the more recent period. Evidence from other countries also shows how healthcare has increased in importance as a reason for descent into poverty.12

The impacts of other factors have also varied across time and space. Land division played a key role for descent in communities of the Western region in both time periods, but it was not significant for communities of Central region in either time period. Land exhaustion became significant in the Western region during the second time period, but it was not an issue in the Central region in either time period.

These variations have important consequences for targeting policy. To the extent that the reasons for escape or descent are similar across an entire state or region, policies can be devised that have a larger geographic scope. To the extent, however, that reasons for escape and descent vary locally, more regionally variegated policies will be required.

Administrative costs already beleaguer agencies attempting to target beneficiaries more accurately. It is not clear whether targeting reasons before targeting beneficiaries will add significantly to these costs, but it will certainly be much more rewarding in terms of ultimate results. Attention to context-specific reasons is critically important for poverty reduction.

Rather than thinking in terms of a purely centralized or a purely decentralized response, a more polycentric response will be more effective. Depending upon the nature of the reason and the required response, a combination of centralized and decentralized responses will be required, as discussed below.

Targeting in its present guise can provide a false sense of accomplishment for policy makers. While the identification of the poor is and should continue to be an important tool, there is a danger that it will be seen as the end rather than the means of poverty reduction. The risk is that once the poor are targeted and the benefits delivered, then the objectives of the program will be considered achieved. Unless this process results in sustainable reductions in poverty rather than temporary alleviation of hardships, it cannot be considered a success.

Targeted programs have commonly suffered from two failings. While the first failing of most targeted programs is that they do not help households and individuals deflect or avert poverty in the first place, coming into effect only after a fall has been suffered; the second failing of targeted programs is that they do not usually identify, far less target, the reasons for escape.13

“The poor” is a static concept, but poverty is inherently dynamic. Thinking in terms of flows – out of poverty but also into poverty – is much more productive for reducing poverty faster. Since one cannot really predict who will be poor at some future time – but can with much greater certainty identify the reasons that lead people into poverty – it makes much greater sense to target reasons before targeting people.

Targeting reasons before people is also a better strategy for promoting more escapes out of poverty. Improved yields from agriculture, jobs in the informal sector, and full-time and protected jobs in the private or public sectors – these have been the most significant pathways out of poverty. As revealed by the set of studies examined above, more than 90 percent of households that have come out of poverty have followed one or more of these three important pathways. They have been assisted by inputs such as education together with information about opportunities (in the case of diversification and jobs) and by irrigation and information (about varietals and market conditions) in the case of agricultural improvements. Practically speaking, relatively few among these inputs – those that target reasons associated with escape – can be provided selectively to any targeted subset of beneficiaries while excluding others interested in obtaining them. Admission to public schools cannot feasibly be denied to any child who is interested to learn. Information about jobs and opportunities cannot be passed selectively into the ears of some more deserving beneficiaries (though affirmative action policies can help). Irrigation schemes cannot simply bypass the fields of less poor farmers; it is neither administratively practical, nor politically feasible, nor even patently fair.

Targeting reasons before people is more effective, therefore, both for preventing descents and for promoting escapes. In order for poverty to be reduced in half by the year 2015, as enjoined upon us by the Millennium Development Goals, such a revised targeting strategy will have to be adopted. Governments and other agencies will have to move away from being seen to be doing important things to actually doing things that make a real difference in practice.14

Reasons for escape and reasons for descent change over time and across regions. Policies must stay current with these changes in order to remain relevant and be effective. Reasons associated with escape and descent will need to be studied more regularly on a decentralized and localized basis.

Hope lies in the fact that a number of new methodologies have been pioneered in recent years, which enable decentralized analysis and programming to become more effective. After examining the lacunae associated with present-day methods of targeting, Besley and Kanbur (1993: 10) claim that “what is needed is detailed country-specific analyses for developing countries. In the past such analysis may have been thought to be problematic given the lack of adequate micro data. But recent advances in micro level data collection make this excuse less plausible.”

One such advance is represented by the Stages-of-Progress methodology, which has been used successfully in eight different countries by researchers, NGOs and governments. In addition to examining the status and various characteristics of different households, this methodology also enables an examination of the processes that accompany households’ escape or descent. Positive reasons – those which help pull households upward – can be identified along with negative reasons, which push households downward. Policies and programs can be formulated to address both sets of reasons as they operate within any specific region or group of communities.15 Other innovative low-cost measurement methods have also been developed in recent years. Combining these methods judiciously will enhance our capacity to identify and target the reasons for poverty.

The scope of responses required will depend upon the nature of reasons that need to be targeted. Different reasons for escaping poverty or falling into poverty can operate over smaller or larger areas. Health might be best addressed through a countrywide response, for example, but other reasons, such as land exhaustion or crop disease, may require more localized responses. A polycentric response, targeting reasons, is likely to make more headway than a fully centralized or a wholly decentralized one. Within each region and country, however, reasons – for escape and for descent – need to be targeted before people. Progress in poverty reduction will be better as a result.

Table 1: The Dynamic Nature of Poverty: Some Illustrations


Country/ Region









Percentage Escaped Poverty


Percentage Fell Into Poverty


Sen (2003)






Haddad and Ahmed (2003)





India (Rural)

Bhide and Mehta (2004)





India (Rajasthan)

Krishna (2004)





Kenya (Western)

Krishna et al. (2004)





South Africa

Carter and May (2001)






Deininger and Okidi (2003)





Table 2. Principal Reasons for Descent into Poverty

(% of descending households)


Rajasthan, India


Gujarat, India


Western Kenya


Andhra, India


Uganda: Central & Western


Peru: Puno &



Poor health and health-related expenses







Marriage/dowry/new household-related expenses






Funeral-related expenses







High interest private debt




Drought/ irrigation failure/crop disease





Unproductive land/land exhaustion



Table 3. Principal Reasons for Escaping Poverty

(% of escaping households)


Rajasthan, India


Gujarat, India


Western Kenya


Andhra, India


Uganda: Central & Western


Peru: Puno &



Diversification of income







Private sector employment







Public sector employment







Government assistance/NGO scheme










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