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В статье на основе оценок трех профилей бедности, рассчитанных на данных выборочных обследований, предлагается методика получения комплексной оценки бедности, которая является решением модели латентно-структурного анализа с бинарными классами. В обследованиях РиДМиЖ, РЛМС ВШЭ, ОБДХ присутствуют вопросы, ответы на которые характеризуют разные профили бедности—экономический профиль, депривационный и субъективный. Последний представляет субъективное ощущение своего материального положения на шкале уровня жизни. Оценки, полученные по трем профилям, измеряют разные стороны бедности, однако не ясно насколько они согласованы между собой, и существует ли латентная бедность, которая статистически отражается в них. На базе модели латентно-структурного анализа можно получить утвердительный или отрицательный ответ на этот вопрос. В случае утвердительного ответа в качестве комплексной оценки бедности предлагается принять вероятность латентной бедности. В статье приведены результаты конкретных расчетов для трёх групп домохозяйств: пенсионеров, трудоспособных и смешанных семей, состоящих из пенсионеров и трудоспособных. На данных самого большого обследования Росстата ВНДН получены оценки латентной бедности для городского и сельского населения России, домохозяйств с разным количеством детей. Показано, что латентная бедность и согласованность для разных групп населения не противоречат содержательным представлениям об этом явлении. Выявлено, что заниженный уровень прожиточного минимума (граница абсолютной бедности) приводит к нарушению согласованности трех оценок для домохозяйств пенсионеров. В этом случае ощущение бедности и уровень лишений плохо согласуются с экономической оценкой бедности., On the basis of estimating three poverty profiles calculated on sample surveys data, the article presents the methods for obtaining an integrated poverty measure, which solves the model of latent structural analysis with binary classes. In such surveys as Parents and Children, Men and Women in Family, HSE Russian Longitudinal Monitoring Survey, Russian Household Budget Survey, there are questions characterizing different profiles of poverty—economic, deprivation and subjective. The last-mentioned profile presents a subjective perception of one’s position on the scale of living standards. Estimates by the three profiles measure different sides of poverty, but it is not clear how they are harmonized, and whether latent poverty is statistically reflected in them. The model of the latent structural analysis may give a positive or negative answer to this question. In case of the positive answer it is proposed to take the probability of latent poverty as an integrated poverty measure. The article provides the results of calculations for three groups of households: those of pensioners, of able-bodied persons, and mixed households consisting of pensioners and the able-bodied. On the data from the largest Rosstat survey—Statistical Survey of Income and Participation in Social Programs (VNDN) were made estimates of latent poverty for urban and rural population of Russia, for households with different number of children. It shows that latent poverty and coherence of different population groups are not contrary to the meaningful views on the phenomenon. It is found out that the understated size of the subsistence minimum (absolute poverty line) leads to lack of coherence between three estimates for households of pensioners. In this case, feeling of poverty and deprivation levels are not in line with the economic estimation of poverty.

What happened to poverty in India in the 1990s has been fiercely debated, both politically and statistically. The debate has run parallel to the wider debate about globalization and poverty in the 1990s and is also an important part of that debate. The economic reforms of the early 1990s in India were followed by rates of economic growth that were high by historical standards. The effects on poverty remain controversial, however. The official numbers published by the government of India, showing acceleration in the rate of poverty reduction from 36 percent of the population in 1993 to 1994 to 26 percent in 1999 to 2000, have been challenged for showing both too little and too much poverty reduction. The various claims have often been frankly political, but there are also many important statistical issues. The debate, reviewed in this article, provides an excellent example of how politics and statistics interact in an important, largely domestic debate. Although there is no consensus on what happened to poverty in India in the 1990s, there is good evidence both that poverty fell and that the official estimates of poverty reduction are too optimistic, particularly for rural India. The issues covered in this article, although concerned with the measurement of poverty in India, have wide international relevance discrepancies between surveys and national accounts, the effects of questionnaire design, reporting periods, survey nonresponse, repair of imperfect data, choice of poverty lines, and interplay between statistics and politics.

This article reviews trends in poverty, economic policies, and growth in a sample of African countries during the 1990s, drawing on the better household data now available. Experiences have varied. Some countries have seen sharp drops in income poverty, whereas others have witnessed marked increases. In some countries overall economic growth has been pro-poor and in others not. But the aggregate numbers hide systematic distributional effects. Taking both macro and micro perspectives of growth and poverty in Africa, the article draws four key conclusions. First, economic policy reforms (improving macroeconomic balances and liberalizing markets) appear conducive to reducing poverty. Second, market connectedness is crucial to enable participation in the gains from economic growth. Some regions and households by virtue of their remoteness were left behind when growth picked up. Third, education and access to land emerge as key private endowments to help households benefit from new economic opportunities. Finally, rainfall variations and ill health have profound effects on poverty outcomes, underscoring the significance of social risk management in poverty reduction strategies in Africa.

Microfinance supports mainly informal activities that often have a low return and low market demand. It may therefore be hypothesized that the aggregate poverty impact of microfinance is modest or even nonexistent. If true, the poverty impact of microfinance observed at the participant level represents either income redistribution or short run income generation from the microfinance intervention. This article examines the effects of microfinance on poverty reduction at both the participant and the aggregate levels using panel data from Bangladesh. The results suggest that access to microfinance contributes to poverty reduction, especially for female participants, and to overall poverty reduction at the village level. Microfinance thus helps not only poor participants but also the local economy.

Rural and urban households in developing countries face substantial idiosyncratic and common risk, resulting in high income variability. Households in risky environments have developed sophisticated (ex-ante) risk-management and (ex-post) risk-coping strategies, including self-insurance via savings and informal insurance mechanisms to do so while formal credit and insurance markets appear to contribute only little to reducing income risk and its consequences. Informal credit and insurance, however incomplete, helps to cope with risky incomes. Despite these strategies, vulnerability remains high, and is reflected in fluctuations in consumption. It is clear therefore, that further development of safety nets will be necessary. In this paper, we focus on the opportunities available to households to use risk-management and risk-coping strategies, and on the constraints on their effectiveness. Fluctuations in consumption usually imply relatively high levels of transient poverty. High income risk may also be a cause of persistent poverty. The failure to cope with income risk is not only reflected in household consumption fluctuations but affect nutrition, health and education and contribute to inefficient and unequal intrahousehold allocations. Deaton’s model provides a useful description of the advantages of self-insurance. Policy conclusions may be limited however. In practice, assets are risky, not safe. The covariance of asset values and income due to common shocks makes self-insurance a far less useful strategy than it seems. We quantify the consequences of holding risky assets that are covariate with incomes, using simulations. Access to relatively safe and profitable assets, which might be useful for consumption smoothing, may also be limited. Lumpiness in assets may be a reason why the poor cannot protect themselves easily via assets. Policies that influence asset market risks could be beneficial to households attempting to deal with shocks. Policies could include providing more attractive and diversified savings instruments. Microfinance initiatives should put savings for self-insurance on the agenda. Macroeconomic stability during income downturns would also allow self-insurance to function better. Income smoothing can be achieved by income portfolio adjustments. In practice relatively little income smoothing (even via income portfolio adjustments) is achieved by poorer households. Income diversification for effective risk-reduction appears limited. Observed diversification patterns are often not aimed at reducing risk. Households face entry constraints to enter into profitable activities. Income risk reduction often comes at a cost. Income skewing is likely if less protection is offered by investing in assets. The long-term consequences for the asset-poor are lower average incomes and a higher income gap relative to asset-rich households. Observing specialisation does not necessarily imply that the household follows a high-risk strategy. Also, entry constraints may limit the diversification that can be achieved, leaving only low-return activities free to the poor. Income portfolios must be seen in relation to the asset portfolio and other options available: a risky, specialised portfolio may mean lower consumption risk than a diversified portfolio, depending on the asset position. Finally, several income-based strategies are only be invoked when a crisis looms. These (income)‘coping’ or ‘survival’ strategies are especially important when the shock is economy-wide. There has been increasing interest in the empirical analysis of informal risk-sharing and theoretical modelling on the sustainability and consequences of these arrangements. Risk-sharing can be viewed as the cross-sectional equivalent of consumption smoothing over time. In the absence of enforcement problems, the existence of better savings opportunities and a public safety net providing transfers when common shocks occur, could improve welfare without crowding out the informal insurance arrangement. A transfer-based safety net is, however, likely to crowd out private (precautionary) savings. Informal insurance arrangements are likely to have to be self-enforcing, imposing sustainability constraints. Circumstances in which risk-sharing arrangements may be sustained are, inter alia: a low discount rate of the future, high frequency of interactions, situations in which idiosyncratic shocks are more frequent relative to other shocks. Evaluating the effects of alternative coping mechanisms such as savings, or of policy interventions such as providing better savings instruments or public safety nets, needs to take into account their effect on incentives to sustain the agreement rather than to go it alone. It is possible that opportunities for precautionary savings or a public safety net would actually be welfare reducing and displace the informal insurance arrangement by more than one to one. Any policy intervention that improves an individual’s position outside a private group-based informal risk-sharing arrangement may provide incentives to break down the informal arrangement. Targeted interventions that target only some members of communities or groups could be particularly counterproductive. Group-based savings schemes could provide a useful alternative or complement if one is concerned about crowding-out. The possibly negative welfare effects can be avoided. Whether the crowding-out and potential negative welfare effects of interventions on informal insurance mechanisms are significant is an empirical question. If common shocks are dominant and if groups and communities rather than just individuals are targeted, these negative effects are likely to be less significant. Standard quantitative poverty analysis assumes that consumption is smooth. If smoothing is not possible, especially when large negative shocks occur, then alternative measures of poverty and vulnerability need to be explored. If interiii temporal data are available, broader definitions can be used to describe vulnerability. Aggregate measures of ‘vulnerability’ can be obtained. Targeting assistance to the vulnerable population requires specific kinds of information. Analysing the characteristics of households experiencing chronic or transient poverty, or in general, their consumption fluctuations, can provide this information. Panel data are required for this analysis. If policies are exogenous to the risk management and coping strategies, then information on how households handle income risk is irrelevant. However, policies may affect household opportunities to cope with risk (e.g. by changing exit options from informal insurance). In that case, how households cope with risk is relevant for the design of policies, in turn increasing data requirements. If effective safety nets and other consumption risk-reducing policies require detailed knowledge of existing risk-reducing actions by households, then surveys need information on physical, human and social capital, on shocks, as well as on opportunities in labour, product and asset markets. Panel and cross-section surveys could be used to collect relevant information. The complexity of consumption-risk reducing strategies implies that a simple indicator is unlikely to be available. Measures of vulnerability would typically require detailed data, including from panels. Some indicators that aim to describe vulnerability are typically flawed. The emphasis on the ability to cope with risk via assets, human capital and informal insurance and on the opportunities available, marks a convergence of different disciplines, bridging gaps with more qualitative approaches.