Estimating Vulnerability

Many existing measures of vulnerability lack a theoretical basis. In this paper we propose to measure vulnerability rigorously as the welfare of a household which solves an intertemporal optimisation model under risk.In such models, in essence a stochastic version of the Ramsey model, an important part of chronic poverty may be caused by the ex ante response of households to risks. Our simulation results indicate that whether or not a household is to be classified as vulnerable depends strongly on the time horizon considered. We use the model to assess the accuracy of existing regression-based vulnerability measures. We find that these methods can be vastly improved by including asset measures in the regression.Vulnerability, household models.

Brazil within Brazil : testing the poverty map methodology in Minas Gerais

The small-area estimation technique developed for producing poverty maps has been applied in a large number of developing countries. Opportunities to formally test the validity of this approach remain rare due to lack of appropriately detailed data. This paper compares a set of predicted welfare estimates based on this methodology against their true values, in a setting where these true values are known. A recent study draws on Monte Carlo evidence to warn that the small-area estimation methodology could significantly over-state the precision of local-level estimates of poverty, if underlying assumptions of spatial homogeneity do not hold. Despite these concerns, the findings in this paper for the state of Minas Gerais, Brazil, indicate that the small-area estimation approach is able to produce estimates of welfare that line up quite closely to their true values. Although the setting considered here would seem, a priori, unlikely to meet the homogeneity conditions that have been argued to be essential for the method, confidence intervals for the poverty estimates also appear to be appropriate. However, this latter conclusion holds only after carefully controlling for community-level factors that are correlated with household level welfare.Statistical&Mathematical Sciences,Population Policies,Science Education,Scientific Research&Science Parks,Small Area Estimation Poverty Mapping

Growth and Risk: Methodology and Micro Evidence

There has been a revival of interest in the effect of risk on economic growth. We quantify both ex ante and ex post effects of risk using a stochastic version of the Ramsey model. We develop a simulation-based econometric methodology which allows us to estimate the model in the structural form suggested by theory. The methodology is applied to micro data from a remarkable long-running panel data set for rural households in Zimbabwe. We find that risk substantially reduces growth: in the ergodic distribution the mean (across households) capital stock is 46% lower than in the absence of risk. About two-thirds of the impact of risk is due to the ex ante effect (i.e. the behavioral response to risk) which is usually not taken into account in policy design. Our results suggest that the e¤ectiveness of policy interventions which reduce exposure to shocks or help households in risk management may be seriously underestimated.Farm household models, stochastic Ramsey growth models, estimation by simulation.

Vulnerability in a Stochastic Dynamic Model

Most measures of vulnerability are a-theoretic and essentially static. In this paper we use a stochastic Ramsey model to find a household's optimal welfare and we measure vulnerability as the shortfall from the welfare attained if the household consumed permanently at the poverty line. The results indicate that vulnerability is very sensitive to the time horizon considered. We find that the accuracy of existing regression-based vulnerability measures can be greatly improved by including asset measures in the regression

How good a map ? Putting small area estimation to the test

The authors examine the performance of small area welfare estimation. The method combines census and survey data to produce spatially disaggregated poverty and inequality estimates. To test the method, they compare predicted welfare indicators for a set of target populations with their true values. They construct target populations using actual data from a census of households in a set of rural Mexican communities. They examine estimates along three criteria: accuracy of confidence intervals, bias, and correlation with true values. The authors find that while point estimates are very stable, the precision of the estimates varies with alternative simulation methods. While the original approach of numerical gradient estimation yields standard errors that seem appropriate, some computationally less-intensive simulation procedures yield confidence intervals that are slightly too narrow. The precision of estimates is shown to diminish markedly if unobserved location effects at the village level are not well captured in underlying consumption models. With well specified models there is only slight evidence of bias, but the authors show that bias increases if underlying models fail to capture latent location effects. Correlations between estimated and true welfare at the local level are highest for mean expenditure and poverty measures and lower for inequality measures.Small Area Estimation Poverty Mapping,Rural Poverty Reduction,Science Education,Scientific Research&Science Parks,Population Policies

Re-interpreting sub-group inequality decompositions

The authors propose a modification to the conventional approach of decomposing income inequality by population sub-groups. Specifically, they propose a measure that evaluates observed between-group inequality against a benchmark of maximum between-group inequality that can be attained when the number and relative sizes of groups under examination are fixed. The authors argue that such a modification can provide a complementary perspective on the question of whether a particular population breakdown is salient to an assessment of inequality in a country. As their measure normalizes between-group inequality by the number and relative sizes of groups, it is also less subject to problems of comparability across different settings. The authors show that for a large set of countries their assessment of the importance of group differences typically increases substantially on the basis of this approach. The ranking of countries (or different population groups) can also differ from that obtained using traditional decomposition methods. Finally, they observe an interesting pattern of higher levels of overall inequality in countries where their measure finds higher between-group contributions.Inequality,Poverty Impact Evaluation,Governance Indicators,Rural Poverty Reduction,Services&Transfers to Poor

Poverty alleviation through geographic targeting : how much does disaggregation help?

Using recently completed"poverty maps"for Cambodia, Ecuador, and Madagascar, the authors simulate the impact on poverty of transferring an exogenously given budget to geographically defined subgroups of the population according to their relative poverty status. They find large gains from targeting smaller administrative units, such as districts or villages. But these gains are still far from the poverty reduction that would be possible had the planners had access to information on household level income or consumption. The results suggest that a useful way forward might be to combine fine geographic targeting using a poverty map with within-community targeting mechanisms.Poverty Monitoring&Analysis,Environmental Economics&Policies,Poverty Reduction Strategies,Services&Transfers to Poor,Health Economics&Finance,VN-Acb Mis -- IFC-00535908,Poverty Assessment,Safety Nets and Transfers,Rural Poverty Reduction,Services&Transfers to Poor

Are neighbors equal?

"A methodology to produce disaggregated estimates of inequality is implemented in three developing countries: Ecuador, Madagascar, and Mozambique. These inequality estimates are decomposed into progressively more disaggregated spatial units and the results in all three countries are suggestive that even at a very high level of spatial disaggregation, the contribution of within-community inequality to overall inequality remains very high. The results also indicate there is a considerable amount of variation across communities in all three countries. The basic correlates of local-level inequality are explored, and it is consistently found that geographic characteristics are strongly correlated with inequality, even after controlling for demographic and economic conditions." Authors' AbstractEquality ,Spatial analysis (Statistics) ,Household surveys ,Economic conditions ,

Vulnerability in a Stochastic Dynamic Model

Most measures of vulnerability are a-theoretic and essentially static. In this paper we use a stochastic Ramsey model to find a household's optimal welfare and we measure vulnerability as the shortfall from the welfare attained if the household consumed permanently at the poverty line. The results indicate that vulnerability is very sensitive to the time horizon considered. We find that the accuracy of existing regression-based vulnerability measures can be greatly improved by including asset measures in the regression.vulnerability, expected poverty, risk, Ramsey model, consumption regressions