"Capita Expenditure." . . "Arbeitspapier Working paper." . . "Small Area Estimation Poverty Mapping." . . "Poverty Mapping." . . "Health, Nutrition and Population." . . "Income distribution." . . "Population Census." . . "Estimates of Poverty." . . "Zonder onderwerpscode: wereldeconomie, ontwikkelingsproblematiek." . . "Finance and Financial Sector Development." . . "Simulation Procedures." . . "Equality." . . "Household Survey." . . "Scientific Research and Science Parks." . . "Pro-Poor Growth." . . "Räumliche Verteilung" . . "Welfare economics." . . "Standard Errors." . . "Population Policies." . . "Variance-Covariance Matrix." . . "Poverty Reduction." . . "Delta Method." . . "Poverty." . . "Science and Technology Development." . . "Inegalitate socială." . . . . . . . "How good a map? putting small area estimation to the test" . "How good a map? putting small area estimation to the test"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "How Good A Map ? Putting Small Area Estimation To The Test" . . . . . . . . . . . . . . . . "How Good A Map ? Putting Small Area Estimation to the Test" . . . . . . . . . "How good a map? : Putting small area estimation to the test"@en . "How good a map? : Putting small area estimation to the test" . . . . . . . . "How good a map? : putting small area estimation to the test" . . . . . . . "Electronic books"@en . . . . . . "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."@en . . . . . . . . . . "Capital Expenditure." . . "Parameter Estimates." . . "Standard Deviation." . . "Sărăcie Modele econometrice." . . "Datenerhebung" . . . . "Household Survey Data." . . "Explanatory Variables." . . "Small Area Estimation." . . "Poverty Mapping Methodology." . . "Armut" . . "Statistical and Mathematical Sciences." . . "Econometrie." . . "Poverty Maps." . . "Simulations." . . "Macroeconomics and Economic Growth." . . "Rural Poverty Reduction." . . "Armut Räumliche Verteilung Statistische Erhebung." . . "Degrees of Freedom." . . "Online-Publikation Online-publication." . . "Poverty Measures." . .