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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.

Confidence intervals --- Descriptive statistics --- Education --- Enumeration --- Geographical Information Systems --- Precision --- Predictions --- Reliability --- Sample design --- Sample surveys --- Science and Technology Development --- Science Education --- Scientific Research and Science Parks --- Small Area Estimation Poverty Mapping --- Standard errors --- Statistical and Mathematical Sciences --- Validity

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The Knowledge Assessment Methodology (KAM) database measures variables that may be used to assess the readiness of countries for the knowledge economy and has many policy uses. Formal analysis using KAM data is faced with the problem of which variables to choose and why. Rather than make these decisions in an ad hoc manner, the authors recommend factor-analytic methods to distill the information contained in the many KAM variables into a smaller set of "factors." Their main objective is to quantify the factors for each country, and to do so in a way that allows comparisons of the factor scores over time. The authors investigate both principal components as well as true factor analytic methods, and emphasize simple structures that help provide a clear political-economic meaning of the factors, but also allow comparisons over time.

Correlation --- Correlations --- Covariance --- Data --- E-Business --- Errors --- Factor Analysis --- Information Security and Privacy --- Matrices --- Matrix --- Measurement --- Missing Data --- Orthogonality --- Population Parameters --- Principal Components Analysis --- Private Sector Development --- Regression Analysis --- Sample Size --- Samples --- Science and Technology Development --- Scientists --- Standard Errors --- Stata --- Statistical and Mathematical Sciences --- Variables

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This paper adds to aid volatility literature in three ways: First it tests the validity of the aid volatility and growth relationship from various aspects: across different time horizons, by sources of aid, and by aid volatility interactions with country characteristics. Second, it investigates the relationship by the level of aid absorption and spending. Third, when examining the relationship between International Development Association aid volatility and growth, it isolates International Development Association aid volatility due to the recipient country's performance from that due to other sources. The findings suggest that, in the long run, on average, aid volatility is negatively correlated with real economic growth. But the relationship is not even. It is stronger for Sub-Saharan African countries than for other regions and it is not present in middle-income countries or countries with strong institutions. For economies where aid is fully absorbed, aid volatility matters for long-run growth; economies with full aid spending also bear a negative impact of aid volatility on long-run growth. Where aid is not fully absorbed, or where it is not fully spent, the aid volatility relationship is not significant. Looking at International Development Association aid separately, the volatility arising from the recipient country's International Development Association performance does not have a causal relationship with growth. In policy terms, the results suggest that low- income countries with weak institutions, especially in Sub-Saharan Africa, could benefit from reduced aid volatility or from being better prepared for the volatility that is there.

Achieving Shared Growth --- Average growth rate --- Development Economics & Aid Effectiveness --- Economic Conditions and Volatility --- Economic growth --- Emerging Markets --- Exogenous volatility --- Fiscal policy --- Fluctuations --- Gender --- Gender and Health --- Growth --- Growth relationship --- Income --- Long-run growth --- Low income --- Low income countries --- Low-income countries --- Macroeconomic shocks --- Macroeconomics and Economic Growth --- Middle-income countries --- Poverty --- Poverty Reduction --- Private Sector Development --- Standard errors --- Volatility --- Volatility literature --- Volatility measure --- Volatility-growth

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Evidence from Uganda shows that poor public provision of infrastructure services - proxied by an unreliable and inadequate power supply - significantly reduces productive private investment; Lack of private investment is a serious policy problem in many developing countries, especially in Africa. Despite recent structural reform and stabilization, the investment response to date has been mixed, even among the strongest reformers. The role of poor infrastructure and deficient public services has received little attention in the economic literature, where the effect of public spending and investment on growth is shown to be at best ambiguous. Reinikka and Svensson use unique microeconomic evidence to show the effects of poor infrastructure services on private investment in Uganda. They find that poor public capital, proxied by an unreliable and inadequate power supply, significantly reduces productive private investment. Firms can substitute for inadequate provision of public capital by investing in it themselves. This comes at a cost, however: the installation of less productive capital. These results have clear policy implications. Although macroeconomic reforms and stabilization are necessary conditions for sustained growth and private investment, without an accompanying improvement in the public sector's performance, the private supply response to macroeconomic policy reform is likely to remain limited. This paper - a product of Public Economics and Macroeconomics and Growth, Development Research Group - is part of a larger effort in the group to study public service delivery and economic growth. The authors may be contacted at rreinikka@worldbank.org or jsvensson@worldbank.org.

Bottlenecks --- Capital Stock --- Debt Markets --- Emerging Markets --- Employment --- Equipment --- Finance --- Finance and Financial Sector Development --- Infrastructure --- Interest --- Interest Rates --- International Economics & Trade --- Investment --- Investment and Investment Climate --- Investment Rate --- Investment Rates --- IRU --- Labor Policies --- M1 --- Macroeconomics and Economic Growth --- Non Bank Financial Institutions --- Prices --- Private Sector Development --- Prof Standard Errors --- Roads and Highways --- Social Protections and Labor --- Statistics --- Tax --- Taxes --- Trade and Regional Integration --- Transport --- Vdu

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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.

Capita Expenditure --- Degrees of Freedom --- Delta Method --- Econometrics --- Education --- Estimates of Poverty --- Explanatory Variables --- Finance and Financial Sector Development --- Financial Literacy --- Health, Nutrition and Population --- Household Survey --- Household Survey Data --- Households --- Macroeconomics and Economic Growth --- Parameter Estimates --- Population Census --- Population Policies --- Poverty Mapping --- Poverty Mapping Methodology --- Poverty Maps --- Poverty Measures --- Poverty Reduction --- Pro-Poor Growth --- Rural Development --- Rural Poverty Reduction --- Science and Technology Development --- Science Education --- Scientific Research and Science Parks --- Simulation Procedures --- Simulations --- Small Area Estimation --- Small Area Estimation Poverty Mapping --- Standard Deviation --- Standard Errors --- Statistical and Mathematical Sciences --- Variance-Covariance Matrix