How Good Is a Map? Putting Small Area Estimation to the Test

• Tác giả: Gabriel Demombynes
• Ngôn ngữ: eng
• Ký hiệu phân loại: 378.15 Specific levels of higher education, evening school
• Thông tin xuất bản: 2012
• Bộ sưu tập: Tài liệu truy cập mở
• ID: 326466
• Chủ đề: 1. Longitudinal Data; 2. Model Construction and Estimation C510; 3. Single Equation Models; 4. Single Variables: Models with Panel Data; 5. Spatial Time Series C230

Tóm tắt

This paper examines the performance small area of welfare estimation. The method combines census and survey data to produce spatially disaggregated poverty and inequality estimates. To test the method, predicted welfare indicators for a set of target populations are compared with their true values. The target populations are constructed using actual data from a census of households in a set of rural Mexican communities. Estimates are examined along three criteria: accuracy of confidence intervals, bias and correlation with true values. We find that while point estimates are very stable, the precision of the estimates varies with alternative simulation methods. 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 we show that bias increases if underlying models fail to capture latent location effects.