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Full-Text Articles in Public Economics
Is Predicted Data A Viable Alternative To Real Data?, Tomoki Fujii, Roy Van Der Weide
Is Predicted Data A Viable Alternative To Real Data?, Tomoki Fujii, Roy Van Der Weide
Research Collection School Of Economics
It is costly to collect the household- and individual-level data that underlies official estimates of poverty and health. For this reason, developing countries often do not have the budget to update their estimates of poverty and health regularly, even though these estimates are most needed there. One way to reduce the financial burden is to substitute some of the real data with predicted data. An approach referred to as double sampling collects the expensive outcome variable for a sub-sample only while collecting the covariates used for prediction for the full sample. The objective of this study is to determine if …
Is Predicted Data A Viable Alternative To Real Data?, Tomoki Fujii, Roy Van Der Weide
Is Predicted Data A Viable Alternative To Real Data?, Tomoki Fujii, Roy Van Der Weide
Research Collection School Of Economics
It is costly to collect the household- andindividual-level data that underlies official estimates of poverty and health. Forthis reason, developing countries often do not have the budget to update their estimatesof poverty and health regularly, even though these estimates are most neededthere. One way to reduce the financial burden is to substitute some of the realdata with predicted data. An approach referred to as double sampling collectsthe expensive outcome variable for a sub-sample only while collecting thecovariates used for prediction for the full sample. The objective of this studyis to determine if this would indeed allow for realizing meaningful reductionsin …
Is Predicted Data A Viable Alternative To Real Data?, Tomoki Fujii, Roy Van Der Weide
Is Predicted Data A Viable Alternative To Real Data?, Tomoki Fujii, Roy Van Der Weide
Research Collection School Of Economics
It is costly to collect the household- and individual-level data that underlies official estimates of poverty and health. For this reason, developing countries often do not have the budget to update their estimates of poverty and health regularly, even though these estimates are most needed there. One way to reduce the financial burden is to substitute some of the real data with predicted data. An approach referred to as double sampling collects the expensive outcome variable for a sub-sample only while collecting the covariates used for prediction for the full sample. The objective of this study is to determine if …
How Well Can We Target Aid With Rapidly Collected Data? Empirical Results For Poverty Mapping From Cambodia, Tomoki Fujii
How Well Can We Target Aid With Rapidly Collected Data? Empirical Results For Poverty Mapping From Cambodia, Tomoki Fujii
Research Collection School Of Economics
We compare commune-level poverty rankings in Cambodia based on three different methods: small-area estimation, principal component analysis using aggregate data, and interviews with local leaders. While they provide reasonably consistent rankings, the choice of the ranking method matters. In order to assess the potential losses from moving away from census-based poverty mapping, we used the concentration curve. Our calculation shows that about three-quarters of the potential gains from geographic targeting may be lost by using aggregate data. The usefulness of aggregate data in general would depend on the cost of data collection.