Accurate targeting is key for the success of any development policy. While a number of factors might explain low targeting efficiency such as governance failure, political interference or lack of political will, this paper focuses on improving indicator-based models that identify poor households...

The recent international financial crisis and the steady decrease in development assistance have put many poor countries under increasing pressure to target more accurately their public spendings at the poor and the population in need. However, further progress is hampered by the lack of...

This paper assesses the cost efficiency of indicator-based targeting. Using household survey data from Malawi, we examine whether an indicator-based targeting of the poor is more target- and cost-efficient than the currently used mechanisms for targeting agricultural subsidy programs in the...

Futures prices when combined with a basis forecast provide a reliable way to forecast cash prices. The most popular method of forecasting basis is historical moving averages. Given the recent failure of longer moving averages proposed by previous studies, this research reassesses past...

Futures prices when combined with a basis forecast provide a reliable way to forecast cashprices. The most popular method of forecasting basis is historical moving averages. Given therecent failure of longer moving averages proposed by previous studies, this research reassessespast...

This paper develops low cost, reasonably accurate, and simple models for improving the targeting efficiency of development policies in Malawi. Using a stepwise logistic regression (weighted) along with other techniques applied in credit scoring, the research identifies a set of easily observable...

Improved software now makes Bayesian estimation a strong alternative to nonlinear maximum likelihood. Bayesian methods were used to estimate a linear response stochastic plateau for cotton and were shown to provide estimates similar to maximum likelihood. Optimal levels of nitrogen were lower...