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330 | Revisiting Targeting in Social Assistance

23. OPM (2011). 24. Escot’s (2018) findings indicate that HEA in Gao was the most appropriate method for an emergency response as it managed to be implemented quickly, guaranteeing the acceptance of leaders but potentially at the expense of reliability. 25. Food insecurity, low human and physical capital asset holding, and low household earning capacity. 26. Escot’s (2018) findings indicate that PMT, which seems less suited to an emergency, has better reliability and its long-term perspective seems better suited for long-term interventions.

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6

How to Harness the Power of Data and Inference: Technical Discussion for Selected Targeting Methods

Phillippe Leite, Emil Tesliuc, Matthew Wai-Poi, and Margaret Grosh

Data and inference are at the heart of differentiating eligibility or benefits. Such differentiation requires making a judgment about where different people (are likely to) fall along the income spectrum in a data-driven sense. Where optimal data are not available, inference is often used to make approximations. This chapter is about data and inference, how to make choices about them in implementing selected targeting methods. Chapter 5 discusses the different methods and their needs in general terms; this chapter is more detailed and specific and focuses on the how-tos. The chapter might be read iteratively with chapter 5, or prior to reading chapter 5, as the choice of method is best made with a deep understanding of the howtos of each candidate method.

The technology revolution is changing the landscape of data and its processing, indeed making some things possible today that were not a few years ago and hinting at what may be possible in the not-too-distant future, possible in some places but not others, or possibly for purposes akin to but not quite the same as determining which households should receive social protection benefits or services. It is an exciting time in the world of data