UC Berkeley

Millions of low-income households have received large one-time transfers of capital as part of private and public anti-poverty programs. Economists have studied the effect of such transfers in a wide variety of settings to understand their effect on household welfare and poverty rates. The standard metric used to study these effects is aggregate consumption, measured in price-adjusted dollars per capita per day, which in turn gets used to define the global poverty lines at $2 and $1.25. In this dissertation, I discuss some of the theoretical and practical issues that these measures face, and then suggest some alternatives pulled from a model of consumer demand. I demonstrate how they can be used to expand our understanding of two programs of direct capital transfers to poor households, with the broad goal of bringing insights from economic theory farther into the practice of impact evaluation.

This dissertation has as its chapters three papers, each written so that they stand alone for those interested in a particular part of the overall project. The first chapter develops a Frischian model of household expenditures, and uses this model to derive estimates of an individual household’s marginal utility in expenditures at any given time, log λit, which serves as the central welfare metric in each chapter. The application of this model to measure the welfare effects of asset transfers is illustrated using the early results of a pilot in South Sudan of the so-called “Targeting the Ultra-Poor” (TUP) program. It concludes that the large asset transfers improved welfare in the short-run.1

Chapter 2 uses the methods in Chapter 1 to reanalyze the first large experimental evaluation of the TUP framework in Bangladesh, previously studied in Bandiera et al. (2017). It goes on to estimate a flexible direct utility function which allows one to estimate welfare in a way that accounts for the immiserating effects of uncertainty faced by poor households. It concludes that this TUP program improved household welfare years after the transfers, and that this benefit was accompanied by a lower level of risk.

Finally, Chapter 3 goes on to study the experiment in South Sudan in more detail. It compares the TUP treatment to an experimental cash transfer, and showcases the practical value of the methods in Chapter 1 by continuing to cost-effectively monitor household welfare

after the long-form panel survey was completed. It then briefly speaks to how participation in the TUP program may have affected households’ response to the outbreak of violent civil conflict in 2014. The results show that both cash and asset transfers improved household welfare only in the short run, but the asset transfers had a sustained positive impact on households’ total stock of assets, which may have reduced the likelihood that those households were left without recourse upon the onset of violence.