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I had promised myself I would deactivate my Twitter X profile after the election to take a break from frantically cycling through the same four or five political pundits’ accounts since early summer. The date to re-activate my account (to avoid it being deleted) came and went without me wanting to do so. And just like that, there went nearly 20,000 followers accrued over the span of 14 years.

My paper with Wahed Rahman and Jeff Bloem titled “Survey Ordering and the Measurement of Welfare” has been accepted and is now forthcoming at the Journal of the Economic Science Association.

Here is the accepted version, and here is the abstract:

Economic policy and research rely on the accurate measurement of welfare. In nearly all instances, measuring welfare requires collecting data via long household surveys. If survey response patterns change over the course of a survey to introduce measurement error, this measurement error can be either classical (i.e., changing distributions, leading to noise) or non-classical (i.e., changing expectations, leading to bias). We embed an experiment in a survey by randomly assigning a questionnaire with either the assets module near the beginning of the survey or the assets module at the end of the survey, delaying enumeration of assets by about 60 minutes. We find no evidence in the full sample that survey ordering introduces differential response patterns, either in the number of reported assets or the reported value of those assets. In exploratory analysis of heterogeneity, we find evidence of non-classical measurement error due to survey ordering within sub-samples of respondents who (i) are from larger households or (ii) have low levels of education. Our experimental design can be generalized to serve as an ex post test of data quality with respect to questionnaire length.

When given additional income, how much do the poor choose to spend on food? This deceivingly simple question is surprisingly difficult to answer and has preoccupied many generations of economists. For starters, do observed correlations between income and food demand truly capture the effect of income on food demand, or do they also capture the effect of confounding factors?
 
In a new paper titled “Income and the Demand for Food Among the Poor,” my coauthors Eeshani Kandpal, Katherina Thomas, and I revisit these age-old questions. To do so, we aggregate publicly-available data from five randomized evaluations of conditional cash transfers in five countries across three continents: two in Mexico, one in Nicaragua, one in the Philippines, and one in Uganda. We first define the demand for food as how much recipients spend on food (i.e., food expenditures). We then look at the impact of (i) being assigned to receiving a conditional cash transfer, and (ii) extra income on food expenditures overall as well as on expenditures on staples, protein, fruits and vegetables, and other foods.