On the Measurement of Food Waste

My colleagues Metin Çakır, Hikaru Hanawa Peterson and I, along with our doctoral students Lindsey Novak (who will be joining the faculty of Colby College this summer) and Jeta Rudi (who has joined the faculty at Cal Poly San Luis Obispo since we started working on this) have a new working paper on food waste.

In that paper, we propose a new definition of food waste–one that avoids value judgments and that has the merit of not counting the productive uses of food (e.g., composting, feeding animals, etc.) as “waste.” On that basis, we argue that most food waste definitions vastly overestimate the extent of the problem.

Moreover, because most food waste is valued at retail prices when, in fact, food often gets wasted well before the retail stage, we also argue that most definitions of food waste overestimate the price per unit of the food that is wasted. Since the value of food waste multiplies those two overstated quantities, it is obvious that reported values are even more overstated.

Here is the abstract of our new paper: Continue reading

The Globalization of Food (and Yours Truly) in The Economist

This week’s issue of The Economist has an article in the Leaders section titled “In Praise of Quinoa,” which mentions the work I have done with my PhD student Johanna Fajardo-Gonzalez and my Towson colleague Seth Gitter on the welfare impacts of rapidly rising quinoa prices from 2004 to 2013: Continue reading

‘Metrics Monday: Combining Bits and Pieces of Likelihood to Study Behavior

I have mentioned a few times that there is an unspoken ontological order of things in applied work, wherein one first needs to take care of the problem of identification before one should worry about properly modeling the dependent variable’s data-generating process. In other words, before you obsess over whether you should estimate a Poisson or a negative binomial regression, your time is better spend thinking about whether the effect of your variable of interest on your dependent variable is properly identified.

This week, however, I wanted to move away from my usual focus on the identification of causal effects to look at the modeling of DGPs.

Let us take an example from the first article I ever published (and which, to this day, remains my most-cited article). In that article, my coauthor and I were interested in the marketing behavior of the households in our sample. In some time periods, some households happened to be net sellers (i.e., their sales exceeded their purchases), some households happened to be net buyers (i.e., their purchases exceeded their sales), and some households happened to be autarkic (i.e., their neither bought nor sold). Continue reading