Back in March, I was asked by Clemson University’s Michael Vassalos to contribute to a special issue of Choices, the Agricultural and Applied Economics’ outreach magazine, on the theme of agricultural contracts.
My article, titled “Contract Farming: What’s In It for Smallholder Farmers in Developing Countries?,” was published last Friday in Choices. After discussing the theoretical pros and cons of participating in contract farming for smallholder farmers in developing countries and whether the institution does make them better off, I offer some skeptical thoughts about the policy relevance of the empirical findings (including my own) on the welfare impacts of contract farming: Continue reading →
Suppose you want to study the demand for a given good. If you want your work to be grounded in theory, you probably want to start with primitives. That is, you will want to start with (i) consumer preferences, as represented by a utility function U(.) defined over the consumption x of the good, (ii) the price p of the good whose demand you want to study (for ease of notation, I am ignoring the prices of other goods, whether they are substitutes or complements), and (ii) consumer income w.
With that information, you can then maximize the consumer’s utility U(x) by choosing x such that px = w (the constraint will hold with equality if you assume that the consumer’s preferences are monotonic, i.e., consumers derive greater well-being for greater amounts of x). This yields x(p,w), the consumer’s Marshallian demand (some prefer to call it a Walrasian demand) for the good whose demand you are studying when price is equal to p and income is equal to w. From x(p,w), you can calculate how consumer demand changes as price increases or as income increases, which you would respectively denote dx/dp and dx/dw. (Yes, I am abusing notation by using d to denote partial derivatives; bear with me.) Continue reading →
(Back from two weeks in Milan, where I attended the 2015 IAAE conference, visited Expo 2015, took some time off, and saw friends I had not seen in a long time. This week’s ‘Metrics Monday is a bit different in that it is not so much about econometrics, but about the consumers of results generated by econometrics, and the need for better statistical education at an early age.)
In a conversation on this blog’s Facebook page a few weeks ago about a new working paper, a friend asked “Does this support [X] or not?” Given that the paper under discussion looked at a number of outcomes and presented a mixed bag of results, and given that the results were not causally identified, I responded: “There is no simple answer to that question. There is a little bit of everything for everyone here. Read the limitations section, too.” My friend then said she had done that but was still confused, and that “We all know it’s much easier to lie with statistics than tell the truth.”
Is it? Or is it just much easier to be misled by statistics than it is to lie with them? Continue reading →