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My experience with blogging tells me that a post on applied econometrics is always a good way to start the week by generating a large number of views, so let me do a ‘Metrics Monday yet again this week.

A few weeks ago, Google Scholar alerted me that a new working paper by Giuseppe de Luca, Jan Magnus, and Franco Peracchi might be of interest to me, given the research topics associated with my profile. (I was under the impression that their paper was forthcoming in the Journal of Labor Economics, but I somehow cannot find any evidence that this is so. No matter, this is an important contribution.)

Let me first present the abstract of the article, which even after reading three times, I had a hard time making heads or tails of given how cryptic it was. Then, I will present the first few paragraphs of the article, which illustrate the point much better. I’ll then go into the results, which are actually pretty important for applied econometrics.

Here is de Luca et al.’s abstract:

This paper studies what happens when we move from a short regression to a long regression (or vice versa), when the long regression is shorter than the data-generation process. In the special case where the long regression equals the data-generation process, the least-squares estimators have smaller bias (in fact zero bias) but larger variances in the long regression than in the short regression. But if the long regression is also misspecified, the bias may not be smaller. We provide bias and mean squared error comparisons and study the dependence of the differences on the misspecification parameter.

Somewhat cryptic, at least to my applied mind. The first two paragraphs of the introduction provide a better idea of what’s going on:

It’s the summer, so I have time to read, both for work and for pleasure, and I have time to read books instead of just journal articles and blog posts. This made me realize that while a lot of my thinking has been shaped by things that I have read in journal articles (economics is an article-based field, after all) and in blog posts, a large part of my thinking has been shaped by books, which often contain more exciting ideas than journal articles–because they face less strict of a review process, books can be more daring in their claims, and thus have more chances of causing you to change how you view the world.

So I decided to start this series of posts on books that shaped my thinking. Because a lot of people are here for the development aspects, I thought I should start with development books. Some recommendations are very general; others are eminently personal. I just hope you can find one or two that will also shape your own thinking. I’m sure I am forgetting a lot of important books I have read and which have also shaped my thinking, but I made this list by taking quick look at the bookshelves in my office.

A fascinating new article in the AJAE by David Just and Andrew Hanks titled “The Hidden Cost of Regulation: Emotional Responses to Command and Control” could have very interesting implications for policy making:

In economic models of behavior, consumers are assumed to value the goods and services they purchase based on stable preferences over externally identifiable attributes such as quality. These models predict that consumers will respond to changes in price in a way that is independent of the source of the price change. Yet research in the behavioral sciences indicates that consumers that are emotionally attached to a consumption good or other behavior might respond with resistance when policies threaten their consumption or behavior. Moreover, policies that in fact validate some emotional attachments can stir a stronger preference for the good or behavior. Reviewing both survey and experimental data from the literature, we demonstrate how such emotional responses can create hidden costs to policy implementation that could not be detected using standard welfare economic techniques. Building upon Rabin’s work on fairness in games, we propose a partial equilibrium model of emotional response to policy whereby preferences are endogenous to policy choices. In accordance with evidence both from our own analysis and the field, we propose that confrontational policies (such as a sin tax) increase the marginal utility for a good, and that validating policies (such as a subsidy) also increases the marginal utility for a good. A social planner that ignores potential emotional responses to policy changes may unwittingly induce significant dead weight loss. Using our model, we propose a feasible method to determine if emotional deadweight costs exist, and to place a lower bound on the size of these costs.

This new paper is theoretical, but while we chatted about our experimental project on price uncertainty last week, David was telling me that when he and his coauthor showed experimental subjects a picture of NYC mayor Michael Bloomberg, who is well-known for his opposition to sweetened beverages, actually caused the same subjects to drink more soda on average than subjects who were not shown the same picture!

In other words, it looks like policies can induce a “Yeah? I’ll show you…” reaction whereby people respond to a ban, a tax, or an effort to curb some behavior by doing more of that behavior rather than less, i.e., by raising the marginal utility of the good banned, taxed, or otherwise regulated. I find it interesting how this is nice evidence in favor of the Lucas critique–has it ever been tested in the lab?– according to which a change in policy induces a change in agents’ preferences, so that it is almost always impossible to predict how people will react to a policy change.