Month: June 2015

This post is part of a continuing series on The Books that Have Shaped My Thinking.

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) and in blog posts (there is no better means of spreading important ideas quickly), 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 write this series of posts on books that shaped my thinking. I talked about development books last week; this week I will talk about food and agriculture. 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. Conversely, some of the books in this list also appeared in my previous post on The Books that Have Shaped My Thinking.

I have blogged about this paper a few times before (see here, here, here, and here in case you want to trace the development of this paper into its final, accepted form), but given that it was accepted last week by and is now forthcoming in the Journal of Development Economics, I thought I should have one final post on it. You can find the accepted version here, and here is the abstract:

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: