Showing posts with label econometrics. Show all posts
Showing posts with label econometrics. Show all posts

Monday, June 23, 2008

Descriptors or Treatments

I too have often thought of background variables, such as race, income, and education as descriptors, rather than treatments. However it seems as if most applied econometricians today think of them as treatments. Andrew Gelman posts on this topic:
Income, education, and religion as "background variables" or "treatments"

The discussion here on the climate change attitude mystery reminded me of a funny thing about how we think when we classify people by education, or income, or religion.

The original question was to explain why college-educated Republicans are less likely (compared to non-college-educated Republicans) to believe in human-caused global warming, while, among Democrats, those with college education are more likely to believe in it. To me this was no surprise: college-educated people are more political polarized and are more likely to align their views with their political attitudes.

But many of Tyler Cowen's commenters had a different sort of explanation, along the lines of, Going to college makes Republicans more skeptical of scientific authority but convinces Democrats of these arguments.

Setting aside the specific issue of climate change, one interesting thing here is the way I, in common with most political scientists, think of education (and other variables such as income and religion) as traits, or background variables, or descriptors of people. Thus when we talk about how rich and poor people vote, or more and less educated, or Protestants and Catholics, or whatever, we think of these as different sorts of people. But you can also think of income, or education, or religious attendance, as "treatments" that affect people--for example, if you go to college and share a room with someone of a different ethnic or political group, you might become more tolerant. Or maybe if you are conservative and go to college, you'll be skeptical of what's taught in your physics class (or if you're liberal, maybe you'll be skeptical of what's covered in your econ class).

I don't really have much to add here . . . somehow it seems more reasonable to me to think of these as descriptors than as treatments, but I guess it depends on the person and on what issue is being considered.

Sunday, June 01, 2008

Mostly Harmless Econometrics

A new Econometrics book : Mostly Harmless Econometrics.
The core methods in today's econometric toolkit are linear regression for statistical control, instrumental variables methods for the analysis of natural experiments, and differences-in-differences methods that exploit policy changes. In the modern experimentalist paradigm, these techniques answer clear causal questions such as: Do smaller classes increase learning? Do minimum wages reduce employment? Should wife batterers be arrested? How much does education raise earnings? Mostly Harmless Econometrics shows how the basic tools of applied econometrics allow the data to speak.

In addition to econometric essentials, Mostly Harmless Econometrics covers important new extensions--regression-discontinuity designs and quantile regression--as well as how to get standard errors right. Angrist and Pischke explain why fancier techniques are typically unnecessary and even dangerous. The applied econometric methods emphasized in this book are easy to use and relevant for many areas of contemporary social science.

* An irreverent review of econometric essentials
* A focus on tools that applied researchers use most
* Chapters on regression-discontinuity designs, quantile regression and standard errors
* Many empirical examples
* A clear and concise resource with wide applications