Monday, December 22, 2014

Econ(ometrics) Talk

I just recently purchased Angrist and Pischke's "Mastering Metrics" (HT Marc Bellemare). And timely, today's EconTalk podcast featured Josh Angrist:

"Joshua Angrist of the Massachusetts Institute of Technology talks to EconTalk host Russ Roberts about the craft of econometrics--how to use economic thinking and statistical methods to make sense of data and uncover causation. Angrist argues that improvements in research design along with various econometric techniques have improved the credibility of measurement in a complex world. Roberts pushes back and the conversation concludes with a discussion of how to assess the reliability of findings in controversial public policy areas."

I've mentioned their previous book, Mostly Harmless Econometrics on this blog many times before and had some actual interaction with the authors via their related blog where I asked a regression/matching related question. I have described their book as an off-road backwoods survival manual for practitioners.
To say the least I am looking forward to the podcast and reading their latest book.

Some related Posts:

Angrist and Pischke on Linear Probabiity Models
Applied Econometrics
Quasi-Experimental Design Roundup
Analytics vs Causal Inference
The Oregon Experiment, Applied Econometrics, and Causal Inference
The Oregon Experiment and Linear Probability Models

Some related EconTalk podcasts that I highly recommend:

Leamer on the State of Econometrics
Manzi on the Oregon Medicaid Study
Manzi on Knowledge, Policy, and Uncontroled

Tuesday, December 2, 2014

A Cookbook Econometrics Analogy

Previously I wrote a post on applied econometrics, which really was not all that original. It was motivated by a previous post made by Marc Bellemare and Dave Giles, and I just added some commentary on my personal experience as well as some quotes from Peter Kennedy's A Guide to Econometrics.

Since then, I've been reading Kennedy's chapter on applied econometrics in greater detail (I have a 6th edition copy) and I found the following interesting analogy. Typically cookbook analogies relate negatively to practitioners mind numbingly running regressions and applying tests etc. without strong appreciation for the underlying theory, but this is of a different flavor and to me gives a good impression of what 'doing econometrics' actually feels like:

From The Valavanis (1959, p.83) in Kennedy 6th Edition:

"Econometric theory is like an exquisitely balanced French recipe, spelling out precisely with how many turns to mix the sauce, how many carats of spice to add, and for how many milliseconds to bake the mixture at exactly 474 degrees of temperature. But when the statistical cook turns to raw materials, he finds that hearts of cactus fruit are unavailable, so he substitutes chunks of cantaloupe; where the recipe calls for vermicelli he used shredded wheat; and he substitutes green garment die for curry, ping-pong balls for turtles eggs, and for Chalifougnac vintage 1883, a can of turpentine."

It really gets uncomfortable when you are presenting at a seminar or conference or other audeince and someone that isn't elbow deep in the data challenges points out that your estimator isn't valid theoretically because you used 'turpentine' when the recipe (or econometric theory) calls for  Chalifougnac vintage 1883 or someone well-versed in theory but unaware of the social norms of applied econometrics tries to make you look incompetent by pointing out this 'mistake.'

Also gives me  That Modeling Feeling.