Posts

If you study enough econometrics or statistics, you’ll eventually hear someone mention “Stein’s Paradox” or the “James-Stein Estimator”. You’ve probably learned in your introductory econometrics course that ordinary least squares (OLS) is the best linear unbiased estimator (BLUE) in a linear regression model under the Gauss-Markov assumptions.

By the end of a typical introductory econometrics course students have become accustomed to the idea of “controlling” for covariates by adding them to the end of a linear regression model.

Here’s a slightly unusual exercise on the topic of Bayes’ Theorem for those of you teaching or studying introductory probability. Imagine that you’re developing a diagnostic test for a disease.

Reading and understanding econometrics papers can be hard work. Most published articles, even review articles, are written by specialists for specialists. Unless you’re already familiar with the literature, it can be a real uphill battle to make it through a recent paper.

As a teaser for our upcoming (2024-07-23) virtual reading group session on Bayesian macro / time series econometrics, this post replicates a classic paper by Sims & Uhlig (1991) contrasting Bayesian and Frequentist inferences for a unit root.

After a year-long hiatus, I’m excited to return to regular blogging about econometrics! I have a long list of posts that I’m eager to write, and I hope you’ll find them interesting.

Here’s a puzzle for you. What will happen if we regress some outcome of interest on both an endogenous regressor and a valid instrument for that regressor? I hadn’t thought about this question until 2018, when one of my undergraduate students asked it during class.

R’s formula syntax is extremely powerful but can be confusing for beginners.1 This post is a quick reference covering all of the symbols that have a “special” meaning inside of an R formula: ~, +, .

To do well in an econometrics or statistics course at any level, you need to have a large number of simple properties of random variables at your fingertips. Some years back I made a handout containing the most important properties for my undergraduate students at the University of Pennsylvania.

In econometrics it’s absolutely crucial to keep track of which things are dependent and which are independent. To make this as confusing as possible for students, a typical introductory econometrics course moves back and forth between different notions of dependence, stopping occasionally to mention that they’re not equivalent but never fully explaining why, on the premise that “you’ve certainly already learned this in your introductory probability and statistics course.