Blog Archives

The Frisch–Waugh–Lovell Theorem for Both OLS and 2SLS

June 5, 2013
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The Frisch–Waugh–Lovell Theorem for Both OLS and 2SLS

The Frisch–Waugh–Lovell (FWL) theorem is of great practical importance for econometrics. FWL establishes that it is possible to re-specify a linear regression model in terms of orthogonal complements. In other words, it permits econometricians to partial out right-hand-side, or control, variables. This is useful in a variety of settings. For example, there may be cases

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Kalkalash! Pinpointing the Moments “The Simpsons” became less Cromulent

April 30, 2013
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Kalkalash! Pinpointing the Moments “The Simpsons” became less Cromulent

Whenever somebody mentions “The Simpsons” it always stirs up feelings of nostalgia in me. The characters, uproarious gags, zingy one-liners, and edgy animation all contributed towards making, arguably, the greatest TV ever. However, it’s easy to forget that as a TV show “The Simpsons” is still ongoing—in its twenty-fourth season no less. For me, and

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texreg: A package for beautiful and easily customizable LaTeX regression tables from R

January 20, 2013
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texreg: A package for beautiful and easily customizable LaTeX regression tables from R

There was a very informative post last week showing how the R package stargazer is used to generate nice LaTeX tables from a number of R objects. This package looks very useful. However, I would like to extol the virtues of another R package that converts model objects in R into LaTeX code: texreg. For

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The Cluster Bootstrap

January 12, 2013
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The Cluster Bootstrap

Adjusting standard errors for clustering can be a very important part of any statistical analysis. For example, duplicating a data set will reduce the standard errors dramatically despite there being no new information. I have previously dealt with this topic with reference to the linear regression model. However, in many cases one would like to

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Identical Champions League Draw: What Were the Odds?

December 24, 2012
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Identical Champions League Draw: What Were the Odds?

A number of news outlets have reported a peculiar quirk that arose during Friday’s Champions League draw. Apparently, the sport’s European governing body, UEFA, ran a trial run the day before the main event, and the schedule chosen during this event was identical to that of the actual draw on Friday. Given this strange coincidence,

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Linear Models with Multiple Fixed Effects

December 11, 2012
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Linear Models with Multiple Fixed Effects

Estimating a least squares linear regression model with fixed effects is a common task in applied econometrics, especially with panel data. For example, one might have a panel of countries and want to control for fixed country factors. In this case the researcher will effectively include this fixed identifier as a factor variable, and then proceed to

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Minimizing Bias in Observational Studies

November 26, 2012
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Minimizing Bias in Observational Studies

Measuring the effect of a binary treatment on a measured outcome is one of the most common tasks in applied statistics. Examples of these applications abound, like the effect of smoking on health, or the effect of low birth weight on cognitive development. In an ideal world we would like to be able to assign

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Heteroskedastic GLM in R

November 20, 2012
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Heteroskedastic GLM in R

A commenter on my previous blog entry has drawn my attention to an R function called hetglm() that estimates heteroskedastic probit models. This function is contained in the glmx package. The glmx package is not available on CRAN yet, but thankfully can be downloaded here. The hetglm() function has a number of computational advantages compared with

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The Heteroskedastic Probit Model

November 19, 2012
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The Heteroskedastic Probit Model

Specification testing is an important part of econometric practice. However, from what I can see, few researchers perform heteroskedasticity tests after estimating probit/logit models. This is not a trivial point. Heteroskedasticity in these models can represent a major violation of the probit/logit specification, both of which assume homoskedastic errors. Thankfully, tests for heteroskedasticity in these

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BMR: Bayesian Macroeconometrics in R

September 4, 2012
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BMR: Bayesian Macroeconometrics in R

The recently released BMR package, short for Bayesian Macroeconometrics with R, provides a comprehensive set of powerful routines that estimate Bayesian Vector Autoregression (VAR) and Dynamic Stochastic General Equilibrium (DSGE) models in R. The procedure of estimating both Bayesian VAR and DSGE models can represent a great computational burden. However, BMR removes a lot of

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