Blunt Instruments

"Blunt Instruments: Avoiding Common Pitfalls in Identifying the Causes of Economic Growth" by Samuel Bazzi and Michael Clemens is an interesting read. I have long thought that it is hard to find valid instrumental variables in macroeconomics, this paper provides lots of evidence for this.

So-called "endogeneity" of explanatory variables in regression analysis is mainly due to the following:

• Reverse causality - Feedback from the dependent variable to the explanatory variable.
• Omitted variables bias - When variables that are correlated with the included variables and the dependent variable are excluded from the regression, the included variables are attributed as explaining too much or too little of the variance in the dependent variable.
• Measurement error - When there is error in measuring the explanatory variables their regression coefficients tend to be biased towards zero.

All of these lead to correlation between the explanatory variables and the true underlying error term (but by design not to the actual estimated regression residuals). One approach to dealing with these issues is instrumental variables regression where variables that are correlated with the explanatory variables but supposedly not with the true residuals are introduced. The instrumental variable estimates effectively only use the part of the explanatory variables associated with the variation in the instrument in estimating the regression coefficient. Bazzi and Clemens point out that there are many pairs of econometric studies that claim to have found the same strong and valid instruments for different explanatory variables but don't include the explanatory variables included in the other studies in their models. If a study finds an instrumental variable is strongly correlated with an explanatory variable and it is used as an instrument in another study that doesn't include the explanatory variable in question then the instrument must be invalid as it will be correlated with the error term. Bazzi and Clemens show that many studies published in top journals suffer from these problems.

Of course, there is much more in the paper, but I think that is the key point.