Instrumental variable (IV) estimation is an important technique in causal inference and applied empirical work. Continue reading You Can’t Test Instrument Validity
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Some time ago I wrote about a paper by Arthur Lewbel in the Journal of Business & Economic Statistics in which he develops a method to do two-stage least squares regressions without actually having an exclusion restrictions in the model. The approach relies on higher moment restrictions in the error matrix and works well for linear or partly linear models. Back then, I expressed concerns that the estimator does not seem to work when an endogenous regressor is binary though; at least not in the simulations I have carried out.
After a bit of email back-and-forth we were able to settle the debate now. Continue reading Follow-up on “IV regressions without instruments” (technical)
Arthur Lewbel published a very interesting paper back in 2012 in the Journal of Business & Economic Statistics (ungated version here). The paper attracted quite some attention because it lays out a method to do two-stage least squares regressions (in order to identify causal effects) without the need for an outisde instrumental variable. Continue reading IV regressions without instruments (technical)
Wolfram Schenker from Columbia University gave a talk about the impact of climate change on agricultural production at ZEW. The part which struck me the most, I found out later, is part of a paper published in the American Economic Review (Roberts and Schlenker, 2013). Seems like I have a good taste… Continue reading The Econ 101 of Agriculture