Mostly Harmless Econometrics: An Empiricist’s Companion


We had the benefit of comments from many friends and colleagues as this project progressed. Special thanks are due to Alberto Abadie, David Autor, Amitabh Chandra, Monica Chen, John DiNardo, Joe Doyle, Jerry Hausman, Andrea Ichino, Guido Imbens, Rafael Lalive, Alan Manning, Karen Norberg, Barbara Petrongolo, James Robinson, Tavneet Suri, and Jeff Wooldridge, who reacted to the draft at various stages. They are not to blame for our presumptuousness or remaining mistakes. Thanks also go to our students at LSE and MIT. They saw the material first and helped us decide what’s important. We would especially like to acknowledge the skilled and tireless research assistance of Brigham Frandsen, Cynthia Kinnan, and Chris Smith. We’re also grateful for the support and guidance of Tim Sullivan and Seth Ditchik, our editors at Princeton University Press. Last, certainly not least, we thank our wives for their love and support; they know better than anyone what it means to be an empiricist’s companion.

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Mostly Harmless Econometrics: An Empiricist’s Companion

Regression Details

1.4.1 Weighting Regression Few things are as confusing to applied researchers as the role of sample weights. Even now, 20 years post - Ph. D., we read the section of …

Getting a Little Jumpy: Regression Discontinuity Designs

But when you start exercising those rules, all sorts of processes start to happen and you start to find out all sorts of stuff about people... Its just a way …

Two-Sample IV and Split-Sample IVF

GLS estimates of Г in (4.3.1) are consistent because E The 2SLS minimand can be thought of as GLS applied to equation (4.3.1), after multiplying by /N to keep the …

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