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Mostly Harmless Econometrics: An Empiricist's Companion

TLDR
The core methods in today's econometric toolkit are linear regression for statistical control, instrumental variables methods for the analysis of natural experiments, and differences-in-differences methods that exploit policy changes.
Abstract
The core methods in today's econometric toolkit are linear regression for statistical control, instrumental variables methods for the analysis of natural experiments, and differences-in-differences methods that exploit policy changes. In the modern experimentalist paradigm, these techniques address clear causal questions such as: Do smaller classes increase learning? Should wife batterers be arrested? How much does education raise wages? Mostly Harmless Econometrics shows how the basic tools of applied econometrics allow the data to speak. In addition to econometric essentials, Mostly Harmless Econometrics covers important new extensions--regression-discontinuity designs and quantile regression--as well as how to get standard errors right. Joshua Angrist and Jorn-Steffen Pischke explain why fancier econometric techniques are typically unnecessary and even dangerous. The applied econometric methods emphasized in this book are easy to use and relevant for many areas of contemporary social science. An irreverent review of econometric essentials A focus on tools that applied researchers use most Chapters on regression-discontinuity designs, quantile regression, and standard errors Many empirical examples A clear and concise resource with wide applications

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Journal ArticleDOI

A Practitioner’s Guide to Cluster-Robust Inference

TL;DR: This work considers statistical inference for regression when data are grouped into clusters, with regression model errors independent across clusters but correlated within clusters, when the number of clusters is large and default standard errors can greatly overstate estimator precision.
Journal ArticleDOI

Recent developments in the econometrics of program evaluation

TL;DR: In the last two decades, much research has been done on the econometric and statistical analysis of such causal effects as discussed by the authors, which has reached a level of maturity that makes it an important tool in many areas of empirical research in economics, including labor economics, public finance, development economics, industrial organization, and other areas in empirical microeconomics.
Journal ArticleDOI

Mendelian randomization analysis with multiple genetic variants using summarized data.

TL;DR: It is concluded that Mendelian randomization investigations using summarized data from uncorrelated variants are similarly efficient to those using individual‐level data, although the necessary assumptions cannot be so fully assessed.
Book ChapterDOI

Endogeneity in Empirical Corporate Finance1

TL;DR: In this paper, applied researchers in corporate finance can address endogeneity concerns, including omitted variables, simultaneity, and measurement error, and discuss a number of econometric techniques aimed at addressing endogeneity problems, including instrumental variables, difference-in-differences estimators, regression discontinuity design, matching methods, panel data methods, and higher order moments estimators.