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Mostly Harmless Econometrics An Empiricist's Companion

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ISBN-10: 0691120358

ISBN-13: 9780691120355

Edition: 2008

Authors: J�rn-Steffen Pischke, Joshua D. Angrist, Joshua D. Angrist, Joshua David Angrist

List price: $42.00
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Description:

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 Econometricsshows how the basic tools of applied econometrics allow the data to speak. In addition to econometric essentials,Mostly Harmless Econometricscovers important new extensions--regression-discontinuity designs and quantile regression--as well as how to get standard errors right. Joshua Angrist and Jouml;rn-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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Book details

List price: $42.00
Copyright year: 2008
Publisher: Princeton University Press
Publication date: 1/4/2009
Binding: Paperback
Pages: 392
Size: 5.50" wide x 8.25" long x 1.25" tall
Weight: 1.122
Language: English

Joshua D. Angrist is professor of economics at the Massachusetts Institute of Technology. Jorn-Steffen Pischke is professor of economics at the London School of Economics and Political Science.

List of Figures
List of Tables
Preface
Acknowledgments
Organization of This Book
Preliminaries
Questions about Questions
The Experimental Ideal
The Selection Problem
Random Assignment Solves the Selection Problem
Regression Analysis of Experiments
The Core
Making Regression Make Sense
Regression Fundamentals
Regression and Causality
Heterogeneity and Nonlinearity
Regression Details
Appendix: Derivation of the Average Derivative Weighting Function
Instrumental Variables in Action: Sometimes You Get What You Need
IV and Causality
Asymptotic 2SLS Inference
Two-Sample IV and Split-Sample IV
IV with Heterogeneous Potential Outcomes
Generalizing LATE
IV Details
Appendix
Parallel Worlds: Fixed Effects, Differences-in-Differences, and Panel Data
Individual Fixed Effects
Differences-in-Differences
Fixed Effects versus Lagged Dependent Variables
Appendix: More on Fixed Effects and Lagged Dependent Variables
Extensions
Getting a Little Jumpy: Regression Discontinuity Designs
Sharp RD
Fuzzy RD Is IV
Quantile Regression
The Quantile Regression Model
IV Estimation of Quantile Treatment Effects
Nonstandard Standard Error Issues
The Bias of Robust Standard Error Estimates
Clustering and Serial Correlation in Panels
Appendix: Derivation of the Simple Moulton Factor
Last Words
Acronyms and Abbreviations
Empirical Studies Index
References
Index