Mostly Harmless Econometrics
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Mostly Harmless Econometrics : An Empiricist's Companion

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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 applicationsshow more

Product details

  • Paperback | 392 pages
  • 139.7 x 213.36 x 27.94mm | 544.31g
  • Princeton University Press
  • New Jersey, United States
  • English
  • 8 halftones. 17 line illus. 26 tables.
  • 0691120358
  • 9780691120355
  • 8,381

Review quote

"This book is an extremely thought-provoking contribution to the literature. It champions a different paradigm to that characterising most econometrics texts and does so with considerable (idiosyncratic) style and grace. Highly recommended!"--David Harris and Christopher L. Skeels, Economic Record "[T]he matter covered in the book is surely of interest to most agricultural economists. Even if it is not a complete overview of existing econometric research methods, it certainly contains a good deal of hands on advice driven by years of experience."--European Review of Agricultural Economics "The applied econometric methods emphasized in this book are easy to use and relevant for many areas of contemporary social sciences."--Pavel Stoynov, Zentralblatt MATH "I'd recommend it to the entire range of empirical economists, from those still in training to those who, like me, have only a hazy memory of statistical theory and stick to our tried and tested methods of estimation . . . an excellent guide to how to do basic regression/IV/panel data estimation really well. In particular, it demonstrates through many examples how to bring about a happy marriage between one's underlying model and the data which might or might not confirm the researcher's hypotheses."--Diane Coyle, The Enlightened Economist Blog "A quirky and thought-provoking read for any budding econometrician. . . . Insightful and refreshing."--James Davidson, Times Higher Educationshow more

Back cover copy

"This pathbreaking book is a must-read for any scientist who is interested in formulating and testing hypotheses about the social world. This includes political scientists, sociologists, historians, geographers, and anthropologists. The book is clever and funny, and guides you through the tangle of problems that confront empirical research in social science. I wish I had had it years ago."--James Robinson, Harvard University "What a fascinating and useful book! The application of econometrics in empirical research is as much art as science. What is most distinctive about Mostly Harmless Econometrics relative to other graduate-level econometrics books (besides the colorful prose style!) is that because the authors are longtime practitioners of applied microeconometrics, they speak often and insightfully about the art. I expect it's a great thing to work in the same department with Angrist or Pischke and to be able to ask their advice. Having this book close at hand is the next best thing. When you consult the book to see 'What would Angrist and Pischke do?' about econometric issues you encounter in your own research, you won't necessarily end up doing what they would in every single instance, but I bet you always will benefit from getting their take on the issue."--Gary Solon, Michigan State University "Interesting and unusual, this is an econometrics book with attitude. It offers real answers and suggestions to problems faced daily by those engaged in the analysis of economic data. I will recommend it to my students."--Guido Imbens, Harvard University "A well-written and very quirky take on econometric practice."--Orley Ashenfelter, Princeton Universityshow more

About J.D. Angrist

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.show more

Table of contents

List of Figures viiList of Tables ixPreface xiAcknowledgments xvOrganization of This Book xviiPART I: PRELIMINARIES 1Chapter 1: Questions about Questions 3Chapter 2: The Experimental Ideal 112.1 The Selection Problem 122.2 Random Assignment Solves the Selection Problem 152.3 Regression Analysis of Experiments 22PART II: THE CORE 25Chapter 3: Making Regression Make Sense 273.1 Regression Fundamentals 283.2 Regression and Causality 513.3 Heterogeneity and Nonlinearity 683.4 Regression Details 913.5 Appendix: Derivation of the Average Derivative Weighting Function 110Chapter 4: Instrumental Variables in Action: Sometimes You Get What You Need 1134.1 IV and Causality 1154.2 Asymptotic 2SLS Inference 1384.3 Two-Sample IV and Split-Sample IV 1474.4 IV with Heterogeneous Potential Outcomes 1504.5 Generalizing LATE 1734.6 IV Details 1884.7 Appendix 216Chapter 5: Parallel Worlds: Fixed Effects, Differences-in-Differences, and Panel Data 2215.1 Individual Fixed Effects 2215.2 Differences-in-Differences 2275.3 Fixed Effects versus Lagged Dependent Variables 2435.4 Appendix: More on Fixed Effects and Lagged Dependent Variables 246PART III: EXTENSIONS 249Chapter 6: Getting a Little Jumpy: Regression Discontinuity Designs 2516.1 Sharp RD 2516.2 Fuzzy RD Is IV 259Chapter 7: Quantile Regression 2697.1 The Quantile Regression Model 2707.2 IV Estimation of Quantile Treatment Effects 283Chapter 8: Nonstandard Standard Error Issues 2938.1 The Bias of Robust Standard Error Estimates 2948.2 Clustering and Serial Correlation in Panels 3088.3 Appendix: Derivation of the Simple Moulton Factor 323Last Words 327Acronyms and Abbreviations 329Empirical Studies Index 335References 339Index 361show more

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407 ratings
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4 36% (148)
3 17% (71)
2 7% (28)
1 2% (7)
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