Mastering 'Metrics (häftad)
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Häftad (Paperback / softback)
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with French flaps
Princeton University Press
213 x 142 x 18 mm
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Mastering 'Metrics (häftad)

Mastering 'Metrics

The Path from Cause to Effect

Häftad Engelska, 2014-12-21
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Applied econometrics, known to aficionados as 'metrics, is the original data science. 'Metrics encompasses the statistical methods economists use to untangle cause and effect in human affairs. Through accessible discussion and with a dose of kung fu-themed humor, Mastering 'Metrics presents the essential tools of econometric research and demonstrates why econometrics is exciting and useful. The five most valuable econometric methods, or what the authors call the Furious Five--random assignment, regression, instrumental variables, regression discontinuity designs, and differences in differences--are illustrated through well-crafted real-world examples (vetted for awesomeness by Kung Fu Panda's Jade Palace). Does health insurance make you healthier? Randomized experiments provide answers. Are expensive private colleges and selective public high schools better than more pedestrian institutions? Regression analysis and a regression discontinuity design reveal the surprising truth. When private banks teeter, and depositors take their money and run, should central banks step in to save them? Differences-in-differences analysis of a Depression-era banking crisis offers a response. Could arresting O. J. Simpson have saved his ex-wife's life? Instrumental variables methods instruct law enforcement authorities in how best to respond to domestic abuse. Wielding econometric tools with skill and confidence, Mastering 'Metrics uses data and statistics to illuminate the path from cause to effect. * Shows why econometrics is important* Explains econometric research through humorous and accessible discussion* Outlines empirical methods central to modern econometric practice* Works through interesting and relevant real-world examples
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  1. Mastering 'Metrics
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  3. Mostly Harmless Econometrics

De som köpt den här boken har ofta också köpt Mostly Harmless Econometrics av Joshua D Angrist, Joern-Steffen Pischke (häftad).

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  • Mostly Harmless Econometrics

    Joshua D Angrist, Joern-Steffen Pischke

    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 moder...

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"I would be hard pressed to name another econometrics book that can be read for enjoyment yet provides useful quantitative insights."--M.S.R., Financial Analysts Journal

Övrig information

Joshua D. Angrist is the Ford 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. They are the authors of Mostly Harmless Econometrics (Princeton).


List of Figures vii List of Tables ix Introduction xi 1 Randomized Trials 1 1.1 In Sickness and in Health (Insurance) 1 1.2 The Oregon Trail 24 Masters of 'Metrics: From Daniel to R. A. Fisher 30 Appendix: Mastering Inference 33 2 Regression 47 2.1 A Tale of Two Colleges 47 2.2 Make Me a Match, Run Me a Regression 55 2.3 Ceteris Paribus? 68 Masters of 'Metrics: Galton and Yule 79 Appendix: Regression Theory 82 3 Instrumental Variables 98 3.1 The Charter Conundrum 99 3.2 Abuse Busters 115 3.3 The Population Bomb 123 Masters of 'Metrics: The Remarkable Wrights 139 Appendix: IV Theory 142 4 Regression Discontinuity Designs 147 4.1 Birthdays and Funerals 148 4.2 The Elite Illusion 164 Masters of 'Metrics: Donald Campbell 175 5 Differences-in-Differences 178 5.1 A Mississippi Experiment 178 5.2 Drink, Drank, ... 191 Masters of 'Metrics: John Snow 204 Appendix: Standard Errors for Regression DD 205 6 The Wages of Schooling 209 6.1 Schooling, Experience, and Earnings 209 6.2 Twins Double the Fun 217 6.3 Econometricians Are Known by Their ... Instruments 223 6.4 Rustling Sheepskin in the Lone Star State 235 Appendix: Bias from Measurement Error 240 Abbreviations and Acronyms 245 Empirical Notes 249 Acknowledgments 269 Index 271