Mastering 'Metrics (eBook)

The Path from Cause to Effect
eBook Download: EPUB
2014
304 Seiten
Princeton University Press (Verlag)
978-1-4008-5238-3 (ISBN)

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Mastering 'Metrics -  Joshua D. Angrist,  Jorn-Steffen Pischke
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From Joshua Angrist, winner of the Nobel Prize in Economics, and Jorn-Steffen Pischke, an accessible and fun guide to the essential tools of econometric researchApplied 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 futhemed 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 Fiverandom assignment, regression, instrumental variables, regression discontinuity designs, and differences in differencesare 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 importantExplains econometric research through humorous and accessible discussionOutlines empirical methods central to modern econometric practiceWorks through interesting and relevant real-world examples

Joshua D. Angrist is the Ford Professor of Economics at the Massachusetts Institute of Technology. Jörn-Steffen Pischke is professor of economics at the London School of Economics and Political Science. They are the authors of Mostly Harmless Econometrics (Princeton).

Erscheint lt. Verlag 21.12.2014
Verlagsort Princeton
Sprache englisch
Themenwelt Wirtschaft Volkswirtschaftslehre Ökonometrie
Schlagworte Accuracy and precision • Addition • Attendance • average treatment effect • Boston Latin School • Calculation • Central Bank • central limit theorem • Ceteris paribus • coefficient • conditional expectation • Confidence interval • Control variable • Covariate • Cross-Sectional Data • data set • debt • diploma • Domestic violence • Dummy variable (statistics) • Econometrics • Economic Growth • Economics • economist • editorial • Educational attainment • Equation • Errors and residuals • estimation • Estimator • expected value • Follow-up • fourth grade • graduation rate • health insurance • high school diploma • High school rank • income • inference • ingredient • instrumental variable • insurance • insurance coverage • law of large numbers • Least Squares • linear regression • Manuscript • Medicaid • monetary policy • mortality rate • National Health Interview Survey • natural experiment • Normal distribution • Notation • Observational error • Ordinary Least Squares • Outcome (probability) • Parameter • Percentage point • Princeton University Press • Private School • private university • Probability • proofreading • Proportionality (mathematics) • Quantity • RAND Health Insurance Experiment • Random assignment • Randomization • Randomized experiment • Regression Analysis • regression discontinuity design • Regression model • Requirement • Residual sum of squares • Sample Size • Sample (statistics) • Sampling (Statistics) • SAT • saving • school choice • scientific notation • Selection bias • sibling • Simple Linear Regression • Special case • standard deviation • standard error • Statistic • Statistical Inference • statistical significance • student loan • Tax • Test score • Treatment and control groups • Variable (mathematics) • Variance • Weighted arithmetic mean • weighting • year
ISBN-10 1-4008-5238-2 / 1400852382
ISBN-13 978-1-4008-5238-3 / 9781400852383
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