Mostly Harmless Econometrics (An Empiricist's Companion)

ISBN: 9780691120355
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$55.00
SKU:
9780691120355
Availability:
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Minimum Purchase:
25 units
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Product Details

Author:
Joshua D. Angrist, Jörn-Steffen Pischke
Format:
Paperback
Pages:
392
Publisher:
Princeton University Press (January 4, 2009)
Imprint:
Princeton University Press
Language:
English
Audience:
College/higher education
ISBN-13:
9780691120355
ISBN-10:
0691120358
Weight:
16.32oz
Dimensions:
5.5" x 8.5"
File:
PrincetonUniversityPress-Metadata_Only_Princeton_University_Press_Metadata_20250719062448-20250719.xml
Folder:
PrincetonUniversityPress
List Price:
$55.00
Country of Origin:
United States
Pub Discount:
37
Case Pack:
32
As low as:
$48.40
Publisher Identifier:
P-MISC
Discount Code:
H

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Overview

From Joshua Angrist, winner of the Nobel Prize in Economics, and Jörn-Steffen Pischke, an irreverent guide to the essentials of econometrics

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 Jörn-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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