Mostly Harmless Econometrics
В основном безвредная эконометрика
2009-12-31
SCID: 54.1/nx3ew9nf
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difference-in-differencesinstrumental variableslinear regressionquantile regressionregression discontinuity
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Abstract (AI)
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 applications
Key Findings
1
It extends the standard toolkit with regression-discontinuity designs, quantile regression, and guidance on obtaining valid standard errors.
2
The authors argue that sophisticated econometric techniques are often unnecessary and can be dangerous in applied research.
3
The book illustrates econometric methods through numerous empirical examples addressing questions such as education, class size, and policy responses to domestic violence.
4
The book presents linear regression, instrumental variables, and differences-in-differences as core tools for answering clear causal questions in applied econometrics.
5
The methods emphasized are designed to be easy to use, empirically grounded, and broadly applicable across contemporary social science.
Research Object
applied econometric analyses of causal questions in contemporary social-science data
Research Subject
the use and interpretation of linear regression, instrumental variables, differences-in-differences, regression-discontinuity, and quantile-regression methods, including appropriate standard-error estimation, for causal inference
Publication Details
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2009-12-31
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