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Causal Inference: The Mixtape [Pehme köide]

  • Formaat: Paperback / softback, 584 pages, kõrgus x laius x paksus: 216x140x30 mm, 119 b-w illus.
  • Ilmumisaeg: 16-Feb-2021
  • Kirjastus: Yale University Press
  • ISBN-10: 0300251688
  • ISBN-13: 9780300251685
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  • Formaat: Paperback / softback, 584 pages, kõrgus x laius x paksus: 216x140x30 mm, 119 b-w illus.
  • Ilmumisaeg: 16-Feb-2021
  • Kirjastus: Yale University Press
  • ISBN-10: 0300251688
  • ISBN-13: 9780300251685
An accessible, contemporary introduction to the methods for determining cause and effect in the social sciences   Causation versus correlation has been the basis of argumentseconomic and otherwisesince the beginning of time. Causal Inference: The Mixtape uses legit real-world examples that I found genuinely thought-provoking. Its rare that a book prompts readers to expand their outlook; this one did for me.Marvin Young (Young MC)

Causal inference encompasses the tools that allow social scientists to determine what causes what. In a messy world, causal inference is what helps establish the causes and effects of the actions being studiedfor example, the impact (or lack thereof) of increases in the minimum wage on employment, the effects of early childhood education on incarceration later in life, or the influence on economic growth of introducing malaria nets in developing regions. Scott Cunningham introduces students and practitioners to the methods necessary to arrive at meaningful answers to the questions of causation, using a range of modeling techniques and coding instructions for both the R and the Stata programming languages.

Arvustused

A new guide to methods for determining cause and effect in the social sciences. In summarising, systematising and prioritising methodological tools for researchers, this book will be of use to all social scientists looking to validate their quantitative findings.Simeon Mitropolitski, LSE Review of Books

Causation versus correlation has been the basis of argumentseconomic and otherwisesince the beginning of time. Causal Inference: The Mixtape uses legit real-world examples that I found genuinely thought-provoking. Its rare that a book prompts readers to expand their outlook; this one did for me.Marvin Young (Young MC)

Cunninghams brilliant book is that rare statistical treatise written for students and practitioners alike. Engaging language and vivid examples bring the tools of causal inference to a broad audience. Read the book, absorb its lessons, and youll develop the skills you need to credibly assess whether a statistics class, a public policy, or a new business practice truly makes a difference.Justin Wolfers, University of Michigan

Accessible and engaging. An excellent introduction to the statistics of causal inference.Alberto Abadie, MIT

Learning about causal effects is the main goal of most empirical research in economics. In this engaging book, Scott Cunningham provides an accessible introduction to this area, full of wisdom and wit and with detailed coding examples for practitioners.Guido Imbens, coauthor of Causal Inference

This book will probably shock economics instructors with the clarity, insights, and tools that modern graphical models introduce to the teaching of econometrics. The benefits will outlast the shock.Judea Pearl, University of California, Los Angeles

Acknowledgments ix
Introduction 1(15)
What Is Causal Inference?
3(3)
Do Not Confuse Correlation with Causality
6(2)
Optimization Makes Everything Endogenous
8(2)
Example: Identifying Price Elasticity of Demand
10(4)
Conclusion
14(2)
Probability and Regression Review
16(80)
Directed Acyclic Graphs
96(23)
Introduction to DAG Notation
97(22)
Potential Outcomes Causal Model
119(56)
Physical Randomization
123(25)
Randomization Inference
148(26)
Conclusion
174(1)
Matching and Subclassification
175(66)
Sub-classification
175(16)
Exact Matching
191(7)
Approximate Matching
198(43)
Regression Discontinuity
241(74)
Huge Popularity of Regression Discontinuity
241(11)
Estimation Using an RDD
252(30)
Challenges to Identification
282(7)
Replicating a Popular Design: The Close Election
289(23)
Regression Kink Design
312(1)
Conclusion
313(2)
Instrumental Variables
315(71)
History of Instrumental Variables: Father and Son
315(4)
Intuition of Instrumental Variables
319(4)
Homogeneous Treatment Effects
323(6)
Parental Methamphetamine Abuse and Foster Care
329(8)
The Problem of Weak Instruments
337(9)
Heterogeneous Treatment Effects
346(6)
Applications
352(7)
Popular IV Designs
359(25)
Conclusion
384(2)
Panel Data
386(20)
DAG Example
386(2)
Estimation
388(8)
Data Exercise: Survey of Adult Service Providers
396(9)
Conclusion
405(1)
Difference-in-Differences
406(105)
John Snow's Cholera Hypothesis
406(5)
Estimation
411(12)
Inference
423(2)
Providing Evidence for Parallel Trends Through Event Studies and Parallel Leads
425(8)
The Importance of Placebos in DD
433(28)
Twoway Fixed Effects with Differential Timing
461(48)
Conclusion
509(2)
Synthetic Control
511(29)
Introducing the Comparative Case Study
511(14)
Prison Construction and Black Male Incarceration
525(15)
Conclusion 540(1)
Bibliography 541(14)
Permissions 555(6)
Index 561
Scott Cunningham is professor of economics at Baylor University. He is also coeditor of The Oxford Handbook of the Economics of Prostitution.