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단행본2024년 4월 TOP 10

The Effect: An Introduction to Research Design and Causality

청구기호
530.01 EFF2022
발행사항
Boca Raton : CRC Press, Taylor&Francis Group , 2022
형태사항
619 p
서지주기
Includes bibliographical references and index
일반주기
"A Chapman & Hall book."
ISBN
9781032125787
소장정보
위치등록번호청구기호 / 출력상태반납예정일
지금 이용 불가 (1)
한국노동연구원00009846대출중2024.10.04
지금 이용 불가 (1)
  • 등록번호
    00009846
    상태/반납예정일
    대출중
    2024.10.04
    위치/청구기호(출력)
    한국노동연구원
책 소개

The Effect: An Introduction to Research Design and Causality is about research design, specifically concerning research that uses observational data to make a causal inference. It is separated into two halves, each with different approaches to that subject. The first half goes through the concepts of causality, with very little in the way of estimation. It introduces the concept of identification thoroughly and clearly and discusses it as a process of trying to isolate variation that has a causal interpretation. Subjects include heavy emphasis on data-generating processes and causal diagrams.

Concepts are demonstrated with a heavy emphasis on graphical intuition and the question of what we do to data. When we “add a control variable” what does that actually do?

Key Features:

  •  ? Extensive code examples in R, Stata, and Python
  • ? Chapters on overlooked topics in econometrics classes: heterogeneous treatment effects, simulation and power analysis, new cutting-edge methods, and uncomfortable ignored assumptions
  • ? An easy-to-read conversational tone
  • ? Up-to-date coverage of methods with fast-moving literatures like difference-in-differences

 



The Effect: An Introduction to Research Design and Causality is about research design, specifically concerning research that uses observational data to make a causal inference. It is separated into two halves, each with different approaches to that subject. 



목차

Chapter 1 Designing Research Chapter 2 Research Questions Chapter 3 Describing Variables Chapter 4 Describing Relationships Chapter 5 Identification Chapter 6 Causal Diagrams Chapter 7 Drawing Causal Diagrams Chapter 8 Causal Paths and Closing Back Doors Chapter 9 Finding Front Doors Chapter 10 Treatment Effects Chapter 11 Causality with Less Modeling Chapter 12 Opening the Toolbox Chapter 13 Regression Chapter 14 Matching Chapter 15 Simulation Chapter 16 Fixed Effects Chapter 17 Event Studies Chapter 18 Difference-in-Differences Chapter 19 Instrumental Variables Chapter 20 Regression Discontinuity Chapter 21 A Gallery of Rogues: Other Methods Chapter 22 Under the Rug