株式会社極東書店トップ ＞ 商品一覧 ＞ Causal Inference with Differences-in-Differences: Credible Answers to Hard Questions.
商品詳細
Causal Inference with Differences-in-Differences: Credible Answers to Hard Questions.
・ISBN 978-0-691-26417-2 hard US$ 120.00
￥28,116.- (税込) ※（※）価格はご注文時の参考価格となります。
納品価格につきましては書籍の入荷時点で確定となります。
版元の原価改定、外国為替の変動等により異なる場合がございますので、予めご了承下さい。
| 著者・編者 | de Chaisemartin, Clement / D'Haultfoeuille, Xavier, |
|---|---|
| 出版社 | (Princeton University Press, US) |
| 出版年月 | 2026 |
| ページ数 | 360 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A05-74504＞ |
解説
A comprehensive, rigorous introduction to modern differences-in-differences (DID) estimators, covering both standard practices and alternatives
Differences-in-differences (DID) is one of the most widely used methods for impact-evaluation in economics and the social sciences. The key idea behind DiD is to compare outcomes trends for treated and control groups, allowing researchers to estimate the effects of policies or interventions when randomized experiments are not feasible. This book provides a clear and rigorous guide to modern DID methods, covering both classical approaches and newer estimators developed for complex real-world settings. Designed for advanced undergraduate students, graduate students, and applied researchers, it explains when standard methods are reliable, when they can mislead, and how alternative approaches can provide more credible results. Throughout, theoretical discussion is paired with empirical applications, exercises using real datasets, and practical recommendations for implementation.
The book offers:
* Discussion of all designs in which DID apply: classical designs, staggered adoption designs, designs with variation in treatment dose, and staggered first switch designs
* Study of standard estimators, estimators without parallel trends (e.g., synthetic controls), and heterogeneity-robust estimators
* 5 lists of dos and don'ts for practitioners
* 150 exercises to understand the theory, and 50 practical exercises to apply it to real empirical examples in Stata and R