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| 이종(heterogeneous) 처리 효과 패널 사건 연구× | 이중차분법 (Diff-in-Diff)× | |
|---|---|---|
| 분야≠ | 인과추론 | 계량경제학 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 2021 | 1994 |
| 창시자≠ | Sun & Abraham; Callaway & Sant'Anna | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| 유형≠ | Causal inference / quasi-experimental | Causal inference / panel regression |
| 원전≠ | Sun, L., & Abraham, S. (2021). Estimating dynamic treatment effects in event studies with heterogeneous treatment effects. Journal of Econometrics, 225(2), 175-199. DOI ↗ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| 별칭≠ | HTE panel event study, heterogeneous effects event study, staggered panel event study, CATT event study | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| 관련≠ | 4 | 5 |
| 요약≠ | A heterogeneous treatment effect panel event study estimates how treatment impacts vary across units and over time in a panel setting, allowing each cohort of treated units to have its own dynamic response. Seminal contributions by Sun and Abraham (2021) and Callaway and Sant'Anna (2021) showed that standard two-way fixed-effects event studies mask sign-reversing treatment heterogeneity across cohorts, motivating cohort-specific estimation followed by flexible aggregation. | Difference-in-Differences is a causal-inference method that estimates the effect of an intervention by comparing how a treatment group and a control group change over time. Made famous by Card and Krueger's 1994 minimum-wage study and developed in Angrist and Pischke's Mostly Harmless Econometrics, it isolates the treatment effect as the difference between the two groups' before-after changes. |
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