방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 패널 데이터 조밀화 정확 매칭× | 이중차분법 (Diff-in-Diff)× | |
|---|---|---|
| 분야≠ | 인과추론 | 계량경제학 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 2012 (CEM); 2021 (panel extension) | 1994 |
| 창시자≠ | Iacus, King & Porro (CEM, 2012); panel extension via Imai, Kim & Wang (2021) | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| 유형≠ | Matching / quasi-experimental | Causal inference / panel regression |
| 원전≠ | Iacus, S. M., King, G., & Porro, G. (2012). Causal Inference without Balance Checking: Coarsened Exact Matching. Political Analysis, 20(1), 1-24. DOI ↗ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| 별칭 | Panel CEM, CEM for panel data, coarsened exact matching with panel data | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| 관련≠ | 6 | 5 |
| 요약≠ | Panel Data Coarsened Exact Matching applies the Coarsened Exact Matching (CEM) algorithm to repeated-measures panel data, matching treated and control units within the same coarsened covariate strata across multiple time periods. It balances pre-treatment characteristics before estimating a causal treatment effect, combining the transparency of exact matching with the richer identification available in longitudinal datasets. | 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. |
| ScholarGate데이터셋 ↗ |
|
|