방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 구조적 단절 차분 GMM× | 동적 패널 데이터 모형× | |
|---|---|---|
| 분야 | 계량경제학 | 계량경제학 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1991 / 1998 | 1988–1991 |
| 창시자≠ | Arellano & Bond (Difference GMM); Bai & Perron (structural break testing) | Arellano & Bond (1991); Holtz-Eakin, Newey & Rosen (1988) |
| 유형≠ | Dynamic panel estimator with structural breaks | Dynamic regression / GMM estimation |
| 원전≠ | Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. The Review of Economic Studies, 58(2), 277–297. DOI ↗ | Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies, 58(2), 277–297. DOI ↗ |
| 별칭 | Difference GMM with structural breaks, break-augmented Arellano-Bond GMM, dynamic panel GMM with regime shifts, structural change Difference GMM | dynamic panel model, panel data model with lagged dependent variable, DPD model, Arellano-Bond model |
| 관련≠ | 6 | 5 |
| 요약≠ | Structural Break Difference GMM extends the Arellano-Bond first-difference GMM estimator to dynamic panel settings where the data-generating process shifts at one or more unknown breakpoints. By explicitly incorporating break indicators or allowing regime-specific parameters, the estimator avoids the biased coefficient and invalid moment conditions that arise when a structural change is ignored in a standard Difference GMM fit. | The dynamic panel data model extends standard panel regression by including a lagged value of the outcome variable as a regressor, capturing persistence and adjustment dynamics. Because the lagged dependent variable is correlated with the unit-specific fixed effect, ordinary OLS or within estimators are biased; GMM-based methods using internal instruments are the standard remedy. |
| ScholarGate데이터셋 ↗ |
|
|