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| 비선형 동적 패널 데이터 모형× | 동적 패널 데이터 모형× | |
|---|---|---|
| 분야 | 계량경제학 | 계량경제학 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1981-2005 | 1988–1991 |
| 창시자≠ | Wooldridge (2005); Honore & Tamer (2006); building on Heckman (1981) | Arellano & Bond (1991); Holtz-Eakin, Newey & Rosen (1988) |
| 유형≠ | Dynamic panel estimator with nonlinear response | Dynamic regression / GMM estimation |
| 원전≠ | Wooldridge, J. M. (2005). Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity. Journal of Applied Econometrics, 20(1), 39-54. 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 | nonlinear dynamic panel, dynamic nonlinear panel estimator, NDPDM, nonlinear panel with lagged dependent variable | dynamic panel model, panel data model with lagged dependent variable, DPD model, Arellano-Bond model |
| 관련≠ | 3 | 5 |
| 요약≠ | The nonlinear dynamic panel data model extends standard panel methods to settings where the outcome is binary, count-valued, or censored and where past realizations of the outcome directly affect current ones. It handles unobserved individual heterogeneity alongside state dependence, disentangling genuine persistence from spurious persistence driven by unmeasured unit characteristics. | 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. |
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