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| 베이지안 차분 GMM× | 베이지안 동적 패널 데이터 모형× | |
|---|---|---|
| 분야 | 계량경제학 | 계량경제학 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1991/2003 | 2002–2007 |
| 창시자≠ | Arellano & Bond (1991) for Difference GMM; Chernozhukov & Hong (2003) for Bayesian GMM framework | Hsiao, Pesaran, Tahmiscioglu; Arellano & Bonhomme |
| 유형≠ | Dynamic panel estimator (Bayesian) | Bayesian panel model |
| 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 ↗ | Hsiao, C., Pesaran, M. H., & Tahmiscioglu, A. K. (2002). Maximum likelihood estimation of fixed effects dynamic panel data models covering short time periods. Journal of Econometrics, 109(1), 107–150. DOI ↗ |
| 별칭 | Bayesian Arellano-Bond estimator, Bayesian difference GMM, quasi-Bayesian difference GMM, Bayesian first-difference GMM | Bayesian DPD model, Bayesian lagged dependent variable panel model, Bayesian autoregressive panel model, B-DPD |
| 관련≠ | 5 | 6 |
| 요약≠ | Bayesian Difference GMM combines the Arellano-Bond first-differencing strategy for dynamic panel data with a Bayesian inference framework. By treating the GMM moment conditions as a quasi-likelihood and placing priors on parameters, the approach produces a full posterior distribution over coefficients rather than a single point estimate with asymptotic standard errors. | The Bayesian dynamic panel data model extends standard dynamic panel models — which include a lagged dependent variable to capture state dependence — by estimating all parameters within a Bayesian framework. Prior distributions are combined with the likelihood to yield a full posterior distribution over model parameters, enabling probabilistic inference and coherent uncertainty quantification even in short panels. |
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