So sánh phương pháp
Xem các phương pháp đã chọn cạnh nhau; những hàng khác biệt được làm nổi bật.
| Ước lượng GMM sai phân (Ước lượng Arellano-Bond)× | Mô hình dữ liệu bảng động× | |
|---|---|---|
| Lĩnh vực | Kinh tế lượng | Kinh tế lượng |
| Họ | Regression model | Regression model |
| Năm ra đời≠ | 1991 | 1988–1991 |
| Người khởi xướng≠ | Manuel Arellano and Stephen Bond | Arellano & Bond (1991); Holtz-Eakin, Newey & Rosen (1988) |
| Loại≠ | GMM panel estimator | Dynamic regression / GMM estimation |
| Công trình gốc | 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 ↗ | 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 ↗ |
| Tên gọi khác | Arellano-Bond estimator, AB-GMM, first-difference GMM, difference GMM estimator | dynamic panel model, panel data model with lagged dependent variable, DPD model, Arellano-Bond model |
| Liên quan | 5 | 5 |
| Tóm tắt≠ | Difference GMM, introduced by Arellano and Bond (1991), estimates dynamic panel data models by first-differencing the equation to remove fixed effects, then using lagged levels of the endogenous variables as GMM instruments. It is the standard approach when a lagged dependent variable or other endogenous regressors are present in a panel with many units and few time periods. | 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. |
| ScholarGateBộ dữ liệu ↗ |
|
|