השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| אמידת GMM מערכתית לפנל (אומד בלנדל-בונד)× | אומדן גאוס-מרקוב-ניואי (GMM) של ארייאנו-בונד× | |
|---|---|---|
| תחום | אקונומטריקה | אקונומטריקה |
| משפחה | Regression model | Regression model |
| שנת המקור≠ | 1998 | 1991 |
| הוגה השיטה≠ | Blundell & Bond (1998); Arellano & Bover (1995) | Manuel Arellano and Stephen Bond |
| סוג | GMM estimator for dynamic panel data | GMM estimator for dynamic panel data |
| מקור מכונן≠ | Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87(1), 115–143. 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 ↗ |
| כינויים | System GMM, Blundell-Bond estimator, SYS-GMM, two-step System GMM | AB-GMM, Difference GMM, first-difference GMM, Arellano-Bond estimator |
| קשורות≠ | 6 | 5 |
| תקציר≠ | Panel System GMM is a two-equation GMM estimator for dynamic panel data that stacks the differenced equation (using lagged levels as instruments) with the levels equation (using lagged differences as instruments). Developed by Blundell and Bond (1998) on the foundation of Arellano and Bover (1995), it is the preferred tool when the lagged dependent variable is highly persistent or individual effects are large. | The Arellano-Bond GMM estimator is the standard approach for dynamic panel data models in which the lagged dependent variable appears as a regressor. By first-differencing to remove fixed effects and using deeper lags as instruments, it yields consistent estimates even when the error is serially correlated and regressors are endogenous. |
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