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| 패널 데이터의 개체 간 추정량× | 패널 데이터에서의 통합 최소제곱법× | |
|---|---|---|
| 분야 | 계량경제학 | 계량경제학 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 2008 | 2010 |
| 창시자≠ | Badi Baltagi (treatment) | Jeffrey Wooldridge (treatment) |
| 유형≠ | OLS on group means | Linear regression on stacked panel observations |
| 원전≠ | Baltagi, B. H. (2008). Econometric Analysis of Panel Data (4th ed.). John Wiley & Sons. ISBN: 978-0-470-51886-1 | Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0-262-23258-8 |
| 별칭 | Between-Groups Estimator, Cross-Sectional Averages Estimator, Panel Between Estimator, Gruplar-Arası Tahmin Edici | Pooled OLS, Pooled Ordinary Least Squares, Simple Panel OLS, Havuzlanmış EKK |
| 관련 | 2 | 2 |
| 요약≠ | The Between Estimator is a panel data regression technique that identifies regression coefficients exclusively from cross-sectional variation across individuals, by collapsing the panel to individual-specific time-averaged observations and applying ordinary least squares to those group means. It is used in economics, sociology, and political science when researchers are interested in long-run or structural differences between units rather than short-run within-unit dynamics. | Pooled OLS applies standard ordinary least squares to panel data by stacking all cross-sectional and time observations into a single dataset and ignoring the panel structure during estimation. It is the most transparent starting point for panel data analysis, widely used in economics, finance, and social sciences when researchers wish to estimate average partial effects across individuals and time periods without imposing strong distributional assumptions about unobserved heterogeneity. |
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