เปรียบเทียบวิธี
ดูวิธีที่เลือกเทียบกันแบบเคียงข้าง แถวที่ต่างกันจะถูกเน้นไว้
| แบบจำลองผลกระทบสุ่ม (Random Effects Panel Model)× | Ordinary Least Squares แบบพูลสำหรับข้อมูลพาเนล× | |
|---|---|---|
| สาขาวิชา | เศรษฐมิติ | เศรษฐมิติ |
| ตระกูล | Regression model | Regression model |
| ปีกำเนิด≠ | 1978 | 2010 |
| ผู้ริเริ่ม≠ | Baltagi (textbook treatment); Hausman specification test | Jeffrey Wooldridge (treatment) |
| ประเภท≠ | Panel data regression | Linear regression on stacked panel observations |
| แหล่งต้นตำรับ≠ | Hausman, J. A. (1978). Specification Tests in Econometrics. Econometrica, 46(6), 1251-1271. DOI ↗ | Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0-262-23258-8 |
| ชื่อเรียกอื่น | random effects panel regression, RE estimator, GLS panel estimator, Panel Rassal Etkiler Modeli | Pooled OLS, Pooled Ordinary Least Squares, Simple Panel OLS, Havuzlanmış EKK |
| ที่เกี่ยวข้อง≠ | 5 | 2 |
| สรุป≠ | The random effects model is a panel data estimator that explains an outcome using both within-unit and between-unit variation, treating the unobserved unit-specific heterogeneity as a random, normally distributed term rather than a fixed parameter. Its validity is judged with the Hausman (1978) specification test, and it is developed in standard treatments such as Baltagi's Econometric Analysis of Panel Data. | 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. |
| ScholarGateชุดข้อมูล ↗ |
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