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| 시간 가변 계수 랜덤 효과 모형× | 베이지안 랜덤 효과 모형× | |
|---|---|---|
| 분야 | 계량경제학 | 계량경제학 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1970–1975 | 1972–1995 |
| 창시자≠ | Swamy (1970); Hsiao (1975) | Lindley & Smith (1972); extended by Gelman, Rubin and colleagues |
| 유형≠ | Panel regression with time-varying random coefficients | Bayesian hierarchical panel model |
| 원전≠ | Swamy, P. A. V. B. (1970). Efficient inference in a random coefficient regression model. Econometrica, 38(2), 311–323. DOI ↗ | Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955 |
| 별칭 | TVP-RE model, random coefficient random effects model, time-varying random effects, TVP panel random effects | Bayesian hierarchical model, Bayesian mixed effects model, Bayesian multilevel model, BREM |
| 관련 | 5 | 5 |
| 요약≠ | The time-varying parameter random effects model extends the classic random effects panel framework by allowing regression coefficients to change over time and across units. Rather than imposing a single fixed slope for all individuals and periods, each coefficient is treated as a random draw that evolves, capturing genuine parameter instability while preserving the random effects assumption that unit-specific components are uncorrelated with the regressors. | The Bayesian random effects model combines panel-data random effects with a Bayesian prior framework, allowing unit-specific effects to be treated as draws from a population distribution whose hyperparameters are estimated from the data. This produces regularised, uncertainty-quantified estimates that borrow strength across units — particularly valuable for short panels, sparse groups, or settings where frequentist variance-component estimation is unstable. |
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