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| 패널 SARIMA 모형× | ARIMA 모형 (자기회귀 누적 이동평균)× | |
|---|---|---|
| 분야 | 계량경제학 | 계량경제학 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1976 (SARIMA); 1990s (panel extensions) | 1970 |
| 창시자≠ | Box & Jenkins (SARIMA foundation); panel extension via mean-group and pooled estimators | George Box and Gwilym Jenkins |
| 유형≠ | Seasonal time series panel model | Time series forecasting model |
| 원전≠ | Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control. Holden-Day. ISBN: 978-0470272848 | Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗ |
| 별칭 | Panel SARIMA, Seasonal ARIMA panel model, SARIMA panel estimation, grouped seasonal time series model | ARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q) |
| 관련≠ | 5 | 6 |
| 요약≠ | The Panel SARIMA model applies the Seasonal Autoregressive Integrated Moving Average (SARIMA) framework to panel data, fitting individual or pooled seasonal time series models across multiple cross-sectional units. It captures both non-seasonal and seasonal autocorrelation, trends, and periodicity, making it suitable for datasets where multiple entities share a common seasonal structure over time. | The ARIMA(p,d,q) model is the standard workhorse for univariate time series forecasting. It combines autoregressive terms (past values), differencing to induce stationarity, and moving average terms (past shocks) into a unified linear framework. Developed by Box and Jenkins (1970), it remains one of the most widely applied models in econometrics and applied statistics. |
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