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| ベクトル誤差修正モデル（VECM）× | 最小二乗法 (OLS) 回帰× | |
|---|---|---|
| 分野 | 計量経済学 | 計量経済学 |
| 系統 | Regression model | Regression model |
| 提唱年≠ | 1987 | 2019 |
| 提唱者≠ | Engle & Granger | Wooldridge (textbook treatment); classical least squares |
| 種類≠ | Multivariate time-series model | Linear regression |
| 原典≠ | Engle, R. F. & Granger, C. W. J. (1987). Co-Integration and Error Correction: Representation, Estimation, and Testing. Econometrica, 55(2), 251-276. DOI ↗ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| 別名 | vector error correction model, error correction model, cointegration model, VECM (Vektör Hata Düzeltme Modeli) | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| 関連≠ | 4 | 5 |
| 概要≠ | The Vector Error Correction Model is a multivariate time-series model for cointegrated series that captures both their short-run dynamics and their long-run equilibrium relationship. It was introduced by Engle and Granger in 1987 as part of the cointegration and error-correction framework. | Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE). |
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