مقایسهٔ روشها
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| رگرسیون حداقل مربعات معمولی (OLS)× | مدل تصحیح خطای برداری (VECM)× | |
|---|---|---|
| حوزه | اقتصادسنجی | اقتصادسنجی |
| خانواده | Regression model | Regression model |
| سال پیدایش≠ | 2019 | 1987 |
| پدیدآور≠ | Wooldridge (textbook treatment); classical least squares | Engle & Granger |
| نوع≠ | Linear regression | Multivariate time-series model |
| منبع بنیادین≠ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 | Engle, R. F. & Granger, C. W. J. (1987). Co-Integration and Error Correction: Representation, Estimation, and Testing. Econometrica, 55(2), 251-276. DOI ↗ |
| نامهای دیگر | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu | vector error correction model, error correction model, cointegration model, VECM (Vektör Hata Düzeltme Modeli) |
| مرتبط≠ | 5 | 4 |
| خلاصه≠ | 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). | 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. |
| ScholarGateمجموعهداده ↗ |
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