विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| साधारण न्यूनतम वर्ग (OLS) समाश्रयण× | क्वांटाइल रिग्रेशन× | सिस्टम जीएमएम (अरेलानो-बोवर / ब्लंडेल-बॉन्ड)× | |
|---|---|---|---|
| क्षेत्र | अर्थमिति | अर्थमिति | अर्थमिति |
| परिवार | Regression model | Regression model | Regression model |
| उद्भव वर्ष≠ | 2019 | 1978 | 1998 |
| प्रवर्तक≠ | Wooldridge (textbook treatment); classical least squares | Koenker & Bassett | Arellano & Bover (1995); Blundell & Bond (1998) |
| प्रकार≠ | Linear regression | Conditional quantile regression | Dynamic panel data estimator |
| मौलिक स्रोत≠ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 | Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗ | Arellano, M. & Bond, S. (1991). Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations. Review of Economic Studies, 58(2), 277-297. DOI ↗ |
| उपनाम≠ | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu | conditional quantile regression, regression quantiles, Kantil Regresyon | Arellano-Bover estimator, Blundell-Bond estimator, dynamic panel GMM, Sistem GMM (Arellano-Bover / Blundell-Bond) |
| संबंधित≠ | 5 | 5 | 4 |
| सारांश≠ | 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). | Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails. | System GMM is a generalized method of moments estimator for dynamic panel models that contain a lagged dependent variable. Introduced by Blundell and Bond (1998), building on Arellano and Bover, it augments the differenced equation of the earlier difference GMM (Arellano-Bond) with the equation in levels to deliver consistent estimates when N is large and T is small. |
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