Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Instrumentální proměnné pomocí dvoufázové metody nejmenších čtverců (IV/2SLS)× | Regrese metodou ordinárních nejmenších čtverců (OLS)× | |
|---|---|---|
| Obor≠ | Kauzální inference | Ekonometrie |
| Rodina | Regression model | Regression model |
| Rok vzniku≠ | 2009 | 2019 |
| Tvůrce≠ | Angrist & Pischke (textbook treatment); Stock & Yogo (weak-instrument theory) | Wooldridge (textbook treatment); classical least squares |
| Typ≠ | Instrumental-variables regression | Linear regression |
| Původní zdroj≠ | Angrist, J. D. & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Další názvy≠ | instrumental variables, IV estimation, 2SLS, instrumental variable regression | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Příbuzné | 5 | 5 |
| Shrnutí≠ | IV/2SLS is a two-stage estimation method that recovers the causal effect of an endogenous regressor by isolating the part of its variation driven by an external instrument. It is the workhorse identification strategy in modern applied econometrics, developed at length in Angrist and Pischke's Mostly Harmless Econometrics (2009). | 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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