विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| साधनात्मक चर द्विपदीय न्यूनतम वर्ग (IV/2SLS) के माध्यम से× | साधारण न्यूनतम वर्ग (OLS) समाश्रयण× | |
|---|---|---|
| क्षेत्र≠ | कारणात्मक अनुमान | अर्थमिति |
| परिवार | Regression model | Regression model |
| उद्भव वर्ष≠ | 2009 | 2019 |
| प्रवर्तक≠ | Angrist & Pischke (textbook treatment); Stock & Yogo (weak-instrument theory) | Wooldridge (textbook treatment); classical least squares |
| प्रकार≠ | Instrumental-variables regression | Linear regression |
| मौलिक स्रोत≠ | 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 |
| उपनाम≠ | instrumental variables, IV estimation, 2SLS, instrumental variable regression | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| संबंधित | 5 | 5 |
| सारांश≠ | 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). |
| ScholarGateडेटासेट ↗ |
|
|