Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Lokālais vidējais ārstēšanas efekts (LATE / CACE)× | Instrumentālās mainīgās, izmantojot divpakāpju mazāko kvadrātu metodi (IV/2SLS)× | |
|---|---|---|
| Nozare | Cēloņsakarību secināšana | Cēloņsakarību secināšana |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1994 | 2009 |
| Autors≠ | Imbens & Angrist (1994); Angrist, Imbens & Rubin (1996) | Angrist & Pischke (textbook treatment); Stock & Yogo (weak-instrument theory) |
| Tips≠ | Instrumental-variable causal estimand | Instrumental-variables regression |
| Pirmavots≠ | Imbens, G. W., & Angrist, J. D. (1994). Identification and Estimation of Local Average Treatment Effects. Econometrica, 62(2), 467-475. DOI ↗ | Angrist, J. D. & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| Citi nosaukumi≠ | LATE, CACE, complier average causal effect, Yerel Ortalama Tedavi Etkisi (LATE / CACE) | instrumental variables, IV estimation, 2SLS, instrumental variable regression |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | The Local Average Treatment Effect is an instrumental-variable estimand, introduced by Imbens and Angrist (1994) and formalised with Rubin (1996), that recovers the average treatment effect for the subpopulation of compliers — units whose treatment status is actually moved by the instrument. It is closely tied to compliance analysis. | 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). |
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