Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Bayesian Instrumental Variables (Bayesian IV)× | Tofauti-katika-Tofauti (Diff-in-Diff)× | |
|---|---|---|
| Nyanja≠ | Uhitimisho wa Kisababishi | Ekonometriki |
| Familia | Regression model | Regression model |
| Mwaka wa asili≠ | 2003 | 1994 |
| Mwanzilishi≠ | Kleibergen & Zivot (2003); Lancaster (2004) | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| Aina≠ | Causal inference / Bayesian estimation | Causal inference / panel regression |
| Chanzo asilia≠ | Kleibergen, F., & Zivot, E. (2003). Bayesian and classical approaches to instrumental variable regression. Journal of Econometrics, 114(1), 29-72. DOI ↗ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| Majina mbadala≠ | Bayesian IV, Bayesian 2SLS, Bayesian LIML, BayesIV | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| Zinazohusiana≠ | 6 | 5 |
| Muhtasari≠ | Bayesian Instrumental Variables combines the instrumental variable strategy for addressing endogeneity with Bayesian posterior inference. Instead of relying on asymptotic sampling distributions, it places prior distributions over all structural parameters and recovers a full posterior distribution for the causal effect, providing probability statements about the parameter rather than p-values — especially valuable when instruments are weak or the sample is small. | Difference-in-Differences is a causal-inference method that estimates the effect of an intervention by comparing how a treatment group and a control group change over time. Made famous by Card and Krueger's 1994 minimum-wage study and developed in Angrist and Pischke's Mostly Harmless Econometrics, it isolates the treatment effect as the difference between the two groups' before-after changes. |
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