Footnote:
In: McCarthy, I. and R. Tchernis. 2011. “On the Estimation of Selection Models when Participation is Endogenous and Misclassified,” in D. Drukker (Ed.), Advances in Econometrics, Missing-Data Methods: Cross-sectional Methods and Applications 27:179-207. London: Emerald Group Publishing
Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments November 1, 2010 erstellt
Description:
This paper presents a Bayesian analysis of the endogenous treatment model with misclassifed treatment participation. Our estimation procedure utilizes a combination of data augmentation, Gibbs sampling, and Metropolis-Hastings to obtain estimates of the misclassifcation probabilities and the treatment effect. Simulations demonstrate that the proposed Bayesian estimator accurately estimates the treatment effect in light of misclassifcation and endogeneity