Quantile regression methods for recursive structural equation models [An article from: Journal of Econometrics]

This digital document is a journal article from Journal of Econometrics, published by Elsevier in 2006. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
Two classes of quantile regression estimation methods for the recursive structural equation models of Chesher [2003. Identification in nonseparable models. Econometrica 71, 1405-1441.] are investigated. A class of weighted average derivative estimators based directly on the identification strategy of Chesher is contrasted with a new control variate estimation method. The latter imposes stronger restrictions achieving an asymptotic efficiency bound with respect to the former class. An application of the methods to the study of the effect of class size on the performance of Dutch primary school students shows that (i) reductions in class size are beneficial for good students in language and for weaker students in mathematics, (ii) larger classes appear beneficial for weaker language students, and (iii) the impact of class size on both mean and median performance is negligible.