Quantile regression methods for recursive structural equation models

Lingjie Ma, Roger Koenker

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Pages (from-to)471-506
Number of pages36
JournalJournal of Econometrics
Volume134
Issue number2
DOIs
StatePublished - Oct 2006

Keywords

  • Average derivatives
  • Conditional quantile functions
  • Control variate
  • Instrumental variable

ASJC Scopus subject areas

  • Economics and Econometrics

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