Quantile regression methods for recursive structural equation models

被引:108
|
作者
Ma, Lingjie [1 ]
Koenker, Roger [1 ]
机构
[1] Univ Illinois, Dept Econ, Champaign, IL 61820 USA
基金
美国国家科学基金会;
关键词
instrumental variable; control variate; average derivatives; conditional quantile functions;
D O I
10.1016/j.jeconom.2005.07.003
中图分类号
F [经济];
学科分类号
02 ;
摘要
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. (c) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码:471 / 506
页数:36
相关论文
共 50 条
  • [1] Asymptotic properties of nonparametric estimation and quantile regression in Bayesian structural equation models
    Kim, Gwangsu
    Choi, Taeryon
    JOURNAL OF MULTIVARIATE ANALYSIS, 2019, 171 : 68 - 82
  • [2] Bayesian Quantile Structural Equation Models
    Wang, Yifan
    Feng, Xiang-Nan
    Song, Xin-Yuan
    STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL, 2016, 23 (02) : 246 - 258
  • [3] Estimation of structural gravity quantile regression models
    Baltagi, Badi H.
    Egger, Peter
    EMPIRICAL ECONOMICS, 2016, 50 (01) : 5 - 15
  • [4] Quantile regression and structural change in the Italian wage equation
    Furno, Marilena
    ECONOMIC MODELLING, 2013, 30 : 420 - 434
  • [5] Bayesian regularized quantile structural equation models
    Feng, Xiang-Nan
    Wang, Yifan
    Lu, Bin
    Song, Xin-Yuan
    JOURNAL OF MULTIVARIATE ANALYSIS, 2017, 154 : 234 - 248
  • [6] Smoothed empirical likelihood methods for quantile regression models
    Whang, YJ
    ECONOMETRIC THEORY, 2006, 22 (02) : 173 - 205
  • [7] Instrumental quantile regression inference for structural and treatment effect models
    Chernozhukov, Victor
    Hansen, Christian
    JOURNAL OF ECONOMETRICS, 2006, 132 (02) : 491 - 525
  • [8] Bayesian Empirical Likelihood Estimation of Quantile Structural Equation Models
    Zhang Yanqing
    Tang Niansheng
    JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY, 2017, 30 (01) : 122 - 138
  • [9] Bayesian empirical likelihood estimation of quantile structural equation models
    Yanqing Zhang
    Niansheng Tang
    Journal of Systems Science and Complexity, 2017, 30 : 122 - 138
  • [10] Bayesian Empirical Likelihood Estimation of Quantile Structural Equation Models
    ZHANG Yanqing
    TANG Niansheng
    JournalofSystemsScience&Complexity, 2017, 30 (01) : 122 - 138