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SIVQR: Stata module to perform smoothed IV quantile regression

Author

Listed:
  • David M. Kaplan

    (University of Missouri)

Programming Language

Stata

Abstract

sivqr estimates quantile regression models in which one or more of the regressors are endogenously determined. It is like qreg, but allowing for instrumental variables to address endogeneity. Or, it is like ivregress, but estimating structural coefficients or causal effects at different levels quantiles) of unobserved heterogeneity (rank variable). As with both qreg and ivregress, the structural model is implicitly linear in the regressors, but those regressors may themselves be nonlinear functions of variables in the raw data. The estimator uses smoothing to improve both computational speed and statistical precision. The methodology was proposed and studied by Kaplan and Sun (2017).

Suggested Citation

  • David M. Kaplan, 2021. "SIVQR: Stata module to perform smoothed IV quantile regression," Statistical Software Components S459002, Boston College Department of Economics, revised 14 Mar 2023.
    • Handle: RePEc:boc:bocode:s459002
    Note: This module should be installed from within Stata by typing "ssc install sivqr". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
    as

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    File URL: http://fmwww.bc.edu/repec/bocode/s/sivqr.ado
    File Function: program code
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/s/sivqr.sthlp
    File Function: help file
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/s/sivqr_examples.do
    File Function: sample do-file
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/s/sivqr_examples_init.do
    File Function: sample do-file
    Download Restriction: no
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