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MLR2SLS: Stata module for 2SLS estimation with multiple-LATEs robust standard error under treatment effect heterogeneity

Author

Listed:
  • Seojeong Jay Lee

    (University of New South Wales)

  • Dandan Yu

Programming Language

Stata

Abstract

mlr2sls calculates the standard error for over-identified 2SLS. Under treatment effect heterogeneity an instrument identifies the instrument-specific local average treatment effect (LATE). When multiple instruments are used together for estimation, the 2SLS estimand is a weighted average of the LATEs and this makes the underlying moment condition be misspecified. As a result the conventional heteroskedasticity-robust standard error is biased. mlr2sls provides a standard error which corrects for this bias and is consistent. It is also robust to heteroskedasticity and clustering is allowed. See Lee, Journal of Business and Economic Statistics, 2017.

Suggested Citation

  • Seojeong Jay Lee & Dandan Yu, 2018. "MLR2SLS: Stata module for 2SLS estimation with multiple-LATEs robust standard error under treatment effect heterogeneity," Statistical Software Components S458487, Boston College Department of Economics, revised 15 Sep 2018.
    • Handle: RePEc:boc:bocode:s458487
    Note: This module should be installed from within Stata by typing "ssc install mlr2sls". 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

    Download full text from publisher

    File URL: http://fmwww.bc.edu/repec/bocode/m/mlr2sls.ado
    File Function: program code
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/m/mlr2sls.sthlp
    File Function: help file
    Download Restriction: no
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