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Robust inference for the Two-Sample 2SLS estimator.

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PubMed
Summary
This summary is machine-generated.

This study derives the asymptotic variance for the Two-Sample Two-Stage Least Squares (TS2SLS) estimator under conditional heteroskedasticity. A robust variance estimator is presented, enhancing its applicability in econometrics and data combination tasks.

Keywords:
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Area of Science:

  • Econometrics
  • Statistical Inference

Background:

  • Two-Sample Two-Stage Least Squares (TS2SLS) is common for linear models with incomplete joint data.
  • Existing literature lacks explicit asymptotic variance formulas for TS2SLS under conditional heteroskedasticity.

Purpose of the Study:

  • To derive the asymptotic variance of the TS2SLS estimator under conditional heteroskedasticity.
  • To develop a robust variance estimator for TS2SLS.

Main Methods:

  • Utilized the TS2SLS estimator as a function of reduced form and first-stage OLS estimators.
  • Derived the limiting normal distribution's variance under conditional heteroskedasticity.

Main Results:

  • Successfully derived the asymptotic variance formula for TS2SLS under conditional heteroskedasticity.
  • Developed a generalized robust variance estimator applicable to various variable availability patterns.

Conclusions:

  • The derived robust variance estimator expands the utility of TS2SLS in econometrics.
  • The study provides practical tools (Stata code) for implementing these estimators.