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csa2sls: A complete subset approach for many instruments using Stata

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  • Seojeong Lee
  • Siha Lee
  • Julius Owusu
  • Youngki Shin

Abstract

We develop a Stata command $\texttt{csa2sls}$ that implements the complete subset averaging two-stage least squares (CSA2SLS) estimator in Lee and Shin (2021). The CSA2SLS estimator is an alternative to the two-stage least squares estimator that remedies the bias issue caused by many correlated instruments. We conduct Monte Carlo simulations and confirm that the CSA2SLS estimator reduces both the mean squared error and the estimation bias substantially when instruments are correlated. We illustrate the usage of $\texttt{csa2sls}$ in Stata by an empirical application.

Suggested Citation

  • Seojeong Lee & Siha Lee & Julius Owusu & Youngki Shin, 2022. "csa2sls: A complete subset approach for many instruments using Stata," Papers 2207.01533, arXiv.org, revised Apr 2023.
    • Handle: RePEc:arx:papers:2207.01533
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    References listed on IDEAS

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    1. Motohiro Yogo, 2004. "Estimating the Elasticity of Intertemporal Substitution When Instruments Are Weak," The Review of Economics and Statistics, MIT Press, vol. 86(3), pages 797-810, August.
    2. Guido Kuersteiner & Ryo Okui, 2010. "Constructing Optimal Instruments by First-Stage Prediction Averaging," Econometrica, Econometric Society, vol. 78(2), pages 697-718, March.
    3. Sokbae Lee & Yuan Liao & Myung Hwan Seo & Youngki Shin, 2021. "Fast and Robust Online Inference with Stochastic Gradient Descent via Random Scaling," Papers 2106.03156, arXiv.org, revised Oct 2021.
    4. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-890, July.
    5. Seojeong Lee & Youngki Shin, 2021. "Complete subset averaging with many instruments," The Econometrics Journal, Royal Economic Society, vol. 24(2), pages 290-314.
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