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Feasible IV Regression without Excluded Instruments

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  • Emmanuel Selorm Tsyawo

Abstract

The relevance condition of Integrated Conditional Moment (ICM) estimators is significantly weaker than the conventional IV's in at least two respects: (1) consistent estimation without excluded instruments is possible, provided endogenous covariates are non-linearly mean-dependent on exogenous covariates, and (2) endogenous covariates may be uncorrelated with but mean-dependent on instruments. These remarkable properties notwithstanding, multiplicative-kernel ICM estimators suffer diminished identification strength, large bias, and severe size distortions even for a moderately sized instrument vector. This paper proposes a computationally fast linear ICM estimator that better preserves identification strength in the presence of multiple instruments and a test of the ICM relevance condition. Monte Carlo simulations demonstrate a considerably better size control in the presence of multiple instruments and a favourably competitive performance in general. An empirical example illustrates the practical usefulness of the estimator, where estimates remain plausible when no excluded instrument is used.

Suggested Citation

  • Emmanuel Selorm Tsyawo, 2021. "Feasible IV Regression without Excluded Instruments," Papers 2103.09621, arXiv.org, revised Nov 2022.
    • Handle: RePEc:arx:papers:2103.09621
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    1. Dominic Edelmann & Konstantinos Fokianos & Maria Pitsillou, 2019. "An Updated Literature Review of Distance Correlation and Its Applications to Time Series," International Statistical Review, International Statistical Institute, vol. 87(2), pages 237-262, August.
    2. Kleibergen, Frank & Paap, Richard, 2006. "Generalized reduced rank tests using the singular value decomposition," Journal of Econometrics, Elsevier, vol. 133(1), pages 97-126, July.
    3. Dieterle, Steven G. & Snell, Andy, 2016. "A simple diagnostic to investigate instrument validity and heterogeneous effects when using a single instrument," Labour Economics, Elsevier, vol. 42(C), pages 76-86.
    4. Alan Sule & Honoré Bo E. & Hu Luojia & Leth-Petersen Søren, 2014. "Estimation of Panel Data Regression Models with Two-Sided Censoring or Truncation," Journal of Econometric Methods, De Gruyter, vol. 3(1), pages 1-20, January.
    5. Carrasco, Marine, 2012. "A regularization approach to the many instruments problem," Journal of Econometrics, Elsevier, vol. 170(2), pages 383-398.
    6. Chamberlain, Gary, 1987. "Asymptotic efficiency in estimation with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 34(3), pages 305-334, March.
    7. Emmanuel Selorm Tsyawo & Abdul-Nasah Soale, 2021. "A Distance Covariance-based Estimator," Papers 2102.07008, arXiv.org, revised Nov 2025.
    8. Hansen, Christian & Kozbur, Damian, 2014. "Instrumental variables estimation with many weak instruments using regularized JIVE," Journal of Econometrics, Elsevier, vol. 182(2), pages 290-308.
    9. Chung Eun Lee & Xiaofeng Shao, 2018. "Martingale Difference Divergence Matrix and Its Application to Dimension Reduction for Stationary Multivariate Time Series," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(521), pages 216-229, January.
    10. Xiaofeng Shao & Jingsi Zhang, 2014. "Martingale Difference Correlation and Its Use in High-Dimensional Variable Screening," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1302-1318, September.
    11. Honore, Bo E. & Powell, James L., 1994. "Pairwise difference estimators of censored and truncated regression models," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 241-278.
    12. Erik Hornung, 2014. "Immigration and the Diffusion of Technology: The Huguenot Diaspora in Prussia," American Economic Review, American Economic Association, vol. 104(1), pages 84-122, January.
    13. Su, Liangjun & Zheng, Xin, 2017. "A martingale-difference-divergence-based test for specification," Economics Letters, Elsevier, vol. 156(C), pages 162-167.
    14. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
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