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Control Functions and Simultaneous Equations Methods

Author

Listed:
  • Richard Blundell
  • Dennis Kristensen
  • Rosa L. Matzkin

Abstract

The control function approach is a convenient method of estimation in simultaneous equation systems. This requires that the system can be expressed in triangular form with variables satisfying a conditional mean independence restriction. Linear simultaneous models with additive errors can always be expressed in this form. However, in nonlinear nonadditive simultaneous systems, conditional independence requires a strong additional restriction known as control function separability. We argue that nonadditive models are a key characteristic of simultaneous models of economic behavior with unobserved heterogeneity. We review alternative "system" approaches and document the biases that occur when the control function approach is used inappropriately.

Suggested Citation

  • Richard Blundell & Dennis Kristensen & Rosa L. Matzkin, 2013. "Control Functions and Simultaneous Equations Methods," American Economic Review, American Economic Association, vol. 103(3), pages 563-569, May.
    • Handle: RePEc:aea:aecrev:v:103:y:2013:i:3:p:563-69
    Note: DOI: 10.1257/aer.103.3.563
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    Citations

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    Cited by:

    1. Meinen, Philipp & Parrotta, Pierpaolo & Sala, Davide & Yalcin, Erdal, 2022. "Managers as knowledge carriers – Explaining firms’ internationalization success with manager mobility," Journal of International Economics, Elsevier, vol. 138(C).
    2. Steven T. Berry & Philip A. Haile, 2020. "Nonparametric Identification of Differentiated Products Demand Using Micro Data," NBER Working Papers 27704, National Bureau of Economic Research, Inc.
    3. Cheuk Yin Ho, 2016. "Better Health With More Friends: The Role of Social Capital in Producing Health," Health Economics, John Wiley & Sons, Ltd., vol. 25(1), pages 91-100, January.
    4. Zorlu, Aslan & Hartog, Joop, 2018. "The Impact of Language on Socioeconomic Integration of Immigrants," IZA Discussion Papers 11485, Institute of Labor Economics (IZA).
    5. Xin Geng & Carlos Martins-Filho & Feng Yao, 2015. "Estimation of a Partially Linear Regression in Triangular Systems," Working Papers 15-46, Department of Economics, West Virginia University.
    6. Blundell, Richard & Kristensen, Dennis & Matzkin, Rosa, 2014. "Bounding quantile demand functions using revealed preference inequalities," Journal of Econometrics, Elsevier, vol. 179(2), pages 112-127.
    7. Brown, Sarah & Taylor, Karl, 2015. "Charitable Behaviour and the Big Five Personality Traits: Evidence from UK Panel Data," IZA Discussion Papers 9318, Institute for the Study of Labor (IZA).
    8. Centorrino, Samuele & Florens, Jean-Pierre, 2021. "Nonparametric Instrumental Variable Estimation of Binary Response Models with Continuous Endogenous Regressors," Econometrics and Statistics, Elsevier, vol. 17(C), pages 35-63.
    9. Hui Li & Qiaowei Shen & Yakov Bart, 2018. "Local Market Characteristics and Online-to-Offline Commerce: An Empirical Analysis of Groupon," Management Science, INFORMS, vol. 64(4), pages 1860-1878, April.
    10. Julia Pullbeck & Firmin Doko Tchatoka, 2020. "Inherent effects of corruption on the erosion of political trust in developing countries:Evidence from Ghana," School of Economics and Public Policy Working Papers 2020-01, University of Adelaide, School of Economics and Public Policy.

    More about this item

    JEL classification:

    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation

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