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Tests of Hypotheses Arising in the Correlated Random Coefficient Model

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  • James J. Heckman
  • Daniel A. Schmierer

Abstract

This paper examines the correlated random coefficient model. It extends the analysis of Swamy (1971, 1974), who pioneered the uncorrelated random coefficient model in economics. We develop the properties of the correlated random coefficient model and derive a new representation of the variance of the instrumental variable estimator for that model. We develop tests of the validity of the correlated random coefficient model against the null hypothesis of the uncorrelated random coefficient model.

Suggested Citation

  • James J. Heckman & Daniel A. Schmierer, 2010. "Tests of Hypotheses Arising in the Correlated Random Coefficient Model," NBER Working Papers 16421, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:16421
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    Cited by:

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    3. Christian N. Brinch & Magne Mogstad & Matthew Wiswall, 2017. "Beyond LATE with a Discrete Instrument," Journal of Political Economy, University of Chicago Press, vol. 125(4), pages 985-1039.
    4. P.A.V.B. Swamy & Stephen G. Hall & George S. Tavlas & I-Lok Chang & Heather D. Gibson & William H. Greene & Jatinder S. Mehta, 2016. "A Method for Measuring Treatment Effects on the Treated without Randomization," Econometrics, MDPI, vol. 4(2), pages 1-23, March.
    5. Gao, Yichen & Li, Cong & Liang, Zhongwen, 2015. "Binary response correlated random coefficient panel data models," Journal of Econometrics, Elsevier, vol. 188(2), pages 421-434.
    6. Swamy Paravastu & Peter Muehlen & Jatinder Singh Mehta & I-Lok Chang, 2022. "The State Of Econometrics After John W. Pratt, Robert Schlaifer, Brian Skyrms, And Robert L. Basmann," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(2), pages 627-654, November.

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    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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