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Exploring the Use of a Nonparametrically Generated Instrumetal Variable in the Estimation of a Linear Parametric Equation

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  • Frank T. Denton

Abstract

The use of a nonparametrically generated instrumental variable in estimating a single-equation linear parametric model is explored, using kernel and other smoothing functions. The method, termed IVOS (Instrumental Variables Obtained by Smoothing), is applied in the estimation of measurement error and endogenous regressor models. Asymptotic and small-sample properties are investigated by simulation, using artificial data sets. IVOS is easy to apply and the simulation results exhibit good statistical properties. It can be used in situations in which standard IV cannot because suitable instruments are not available.

Suggested Citation

  • Frank T. Denton, 2005. "Exploring the Use of a Nonparametrically Generated Instrumetal Variable in the Estimation of a Linear Parametric Equation," Social and Economic Dimensions of an Aging Population Research Papers 124, McMaster University.
    • Handle: RePEc:mcm:sedapp:124
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    References listed on IDEAS

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    1. Pagan,Adrian & Ullah,Aman, 1999. "Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521355643, September.
    2. Newey, Whitney K, 1990. "Efficient Instrumental Variables Estimation of Nonlinear Models," Econometrica, Econometric Society, vol. 58(4), pages 809-837, July.
    3. James H. Stock & Francesco Trebbi, 2003. "Retrospectives: Who Invented Instrumental Variable Regression?," Journal of Economic Perspectives, American Economic Association, vol. 17(3), pages 177-194, Summer.
    4. Buckley, Neil J. & Denton, Frank T. & Leslie Robb, A. & Spencer, Byron G., 2004. "The transition from good to poor health: an econometric study of the older population," Journal of Health Economics, Elsevier, vol. 23(5), pages 1013-1034, September.
    5. Yatchew,Adonis, 2003. "Semiparametric Regression for the Applied Econometrician," Cambridge Books, Cambridge University Press, number 9780521812832.
    6. Pakes, Ariel, 1982. "On the Asymptotic Bias of Wald-Type Estimators of a Straight Line When Both Variables Are Subject to Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 23(2), pages 491-497, June.
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    Cited by:

    1. Frank T. Denton & Christine H. Feaver & Byron G. Spencer, 2005. "Population Aging in Canada: Software for Exploring the Implications for the Labour Force and the Productive Capacity of the Economy," Quantitative Studies in Economics and Population Research Reports 403, McMaster University.
    2. Isik U. Zeytinoglu & Margaret Denton, 2006. "Satisfied Workers, Retained Workers: Effects of Work and Work Environment on Homecare Workers' Job Satisfaction, Stress, Physical Health, and Retention," Quantitative Studies in Economics and Population Research Reports 412, McMaster University.
    3. Margaret Denton & Karen Kusch, 2006. "Well-Being Throughout the Senior Years: An Issues Paper on Key Events and Transitions in Later Life," Quantitative Studies in Economics and Population Research Reports 411, McMaster University.
    4. Margaret Denton & Linda Boos, 2007. "Gender Inequality in the Wealth of Older Canadians," Quantitative Studies in Economics and Population Research Reports 413, McMaster University.

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    More about this item

    Keywords

    single equation models; nonparametric; instrumental variables;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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