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Nonparametric Kernel Estimation of the Impact of Tax Policy on the Demand for Private Health Insurance in Australia

Author

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  • Gong, Xiaodong

    (NATSEM, University of Canberra)

  • Gao, Jiti

    (Monash University)

Abstract

This paper is motivated by our attempt to answer an empirical question: how is private health insurance take-up in Australia affected by the income threshold at which the Medicare Levy Surcharge (MLS) kicks in? We propose a new difference de-convolution kernel estimator for the location and size of regression discontinuities. We also propose a bootstrapping procedure for estimating confidence bands for the estimated discontinuity. Performance of the estimator is evaluated by Monte Carlo simulations before it is applied to estimating the effect of the income threshold of Medicare Levy Surcharge on the take-up of private health insurance in Australia using contaminated data.

Suggested Citation

  • Gong, Xiaodong & Gao, Jiti, 2015. "Nonparametric Kernel Estimation of the Impact of Tax Policy on the Demand for Private Health Insurance in Australia," IZA Discussion Papers 9265, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp9265
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    References listed on IDEAS

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    1. Kang, Kee-Hoon & Koo, Ja-Yong & Park, Cheol-Woo, 2000. "Kernel estimation of discontinuous regression functions," Statistics & Probability Letters, Elsevier, vol. 47(3), pages 277-285, April.
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    6. Delaigle, Aurore & Meister, Alexander, 2007. "Nonparametric Regression Estimation in the Heteroscedastic Errors-in-Variables Problem," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1416-1426, December.
    7. A. Delaigle & I. Gijbels, 2004. "Bootstrap bandwidth selection in kernel density estimation from a contaminated sample," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 56(1), pages 19-47, March.
    8. Stavrunova, Olena & Yerokhin, Oleg, 2014. "Tax incentives and the demand for private health insurance," Journal of Health Economics, Elsevier, vol. 34(C), pages 121-130.
    9. Hahn, Jinyong & Todd, Petra & Van der Klaauw, Wilbert, 2001. "Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design," Econometrica, Econometric Society, vol. 69(1), pages 201-209, January.
    10. Alfons Palangkaraya & Jongsay Yong, 2005. "Effects of Recent Carrot‐and‐Stick Policy Initiatives on Private Health Insurance Coverage in Australia," The Economic Record, The Economic Society of Australia, vol. 81(254), pages 262-272, September.
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    13. Randall Ellis & Elizabeth Savage, 2008. "Run for cover now or later? The impact of premiums, threats and deadlines on private health insurance in Australia," International Journal of Health Economics and Management, Springer, vol. 8(4), pages 257-277, December.
    14. Delaigle, A. & Gijbels, I., 2006. "Data-driven boundary estimation in deconvolution problems," Computational Statistics & Data Analysis, Elsevier, vol. 50(8), pages 1965-1994, April.
    15. Irene Gijbels & Peter Hall & Aloïs Kneip, 1999. "On the Estimation of Jump Points in Smooth Curves," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 51(2), pages 231-251, June.
    16. Thomas C. Buchmueller & John DiNardo & Robert G. Valletta, 2011. "The Effect of an Employer Health Insurance Mandate on Health Insurance Coverage and the Demand for Labor: Evidence from Hawaii," American Economic Journal: Economic Policy, American Economic Association, vol. 3(4), pages 25-51, November.
    17. Finkelstein, Amy, 2002. "The effect of tax subsidies to employer-provided supplementary health insurance: evidence from Canada," Journal of Public Economics, Elsevier, vol. 84(3), pages 305-339, June.
    18. Randall P. Ellis & Elizabeth Savage, 2008. "Run for Cover Now or Later? The impact of premiums, threats and deadlines on supplementary private health insurance in Australia," Boston University - Department of Economics - Working Papers Series wp2008-013, Boston University - Department of Economics.
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    More about this item

    Keywords

    de-convolution kernel estimator; regression discontinuity; error-in-variables; demand for private health insurance;
    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
    • C29 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Other
    • I13 - Health, Education, and Welfare - - Health - - - Health Insurance, Public and Private

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