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Demand for traditional medicine in Taiwan: a mixed Gaussian–Poisson model approach

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  • Steven T. Yen
  • Chao‐Hsiun Tang
  • Shew‐Jiuan B. Su

Abstract

Hurdle count models are used to examine the participation and consumption decisions in Chinese medicine use. Motivated by a household production model, a second censoring mechanism is introduced into existing single‐hurdle models, and the resulting specification accommodates conscientious abstainers, as well as economic non‐consumers, and admits excessive zeros in the sample. In contrast to previous studies that found few predictors, empirical results based on a Taiwanese national sample suggest that Western medicine is a gross substitute to Chinese medicine, and both time price and money price play more important roles than income. Insurance, lifestyle and demographics also determine the use of Chinese medicine. Copyright © 2001 John Wiley & Sons, Ltd.

Suggested Citation

  • Steven T. Yen & Chao‐Hsiun Tang & Shew‐Jiuan B. Su, 2001. "Demand for traditional medicine in Taiwan: a mixed Gaussian–Poisson model approach," Health Economics, John Wiley & Sons, Ltd., vol. 10(3), pages 221-232, April.
  • Handle: RePEc:wly:hlthec:v:10:y:2001:i:3:p:221-232
    DOI: 10.1002/hec.582
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    References listed on IDEAS

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    Cited by:

    1. Kajal Lahiri & Guibo Xing, 2002. "An Empirical Analysis of Medicare-eligible Veterans' Demand for Outpatient Health Care Services," Discussion Papers 02-01, University at Albany, SUNY, Department of Economics.
    2. Steven Yen & Hung-Hao Chang & Tsui-Fang Lin, 2013. "Out-of-pocket expenditures on traditional and Western medicine in Taiwan," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 58(4), pages 583-592, August.
    3. Alfonso Miranda, 2010. "A double-hurdle count model for completed fertility data from the developing world," DoQSS Working Papers 10-01, Quantitative Social Science - UCL Social Research Institute, University College London.
    4. Gregori Baetschmann & Rainer Winkelmann, 2012. "Modelling zero-inflated count data when exposure varies: with an application to sick leave," ECON - Working Papers 061, Department of Economics - University of Zurich.
    5. Kevin E. Staub & Rainer Winkelmann, 2013. "Consistent Estimation Of Zero‐Inflated Count Models," Health Economics, John Wiley & Sons, Ltd., vol. 22(6), pages 673-686, June.
    6. Chung, Rebecca H. & Lee, Jonq-Ying & Brown, Mark G., 2004. "A Study of the Demand for Medical Services in Taiwan," Research papers 53389, Florida Department of Citrus.

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