Skip to main content

The Determinants of Health Care Utilization in Portugal: An Approach with Count Data Models

Summary

This work aims to identify the determinants of health care utilization in Portugal and to quantify their effects. A clear idea about this may help the policy debate on the delivery and organization of health services. Toward this end, we developed an approach based on count data models. We found that demographic factors influence health care demand; unemployment strongly increases utilization, and income effects are only observed for frequent users. Furthermore, chronic conditions increase demand for health services, and personal habits have mixed effects. Both private insurance and the use of subsystems increase the utilization.

References

  • Bago d’Uva, T. (2005), “Latent Class Models for Utilization of Health Care”, Health Economics, 14, pp. 873–892.

    Article  Google Scholar 

  • Barros, P. P. (2005), “Economia da Saude: Conceitos e Comportamentos”, Almedina.

  • Cameron, A. C., P. K. Trivedi, F. Milne, and J. Piggot (1988), “A Micro-econometric Model of the Demand for Health Care and Health Insurance in Australia”, Review of Economic Studies, 55, pp. 85–106.

    Article  Google Scholar 

  • Cameron, A. C., and P. K. Trivedi (1998), Regression Analysis of Count Data, Econometric Society Monographs, vol. 30. New York, Cambridge University Press.

    Book  Google Scholar 

  • Cameron, A. C., and P. K. Trivedi (2005), Microeconometrics: Methods and Applications, Cambridge University Press.

  • Deb, P., and P. K. Triverdi (1997), “Demand for Medical Care by the Elderly: A Finite Mixture Approach”, Journal of Applied Econometrics, 12, pp. 313–336.

    Article  Google Scholar 

  • Deb, P., and P. K. Triverdi (2002), “The Structure of Demand for Health Care: Latent Class versus Two-Part Models”, Journal of Health Economics, 21, pp. 601–625.

    Article  Google Scholar 

  • Dempster, A., N. Laird and D. Rubin (1977), “Maximum Likelihood from Incomplete Data via the EM Algorithm”, Journal of the Royal Statistical Society. Series B (Methodological), 39, pp. 1–38.

    Google Scholar 

  • Gerdtham, U. G. (1997), “Equity in Health Care Utilization: Further Tests Based on Hurdle Model and Swedish Micro Data”, Health Economics, 6.

  • Gourieroux, C., A. Monfort and A. Trognon (1984), “Pseudo Maximum Likelihood Methods: Theory”, Econometrica, 52, pp. 681–700.

    Article  Google Scholar 

  • Grogger, J. T., and R. T. Carson (1991), “Models for Truncated Counts”, Journal of Applied Econometrics, 6, pp. 225–238.

    Article  Google Scholar 

  • Grossman, M. (1972), “On the Concept of Health Capital and the Demand for Health”, Journal of Political Economics, 80, pp. 223–235.

    Article  Google Scholar 

  • Hausman, J., B. H. Hall and Z. Griliches (1984), “Econometric Models for Count Data with an Application to the Patents-R&D Relationship”, Econometrica, 52, pp. 909–938.

    Article  Google Scholar 

  • Lourenço, O. D., and P. L. Ferreira (2005), “Utilization of Public Health Centers in Portugal: Effect of Time Costs and Other Determinants. Finite Mixture Models applied to Truncated Samples”, Health Economics, 14, pp. 939–953.

    Article  Google Scholar 

  • Pohlmeier, W., and V. Ulrich (1995), “An Econometric Model of the Two-Part Decision Making Process in the Demand for Health Care”, Journal of Human Resources, 30, pp. 339–361.

    Article  Google Scholar 

  • Sarma, S., and W. Simpson (2006), “A Microeconometric Analysis of Canadian Health Care Utilization”, Health Economics, 15, pp. 219–239.

    Article  Google Scholar 

  • Sindelar, J. L. (1982), “Differential Use of Medical Care by Sex”, The Journal of Political Economy, 90, pp. 1003–1019.

    Article  Google Scholar 

  • Verbeek, M. (2004), A Guide to Modern Econometrics, 2nd Edition, John Wiley & Sons, Ltd.

  • Wedel, M., W. S. Desarbo, J. R. Bult and V. Ramaswamy (1993), “A Latent Class Poisson Regression Model for Heterogeneous Count Data”, Journal of Applied Econometrics, 8, pp. 397–411.

    Article  Google Scholar 

  • Wedel, M., and W. A. Kamakura (1999), Market Segmentation: Conceptual and Methodological Foundations, Dordrecht, Kluwer, 2nd edition.

    Google Scholar 

  • Windmeijer, F. A., and J. M. C. Santos Silva (1997), “Endogeneity in Count Data Models: An Application to Demand for Health Care”, Journal of Applied Econometrics, 12, pp. 281–294.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to João Cotter Salvado.

Additional information

I am very grateful to Pedro Portugal who helped me throughout this paper as my master advisor. Additionally, I would like to thank to Pedro Pita Barros, Mafalda Sampaio, Miguel Câmara and Pedro Robalo for their important suggestions and corrections.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and permissions

About this article

Cite this article

Salvado, J.C. The Determinants of Health Care Utilization in Portugal: An Approach with Count Data Models. Swiss J Economics Statistics 144, 437–458 (2008). https://doi.org/10.1007/BF03399261

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF03399261

JEL-Classification

Keywords