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Proportional treatment effects for count response panel data: effects of binary exercise on health care demand

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  • Myoung‐Jae Lee
  • Satoru Kobayashi

Abstract

We define conditional and marginal treatment effects appropriate for count data, and then conduct an empirical analysis for the effects of exercise on health care demand using panel data from the Health Retirement Study. The response variables are office visits to doctors and hospitalization days, and the treatments of interest are light and vigorous exercises. We found that short‐run light exercise increases health care demand by 3–5%, whereas long‐run light exercise decreases it by 3–6%. We also found that short‐run vigorous exercise decreases health care demand by 1–2%, whereas long‐run vigorous exercise decreases it by 1–3%. However, many of these numbers are not statistically significantly different from zero. These findings suggest that it will be difficult to reduce health care cost much by encouraging people to do more exercise—at least in the short‐run. Copyright © 2001 John Wiley & Sons, Ltd.

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  • Myoung‐Jae Lee & Satoru Kobayashi, 2001. "Proportional treatment effects for count response panel data: effects of binary exercise on health care demand," Health Economics, John Wiley & Sons, Ltd., vol. 10(5), pages 411-428, July.
  • Handle: RePEc:wly:hlthec:v:10:y:2001:i:5:p:411-428
    DOI: 10.1002/hec.626
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    1. James J. Heckman & Jeffrey Smith & Nancy Clements, 1997. "Making The Most Out Of Programme Evaluations and Social Experiments: Accounting For Heterogeneity in Programme Impacts," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 487-535.
    2. Hofer, T.P. & Katz, S.J., 1996. "Healthy behaviors among women in the United States and Ontario: The effect on use of preventive care," American Journal of Public Health, American Public Health Association, vol. 86(12), pages 1755-1759.
    3. Windmeijer, F A G & Silva, J M C Santos, 1997. "Endogeneity in Count Data Models: An Application to Demand for Health Care," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 281-294, May-June.
    4. Myoung‐jae Lee, 2000. "Median treatment effect in randomized trials," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(3), pages 595-604.
    5. Hausman, Jerry & Hall, Bronwyn H & Griliches, Zvi, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," Econometrica, Econometric Society, vol. 52(4), pages 909-938, July.
    6. Deb, Partha & Trivedi, Pravin K, 1997. "Demand for Medical Care by the Elderly: A Finite Mixture Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 313-336, May-June.
    7. Wooldridge, Jeffrey M., 1999. "Distribution-free estimation of some nonlinear panel data models," Journal of Econometrics, Elsevier, vol. 90(1), pages 77-97, May.
    8. Winkelmann, Rainer & Zimmermann, Klaus F, 1995. "Recent Developments in Count Data Modelling: Theory and Application," Journal of Economic Surveys, Wiley Blackwell, vol. 9(1), pages 1-24, March.
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    Cited by:

    1. Fali Huang & Myoung-Jae Lee, 2010. "Dynamic treatment effect analysis of TV effects on child cognitive development," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(3), pages 392-419.
    2. Mullahy, John, 2018. "Individual results may vary: Inequality-probability bounds for some health-outcome treatment effects," Journal of Health Economics, Elsevier, vol. 61(C), pages 151-162.
    3. John Mullahy, 2020. "Discovering Treatment Effectiveness via Median Treatment Effects—Applications to COVID-19 Clinical Trials," NBER Working Papers 27895, National Bureau of Economic Research, Inc.
    4. Majo, M.C., 2010. "A microeconometric analysis of health care utilization in Europe," Other publications TiSEM 1cf5fd2f-8146-4ef8-8eb5-e, Tilburg University, School of Economics and Management.
    5. Martin, Robert S., 2017. "Estimation of average marginal effects in multiplicative unobserved effects panel models," Economics Letters, Elsevier, vol. 160(C), pages 16-19.
    6. Myoung-jae Lee & Sanghyeok Lee, 2021. "Difference in Differences and Ratio in Ratios for Limited Dependent Variables," Papers 2111.12948, arXiv.org, revised Aug 2023.
    7. John Mullahy, 2017. "Individual Results May Vary: Elementary Analytics of Inequality-Probability Bounds, with Applications to Health-Outcome Treatment Effects," NBER Working Papers 23603, National Bureau of Economic Research, Inc.
    8. Yuriy Pylypchuk & Julie Hudson, 2009. "Immigrants and the use of preventive care in the United States," Health Economics, John Wiley & Sons, Ltd., vol. 18(7), pages 783-806, July.
    9. Govert E. Bijwaard & Andrew M. Jones, 2019. "An IPW estimator for mediation effects in hazard models: with an application to schooling, cognitive ability and mortality," Empirical Economics, Springer, vol. 57(1), pages 129-175, July.
    10. Majo, M.C. & van Soest, A.H.O., 2011. "The Fixed-Effects Zero-Inflated Poisson Model with an Application to Health Care Utilization," Discussion Paper 2011-083, Tilburg University, Center for Economic Research.
    11. Javier Gardeazabal & Todd Sandler, 2015. "INTERPOL's Surveillance Network in Curbing Transnational Terrorism," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 34(4), pages 761-780, September.
    12. Myoung-Jae Lee, 2004. "Selection correction and sensitivity analysis for ordered treatment effect on count response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(3), pages 323-337.
    13. Myoung‐jae Lee & Sang‐jun Lee, 2005. "Analysis of job‐training effects on Korean women," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(4), pages 549-562, May.
    14. Lyytikäinen, Teemu, 2009. "Three-rate property taxation and housing construction," Journal of Urban Economics, Elsevier, vol. 65(3), pages 305-313, May.
    15. John Mullahy, 2021. "Discovering treatment effectiveness via median treatment effects—Applications to COVID‐19 clinical trials," Health Economics, John Wiley & Sons, Ltd., vol. 30(5), pages 1050-1069, May.

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