IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i12p4183-d370463.html
   My bibliography  Save this article

Age Structural Transitions and Copayment Policy Effectiveness: Evidence from Taiwan’s National Health Insurance System

Author

Listed:
  • Ya-Ling Lin

    (Department of Public Health, China Medical University, 91 Hsueh-Shih Road, Taichung 40402, Taiwan
    Department of Nursing, Taichung Hospital, Ministry of Health Welfare, 199, Sec. 1, Sanmin Road, Taichung 40343, Taiwan)

  • Wen-Yi Chen

    (Department of Senior Citizen Service Management, National Taichung University of Science and Technology, 193, Sec. 1, Sanmin Road, Taichung 40343, Taiwan)

  • Shwn-Huey Shieh

    (Department of Health Services Administration, China Medical University, 91 Hsueh-Shih Road, Taichung 40402, Taiwan)

Abstract

Background: Population ageing is a worldwide phenomenon that could influence health policy effectiveness. This research explores the impact of age structural transitions on copayment policy responses under Taiwan’s National Health Insurance (NHI) system. Methods: The time-varying parameter vector autoregressive model was applied to create two measures of the copayment policy effectiveness, and multiple linear regression models were used to verify the nonlinear effect of age structural transitions on copayment policy responses. Results: Our results show that copayment policy effectiveness (in terms of the negative response of medical center outpatient visits to upward adjustments in copayment) is positively correlated with the proportions of the population in two older age groups (aged 55–64 and ≥ 65) and children (age < 15), but negatively correlated with the proportion of the population that makes up most of the workforce (aged 15‒54). These tendencies of age distribution, which influence the responses of medical center outpatient visits to copayment policy changes, predict that copayment policy may have a greater influence on medical center outpatient utilization in an ageing society. Conclusions: Policymakers should be concerned about the adverse effects of copayment adjustments on the elderly, such as an increasing financial burden and the effect of pricing some elderly patients out of Taiwan’s NHI system.

Suggested Citation

  • Ya-Ling Lin & Wen-Yi Chen & Shwn-Huey Shieh, 2020. "Age Structural Transitions and Copayment Policy Effectiveness: Evidence from Taiwan’s National Health Insurance System," IJERPH, MDPI, vol. 17(12), pages 1-17, June.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:12:p:4183-:d:370463
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/12/4183/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/17/12/4183/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rong Fu & Haruko Noguchi, 2019. "Moral hazard under zero price policy: evidence from Japanese long-term care claims data," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(6), pages 785-799, August.
    2. Fair, Ray C & Dominguez, Kathryn M, 1991. "Effects of the Changing U.S. Age Distribution on Macroeconomic Equations," American Economic Review, American Economic Association, vol. 81(5), pages 1276-1294, December.
    3. Nicolas Ziebarth, 2014. "Assessing the effectiveness of health care cost containment measures: evidence from the market for rehabilitation care," International Journal of Health Economics and Management, Springer, vol. 14(1), pages 41-67, March.
    4. Takaku, Reo, 2017. "The Effect Of Patient Cost Sharing On Health Care Utilization Among Low-Income Children," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 58(1), pages 69-88, June.
    5. Herr, Annika & Suppliet, Moritz, 2017. "Tiered co-payments, pricing, and demand in reference price markets for pharmaceuticals," Journal of Health Economics, Elsevier, vol. 56(C), pages 19-29.
    6. Jouchi Nakajima, 2011. "Time-Varying Parameter VAR Model with Stochastic Volatility: An Overview of Methodology and Empirical Applications," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 29, pages 107-142, November.
    7. Patrick A. Imam, 2015. "Shock from Graying: Is the Demographic Shift Weakening Monetary Policy Effectiveness," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 20(2), pages 138-154, March.
    8. Chung Jen Yang & Ying Che Tsai & Joseph J. Tien, 2017. "The Impacts of Persistent Behaviour and Cost-Sharing Policy on Demand for Outpatient Visits by the Elderly: Evidence from Taiwan’s National Health Insurance," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 42(1), pages 31-52, January.
    9. Patrizio Armeni & Claudio Jommi & Monica Otto, 2016. "The simultaneous effects of pharmaceutical policies from payers’ and patients’ perspectives: Italy as a case study," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 17(8), pages 963-977, November.
    10. Hansen, Bruce E, 2002. "Tests for Parameter Instability in Regressions with I(1) Processes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 45-59, January.
    11. Landsem, Mari Magnussen & Magnussen, Jon, 2018. "The effect of copayments on the utilization of the GP service in Norway," Social Science & Medicine, Elsevier, vol. 205(C), pages 99-106.
    12. Kolasa, Katarzyna & Kowalczyk, Marta, 2019. "The effects of payments for pharmaceuticals: a systematic literature review," Health Economics, Policy and Law, Cambridge University Press, vol. 14(3), pages 337-354, July.
    13. Enders, Walter & Lee, Junsoo, 2012. "The flexible Fourier form and Dickey–Fuller type unit root tests," Economics Letters, Elsevier, vol. 117(1), pages 196-199.
    14. Government of India, 2017. "National Health Policy 2017," Working Papers id:11664, eSocialSciences.
    15. Hansen, Bruce E, 1997. "Approximate Asymptotic P Values for Structural-Change Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 60-67, January.
    16. Feng, Jin & Song, Hong & Wang, Zhen, 2020. "The elderly's response to a patient cost-sharing policy in health insurance: Evidence from China," Journal of Economic Behavior & Organization, Elsevier, vol. 169(C), pages 189-207.
    17. Wen-Yi Chen, 2017. "Demographic structure and monetary policy effectiveness: evidence from Taiwan," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2521-2544, November.
    18. Tsangyao Chang & Chia-Hao Lee & Pei-I Chou, 2012. "Is per capita real GDP stationary in five southeastern European countries? Fourier unit root test," Empirical Economics, Springer, vol. 43(3), pages 1073-1082, December.
    19. Kim, Jaehoon & Kim, Sangsin, 2015. "2012년 국회법 개정의 효과 연구 [A Study on the Effect of the 2012 National Assembly Act Amendment]," KDI Research Monographs, Korea Development Institute (KDI), volume 127, number v:2015-03(k):y:2015:p:1-1.
    20. Nilsson, Anton & Paul, Alexander, 2018. "Patient cost-sharing, socioeconomic status, and children's health care utilization," Journal of Health Economics, Elsevier, vol. 59(C), pages 109-124.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Vanessa Cirulli & Giuliano Resce & Marco Ventura, 2024. "Co-payment exemption and healthcare consumption: quasi-experimental evidence from Italy," Empirical Economics, Springer, vol. 67(1), pages 355-380, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wen-Yi Chen, 2017. "Demographic structure and monetary policy effectiveness: evidence from Taiwan," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2521-2544, November.
    2. Bertrand Groslambert & Raphaël Chiappini & Olivier Bruno, 2015. "Bank Output Calculation in the Case of France: What Do New Methods Tell About the Financial Intermediation Services in the Aftermath of the Crisis?," GREDEG Working Papers 2015-32, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    3. Liang-Chung Huang & Wu-Fu Chung & Shih-Wei Liu & Jau-Ching Wu & Li-Fu Chen & Yu-Chun Chen, 2019. "Characteristics of Non-Emergent Visits in Emergency Departments: Profiles and Longitudinal Pattern Changes in Taiwan, 2000–2010," IJERPH, MDPI, vol. 16(11), pages 1-16, June.
    4. Hassan Belkacem Ghassan & Hassan Rafdan Al-Hajhoj & Faruk Balli, 2019. "Bi-Demographic Changes and Current Account using SVAR Modeling: Evidence from Saudi Economy," Working Papers hal-01742574, HAL.
    5. Ramzi Issa & Robert Lafrance & John Murray, 2008. "The turning black tide: energy prices and the Canadian dollar," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 41(3), pages 737-759, August.
    6. Mikael Juselius & Elod Takats, 2015. "Can demography affect inflation and monetary policy?," BIS Working Papers 485, Bank for International Settlements.
    7. Avdulaj, Krenar & Barunik, Jozef, 2015. "Are benefits from oil–stocks diversification gone? New evidence from a dynamic copula and high frequency data," Energy Economics, Elsevier, vol. 51(C), pages 31-44.
    8. Moayad H. Al Rasasi, 2020. "Assessing the Stability of Money Demand Function in Saudi Arabia," International Journal of Economics and Financial Research, Academic Research Publishing Group, vol. 6(2), pages 22-28, 02-2020.
    9. Gonzalo, Jesus & Pitarakis, Jean-Yves, 2010. "Regime specific predictability in predictive regressions," Discussion Paper Series In Economics And Econometrics 0916, Economics Division, School of Social Sciences, University of Southampton.
    10. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2016. "Gold, oil, and stocks: Dynamic correlations," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 186-201.
    11. Ghassan, Hassan & Alhajhoj, Hassan R. & Balli, Faruk, 2018. "Bi-Demographic Changes and Current Account using SVAR Modeling: Evidence from Saudi Arabia," MPRA Paper 93013, University Library of Munich, Germany, revised 01 Feb 2019.
    12. Jaehyeok Kim & Minwoo Jang & Donghyun Shin, 2019. "Examining the Role of Population Age Structure upon Residential Electricity Demand: A Case from Korea," Sustainability, MDPI, vol. 11(14), pages 1-19, July.
    13. Habibi Reza, 2011. "A note on approximating distribution functions of cusum and cusumsq tests," Monte Carlo Methods and Applications, De Gruyter, vol. 17(1), pages 1-10, January.
    14. Evrim Mandaci, Pinar & Cagli, Efe Caglar, 2022. "Herding intensity and volatility in cryptocurrency markets during the COVID-19," Finance Research Letters, Elsevier, vol. 46(PB).
    15. Hassan B. Ghassan & Hassan R. Al-Hajhoj & Faruk Balli, 2018. "Bi-Demographic Changes and Current Account using SVAR Modeling," Papers 1803.11161, arXiv.org, revised Mar 2019.
    16. Narayan, Paresh Kumar & Narayan, Seema, 2010. "Modelling the impact of oil prices on Vietnam's stock prices," Applied Energy, Elsevier, vol. 87(1), pages 356-361, January.
    17. Hassan B. Ghassan & Hassan R. Alhajhoj & Faruk Balli, 2022. "Bi-demographic and current account dynamics using SVAR model: evidence from Saudi Arabia," Economic Change and Restructuring, Springer, vol. 55(3), pages 1327-1363, August.
    18. El-Shazly, Alaa, 2016. "Structural breaks and monetary dynamics: A time series analysis," Economic Modelling, Elsevier, vol. 53(C), pages 133-143.
    19. Walsh, Brendan & Lyons, Seán, 2021. "Demand for the Statutory Home Care Scheme," Research Series, Economic and Social Research Institute (ESRI), number RS122.
    20. Adda, Jerome & Gonzalo, Jesus, 1996. "P-Values for non-standard distributions with an application to the DF test," Economics Letters, Elsevier, vol. 50(2), pages 155-160, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:17:y:2020:i:12:p:4183-:d:370463. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.