The Future of Health Expenditure in ASEAN Countries: A Forecasting Analysis with ARIMA
DOI:
https://doi.org/10.15408/sjie.v14i2.46420Keywords:
health expenditure forecasting, forecasting model, ARIMA, health systemAbstract
Research Originality: The primary contribution of this research is its novel analysis and forecasting of health expenditure in the ASEAN region, which has been previously underexamined by scholars.
Research Objectives: This research forecasts per capita health expenditure across three ASEAN countries, broken down by government, private, and out-of-pocket sources.
Research Methods: This study employs a time series ARIMA model approach using secondary data from the World Bank for the period 2000 to 2021
Empirical Results: The findings indicate that projections for all three countries significantly increase across all health expenditure categories. Singapore is expected to see a sharp surge in all health expenditure components. At the same time, Indonesia is forecasted to achieve the highest growth rate in percentage terms, but lags in nominal terms. Conversely, Malaysia is projected to experience moderate growth in health expenditure.
Implications: This research underscores the financing disparities and the urgent need for health system reform.
JEL Classification: I18, C22, O53
How to Cite:
Melati, A. P. S., & Sihaloho, E. D. (2025). The Future of Health Expenditure in ASEAN Countries: A Forecasting Analysis with ARIMA. Signifikan: Jurnal Ilmu Ekonomi, 14(2), 449-466. https://doi.org/10.15408/sjie.v14i2.46420.
References
Agachi, E., Mierau, J. O., van Ittersum, K., & Bijmolt, T. H. A. (2024). Ramification of Healthcare Expenditure on Morbidity Rates and Life Expectancy in the Association of Southeast Asian Nations Countries: A Dynamic Panel Threshold Analysis. Preventive Medicine, 189, 108174. https://doi.org/10.1016/j.ypmed.2024.108174.
Agustina, R., Dartanto, T., Sitompul, R., Susiloretni, K. A., Suparmi, Achadi, E. L., Taher, A., Wirawan, F., Sungkar, S., Sudarmono, P., Shankar, A. H., & Thabrany, H. (2019). Universal Health Coverage in Indonesia: Concept, Progress, and Challenges. The Lancet, 393(10166), 75–102. https://doi.org/10.1016/S0140-6736(18)31647-7.
Bandyopadhyay, G. (2016). Gold Price Forecasting Using ARIMA Model. Journal of Advanced Management Science, 117–121. https://doi.org/10.12720/joams.4.2.117-121.
Chan, A. (2017). Supporting Successful Aging in Singapore: Recent Policiy Initiative. Innovation in Aging, 1, 1271. https://doi.org/10.1093/GERONI/IGX004.4632.
Charlesworth, A., Anderson, M., Donaldson, C., Johnson, P., Knapp, M., McGuire, A., McKee, M., Mossialos, E., Smith, P., Street, A., & Woods, M. (2021). What Is the Right Level of Spending Needed for Health and Care in the UK? The Lancet, 397(10288), 2012–2022. https://doi.org/https://doi.org/10.1016/S0140-6736(21)00230-0.
Choudhary, A., Kumar, S., Sharma, M., & Sharma, K. P. (2022). A Framework for Data Prediction and Forecasting in WSN with Auto ARIMA. Wireless Personal Communications, 123(3), 2245–2259. https://doi.org/10.1007/s11277-021-09237-x.
Deka, B. (2020). The Nexus between Public Health Care Expenditure and Health Outcomes in India. International Journal of Geographical Information Science, 15, 300–312.
Earn, L. (2020). International Health Care System Profiles Singapore. The Commonwealth Fund.
Edney, L. C., Haji Ali Afzali, H., Cheng, T. C., & Karnon, J. (2018). Mortality Reductions from Marginal Increases in Public Spending on Health. Health Policy, 122(8), 892–899. https://doi.org/https://doi.org/10.1016/j.healthpol.2018.04.011.
Fahdhienie, F., Mudatsir, M., Abidin, T. F., & Nurjannah, N. (2024). Risk Factors of Pulmonary Tuberculosis in Indonesia: A Case-Control Study in a High Disease Prevalence Region. Narra Journal, 4(2), 943. https://doi.org/10.52225/narra.v4i2.943.
García-Escribano, M., Juarros, P., & Mogues, T. (2022). Patterns and Drivers of Health Spending Efficiency. Washington DC: IMF.
GHED WHO. (2018). Global Health Expenditure Database. Retrieved from: https://apps.who.int/nha/database/Home/Index/en/
Gourley, M., & team, A. B. of D. S. (2021). Burden of Disease and Injury in Australia. International Journal of Epidemiology, 50(Supplement_1), dyab168.237. https://doi.org/10.1093/ije/dyab168.237.
Jakovljevic, M., Lamnisos, D., Westerman, R., Chattu, V. K., & Cerda, A. (2022). Future Health Spending Forecast in Leading Emerging BRICS Markets in 2030: Health Policy Implications. Health Research Policy and Systems, 20, 23. https://doi.org/10.1186/s12961-022-00822-5.
Li, Z. Z., Liu, G., Tao, R., & Lobont, O. R. (2021). Do Health Expenditures Converge Among ASEAN Countries? Frontiers in Public Health, 9, 699821. https://doi.org/10.3389/fpubh.2021.699821.
Lim, H. M., Sivasampu, S., Khoo, E. M., & Mohamad Noh, K. (2017). Chasm in Primary Care Provision in a Universal Health System: Findings from a Nationally Representative Survey of Health Facilities in Malaysia. PLoS ONE, 12(2), 0172229. https://doi.org/10.1371/journal.pone.0172229.
Lim, J. (2017). Sustainable Health Care Financing: The Singapore Experience. Global Policy, 8, 103–109. https://doi.org/10.1111/1758-5899.12247
Loganathan, T., Rui, D., Ng, C. W., & Pocock, N. S. (2019). Breaking Down the Barriers: Understanding Migrant Workers’ Access to Healthcare in Malaysia. PLoS ONE, 14(7), 0218669. https://doi.org/10.1371/journal.pone.0218669.
Lozano, R., Fullman, N., Mumford, J. E., Knight, M., Barthelemy, C. M., Abbafati, C., Abbastabar, H., Abd-Allah, F., Abdollahi, M., Abedi, A., Abolhassani, H., Abosetugn, A. E., Abreu, L. G., Abrigo, M. R. M., Abu Haimed, A. K., Abushouk, A. I., Adabi, M., Adebayo, O. M., Adekanmbi, V., & Murray, C. J. L. (2020). Measuring Universal Health Coverage Based on an Index of Effective Coverage of Health Services In 204 Countries and Territories, 1990–2019: A Systematic Analysis for the Global Burden of Disease Study 2019. The Lancet, 396(10258), 1250–1284. https://doi.org/10.1016/S0140-6736(20)30750-9.
Luo, L., Luo, L., Zhang, X., & He, X. (2017). Hospital Daily Outpatient Visits Forecasting Using a Combinatorial Model Based on ARIMA and SES Models. BMC Health Services Research, 17, 469. https://doi.org/10.1186/s12913-017-2407-9.
Luo, S., Zhang, J., & Heffernan, M. (2024). Forecast of Total Health Expenditure on China’s Ageing Population: A System Dynamics Model. BMC Health Services Research, 24, 1655. https://doi.org/10.1186/s12913-024-12113-6.
Martínez, M. D. C. V., Ramírez-Orellana, A., & Grasso, M. S. (2021). Health Investment Management and Healthcare Quality in the Public System: A Gender Perspective. International Journal of Environmental Research and Public Health, 18(5), 1–25. https://doi.org/10.3390/ijerph18052304.
Ministry of Health Malaysia. (2023). National Health Accounts Health Expenditure Report 2011-2021. Kuala Lumpur: Ministry of Health Malaysia
Ministry of Health Singapore. (2024). Managing Medical Bills: Learn About Subsidies and Schemes That Help Keep Healthcare Affordable. Retrieved from: https://www.moh.gov.sg/managing-expenses/keeping-healthcare-affordable/managing-medical-bills
Myint, C. Y., Pavlova, M., Thein, K. N. N., & Groot, W. (2019). A Systematic Review of the Health-Financing Mechanisms in the Association of Southeast Asian Nations Countries and the People’s Republic of China: Lessons for the Move Towards Universal Health Coverage. PLoS ONE, 14(6), e0217278. https://doi.org/10.1371/journal.pone.0217278.
Pei, J., Fukang, Z., & and Li, Q. (2024). Diagnostic Checks in Time Series Models Based on a New Correlation Coefficient of Residuals. Journal of Applied Statistics, 51(12), 2402–2419. https://doi.org/10.1080/02664763.2023.2297155.
Phan, T. P., Alkema, L., Tai, S., Tan, K. H. X., Yang, Q., Lim, W.-Y., Teo, Y. Y., Cheng, C.-Y., Wang, X., Wong, T. Y., Chia, K. S., & Cook, A. R. (2014). Forecasting the Burden of Type 2 Diabetes in Singapore Using a Demographic Epidemiological Model of Singapore. BMJ Open Diabetes Res Care, 2, e000012. https://doi.org/10.1136/bmjdrc-2013-000012.
Raghupathi, V., & Raghupathi, W. (2020). Healthcare Expenditure and Economic Performance: Insights from the United States Data. Frontiers in Public Health, 8, 00156. https://doi.org/10.3389/fpubh.2020.00156.
Rahman, M. M., Khanam, R., & Rahman, M. (2018). Health Care Expenditure and Health Outcome Nexus: New Evidence from the SAARC-ASEAN Region. Globalization and Health, 14(1), 113-120. https://doi.org/10.1186/s12992-018-0430-1
Rambe, M. J., Siregar, M. A., & Sembiring, D. S. (2024). Indonesian National Health Policy: Legal Analysis of the Elimination of Mandatory Health Spending. Proceeding of International Conference on Healthy Living, 1(1), 305-314. https://doi.org/10.24123/incoheliv.V1i1.6569.
Sahoo, P. M., Rout, H. S., & Jakovljevic, M. (2023). Future Health Expenditure in the BRICS Countries: a Forecasting Analysis for 2035. Globalization and Health, 19, 49. https://doi.org/10.1186/s12992-023-00947-4.
Singh, S., Bala, M. M., & Kumar, N. (2022). The Dynamics of Public and Private Health Expenditure on Health Outcome in Southeast Asia. Health & Social Care in the Community, 30(5), e2549–e2558. https://doi.org/https://doi.org/10.1111/hsc.13698.
Stenberg, K., Hanssen, O., Edejer, T. T. T., Bertram, M., Brindley, C., Meshreky, A., Rosen, J. E., Stover, J., Verboom, P., Sanders, R., & Soucat, A. (2017). Financing Transformative Health Systems Towards Achievement of the Health Sustainable Development Goals: A Model for Projected Resource Needs in 67 Low-Income and Middle-Income Countries. The Lancet Global Health, 5(9), e875–e887. https://doi.org/10.1016/S2214-109X(17)30263-2.
Tan, C., Lam, C., Matchar, D., Zee, Y. K., & Wong, J. (2021). Singapore’s Health-Care System: Key Features, Challenges, and Shifts. The Lancet, 398, 1091–1104. https://doi.org/10.1016/S0140-6736(21)00252-X.
Tan, S., Lew, K. J., Xie, Y., Lee, P., Koh, H. L., Ding, Y., & Lee, E. S. (2021). Healthcare Cost of Patients with Multiple Chronic Diseases in Singapore Public Primary Care Setting. Annals of the Academy of Medicine, Singapore, 50(11), 809-817. https://doi.org/10.47102/annals-acadmedsg.2021246.
Wang, G., Su, H., Mo, L., Yi, X., & Wu, P. (2024). Forecasting of Soil Respiration Time Series via Clustered ARIMA. Computers and Electronics in Agriculture, 225, 109315. https://doi.org/10.1016/j.compag.2024.109315.
Wang, J., Qin, Z., Hsu, J., & Zhou, B. (2024). A Fusion of Machine Learning Algorithms and Traditional Statistical Forecasting Models for Analyzing American Healthcare Expenditure. Healthcare Analytics, 5, 100312. https://doi.org/10.1016/j.health.2024.100312.
Westmoreland, T. M., & Watson, K. R. (2006). Fulfilling the Hollow Promises Made to Indigenous People Redeeming Hollow Promises: The Case for Mandatory Spending on Health Care for American Indians and Alaska Natives. American Journal of Public Health, 96(4), 600-605. https://doi.org/10.2105/AJPH.
WHO. (2022). World Health Organization Data. Switzerland: World Health Organization Data
Wong, W., Lee, M., Azman, A., & Rose, L. (2021). Development of Short-term Flood Forecast Using ARIMA. International Journal of Mathematical Models and Methods in Applied Sciences, 15, 68-75. https://doi.org/10.46300/9101.2021.15.10.
World Bank. (2025). World Development Indicators. Washington DC: World Bank.
Zhang, Y., & Meng, G. (2023). Simulation of an Adaptive Model Based on AIC and BIC ARIMA Predictions. Journal of Physics: Conference Series, 2449, 012027. https://doi.org/10.1088/1742-6596/2449/1/012027.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Alexsandra Putri Sekar Melati, Estro Dariatno Sihaloho

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
