Asymmetric Effect of Income on the Healthcare Expenditure in Türkiye

Year 2024, Volume: 11 Issue: 1, 310 - 328, 31.03.2024

Muhammed Benli

https://doi.org/10.30798/makuiibf.1376173

Abstract

This paper examines the dynamics between income and health spending in Türkiye from 1988 to 2020, employing autoregressive distributed lag (ARDL) and nonlinear ARDL (NARDL) methodologies. One of the key findings of this study is the presence of an asymmetric relationship between variations in income and overall healthcare expenditure. This means that changes in income levels do not have uniform effects on health expenditure, and the direction of these effects depends on whether income is rising or falling. Interestingly, the research reveals that both increases and decreases in income lead to a rise in total health expenditure. However, the impact of income declines on health expenditure is more pronounced. In other words, when people experience a decrease in income, they tend to allocate a larger portion of their reduced resources to health-related expenses. This highlights the significant financial strain that income reductions can place on individuals and households when it comes to healthcare costs. This pattern of asymmetric effects also extends to government or compulsory health expenditures. When income falls, the government's role in funding health expenses becomes more prominent, as individuals rely more on public healthcare services during economic downturns. Furthermore, the study sheds light on the intriguing relationship between income shifts and voluntary or out-of-pocket health expenses. Positive income shifts are found to be associated with a reduction in voluntary health expenditure. This suggests that as people experience an improvement in their financial situation, they may opt for less costly or more efficient healthcare services, leading to a decrease in out-of-pocket expenses. Conversely, when income levels decrease, individuals may find themselves with limited options, potentially resorting to more expensive private healthcare services or bearing a greater burden of out-of-pocket expenses. This finding underscores the financial vulnerability that can accompany negative income shifts.

Keywords

Health Expenditure, Asymmetric Effect, NARDL

References

• Acemoglu, D., Finkelstein, A., & Notowidigdo, M. J. (2013). Income and health spending: Evidence from oil price shocks. Review of Economics and Statistics, 95(4), 1079-1095. https://doi.org/10.1162/REST_a_00306
• Apergis, N., Bhattacharya, M., & Hadhri, W. (2020). Health care expenditure and environmental pollution: A cross-country comparison across different income groups. Environmental Science and Pollution Research, 27, 8142-8156. https://doi.org/10.1007/s11356-019-07457-0
• Baltagi, B. H., & Moscone, F. (2010). Health care expenditure and income in the OECD reconsidered: Evidence from panel data. Economic Modelling, 27(4), 804-811. https://doi.org/10.1016/j.econmod.2009.12.001
• Baltagi, B. H., Lagravinese, R., Moscone, F., & Tosetti, E. (2017). Health care expenditure and income: A global perspective. Health Economics, 26(7), 863-874. https://doi.org/10.1002/hec.3424
• Barati, M., & Fariditavana, H. (2020). Asymmetric effect of income on the US healthcare expenditure: Evidence from the nonlinear autoregressive distributed lag (ARDL) approach. Empirical Economics, 58, 1979-2008. https://doi.org/10.1007/s00181-018-1604-7
• Bilgel, F., & Tran, K. C. (2013). The determinants of Canadian provincial health expenditures: Evidence from a dynamic panel. Applied Economics, 45(2), 201-212. https://doi.org/10.1080/00036846.2011.597726
• Caporale, G. M., Cunado, J., Gil-Alana, L. A., & Gupta, R. (2018). The relationship between healthcare expenditure and disposable personal income in the US states: A fractional integration and cointegration analysis. Empirical Economics, 55(3), 913-935. https://doi.org/10.1007/s00181-017-1297-3
• Casas, I., Gao, J., Peng, B., & Xie, S. (2021). Time‐varying income elasticities of healthcare expenditure for the OECD and Eurozone. Journal of Applied Econometrics, 36(3), 328-345. https://doi.org/10.1002/jae.2809
• Chakroun, M. (2010). Health care expenditure and GDP: An international panel smooth transition approach. International Journal of Economics, 4(1), 189-200.
• Chen, A. Y., & Escarce, J. J. (2004). Quantifying income-related inequality in healthcare delivery in the United States. Medical Care, 38-47. https://doi.org/10.1097/01.mlr.0000103526.13935.b5
• Dubey, J. D. (2020). Income elasticity of demand for health care and it’s change over time: Across the income groups and levels of health expenditure in India. National Institute of Public Finance and Policy, (20/324).
• Farag, M., NandaKumar, A. K., Wallack, S., Hodgkin, D., Gaumer, G., & Erbil, C. (2012). The income elasticity of health care spending in developing and developed countries. International Journal of Health Care Finance and Economics, 12, 145-162. https://doi.org/10.1007/s10754-012-9108-z
• Freeman, D. G. (2003). Is health care a necessity or a luxury? Pooled estimates of income elasticity from US state-level data. Applied Economics, 35(5), 495-502. https://doi.org/10.1080/00036840210138374
• Gerdtham, U. G., Søgaard, J., Andersson, F., & Jönsson, B. (1992). An econometric analysis of health care expenditure: A cross-section study of the OECD countries. Journal of Health Economics, 11(1), 63-84. https://doi.org/10.1016/0167-6296(92)90025-v
• Hall, R. E., & Jones, C. I. (2007). The value of life and the rise in health spending. The Quarterly Journal of Economics, 122(1), 39-72. https://doi.org/10.1162/qjec.122.1.39
• Ilgun, G., Konca, M., & Sonmez, S. (2023). The relationship between the health transformation program and health expenditures: evidence from an autoregressive distributed lag testing approach. Value in Health Regional Issues, 38, 101-108. https://doi.org/10.1016/j.vhri.2023.08.003
• Kilci, E. N. (2022). Can we increase health expenditure per capita through higher economic growth? empirical evidence from Turkey. Ekoist: Journal of Econometrics and Statistics, (36), 137-152. https://doi.org/10.26650/ekoist.2022.36.982652
• Kim, T. J., Vonneilich, N., Lüdecke, D., & von dem Knesebeck, O. (2017). Income, financial barriers to health care and public health expenditure: A multilevel analysis of 28 countries. Social Science & Medicine, 176, 158-165. https://doi.org/10.1016/j.socscimed.2017.01.044
• Moore, W. J., Newman, R. J., & Fheili, M. (1992). Measuring the relationship between income and NHEs. Health Care Financing Review, 14(1), 133.
• Moscone, F., & Tosetti, E. (2010). Health expenditure and income in the United States. Health Economics, 19(12), 1385-1403. https://doi.org/10.1002/hec.1552
• Musgrove, P., Zeramdini, R., & Carrin, G. (2002). Basic patterns in national health expenditure. Bulletin of the World Health Organization, 80, 134-146. https://doi.org/10.1590/S0042-96862002000200009
• Newhouse, J. P. (1977). Medical-care expenditure: a cross-national survey. The Journal of Human Resources, 12(1), 115-125. https://doi.org/10.2307/145602
• Nghiem, S. H., & Connelly, L. B. (2017). Convergence and determinants of health expenditures in OECD countries. Health Economics Review, 7, 1-11. https://doi.org/10.1186/s13561-017-0164-4
• Okunade, A. A., & Murthy, V. N. (2002). Technology as a ‘major driver’of health care costs: A cointegration analysis of the Newhouse conjecture. Journal of Health Economics, 21(1), 147-159. https://doi.org/10.1016/s0167-6296(01)00122-9
• Ozer, M. (2023). Socioeconomic determinants of out-of-pocket health care expenditures in Türkiye. Fiscaoeconomia, 7(2), 1196-1211. https://doi.org/10.25295/fsecon.1239845
• Pampel, F. C., Krueger, P. M., & Denney, J. T. (2010). Socioeconomic disparities in health behaviors. Annual Review of Sociology, 36, 349-370. https://doi.org/10.1146/annurev.soc.012809.102529
• Parker, S. W., & Wong, R. (1997). Household income and health care expenditures in Mexico. Health Policy, 40(3), 237-255. https://doi.org/10.1016/s0168-8510(97)00011-0
• Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289-326. https://doi.org/10.1002/jae.616
• Rana, R. H., Alam, K., & Gow, J. (2020). Health expenditure and gross domestic product: Causality analysis by income level. International Journal of Health Economics and Management, 20(1), 55-77. https://doi.org/10.1007/s10754-019-09270-1
• Roberts, J. (1999). Sensitivity of elasticity estimates for OECD health care spending: Analysis of a dynamic heterogeneous data field. Health Economics, 8(5), 459-472. https://doi.org/10.1002/(SICI)1099-1050(199908)8:5<459::AID-HEC454>3.0.CO;2-U
• Samadi, A., & Rad, E. H. (2013). Determinants of healthcare expenditure in Economic Cooperation Organization (ECO) countries: Evidence from panel cointegration tests. International Journal of Health Policy and Management, 1(1), 63. https://doi.org/10.15171/IJHPM.2013.10
• Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. Festschrift in honor of Peter Schmidt: Econometric Methods and Applications, 281-314. https://doi.org/10.2139/ssrn.1807745
• Wang, Z. (2009). The determinants of health expenditures: Evidence from US state-level data. Applied Economics, 41(4), 429-435. https://doi.org/10.1080/00036840701704527
• World Health Organization. (2021). Turkey: WHO statistical profile.
• Wu, P. C., Liu, S. Y., & Pan, S. C. (2014). Nonlinear relationship between health care expenditure and its determinants: A panel smooth transition regression model. Empirica, 41, 713-729. https://doi.org/10.1007/s10663-013-9233-z
• Zare, H., Trujillo, A. J., Leidman, E., & Buttorff, C. (2013). Income elasticity of health expenditures in Iran. Health Policy and Planning, 28(6), 665-679. https://doi.org/10.1093/heapol/czs106