A Dynamic Relationship between Environmental Degradation, Healthcare Expenditure and Economic Growth in Wavelet Analysis: Empirical Evidence from Taiwan.

This paper analyzes the co-movement and causal linkages between environmental pollution and healthcare expenditure, taking economic growth as a control variable by using wavelet analysis for Taiwan over the period 1995 Q1-2016 Q4. The results show that there exists co-movement and causality between environmental pollution and healthcare expenditure at different frequencies and times. The changes in the relationships of the two variables are observed in certain events such as the period of the expansion stage, the policy of environmental pollution, and the issue of the National Health Insurance Integrated Circuit card (NHI-IC) in Taiwan. In the short-term, positive causality runs from healthcare expenditure to environmental pollution before 2004, while negative causality runs from healthcare expenditure to environmental pollution before 2007 in the long-term. After adding economic growth as a control variable, positive causality runs from healthcare expenditure to environmental pollution in the period 2009-2011 in the short-term, while negative causality running from healthcare expenditure to environmental pollution is shown in 2008 in the long-term. The results indicate that "higher government health expenditure leading to higher demand for environment quality" exists in different sub-periods and the argument may concern the factor of economics in the long-term. The positive healthcare lead in the short-term may be based on economics in the expansion stage. Also, the issue of NHI-IC possibly affects the dynamic relationship between healthcare expenditure and environmental pollution without considering economics. Based on empirical analysis, certain policy and managerial implications are addressed for decision-makers at macroeconomic and microeconomic levels.

Investigation of the Co-Movement Relationship between Medical Expenditure and GDP in Taiwan-Based on Wavelet Analysis.

In this study, using the medical expenditures of the Taiwanese government and gross domestic product (GDP) as variables, the wavelet analysis method was used to empirically study the correlations and lead-lag relationships in quarterly data in the period from 1996 to 2016. In addition, the dependent population of the insured was used as the control variable. Results: After the dependent population was included as a control variable, there was a period of low- frequency (one to four years, short-term) linkage correlation, as well as a period of high- frequency (four to eight years, long-term) linkage correlation. In addition, for more than eight years, there was a high degree of linkage correlation, indicating that the linkage between medical expenditures and GDP occurred over the long- term. Moreover, since medical expenditures positively affected GDP, one-way causality was observed. However, after 2008, regardless of whether long or short- term was examined, there was almost no linkage correlation. Before 2008, the medical expenditures of the government were positively correlated with economic growth. After 2008, this effect had already disappeared. The universal health insurance system has long been denounced as a waste of medical resources. The government needs to find a new solution.

Bootstrap ARDL on Health Expenditure, CO2 Emissions, and GDP Growth Relationship for 18 OECD Countries.

Using annual time-series data over the period 1975-2017, the researcher applied the bootstrap autoregressive-distributed lag (ARDL) cointegration model developed by McNown et al. (1) to examine whether there is a long run relationship among health expenditure, CO2 emissions, and gross domestic product (GDP) per capita in 18 Organization for Economic Cooperation and Development (OECD) countries. We find cointegration exists in Netherlands when real GDP per capita serves as a dependent variable, in New Zealand when health expenditure is the dependent variable, and in the United States when CO2 emissions are dependent variables. The main results show evidence of a short run relationship between the three variables. The empirical results support that there is a bidirectional causality between health expenditure and GDP growth for Germany and the United States, between CO2 emissions and GDP growth for Canada, Germany, and the United States, and between health expenditure and CO2 emissions for New Zealand and Norway. The results also indicate that there are unidirectional causality in other countries.