Fangjhy Li

This work utilizes the Taiwanese data primarily focused on retailing investor behavior to examine whether Taiwanese brokerage analysts issue target price revisions, whether implicit information connotation exists and whether their own brokerages use the market reaction brought about by target price revisions to conduct conflict of interest operations. The event study is used to verify whether the above results exist. The empirical results show that analysts may publish information that includes investment recommendations, earnings forecasts, or price target forecasts. Whether investors with immediate and post-event media coverage revise their relevant investment strategies and avoid serious losses caused by this news is established. The research results show that the target price revision has implicit information content no matter the target price being revised. In addition, a conflict of interest between dealers’ trading behavior and analysts’ target price revisions exists. The major contribution of this work is to fill the research gaps concerning which retail investors are easily influenced by social media and herding behavior, as well as target price forecasting. The most efficient use of resources relates to the satisfaction of everyone’s interests on a fair basis, and thus greater contribution. The governance mechanism and check and balance function can help maximize the value of the company, not only by enhancing the competitiveness of the enterprise, but also by increasing the value of shareholders’ rights and interests and better fulfilling corporate social responsibility.

Regarding the huge negative effects of the COVID-19 pandemic on the tourism market of the US, we investigate the persistent degree of the shocks to three markets: overseas, Canada, and Mexico. To measure persistence degree and its dynamics, we apply the Fourier quantile unit root test and rolling-window indirect inference estimators. Overall results indicate (i) negative shocks to the US’ tourist markets have more long-lasting effects than positive ones, (ii) degree of persistence of all three markets increased due to the COVID-19 pandemic, and (iii) Canada tourist marker displays more persistence behaviour than the other two markets.

This study intends to explore the impact of Thailand's capital account opening on financial market stability. The data period in this paper is from 2000 to 2018, the sample country is Thailand, and annual data are collected. The degree of capital account opening uses the capital account net value as the data, the financial market stability uses the Thailand stock price index as the proxy variable, and the control variable uses the International Monetary Fund (IMF) indicator: the financial market efficiency index. We use wavelet analysis to demonstrate it. Empirical results: (1) on the island of correlation, regardless of whether control variables are included, there is no correlation between the two variables during the full sample period. The degree of capital account opening in Thailand is not related to the stability of the financial market (Thailand stock market). (2) The short-term (1-4 years) phase difference shows that, regardless of whether the control variables are included; there is no correlation between the two variables during the entire sample period. The degree of capital account opening in Thailand is not related to the stability of the financial market (Thailand stock market). There is no long-term (4-8 years) linkage relationship. In view of the empirical results, it is recommended that international investors be optimistic about the changes in the degree of capital account opening in Thailand's balance of payments and the changes in its net value when investing in the Thailand's stock market in the short and long-term. Because of the degree of opening of the Thailand's capital account, there is no correlation to the Thailand's stock market. Therefore, international investors can ignore this overall economic indicator when investing in long- and short-term investments.

The current study employs a Granger causality test within a Quantile approach investigating CO₂ emission determinants in China. Results show urbanization, financial development and openness to trade are leading determinants of CO₂ emissions in China. These results highlight climate change issues while taking advantage of a new methodology to fill a gap in the current literature. Our findings show key implications for PRC government policy related to pollutant reduction policy.

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.

We used the Bootstrap Autoregressive Distributed Lagged Model (ARDL) method to test the relationship among BRICS (Brazil, Russia, India, China, and South Africa) countries’ trade, foreign direct investment (FDI), and CO₂ emissions. We found that Brazil’s CO₂ emissions and FDI have a cointegration relationship with the trade on the lag of one-period. Russia and India and CO₂ emissions and trade have a cointegration relationship with FDI on the lag of one-period. In the long-term, Brazil’s FDI has a long-term causal relationship with the trade on the lag of one-period. The trade between Russia and India has a long-term causal relationship with FDI on the lag of one-period. Among other BRICS variables, Russian trade and FDI on the lag of one-period of CO₂ emissions and FDI and CO₂ emissions are on the lag of one-period on trade, which McNown et al. mentioned is the degeneration case #1 in their paper; while China’s trade and FDI on the lag of one-period of CO₂ emissions is the country of degeneration case #2. When we examined short-term causality, we found that CO₂ emissions showed a causal relationship with trade, while FDI and CO₂ emissions were less pronounced. Trade has a positive causal relationship with FDI. These variables are different in different situations and in different countries. These results should be related to BRICS countries’ FDI, international trade development, and their different CO₂ emission policies.

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.

We used the Bootstrap ARDL method to test the relationship between the export trades, FDI and CO₂ emissions of the BRICS countries. We found that China's foreign direct investment and the lag one period of CO₂ emissions have a cointegration on exports. South Africa's foreign direct investment and CO₂ emissions have a cointegration relationship with the lag one period of exports, and South Africa's the lag one period of exports and foreign direct investment have a cointegration relationship with the lag one period of CO₂ emissions. But whether it is China or South Africa, these three variables have no causal relationship in the long-term. Among the variables of other BRICS countries, Russia is the only country showed degenerate case #1 in McNown et al. mentioned in their paper. When we examined short-term causality, we found that CO₂ emissions and export trade showed a reverse causal relationship, while FDI and carbon emissions were not so obvious. Export trade has a positive causal relationship with FDI. Those variables are different from different situations and different countries.