Speaker
Description
The motivation of this study is to examine the short run and long run relationships between different proxies for non-life insurance and selected macroeconomics variables in Malaysia. Non-life insurance is represented by penetration rate (NLIPR), density (NLID), net written premium (NLINWP), adjusted premium for population and GDP (NLIAP) and claim ratio (NLICR), while the selected macroeconomic variables include Real Gross Domestic Product (Real GDP), Producer Price Index (PPI), Real Effective Exchange Rate (REER), Foreign Direct Investment (FDI) and the Unemployment Rate (UNP)). The Autoregressive Distributed Lag (ARDL) method has been applied in this study to separate the long-run and short-run effects among these variables. This study utilizes quarterly time series data spanning from 1997Q1 to 2023Q4. This issue is significant to be explored since the complex interactions between these selected macroeconomic variables and non-life insurance proxies remain underexplored, creating a critical gap in the literature. The ARDL approach clearly indicates that, for penetration rate, a long run relationship exists with the selected macroeconomic variables except for PPI, while the short run coefficient is -0.229927. For density, all selected macroeconomic variables are intuitively proven to have long run relationship, with a short run coefficient of -0.225272. Similarly, for net written premium, the variables intuitively demonstrate a long run relationship, and the short run coefficient is -0.173117. A long run relationship is intuitively found for adjusted premium for population and GDP except for real GDP, which has a short run coefficient of -0.089504. Lastly, for the claim ratio, the selected macroeconomic variables intuitively show a long run relationship, except for PPI and UNP, with a short run coefficient of -0.072643. Therefore, this study suggested that, policymakers should prioritize fostering economic growth, as higher GDP levels improve individuals' ability to afford insurance.
