Interrelationship Between Macroeconomic Variables With Insurance Premiums and Claims – Lessons For Indonesia & ASEAN
DOI:
https://doi.org/10.21512/jas.v11i2.10214Keywords:
insurance sector, premium & claim, macroeconomic condition, panel-data estimationAbstract
The insurance sector plays a crucial economic role by helping individuals and businesses manage risks and uncertainties. By transferring some of their risks to insurance companies, individuals and companies can reduce the likelihood of bankruptcy compared to bearing the risks themselves. This role has become increasingly important in recent decades, particularly due to climate change, financial crises, and the COVID-19 pandemic, leading to greater volatility in macroeconomic indicators. Understanding these potential risks is key to ensuring the future sustainability and growth of the insurance sector in both Indonesia and ASEAN. The research objective is to examine the relationship between macroeconomic variables and insurance and claims. Using annual panel data regression analysis, we examine the relationship between macroeconomic indicators and insurance gross premiums in a sample of 63 countries from 2010 to 2019. The macroeconomic indicators used in the model are real Gross Domestic Product (GDP), inflation, interest rates, and exchange rates. The results suggest that macroeconomic variables play a significant role in determining the performance of gross premiums and claims. Lessons learned include that real GDP, inflation, and real interest rates show a positive and significant relationship with gross premiums, while exchange rates show a negative relationship. However, the lasting impact of these macroeconomic variables on gross premiums varies from one to the other. In fact, only two variables, real GDP and inflation, have a lasting impact. The results suggest that market players should provide strong and comprehensive risk management systems to address macroeconomic turbulence. Surveillance and monitoring macroeconomic indicators are essential, especially in a macro-dependent sector.
Plum Analytics
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