INSURANCE CONSUMPTION AND ECONOMIC POLICY UNCERTAINTY IN INDIA: AN ANALYSIS OF ASYMMETRIC EFFECTS

This study examines the asymmetric effect of economic policy uncertainty (EPU) on life and non-life insurance consumption in India using monthly data from April 2004–October 2020. The paper has employed a nonlinear autoregressive distributed lag (NARDL) model with a structural break. The results reveal that there exists an asymmetric effect of EPU on life insurance as well as non-life life insurance consumption. A negative relationship is found between EPU and insurance consumption in both life and non-life insurance. Based on the findings, the study suggests the policymakers to consider the asymmetric effects of EPU while formulating insurance-related policies in India.

A STUDY OF DETERMINANTS IMPACTING LIFE INSURANCE CONSUMPTION WITH REFERENCE TO AHMEDABAD CITY

Paper investigates how various demographic factors influence the life insurance consumption. Life insurance is complex and abstract service that has become an essential part of individual’s future planning and safety by offering a diverse variety of policies. What are the major factors that influence the purchase of life insurance? Research hypotheses are tested empirically using chi-square test and the results of study are based on nearly three hundred responses from Ahmedabad city. Paper finds that educational background, occupation and annual income are significant demographic variables where as no association found between age and consumption of life insurance

Drivers of life insurance consumption - an empirical analysis of Western Balkan countries

Life insurance in the Western Balkan Countries is underdeveloped, but it has huge potential for development in the future. The scope of this article is to examine whether and how economic, socio- demographic, and institutional factors determine the demand for life insurance in the Western Balkans, using life insurance density and life insurance penetration as indicators of life insurance demand during 2006-2019. In order to conduct a crosscountry analysis we use panel data regression models and a feasible generalised least squares regression model. The analysis reveals that the most significant factors are income per capita and changes in the urban population. The article contributes to the existing literature by identifying the variables that affect demand for life insurance in the Western Balkans and by providing evidence for insurance operators, authorities, and governments of the respective countries to find ways to further develop the insurance market.