Insurance–growth nexus: empirical evidence from emerging Asian markets

Abstract

This study examines the drivers of insurance market growth and causality between insurance and economic growth using a dynamic one-step system GMM estimator and panel Granger causality test on the sample of 19 emerging Asian economies over the period 2007-2017. Several macro-economic factors influence the development of the insurance market but the magnitude of effects varies between high and middle-income countries and types of insurance growth proxies used. On examining the causality between insurance and economic growth, the result of the Granger causality test shows that unidirectional causality is running from economic growth to the insurance sector supporting demand leading framework of insurance growth literature. The study suggests that higher economic activities with regulated price levels, higher banking activities with credit rationing and more outreach programmes are contributing to insurance sector growth. Therefore, policymakers should stimulate economic activities of the country to boost insurance growth.

Keywords:

• Insurance growth
• demand following hypothesis
• supply leading hypothesis
• macro-economic factors
• demographic characteristics
• emerging Asia

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Demand following hypothesis posits a positive causal relationship from economic growth to insurance development. It is based on the presumption that borrowers and savers would need various new financial services as real income rises, leading to the establishment of modern financial institutions and the introduction of related financial services/insurance products.

2 Supply leading hypothesis presents a positive causal relationship from insurance to economic growth. The supply-leading hypothesis accentuates the establishment of financial institutions and the delivery of financial services in anticipation of their demand. The theory assumes that the financial sector is leading and stimulating economic growth.

3 We took gross written premium, insurance density, gross domestic product, and exchange rate in their natural logarithm form. This logarithm transformation reduces the data variations without changing its characteristics, which makes it easy to interpret the coefficient of regression. Due to space constraints, we are not showing the descriptive statistics after taking a log and charts of asymmetrical and symmetric distribution.

4 Endogeneity in regression models refers to the situation where an independent variable correlates with the residuals. There may be different sources of endogeneity bias, so different approaches to its resolution are accessible. Endogeneity includes errors in measurement, common-method variance and omitted and simultaneity bias.

5 Simultaneity bias exists when two variables cause/affect each other simultaneously.

6 Omitted bias can arise when researchers check a construct’s validity without including any other relevant variables/constructs.

7 The application of causality test forms is based on the outcomes of the cointegration test. The error correction term (ECM) and vector error correction term (VECM), as proposed by Granger (1988) is applicable when variables are cointegrated. If the variables are not cointegrated, causality can still be analysed using the Granger causality test through the VAR framework.

Additional information

Notes on contributors

Nikita Singhal

Dr. Nikita Singhal is working as an Assistant Professor of finance at IIMT University. She has completed her Ph.D. from the Department of Commerce, Aligarh Muslim University and JRF in both Commerce and Management. She has been a speaker and organiser of various faculty development programmes and conferences. She has also received a special mention paper award for her manuscript in the 7th PAN IIM World Management Conference organised by IIM Rohtak.

Shikha Goyal

Ms. Shikha Goyal is working as a research scholar at Amity University. She has qualified NET in commerce and receiving ICSSR fellowship for her doctoral work. She has completed her M.Com from the Department of Commerce, Aligarh Muslim University.

Tanmay Singhal

CA Tanmay Singhal is a fellow member Institute of Chartered Accountants of India and he is working as a partner with a chartered accountancy firm M/s STM & Associates established in 1986. He is extensively exposed to audit & assurance, internal financial control, insurance risk assessment, secretarial compliances, tax planning, assessment and other taxation matters.