Using Panel Time Series Models to Investigate Causality Between Insurance and Economic Growth in GCC Countries

(Elsayed Elashkar, Abdullah Alnefaiee and Mohammad Zayed)

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Abstract

Developing a country’s insurance sector positively affects its economic growth. Therefore, this study aims to analyze the existence and extent of mutual effects or causal relationships between the insurance sector and economic growth in Gulf Cooperation Council countries. This study builds upon Arabic applied studies in the field of multivariate panel time series models by studying the relationship between insurance and economic growth. Data was used from the years 1990–2018 in the Swiss-Re database for gross written premiums, insurance density and insurance penetration as indicators of insurance activity and GDP and GDP per capita as indicators of economic growth. Several statistical methods were applied, including stationarity and co-integration tests for panel data, causality tests, Vector Auto-Regression models, and Vector Error-Correction models. The study found that there was a statistically significant short-run effect of insurance activity on economic growth and a statistically significant long-run relationship between economic growth and insurance. It is recommended that more attention should be given to developing the insurance sector, creating new insurance products, and taking advantage of digital transformation. In addition, further studies into the relationship between insurance and economic growth using other insurance and economic indicators and statistical methods are recommended.

KEYWORDS
GDP, Granger causality, insurance density, panel data, VAR models, VEC models

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References

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