Does insurance market impact the economic growth? Evidence from Albania.

• Author: Sharku, Gentiana

1. Introduction

   Albania is a country that has experienced a long transition, after the beginning of the reforms in 1990. Insurance market has not been a priority of the economic reforms in the first decade. According to the statistics of the Insurance Commission (Albanian Financial Supervisory Authority at the present), the premium per capita in 1999 was only USD 4.2, while in 2018 it has been increased more than tenfold. The insurance market in Albania is significantly developed in the second decade of transition period. The number of insurance companies has been increased, the foreign capital entered, the legislation was significantly improved etc. The insurance market in Albania has always been dominated by non-life insurance products. In 2019, the life insurance activity shared about 7% of total insurance activity. The structure of the insurance market in Albania has been changed from the state monopoly (until 1999) to oligopoly (up to 2002) and then to monopolistic competition (during the last decade) according to Sharku & Shehu (2016). However, the competition degree varies within the classes and activities of the insurance market. Among life and non-life insurance, the life insurance activity is more concentrated than the non-life insurance market, due to the small number of insurance companies operating in the life insurance market.

   Many academics and practitioners in Albania have explored the factors that influence the economic development in Albania, such as foreign direct investment, remittances, banking sector, monetary policy, fiscal policy etc. But very few of them have included the insurance activity as a potential variable of economic development. The late development of the insurance sector in Albania, may be one of the reasons that it is not considered in their studies. However, the international literature suggests that a relationship between economic development and insurance activity may exist even in developing countries like Albania.

   The aim of this article is to explore the relationship between insurance activity and economic growth, considering both the segments: life and non-life insurance and economic development. The literature review regarding this relationship is summarized in the first section of the article. The second section presents the methodology and the data base used in the study and the third section discusses the findings. The final section contains some conclusions regarding the insurance market in Albania.

2. Literature Review

   The relationship between economic growth and insurance industry is subject of many authors, studying the data in different countries and in different economic development periods. In this study, we classify the authors and their findings according the to the economic development of the countries taken in consideration, starting with Ward & Zubruegg (2000), who introduced a study that represents a great contribution to examine the dynamic relationship between economic growth and increase in the insurance industry for nine OECD countries. They used a unique set of annual data for real GDP and total real premiums, from 1961 to 1996, for each country. The Granger causality test suggests that in some OECD countries, the insurance industry causes economic growth, but in other countries the reverse effect. Only for the UK and USA the authors revealed an insignificant relationship. Kugler & Ofogi (2005) studied the UK data for the period 1966-2003. The models they used to investigate the long-run relationship between insurance market and economic growth, were based on disaggregated data. They used Johansen's cointegration test and Granger causality, and their empirical analysis revealed a positive long-run relationship between GDP and the size of the insurance sector, which is characterized as bidirectional. It is important to mention Kugler & Ofogi (2005) realized that Ward & Zubruegg (2000) concluded insignificant results, because they used aggregate data (life and non-life premiums).

   Differently from previous authors, Adams et al. (2009), examined the dynamic relation between commercial bank activity, insurance and economic growth only in one country, in Sweden for the period 1830 to 1998, using time-series data and performing tests for Granger causality. The study concluded that insurance has Granger-caused economic growth and bank lending. Furthermore, the insurance sector has a positive effect on economic growth only in the high economic development periods.

   Later on, Ege & Bahadir (2011) explored the role of insurance in changing economic growth using data of twenty-nine countries from 1999 to 2008 (Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italia, Japan, Turkey, South Korea, Luxemburg, Mexico, Holland, Norway, Poland, Portugal, Slovakia, Spain, Sweden, Switzerland, England and USA). The panel data analysis revealed a positive relationship between insurance and economic growth.

   Chang et al. (2014) applied bootstrapping Granger causality model over a period of 1979--2006, for 10 OECD to examine the relationship between insurance and economic growth. Their findings were not uniform for all the countries included in the study. While Pradhan at al. (2017) explored the causal relationship between insurance market penetration and economic growth per capita in 19 Eurozone countries for the period 1980--2014. Employing Granger causality, the results were mostly non-uniform across the Eurozone countries during this selected period.

   Despite the low level of development, there are a lot of authors that have studied the relationship between economic growth and the insurance market in developing countries. Verma & Bala (2013) based on the Ordinary Least Square regression model, examined the relationship between the life insurance and economic growth in India for the time period 1990 to 2011. The findings of the study concluded that life insurance significantly influences the economic growth of India. These findings are in line with Ghosh (2013) and Din et al. (2017) for India and Chau et al. (2013) for Malasyia.

   Olayungbo & Akinlo (2016) and Alhassan, A.L. (2016) studied the relationship between insurance and economic growth in African countries (five out of eight countries were the same in both studies). Olayungbo & Akinlo (2016) focused their research in eight African countries for the period of 1970--2013. The study showed positive relationships for Egypt, while short-run negative and long-run positive effects were found for Kenya, Mauritius, and South Africa. On the contrary, negative effects were found for Algeria, Nigeria, Tunisia, and Zimbabwe. On the other hand, Alhassan (2016), revealed a long-run relationship between insurance market activities and economic growth for Kenya, Mauritius, Morocco, Nigeria and South Africa. Omoke (2011) studied the impact of the insurance market in Nigeria on economic growth for a period between 1970 and 2008. Contrary to the findings of Olayungbo & Akinlo (2016) and Alhassan (2016), the insurance sector did not reveal any positive and significant impact on economic growth in Nigeria within the period of study. Akinlo & Apanisile (2014), studied the relationship between insurance and economic growth in sub-Saharan Africa over the period 1986-2011. The authors found that insurance has a positive and significant impact on economic growth in sub-Saharan Africa.

   The effect of the insurance sector in the economic development of Turkey has been examined by Yildirim (2015). He employed the Granger Causality Test and VAR Model using trimester data between 2006-2014 years. He found a positive relationship between the economic development and insurance sector.

   Cristea et al. (2014) aimed to establish the correlation between insurance and economic growth in Romania, for the period 1997-2012, based on statistical methods concerning the analysis between the GDP and insurance indicator, taking into consideration insurance penetration and insurance density. As a conclusion, they found out the life insurance is affecting more significantly the GDP per capita, compared with the non-life insurance. The impact of insurance market in economic growth in the exYugoslavia region is tested by Njegomir & Stojic (2010). They used the country-specific fixed effects models for panel data for the period 2004-2008. The analysis revealed a positive effect of insurance on economic growth. Kjosevski (2011) studied the relationship of insurance and economic growth for Macedonia, for the period 1995--2010, using the multiple regression models. With the scope to solve the model it was used the technique of least squares, followed by analysis of variability in order to identify the effects of each variable. He used three different insurance variables--life insurance, non-life insurance and total insurance penetration, and he concluded that the total insurance industry and non-life insurance have a positive and significant effect on economic growth of Macedonia. Life insurance affects the economic growth of Macedonia significantly, but in a negative way.

   Few researchers have studied the relation between the insurance market and economic development in Albania. Madani and Bazini (2017) have...