Journal of Economic Modeling Research

The insurance industry as a means of transferring risk and paying damages, ensures the future and the confidence of individuals and as an investor's institution, It cumulation the saving resources and allocates it to the needs of investment and economic growth of the countries. Therefore, it is necessary to identify the factors influencing the development of this industry in countries with a low insurance penetration and action must be taken regarding reinforcement the increasing factors and Elimination its decreasing factors.In this regard, the present study has tried to determine the interaction between financial development and economic freedom indicators (total index, size of government, legal system and property rights, sound money, freedom to trade internationally and regulations) on the penetration insurance in Fifteen unsuccessful insurers will be insured over the period 2014-2000. For this purpose, the research model was estimated using panel data and generalized moment’s method. The results it shows the interaction of financial development and all index of economic freedom on insurance penetration the in selected countries have had a positive and meaningful.  Also, the individual effect of financial development and total economic freedom index is positive and significant. However, their individual influence on the insurance penetration is less than their interaction. Finally, the effect of control variables including per capita income, human capital and urbanization rate on the insurance penetration in the selected countries have had a positive and meaningful and the effect of unemployment and inflation have had a negative and meaningful.

Life insurance is one of the most important economic instruments. Considering the important role of life insurance, this study investigates the life insurance capability in Iran. For this purpose, the Panel ARDL model has been used. Then, for the period 1990-2016, suitable models for the first group (Iran with the leading countries in the industry), the second group (Iran with the countries that were close to Iran in premiums) and the group Third (countries in two groups) were estimated. Based on models, the fitted value of life insurance premiums per capita in Iran is analyzed and compared as the potential or optimal level in each groups. The results showed that in each group, the actual life insurance premiums per capita in Iran are significantly lower than the optimal level. The capacity level of life insurance in Iran compared with first group is 46%, and compared with second group is about 42% and compared with third group is about 44%. The results indicate that Life insurance in our country has a high potential, and a large part of the insurance capacity in our country has not yet been fully acquired.

Insurance as a central risk-taking institution as well as one of the investment institutions increases economic participation, investment development and stimulating economic growth. Therefore, identification of the effective factors on the insurance penetration in developing countries seems necessary. In this regard, the present study attempted to investigate the impact of national competitiveness on insurance penetration coefficient in 20 developing countries during the period 2007-2017. The research model was estimated using panel data and generalized moment’s method in two case. In the first case, the sub-indicators of national competitiveness including basic requirements, efficiency enhancer’s factors and innovation and sophistication factors were used as key variables in the research, and in the second case, the overall competitiveness index is used as a key variable in the research model. The results showed that the effect of overall competitiveness index and its sub-indicators on insurance penetration was positive and significant. Also, the effect of control variables, including per capita income and urbanization rate on insurance penetration is positive and significant, and the effect of dependency ratio on insurance penetration is negative and significant.

The pension coverage of the Iranian Social Security Organization for self-employed workers is offered at three contribution rates of 12, 14 and 18 percent, but looking at the statistics shows that the demand for these types of insurances is low. This research investigates the characteristics of these insured groups by using data mining and applying two machine learning algorithms, decision tree and random forest, and predicts their behavior by providing a classification model. This will help the Social Security Organization to improve customer relationship management. For this purpose, the information of 1286174 insured persons of self-employed in 2020 was used, which includes the characteristics of age, gender, average monthly income, the years of service, and the type of self-employed pension scheme. The obtained results show that women mainly apply for the scheme with 12 percent contribution, while men tend to be covered by schemes with contribution rates of 14 and 18 percent due to the burden of supporting the family. Also, for men, the demand for schemes of 14 and 18 percent increases with the increase of age, income and years of service, but there are no such trends for women. According to the obtained results, years of service and then gender are decisive in choosing the type of pension scheme in such a way that according to the prediction of the model, people with less than 4.5 years of service are known as definite applicants for 12 percent self-employed pension scheme.