Investigate the Effect of Exchange Rate Volatility on the Demand for Life Insurance in Iran
Maryam Hosseinzadeh and
Saeed Daei-Karimzadeh
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Maryam Hosseinzadeh: Department of Economics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran,
Saeed Daei-Karimzadeh: Department of Economics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran.
International Journal of Economics and Financial Issues, 2017, vol. 7, issue 2, 166-174
Abstract:
Numerous factors affect the insurance industry and its growth and development that comprehensive study and recognition about them and taking action to solve or control the negative effects of each one can in turn have a significant effect on the development of this potential market, particularly in the life insurances sector. One of the most important factors is the presence of some economic variables including exchange rate fluctuations in the economy of a country. Given the growing importance of variable exchange rate, especially in the current economic situation of Iran, the effect of exchange rate volatility on the demand for life insurance has been discussed in this study on a monthly basis during the period 1991-2012. Accordingly, the hybrid model of neural network and autoregressive conditional heteroscedasticity (ARCH) method for modeling and predicting the effect of exchange rate volatility on demand for life insurance have been used. The results showed that hybrid model of neural network group method of data handling and ARCH (1, 1), based on the criteria of root mean squared prediction error, significantly able to explain changes of exchange rate volatility on the demand for life insurance.
Keywords: Exchange Rate; Demand for Life Insurance; Instability (Volatility); Neural Network Group Method of Data Handling; Autoregressive Conditional Heteroscedasticity (search for similar items in EconPapers)
JEL-codes: C22 C45 C53 C63 C87 F41 G22 (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:eco:journ1:2017-02-22
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