چکیده:
چکیده هدف اصلی مقاله حاضر بررسی اثر نااطمینانی سیاست پولی و درآمد سرانه بر حق بیمه در ایران است. تئوریهای اقتصادی بهوضوح اثر نااطمینانی سیاست پولی را بر حق بیمه نشان نمیدهند، لذا مسئله مذکور اساساً یک مسئله تجربی است. ازاینرو، با ارائه یک مدل تجربی، اثر نامتقارن نااطمینانی سیاست پولی بر حق بیمه سرانه در ایران با استفاده از الگوی خودتوضیحی با وقفههای توزیعی غیرخطی (NARDL) در بازه زمانی 1350-1397 آزمون گردید. برای این منظور، ابتدا نااطمینانی سیاست پولی با استفاده از الگوی EGARCH استخراج شد و به تغییرات مثبت و منفی تجزیه گردید. نتایج حاصل از برآورد ضرایب بلندمدت تغییرات مثبت و منفی نااطمینانی سیاست پولی بر حق بیمه سرانه نشان میدهد هر دو ضریب بلندمدت نامتقارن، منفی و معنیدار هستند. همچنین، در بلندمدت رابطه مثبت و معنیداری بین درآمد سرانه و حق بیمه سرانه کل وجود دارد. در کوتاهمدت رابطه معنیداری بین تغییرات مثبت نااطمینانی و حق بیمه سرانه در ایران وجود ندارد، اما با یک وقفه، رابطه مثبتی بین این دو وجود خواهد داشت. درعینحال، در کوتاهمدت رابطه منفی و معنیداری بین تغییرات منفی نااطمینانی و حق بیمه سرانه وجود دارد، اما با یک وقفه، این رابطه معنیدار نیست.
Extended abstract 1- Introduction The relationship between the banking and the real sector of the economy has long been considered by economists. The banking sector as the main gateway to monetary policy and the real sector of the economy as the main gateway to the fiscal policy has a significant impact on the country's economic balance. The more coordination between the two sectors, the higher the economic growth. Given the relationship between the performance of monetary policy and the macro variables of the real sector of the economy, any uncertainty in the performance of monetary policy can have adverse effects on the real sector of the economy. One of the factors that monetary policy uncertainty can affect is insurance premiums. Since premium rates are usually based on projected investment income and expected losses (which are themselves exposed to business cycles), it is reasonable to expect a significant correlation between insurance premiums and macroeconomics. Therefore, this paper examines the effect of monetary policy uncertainty on insurance premiums in Iran. 2- Theoretical Framework Economic theories do not clearly show the effects of monetary policy uncertainty on insurance premiums. Therefore, this is essentially an empirical problem. In general, many economic studies agree that economic policy uncertainty plays an important role in shaping real economic activities such as business cycles, inflation, investment, employment, and economic growth (Bloom (2019); Julio & Yook (2012); Jones & Olson (2013); Kang et al. (2014); Wang et al. (2014); Gulen & Ion (2016); Bloom et al. (2018)). For example, Baker et al. (2016) by constructing an index to measure economic policy uncertainty, found that this index harms investment, production, and employment in the United States. The key point that can be made here is that the uncertainty of economic policy has a real effect on the behavior of buying insurance if it has a significant effect on these economic activities. From the perspective of risk aversion behavior, political uncertainty is one of the basic components of insurance premiums to reduce risk. Park et al. (2002) believe that people's risk and uncertainty depend primarily on their understanding of their socio-political environment. Beck & Webb (2013) also believe that political instability may hinder the development of the insurance market, as this affects the economic horizons of potential buyers and suppliers of life insurance products. 3- Methodology Following Balcilar et al. (2018) we have presented an empirical model to test the asymmetric effects of monetary policy uncertainty on per capita insurance premiums in Iran using the Non-Linear Autoregressive Distributed Lag (NARDL) model for 1971-2018. To measure the uncertainty of monetary policy, there are various indicators such as standard deviation of the moving average, deviation from the trend, and autoregressive conditional heteroskedasticity. Also, studies show that there is no theoretical basis for the preference of one indicator to measure real money supply fluctuations (as a measure of monetary policy uncertainty) over another. Therefore in this study, the monetary policy uncertainty was extracted using the EGARCH model and divided into positive and negative changes. 4- Results & Discussion The results of the estimation of long-term coefficients for positive and negative changes in monetary policy uncertainty on per capita insurance premiums showed that both long-term coefficients are asymmetric, negative, and significant. Also, there is a positive and significant relationship between per capita income and total per capita insurance premiums in the long run. In the short term, there is no significant relationship between positive uncertainty changes and per capita insurance premiums in Iran, but with a time lag, this relationship is positive. At the same time, there is a negative and significant relationship between negative uncertainty changes and per capita insurance premiums, but with a time lag, this relationship is not significant. 5- Conclusions & Suggestions The negative impact of uncertainty on insurance premiums suggests that in times of high economic uncertainty, people seek to reduce costs and maintain the value of their assets in the housing, foreign exchange, and gold markets, so their demand for Insurance is reduced. In conditions of economic stability, due to the uncertainty of the life expectancy of the head of the household and as a result of the uncertainty of income, the demand for insurance has increased, which increases the per capita insurance premium. Therefore, given the negative impact of monetary policy uncertainty on insurance premiums, the central bank's relationship with the financial markets must be well managed. The use of communication strategies can become a central bank policy tool in monetary policy. Proper management of these communication strategies can improve the effectiveness of the financial sector by reducing uncertainty in monetary policy. In other words, policymakers must consider the effects of these decisions on financial markets when formulating monetary policy at the macro level.