Hossein Tavakolian; Mehdi Sarem; Javad Taherpoor; Mahnoosh Abdollah Milani
Abstract
This paper models the assets and liabilities of the Social Security Fund in Iran. The fund's financial position in practice is influenced by the population dynamics between two generations of employed and retired people, focusing on four important characteristics: the premium rate and pension ...
Read More
This paper models the assets and liabilities of the Social Security Fund in Iran. The fund's financial position in practice is influenced by the population dynamics between two generations of employed and retired people, focusing on four important characteristics: the premium rate and pension benefits of the working and retired generation, the two-generation employed and retired population pyramid, the employment generation period and the retirement period. In this study, an overlapping generation model is designed to show the dependence of the stability of the fund on the generational population and the transitions between generations taking into account such characteristics. The simulation results show that although the ratio of assets to liabilities can be potentially high, the gap between assets and liabilities of the fund is so high that any of the proposed policies alone cannot close the gap and ensure its stability. Therefore, policy implication s to stabilize the fund's assets and liabilities can be proposed in two scenarios. The similarity of both scenarios is that the government first pays its share of the insurance and secondly increases the premium rate to 10%, with the retirement pension being reduced by 50% in the first scenario and 10% in the second scenario. The results of the analysis show that the improvement of the fund stabilization is mainly dependent on the decrease in retirement pension, which can be stabilized in a certain time horizon.
Majid Babaie; Hossein Tavakolian; abbas shakeri
Abstract
First studies in inflation forecasting were mostly based on traditional Philips curve in which the relation between inflation and unemployment is studied. However, after several decades and especially after the Lucas criticism, Philips curve faced great takeovers. The new Philips curve ties real and ...
Read More
First studies in inflation forecasting were mostly based on traditional Philips curve in which the relation between inflation and unemployment is studied. However, after several decades and especially after the Lucas criticism, Philips curve faced great takeovers. The new Philips curve ties real and expected inflation, not to unemployment rate but to a scale of the marginal cost. Since in the original form of Philips curve, marginal cost stimulates inflation, it is difficult to formulate models that are effective in predicting inflation. Therefore, using TVP-DMA model, which has the ability to fix these deficiencies, we try to improve predictability of inflation in Iranian economy. An independent variable in conventional models can be either significant or insignificant while in TVP-DMA model, it may be significant during a period of time and insignificant in rest of the times. Therefore, this approach lets us to determine the periods in which an independent variable is significant and when it is not. In this study, we use seasonal data during the period 1991-2015. The results based on outputs of the TVP, DMS, and DMA models show that, out of 100 time periods under study, the liquidity growth rate in 19, economic growth rate in 7, unemployment in 8, exchange rate growth in 31, changes in the bank deposit rate in 14, oil revenues growth rate in 15, inflation uncertainty in 14 and the budget deficit growth rate in 4 periods have significant effect on inflation. Based on these results, it can be stated that exchange rate growth, liquidity growth and oil revenues growth rate are the most important indicators influencing inflation rate in Iran.