فهرست مطالب avin khezri

The housing sector has always played a crucial role in the economy, with its fluctuations exerting significant effects on various economies. Prior to the 2007 financial crisis, standard models were commonly employed to explain price changes. These models assumed that agents were rational and well-informed, disregarding factors like irrationality and the heterogeneity of individuals that could contribute to such crises. However, agent-based models offer a different perspective, viewing the economy as a complex system with heterogeneous agents possessing limited information, engaging in interactions with each other. As a result, this study aims to evaluate a spatial agent-based model, specifically developed to analyze the housing market in Tehran. The simulation's results over an eleven-year period revealed that the growing demand from young households with limited savings for residential units under 100 square meters significantly drove up the prices of these particular units, outpacing other residential properties. Moreover, the findings indicated the higher growth of housing prices in the central areas of the city, primarily triggered by the influx of young households into these regions, seeking investment opportunities.

The rapid changes in the economic and social structure experienced by households during the economic transition prevent the generalization of a single model for the household’s distribution of household expenditures and incomes in developed countries. Therefore, the goal of this study is to estimate the revenue and consumption life cycle indices in Iran during the years 2001 to 1399. Based on the results, the age-profile indices show a hump-shaped pattern. Because the spending smoothing behavior distributes definitive sources of inequality evenly throughout the life cycle, it has a smoother age profile than income. More educated households with higher income levels and expenses have higher income growth rates for a longer period of time. Slow increase in consumption inequality relative to income indicates that most permanent changes in income have been predictable for individuals. Also, according to the permanent income hypothesis and the findings of other economies, consumption inequality has increased for households over 30 years old. This result is consistent with incomplete market life cycle models in which variance is a constant component for all early in life cycle is small, and increases over time due to the accumulation of certain permanent shocks. Finally, estimates of the income process show that although permanent income shocks are the same for all households, in without an academic degree group, past incomes have a greater effect on current incomes, and this group suffers larger transient income shocks.

Health shocks increase household health expenditures due to disease and reduce national income due to reduced productivity and labor force size. The main purpose of the present study is to investigate the impact of health shocks on economic growth and life insurance consumption in developed and developing countries between 2000 and 2017.

 In this study, first positive and negative health shocks are extracted using the Mork rule and then the relationship between these shocks with economic growth and life insurance has been studied in the PVAR framework.

The results of Impulse response function indicate that because of lower life expectancy and lower public health levels in developing countries compared to in developed countries, public expenditures have been more effective. Therefore, positive health shocks will have faster economic growth in these countries. Also, the response of life insurance consumption to health shocks varies in two country groups, and each additional health surcharge in richer countries is weaker than poorer ones. The results of variance decomposition in both groups of countries showed that most economic growth fluctuations are explained in the long term by negative health shocks. The results of variance decomposition in life insurance for two groups of countries indicate that most volatility of life insurance consumption is explained by negative health shocks. Granger causality test results show the causality relationship from health shocks to life insurance consumption and economic growth in the studied countries.

According to the results of impuls response functions, variance decomposition and Granger causality, the positive effect of increasing government health expenditure on economic growth and life insurance consumption and the negative effect of reducing health expenditure on life insurance consumption in developing countries, shows the important and strategic role of government in health promotion and economic growth. 

In recent years, many countries have experienced boom-bust cycles in credit and asset prices, some of which resulted in severe financial crises. Given that housing prices in both advanced and emerging countries have been heavily influenced by housing credit, the decline in housing prices is similar in both groups of countries. In response to these cycles, authorities in many countries have used macro prudential policies as the frontline of defense against the financial instability risks. Macro prudential measures are, indeed, policy tools that have been used intensively in recent years to target suppliers or applicants of financial services (e.g., households and firms). There is no consensus on the relationship between monetary stability and financial stability and their effects on each other. Some argue that while high-interest rates may control inflation (monetary stability), they are deemed to destroy banks’ balance sheets (financial instability). Another argument is that in the financial instability condition, the contraction monetary policy intensifies the likelihood of instability in the financial institutions. In turn, some believe that the financial policies adopted by monetary institutions, including the central bank, are the leading causes of financial instability. On the other hand, some believe that financial stability preservation is always one of the intrinsic duties of the central bank. In effect, the lack of cooperation between the macro prudential and monetary policy-maker authorities may lead to conflicting policies and, therefore non-optimal results. Moreover, monetary and macro prudential policies as complements to each other can guarantee monetary and financial stability at the same time. This paper studies the effect of macro prudential policies and the interaction of monetary and macro prudential policies on the credit growth and housing prices using the generalized moment method. To that end, the first macro prudential tools index (including the capital requirements, loan-to-value ratios, and debt-to-income ratios) are constructed for the advanced and emerging economies over the period 2000 to 2014. Then, an aggregate index was constructed under two scenarios of tightening (contraction) and easing (expansion) actions. In effect, the produced aggregate index showed the state of macro prudential policy in each country. To construct the macro prudential tools, IMF (2011) data used in the study of Lim et al. (2011) and Shim et al. (2013) were considered. Following Eckinsky and Ramsey (2017), this paper used seven macro prudential tools (i.e., loan-to-value ratios, debt-to-income repayments and other housing sector tools, countercyclical capital requirements, loan-loss provision requirements, consumer loan limits, and credit growth limits), to construct the aggregate indicator for the macro prudential policy and sub-indices for housing and non-housing in the studied countries. The dummy variable was, in turn, used to construct the macro prudential tools. If the macro prudential tool was used or intensified in the desired season, the dummy variable was considered 1, and if the use of the macro prudential tool was reduced, the dummy variable was -1. Otherwise, if no macro prudential tool was used, the value was zero. The aggregate macro prudential policy index for each of the housing and non-housing sectors was considered as the sum of the dummy variables. In addition, by aggregating the dummy variables of the specific tools in each country, the non-housing and housing macro prudential policy indexes were constructed. The aggregate macro prudential index was also obtained from the sum of the housing and non-housing indexes. The results showed that the macro prudential policy indexes (aggregate-housing) had no significant effect on the housing prices and credit growth. However, the simultaneous adoption of the macro prudential policies and monetary policies inhibited the growth of the credit and, consequently the rise in the housing prices. In turn, a comparison of the coefficients showed that the effect of these tools on the credit growth was greater than the housing price growth. This finding, consistent with the results of other research including Wenden Beach et al. (2012), Kotner and Shim (2012), Brno and Friedrich (2014), Bruno et al. (2017), showed that the effectiveness of macro prudential policies in controlling the credit growth was more than lowering the housing prices. On the other hand, the interaction of monetary policies with the non-housing and housing macro prudential policies produced results which were more effective in controlling the credit and housing prices, respectively. In other words, the macro prudential policies that targeted the housing sector were more effective in controlling the housing prices. However, non-housing macro prudential policies were more effective in reducing the credit growth.

Foreign trade sector works as main lever of economic growth and development, Therefore it has been drawing much attention in developing countries.The impact of economic sanctions on Iran’s foreign trade Structure is important especially in the composition of imports because it is an essential ingredient of economic growth and development. The main purpose of this study is to assess the impact of economic sanctions on imports composition of Iran (1981-2013). For this purpose, sanctions have been divided in to limited, moderate and extensive sanctions based on the scales provided by Hufbauer that two dummy variables presented in the model, Then, the impact of these dummy variables along with other variables in the import demand function of capital, Intermediate and consumer goods have been estimated by FMOLS. The results showed that both of extensive and limited economic sanctions have reduced import of intermediate goods. On the other hand, capital and consumer goods import have increased during the period of extensive economic sanctions. However, limited economic sanctions have no significant effect on consumer imports.

The main purpose of this study is to assess the impact of economic sanctions on composition of major trade partners of Iran (1992-2013). For this purpose, sanctions have been divided in to limited, moderate and extensive sanctions based on the scales provided by Hufbauer and compiled two dummy variables in the model, Then the impact of this dummy variables along with other variables in the model's share of trade with partners have estimated by Panel data analysis. The model structure this study consists of two stages. At first, the model was estimated for all foreign trade partners. The results showed that extensive economic sanctions not only in current period but also in post-sanctions period has reduced Iran’s trade share with the trading partners. Second, to analyze the sensitivity of the model estimation results, all selected countries were divided into two groups; declining trade with Iran, ascending trade with Iran countries by using Iranian trade share with them. The results showed that extensive economic sanctions not only in current period but also in post-sanction period have reduced Iran trade with the first group on the other hand the trade with second sub-group countries has reduced in the period of sanctions.