Iranian Journal of Economic Research
Year:2016 | Volume:21 | Issue:67 |Papers Count:8

There have been many conflicting studies on income inequality and life expectancy in the past four decades. It seems that many of these studies are affected by a statistical artifact which could lead to measurement error. In this paper, after correcting the statistical artifact, we examine the relationship between Gini coefficient (as an index for income inequality) and life expectancy (as an index for public health). To this end, this study uses panel data with random effects for 19 countries (including Iran) over the period 2004 -2012. After correcting the statistical artifact, results do not suggest any particular association between income inequality and life expectancy.

Investigating the behavior of religious households is among important subjects in Islamic countries. As there are religious expenditures in consumption basket, recognizing factors affecting those expenditure is significantly important. By using income- expenditure data, and probit method, this paper is analyzing the case of Iran, in urban and rural regions for 2014. The variables include payment to charity funds, age, literacy level, household dimensions, employment, marriage situation, and home ownership. The results show that there is a positive and significant relationship between the above variables and the religious payments. The household dimension, however, does indicate a negative impact on religious payments. The literacy in rural area and employment in urban area do have much more impact relatively. Finally this research is an implicit testing of Barro’s hypothesis (negative relationship between religious behavior at one hand and prosperity and literacy on the other).

One of the main approaches to achieve food security is redistribution measures such as the subsidy reform program with the aim of social justice and improved welfare of low-income groups. In this study, we analyzed the effect of the implementation of targeted subsidies program on food security in Iran during 2005-2012. A model of food security was estimated after calculating the adult’s energy intake through household’s consumption information. We found an inverse relationship between the subsidy reform program and food security among Iranian households. Due to this program, food prices increased and households’ real income decreased. The results of these changes are the increased cost of living and decreased share of income spent on food.

The employment and access to job is one of the most basic needs of a community so that the increase in employment is seen as one of the indicators of development in societies. Given the importance of the issue, the aim of this study is to evaluate the effect of exchange rate overshooting on employment in agriculture, industry and service sectors in Iran during 1973- 2011 using the seemingly unrelated regression and vector error correction model. The results of vector error correction model indicate that due to expansion in money supply exchange rate increases and divergence from equilibrium path occurs which finally leads to adjustment in the long run. Also, the results of seemingly unrelated regression model show that employment in industry and service sectors is respectively negatively and positively affected by exchange rate overshooting, yet the impact of this overshooting on employment in agriculture sector is not significant. In this regard, the demand of labor in the industry sector compared to service and agriculture sectors was the most sensitive to exchange rate overshooting. In addition, capital stock in industry and service sectors has a positive impact on employment in each sector.

The purpose of this study is to calculate Value at Risk (VaR) of a selection of bank's currency portfolio, using GARCH- EVT- Copula (GEC) approach. Today's main challenge of a banking system is to calculate and quantify the risks that the system is encountered. There are numerous approaches to calculate the risks. usually these approaches assume a common known distribution for the assets portfolio and generally a normal distribution is utilized for the experimental models. Nevertheless, the distributions of the assets are fat-tailed distribution and consequently normal distribution assumption may lead to inaccurate estimation. This article does not assume a specific asset distribution. This study applies autoregressive threshold variances (GJR- GARCH) for inter temporal individual's asset variable returns distribution. It also utilizes extreme value theory or the fat-tailed distributions and Coppola functions for all asset returns in an asset portfolio. In this study VaR is estimated using variance- covariance and historical simulation methods. Finally, in order to test the reliability of the applied models Kopic method is used. The sample data of the bank's currency portfolio consists of the market daily figures of the US Dollar, Japan's Yen, Turkish Lire, Emirate Dirham, Korean Won, and Euro exchange rates from 21March 2007 till 19 April 2012. Results show that the estimated VaR using GEC model is higher than those of estimated using the other two methods. They also show that reliability and precision of Kopic test is higher than those of variance-covariance and historical simulation models.

In this study, by employing a flexible cost function we calculate the technological change measure and total factor productivity and examine the impact of technology on the combination of input and scale of production in Iranian manufacturing industries. According to the results of technological change at the average data level, total production cost of industry has decreased by an amount of 0.49 percent during the period 1996-2009. All 23 studied industries have deviation from input technology. In addition, technological change has led to saving in raw materials and to an increase in the use of three inputs of labor, capital and energy. The technological change is non- neutral and has led to changes in production scale and based on the technology scale bias, technological change has led to a decrease in optimal production scale.

During two last decades, Iranians have faced with a wide and substantial increase in housing prices, especially in great metropolitans such as Tehran, Mashhad, Isfahan and Shiraz. This easily could be imputed to a high inflation which significantly impeded the access to housing for low and medium income families. This study uses a structural model to recognize the influential factors of such a rise in housing prices and to show whether there is any price bubble in market. The model consists of both supply and demand side determinants to explain the price changes across Iranian provinces over 1375-1390, in a panel data context. In particular, we use a longer and larger database which also includes more number of influential factors. Some specific features of data such as non- stationarity and cointegration have been also taken into account. Our results show that, in contrast to the common thought, there is no price bubble in the Iranian housing sector. That is, the structural model could well explain the rapid increase in Iranian house prices during the last decade. In particular, we find that the expansionary monetary policies of the government, the land price for urban uses, along with the increase of the real demand for housing are the main reasons of the past inflation in the sector. On the average, one percent increase in the urban land price or liquidity, ceteris paribus, leads to, respectively, 0.375 and 0.5 percent increase in house prices.