Journal of Quantitative Economics
Year:2015 | Volume:12 | Issue:3 (46)|Papers Count:8

In recent years, factors influencing corruption have attracted more attention among the economists and policy makers, because corruption is one of the main obstacles to economic growth just as it causes declining government legitimacy, increasing illegal activities and political instability of countries. Therefore the purpose of this study is to estimate the index of corruption in Iran during the period of 1978-2013. In this study, to estimate the index of corruption the fuzzy logic (Fuzzy Logic) that is popular in applications such as ambiguous time series is used. The results show that the index of corruption fluctuated in some years but in recent years the trend for index of corruption has been upward. The other results of this study show that there exists a two-way causal relationship between underground economy and corruption in Iran.

The purpose of this paper is to examine the impact of uncertainty in macroeconomics on imports from selected developing countries. Exchange rate fluctuations, growth rate and inflation rate have been considered as indicators of uncertainty in macroeconomics. Uncertainty in macroeconomics causes uncertain environment in market and therefore creates some changes in the volume of imports. This paper tries to use Panel data model during 1980-2009 and General autoregressive Conditional heteroskedasticity to measure uncertainty and then examines the impact of uncertainty in macroeconomics on imports. The results of estimation of models indicate that uncertainty of economy influences the rate of imports.

This paper, using a dynamic panel data approach, investigates the impact of the profitability on the market concentration in the Iran four-digit textile industries during the years 2000-2007. To this end, we used profitability and market concentration degree to measure market performance and market structure, respectively. The results of this study indicate that profitability, as a criterion for market performance, has a positive effect on market concentration. In addition, the effects of export intensity, sales ratio, and investment intensity on market concentration are positive.

The aim of this paper is to study the effect of minimum wage increase on employment in Iran. For this purpose, a multi-sector, multi-labor computable general equilibrium model which includes some important assumptions of the labor market such as imperfect mobility of labor, labor-leisure choice, minimum wage and substitution between skilled and unskilled labor has been designed. Two types of labor-skilled and unskilled - are considered in this model. The model has been calibrated based on 2001 Micro Consistent Matrix. Results show that minimum wage increase will decrease unskilled labor employment in all sectors while it will increase skilled labor employment in agriculture and service sectors. It will also decrease skilled labor employment in other sectors.

In many studies, in order to predict economic variables, quantitative methods based on time series data or cross-section data are mostly used. Time series data or cross-section data do not control the heterogeneity of countries, and there exists the possibility of obtaining the risk of biased results. Panel data provides more informative data and a higher level of freedom so it leads to more precise results and predictions. In this study, while considering the significant role and proportion of dried fruits in non-oil exports, the synthetic artificial neural network-panel data method has been used to predict the price of pistachio, raisin and date exports. Then the predictions were compared, using the accuracy criteria, with the regression model (the two-way error component model). The data from ten target markets for each of the dried fruits from 1992 to 2012 was used, and the results of this study show that the new and synthetic artificial neural network- panel data method has a better performance in predicting the price of Iran's pistachio, raisin and date exports than that of the regression method. Therefore, it is suggested that exporters, policy makers, and researchers use this method in order to predict economic variables.

Inflation is one of the most important considered problems in economics, which has many harmful effects. Some of these harmful effects are lack of optimum allocation of sources, retarding the process of economy development and creation of inconfidence for the future. This study with the topic of "estimation of optimum rate of inflation for Iranian economy calibring Sydraski model" has been also an attempt to clear one subset of inflation issue. The method of tills study is descriptive-analytic. First, the model of study that is adopted Sydraski model (1967), is developed and for approaching tills model to reality, some parameters are added to it and it is solved by using Ramsey optimization method, which is a Dynamic general Equilibrium method. Having gathered and estimated necessary data, the model of tills study is established and optimization and calibration operations will be accomplished by using Matlab software. The results of tills investigation indicate that the inflation rate, which is able to have the most social welfare for Iranian economy, is -0.0196. This rate that expresses the most amount of welfare dependent, provide Freedman's optimization formula, From tills investigation's result, by increasing the population growth and also by decreasing rate of money circulation growth, by money creation by means of commercial banks, it is possible to reach lower inflation rate.