فصلنامه مطالعات اقتصادی کاربردی ایران
پیاپی 16 (زمستان 1394)

This paper extends recently developed parametric hyperbolic distance functions to the analysis of energy and environmental efficiency for a panel data of 30 provinces in Iran from 2006-2011, and then decomposes the growth of environmental total factor productivity into two component measures, namely, environmental technology change and environmental technical efficiency change based on the estimated hyperbolic distance functions. In this period of time, the results show that environmental total factor productivity change has decreased average 8/47 percent, because of high decreases in the environmental technical efficiency and increases emission of CO2. With increases emission of CO2, the environmental total factor productivity change has been smaller than total factor productivity change and means that in this period of time, the environment is faced with the phenomenon of destruction rather than improving.

Diversification of income sources is a strategic policy application in economics and management. Deal with the diversity makes it possible to access a more stable financial management objectives and its performance. In this paper, the effects of some variables such as fluctuations in GDP, tax diversification index, the share of indirect taxes, the tax to GDP ratio, oil income growth rate, GDP per capita, the share of agriculture value added, Gini coefficient on government tax income fluctuations are examined by using ARDL regression model.The results of estimating the regression model show that tax structure and the structure of the economy are important to bring stability for the combination of government tax revenue. In addition the tax structure and tax consequences affects on performance.

Carbon Dioxide (CO2) resulting from the combustion of fossil fuels has the highest share of greenhouse gas emissions. Non-metallic mineral products industries with a share of 25.8 per cent had a significant role in CO2 emissions of Iranian ten people or more industries at 2011. In order to have knowledge about the changes of such pollutions, the recognition of the influencing factors of emissions of them is required. In this study, using the LMDI approach, the changes in total CO2 emissions in Iranian non-metallic mineral products industries are traced back to changes in activity level, structural change between sectors, structural change within sectors, energy intensity, fuel mix and emission factors, over the period of 2000 – 2011. The results indicate that the changes in the activity level, structural change between sectors and emission factors are the major factors of increasing CO2, respectively. In contrast, changes in the energy intensity, structural change within sectors and fuel mix factors have decreased the CO2 emissions of such industries.

This study focuses on the relationship of poverty with economic growth and inequality during different socio-economic development programs in Iran between1989-2013. To this end, the elasticity of poverty was decomposed into growth and inequality effects; then the outcome of the economic growth is calculated using Kakwani and Son’s (2008) Poverty Equivalent Growth Rate index. This index demonstrates how the benefits of growth are distributed between the poor and the non-poor people. Study of the poverty equivalent growth rate can be an important tool for the governments to reduce poverty. Poverty changes decomposition to the neutral effects of the growth and inequality in rural and urban area shows that the effect of neutral growth on poverty is negative, whilst the neutral effect of inequality has positive and negative fluctuation. Iran’s economic and political evolvement during the years which our study focused on, can explain these fluctuations. Calculating Poverty Equivalent Growth Rate index and its comparison with the economic and social development programs in Iran, show that there were not any effective policies to achieve sustainable welfare.

In this study, using time series analysis, the long-run relationship between human capital dimensions (education and health) and total factor productivity of production in Iran’s economy is estimated during 1978 to 2010. Along with human capital indicators, other variables such as accumulation of domestic R&D capital and capital stock per workers are used as control variables. Cointegration analysis with estimating Unrestricted Error Correction Model (UECM) based on Bounds Test is performed. The Long-run and short-run coefficients, using Autoregressive Distributed Lag (ARDL) method, are estimated. The results confirm that the human capital indicators and capital stock per workers have significant and positive effect on the productivity level. The results of Granger-causality test based on Error Correction Model (ECM), show that there exist a bi-directional causal relation between the human capital (education) and total factor productivity of production in the long-run.

This paper investigates the relationship between demographic changes and tax revenues, as a prominent economical subject which can be transformed to an economic problem, potentially. So, the two tax bases, which have the closest relation with population changes, have been considered. To continue analysis, a microsimulation framework is employed which itself involves several stages: Firstly, income profiles of individuals have estimated. Then, using multi-rate tax function the tax revenue of every age group has been estimated. After aggregation and projection of total income tax revenues based on multi-rate function output, sensitivity analysis of each group's income against demographic changes has performed. Also, tax on consumption has estimated based on multi stage process and applying several estimator tools and input-output coefficients. Results show that, at the present, income's tax revenues of younger groups is affecting by demographic changes and other old age groups will be affect until 2030s decade. Tax on consumption will be affect slower than tax on income.

Aim of this paper is to survey asymmetric effects of natural gas price on it's demand in industrial sector and demand function of natural gas in this sector is derived. This paper surveyed existence of asymmetric effects of natural gas price in koyck model for period of 1991-2013. Results of this paper revealed that effects of natural gas price on it's demand in industry sector is symmetric in this period and effect of income changes on natural gas demand in this sector is asymmetric. In this period, as estimation results long run and short run elasticties of natural gas are -0.56 and -0.33 and long run and short run income elasticities of natural gas demand is 16/59.

There are two well-known indicators used to study how energy inputs are efficiently used: One is energy intensity which measures the amount of energy consumption for every economic output produced in the economy, and the other is energy efficiency (or energy productivity) defined as economic output divided by energy input. These two indices only take energy into account as a single input to produce GDP output. In contrast, total-factor energy efficiency index (TFEEI) incorporates other key inputs such as capital and labor as multiple inputs so as to produce economic output. This article estimates TFEEI of Iranian provinces large industries using total-factor frameworks based on data envelopment analysis (DEA) in the period 1387-1390. Results indicate that Total average of TFEE in The Iranian provinces large industries is 0.4 percent. Furthermore Hormozgan, Tehran, Bushehr, Azerbayjan Sharghi and Kerman provinces have the greatest value of TFEE, while the lowest value of TFEE index considered in Khorasan Shomali, Chaharmohal Bakhtiari, Sistan and Baluchestan, Khorasan Jonubi and Lorestan provinces. Also, according to the computation results, the average of TFEE in large industries in Iran decreased during 1387-1389 and due to recent plan subsidies and energy price reform improved in 1390.

Study on factors affecting income distribution is one of the most important goals of social scientists in developing countries. The role of education on income distribution, among others, is an issue that many social scientists have concentrated on it. In Iran, too, Income distribution is an important issue for many researchers and policy makers. In this paper, thus, it is tried to examine the effect of inequality in education on income distribution of Iran in the period of 1981-2011. Using Johansen-Juselius Approach and variables such as education Gini coefficient of labor force, and average schooling years as indices for inequality of education, we have examined the effect of unequal education on income distribution. Furthermore, the ratio of government expenditures on education, government size and per capita income are explanatory variables that are used in research models of this paper. This study showed that Gini coefficient of education is a better variable explaining the effect of unequal education on income distribution, indicating a direct relationship between unequal education and unequal income distribution. However, there is an indirect relationship between the ration of government expenditures on education and Gini coefficient of Income. This study shows that moving toward equality in education will result in a better income distribution. Furthermore, an increase in education ratio of government expenditures has led to a better condition in income distribution, i.e. decrease in Gini coefficient.

The hospitals are responsible for maintaining the health of the population and devote himself a large part of health expenditure. Evidence shows that there is a vast prospect to improve and promote hospitals resources (financial and human). Awareness of the amount of future demand highly ensures optimal management of resources and quality of services in the health field. The aim of this study is to investigate the linear (ARIMA) and nonlinear (neural network MLP) models to estimate the treatment demand at Imam Reza hospital of Urmia, using data at different time intervals such as daily, weekly and monthly in different sections of the hospital. The results of this study indicate that ANN MLP nonlinear model has a good performance in predicting treatment demand and it is capable to provide more accurate forecasts than ARIMA model. Neural network MLP model with an average error of 24.96% compared to ARIMA model with an average error of 26.73% has a high predictive power. Also the estimation results of pediatric ward indicate that the ARIMA model compared to Neural network MLP model has more predictive power, the reason for this inconsistency with research hypotheses must be sought in low variance of this section.