فصلنامه پژوهش ها و سیاست های اقتصادی
پیاپی 57 (بهار 1390)

This paper studies the impacts of domestic energy price increase along with cash subsidy payment to households and also to production sectors. We applied the MOF_CGE (Ministry of Finance_Computable General Equilibrium Model) which considers transport and trade margins and introduces a modified Armington aggregator for foreign transactions. The data is based on the 2001 social accounting matrix which includes energy carriers. We assume two policy scenarios for price increase and two scenarios for cash subsidy payment. The energy prices increase up to FOB price in one scenario and to the 75% of FOB in another. The government pays 50% of the policy revenue to households in one scenario and 60% in another with 30% to production sectors in both. We found that increasing the household share from 50% to 60% will compensate half of welfare reduction. The results show that in short run the welfare and production decline but imports and exports increase. Comparing with those studies with no redistribution consideration, we found that the cash payment policy compensates the welfare and productivity reduction to some extent.

Housing economy is one of the new branches of economics. During recent years, for reasons: development of housing market, intense fluctuations in amount of demand and supply for this good and so direct and indirect influences of housing sector upon other economy sectors led to need for accurate and suitable programming for take a decision about future investment policies in housing sector.This study want to make a mathematical model in order to enter risk conditions, uncertainty and recent fluctuations in demand and supply sector of housing. so this study want to introduce optimum modeling to investors and managers in order to feasibility and determination of investment priority for future investments and preparation of investment comprehensive map in housing sector of Iran. This study consider aims of the research in three scenarios (pessimistic, optimism and uncertainty), so this study done upon the whole of provinces and in the period of (1377-1387).The results are composed of investment index, priority rank and share of each province of the total investment in housing sectors. Furthermore the final result indicated that regarding risk and uncertainty conditions and market fluctuations, current model of investment in housing sector is not optimum and need for adjustment in quantities and percents of investment.

Inter industry trade (IIT) is simultaneous import and export of commodity and services which have been categorized in a similar industrialized group. IIT deals two parts including horizontal and vertical IIT that are defined by trading of yields which are similar and different in qualification, respectively. Vertical IIT in Iran is about 80/92% of whole IIT, so this paper is focused on it. This study has analyzed the vertical IIT specifications by Grubel and Lloyd between Iran and several important trading partners (such as china, South korea, United arabic emirates, Japan, Turkey, Malaysia and Singapore) via panel data approach at (1997- 2004). The finding results of this paper without considering fixed effects indicates that there is positive relation between vertical IIT levels and GDP and also between the differences of per capita GDP and geographical interval between Iran and selected countries. Therefore, these three variables can be the determinant factors of vertical IIT but by considering fixed effects method, the obtained coefficient for geographical interval is inconsistent with theory which might being lead by structure of transportation network. Findings of this paper can help to shed light on Iran trading policy procedure.

Productivity, illustrates the relationship between the quantity of produced goods and services, output, and the quantity of labor, capital, land, energy, and other resources that produced it, the input, is a key element in analyzing an economy, for it illustrates both the efficiency of industry and the wealth-generating capability of the economy. However, this paper computes key industries to promote overall labor productivity in Iran by xiaoming,1998 method. In this study, we use the Input-Output tables of Iran for the years1984,1988,1993,1999 and 2005.We found that paper industry and water, electricity and Gas and financial sectors are key sectors or productivity incentives sectors in Iranian economy.

In this study, the total factor productivity from 1994 to 1999 has been evaluated by Solo residual and Tornquist index and then the total factor productivity process in large industrial centers separated in two digit code of ISIC, have been compared. The results of productivity evaluate show that total factor productivity in investigating period time has increased an average annual 4/1%. In addition, by using internal growth index and in the field of human capital, the role of education, experience on the technical progress in the growth of total factor productivity have been investigated. The results of studies by applying the panel data technique show that human capital of education type, have positive and meaningful effect on total productivity rate. In additional, the increase of the share of employees with minimum 10 years experience has a positive meaningful effect in improvement of total factor productivity. The positive and meaningful effect of technical progress have been confirmed. Finally, improvement social capital by unemployment capacity of agencies has a positive and meaningful effect in improvement of total factor productivity.

There is a high potential for nurturing cold water fish and especially trout in Fars province. The objective of this study is to investigate the production condition of the individual trout nurturing farms in Fars province. To get the objective concepts of production function, efficiency and Total Factor Productivity (TFP) was applied. The concepts were evaluated by using data of 56 active farms during (1382-1387). The findings of the production function showed that the farms have experienced a constant return to scale during the selected period and the food has been the main production factor. Under variable return to scale, the technical, allocative and scale efficiency of the farms were obtained 0/963, 0/622 and 0/984 on average, respectively. The results showed increasing return to scale in the case of more than two-third of farms. It was also revealed that TFP of the farms has been increased by 16% during the selected period, coming from only technological progress and both part of technical efficiency including pure technical efficiency and scale efficiency has been decreased.

The purpose of the present article is to investigate the impact of fiscal corruption on government tax revenues and government expenditure in selected developing countries. To do so, by using from panel data method and statistical information of years (2000-2007) for 31 developing countries, the impact of fiscal corruption and other independent variables on government tax revenue and government expenditure have been investigated. The results show that, following the increase in fiscal corruption reduce government tax revenue relative share of gross domestic product. That means a negative impact on government tax revenues, the results also indicate that because of increase in corruption index (reduced levels of corruption), government expenditure increases as a percentage of gross domestic product.

Health sector and its infrastructure needs in both software and hardware sector has always been emphasized. Among importance of the medical equipment and items in the health system of the country is not covered on any one. Organizations and companies active in this sector should be able to take correct decisions with regard to information in the volatile business environment today on time. Thus, estimating demand in future periods seems vital. There are various methods and tools for forecasting demand that each have advantages and disadvantage its own special. In this paper, using a multilayer neural network with two hidden layers that has been learned with genetic algorithm as the learning algorithm, the comparative system with Common method used in the prediction (Box - Jenkins Method) with model ARIMA (2,1,1) has been presented for the forecasting demand CT-Scan set, that According to the measure of the accuracy of models, the mean squared error (MSE), the neural network model shown of the more effectiveness and efficiency as compared to ARIMA method according to the data and information in forecasting demand CT-Scan set.

The main purpose of this research is to investigate causality relationship between digital divide and income divide. Between Countries does digital divide (ICT infrastructure and access) support income divide? Or there is feedback between them? We use panel data set for 28 countries an period (2000 –2006) they have been assembled to test the Hsiao Causality. In order to, first the cross-country data concerning Gini coefficient for income divide and, Digital Opportunity Index (DOI) for digital divide and apply Hsiao Causality test. So the model is estimated applying the GLS estimation method. The results indicate that there is causality relationship between digital divide and income divide an Increase in digital opportunity support increase income inequality and by increase in the income inequality digital opportunity decreases.