جستجوی مقالات مرتبط با کلیدواژه « provinces of Iran » در نشریات گروه « اقتصاد »

Identification and analysis of energy consumption components can provide opportunities to optimize energy consumption, especially if combined with spatial analysis. The main purpose of the present research is to analyze the spatial panel of the determining factors of energy consumption components (activity, intensity and structure) for 31 provinces of Iran. For this purpose, first, with the factor analysis approach, energy consumption was decomposed by using the latest available data during the period of 2011-2017, and then, using spatial panel data regression, the determining factors of the components of energy consumption in the provinces were investigated. Based on the findings, firstly, Spatial Durbin Model has been selected as the optimal spatial model. Secondly, value added(activity index), industry share(structure index) and urbanization share have direct and significant spillover effects on energy consumption components. The positive effect of industry's share on structural and intensity components can be caused by changing the economic structure towards energy-intensive and low-tech activities. As expected, technical efficiency has a negative and significant effect on the intensity component of energy consumption, and in this regard, spatial effects have strengthened the direct effect. Based on the results, it is recommended to pay attention to the spatial structure of the provinces in energy planning. Secondly, it is recommended to improve the efficiency of economic activities and human capital. Emphasizing the intensity and structural components in order to reduce energy consumption can neutralize the positive effects of variables such as urbanization.

Housing price shocks of one region may spread to the housing market of neighboring regions or geographical areas bounded by political border and lead to the formation of price shocks in shock-receiving areas. The housing policies may not be effective when implemented regionally and separately if there is a confirmed network connection between the housing markets of regions. Price shocks to a housing market spreads with a delayto interconnected housing markets, ultimately resulting in the diffusion of the price shock across the entire of the housing network. This researchaims to investigate the housing network between selected cities (centers of the country's provinces) using the VAR model and Forecast Error Variance Decomposition (FEVD). The results of this research confirm the existence of a network connection between the housing markets of the country's provinces, and unlike previous studies, the results show that it is not only the city of Tehran that spreads price shocks to other regions, but also cities such as Karaj, Shiraz, and Arak spread price shocks to other cities. In addition, the results suggest that the recent price jump, since 2019 has significantly increased the density of the housing network in the country. Based on this, price shocks are expected to be distributed more quickly throughout the country.

Introduction :

In recent decades, achieving sustainable employment has become one of the main goals of economic policies. As a result, a large amount of research has been carried out in order to determine the most influential variables on the increase of employment in order to make a suitable economic policy. In this research, variables such as human capital (Kapelras et al., 2019), government spending (Doi et al., 2018), income distribution (Neos et al., 2016) and institutions (Galindo Martin et al., 2021 and Urbano et al., 2019)) have been effective factors in increasing the level of employment. However, important factors can potentially provide a significant portion of new jobs. Therefore, entrepreneurship can be another effective factor in increasing the employment rate.Over the years, entrepreneurship has been proposed not only as a policy and strategy priority for economic growth (Adertesh, 2018 and Pepra and Adekoya, 2020), but also as an engine for creating employment and poverty alleviation (Desai and Hessels, 2008, Adosi, 2016 and Folster, 2000). In other words, the existing literature has proven that entrepreneurship ensures the welfare, productivity and efficiency of the economy (Bamol, 1990) and acts as a main driving force for promoting innovation, achieving new business ideas and changing economic structures(Adretsch et al., 2002; Fritsch, 2008 and Gomes et al., 2022). Furthermore, entrepreneurial activities in an economy have been proven to contribute to resilient economic performance by introducing innovations, implementing change, promoting and improving competitiveness (Wang et al., 2005). The organizational policy of the European Union also confirms the importance of entrepreneurship as a core competency for employment, growth and personal fulfillment (EC, 2004).

In spatial econometrics, spatial effects are added to the performance of periodic or complex regression models (panels). Therefore, in spatial econometrics, sample information has a spatial component. When data has a spatial component, two issues can be raised: (1) Spatial dependence, and (2) Spatial heterogeneity. Before estimating spatial panel models, we need to perform spatial dependence tests and to check the existence of autocorrelation between disturbance terms. The existence of spatial coherence between observations and spatial autocorrelation between disturbance terms indicates the need to use spatial panel models. To do this, Moran, Jerry C, and Jetis Ord J tests are used. The Moran test examines the assumption of spatial autocorrelation between disturbance terms. In spatial econometric models, to model spatial reactions, it is necessary to select the numerical value of spatial directions. For this purpose, we have two sources of assumptions: (1) Position on the coordinate plane, which is expressed by latitude and longitude, so that the distance of any point in the location, or distance of any observation located at any point relative to fixed or central points or observations can be calculated. (2) The source of spatial information is neighborhood, and which expresses the relative location in the space of an observed peripheral unit, compared to other such scales.

The aim of the current research was to analyze the effect of entrepreneurship on employment in the provinces of Iran during 2013-2020 with a spatial econometric approach. First, in order to check the diagnosis of spatial dependence, the spatial dependence of the provinces was confirmed by Moran's test and based on the significance of the above test and according to the statistical coefficient of the Lagrange test, the research was evaluated in the framework of the spatial Durbin model. According to the results of the research, the entrepreneurship index has positive and significant effect on the employment rate of the target and neighboring provinces (overflow), and this result is coompatible with the findings of other researches, including Zu et al. 2022), Levin and Rubinstein (2018), Ataf and Al Balushi (2015), Miriam and Sandi (2015), Amini et al. (2013), Khoda Muradpour et al. (2018) and Khorsand et al. The research questions were confirmed. In addition, the variables of price index and wage rate have negative and significant effects on the employment rate of the target and neighboring provinces, while the gross domestic product has a positive and significant effect on the employment rate of the target provinces.

Based on the results, the suggestions of the present research in order to increase the employment are as follows:Financial support for provincial entrepreneurs through the removal of production barriers, the use of up-to-date global technologies in order to create competition with international entrepreneurs and reduce capital risk.Presenting specialized trainings in the field of entrepreneurship with the approach of better understanding of investment opportunities, familiarity with different regions and provinces in terms of relative advantages.Supporting small and medium enterprises in provincial development programs through incentives, tax exemptions, and government subsidies.Stabilizing the price level in order to create a safe environment for encouraging entrepreneurs.Adoption of policies to create small and medium industries in rural areas and small towns.Establishing provincial meetings between top entrepreneurs for consultation, transfer of experiences, and awareness of existing problems in this field.Improving various infrastructures in deprived areas to attract more entrepreneurs.

Poverty is one of the major problems of human societies that causes many social harms. Therefore, policymakers and economic development planners always aim to eliminate it. In addition, economic growth is one of the important and influential variables of macroeconomics. Therefore, examining the impact of economic growth on poverty through the lens of growth and distribution effects offers valuable insights for policymaking and poverty reduction strategies. In this study, we use the log-normal curve approach introduced by Bourguignon to estimate the growth effect on poverty utilizing data from urban households in Iran over the period 2013-2019. The results indicate that only in the one-year period of 2015-2016, the triangle of poverty, growth, and inequality has worked well and the growth has been pro-poor.Furthermore, provincial-level findings unveil discernible patterns:(a) In provinces experiencing positive growth, urban areas in Qom exhibit pro-poor growth, while those in Alborz, Golestan, and Hamedan provinces observe a trickle-down effect. Meanwhile, in other provinces, growth demonstrates an immiserizing trend.(b) In provinces with negative growth, only urban areas in Markazi province observe a reduction in poverty. However, due to the lack of growth, it cannot be concluded that this province has had pro-poor growth. In the urban areas of other provinces in this group, the situation has been unfavourable for the poor.

Inequality of income and consumption of renewable and non-renewable energies is one of the important issues of many countries and has many economic, social and environmental dimensions. Also, income inequality is one of the most important obstacles to the development of different societies. In this research, using data from 1389 to 1398 and the method of generalized moments (GMM), in addition to income inequality, the effect of economic growth and urbanization on electricity consumption in the provinces of Iran has been investigated. The results show that a 1% increase in the Gini coefficient reduces electricity consumption by more than 5%. Also, a 1% increase in GDP increases electricity consumption by more than 1.5%. This is despite the fact that the square of gross domestic product has a negative and significant effect on electricity consumption, and an increase of one percent causes a decrease in electricity consumption by more than 0.03 percent.   Therefore, the existence of an inverted U-shaped relationship between gross domestic product and electricity consumption in Iran's provinces is confirmed. Finally, the results show a positive and significant effect of urbanization on electricity consumption, so that with a 1% increase, electricity consumption increases by more than 0.2%.

Regional equal opportunities are the most important socio-economic challenges, whose inappropriate distribution can have detrimental effects on achieving economic stability and integrated progress of a country. Fiscal decentralization is one of the factors that affect the distribution of development opportunities. For this purpose, in the current research, first, by using the two-stage TOPSIS method, an attempt is made to calculate the composite index of development opportunities in six sectors (cultural-social, educational, infrastructure, health-therapeutic, environmental, and economic), then using the vector autoregression method. The effect of fiscal decentralization on the equal distribution of development opportunities in the Iranian provinces spanning from 2006 to 2019 is investigated here by using Panel VAR. Additionally, a consequence of the existence of collinearity between the variables, the long-term relationships between the variables are determined and estimated using the Fully Modified Least Squares (FMOLS) method. The results imply that the impact of the variables of expenditure and revenue decentralization on the equality of development opportunities is positive in the short term, nevertheless, depending on the levels of development of the provinces, in the long term. Consequently, the more developed the provinces are and have a higher GDP per capita, the more equal the distribution of development opportunities may occur. Furthermore, the model estimation results indicate that there is a U-shaped association between economic growth and equality of opportunities. In addition, it was found that the variable of relative population density has an insignificant effect in the short term,

Industrial investments play an important role in improving economic performance and developing economic regions. The industrial sector is one of particular importance in the development process of a region where a significant portion of the population accommodates different levels of income. Achieving this important goal has an effective and decisive role in directing and accelerating the economic performance of the provinces of the country. Therefore, this study aims to analyze the spatial effect of industrial investment on economic performance in all provinces of the country, Iran with a combined spatial econometric approach during the period 2007-2019. Based on the results, the variable of industrial investment and its indirect effects have a positive and significant effect on improving the economic performance of the studied provinces. The results indicated that, the industrial investment should be considered as an important variable in regional development studies in adjacent areas with high economic growth provinces (spatial spillover effects). The results also show that the active population and employment had a positive and significant effect on economic performance, while the wage rate had a negative and significant relationship with the economic performance of the provinces.

In recent decades, the risks and environmental damage caused by economic growth, population growth and energy consumption have become more apparent. Meanwhile, one of the new advances in the study of the relationship between economic factors affecting environmental quality is the attention to the spatial nature of environmental phenomena. Therefore, the aim of this study was to model the relationship between carbon dioxide (CO2) emissions and economic growth along with other influential factors. CO2 emissions as a criterion for environmental pollution in Iran have been studied using the Spatial Durbin Model(SDM) and in the framework of spatial panel data among the provinces of Iran during the period 2003-2017. The results of this study show that in total, real GDP per capita increases CO2 emissions at the provincial level, because the positive real GDP per capita coefficient is larger than the negative real GDP per capita coefficient of space. Another very important variable is the intensity of energy consumption and its spatial interruption, which has the highest significant and positive coefficients in the model of this paper. Also, the weighted price of provincial energy and its space interruption have had a significant and negative effect on CO2 emissions. Also increasing the degree of urbanization in neighboring provinces has increased CO2 emissions. Finally, the spatial interruption coefficient of the dependent variable is significant and positive, which shows that the increase in CO2 emissions in neighboring provinces has increased CO2 emissions in the same province.

The main goals of this article are to measure pro-poor growth in urban areas of Iran using the Chanona (2020) matrix and to rank the categories of activities and occupational groups in urban areas of Iran based on poverty growth using the Euclidean TOPSIS technique. For this purpose, cost and income data of urban households in Iran during the period 2013-2019 has been used. The results show that during the period under review, only the period of 2016-2017, both growth and income distribution have reduced poverty and the growth has been pro-poor. However, in the period of 2015-2016, poverty has increased and growth has been Immiserizing. In other years, the Chanona index has shown an increase in poverty. The results of the TOPSIS model also show that among the categories of activities "financial and insurance activities" and among the occupational groups; The "Administrative and Office Staff" group ranks first in poverty alleviation. Therefore, to reduce poverty, it is recommended to pay attention to income growth and redistribution in economic planning and policy-making. Because paying attention only to growth such as the period 2015-2016 can increase poverty in Iran. In addition, although the improvement in income distribution can be such that poverty is reduced even in the absence of growth; But in other one-year periods examined, it can be seen that the lack of attention to growth has led to an increase in poverty in Iran and reduce in inequality alone cannot lead to a reduction in poverty

Industrialization is the engine of economic growth on the one hand, and on the other hand, it has the greatest effect on the emission of carbon dioxide. According to the economic literature, one of the most important factors in the emission of air pollutants is industrialization and the production structure in the industrial sector. Based on this, the aim of this research is to investigate the effect of industrial concentration on carbon dioxide emissions. This research was conducted using the panel data econometric model for 30 provinces during the period of 2010-2017. Investigating the industrial concentration index shows that the highest value is related to Bushehr province with 0.66 and the lowest value is related to Qazvin province with 0.018. In addition, at the country level, this index has increased from 0.110 in 2010 to 0.114 in 2017. The results of the model estimation show that industrial concentration, energy intensity, population and GDP have a positive and significant effect on carbon dioxide emissions. According to the research results, diversification of industrial activities in Iran's provinces is recommended based on regional advantage and the use of new production technologies to reduce energy intensity and thus reduce the emission of pollutants.

Energy intensity is an important indicator of energy consumption assessment and its reduction is one of the goals of policymakers and planners in countries. Developing effective policies to reduce energy intensity requires a thorough study of the factors that affect it. In this study, the effect of foreign direct investment on energy intensity convergence by Iranian provinces using spatial econometric technique and panel data of 30 provinces of the country from 2010 to 2015 was studied. After confirming the spatial dependence by Moran and Panel (robust) LM and LM tests, the absolute and conditional convergence of "β" has been tested. According to the results, the absolute convergence of energy intensity in the provinces of Iran was confirmed. This means that the rate of decrease in energy intensity in provinces with higher energy intensity is higher than the rate of decrease in energy intensity in provinces with lower energy intensity. To investigate the conditional convergence, the foreign direct investment variable was added to the model. The results indicate a conditional convergence of energy intensity in the provinces of Iran, as well as a decrease in energy intensity with an increase in foreign direct investment. In fact, foreign direct investment with the introduction of new production technology increases the efficiency of the use of production inputs such as energy, and this leads to the convergence of energy intensity among the provinces of Iran. The effects of the spillovers of foreign direct investment on the convergence of negative and meaningless energy intensity can be attributed to the low level of foreign direct investment attraction and its non-distribution at the provincial level. In general, the increase in foreign direct investment in a particular province causes the convergence of energy intensity and its spillovers effect potentially causes the convergence of energy intensity in the provinces of the country.

This study aimed to investigate the effect of social security expenditure on the convergence of social welfare in provinces of Iran. Results of estimating models, using Spatial Econometrics, revealed that social security expenditure has a positive and significant effect on the convergence of social welfare in provinces of Iran during the period 2006-2020. Moreover, findings demonstrated that direct and indirect effect of social security expenditure is also positive, in the sense that the increases in social security expenditure has not only improved the convergence of social welfare in all provinces, but its spillover effects have also improved the convergence of social welfare in neighboring provinces on average. Besides, the Absolute Convergence Rate was 0.053 and in the conditional models, its’ values were estimated to be 0.054 and 0.059, respectively. These findings show that the estimated Conditional Beta-Convergence Rate is higher while considering social security expenditures. Additionally, results revealed that the Misery Index and the Government Size have a negative and significant effect, while the Information and Communication Technology (ICT) and Human Capital have a positive and significant effect on the convergence of social welfare. Finally, an estimation of the Spatial Spillover Effects of social security expenditures in 2019 showed that each one of the provinces has the highest direct effect coefficient on itself, and then has the highest effect on neighboring provinces.

The unequal distribution of facilities, demand and supply of tourism in provinces of Iran is due to the different levels of tourism competitiveness in provincial. One of the reasons that can have a significant effect on this difference is the specialization of different subdivisions of the tourismsector in the provinces. But because of the indirect effects and the various behaviors of local governments in the specialization of tourism, the relationship between this specialization and the competitiveness in tourism is not necessarily the samedirection. This study aimed to investigate the impact of tourism specialization (by separating production specialization, accommodation specialization, travel agencies specialization and tour services specialization) on the tourism competitiveness between provinces of Iran using spatial panel econometrics. Data were collected for 31 provinces during the period 2011-2016. The results of Spatial autoregressive (SAR) showed that besides the accommodation specialization, other indicators of tourism specialization had a positive and significant impact on tourism competitiveness. Both demand-side indicators (including indexes of tourism demand, travel agency specialization and tour services specialization) and supply-side indicator (production specialization) has a positive and significant relationship with tourism competitiveness. Not significant of accommodation specialization can be from the consequence of the indirect and widespread effects that led to a deviation of investment in accommodation facilities and especially in the hotel industry. Also, the results of the spatial model on “specialization of tour services” index show that overnight stays of tourists in the border provinces are higher than the central provinces (including Tehran, Alborz, Qom, Qazvin, Markazi, Isfahan and Yazd). This conclusion, for the index of tour services specialization, indicates the weakness of these services in performance as an advanced means of attracting tourists and enhancing tourism sustainability in destination provinces.

Considering the difference in consumption patterns in different urban, rural and semi-urban areas; In the current situation, due to the increase in the number of consumers, the trend towards settlement and urbanization, the change in people's lifestyles, the desire to use luxury goods, the need to access consumer needs due to time constraints, there is always the risk of wasting and reducing resources and energy production forces. And also there has been a concern to improve and optimize the consumption patterns of people in the society. Therefore, semi-urbanization is an important factor on energy efficiency. Therefore, the present study investigated the effect of the semi-urbanized population of the country's provinces on the improvement of energy efficiency during the years 1389-1399 using the dynamic spatial econometric technique. In addition to the main variable of semi-urbanization, the effect of some other explanatory variables has also been investigated; Labor force, real GDP, added value of the industrial sector, foreign direct investment, population with high school education and above, degree of trade openness and dependent variable lag have a positive effect on energy efficiency. So that all the variables, except for the width from the origin, have had a statistically significant effect on energy efficiency. Finally, to compare the urban and rural conditions of the mentioned model, an estimate was also made for only urban and rural conditions, which shows the positive effect of the city and Village living is based on energy efficiency.

Qard-Al-Hasan is one of the most important Islamic banking facilities that can affect employment. In this regard, the present study investigates the effect of Qard-Al-Hasan loan, which is not in the category of echange and partnership mods in Islamic banking system of Iran on employment in Iran’s provinces will be analyzed. In this regard, a Panel Data model has been used for this purpose during 2015-2019. The preparing tests for the estimation of the modle lead the study to use the Feasible Generalized Least Squares method, and the results show that Qard-Al-Hasan loan has a positive and significant effect on employment in Iran’s economy. In addition, results show that Gross Domestic Product, Physical Capital and Labor Productivity have also a positive and significant effect on employment in Iran’s provinces, however, the impact of Gross Domestic Product and Phiscal capital are greater than other variables, indicating that employment in Iran more affected by such variables than other factors.

Regional development policy based on the existing capacities of knowledge and innovation in the regions is one of the neglected issues in Iran's development policy. At present, there is no serious difference in providing solutions for different provinces, while the provinces of the country are different both in terms of the level of knowledge and innovation and its absorption capacity. In this research, based on the review of existing studies and new principles of measuring regional innovation capacity, a suitable framework for measuring innovation capacity is presented and accordingly, the innovation capacity of the country's provinces is measured. Results showed that in proportion to the decrease or increase in the level of development of regions, the innovation capacity of regions also increases or decreases. Innovation capacity has also decreased in proportion to the increasing geographical distance from the center of the country. Hence, Sistan and Baluchestan province has the lowest level of innovation capacity and provinces around Tehran such as Semnan, Karaj, Qazvin and Qom, have relatively high levels of innovation capacity. Nevertheless, Ilam and Bushehr provinces are in the first to fifth place among 31 provinces in terms of innovation capacity due to two important factors: 1. Small population and 2. Existence of oil and gas industries.

The distribution of income, which means the distribution of national income between groups, social classes and economic sectors, is one of the main components of social justice. There are many factors affecting the income distribution. The purpose of this study is to identify the effect of unemployment rate along with other major factors related to income distribution in Iran’s provinces. For this purpose, the annual data for Iran’s provinces during 1999 to 2014, with DOLS estimator have been analyzed. The results show that increasing unemployment in the long run will increase the income inequality in the provinces. Also, inflation rate, economic growth rate and current government spending increase the Gini coefficient in the long run. Error correction model results indicate that, unemployment and government size variables have no significant relationship with the dependent variable in the short run. However Inflation rate and economic growth rate have a positive relationship with inequality in the short run.

In the literature on energy economics, estimating and analyzing price elasticities of energy demand is one of the important issues in examining the effectiveness of pricing modalities for energy conservatin and environmental policy follow-up. In this regard, low price elasticities of energy demand will increase the need for non-price policies to change consumer behavior and stimulate energy savings. This study aims to estimate and analyze the price elasticities of energy demand with an emphasis on regional (provincial) diversity. For this purpose, price elasticities of energy demand in Iran's provinces during the period of 2001-2016 were estimated using Augmented Mean Group (AMG) estimator with heterogeneous slope coefficients. According to the results, the absolute value of the price elasticity of energy demand among the provinces is less than unit (0. 92) , and by the provinces separately, it lies between 0. 37 and 1. 32, as well as the least and greatest values of the price elasticity impute to provinces Qom and Bushehr, respectively. In general, 12 provinces have a price elasticity of energy demand higher than unit and 16 provinces have less than one, among which those of Qom, Hamedan, Qazvin, Tehran and Gilan have the priority of implementing for non-price policies, respectively. Furthermore, results revealed that the price elasticities of energy demand among provinces have positive spatial autocorrelation. The most important policy and research recommendations of this study are discussed for policy makers and researchers.

The impacts of the tourism industry on economic growth can be divided into two categories: direct and indirect (spillover) effects. In the field of tourism, direct impacts have been the subject of many studies but the analysis of spillover effects, particularly the effects from tourism infrastructure development, have received less attention. This study, with an analytical approach and along with examining the quantitative methods and analysis of the spillover effects of various variables affecting the development of the tourism industry, has investigated these impacts for each the variables and in each province. For this purpose, it has used spatial econometric models. The results confirmed the existence of spatial fixed effects and was applied Spatial Durbin Model (based on Lagrange coefficient test). The results show a positive and significant impact of transport infrastructure variables (road, rail, air) and travel agencies on the growth of value added in the tourism industry. Investigation of the spillover effects of infrastructure variables on growth of value added has shown that, except for Accommodation services, other tourism infrastructure variables have negative spillover effects for neighboring provinces, and also have positive spillover effects for other (non-neighbor) provinces. The negative spillover effects on the tourism growth of the neighbor provinces are due to competition impact and relative stability in the number of domestic tourists, and the positive spillover effects on non-neighbor provinces are due to factors such as the development of multi-purpose trips and increased market access.

This paper presents a model for assessing the efficiency of e-commerce in the provinces of IRAN with data envelopment analysis (DEA). For this purpose, first, we assess the factors that affect to growth and use of e-commerce in Iran, then to show the efficiency of IRAN's provinces on e-commerce, data analysis model applied. Results show the average efficiency in IRAN in year 2016 compared to year 2013 increased. The numbers of efficiency in years 2014, 2015 and 2016 have a normal distribution, and only in 2013 we have outliers. Also MALMQUIST efficiency coefficient calculation results show we have progress in years 2015 and 2014 compared to 2014 and 2013.The most progress is in year 2014 that related to Isfahan province and in year 2015 related to Charmahalobakhtyari province. Ultimately the efficiency coefficient of MALMQUIST results 8 provinces in year 2016 have progress compared to year 2015 and 22 provinces during the same time period have regressed. The greatest progress in year 2016 is relating to Khuzestan provinces and most regression is relating to North Khorasan Province.