Zahra Moshfegh; Golrooz Ramezandeh Valis; Afsaneh Sherkat; Mohadeseh Soleimani; Ali Asghar Banouei
Volume 19, Issue 58 , April 2014, , Pages 117-152
Abstract
There are several methods of updating input-output coefficient matrix in last six decades, but there are still issues about RAS and adjusted RAS methods which have been focus of input-output analysts in recent years. One challenging issue is the relationship between more exogenous, superior or additional ...
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There are several methods of updating input-output coefficient matrix in last six decades, but there are still issues about RAS and adjusted RAS methods which have been focus of input-output analysts in recent years. One challenging issue is the relationship between more exogenous, superior or additional information of target year in adjusted RAS method and its statistical reduction error relative to conventional RAS method in updating the input-output coefficient matrix. Some analysts observe the positive relationship, whereas others by focusing on the nature and criteria of exogenous information opine that using more exogenous information in the adjusted RAS will not necessarily reduce the statistical errors compared to conventional RAS method. The existing evidence in Iran is around the findings of the positive relationship which has in fact lead to the common belief between compilers and also users of table in Iran. In this article we attempt to examine this issue by means of two symmetric input-output tables of the years 1996 & 2001 by posing two main questions. The first question: Is there any relationship between more exogenous information in adjusted RAS method compared to conventional RAS method in reducing statistical errors? Second question: Do the nature and criteria of more exogenous information, irrespective of more or less cells; have an influence on increase or reduction of statistical errors in updating coefficients? Our findings do not support the existing common belief among the compilers and users of Input-Output Table in Iran and reveal the followings: 1- The adjusted RAS method, in some of exogenous information, is not preferable to conventional RAS method. 2: Measurement of credibility of updated coefficients depends on choice of the nature and criteria of exogenous information, and 3: Using more exogenous information of the target year would not necessarily lead to decrease of statistical errors in the updated coefficients.
Majid Sameti; Saeedeh Izadi
Volume 19, Issue 59 , July 2014, , Pages 117-152
Abstract
Price change is the most important element in explaining the change of consumer welfare. Increase in prices decrease real revenue of consumers and by effect on consumer’s purchasing power, influence their poverty and welfare. Thing that helps governments in suitable policy-making ...
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Price change is the most important element in explaining the change of consumer welfare. Increase in prices decrease real revenue of consumers and by effect on consumer’s purchasing power, influence their poverty and welfare. Thing that helps governments in suitable policy-making for reducing poverty and protection of consumer welfare, is awareness from welfare loss resulting from changing in prices. In this paper, amount of welfare loss after increase in prices for various income deciles of urban households of Isfahan, is computed. For this, linear expenditure system by seemingly unrelated regression method is estimated by using data of income and expenditure of urban households during 2004-2011. And then amount of supernumerary expenditures, marginal propensity to consume out of supernumerary expenditures and the mental poverty line are computed. Compensation variations and equivalent variations in each of eight groups of commodity and service and also in each of ten income deciles are computed. Results show that increase in prices of foods, dwelling, transportation, miscellaneous commodity, health and treatment, clothes and shoes, furnitures, entertainments and education respestively lead to most welfare loss.
Esmaiel Abounoori; Azizallh Farhadi
Abstract
Input-Output Table (IOT) analysis is important especially concerning trade, environments, productivity for planning and policy making. Quality of the analyses depends on the estimation of Symmetric Input-Output Tables (SIOT) and also the use of the types of technology assumption (Product Technology versus ...
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Input-Output Table (IOT) analysis is important especially concerning trade, environments, productivity for planning and policy making. Quality of the analyses depends on the estimation of Symmetric Input-Output Tables (SIOT) and also the use of the types of technology assumption (Product Technology versus Activity Technology). The choice of the type of technology concerning SIOT estimation has been left to the member countries by the UN Manual. Choosing technology assumption in Iran has been based on expert judgments, institutional data requirement and avoiding negative elements. The question which arises here is that, would it be possible to choose the appropriate type of technology for estimation of SIOT in Iran? The main aim of this paper is to suggest an econometric test of hypothesis method concerning the choosing of technology type. For this reason, we suggest a Fisher type (F) test in which the Product Technology or the Activity technology will be chosen. If the Product Technology is dominant, the SIOT will be estimated based on the Product Technology. Otherwise, the Activity Technology may be applied. The results of the tests concerning 2011 SIOT have shown that Product Technology Hypotheses is more appropriate for some sectors, whereas Activity Technology Hypotheses for other sectors are not valid.
Agriculture, natural resources and environment Economics
Simin Azizmohammadi; Fatemeh Bazzazan
Abstract
Human demand for natural resources is surpassing the Earth’s biocapacity and regenerative capacity, leading to environmental degradation. Accurate research is essential to investigate and predict these changes more precisely. The ecological footprint serves as a suitable index for tracking human ...
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Human demand for natural resources is surpassing the Earth’s biocapacity and regenerative capacity, leading to environmental degradation. Accurate research is essential to investigate and predict these changes more precisely. The ecological footprint serves as a suitable index for tracking human demand, resource recovery capacity, and waste absorption in the environment. The concept aims to offer a land-based measure that estimates the impact of consumption on the environment in the land area required to fulfill consumption. The dynamic input–output approach represents a novel method for measuring the ecological footprint, predicting land use based on economic growth rates. Pioneering the dynamic ecological footprint calculation using real-world data, the current study calculated Iran’s ecological footprint by relying on 1395/2016 input-output tables from the Central Bank in three sectors: agriculture, industry, and services. The per-capita ecological footprint for Iran was determined to be 0.42 hectares with an 8% planned economic growth rate. If the ecological footprint continues to grow at the same rate, it is estimated that Iran’s land biocapacity will be depleted by the year 1412/2033. Considering a growth rate of 6.4% (excluding oil) in the year 1395/2016, this scenario is anticipated to occur by the year 1417/2038. IntroductionLand use has undergone significant changes due to urbanization and the expansion of economic activities, surpassing the Earth’s capacity for regeneration and absorption and resulting in environmental degradation. Exacerbated by population growth, the issue has caused more serious concerns among policymakers and researchers regarding the future of the environment. It is thus necessary to measure human demand and regenerative capacity of natural resources. In this respect, the ecological footprint is considered a useful measure, defined as an environmental index that quantifies natural resource consumption based on land use, and reflects the impact of human demand on nature. The comparison between human consumption and biocapacity aids in assessing the level of sustainability. Existing literature refers to two methods of ecological footprint calculation. Employing a macro perspective, the first method relies on the evident consumption of resources (land or water) involved in producing domestic goods and services—including imported goods but excluding exported goods. Many scholars have used the input–output model to calculate the ecological footprint for resource management at the sectoral level. The versatility of the model has led to its widespread application in recent years, as it can adapt to variations in monetary and physical units at the same time. It proves particularly useful in analyzing a wider range of environmental issues, such as life cycle assessment and ecological footprint calculation. While the ecological footprint is a vital tool for studying sustainable development, its traditional version primarily focuses on static calculations derived from past footprints. Some critics contend that ecological footprint analysis lacks a dynamic approach to the future, but offers more of a snapshot in time. Dobos and Tóth-Bozó (2023) employed a dynamic input–output model to develop a method for ecological footprint calculation. Within this dynamic model, the ecological footprint becomes predictable through the utilization of the capital coefficient matrix (investment matrix) in conjunction with the direct input coefficient matrix. The present study pioneered the dynamic ecological footprint calculation by utilizing real-world data and the dynamic input–output table of the year 1395/2016.Materials and MethodsThe study employed a dynamic input–output model that maintains equilibrium between supply and demand over specific time periods. Investment was taken into account through capital-output coefficients within an intra-sectoral capital coefficient matrix which shows capital exchanges between demand sectors and capital suppliers, proving valuable in predicting crucial economic variables and growth patterns. It also serves as an efficient tool for economic planning. The model proposed by Dobos and Tóth-Bozó (2023) is a function of vectors representing final consumption, exports, and imports of final goods. They had actually used the dynamic model developed by Leontief (1970) to calculate land demand for each period of national production. The present study showed how the index changes by taking into account the investment flow and the equilibrium path of consumption and production growth. The total ecological footprint is predicted in relation to the potential economic growth rate; Iran’s Sixth Five-Year Economic, Cultural and Social Development Plan (1396–1400); and the growth rate excluding oil in 1395/2016. To accomplish this, three sectors (agriculture, industry, and services) were formed within a closed dynamic input–output model, referred to as forward-looking. The data was gathered from the 1395/2016 input–output table from the Central Bank database, capital stock, inventory data (agriculture and industry) from the Statistical Center of Iran. The lands were studied in three sectors: agriculture, industry, and services.Results and DiscussionIn the dynamic input-output model, the potential growth rate is determined by the maximum eigenvalue of the matrix composed of the direct input coefficient matrix and the capital coefficient matrix. The potential growth rate was found to be 41%. Moreover, the planned growth rate of 8% in Iran’s Sixth Five-Year Economic, Cultural and Social Development Plan (1396–1400) was also considered. According the Statistical Center of Iran, the gross domestic product experienced an overall growth of 11.1% in 1395/2016. Excluding oil, this growth rate stands at 6.4%. The per-capita Iranian ecological footprint was measured at 0.42 hectares with an 8% planned economic growth rate. If the ecological footprint continues to grow at the same rate, it is estimated that Iran’s land biocapacity will be depleted by the year 1412/2033. Considering a growth rate of 6.4% (excluding oil) in the year 1395/2016, this scenario is anticipated to occur by the year 1417/2038.ConclusionAccording to the research results, changes in the growth rate alter the time horizon for land use. The growth rate is influenced by various factors. Consequently, advocating for short-term planning becomes crucial to either manage its effects in the long run or mitigate its adverse consequences—in case of its deviation from sustainable development goals. This model does not incorporate assumptions about technological progress in the economy. Future research could enhance the economic model by integrating technological progress, allowing for the evolution of model matrices over time. In the contemporary economy, Research and Development (R&D) plays a vital role in developing new technologies to promote environmental preservation. Furthermore, providing ample data can enable the creation of inverse Leontief matrices with larger dimensions, facilitating more practical outcomes, such as dynamic analysis of land-use changes within specific timeframes. The current research exclusively sought to introduce the index alongside its predictability. However, the absence of sufficient data might have resulted in estimates based on unrealistic data, impacting the accuracy and validity of the results. Nonetheless, these findings can aid in large-scale policymaking.
Employment
Leyla Jabari; Ali Asghar Salem
Abstract
Climate change, caused by the increase in the emission of carbon dioxide and other greenhouse gases, is one of the critical issues that mankind has faced and has created significant risks for both humans and the environment. In recent decades, many researchers have studied the factors that cause and ...
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Climate change, caused by the increase in the emission of carbon dioxide and other greenhouse gases, is one of the critical issues that mankind has faced and has created significant risks for both humans and the environment. In recent decades, many researchers have studied the factors that cause and affect carbon dioxide and their control. Among the factors affecting the emission of carbon dioxide, we can mention the structural labor change, which can play an important role in increasing the emission of carbon dioxide through the increase of industrial activities and economic growth. Therefore, in the present study, the effect of structural labor change on carbon dioxide emissions in Iran’s provinces was investigated using the Quantile regression with non-additive fixed effects presented by Powell (2016). The results show that increasing labor transfer from the agricultural sector to other economic sectors, including services and industry, increases carbon dioxide emissions. Additionally, indirectly, the structural labor change index has a positive and significant effect on carbon dioxide emissions in Iran’s provinces. The study also confirmed an inverse N relationship between carbon dioxide emissions and economic growth. The coefficients obtained for income inequality are negative and significant, while those for per capita energy consumption, industrialization, and urbanization are positive and significant. IntroductionSince the early 1990s, the emission of carbon dioxide and other greenhouse gases has increased in most countries, aligning with economic growth. This has given rise to numerous challenges for humanity, inflicting detrimental effects on ecosystems across various parts of the world. The increase in carbon dioxide emissions over the past two decades has prompted researchers to delve into the factors influencing such emissions and their control. One significant factor influencing carbon dioxide emissions is the transfer of labor from the agricultural sector to other sectors. This transition is recognized as a hallmark of economic development, commonly referred to as a structural labor change in the field of development economics. Though most economic theories view the labor transfer as an indicator of socio-economic progress, this phenomenon also has disadvantages that can result in abnormal consequences affecting culture, the environment, society, and economy. Shao et al. (2021) and Yang et al. (2021) highlight it as a pivotal factor influencing carbon dioxide emissions and environmental degradation. Understanding the impact of this phenomenon on carbon dioxide emissions is crucial for formulating policies aimed at regulating the emitted carbon dioxide levels. In Iran, the transfer of labor from the agricultural sector to other economic sectors has risen, driven by diverse motives and concurrent with the expansion of urbanization and industrialization. This shift may entail numerous environmental challenges. Long-term statistics reveal that since 1956, the agricultural sector has lost its superiority, while the industrial and service sectors have experienced an increase in the number of workers. The disparity between the industry and services sectors compared to agriculture has widened (Mohinizadeh et al., 2019). However, in Iran, the impact of structural labor change on carbon dioxide emissions has not received significant scholarly attention. In this respect, the present research aimed to explore the nonlinear effects of structural labor change across 31 provinces in Iran during 2010–2020. The study first calculated the carbon dioxide emissions in each province. Subsequently, the analysis focused on the impact of structural labor change, particularly the transfer of labor from the agricultural sector to other economic sectors, on carbon dioxide emissions in the provinces. Materials and MethodsThe study adopted the experimental model proposed by Liu et al. (2019) and Yang et al. (2021), utilizing the subform presented in Equation (1). (1) Equation (1) defines the following variables: lnCO_2 represents the logarithm of carbon dioxide emissions per capita; lnGDP signifies the logarithm of real GDP; ln2GDP denotes the square of the logarithm of real GDP; ln3GDP represents the cube of the logarithm of real GDP; lnRatioagr indicates the logarithm of structural labor change; lnGini is the logarithm of income inequality; lnUrb denotes the logarithm of urbanization; lnIndst is the logarithm of industrialization; and lnEC stands for the logarithm of energy consumption. Furthermore, lnRatioagr×GDP represents the logarithm of the interaction term between structural labor change and real GDP. This variable was incorporated into the model due to the indirect impact of structural labor change on carbon dioxide emissions. In addition to the variable of structural labor change, the study examined the effect of other explanatory variables on carbon dioxide emissions. These variables are summarized in Table 1. Table 1. Introduction of explanatory variablesSourceDescriptionVariableStatistical Center of IranThe ratio represents the percentage of the working labor force in the agricultural sector compared to the total working population. A higher percentage indicates less change in the employment structure, while a lower percentage signifies more pronounced structural changes in the labor force.Structural labor changeEnergy balanceTotal energy consumption per capita, encompassing natural gas, kerosene, fuel oil, and gasoline (thousand liters).Energy consumptionStatistical Center of IranThe ratio of the added value of the industrial sector to the GDP (million rials)IndustrializationMinistry of Economic Affairs and FinanceReal GDP (million rials).Economic growthStatistical Center of IranGini coefficient of total consumption expenditure of urban and rural households in each province, weighted by population (percentage)Income inequalityStatistical Center of IranThe ratio of the urban population in each province to the total population of the province (percentage)Urbanization Results and DiscussionFocusing on the transfer of labor from rural and agricultural areas to urban and industrial or service centers, the present study investigated the impact of this labor transfer on carbon dioxide emissions across 31 provinces in Iran during 2010–2020. First, the carbon dioxide emissions for each province were calculated. Then, the study introduced a model based on quantile regression with nonadditive fixed effects at varying quantile levels. The primary rationale behind employing this regression technique was to offer a detailed and comprehensive analysis of the model’s response variable. This approach allows for intervention not only at the center of gravity of data but also at all levels of the distribution particularly the extremes avoiding the issues associated with assumptions such as ordinary regression, heterogeneity of variance, and the potential impact of outlier data on coefficient estimations. Consequently, the panel quantiles were used to estimate the regression model, and the results are presented in Tables 2 and 3.Table Table 2. Estimation results ation resultsvariables / (τ)5040302010 -48.59***-30.69***29.14***-24.32***-24.46*** 3.13***1.94***1.84***1.52***1.56*** -0.067***-0.041***-0.039***-0.032***-0.033*** -0.622***-0.592***-0.508***-0.758***-0.525*** -0.161-0.068***-0.120***-0.117***-0.202*** 0.0520.722***0.996***1.089***0.918*** 0.143***0.123***0.096***0.103***0.076*** 0.614***0.684***0.646***0.662***0.719*** 0.038***0.046***0.044***0.059***0.042***Source: Research resultsTble Table 3. Estimation results ation resultsvariables / (τ)90807060 -154.60***-73.48***-41.63***-46.65***ln2GDP9.99***4.73***2.96***30.9*** -0.214***-0.101***-0.058***-0.068***Ratioagri-1.99**-0.221***0.0070.612 -0.144-0.257***-0.017-0.046***lnUrb0.340***0.0360.184***0.396*** 0.106***0.130***0.135***0.128*** 0.645***0.724***0.671***0.586*** 0.126**0.015**0.0007-0.039Note: ***, ** and * represent the significance level of 1, 5 and 10%, respectively.Source: Research resultsIncreasing the proportion of the working population in the agricultural sector relative to other sectors or minimizing changes in the labor structure, except between the 60th and 70th percentiles, leads to a reduction in carbon dioxide emissions. As a result, the structural labor change exerts a direct and significant impact on the levels of carbon dioxide emissions across Iran’s provinces. As changes in the labor structure intensify, the agricultural sector might resort to machinery to compensate for the workforce reduction, maintaining production and moving towards capitalization that, in turn, amplify energy consumption and carbon dioxide emissions. Furthermore, the transition from rural areas and agricultural hubs to urban and industrial centers can increase income, thereby contributing to an increase in carbon dioxide emissions. The study also examined the indirect impact of structural labor change on carbon dioxide emissions through the economic growth channel. According to the estimation results, the coefficient for the interaction term of structural labor change and economic growth is positive and statistically significant in all quantiles, except the 60th and 70th percentiles. As noted by Yang et al. (2021), the increased transfer of labor from the agricultural sector to other sectors, particularly industry, during the course of economic development can indirectly boost economic growth and carbon dioxide emissions. The labor transfer increases as the scale and GDP rise, and there is an expansion in fossil fuel consumption accompanying economic growth, leading to a subsequent increase in carbon dioxide emissions in the provinces of Iran. The study validated two direct and indirect effects of structural labor change on carbon dioxide emissions in Iran’s provinces. In both scenarios, structural labor change contributed to an increase in carbon dioxide emissions. The first effect stems from the increasing use of machinery to compensate for the labor force depleted from the agricultural sector, leading to increased energy consumption and subsequent carbon dioxide emissions. The second effect can be explained with an eye to the increased economic growth and GDP resulting from the structural labor change, as discussed in the Lewis model. ConclusionThe study examined both the direct and indirect effects of structural labor change, in conjunction with other socio-economic variables, using a nonlinear method. The data was gathered from 31 provinces of Iran spanning from 2010–2020, and the study used a quantile regression with nonadditive fixed effects. The variable denoting labor transfer from the agricultural sector to other sectors was used as the ratio of the working population in the agricultural sector to the total working population, serving as the index for structural labor change. The findings revealed that structural labor change has a direct effect on carbon dioxide emissions. Furthermore, concerning indirect effects, it can be affirmed that the index has a positive and significant effect on the dependent variable through the indirect channel of economic growth. Considering the positive effect of labor transfer and its negative impact on carbon dioxide emissions and environmental degradation, it is recommended to adopt measures to control and regulate the labor transfer. Specifically, strategies should be devised to increase the income of workers in the agricultural sector, aiming to establish an equitable wage balance relative to other sectors. Moreover, provincial authorities should prioritize initiatives that increase the real added value in agriculture, with a focus on expanding industries associated with agricultural production, such as transformative and complementary sectors.
Mohammad Asiaei
Volume 3, 9(Autumn and Winter ) , October 2001, , Pages 127-160
Abstract
An Intersectoral Capital Coefficients Matrix contains the main features of the structural parameters of an economy. One of its main functions is the role it plays in dynamic input - output models. It is also used as a tool in forecasting the economic variables.In this paper, the net capital stocks are ...
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An Intersectoral Capital Coefficients Matrix contains the main features of the structural parameters of an economy. One of its main functions is the role it plays in dynamic input - output models. It is also used as a tool in forecasting the economic variables.In this paper, the net capital stocks are used to estimate the intersectoral capital coefficients. For our purpuse, the use of the net capital stocks appear to be appropriate for the life spans of the various fixed capital goods. It can also be used in certain methods for the calculation of the depreciation of real assets.We have used experiences of other countries in estimating the intersectoral capital matrix, by adding the net fixed capital matrix and the inventory matrix. The intersectoral net fixed capital matrix consists of fifteen capital demander sectors and three supplyer sectors as follow: a) Machinary, b) Motor vehicle equipments, C) Construction.The average life spans of the above sectors are respectively 16, 10, 50 years.The intersectoral capital coefficients matrix for the year 1370 is obtained by dividing the elements of each column of the capital matrix to the value of output of each relevant sector. We have made use of the average capital- output ratios in our calculations.In our study, we have found out that the calculated coefficients of the Iranian economy are comparable with many other countries.To estimate the maximum possible growth rate of our economy, one can make use of the intersectoral capital coefficients matrix in a dynamic input-output model. One can also use it for economic planning and in the prediction of some economic variables.
Regional Planning
Bahareh Karami; Azad Khanzadi; Ali Falahati; Mohammad Sharif Karimi
Abstract
Equality of development opportunities is one of the socio-economic goals and a basic prerequisite for achieving economic stability and integrated progress in a country. In the present research, 69 development indicators related to cultural-social, educational, infrastructure, health-treatment, environmental ...
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Equality of development opportunities is one of the socio-economic goals and a basic prerequisite for achieving economic stability and integrated progress in a country. In the present research, 69 development indicators related to cultural-social, educational, infrastructure, health-treatment, environmental and economic sectors were analyzed to identify and compare the development opportunities of 30 provinces of Iran. Shannon's entropy method was used to determine the weights of the indicators and the TOPSIS method was used to rank the provinces in terms of access to the opportunities of each sector. Finally, by using the taxonomy technique, the degree of enjoyment of the provinces from a total of six opportunities was evaluated. The results show that there is a deep gap in the distribution and allocation of facilities and opportunities among the provinces of the country. Tehran province was the most privileged and Kurdistan, South Khorasan, Lorestan, West Azerbaijan and North Khorasan provinces were determined as the most deprived provinces. Based on significant difference among provinces, it is recommended that the priorities of the budget allocation be determined according to the degrees of benefits for the provinces. IntroductionThe growth and development of regions is condemned to be asynchronous; unequal and unbalanced development of different regions is one of the main challenges in most countries and economics. Due to many geographical, demographic and economic factors, Iran is prone to all kinds of regional inequalities and imbalances and is by no means an exception. The lack of balance among the provinces of a country can cause many harms, including damage to national unity, income gap, and limited areas enjoying the desired level of development and intensifying deprivation in other areas, immigration, geographic density, poverty, injustice and finally stopping development in all dimensions. The basic question that regional economic theorists try to answer is why some regions are more developed and growing faster than others and some are declining. In response to this controversial question, it is necessary to mention that the regional difference can be seen as a clear manifestation of the lack of equal access to opportunities, because inequalities are largely rooted in unequal opportunities. Therefore, the way of allocating resources and opportunities in societies is one of the important factors determining the distribution pattern of their growth and development. Methods and materialThe purpose of this study is to investigate, identify and analyze the situation of Iran provinces in terms of development opportunities during the period of 2006-2019. For this purpose, it is tried to calculate the index of development opportunities by using a comprehensive set of development indicators that are closely related to equal opportunities and also we use multi-criteria decision-making method, and then the provinces of Iran according to the degree of prosperity are ranked and classified. We also combine the sub-indices to make one-dimensional indices, by using TOPSIS technique with weighted entropy for six main indices; These indicators are: 1. Socio-cultural dimension, 2. Economic dimension, 3. Health-treatment dimension, 4. Infrastructural dimension, 5. Educational dimension and 6. Environmental dimension. Then, by using Taxonomy method, we combine six indices, to separate and grade provinces into five homogeneous groups based on the level of access to development opportunities.The statistical population includes all provinces of Iran (thirty provinces including Alborz province in Tehran province). The data has been extracted from the most important database of the country, namely the portal of the Statistical Center of Iran, while the time period has been limited according to the availability of provincial data. Results and DiscussionThe findings of the research show that Tehran province has the highest development opportunities among the provinces of the country. This province ranks first in the ranking of provinces in terms of educational, health, economic and cultural-social indicators, third in infrastructure and sixth in environmental indicators. Meanwhile, the seventeen provinces of Iran including Hamedan, Markazi, Chaharmahal and Bakhtiari, Yazd, Golestan, Kohgiluyeh and Boyer Ahmad, Zanjan, Kermanshah, Ardabil, Ilam, Kerman, Sistan and Baluchistan, Kurdistan, South Khorasan, Lorestan, West Azerbaijan and North Khorasan has been placed in the category of underprivileged or very underprivileged provinces in terms of development opportunities gains.It seems that advantages such as access to appropriate infrastructure like communication, physical and information networks, commercial services, proximity to skilled labor markets and competitive enterprises, as well as the ability to access research institutions have a great role in Tehran province situation compared to other provinces. ConclusionThe results showed that the hypothesis of uneven distribution of various facilities and services among the provinces of the country is confirmed, In other words, there are significant differences among the different provinces of the country in terms of development opportunities. Therefore, it is suggested to policy makers and planners to pay attention to the research done on regional opportunities and in their policies and orientations, and in addition to national approaches, consider regional development approaches by prioritizing provinces based on the degree of development and the level of prosperity, in the framework of planning based on land use. It is also suggested that in future studies, considering the scope of the concept of development opportunities and the quantitative and qualitative indicators of this category, these indicators be extended further so that more useful information is available to planners and policy makers in order to eliminate imbalances.
urban economy
Fatemeh Moheiseni; Seyed Aziz Arman; Seyed Amin Mansouri
Abstract
In today’s world, countries have come to the realization that their available resources, including human capital, natural resources, and capital, are limited. To use these resources optimally requires that consumption be adjusted and productivity be increased. In this context, the labor force, ...
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In today’s world, countries have come to the realization that their available resources, including human capital, natural resources, and capital, are limited. To use these resources optimally requires that consumption be adjusted and productivity be increased. In this context, the labor force, as a fundamental factor in production, deserves special attention. Several factors such as geographical location, wages, welfare and health indicators, proximity, and population density can impact labor productivity. The present research aimed to investigate the impact of urbanization and its spatial spillovers on the productivity of provincial labor forces during 2006–2019, using the components of the human development index, urbanization rate, population density, and industrial wages. The study revealed the existence of spatial autocorrelation among the investigated provinces. The variables of human development index, urbanization rate, and industrial wage have direct and indirect positive and significant effects on provincial labor productivity, while the population density index has a direct positive effect and an indirect negative effect on labor productivity.IntroductionSustainable urbanization has been a fundamental component of the development of every country. Urbanization can have a significant positive impact on economic activities by providing better services, creating job opportunities, and increasing access to basic services. Cities have the ability to transform low-productivity agriculture into a high-productivity manufacturing industry and cost-effective service sectors. Cities in developing countries are the driving force behind economic growth, accounting for 70% of the gross national product (World Bank, 2009). With the increasing share of the population living in cities, improving the productivity of urban areas has become a priority for many governments and economic consulting organizations (OECD, 2016). Accordingly, cities possess the necessary ability and capacity to influence key economic factors. In this respect, the present study aimed to investigate the impact of urbanization on labor productivity, as a crucial factor for development, by evaluating the economic growth and examining several components of cities. The objective of research was to examine the spatial spillover effects of urbanization on labor productivity in Iran’s provinces, specifically focusing on the savings of density. The study tried to answer the following questions:Is it possible for an urban area to enhance labor productivity at the provincial level?Is there a relationship between labor productivity in a province and the direct and indirect effects of the provincial human development index?Are the external benefits of population density and urbanization (such as benefits from population increase and industrial concentration) responsible for this relationship?Is labor productivity affected by the direct and indirect effects (spillover) of industrial wages?Can the positive side effects of a more efficient urban economy in urban centers be affected by structural problems caused by rapid and dense population growth?Materials and MethodsThe basic model used in this study is as follows: The panel spatial econometric method was employed to analyze the spatial spillovers and geographic space involved in the impact of urbanization on provincial labor productivity. The Stata software was used to examine the final data, and a square matrix was created through GeoDa software in order to estimate the model with the spatial econometric method. This matrix represents the proximity between the provinces and assigns a value of 1 to neighboring provinces and 0 to non-neighboring provinces. Stata software packages were then used to standardize the provincial neighborhood matrix, and a vector was obtained by multiplying the matrix by the vector of each variable. The obtained vector was entered as an explanatory variable in the model, and its coefficient expresses the spatial effect. Based on the evaluated processes, the final model is as follows:+ ConclusionFirst, the estimated coefficients of the human development index and industrial wage of the labor force indicate that an increase in these factors within each province has a positive effect on labor productivity. Furthermore, the positive effects of these factors spill over into neighboring provinces. In this respect, competitive markets play a role in improving labor attraction factors within the province, thereby preventing the departure of skilled labor. With the implementation of necessary policies, job skills are promoted, and the permanent departure of highly skilled labor force is reduced.Second, the estimated coefficients of the urbanization variable show that the increase in urban population and demand, in addition to the training of specialized labor in cities, leads to the recruitment of skilled labor. This in turn has a positive spillover effect, increasing the urbanization rate of neighboring provinces. As a result, it leads to an increase in labor productivity in the neighboring provinces.Finally, the direct effect of population density in a province has a positive impact on labor productivity. However, the indirect effect of population density on labor productivity is complex. While creating a positive external effect due to economies of scale, the indirect effect is also countered by the crowding effect caused by population density. The crowding effect is actually due to the lack of sufficient infrastructure in line with population growth in the province, which leads to negative spillovers of neighboring regions into the province.The various effects observed provide strong evidence for a positive relationship between urbanization and labor productivity. These effects suggest that, under the appropriate conditions, cities have the potential to generate significant employment opportunities and stimulate growth and development not only within the city and province but also across the country. Cities can create sustainable jobs and increase productivity, thereby maximizing the ability to innovate, respond to market demand, and benefit from the advantages of dense markets.
Parisa Mohajeri; Zahra Zabihi; Sahar Sadeghi; Ziba Eghtesadi
Abstract
Since the introduction of supply-use input-output model by the United Nations in its 1968 SNA, there has been a controversy on choosing the most appropriate technology assumption for estimating symmetric product by product input-output table. These arguments have focused on two technology assumptions; ...
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Since the introduction of supply-use input-output model by the United Nations in its 1968 SNA, there has been a controversy on choosing the most appropriate technology assumption for estimating symmetric product by product input-output table. These arguments have focused on two technology assumptions; the product technology assumption (PTA) and the activity technology assumption (ATA). The PTA states that each product has a unique input structure that is independent of producing industry. In contrast, the ATA is defined as each activity has its own specific way of production, irrespective of its product mix. Each assumption has its own advantages and disadvantages. Because of ATA’s inconsistency with some fundamental economic theories, “Product Technology” assumption is more widely applied for calculating symmetric product-by-product input-output table. In this paper, we show that only PTA fulfills the four desirable properties (material balance, financial balance, scale invariance and price invariance) which are introduced by Jansen and ten Raa (1990) but ATA fulfils only one of them. This result can be used by compliers and users in choosing the appropriate economic assumptions for deriving symmetric input-output tables.
Mehdi Yazdani; Ali Esmaeili
Abstract
Financial crises have been frequently occurred in the global economy, and due to the negative impacts of financial crises on the real sectors performances, the economists tried to predict them. This study tries to investigate the role of the trade flows on occurrence of these phenomena and also the effects ...
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Financial crises have been frequently occurred in the global economy, and due to the negative impacts of financial crises on the real sectors performances, the economists tried to predict them. This study tries to investigate the role of the trade flows on occurrence of these phenomena and also the effects of contagion on trade flows. Hence, a sample of the emerging markets countries is selected during 1990-2013, and the simultaneous equations method has been used with discrete dependent variable (contagion of financial crises) in panel data. The results show that the trade flows lead to the acceleration of the contagion of the financial crises and on the other hand, the trade flows has been decreased by financial crises in the selected emerging markets countries. Finally, similar to the probability for contagion of the financial crises, more financial and regional linkages can increase the trade flows among selected countries.
International economy
Fakhri Mirshojaee; Nasser Elahi; Mohsen Seighali
Abstract
An important subject in the field of global economy is the financial crisis contagion on various markets. Given the expansion of trade relationships among different countries, proving the existence of contagion will facilitate policymaking in times of crisis. The present article tries to find the answer ...
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An important subject in the field of global economy is the financial crisis contagion on various markets. Given the expansion of trade relationships among different countries, proving the existence of contagion will facilitate policymaking in times of crisis. The present article tries to find the answer to the question of whether the Iranian foreign exchange market is affected by certain global crises. The answer may initially seem to be obvious; nevertheless, the channels of contagion or its share in market fluctuations cannot be confirmed if the existence of the phenomenon is not proved at first place. This study reviews the contagion effects of financial crises in selected crisis-stricken countries and those of oil and gold markets on Iran's free foreign exchange market, covering four crises including the US stock market crash, the Mexican financial crisis, SAARC, and the US subprime mortgage crisis during 1987-2008. For each crisis, stability periods were identified and using daily data and the Copula-GARCH model, the existence of contagion effects was studied. Findings indicated the contagion effects of the crises in the mentioned markets on the foreign exchange market. This was specifically witnessed in the case of the 2008 crisis with effects larger than others, manifesting themselves in the foreign exchange as well as the oil and gold markets. Therefore, part of the fluctuations in the market may be attributed to external factors, requiring the policymaker to avoid any intervention during global financial crisis or turbulence in the oil and gold markets.
Mohammad Ali Moradi
Volume 4, Issue 12 , October 2002, , Pages 11-29
Abstract
The objective of this paper is to investigate the dynamics of adjustment to long-run purchasing power parity (PPP)in a nonlinear framework using the Iranian data over the period 1959-2000. Two PPP measures are considered and nonlinearity in the real exchange rates are investigated. First, the standard ...
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The objective of this paper is to investigate the dynamics of adjustment to long-run purchasing power parity (PPP)in a nonlinear framework using the Iranian data over the period 1959-2000. Two PPP measures are considered and nonlinearity in the real exchange rates are investigated. First, the standard and modified unit root tests are applied and then, cointegration analysis is carried out, based on the Johansen (1988) and Johansen and Juselius (1990) cointegration methodology, rather than imposing the strict cointegating vector in calculating real exchange rate measures. Furthermore, the Smooth transition autoregressive (STAR) representation for the adjustment process towards PPP, which provides a superior alternative, are specified and estimated. It was found that purchasing power parity (PPP) holds in the long-run after accounting for structural breaks. Moreover, linearity was strongly rejected and the dynamic STAR models were specified and estimated by using nonlinear least squares. The strong evidence in favour of nonlinear behaviour for PPP suggests that the linear models are misspecified.
Hassan Heydari
Volume 16, Issue 46 , April 2011, , Pages 77-96
Abstract
This paper focuses on the development of modern non-structural dynamic multivariate time series models and evaluating performance of various alternative specifications of these models for forecasting Iranian inflation. The Quasi-Bayesian method, with Literman prior, is applied to Vector autoregressive ...
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This paper focuses on the development of modern non-structural dynamic multivariate time series models and evaluating performance of various alternative specifications of these models for forecasting Iranian inflation. The Quasi-Bayesian method, with Literman prior, is applied to Vector autoregressive (VAR) model of the Iranian economy from 1981:Q2 to 2006:Q1 to assess the forecasting performance of different models over different forecasting horizons. The Bewley transformation is also employed for the re-parameterization of the VAR models to impose the mean of the change of inflation to zero. Applying the Bewley (1979) transformation to force the drift parameter of change of inflation to zero in the VAR model improves forecast accuracy in comparison to the traditional BVAR.[1]
[1]. Acknowledgement
I would like to thank Paolo Girodani for comments and providing some GAUSS procedures, Ronald Bewley, David Forrester, Jan Libich, and two anonymous referees for their helpful comments and suggestions on an earlier version of this paper. Financial support from the Urmia University is gratefully acknowledged. The usual disclaimer applies.
Masoud Sadeghi; Mostafa Emadzadeh
Volume 5, Issue 17 , February 2004, , Pages 79-98
Abstract
This paper focuses on human capital as a determinant of economic growth. In this article empirical evidences relating education to economic growth are examined. In the context of neoclassical growth models, i.e. as in Cobb-Douglas production function, human capital serves as an input to production. These ...
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This paper focuses on human capital as a determinant of economic growth. In this article empirical evidences relating education to economic growth are examined. In the context of neoclassical growth models, i.e. as in Cobb-Douglas production function, human capital serves as an input to production. These models expand on the neoclassical growth model of Solow, by allowing the output of a country to be an increasing function of its stock of human capital. It is shown that investment in education leads to increased output and therefore growth. Using an Ordinary Least Squares (OLS) regression function, we found that the production elasticities of the skilled labour, non skilled labor, and physical capital are respectively 0.21, 0.49 and 0.35 percentages. Our investigation concludes that schooling has a significant and substantial positive effect on productivity and GDP growth.
Alaeddin Ezoji; Alireza Amini
Volume 12, Issue 37 , February 2009, , Pages 81-105
Karim Azarbaijani; Golara Ezadi
Volume 8, Issue 26 , April 2006, , Pages 81-99
Abstract
The Purpose of this study is reviewing the Intra Industry Trade between Iran and China by using Trade Type Approach. To avoid the geographic and sectoral bias, we consider the bilateral Trade and we concentrate on quality and commodity differentiation. Our findings show that the share of Intra Industry ...
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The Purpose of this study is reviewing the Intra Industry Trade between Iran and China by using Trade Type Approach. To avoid the geographic and sectoral bias, we consider the bilateral Trade and we concentrate on quality and commodity differentiation. Our findings show that the share of Intra Industry Trade between Iran and China is very low. In fact, a large part of our trade belongs to vertical (and horizental) Intra Industry Trade. This means that we have a low competetive power in final products, whereas we have a high competetive power in raw materials, and low quality products. Our investigations indicate that Iran’s situation can be improved by ameliorating the quality of exproted products. This study shows that a high unemployment rates belongs to sectors in which the Intra Industry Trade is weak. Thus, one of our main finding requires changes in free trade strategy, so that by increasing the quality of Iranian products, Iran could have a significant share in Intra Industry Trade with China and a progress in industrial employment.
Esfandiyar Jahangard
Volume 2, 4&5(Spring and Summer) , April 2000, , Pages 81-106
Abstract
This paper tries to analyse the structural changes of the Iranian economy during 1969-1988.
For this purpose the Input - Output tables of 1969, 1974, 1984and 1988 have been used. The original tables were at current prices and therefore could not be used to quantify the structural changes of ...
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This paper tries to analyse the structural changes of the Iranian economy during 1969-1988.
For this purpose the Input - Output tables of 1969, 1974, 1984and 1988 have been used. The original tables were at current prices and therefore could not be used to quantify the structural changes of the Iranian economy in real term. For this purpose, after making sectoral comparisons, and taking the year 1974 as the base year, all the tables have been deflated by using the double deflation methods.
Teymur Mohamadi
Volume 1, Issue 2 , October 1996, , Pages 82-97
Esfandiar Jahangard
Volume 7, Issue 25 , February 2006, , Pages 83-107
Abstract
Technology has long been considered very important to contribute to economic growth through productivity improvement. The empirical studies indicate that the contribution of information technology(IT) to growth in developed and some developing countries over the second half of the 1990s has been ...
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Technology has long been considered very important to contribute to economic growth through productivity improvement. The empirical studies indicate that the contribution of information technology(IT) to growth in developed and some developing countries over the second half of the 1990s has been significant. There is still room for more investigation, specially in developing countries where the socio-economic infrastructure may not fully support the IT and economic growth relationship. This study uses an explicit production function to estimate the elasticity of IT factors in the Iranian manufacturing industry using the panel data method covering the period 2000-2001.
Reveal that IT has had a positive and significant effect on the production in the Iranian manufacturing industry. Our results suggest that an increase in IT expenditure beside improving complementary factors will eventually lead to higher labour productivity and growth in manufacturing industry.
Volume 5, Issue 14 , April 2003, , Pages 83-112
Abstract
There is a tension between energy efficiency of the State Owned Enterprise (SOE) sector versus the economic efficiency of the Township and Village Enterprise (TVE) Sector in China. Research has shown that the cokemaking sector in Shanxi Province exhibits contradictory features of having greater overall ...
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There is a tension between energy efficiency of the State Owned Enterprise (SOE) sector versus the economic efficiency of the Township and Village Enterprise (TVE) Sector in China. Research has shown that the cokemaking sector in Shanxi Province exhibits contradictory features of having greater overall factor productivity than the SOE cokemaking sector, while at the same time being less energy efficient. In my current research I have shown that this is not a unique feature of the TVE cokemaking sector in Shanxi Province, but that the same paradoxical behavior is exhibited by an overwhelming majority of industrial and service sectors, in addition to the agricultural sector, in Shanxi Province and China as a whole.Virtually, all productivity studies of state-owned and township and village enterprises in China during the 1980s and 1990s concluded that the growth of productivity in the TVE sector has outpaced that of the NTVE sector. In this paper, I show some of the reasons behind the economic efficiency of the TVE sector as compared to the NTVE sector, despite the fact that my analysis also shows that they are less energy efficient. Using Structural Decomposition Analysis, I show that 28 out of 29 TVE sectors in China are less energy efficient than their NTVE counterparts. This, despite the fact that TVEs in China have enjoyed far better economic performance than NTVEs, particularly SOEs, with among other things total factor productivity being three times as great as that of NTVEs. In order to reconcile this paradox, I examine the direct and indirect labor inputs between the TVE and NTVE sectors in China. It is apparent from the analysis that TVEs direct and indirect labor inputs are much lower than that of NTVEs, which offsets the differences in direct and indirect energy inputs. In order to explain the above differences in economic, energy and labor productivity between TVEs and NTVEs, I have extended previous studies on institutional theories of property and ownership, showing the contribution of many institutional factors to TVEs economic performance. Among the most important of these factors are financing of investment, security of property rights, transaction costs, urban proximity, collective heritage, government revenue, non-farm employment, and per capita income. In this paper, I examine the paradox in the energy and economic efficiencies between China's Township and Village Enterprise (TVEs) and Non-TVE (NTVEs), the majority of which are State Owned Enterprises (SOEs). Many analysts (e.g. Jefferson 1999, Steinfeld 1998, Lardy 1997, Liew 1997, Fewsmith 1994) have tried to explain the superior economic efficiency of TVEs and their rapid growth since the beginning of the reform process, in 1979. These analysts laud the TVEs economic efficiency as an example of how the privatization process in China is making the entire economy more efficient; however, they overlook two important facts. First, TVEs are not mainly privately owned firms, and, second, even those that are, do not have the basic features of traditional private enterprises.At the same time, the success of TVEs has been used to criticize the supposedly bloated SOE sector, which constitutes the majority of industries in the NTVE sector and its inefficient and unproductive industries. Although SOEs may be economically inefficient, most analysts neglect to note that SOEs engage in many social functions other than profit maximization and improving productivity. The purpose here is to add another element into the debate between the SOE and TVE sectors, namely, although most TVEs are more economically efficient, SOEs are more energy efficient. I show that the primary reason behind this paradox is the fact that ambiguous property rights in the TVE sector allow these industries to establish informal relationships that often result in lower input and labor costs than in the NTVE sector.This paper is divided into three parts. In the first part, I give an overview of the differences between TVEs and NTVEs. In the second part, I examine the underlying energy and economic efficiency differences between TVEs and NTVEs by structural decomposition analysis. Finally, based on the results of the first two parts of this research, I give a theoretical basis for the observed paradox, focusing on the issues of property relations in the TVE sector.
Ahmad Sadraei Javaheri
Volume 18, Issue 57 , February 2014, , Pages 85-95
Abstract
The paper studies the changes of total factor productivity forall Iranian Insurance companies for the period 2003-2009. In order to measure the changes in productivity, data envelopment analysis (DEA) method is applied. DEA method is used to estimate output oriented Malmquist productivity index. To determine ...
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The paper studies the changes of total factor productivity forall Iranian Insurance companies for the period 2003-2009. In order to measure the changes in productivity, data envelopment analysis (DEA) method is applied. DEA method is used to estimate output oriented Malmquist productivity index. To determine effective factors on the total factor productivity growth of insurance companies tobit regression is used. The results of the study confirm the positive effect of liberalization policy adopted by government on productivity growth. The results also indicate that dimension and the field of activity have significant positive effect on productivity growth.
Saeed Moshiri; Ebrahim Eltejaei
Volume 12, Issue 36 , October 2008, , Pages 85-113
Abstract
Structural change can contribute to economic growth through an improvement in utilization of resources along with the traditional factors such as physical capital human capital, and technology. In this paper, we investigate the impact of structural change on economic growth in the new industrialized ...
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Structural change can contribute to economic growth through an improvement in utilization of resources along with the traditional factors such as physical capital human capital, and technology. In this paper, we investigate the impact of structural change on economic growth in the new industrialized countries (NIC). Among many variables traditionally used as proxies for structural changes, we identify 20 variables to represent the structural changes in 11 NICs for the period 1970-2004. We then use principal components and dynamic factor analysis to obtain an index for structural changes in these countries. Our estimation results obtained from the growth equation indicate that structural change has had a positive and significant effect on economic growth in NICs.
Morteza Sameti; Rohollah Shahnazi; Zahra Deghan Shabani
Volume 8, Issue 28 , October 2006, , Pages 87-105
Abstract
In this paper, factors affecting fiscal corruption, especially economic freedom, have been analyzed using three panel data models for 73 countries during 2000-2003. The results show three main components of economic freedom; i.e., legal structure and property rights, sound money and freedom ...
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In this paper, factors affecting fiscal corruption, especially economic freedom, have been analyzed using three panel data models for 73 countries during 2000-2003. The results show three main components of economic freedom; i.e., legal structure and property rights, sound money and freedom to exchange with foreigners, have positive effect on fiscal corruption. Two other component of economic freedom, i.e., size of government and regulation in credit, business and labor markets, have not significant effects on fiscal corruption.
Mehdi Sadeghi; Seyyed Rohollah Ahmadi
Volume 17, Issue 51 , July 2012, , Pages 89-112
Abstract
Policy-makers around the world have emphasized the virtues of deregulation. The banking industry in Iran has partly experienced reform after the domestic peivate banks entry since 2000. This study investigates the impact of this policy on economic efficiency of banking sector by using banking data over ...
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Policy-makers around the world have emphasized the virtues of deregulation. The banking industry in Iran has partly experienced reform after the domestic peivate banks entry since 2000. This study investigates the impact of this policy on economic efficiency of banking sector by using banking data over the period 1997-2006. We measured the economic efficiency of banks using SDEA which necessitated a grasp of technical and allocation efficiency and calculated the model by GAMS software. The purpose of stochastic setting of DEA is accommodating both the inefficiency and the presence of measurement errors. In the second step we used the fixed effect model on panel data to regress efficiency measures on policy variable of entry. We solved the regression model by Eviews and Stata softwares. Our result show that entry variable has not meaningful effect on efficiency. So economic efficiency cannot be differentiated on the basis of policy reform of entry.
Mehdi Taghavi; Maryam Khalili Araghi
Volume 7, Issue 22 , April 2005, , Pages 91-113
Abstract
Financial repression, according to many scholars, is a drag on economic growth and development. To identify factors influencing financial repression we analyzed experts opinion using Delphi Method. We used DEMATEL technique and Graph theory to sequence their importance and feedbacks. The result shows ...
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Financial repression, according to many scholars, is a drag on economic growth and development. To identify factors influencing financial repression we analyzed experts opinion using Delphi Method. We used DEMATEL technique and Graph theory to sequence their importance and feedbacks. The result shows that dependence on oil export revenue is the most important factor causing financial repression and it has increased economic rent and corruption, and it is self-perpetuating. Our findings are consistant with structuralists and post Keynesian views. Reliability of model used is consistant with stylized facts and expert opinion. Besides DEMATEL is a very reliable mathematical model for this types of study.
