Other
Soraya Jelvezan; Ataaulah Mohammadi Malqarani; Behrooz Shahmoradi
Abstract
Profit, as presented in financial statements, is one of the most important performance metrics and a key determinant of an economic entity's value. The primary objective of this research is to assess product profitability based on a Product Complexity Index (PCI), considering the product's diversity ...
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Profit, as presented in financial statements, is one of the most important performance metrics and a key determinant of an economic entity's value. The primary objective of this research is to assess product profitability based on a Product Complexity Index (PCI), considering the product's diversity and market reach across different markets. The study analyzes a sample of 500 profitable companies listed in the Fortune, spanning the financial years from 2014 to 2018. The analysis employs both panel and pooled data methods. The study aims to estimate the profitability of each product to help investors identify the most profitable products for investment, based on their profitability as determined by the PCI. The findings suggest that adopting a new approach focused on producing high-complexity products, rather than merely selecting product types or business activities, along with measuring the profitability index of each product, can enhance decision-making. By examining the relationship between product complexity and profitability, and introducing an index to forecast product profitability, investors who are key users of financial information can make more informed decisions. These decisions, based on the optimal combination and selection of products, can foster economic growth and contribute to the development of society. The results show a positive and significant relationship between operating profit and the Product Complexity Index, as well as the estimation of profitability based on product diversity and market reach.
Persian Abstracts Persian Abstracts
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Persian Abstracts
, Behavioral Economics
Saeid Tajdini; Mohammad Qezelbash; Mohsen Mehrara; Majid Lotfi Ghahroud; Mohammad Farajnezhad
Abstract
This paper introduces an innovative model of Central Bank Digital Currency (CBDC), offering a novel perspective on its design and functionalities. It presents an innovative approach to digital currency design, introducing "Export Crypto" as a novel cryptocurrency that diverges from conventional Central ...
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This paper introduces an innovative model of Central Bank Digital Currency (CBDC), offering a novel perspective on its design and functionalities. It presents an innovative approach to digital currency design, introducing "Export Crypto" as a novel cryptocurrency that diverges from conventional Central Bank Digital Currencies (CBDCs) by anchoring its value not to fiat currencies but to intrinsic economic factors and global trade dynamics. In contrast to traditional CBDCs, our model relies on the principles of purchasing power parity (PPP) to establish a more robust and transparent link between the cryptocurrency's value and real economic activities. The core parameters for assessing the value of Export Crypto revolve around equitable trade balances among nations and their respective export volumes. This approach fundamentally deviates from the conventional practice of pegging digital currencies to a country's fiat currency. Our research findings underscore that a cryptocurrency rooted in economic fundamentals can offer a more effective tool for managing the money supply, particularly in regions where traditional CBDCs may not be optimally suited. Furthermore, Export Crypto's design has the potential to foster fair-trade practices and encourage sustainable economic growth by aligning its worth with a nation's economic prowess and its trade interactions on the global stage. This groundbreaking approach to central bank digital currency opens new avenues for enhancing economic stability and promoting equitable international trade relationships.
Econometrics
Forough Esmaeily Sadrabadi; Maedeh Khanari
Abstract
This study explores the effects of artificial intelligence (AI) investment on total factor productivity (TFP) in Iranian industries from 1997 to 2020, utilizing a comprehensive dataset organized by four-digit International Standard Industrial Classification (ISIC) codes. We employ the generalized method ...
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This study explores the effects of artificial intelligence (AI) investment on total factor productivity (TFP) in Iranian industries from 1997 to 2020, utilizing a comprehensive dataset organized by four-digit International Standard Industrial Classification (ISIC) codes. We employ the generalized method of moments (GMM) approach to address challenges such as endogeneity and collinearity within a dataset comprising over 200 cross-sectional variables.Our results reveal that both physical and intangible investments significantly influence TFP; a 1% increase in physical investment results in a 0.514% rise in TFP, while intangible investment leads to a 0.288% improvement. A key innovation of this research is the introduction of an AI measurement variable in the production function, employing the Corrado, Hulten, and Sichel (CHS) methodology for a clearer assessment of AI's productivity effects.Although AI investment positively correlates with TFP, its current impact is limited, reflecting the gradual adoption of advanced technologies in Iranian industries. This highlights the need for a comprehensive strategy to fully realize the productivity benefits of AI. We recommend policies aimed at facilitating technology integration and workforce specialization, including investing in training, providing incentives for AI adoption, and promoting collaboration between industry and educational institutions to enhance productivity and competitiveness in the global market.
Econometrics
Tofigh Beigi; Ahmad Sadraei Javaheri; Ali Hussein Samadi; Ebrahim Hadian
Abstract
Uncertainty is a controversial issue in the philosophy and methodology of economics. Since economic uncertainty is not directly observable, quantifying it is confronted with significant complexities. A common method in this context involves computing the proxy of uncertainty using time series models. ...
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Uncertainty is a controversial issue in the philosophy and methodology of economics. Since economic uncertainty is not directly observable, quantifying it is confronted with significant complexities. A common method in this context involves computing the proxy of uncertainty using time series models. Within this framework, the conditional volatility of the unforecastable components of time series is considered as an uncertainty measure. In this regard, the basic forecasting model should be specified in a way that its forecast errors lack any predictable content. In previous studies, the focus has solely been on economic and financial variables in computing the uncertainty measure, while the role of institutional factors has been neglected in the forecasting model. Meanwhile, based on economic literature, institutions play an important role in controlling and reducing uncertainty. Therefore, in the present study, the economic uncertainty measure is extracted based on a Large-dimensional dynamic factor model, employing a set of 72 macroeconomic and institutional time series for the Iranian economy. The results indicate that overlooking institutional factors in the forecasting model can lead to an overestimation of economic uncertainty. Our perspective enhances the accuracy of uncertainty measurement and provides a more comprehensive understanding of the determinant factors of economic uncertainty.
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Institutional Economics
Hassan Daliri
Abstract
This study explores the impact of governance indicators, , on economic growth across different income groups. Using dynamic panel data estimation with the one-step system GMM method, we analyze data from low-income (15 country), lower-middle-income (40 country), upper-middle-income (40 country), and ...
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This study explores the impact of governance indicators, , on economic growth across different income groups. Using dynamic panel data estimation with the one-step system GMM method, we analyze data from low-income (15 country), lower-middle-income (40 country), upper-middle-income (40 country), and high-income economies (52 country) in 2007-2022. The findings suggest that governance indicators have varying effects on economic growth depending on the income group. The analysis reveals that the impact of governance indicators on economic growth varies significantly across income groups. In low-income economies, "Control of Corruption" and "Regulatory Quality" have the strongest positive effects, emphasizing the critical role of governance improvements in fostering growth in these settings. For lower-middle-income economies, the "Rule of Law" and "Government Effectiveness" are key drivers, reflecting the importance of legal frameworks and efficient public services during economic transitions. In upper-middle-income economies, "Government Effectiveness" and "Voice and Accountability" are significant, though the moderate coefficients suggest structural and external constraints limit governance's role in driving growth. For high-income economies, "Regulatory Quality," "Rule of Law," and "Political Stability" are essential for sustaining growth, highlighting the role of efficient, stable, and innovation-friendly institutions. These findings underscore the evolving importance of governance indicators across development stages and the need for tailored institutional priorities to maximize growth potential. Interestingly, COVID-19 had a significant negative impact on economic growth across all groups, though its magnitude varied. The results show that the negative impact of the Corona shock on economic growth has increased as countries' income levels have decreased
, Behavioral Economics
Raheleh Dabiri; Mohammad Vaez Barzani; Saeed Samadi
Abstract
Decision-making on financing methods is one of the most important decisions of managers that can be affected by their behavioral biases. Behavioral biases can cause managers to make irrational decisions and select the optimal financing method with difficulty. Recognizing and evaluating biases is an important ...
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Decision-making on financing methods is one of the most important decisions of managers that can be affected by their behavioral biases. Behavioral biases can cause managers to make irrational decisions and select the optimal financing method with difficulty. Recognizing and evaluating biases is an important step to control them and improve decision making. Given the importance of this issue, the present study has analyzed the pathology of evaluation methods of behavioral biases, specifically in research on financing methods. In this study, for the first time, research onion is used to review studies on evaluation of behavioral biases by research onion. In order to select the articles, related keywords such as behavioral finance, evaluation of behavioral biases, and financing methods were searched in reliable databases and articles related to the research topic were collected. More than 200 articles have been studied and 33 related articles have been selected to examine the methods of evaluating behavioral biases. The study results showed the low variety of statistical analysis methods for evaluating behavioral biases in financing. The application of research onion shows that the methodology of these studies was mainly based on the philosophy of positivism, practical orientation, and comparative approach. Also, it was mainly conducted by the quantitative research and survey strategy, and the data was collected by the library documents.
Monetary economics
Reza Taheri Haftasiabi; Ameneh NaderI; Yousef Mohammadzade; Akbar Zavari Rezai
Abstract
Self-employment plays an important role in the Iranian economy and understanding the factors affecting it is of great importance. This study aimed to investigate the impact of private sector credit on self-employment in Iran using artificial intelligence techniques such as artificial neural networks, ...
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Self-employment plays an important role in the Iranian economy and understanding the factors affecting it is of great importance. This study aimed to investigate the impact of private sector credit on self-employment in Iran using artificial intelligence techniques such as artificial neural networks, deep neural networks and machine learning algorithms to identify nonlinear relationships and complex patterns in the data. Also, spatial econometric models SAR, SEM and SDM were used to consider spatial dependencies between provinces and to examine the spatial spillover effects of use for the period 1990-2023 at the provincial level of the country.The findings indicate a negative and significant relationship between the ratio of microfinance to GDP and the self-employment rate. Also, the negative coefficients of the economic openness index and the capital formation rate indicate their negative effect on self-employment. In contrast, the variables of total factor productivity and educational expenditure have a positive and significant effect on the self-employment rate. The results of the spatial models also indicate the dependence of the self-employment rate in different regions of the country on each other. Therefore, this study found a negative relationship between the two, which could be due to inefficiency in the provision of microfinance and its insufficient focus on creating sustainable and productive jobs. Increased economic openness and higher rates of capital formation also have a negative effect on self-employment by intensifying foreign competition and encouraging investment in larger economic sectors.
International Economics
Saeed Iranmanesh; Reza Etesami; reza Ashraf gangoei
Abstract
Since the revolution, Western countries such as the United States of America, the European Union, and the United Nations Security Council have consistently implemented a variety of extensive sanctions on the Islamic Republic of Iran. These sanctions have had a significant impact on Iran's foreign balance ...
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Since the revolution, Western countries such as the United States of America, the European Union, and the United Nations Security Council have consistently implemented a variety of extensive sanctions on the Islamic Republic of Iran. These sanctions have had a significant impact on Iran's foreign balance of payments, particularly in the area of foreign trade. To analyses the effects of these sanctions, a dynamic systems approach was used to simulate Iran's foreign trade pattern. Additionally, the opinions of 15 economics experts were collected through fuzzy questionnaires and analyses using the fuzzy logic method to determine the variable index of sanctions. The research period covered 1979-2021, and four scenarios were examined to assess the economic effects of sanctions on Iran's foreign trade model. The results revealed that sanctions on Iran's exports pose the greatest risk to the country's foreign balance, highlighting the importance of focusing on export development to mitigate the impact of economic sanctions. Furthermore, the study suggests that leveraging trade agreements and strategic partnerships with regional countries can help mitigate the economic consequences of sanctions.
International Economics
sirus charkh; Ahmad Googerdchian; karim azarbayejani; saeed jahaniyan
Abstract
There is a lack of study in Iran’s trade literature to investigate the role of unilateral trade preferences in the attraction of foreign direct investment (FDI) inflows. Indeed, this study aims to fill such research gap of the literature. This study examined the influence of non-reciprocal trade ...
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There is a lack of study in Iran’s trade literature to investigate the role of unilateral trade preferences in the attraction of foreign direct investment (FDI) inflows. Indeed, this study aims to fill such research gap of the literature. This study examined the influence of non-reciprocal trade preferences (NRTPs) on foreign direct investment (FDI) flows in Iran, with a focus on the Quad nations' (QUAD ) Generalized System of Preferences (GSP) programs. The analysis used the time series data for the period 1985 to 2021 using the ARDL technique to examine the relationship between preferences of unilateral trade utilization and FDI inflows. the symmetric results show that GSP intensify FDI in both the long and short-run. Furthermore, this study revealed that if Iran seeks to export sophisticated items or products that are less reliant on natural resources, as well as greatly liberalize its trading policy, the adoption of GSP is projected to create bigger FDI flows to the nation. Other significant research findings of the symmetric impact indicate the existence of an inverse relationship between real effective exchange rate, the share of natural resources, and GDP on the level of foreign direct investment.Keywords: International Trade, Preferences, Foreign Direct Investment (FDI), ARDL, Iran
Other
Malihe Hadadmoghadam; Pedram Davoudi
Abstract
The phenomenon of child labor and street children is one of the pressing issues in most contemporary large cities around the world. The prevalence of this phenomenon has become so significant that it engages both developed and developing societies equally. Child labor refers to any form of employing ...
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The phenomenon of child labor and street children is one of the pressing issues in most contemporary large cities around the world. The prevalence of this phenomenon has become so significant that it engages both developed and developing societies equally. Child labor refers to any form of employing children in activities that are mentally, physically, socially, or ethically hazardous and deprive them of their childhood and continuous participation in education. In this study, an attempt was made to present an overview of the situation of these children in Iran using available data related to child labor (microdata from the labor force survey conducted between the years 2016 to 2020 has been used). Subsequently, by applying logistic regression, the individual and household factors influencing child labor were examined. In the overall model, migration (both international and domestic), lack of education among household heads, and rural living were identified as the most significant environmental factors contributing to child labor participation. In urban areas, the most influential environmental factors affecting child participation, in order of importance, were migration (both international and domestic) and household head unemployment. In rural areas, the key environmental variables increasing child participation included the education level of the household head, migration, and household head unemployment. Analyzing urban and rural patterns separately, while avoiding aggregation errors from the overall model, underscores the high impact of economic factors on child labor.
Econometrics
Pegah Mahdavi; Mohammad Ali Ehsani
Abstract
The understanding of applied modeling in causal effects is of particular importance in econometrics, according to recent developments and research in causal inference applications. We also provide an outline of econometrics’ use of causal inference. The majority of economists would agree that the ...
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The understanding of applied modeling in causal effects is of particular importance in econometrics, according to recent developments and research in causal inference applications. We also provide an outline of econometrics’ use of causal inference. The majority of economists would agree that the randomized controlled experiment is the gold standard for drawing conclusions, but actually, a significant portion of empirical work in econometrics relies on observational data, where, among other things, the possibility of confounding or loss of exogeneity must be taken into account. We focus in particular on two types of contemporary research: randomized experiments and observational studies. Our review of the dynamic causality study approach, the linear method, which includes LP and VAR, and nonlinear statistical modeling which includes BART, and their use in econometrics, are all reviewed in this paper. Modeling dynamic systems with linear parametric models usually suffer limitation which affects forecasting performance and policy implications. On the nonparametric framework, BART specifications can produce more precise tail forecasts than the VAR structure. Finally, BART has the lowest RMSE in linear and non-linear data generation processes, and also the performance of BART important variables in a set of macroeconomic data has an optimal performance than other regression estimators.
Monetary economics
Mohammad Amin Shojaeenia; Ahmad Barkish; Abolmohsen Valizadeh
Abstract
This study examines how exchange rate growth and liquidity growth impact the relationship between consumer price index “CPI” inflation and producer price index “PPI” inflation in Iran from 2005 to 2023, using monthly data. We employ continuous wavelet transformation to capture ...
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This study examines how exchange rate growth and liquidity growth impact the relationship between consumer price index “CPI” inflation and producer price index “PPI” inflation in Iran from 2005 to 2023, using monthly data. We employ continuous wavelet transformation to capture the dynamic relationship between CPI and PPI across different frequency bands. Additionally, we use a vector auto-regressive with exogenous variables model to validate our findings and utilized the Granger causality test. In this study, CPI and PPI indices are divided into three categories: CPI and PPI of goods, CPI and PPI of services, and total CPI and PPI, which is the weighted mean of the two priors. Our models are applied separately to each category of CPI and PPI inflation. The results indicate that the relationship between CPI inflation and PPI inflation for goods is stronger and more reliable than for services. Also, we demonstrate how liquidity growth and exchange rate growth contribute to inflation through demand-pull and cost-push mechanisms, respectively. Finally, we highlighted that this relationship is more dependent on exchange rate growth than liquidity growth, particularly in recent years. This indicates that inflation in Iran during the studied period is predominantly driven by cost-push factors rather than demand-pull forces.
Social Economic
Mahdi Filsaraei; Arezoo Yaghoobi
Abstract
Sustainable corporate growth is defined as the sustainable growth of sales and profits under an economic policy and external environment. The ability of enterprises to grow sustainably is not only a guarantee of achieving their long-term business goals, but also a physical requirement for sustainable ...
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Sustainable corporate growth is defined as the sustainable growth of sales and profits under an economic policy and external environment. The ability of enterprises to grow sustainably is not only a guarantee of achieving their long-term business goals, but also a physical requirement for sustainable development of the national economy. Some companies consider sales growth rate or rapid expansion of the company scale as their development goals. This growth is fast, short-term and unstable. The purpose of this research is to investigate the effect of the effectiveness of intellectual capital on the sustainable growth of companies listed in the Tehran Stock Exchange. In this regard, research hypotheses were tested based on a statistical sample of 102 companies during the years 2017 to 2021 and using multivariable regression models. Research results shows that the efficiency of intellectual capital, structural capital and human capital have a positive and significant effect on the growth of the sustainability of listed companies, while efficiency of the used capital has a negative and significant effect on the sustainable growth. The results of this research can be useful for policy makers and company managers, so that they can create sustainable growth in the company. The components of intellectual capital can create long-term sustainable growth in the company and increase the value of the company.
Energy Economics
Hamidreza Panah; Seyed Nematollah Mousavi; Bahaaldin Najafi
Abstract
Oil has a large share of the world's total energy consumption. For this reason, it is obvious that any fluctuations in demand, supply, price and other variables affecting this sector have many effects on the economy of oil producing and consuming countries. Any factor that causes a disruption in the ...
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Oil has a large share of the world's total energy consumption. For this reason, it is obvious that any fluctuations in demand, supply, price and other variables affecting this sector have many effects on the economy of oil producing and consuming countries. Any factor that causes a disruption in the supply or demand of oil and the subsequent market will in most cases lead to a change (decrease or increase) in the price. These price changes have had effects on the behavior of energy producers and consumers due to the price determining factor on both supply and demand sides of the energy market. This study examines the inter-variable time-varying conditional correlation between the world oil price and the return of industrial production index (real GDP) in oil exporting countries (Iran, Saudi Arabia, UAE) and OECD countries. Therefore, in this study, using the monthly data of world oil prices, the efficiency of the industrial production index of the Middle East and OECD countries from 2000-2021, and using the Oxmetrics software, the time-varying conditional correlation of the global oil price and the efficiency of the production index Industry in selected countries has been analyzed by CDCC-GARCH method. The results showed that the time-varying conditional correlation with the global oil price and GDP is real and the changes in the final oil price have caused significant changes in the dynamic correlation between the variables in the form of uncertainty.
Energy Economics
Mina Javadinia; seyyed Abdol Majid Jalaee Esfand Abadi; Mehdi Nejati
Abstract
Today, the energy market in the world is facing an important position, and on the other hand, the importance of gas as a clean fuel is significant. According to the approach and structure of the energy market, the main axis of this research is based on the game theory approach. On the other hand, the ...
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Today, the energy market in the world is facing an important position, and on the other hand, the importance of gas as a clean fuel is significant. According to the approach and structure of the energy market, the main axis of this research is based on the game theory approach. On the other hand, the interests of Iran and Qatar will give rise to a conflict over price between the two countries. Therefore, in the present study the dynamic computable general equilibrium model and the 2014 social accounting matrix were used to investigate the impact of gas price shocks on the gas exports of these two countries. As Iran and Qatar are known as main competitors in the natural gas sector of world energy market, it is necessary to specify a win-win pricing strategy for both countries. Taking this into account, in the present study a model that incorporates both the dynamic computable general equilibrium and game theory is used for investigation purposes. The results indicate that, 0.5% price increase would be the best strategy from among the wide range of gas price scenarios presented for 2022-2024, because a 0.5% increase in gas prices in general would further increase the exports of Iran and Qatar as two competitors. Thus, based on the equilibrium forms, stepwise price rise over a specific time interval can help these two countries maximize their interests.
Energy Economics
Fatemeh Rafiei
Abstract
Energy subsidies have significant economic implications. On the one hand, they have protected consumers, but on the other hand, they have increased the budget deficit and public spending recently. Moreover, they have reduced private investment, especially in the energy sector, another dangerous consequence ...
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Energy subsidies have significant economic implications. On the one hand, they have protected consumers, but on the other hand, they have increased the budget deficit and public spending recently. Moreover, they have reduced private investment, especially in the energy sector, another dangerous consequence of energy subsidies. It is one of the key and controversial debates in the energy sector of the Iranian economy. The present paper is aimed at promoting thinking and research on how to eliminate energy subsidies. One idea is that energy subsidies should be reduced all at once, while others suggest a gradual elimination of energy subsidies. This paper simulates the elimination of energy subsidies in the base metals industry as one of the most energy-intensive industries in Iran. A dynamic recursive computable general equilibrium model is estimated to evaluate the economic impacts of removing gas subsidies in basic metal manufacture in Iran. according to the results, gas consumption will decrease, and electricity and petroleum products will increase in both scenarios (gradual increase in gas prices after 5 years as Scenario 1 and an increase in gas prices at once as Scenario 2). However, during the period, Scenario 2 reduces the supply of basic metals more than Scenario 1.
Monetary economics
Fariba Osmani; Ali Cheshomi; Narges Salehnia; Mohammad Taher Ahmadi Shadmehri
Abstract
In recent years, Iran's economic problems have increased inflation and subsequently affected fluctuations in consumption. Therefore, this research analyzed the impact of positive and negative inflationary shocks on consumption during the monthly period from April 2010 to March 2022 with the NARDL approach. ...
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In recent years, Iran's economic problems have increased inflation and subsequently affected fluctuations in consumption. Therefore, this research analyzed the impact of positive and negative inflationary shocks on consumption during the monthly period from April 2010 to March 2022 with the NARDL approach. This study considers GDP per capita, nominal interbank interest rate, and unofficial exchange rate variables as control variables. The results, supporting Duesenbery’s ratchet effect, show that positive and negative inflation shocks have an asymmetric effect on per capita consumption. One unit of positive inflation shocks growth causes a 0.012 decrease in consumption, and one unit of negative inflation shock causes a 0.049 increase in consumption. This means that there is always excess demand in the market; on the one hand, it is an expression of consumerism in Iranian society. Positive changes in real GDP increase real consumption by a coefficient of 0.733, and negative changes in GDP cause a decrease in consumption by a coefficient of 0.314. Empirical results also discovered long-run asymmetric effects between interest rates and consumption, so with one unit increase in interest rate, consumption decreases by about 0.133. With one unit decrease in interest rate, consumption increases by about 0.117. This study suggests policymakers should prioritize low inflation and economic growth goals in implementing monetary policies to increase household consumption and well-being.
Environmental Economics
Sasan Gharakhani; Hadi Amiri; Babak Saffari; Maede Mohammadi
Abstract
Groundwater is a natural common-pool resource that has long been a victim of tragedy of the commons due to selfish withdrawal of farmers During recent years. One solution to coping with this problem is to replace flood irrigation with large-scale irrigation system (LIS) within the framework of participatory ...
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Groundwater is a natural common-pool resource that has long been a victim of tragedy of the commons due to selfish withdrawal of farmers During recent years. One solution to coping with this problem is to replace flood irrigation with large-scale irrigation system (LIS) within the framework of participatory conservation projects. As these projects are costly, they require financial support by the government and cooperation among farmers. In this study, given the unstable raining conditions and drying out of Zayanderud, an agent-based model (ABM) on participatory management of groundwater resources is proposed for 223 villages in Isfahan Province in the form of participatory conservative projects. The results of this study indicate sensitivity of model’s simulation and high sensitivity of villagers to the government’s financial supports. This model predicts when the government pays 85% of the costs for changing the irrigation system, the participation will rise to two-thirds. Further, the results of simulation suggest that with increasing the number of farmers, the rate of participation will significantly drop. Finally, according to different scenarios in this study, it is suggested that the government begins its financial support from the small villages with the pioneer group (near the pumping water) and scale-free social network.
International Economics
Mohammad Rahimi Ghasemabadi; Reza Zeinalzadeh; Zeinolabedin Sadeghi; Mohsen Zayandehroodi
Abstract
In the modern age, the rise in environmental protection information has resulted in undertaking ecological initiatives by different countries and corporation, aiming to raise environmental performance. This study investigates environmental and socioeconomic monetary values related to carbon emissions ...
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In the modern age, the rise in environmental protection information has resulted in undertaking ecological initiatives by different countries and corporation, aiming to raise environmental performance. This study investigates environmental and socioeconomic monetary values related to carbon emissions produced in activities required for Iran's export. Monetary value damages caused by air pollution have received attention, and in this research, we focused on the financial damages of pollution. Using these monetary values allowed us to compare damages with the economic effects of trade, identify polluted industries and compute trade balance indicators with a wider scope. For this purpose, we used the Input-Output table and calculated the pollution for different industries. The results show that the damages associated with international trade are considerable to the extent that cannot be neglected. Iran 2015 economic data show that avoided Damages were $2432 million by importing, and at the same time, exports caused $3448 million of damages. While the imports had been produced domestically, $2439 million of damages (DIM) and $ 2049 million of value added (VIM) would have been generated. Net damages (ΔD) generated by the trade amounted to $1008 million, which accounts for 0.84 % of the net value added created by the trade of Agriculture. This implied that the net effect of trade was a $1016-million increase in damages caused by CO2 in 2015. Furthermore, the results show that every $1 million of net value added generated by trade caused emission-related net damages of $0.321 million overall.