Shahryar Zaroki; Ahmadreza Ahmadi; Mehdi Hasanpour Varkolaei; Mohammad Reza Zare Chamazkoti
Abstract
This study investigates the impact of government subsidies on economic well-being in Iran, using both symmetric and asymmetric approaches. Economic well-being is first quantified using a composite index based on four components: consumption flow, wealth stocks, income distribution, and economic ...
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This study investigates the impact of government subsidies on economic well-being in Iran, using both symmetric and asymmetric approaches. Economic well-being is first quantified using a composite index based on four components: consumption flow, wealth stocks, income distribution, and economic security. The study then applies an ARDL & NARDL model to assess the linear and non-linear effects of subsidies on economic well-being over the period from 1973 to 2022.
The findings reveal a significant decline in economic well-being from 1975 until the end of the Iran-Iraq War, followed by an upward trend until the Sixth Development Plan. The average index value increased from 20.9 in the First Plan to 60.3 in the Fifth Plan, but then fell to an average of 8 in the Sixth Plan. The share of subsidies in total government expenditure increased from 1973 to the end of the war and during the First to Fourth Development Plans, but decreased thereafter, particularly in the Sixth Plan.Long-term estimates indicate that both increases and decreases in subsidy expenditures directly impact economic well-being. However, the effect of subsidy reductions on economic well-being is more significant than that of increases, suggesting the presence of an asymmetric impact. Moreover, the analysis of the optimal subsidy level reveals that subsidies enhance economic well-being up to a threshold of 8.8% of government expenditure; beyond this point, increasing subsidies has a detrimental effect on economic well-being.Additionally, the study highlights a marked decline in economic well-being during the periods 1976-1989 and 2017-2022, with the post-JCPOA period witnessing a more substantial decline due to the intensification of sanctions.
Introduction
The issue of well-being and its improvement is one of the central concerns of societies, with politicians often claiming to prioritize the creation of well-being for their citizens. Economic well-being is influenced by numerous factors, including population size, economic complexity, globalization, exchange rate fluctuations, economic growth, unemployment, inflation, sanctions, production volatility, government size, and government spending. Empirical studies by Sowa and Edpri (2007), Nan and Zhang (2018), Sunita and Mahendra (2022), and Wu and Liu (2023) highlight the significant impact of government expenditures, such as subsidies, on both economic and social well-being. These studies establish a notable relationship between government spending and economic well-being.
Among the key factors influencing economic well-being, government expenditures, and specifically subsidized spending, play a critical role. These expenditures can directly or indirectly affect economic well-being. Consequently, analyzing changes in government expenditures, particularly subsidies, is crucial for policies aimed at promoting economic growth and improving well-being. Given the close relationship between these two variables, determining the optimal level and composition of government spending can have substantial implications for macroeconomic policy.
It is important to note that the relationship between government expenditures, subsidies, and the factors influencing them is not necessarily symmetrical. Rather, it may exhibit asymmetry. This study seeks to first calculate economic well-being over the past fifty years using a composite index. Second, it aims to analyze both the symmetric and asymmetric effects of subsidy expenditures on well-being in Iran from 1973 to 2022 through three separate models. The autoregressive distributed lag (ARDL) model, incorporating both linear and nonlinear approaches, is employed for model estimation. Additionally, the study explores how variations in subsidy spending impact economic well-being, particularly by distinguishing between the effects of subsidy increases and decreases.
This research is innovative in several ways. First, it uses a comprehensive economic well-being index, as opposed to the Amartya Sen social welfare index, over a more extensive time period (1973-2022), which covers significant political and economic events, including Iran’s development plans, the Iran-Iraq War, the revolution, and international sanctions. Second, while previous studies have not specifically examined the asymmetry in subsidy effects on well-being, this research distinguishes between the impacts of subsidy increases and decreases. Third, the study aims to determine the optimal level of government subsidy expenditures for maximizing economic well-being.
Method
For this study, the IEWB (Index of Economic Well-Being) is used as a comprehensive measure to analyze the economic well-being of Iran over the period from 1973 to 2022. The IEWB index incorporates four key dimensions: effective per capita consumption flow, wealth stocks, distribution of individual income, and economic security. Each of these dimensions is weighted based on its relative importance.The general formula for the IEWB index is as follows:
IEWB=CF+WS+ID+E
Where:
CF = Effective per capita consumption flow
WS = Wealth stocks
ID = Distribution of individual income
E = Economic security
To calculate the economic well-being index, each of these components is assigned a coefficient based on their relative importance. Following the methodology of Osberg and Sharp (2009) and prior studies, the coefficients are as follows:
4 for consumption (CF),
for wealth stocks (WS),
25 for income distribution (ID),
25 for economic security (E).
Given that the dimensions are measured using different units, each component is first normalized before calculating the weighted average. The normalization process ensures comparability across the dimensions, and it is carried out using the following formula:
Here, represents the normalized value, while and denote the minimum and maximum values of the respective dimension. Using this approach, the economic well-being index was calculated for the period from 1973 to 2022.
As mentioned in the introduction, the main goal of this research is to analyze and investigate the symmetrical and asymmetrical effects of subsidies on economic well-being in Iran. The research model focuses on examining how subsidies affect economic well-being, specifically distinguishing between the effects of subsidy increases and decreases. The asymmetric model specification follows Shin et al. (2014), who examined how coefficients of factors affecting a dependent variable may differ during periods of economic well-being versus recession. Building on Pesaran et al.'s (2001) work, they developed the non-linear autoregressive with distributed lag (NARDL) model. This study applies their pattern in two formats (symmetrical and asymmetric) to analyze our research variables. Additionally, a third model is specified to calculate the optimal ratio of subsidy to total government expenditure.
Results and Discussion
The present research investigates and analyzes the effect of subsidies on Iran's economic well-being based on symmetrical and asymmetrical approaches. Additionally, in a separate model (the third model), the optimal ratio of subsidy to government expenditure was calculated. For this purpose, economic well-being was first calculated using the composite index of well-being based on four dimensions for the period 1973-2022, and the coefficients were estimated using three patterns with ARDL & NARDL approaches.
The results of calculating the well-being index and describing the data show that the well-being index increased consistently from the first plan to the fifth plan, rising from 20.9 in the first plan sub-period to 60.3 in the fifth plan sub-period. Furthermore, after the third plan sub-period, the level of well-being remained higher than the average of the studied periods.
The long-run estimation results indicate that subsidies have a direct and asymmetric effect on economic well-being. The direct effect of subsidy decreases on economic well-being is greater than the effect of subsidy increases. Additionally, subsidies demonstrate an inverted U-shaped effect on economic well-being. The optimal ratio of subsidy to total government expenditure for maximizing economic well-being is 8.8%. When subsidies are
below this 8.8% threshold, increases in subsidies are associated with improved economic well-being; above this threshold, additional subsidies lead to decreased economic well-being.
Real GDP per capita and economic growth show positive effects on economic well-being, while inflation demonstrates a negative effect. Based on these findings, it is recommended that policymakers focus on policies to increase subsidy expenditures. However, given the significant negative impact of inflation on economic well-being, policymakers should carefully consider inflation when increasing subsidized expenditures. Non-inflationary methods should be prioritized when financing subsidized expenditures wherever possible.
Aso Esmailpour
Abstract
This study examines how real commodity prices affect foreign exchange market pressure (EMP) in resource-exporting countries using a Panel Smooth Transition Regression (PSTR) approach. Exchange market pressure, characterized by excess demand or supply of domestic currency, often requires monetary ...
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This study examines how real commodity prices affect foreign exchange market pressure (EMP) in resource-exporting countries using a Panel Smooth Transition Regression (PSTR) approach. Exchange market pressure, characterized by excess demand or supply of domestic currency, often requires monetary policy intervention to stabilize currency values. This research specifically investigates the relationship between EMP and real prices of four commodity categories: food, metals, energy, and raw materials.Using data from 1990-2022, we first calculated the EMP index using an independent model method. Our findings reveal the non-linear nature of exchange market pressure, with studied countries experiencing continuous fluctuations between appreciation and depreciation pressures throughout the period, never reaching a pressure-free equilibrium.The PSTR model results demonstrate that real commodity prices have a significant indirect effect on exchange market pressure across the studied countries. The real price index shows a strengthening effect on market pressure in both regimes for all exporting countries, with food-exporting nations particularly exhibiting positive and significant pressure effects across both regimes. Our findings indicate that monetary authority intervention is necessary across all four country groups to achieve target exchange rates and mitigate exchange market pressure.These results have important implications for monetary policy in resource-exporting countries, suggesting the need for active management of exchange market pressure in response to commodity price fluctuations.IntroductionThe collapse of the Bretton Woods fixed exchange rate system marked a fundamental shift in international financial architecture, leading to the emergence of floating, fixed, and intermediate exchange rate systems (Jalal, 2019). Fixed exchange rates encompass currency unions, where one country adopts another's currency or joins a broader monetary union. Floating exchange rates can be either free or managed, with central banks intervening to moderate adverse fluctuations without committing to specific exchange rate levels. Intermediate systems include fixed rates, crawling pegs, currency devaluation, and various hybrid arrangements - all involving central bank intervention to mitigate pressure on domestic currency. Fisher (2001) documents this evolution, noting that countries employing intermediate exchange rates decreased from 98 in 1992 to 63 in 1999, though a significant number maintained these systems.Exchange rates serve as crucial predictive variables for commodity market movements, offering insights that simple time series models cannot capture and necessitating analysis through comprehensive, mixed-data approaches (Ferraro et al., 2015). As a fundamental indicator of international competitiveness, exchange rates significantly influence national trade and economic performance. Exchange rate fluctuations both reflect and perpetuate economic instability, potentially undermining overall economic performance. Research in developing economies suggests that unmanaged structural changes, combined with inconsistent monetary and fiscal policies, create disparities between actual and equilibrium exchange rates.While existing literature has predominantly focused on oil price fluctuations' impact on exchange rates in oil-exporting nations, this study addresses a critical research gap by examining how real commodity price index fluctuations affect foreign exchange market pressure. The need to understand exchange rate dynamics and currency market pressure remains crucial for economic policymaking and market stability. Previous domestic studies have largely employed linear models to evaluate factors affecting currency market pressure. However, given the inherently non-linear nature of currency market pressure, non-linear analytical approaches are necessary for more accurate assessment.This study aims to examine the non-linear relationship between real commodity prices and foreign exchange market pressure across major commodity-exporting countries, categorized into four groups: energy, metals, food, and raw materials exporters. Using a panel smooth transition regression approach for the period 1990-2022, this research extends beyond traditional variables like oil, trade, and GDP to investigate the understudied impact of real commodity price fluctuations on exchange market dynamics.Methods and MaterialThe Panel Smooth Transition Regression (PSTR) model is an extension of the standard panel data framework, characterized by two limiting regimes and a transition function. The basic model is defined by equation (1): Results and DiscussionThe first step in estimating a soft transition regression model involves testing the null hypothesis of model linearity against the alternative hypothesis that the model includes at least one transition variable. The results of Wald's Lagrange Multiplier (LMw), Fisher's Lagrange Multiplier (LMf), and the Likelihood Ratio (LR) tests confirm, at the 5% significance level, the presence of a soft transition regression model (PSTR) with at least one regime. These findings strongly support the non-linear relationship between the variables under study.Subsequently, the residuals were examined to verify the non-linear structure and determine the number of transition functions (𝑟r). This process involves testing the null hypothesis of a single soft transition function against the alternative hypothesis of at least two transition functions. If the null hypothesis is rejected, additional hypotheses are tested sequentially (e.g., two functions vs. three functions) until the null hypothesis is accepted. Ultimately, a soft transition regression model with one transition function, corresponding to a two-regime structure, was selected for the analysis.For food and raw material-exporting countries, the estimated parameters of the two-regime PSTR model reveal the following:(a)Food-Exporting Countries:Slope Parameter: 3.594 (indicating the speed of transition between regimes).Threshold Value: 6.765 for the real food price index.When the food price index equals 6.765, the relationship between the food price index and currency market pressure changes. If the index exceeds 6.765, the model transitions to the second regime at a transition speed of 3.594. Conversely, if the index falls below this threshold, the first regime applies.(b) Raw Material-Exporting Countries:Slope Parameter: 0.876.Threshold Value: 8.302 for the real raw material price index.For these countries, when the raw material price index reaches 8.302, a regime change occurs. If the index exceeds this threshold, the model transitions to the second regime at a speed of 0.876. If it remains below the threshold, the first regime applies.The results highlight the non-linear dynamics of the relationship between real price indices and currency market pressure. The coefficients of variables vary with the transition variable's value (price index) and slope parameters, differing across countries and over time. These findings underscore the need for country-specific and time-sensitive policy interventions to manage currency market pressures effectively.ConclusionThis study analyzed the impact of real prices for food, raw materials, metals, and energy on foreign exchange market pressure (EMP) in exporting countries during the period 1990–2022, using the soft transition regression (PSTR) approach. The findings reveal significant and varied effects across different export categories and regimes, highlighting the non-linear nature of these relationships:Metal-Exporting Countries:The real price index of metals negatively impacts currency market pressure in both regimes.However, the trade balance level exerts a positive influence on EMP in both the linear and non-linear regimes.Energy-Exporting Countries:The real price index of energy strengthens EMP in both regimes, indicating heightened sensitivity of currency markets to energy price fluctuations.The trade balance level exerts a negative effect on EMP, demonstrating its stabilizing role in both linear and non-linear contexts.Food-Exporting Countries:The real food price index has a positive and significant effect on EMP in both regimes, reflecting increased market pressure with rising food prices.Net foreign assets also contribute positively and significantly to EMP in both linear and non-linear regimes.In contrast, the trade balance equilibrium level mitigates EMP in both regimes.The Balassa-Samuelson effect is found to significantly influence EMP, underscoring the role of productivity differentials in currency market pressures.Raw Material-Exporting Countries:Price indices and the trade balance level negatively and significantly affect EMP in both regimes, suggesting that higher raw material prices and stronger trade balances alleviate market pressures.Net foreign assets exhibit a dual effect: positively impacting EMP in the first regime but negatively and significantly affecting it in the second regime.The real price index of goods and the Balassa-Samuelson effect exert positive and significant influences on EMP in both linear and non-linear regimes.The findings emphasize the importance of tailored monetary and fiscal policies in addressing foreign exchange market pressures. For instance:-Policymakers in metal-exporting countries should focus on trade balance optimization to counter EMP despite price fluctuations.-In energy-exporting countries, stabilizing energy prices and enhancing the trade balance are critical to managing EMP effectively.-For food-exporting countries, mitigating the adverse effects of rising food prices and leveraging net foreign assets can stabilize currency markets.-Raw material-exporting countries should consider balancing price dynamics and trade balances while accounting for the dual role of net foreign assets in EMP.
Sholeh Bagheri Pormehr; Zahra Laki; Hanieh Parnyan
Abstract
Economic growth models have long grappled with fundamental questions regarding the relationship between different types of capital and real growth rates. While numerous empirical studies have demonstrated the independent effects of physical capital and social capital on the quantity and quality ...
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Economic growth models have long grappled with fundamental questions regarding the relationship between different types of capital and real growth rates. While numerous empirical studies have demonstrated the independent effects of physical capital and social capital on the quantity and quality of economic growth, less attention has been given to the interactive effects of these investment types. This study examines the influence of social capital on the interaction between physical capital and Iran's economic growth using the Smooth Transition Regression (STR) model. The analysis covers the period 1346–1400 (1967–2021) and employs four indicators inspired by Fukuyama's framework to measure social capital.
The findings indicate that the impact of physical capital on Iran's gross domestic product (GDP) varies across different levels of social capital. Periods of greater fluctuations in social capital have been associated with increased variability in the effect of physical capital on economic growth. Specifically, stronger social capital enhances the productivity of physical capital, while weaker social capital reduces its effectiveness.
This study highlights the critical role of social capital in shaping the returns on physical capital investments, suggesting that strategies to stabilize and strengthen social capital could lead to more consistent and sustainable economic growth outcomes.
Introduction
Economic growth, as a key driver of national welfare, has long captured the attention of not only economists but also social and political scientists. This interest stems from its profound impact on living standards, social stability, and political dynamics. Unstable economic conditions, linked to phenomena such as unemployment, inflation, and disparities in quality of life and life expectancy, can trigger social unrest and political crises. As such, understanding the determinants of economic growth is essential for shaping policies that foster sustainable development and prosperity.
One of the enduring questions in the study of economic growth concerns why nations or regions with similar resource endowments and economic conditions often experience divergent growth trajectories. This question remains partially unresolved, especially regarding the interplay of various forms of capital in driving economic outcomes.
This study focuses on examining the factors influencing Iran's gross domestic product (GDP), with a particular emphasis on the role of social capital in shaping the impact of physical capital over the period 1346–1400 (1967–2021). Specifically, the research investigates the threshold effect of social capital on the interaction between physical capital and GDP, exploring how varying levels of social capital influence the productivity of physical capital in the Iranian context.
A review of prior studies reveals mixed findings regarding the relationship between human capital and economic growth. While some research highlights a positive correlation, others argue that variables such as social capital and the broader developmental context mediate this relationship. Similarly, studies on the role of social capital in economic growth suggest its contribution, albeit often emphasizing its indirect role or relatively modest impact compared to other variables. This study seeks to build on these findings by specifically exploring the interaction between social capital, physical capital, and production, offering new insights into their combined effects on economic growth in Iran.
The study is structured into seven sections. Section 2 reviews the theoretical foundations underpinning the research. Section 3 explores the existing literature and contextual background of the study. Section 4 details the research methodology, while Sections 5 and 6 discuss the data and findings, respectively. Finally, Section 7 presents the conclusions and policy recommendations derived from the analysis.
Methods and Material
While linear estimation methods are simpler and often preferred for their ease of use, they are not always suitable for analyzing economic phenomena with inherently nonlinear behavior. Relying on linear models in such cases can lead to inaccurate specifications and misleading results, underscoring the need for more flexible nonlinear regression models.
In the context of social capital's impact on economic growth, the dynamics differ from the short-term effects of trade shocks or external economic fluctuations, which often have a pendulum-like nature. Instead, the erosion of social capital gradually distorts the economic landscape, exerting a prolonged and subtle influence on growth trajectories. These long-term and incremental changes necessitate a modeling approach capable of capturing both the gradual and nonlinear nature of these effects.
To address this, the Smooth Transition Regression (STR) model was selected for the analysis. The STR model offers significant flexibility by accommodating nonlinear relationships between variables without imposing restrictive or predefined functional forms. This approach allows for the modeling of transitional changes based on observations of the threshold variable, enabling the examination of how variables evolve and interact continuously across regimes.
In essence, the STR model is particularly suited to studying the nonlinear effects of social capital on GDP, as it captures the slow and progressive changes in economic outcomes resulting from variations in social capital. By employing a transfer function, the model identifies regime-dependent behaviors and thresholds, providing a comprehensive framework to analyze the nuanced relationship between social capital, physical capital, and economic growth over the long term.
Conclusion
This study aimed to investigate the role of social capital in the interaction with physical capital and its effect on Iran's GDP. Specifically, it explored how social capital influences economic growth both directly, as a production input, and indirectly, as a threshold variable that modulates the impact of other inputs, including physical capital.
The findings align with the broader literature, underscoring the pivotal role of social capital in differentiating the economic outcomes of nations. Social capital, reflected in the quality of governing institutions, their behavior, and their interactions with society, is confirmed to have a strong, two-way relationship with economic growth. Importantly, previous studies have highlighted that while measuring social capital quantitatively is challenging, its absence (manifested through phenomena such as crime or corruption) provides compelling evidence of its critical role.
Over the 54-year period of analysis (ending in 1400), this study employed Fukuyama's conceptual framework for social capital and utilized a smooth transition regression model with an exponential transfer function. The results validated the hypothesis that social capital significantly influences the interaction between physical capital and economic output. Specifically, periods of greater fluctuations in social capital were associated with more pronounced variations in the effect of physical capital on production.
Given the unique properties of social capital—particularly its tendency to depreciate if not actively utilized—this study recommends adopting strategies to bolster its presence in society. Drawing from the experiences of successful nations, the following steps are proposed:
Encouraging Non-Governmental Organizations (NGOs): Promote the activities of NGOs to foster public participation, especially among youth and elites, thereby building trust and strengthening social networks.
Reversing Brain Drain: Iran’s position as a major exporter of human resources underscores the need for policy reforms that create opportunities for the political participation of diverse groups. Ensuring inclusivity—irrespective of religion or political affiliation—can help rebuild public trust and attract expatriates with human and financial capital.
Strengthening Public Trust: As the cornerstone of social capital, public trust must be prioritized through transparency, equitable governance, and the provision of meaningful social roles for all citizens.
Ultimately, by fostering social capital and leveraging it to enhance the productivity of physical capital, Iran can create the foundation for sustainable economic growth and development.
Reza Talebloo; parisa mohajeri; Mortaza Yeganeh
Abstract
Volatility analysis is considered a modern and efficient tool for estimating, managing, and hedging risk, valuing and selecting optimal portfolios, and aiding investors in making informed financial decisions. This research aims to present a model for the risk analysis of 30 large companies listed ...
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Volatility analysis is considered a modern and efficient tool for estimating, managing, and hedging risk, valuing and selecting optimal portfolios, and aiding investors in making informed financial decisions. This research aims to present a model for the risk analysis of 30 large companies listed on the Tehran Stock Exchange using the Multivariate Factor Stochastic Volatility Model (MFSVM) within the framework of a non-linear state-space approach. In this framework, the volatility of stock returns is decomposed into two components, "volatility arising from latent factors" and "idiosyncratic risks". The dynamic correlation matrix of the volatility of stock returns is then estimated. In this regard, weekly stock return data from January 10, 2018, to October 7, 2023, were utilized. The results of the research indicate that the first three hidden factors influence the volatility of stock returns. The first factor impacts stocks in the oil products industry, chemical products, basic metals, mining, and investment funds. The second factor predominantly affects banks, while the third factor also influences bank stocks to some extent. Second, the strongest posterior pairwise correlations are observed between “GDIR” and “PTAP” (74%), “PASN” (73%), and “FOLD” (71%). Additionally, “FOLD” shows a 69% correlation with both “PASN” and “PTAP,” and a 66% correlation with “MSMI” and “MADN”. The weakest correlation is between “GDIR” and “BPAS” (-10%). Third- “BPAS” exhibits the lowest correlation within the stock network, whereas “GDIR” shows the highest correlation.
Introduction
The research utilizes a multivariate factor stochastic volatility model to analyze the volatility of stock returns for 30 major companies listed on the Tehran Stock Exchange. Factor models operate on the premise that all systems, even those with high dimensions, are driven by a few random factors. These random factors influence the hidden common interactions among observations. Essentially, these models reduce the number of unknowns by decomposing the dynamic covariance matrix into two distinct matrices: one for the latent factors and another diagonal matrix for the idiosyncratic variances. By employing an orthogonal latent factor space with fewer dimensions, the model effectively reduces the number of unknowns, enabling a more precise representation of stock return volatilities. This approach mitigates the curse of dimensionality and provides an efficient estimate of the dynamic covariance matrix.
The model highlights the crucial role of latent factors in stock return volatility and provides a framework for comprehending dynamic correlations in stock markets, which fluctuate among different stocks over time. It effectively captures potential elements such as clustered volatility and co-movements of volatilities, while remaining resilient against shocks unique to each company’s stock.
Methods and Material
In this research, a multivariate factor stochastic volatility model in R software, along with the relevant packages, based on the Markov Chain Monte Carlo (MCMC) method, has been used to analyze volatilities in the Iranian stock market. The study sample includes weekly return data of 30 large stocks listed on the Tehran Stock Exchange, covering the period from January 20, 2018, to October 7, 2023, extracted using TseClient 2.0 software. The 30 large companies operate in various industries, including banking, insurance, petrochemicals, and other sectors. In this model, based on the Gibbs sampling method in the R software package (Kastner, 2016), the aim is to estimate the parameters and their sampling uncertainty within a Bayesian framework. By quantifying the inherent uncertainty, an appropriate estimate of the sample density distribution is provided.
Results and Discussion
The results indicate the presence of three latent factors. (figure 1) The first latent factor, seemingly rooted in international events, primarily affects export-oriented commodity companies. The second and third latent factors, which appear to have domestic origins, predominantly impact the volatilities of bank returns (figure 2). The studied stock volatilities exhibit clustered and co-movement behaviors, which intensify at certain times. The correlation intensity between the stock return volatilities of the companies under study has increased over time. Initially, during the study period, the correlations were relatively weak and mainly limited to relationships among export-oriented commodity companies. However, these correlations increased across the entire market, peaking from August 2019 to July 2020, before subsequently declining.
The highest posterior pairwise correlations are between Ghadir Investment Company (GDIR) and Oil, Gas, and Petrochemical Investment Company (PTAP), Parsian Oil and Gas Development Company (PASN), and Mobarakeh Steel Company (FOLD) at 74%, 73%, and 71%, respectively. Additionally, FOLD shows correlations of 69% with both PASN and PTAP, and 66% with National Iranian Copper Industries Company (MSMI) and Mines and Metals Development Investment Company (MADN). The weakest pairwise correlation is between Pasargad Bank (BPAS) and GDIR at -10%. BPAS also exhibits the weakest average correlation of approximately (-5%) with the entire stock network, while GDIR has the strongest average pairwise correlation with the entire stock market network at 47.5%.
Figure 1: log Variance of Factors
Figure 2: loading of factors
Given that forming an efficient and diversified stock portfolio requires an understanding of the behavior and correlations between the volatilities of the desired stock returns, the results of this study can provide a clear understanding of the return volatilities of the large companies’ stock network and assist in designing appropriate investment strategies. Additionally, optimizing stock portfolios, valuing options, and calculating value at risk using MFSVM could be subjects for future research, which have not been extensively explored in the domestic research space.
Conclusion
In this article, the Multivariate Factor Stochastic Volatility Model (MFSVM) is used within a non-linear state-space framework to decompose the volatility of stock returns into two components: “volatility arising from latent factors” and “idiosyncratic risks”. Additionally, the dynamic correlation matrix of stock return volatilities is estimated. The results reveal three hidden factors. The first hidden factor, seemingly influenced by international events, primarily affects export-oriented commodity companies. National events are reflected in the second and third factors, which predominantly impact the volatilities of bank returns. The volatilities of stock returns exhibit clustering and co-movement behaviors, which intensify at certain intervals. At the beginning of the investigation period, only the volatilities of export-oriented commodity companies were related to each other. However, during an upward trend, correlations increased across the entire market, peaking from August 2019 to July 2020, before subsequently declining.
Pairwise posterior correlations between stock volatilities were also investigated. The highest posterior correlations were observed between Ghadir Investment Company (GDIR) and Oil, Gas, and Petrochemical Investment Company (PTAP), Parsian Oil and Gas Development Company (PASN), and Mobarakeh Steel Company (FOLD), with correlation coefficients of 74%, 73%, and 71%, respectively. The weakest correlation coefficient was between GDIR and Pasargad Bank (BPAS) at -10%. BPAS exhibited the lowest average correlation of approximately -5% with the entire stock network, while GDIR had the strongest average pairwise correlation with the entire stock market network at 47.5%. The results of this research provide a clear understanding of the volatility of the listed companies’ stocks and can assist in designing suitable investment strategies, optimizing portfolios, and calculating value at risk using MFSVM. These areas could be subjects for future research, which have not been extensively explored in the domestic research space.
Mohammad Azimzadeh Arani; mohsen kojury
Abstract
Features such as natural monopoly and economies of scale in network industries such as the electricity industry led to the fact that in most countries, the ownership and management of the mentioned industries in a vertically integrated form is provided to the government. Such an attitude ...
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Features such as natural monopoly and economies of scale in network industries such as the electricity industry led to the fact that in most countries, the ownership and management of the mentioned industries in a vertically integrated form is provided to the government. Such an attitude prevailed in most countries until the end of the 1980s. Technological advances in these industries, including the electricity industry, led to a new attitude in the 1990s. Based on this approach, vertically integrated network industries include separate activities that have different economic characteristics from competitive to monopoly levels, and this provided the basis for power sector reform.
This study employs analytical-descriptive methods and a case study approach, structured into three parts. The first part establishes a theoretical framework, examining the key components of electricity sector reforms and the importance of sequencing these reforms. The second part analyzes China's electricity sector reform process in five stages, based on the developed framework. The third part provides tailored policy recommendations for Iran's electricity industry. The findings of this research show that China's experience in the gradual separation of policy-making, regulation, and service provision affairs from each other, decentralization through the mechanism of provincial and local governments, and the commercialization of state-owned companies can bring lessons learned for Iran's electricity industry. In this regard, recommendations such as a-reorganizing the Ministry of Energy as a policy-making body and state-owned companies as actors of the service provider layer and b- Redefining the new financial relationship between the key companies of the electricity industry and the Ministry of Energy in order to commercialize the behavior of state-owned companies are suggested for Iran's electricity sector.
Introduction
In the 1990s, the atmosphere for breaking the vertically integrated structure in the electricity industry was provided.Chile was the first country to start reforming the electricity sector in 1978. After Chile, the wave of reforms in the electricity sector reached a new stage in England and America in 1979 and 1981, respectively. The design and implementation of electricity sector reforms in developing countries and even developed countries have followed different paths with completely different results. For example, despite the success of England, South Korea's power sector reforms met with a degree of failure.
Since China has experienced a structurally and functionally different process in the reforms of the electricity sector and has many similarities with Iran's economy from the point of view of the level of government intervention in economic activities, therefore, in this article, the experience of this country has been analyzed. This article intends to answer the following questions in this regard: 1- What components are included in the reforms of the electricity sector and is their sequence (first and last) important? 2- How and during what stages has China been able to implement reforms in the electricity sector? And 3- What lessons can China's experience in the field of electricity sector reforms bring to Iran's electricity industry?
Methods and Material
The first section of this research is done by analytical and descriptive methods through the review of related articles and books. In the second section, China's electricity sector reforms have been analyzed by case study method. This method deals with the deep study of a case, a specific topic, or a specific phenomenon. The last section is dedicated to providing recommendations for Iran's electricity industry.
Results and Discussion
In this article, the components of the electricity sector reforms were analyzed from the perspective of the World Bank and other experts. Unlike the World Bank's model, which summarizes the reform process in four key components, other thinkers in this field not only believe in the components of electricity sector reform in various forms such as three-stage, four-stage, and five stages models, but they have also criticized their sequence depending on the conditions of each country.
The next part was devoted to China's experience in the reform of the electricity sector. The process of reforming the electricity sector in this country is summarized in five stages.
In the first stage (1949 to 1985), all activities were vertically integrated within the Ministry of Electric Energy (MEP). In the second stage (1985 to 1996), structural and institutional changes occurred through diversification of ownership and management decentralization by granting powers to provincial governments, and gradually the governance structure of China's electricity sector became very similar to the quasi-federal model.
The third phase (1997 to 2001) in China is dedicated to the commercialization of state-owned enterprises (SOEs) in the electricity industry. Corporatization and commercialization at this stage, provided conditions for government service companies to operate as commercial entities. The fourth stage (2002 to 2014) is assigned to the separation of the generation sector from the network and institutional changes in this regard. In the fifth stage (2015 until now), additional measures have been taken to improve the electricity market situation in China. At this stage, the powers of the provincial governments increased compared to before, and matters such as the responsibility of creating a separate transmission and distribution tariff, and creating electricity markets, were all granted to the provincial institutions.
Conclusion
The key finding of this research shows that China has been able to achieve a successful path through three policies: 1- Gradual separation of policy making, regulation and service provision affairs from each other, 2-Decentralization through the mechanism of provincial and local governments, and 3- Commercialization of state-owned companies. In this regard, the following recommendations are suggested for Iran's electricity industry:
Legislative revisions: Revision of the Iranian Electricity Organization Law (1967) and the Ministry of Energy law (1975) based on specifying the duties and authorities in three layers: policy making, regulation and service provision.
Restructuring governance: Reorganizing the Ministry of Energy as a policy-making body and state-owned companies as actors of the service provider layer.
Financial restructuring: Redefining the financial relationship between the key companies of the electricity industry and the Ministry of Energy in order to commercialize the behavior of state-owned companies in this sector
Sogol Shahidi; Davood Abbasi Karjagan; Seyyed Mohsen Tabatabaei Mozdabadi
Abstract
This study examines the impact of organizing informal street businesses on food tourism in Tehran, with a focus on sustainable urban development. The research surveyed 384 tourists on 30 Tir Street using a validated questionnaire. Path analysis revealed significant relationships between both ...
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This study examines the impact of organizing informal street businesses on food tourism in Tehran, with a focus on sustainable urban development. The research surveyed 384 tourists on 30 Tir Street using a validated questionnaire. Path analysis revealed significant relationships between both personal and collective organization of street vendors and tourist satisfaction. Personal organization positively influenced satisfaction, enhancing service quality, while collective organization among vendors further improved overall experiences. These results suggest that the structured organization of street vendors can boost service quality, thereby supporting sustainable economic growth in urban areas.
Introduction
Food tourism has become a critical factor in attracting visitors and enhancing their experiences. Informal street vendors play a significant role in this niche, particularly in urban areas where street food culture is prevalent. However, the lack of organization and support for these businesses often leads to challenges in maintaining service quality, which can affect tourist satisfaction.
This study explores how the personal and collective organization of informal street vendors can enhance the overall food tourism experience, particularly in Tehran's 30 Tir Street.
Research Questions
How does the personal organization of informal street vendors affect tourist satisfaction?
What role does collective organization play in enhancing the quality of food tourism services?
Methods and Materials
The study employed a descriptive-correlational research design with a sample of 384 street food visitors selected using non-random convenience sampling. Data were collected through a structured questionnaire validated by experts in the field. Path analysis was conducted to evaluate the relationships between the organization of informal street vendors and tourist satisfaction.
Results and Discussion
The findings revealed a significant positive relationship between personal organization of vendors and tourist satisfaction, highlighting the importance of effective planning and management. Additionally, collective organization among vendors positively impacted service quality, enhancing the overall tourist experience. These results indicate that organizing informal businesses, both individually and collectively, can lead to improved service quality and higher tourist satisfaction. The path analysis model, which illustrates these relationships, is shown in Figure 1 below. The figure demonstrates the influence of personal and collective organization on tourist satisfaction, with significant path coefficients indicating the strength of these effects.
Figure 1. Path Analysis of the Impact of Personal and Collective Organization on Tourist Satisfaction
As depicted in Figure 1, the analysis confirms that personal organization (factor loading = 0.582, t = 7.0532) and collective organization (factor loading = 0.181, t = 2.6051) have a statistically significant impact on improving satisfaction with food services.
Conclusion
The study concludes that organizing informal street vendors significantly contributes to enhancing tourist satisfaction in food tourism, which in turn can support the sustainable economic development of urban areas. It is recommended that training programs focusing on hygiene, food safety, and customer service be provided to street vendors. Additionally, collaborative efforts, such as forming associations or cooperatives, could strengthen vendor capabilities and improve service quality.
Acknowledgments
We would like to express our gratitude to all participants and experts who contributed to this study, as well as the faculty members who provided their valuable feedback.
Conflict of Interest
The authors declare no conflict of interest regarding the publication of this research.
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