Research Paper
Monetary economy
Mohammad Mahdi Asgari Dehabadi; Ali Nassiri Aghdam; Hossein Doroodian; Parisa Mohajeri
Abstract
Iran’s economy has encountered significant challenges in recent years, with the government debt to contractors emerging as one of the most urgent issues. This situation has negatively impacted Iran’s monetary and banking system, leading to several adverse consequences such as increased funding ...
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Iran’s economy has encountered significant challenges in recent years, with the government debt to contractors emerging as one of the most urgent issues. This situation has negatively impacted Iran’s monetary and banking system, leading to several adverse consequences such as increased funding costs for banks, higher loan interest rates, excessive money supply, and a reduced capacity for banks to provide loans. A proposed solution is based on credit easing and endogenous money, which involves settling the government debt to contractors by making adjustments on the asset side of the Central Bank’s balance sheet. However, the practical implementation of this policy depends on the use of Central Bank resources, which raises concerns about a sudden increase in the money supply and potential negative effects on other economic variables, especially inflation. This uncertainty has led to doubts about the feasibility of such a strategy. The present research aimed to examine the fundamental principles and prerequisites for adopting a credit easing policy in Iran. The study also used stock-flow consistent models to evaluate the potential outcomes of implementation of the policy. The findings indicate that settling the government debt to banks by using the Central Bank resources results in an expansion of the monetary base and money supply, an increase in real GDP, and a reduction in both inflation and interest rates compared to the baseline scenario.1.IntroductionIran’s economy has been facing various problems in recent years. One significant issue is the government debt to contractors, which has adversely affected Iran’s economy, particularly the monetary and banking system. The government’s failure to settle its debts with contractors results in contractors being unable to repay loans taken from banks, leading to an increase in the banks’ non-performing loans. This predicament has precipitated several adverse consequences, including higher funding costs for banks, increased interest rates on loans, an uncontrolled surge in the money supply, and a diminished capacity for banks to provide loans. To address this challenge, some economists, emphasizing endogenous money, look to the quantitative policies applied by central banks in advanced countries like Japan and the United States. They have proposed a solution grounded in credit easing, which involves settling the government debt to contractors by making adjustments on the asset side of the Central Bank’s balance sheet.2.Materials and MethodsIn this method, the government issues bonds to settle its debt with contractors and provides these bonds to the contractors. The Central Bank then purchases these bonds by increasing the bank’s reserves. Since the Central Bank does not directly transact with individuals, it uses commercial banks as intermediaries to facilitate the payments. Consequently, the money supply and the monetary base increase immediately. However, if the contractors owe money to the banks, according to the law of reflux, the newly created money will quickly disappear. This method is largely similar to the second type of treasury bonds used by the Iranian government in recent years. Implementing this policy can reduce non-performing loans, curb the growth of the money supply, and prevent the recognition of illusory profits. It can also lower the level of overdue loans and improve banks’ balance sheets. Additionally, it can reduce the banks’ debt to the Central Bank, thereby lowering the cost of money and reducing loan interest rates. Moreover, the reduction in interest rates can lead to increased loan demand and, consequently, future growth in the money supply.It should be noted that this policy leads to a change in the composition of the Central Bank’s assets, but it does not necessarily result in the growth of monetary base and money supply. However, since the policy relies on the use of Central Bank resources, concerns about a sharp increase in the money supply and potential adverse effects on macroeconomic variables, such as inflation, have always hindered its adoption. The present study used Stock-Flow Consistent (SFC) models to evaluate the effects of these policies on Iran’s macroeconomy. Having gained prominence since the 2007–2008 financial crisis, SFC models aim to integrate the real and financial sectors of the economy within a single framework. They help predict endogenous crises in the economy and enable modeling of the economy based on endogenous money. Therefore, SFC models were used to determine the effects of policies similar to credit easing to settle the government debt with contractors. The focus is on various economic variables, including the monetary base, money supply, and banks’ balance sheets in the monetary sector, as well as real GDP, economic growth, real consumption, inflation, and interest rates in the real sector of the economy.3.Results and DiscussionThe results indicate that settling the government debt to banks by using the Central Bank resources leads to an expansion in the monetary base and money supply, as well as an increase in real GDP and real consumption compared to the baseline scenario. However, the effect of this policy on economic growth completely dissipates after eight periods following its implementation, with the growth rate difference eventually tending towards zero. The graph below illustrates the difference in economic growth between the baseline scenario and the scenario where the government debt to contractors is settled using the Central Bank resources. Figure 1. Difference in Economic Growth: The Baseline Scenario and the Government Debt Settlement Scenario Source: The research analysisAccording to the model’s results, implementing this policy leads to a long-term decrease in inflation by 0.23 percentage points.Figure 2. Difference in Inflation: The Baseline Scenario and the Government Debt Settlement Scenario Source: The research estimationsAdditionally, the results indicate that the policy can lead to a 0.53 percentage point decrease in the interest rate. Figure 3. Difference in the Interest Rate: The Baseline Scenario and the Government Debt Settlement Scenario Source: The research estimations4.ConclusionThe model’s results indicated that the policy, despite increasing the money supply compared to the base scenario, leads to improved economic growth, reduced inflation and interest rates, enhanced bank balance sheets, and increased household welfare (via higher real consumption) compared to the baseline scenario.However, the method is recommended only to address the current problem in the present situation. The research results showed that the proposed policies guide the economy onto a better path than its current trajectory, but they are not a prescription for the government’s indiscriminate use of the monetary base. To improve conditions in the long term, the government needs a program to control its budget deficit and stop borrowing from banks and the Central Bank. According to the findings, borrowing from the Central Bank to settle outstanding debts with contractors is preferable to leaving these debts unpaid. However, the optimal approach is for the government to avoid needing to borrow from the Central Bank altogether.
Research Paper
Financial Economics
Teimur Mohammadi; Mohammad Reza Feghhi Kashani; Mahdi Samei
Abstract
The negative correlation between an asset’s volatility and its return is known as leverage effect. This relationship is explained by the effect of a firm’s equity return on the degree of leverage in its capital structure. If this relationship holds, the increased volatility resulting from ...
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The negative correlation between an asset’s volatility and its return is known as leverage effect. This relationship is explained by the effect of a firm’s equity return on the degree of leverage in its capital structure. If this relationship holds, the increased volatility resulting from a fall in stock price should be comparable with the decreased volatility resulting from a price rise with the same magnitude, and this effect should also be persistent. Most research on the leverage effect has examined the relationship between the behavior of returns and return volatility. The present study aimed to examine the relationship between return volatility, returns, and the debt ratio. The data were collected from 22 biggest companies listed on the Tehran Stock Exchange for the period from March 2009 to March 2019. The value of debt in the capital structure of the selected companies was calculated using the Geske compound option pricing model. According to the results, the existence of an asymmetric effect on returns only during bearish market conditions, alongside the instability of this effect, indicates that the debt ratio cannot explain the behavior of returns and return volatility.1.IntroductionExtensive research on return volatility and its modeling reflects the considerable attention and importance this topic holds within various financial domains. The sheer number of scientific inquiries into volatility modeling and prediction underscores its significance in financial discourse, playing a pivotal role in both theoretical and empirical realms (Kambouroudis et al., 2021). Uncovering the influential factors affecting return volatility and gaining insights into their impact can contribute to a deeper understanding of return volatility. The leverage effect, which denotes the negative relationship between an asset’s return and its return volatility, suggests that as an asset’s return increases, its volatility decreases and vice versa. A common explanation attributes the divergent behavior of stock returns and return volatility to the debt ratio in a company’s capital structure (Aït-Sahalia et al., 2013). When a company’s value increases, assuming the debt value remains stable, the relative return on equity will rise more than the overall company return because the total stock value is less than the total company value. Therefore, equity in a company with a higher debt ratio will exhibit greater volatility compared to the overall company, with this difference depending on the equity ratio in the company’s capital structure. This relationship with the debt ratio also leads to a systemic and inverse change in equity return volatility relative to its own return. When negative stock returns lead to a decrease in equity value relative to the fixed amount of debt, the debt ratio increases, resulting in an anticipated increase in stock volatility in the future. Conversely, positive stock returns are expected to have the opposite effect. The market value of a company’s equity affects the value of its debt. This research aimed to examine the ability of debt ration to explain the observed leverage effect. Therefore, accurately estimating the debt ratio and the value of the debt is crucial. In this line, the present inquiry investigated the relationship between stock return volatility and the debt ratio in the case of companies listed on the Tehran Stock Exchange.2.Materials and MethodsThis study used the model proposed by Figlewski and Wang (2000) in order to investigate the leverage effect. A distinctive aspect of the current research lies in the calculation of the debt value and the debt ratio using the Geske compound options pricing model (Geske, 1979).The sample of the study consisted of 22 non-banking companies selected from the top 30 listed on the Tehran Stock Exchange. Seven banking symbols and one symbol with insufficient information were excluded from the analysis. Banking symbols were excluded due to the unique nature of the banking business, which significantly influences debt performance (Damodaran, 2013). Data on prices, number of shares, and debt structure for these companies were systematically collected from 2009 to 2019. The study relied on quantile regression as the analytical approach. Quantile regression is particularly robust in scenarios where errors deviate from a normal distribution or outliers are present in the data. This method allows for model estimation without being constrained by assumptions typical in ordinary regression, such as homoscedasticity and the influence of outliers on coefficient estimation.3.Results and DiscussionIf the leverage effect, characterized by the negative relationship between return volatility and stock returns, were solely due to returns influencing the debt ratio, one would expect this effect to be consistent across positive and negative returns. Additionally, assuming the effect of returns on the debt ratio remains stable over time, one would anticipate a stable effect on return volatility as well. The findings indicated asymmetric effects of returns on return volatility, with a notable difference between positive and negative returns. Moreover, over time, both the magnitude and significance of this effect diminish. Another objective was to explore the direct effect of the debt ratio on return volatility. Similar to the previous case, the data suggested differing effects of the debt ratio during upward and downward trends. When the debt ratio increases due to declining returns, there is a consistent relationship observed between return volatility and the debt ratio. Conversely, during upward trends, the relationship between the debt ratio and return volatility is inverse. Furthermore, in assessing the stability of the effect of debt ratio on return volatility, the coefficients of lagged debt ratios were not significant, with only the coefficient of the current period’s debt ratio showing meaningful impact over the study duration.4.ConclusionAccording to the results, if a leverage effect exists, it manifests primarily in bearish market conditions (associated with an increasing debt ratio), and this effect is not stable over time. Consequently, the debt ratio alone cannot fully explain the relationship between return behavior and return volatility.
Research Paper
Banking
Meysam Amiri; Samira Farahani
Abstract
In recent decades, the functioning of financial markets and banks has undergone significant changes. Many institutions resembling traditional banks have emerged outside the regulatory framework of the central bank, a phenomenon known as shadow banking. Instead of engaging in the traditional activities ...
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In recent decades, the functioning of financial markets and banks has undergone significant changes. Many institutions resembling traditional banks have emerged outside the regulatory framework of the central bank, a phenomenon known as shadow banking. Instead of engaging in the traditional activities of conventional banks, shadow banking employs a more diverse set of resources and instruments, lead to changes in economic risks and influencing economic policies in various countries. The present study aimed to examine shadow banking and its relationship with traditional banking from 2011 to 2021 in Iran. It relied on the modeling of money demand functions within a system of simultaneous equations along with the Minflex Laurent flexible functional form. Moreover, the BEKK–GARCH model was used to address heteroscedasticity. The findings indicate that shadow banking has grown at an increasing rate over the past decade. According to the Morishima elasticity of substitution, conventional banking and shadow banking alternated in replacing each other during the 2010s. Additionally, the results showed that the spillover effect of short-term deposit shocks and fixed-income funds on Islamic bonds was positively significant, while the effect of shocks from fixed-income funds on cash and short-term deposits was not significant.1.IntroductionSince the early 1960s, a new phenomenon has emerged in the banking sector and has rapidly expanded, which involves the shift of intermediation from traditional banks to non-banks outside the supervision of the central bank (Buchak et al., 2018). These institutions, known as shadow banks, have grown rapidly in both developed and emerging countries over the past decades, playing a crucial role in the development of their monetary and financial markets (Łasak, 2015). However, shadow banking has also posed several challenges. Many financial experts attribute the recent global financial crisis to the complex structure of shadow banking, supported by a global consensus on the significant role of shadow banks in the 2007–2009 financial crisis (Pozsar et al., 2013; Lysandrou & Nesvetailova, 2014). Shadow banking presents both an opportunity and a challenge. While companies and households benefit from shadow banking as an alternative financial channel, maintaining financial stability in the market has become even more complex and challenging (Allen & Gu, 2020). In the present study, the term cash includes paper money, foreign currency, coins, traveler’s checks, and short-term deposits as liabilities of bank deposits. Fixed-income funds and commercial papers are considered the liabilities of shadow banks. The study is based on the hypothesis that substitutability or complementarity between bank services and shadow banks is a critical factor in the effectiveness of monetary policies. An explanatory framework was developed to examine whether the relationship between traditional banking services and shadow banking in Iran is complementary or substitutive.2.Materials and MethodsTo model the money demand function, the study used the Minflex Laurent flexible functional form within a dual approach encompassing both conventional and shadow banking, as well as demand systems proposed by Diewert (1974). Additionally, Barnett’s (2002) approach was employed to ensure the systematicity conditions of classical models, namely monotonicity, curvature, and positivity. The BEKK–GARCH model was used to address heteroscedasticity and estimate the model. MATLAB R2018b, Eviews11, and WinRATS10 were used estimate the theoretical models of the study.3.Results and DiscussionThe Morishima elasticity of substitution between different components of money demand showed that despite fluctuations in the level of elasticity, the elasticity of all components is less than one. Furthermore, since all elasticities are positive, the components act as substitutes for each other. Among the examined elasticities, the highest average substitution occurred with Islamic securities compared to changes in fixed-income funds, while the lowest substitution occurred with fixed-income funds compared to changes in cash. In addition, investigating the response to shocks in each component of money demand revealed several points. First, the reaction of assets to demand shock fluctuations was initially positive for cash, although for Islamic securities, this effect decreased after three periods or months. The reaction of cash fluctuations to cash shock was significantly greater and increased for all assets. Second, the reaction of each asset to short-term deposit shocks was positive but small, except for the case of cash in which it was slightly negative in the first and second periods. This reaction increased during subsequent periods in the case of short-term deposits themselves. Third, concerning the fixed-income fund shock, although it was negative in the first period, it became positive in subsequent periods. The shock related to Islamic bonds and short-term deposits maintained a stable positive trend, and shocks from fixed-income funds increased for three periods but had a decreasing but positive trend thereafter. Fourth, investigating the reaction of fluctuations to shocks in Islamic securities showed that-except for cash which had a positive increasing trend-the trend for the other three assets initially increased and then decreased.4.ConclusionThe results indicate that the demand for shadow banking services has gradually increased in Iran, aligning with global economic trends and the advantages shadow banks offer over conventional banks. Although shadow banks in Iran are perceived as competitors to conventional banks, studies show that the limitations imposed by unilateral policies in Iran’s monetary market have led many shadow banking activities to be conducted by institutions related to conventional banking. In fact, utilizing shadow banking capacities has helped establish stability in Iran’s conventional banking system. This finding aligns with the results of the Financial Stability Board (2013) and the related studies (Liu & Xie, 2020; Moshirian, 2014). According to these studies, many shadow banking services by conventional banks are carried out to bypass central bank regulations. Moreover, the findings of the present study on the substitution between conventional and shadow banking are consistent with the findings of Serletis and Zhou (2019), as contrasted to Lin and Li (2017), Górnicka (2016), and Noeth and Sengupta (2011), who view conventional and shadow banking as two complementary systems.
Research Paper
Financial Economics
Soheil Rudari; Ali Mohammad Ahmadi; Vahid Omidi
Abstract
One of the primary concerns of the Iranian National Pension Fund is managing its investment portfolio. In this respect, the present study aimed to examine the long-term investment portfolio, the largest subset of which is V-sandoq. The analysis used the R2 connectedness approach proposed by Naeem et ...
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One of the primary concerns of the Iranian National Pension Fund is managing its investment portfolio. In this respect, the present study aimed to examine the long-term investment portfolio, the largest subset of which is V-sandoq. The analysis used the R2 connectedness approach proposed by Naeem et al. (2023) over the period from September 17, 2013, to September 22, 2023. The study focused on the immediate influence and susceptibility to influence of the stocks within the National Pension Fund. The results showed that, in terms of net influence and susceptibility, the stocks of Group 1 (i.e., Kechad, Foulad, Kegol, and Sheranol) were the most influential, transferring risk to the network. Conversely, the stocks of Group 2 (i.e., Shepas, Pasa, Shekabir, and Vebshahr) were the most influenced by the network. Therefore, risk is transferred from Group 1 stocks to the network, impacting Group 2 stocks the most. In network analysis, during a bear market with a threshold of -4%, there is a high degree of connectivity among the stocks in the portfolio. This suggests that portfolio adjustments are necessary under bear market conditions. Conversely, in a bull market with a threshold of +4%, there is no connectivity between the stocks, indicating that no portfolio adjustments are needed under such conditions.1.IntroductionIn recent years, Iran has consistently faced challenges with pension funds and the inability to generate adequate income to pay retirement salaries. With the number of retirees expected to increase in the coming years (particularly from the 1980s generation), effective management of the investment portfolio of the National Pension Fund’s subsidiaries has become increasingly critical. Many state-owned companies were transferred to the National Pension Fund to finance retired pay from their profitability. However, budget evidence indicates that over 80% of retirement salaries are still financed through the government budget. This underscores the importance and necessity of revising the investment portfolio of the National Pension Fund’s investment holdings. In this respect, the present study aimed to examine the portfolio management of one of the largest subsidiaries of the National Pension Fund, namely the Investment Company of the National Pension Fund or V-sandoq, over the period from September 17, 2013, to September 22, 2023. The study used the vector autoregression (VAR) model with time-varying parameters and R2 connectedness, as an immediate response, proposed by Naeem et al. (2023). The immediate impact analysis of variables on/from each other was chosen because any national, regional, or global event has immediate effects, and providing an appropriate response in portfolio management is of great importance.2.Materials and MethodsThe study employed the TVP-VAR algorithm and the Kalman filter introduced by Antonakakis et al. (2020), in conjunction with the approach proposed by Naeem et al. (2023). The key econometric structure of the TVP-VAR model is outlined below. For the sake of simplicity, it is presented in the form of a first-order VAR. Thus, the TVP-VAR model is as follows:(1) (2) Time-varying parameters and time-varying error variances are essential components for the generalized impulse response functions (GIRF) and generalized forecast error variance decomposition (GFEVD) developed by Koop et al. (1996) and Pesaran and Shin (1998). These components underpin the connectivity approach of Diebold and Yılmaz (2012, 2014). To obtain GIRF and GFEVD, the TVP-VAR needs to be converted to TVP-VMA by applying the Wold representation theorem. According to this theorem, GIRFs i j,t (K) at a forecast horizon K do not assume or depend on the ordering of shocks, providing a more robust interpretation of VAR models compared to standard IRFs, which are sensitive to the order of variables in the econometric system. The GIRF approach reflects the dynamic differences between all variables jjj. Mathematically, it can be expressed as Equation (3):(3) (4) Subsequently, GFEVD ψij,t(K)\psi_{ij,t} (K)ψij,t(K) represents the unique contribution of each variable to the forecast error variance of variable iii, interpreted as the percentage impact of one variable on the forecast error variance of another variable. This can be expressed as Equation (5):(5) The criteria for GIRF and GFEVD can help determine how much variable iii is influenced by others and how much it influences others. Three metrics are used for this purpose.First, we must determine how much other variables in the system influence variable iii. This is obtained by summing the error variance shares for variable iii relative to variable jjj. The influence from others is then calculated using Equation (6):(6) Second, the impact of variable iii on others in the system is calculated through the measurement known as influence on others. This measurement is derived by summing the effects (error variance) that variable iii imposes on the forecast error variance of other variables:(7) The total connectivity index (TCI) is calculated based on the Monte Carlo simulations presented by Chatzanzinou et al. (2021). It demonstrates that the self-variance share consistently exceeds or equals all cross-variance shares. Since the average co-movement of the network is expressed as a percentage, which should be between [0,1], TCI needs to be slightly adjusted:(8) Finally, the TCI definition is modified to obtain pairwise partial connectivity index (PCI) scores between variables iii and jjj as follows:(9) 3.Results and DiscussionFigure 2 illustrates the temporal dynamics of stock influences received from other stocks. It shows the extent to which each stock has transferred or received risk from others. The stocks above the zero line indicate a net influence on the network, while those below indicate a net reception from the network during the examined period. Notably, Kechad, Foulad, Kegol, and Sheranol (Group 1) predominantly acted as influencers, transferring risk to the network. In contrast, Shepas, Pasa, Shekabir, and Vabshahr (Group 2) exhibited the highest reception from the network. Therefore, it can be inferred that external shocks transfer risk from Group 1 to the network, notably impacting the stocks in Group 2.It is crucial to recognize that this influence/reception patterns vary over time and exhibit significant fluctuations. Specifically, the chart shows that the influence/reception of stocks on/from the network decreased with the outbreak of the COVID–19 pandemic from January 19, 2021. Conversely, the disclosure of the letter regarding the increase in petrochemical feed rates on May 7, 2023 heightened the risk transfer from petrochemical stocks to the studied network. This underscores that external shocks do not uniformly affect the portfolio under review, necessitating separate examination of each. Figure1: Net Influence/Reception of Stocks on/from Each Other Source: Research findings4.ConclusionThe results of the long-term portfolio analysis indicated varying levels of interconnectedness influenced by economic, political, military, and health conditions—with the connectivity averaging around 45%. This reflects a high risk for the long-term portfolio. In terms of net influence and reception, Kechad, Foulad, Kegol, and Sheranol (Group 1) generally exerted influence by transferring risk to the network. In contrast, Shepas, Pasa, Shekabir, and Vabshahr (Group 2) predominantly received risk from the network. Thus, during external shocks, risk tends to shift away from Group 1 stocks, thus impacting Group 2 significantly. The outbreak of the COVID–19 pandemic on January 19, 2021 led to a decrease in the influence/reception of stocks on or from the network. Conversely, the disclosure of an increase in petrochemical feed rates on May 7, 2023 heightened risk transfer from petrochemical stocks to the studied network. Concerning the network analysis, there is a high degree of connectivity among the stocks in the portfolio during a bear market with a threshold of -4%. This suggests that portfolio adjustments are necessary under bear market conditions. In bearish markets, it thus becomes imperative to select stocks that have less connectivity. On the contrary, in a bull market with a threshold of +4%, there is no connectivity between the stocks, indicating that no portfolio adjustments are needed under such conditions. Hence, while the examined portfolio is optimal during bull markets, adjustments are essential during bear markets to mitigate risks associated with high connectivity.
Research Paper
Political economy
Alireza Raanaei; Rouhollah Shahnazi; Seyyed Aqil Hoseiny
Abstract
The history of modern Iran is marked by numerous movements and revolutions, primarily aimed at achieving a proper balance between the state and society. Despite significant efforts, Iranians have not yet reached the ideal equilibrium. This research aimed to provide a brief overview of modern Iranian ...
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The history of modern Iran is marked by numerous movements and revolutions, primarily aimed at achieving a proper balance between the state and society. Despite significant efforts, Iranians have not yet reached the ideal equilibrium. This research aimed to provide a brief overview of modern Iranian history and examine the pathways of progress for both the state and society. Utilizing an institutional analysis framework and the concept of institutional congruity, the study developed a new analytical framework to analyze the state–society interaction in Iran. A game theory approach was then used to examine various scenarios of the state–society interaction. The findings revealed that the depreciation, economy of scale, and instability of preferences are crucial factors in the dynamics between the state and society. However, the rate of time preference emerged as the most decisive factor, leading to three possible equilibriums: democracy, despotic Leviathan, and absent Leviathan.1.IntroductionAccording to Hegel, Iranians were historically the first people to establish a state, with their continuous history beginning with their empire (Hegel, 2004, p. 191). This continuous history narrates the dialectic between the state and society in Iran. The dynamics of this interaction can result in a stable equilibrium, an unstable equilibrium, or a fundamental disequilibrium. Given the unique nature of Iran, is it possible to achieve a balanced relationship where societal demands are met, and the state could provide ideal governance? How can we conceptualize the successive transformations and instability in the state–society interaction in contemporary Iran? Why did the Constitutional Revolution lead to Reza Khan’s dictatorship? Why did the secularization under Pahlavi II lead to the Islamic Revolution? How can we interpret this history of highs, lows, and turbulence? To address these issues, the present study aimed to explain the contemporary interaction between the state and society in Iran by using the institutional congruity framework and game theory. The goal was to present various possible equilibriums for Iran’s contemporary political economy. In other words, the research sought to elucidate the potential balance of the political economy in Iran based on the state–society interaction.2.Materials and MethodsIn the institutional balance between the state and society, a dynamic interplay is unfolding. Building on the model proposed by Acemoglu and Robinson (2023), this study attempted to derive various possible scenarios of the state–society interaction in Iran. Time is represented discretely, with the length of each period denoted as Δ>0. At time t, the variables from the previous period are as follows: where x represents the capacity of society, and s represents the capacity of state. At each point, society and the state are represented by a player. At any time, players simultaneously choose their investments , which determines their current capacity according to the following equations: For both the short-term state and society, various scenarios can be formulated regarding the presence or absence of depreciation and the oscillating nature of their inclinations. Consider the cost function for two players as follows: and 3.Results and DiscussionThe results suggest that beginning with low capacities for both the state and society can lead to a trajectory where a society starting with a weak state might directly evolve into one moving toward either a despotic Leviathan or an absent Leviathan. This dynamic is illustrated in the following phase diagram:Figure 1: First Scenario: The Short-Term Society In this scenario, it is evident that without depreciation, there is significant potential for Iranians to advance within a narrow corridor. However, as depreciation increases, this potential diminishes, eventually leading to a state of collapse (0, 0). Figure 2: Second Scenario: The Short-Term Society with Unstable Preferences The transformations in modern Iranian history show varying dynamics in both society and the state across different periods, reflecting differences in their types and levels of societal participation and efforts to achieve their respective goals. The high dynamics demonstrate that in a short-term scenario-assuming a depreciation rate of 0.1-if society is active (while the state is not), the predominant state tends towards anarchy. In the opposite scenario, the predominant state shifts towards a despotic Leviathan.Figure 3: Third Scenario: The Short-Term State The results of this scenario mirror those of the first scenario, highlighting the significant impact of depreciation on future possibilities. In contrast, the possibilities lean more towards a despotic Leviathan, whereas in the first scenario, the tendencies for a short-term society leaned more towards anarchy. Figure 4: The Short-Term State with Unstable Preferences In this scenario, similar to the second one, it is apparent that the efforts and engagement of both society and the state must be parallel and substantially proportional to each other. If either entity remains passive, the situation tends towards either pure despotism or anarchy.When it comes to time preference rates, it is crucial to consider the long-term, forward-looking perspectives of both the state and society. In the first scenario, the state is short-term and active with . Being active implies significant investment in the state capacity accumulation. In the second scenario, the state remains short-term and active with . These two situations were examined under two conditions: and .Figure 5: The Role of Time Preference in the Long-Run Equilibria of Iran’s Political Economy The above phase diagram effectively illustrates the significance of time preferences and their causal precedence in determining the state of the Leviathan in Iran. Even with depreciation and the short-term nature of both society and the state, achieving a stable equilibrium state (narrow corridor) is feasible when time preferences are appropriately aligned. Otherwise, depending on the short-term nature of either society or the state, the expected outcome will tend towards despotism or pure anarchy.4.ConclusionIn Iran, both society and the state must adopt a long-term rationality based on historical self-awareness to progress harmoniously. The primary challenges faced by Iranian society and the state stem from their short-term outlooks, as reflected in their time preferences. Whether society or the state prioritizes short-term goals, it becomes evident that depreciation significantly limits the possibility to enter the narrow corridor of stability. When both the state and society fail to coordinate efforts— whether in the short-term society or short-term state—it often leads to either pure despotism or anarchy. Despite the depreciation, economies of scale, and instability of preferences, it is the rate of time preferences that ultimately determines whether entry into the narrow corridor is feasible. Furthermore, this rate of time preferences dictates whether the equilibrium state leans towards a despotic Leviathan or an absent one, contingent upon the economies of scale achieved by both the state and society.
Research Paper
Economic Development
Sayed Amin Mansouri; Seyed Morteza Afghah; Behrouz Sadeghi Amroabadi; Hassan Farazmand; Yaghoub Andayesh; Ali Boudaghi
Abstract
One of the significant challenges in regional development is examining the role of local governments and their relationship with large local companies in income distribution. This challenge is particularly pertinent when large companies have national objectives, and most of their production capacity ...
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One of the significant challenges in regional development is examining the role of local governments and their relationship with large local companies in income distribution. This challenge is particularly pertinent when large companies have national objectives, and most of their production capacity is capital-intensive and knowledge-intensive, but their operational area is locally focused on the user. The present research aimed to explore the role of the government and large local companies in income distribution. Khuzestan Province was chosen due to its unique characteristics in this regard. The study covered the period from 2006 to 2020, analyzing seasonal data using the generalized method of moments (GMM). The findings indicate that the government’s current and construction expenditures in the province have a negative and significant effect on the urban Gini coefficient. In contrast, the value-added variable of large industrial companies in the province has a positive and significant effect on the urban Gini coefficient. The results suggest that careful planning and coordination between large companies and provincial managers should be sought by adopting policies such as increasing local employment and training local workforce, thereby reducing dissatisfaction and income inequality in the province.IntroductionOne of the significant challenges in regional development is examining the role of local governments and their relationship with large local companies in income distribution. This challenge is particularly pertinent when large companies have national objectives, and most of their production capacity is capital-intensive and knowledge-intensive, but their operational area is locally focused on the user. Based on the available evidence, large companies in Khuzestan Province (e.g., oil, petrochemical, and steel companies), which are part of national entities, generate national income. However, the local population’s share of this income is small. Meanwhile, private companies in Khuzestan Province are under pressure to pay taxes. This has led to the perception among the people in the province that the presence of these national entities has resulted in a low local share of their income. In other words, the income generated by these companies flows out of the province, leaving the local population with a minimal share. In this respect, the present research aimed to explore the role of the government and large local companies in income distribution in Khuzestan Province during 2006–2020. Materials and MethodsThe primary research question is whether the government’s financial policies and the presence of large companies in Khuzestan Province significantly affect income distribution within the province. Using the generalized method of moments (GMM), the study relied on the seasonal data from 2006 to 2020 to address the research question. Results and DiscussionThe results indicate that government’s current and construction expenditures in the province have a negative and significant effect on the urban Gini coefficient. Conversely, the value-added variable of large industrial companies in the province has a positive and significant effect on the urban Gini coefficient. This suggests that the presence of large industrial companies has not only failed to reduce inequality but actually increased urban inequality in the province. The findings also show that both types of user investment and Berber knowledge are effective in reducing the urban Gini coefficient in Khuzestan Province. Additionally, the study found that air pollution in the province has a positive and significant effect on the urban Gini coefficient. This implies that increased pollution, caused by industrial activities, disproportionately impacts the lower classes as the benefits of these activities do not reach the lower-income population. Instead, these polluting industries impose negative external effects on the local population while contributing to increased inequality by introducing imbalances considering payments to national production factors. ConclusionAccording to the research results, the presence of large companies in the province has neither generated local benefits nor reduced income inequality in the urban sector. It is thus recommended that careful planning and coordination between large companies and provincial managers should be sought by adopting policies such as increasing local employment and training local workforce, thereby reducing dissatisfaction and income inequality in the province.AcknowledgementsWe express our gratitude to the Vice-Chancellor for Research Affairs of Shahid Chamran University of Ahvaz for his assistance in conducting this research.Conflict of interestThe authors declare no conflict of interest in publishing this articleFundingThis study is part of a research project related to industry between Shahid Chamran University of Ahvaz and the Management and Planning Organization of Khuzestan Province, financially supported by contract number 100z1310004 (971875).
Research Paper
Monetary economy
Sosan Etemadinia; Kiumars Shahbazi; Khadijeh Hassanzadeh
Abstract
Financial instability causes uncertainty and a lack of transparency in the market and decision-making processes, ultimately leading to reduced investment and economic growth. Additionally, economic shocks alter investors’ expectations. This study relied on the seasonal data from 1991/3 to 2021/6 ...
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Financial instability causes uncertainty and a lack of transparency in the market and decision-making processes, ultimately leading to reduced investment and economic growth. Additionally, economic shocks alter investors’ expectations. This study relied on the seasonal data from 1991/3 to 2021/6 in order to identify financial shocks and their impact on macroeconomic variables such GDP, the debt-to-GDP ratio, and financial instability. The Threshold Vector Autoregression (TVAR) model was used to analyze the data. The findings showed that fiscal policies (debt-to-GDP ratio) reduce GDP. Second, positive shocks from financial instability lead to a decrease in GDP and the debt-to-GDP ratio. In the first regime, positive fiscal policy shocks (increase in the debt-to-GDP ratio) leads to an increase in financial instability, while in the second regime, positive fiscal policy shocks can reduce financial instability.IntroductionFinancial instability leads to uncertainty and a lack of transparency in the market and decision-making processes, ultimately resulting in reduced investment and economic growth. Economic shocks also alter investors’ expectations, affecting the value of current assets and influencing both the financial and real sectors. During periods of financial instability, government debt management needs to adopt specific strategies. The simultaneous occurrence of a financial crisis and an economic recession signals a major downturn, and historical evidence shows a relative correlation between economic recessions and heightened financial market instability. In times of increased financial instability, the share of overdue loans rises, and negative market sentiments reduce the value of other financial assets. Disruptions in financial markets or a high level of overdue loans on banks’ balance sheets can lead to an economic recession by restricting credit flows to other sectors. Countercyclical fiscal policy can mitigate the reduction in the private sector demand by increasing government spending or cutting taxes, thereby compensating for the diminished credit flows from a weakened financial sector. Furthermore, government spending dependent on financial aid in weak sectors can improve economic sentiments and expectations, helping to strengthen the economy. However, financial development that facilitates easy access to existing financial resources can increase financial instability due to concerns about government debt sustainability. In this respect, the present study aimed to examine the nonlinear relationship (the effects of positive and negative shocks) between financial market instability, fiscal policy, and the production sector in Iran.Materials and MethodsThis study relied on using the seasonal data from 1991/3 to 2021/6 in order to examine the relationship between financial market instability, fiscal policy, and production in Iran. The Threshold Vector Autoregression (TVAR) model was used for the analysis. The primary version of the model used in this study is as follows:yt=[LGDPt,FSIt, DFt, LCPIt, LM2t]Due to its nonlinearity, the TVAR model can capture the varying magnitudes and directions of shocks that can affect how variables impact each other. Unlike the linear VAR model, where the impact of a negative shock is merely the opposite of a positive shock, the TVAR model allows for asymmetrical effects, where shocks of different sizes and directions can yield different outcomes. Results and DiscussionAccording to the findings, fiscal policies (debt-to-GDP ratio) decrease GDP, and positive shocks from financial instability lead to a decrease in both GDP and the debt-to-GDP ratio. Moreover, a positive shock in fiscal policy (increase in the debt-to-GDP ratio) increases financial instability in the first regime, but reduces it in the second regime. Also, negative shocks have opposite effects in both regimes. This suggests that in strong regimes with high liquidity, the debt-to-GDP ratio is lower, thus reducing the risk of instability. However, when fiscal policies such as tax cuts and increased government spending are pursued in a strong economy, financial instability may increase partly due to higher tax revenue and increased government spending; however, these policies are less profitable. In weak, low-cash regimes with unsustainable and income-dependent economies, the debt-to-GDP ratio is higher, leading to greater instability. Nonetheless, appropriate fiscal policies can prevent financial instability even in weaker regimes, promoting significant economic growth without increasing the risk of financial instability. The estimated TVAR model indicates nonlinear effects in the response of variables to exogenous shocks. Based on threshold effect tests in the first model (production response), the optimal threshold value (liquidity difference) is 0.4794. Periods where the threshold variable is less than 0.4794 are categorized as low regime, while other periods are categorized as high regime. In both regimes, a positive financial instability shock reduces fiscal policy (debt-to-GDP ratio). In the first regime, a positive fiscal policy shock (increase in the debt-to-GDP ratio) increases financial instability, while in the second regime, it reduces financial instability.ConclusionThe present study employed the TVAR model and the seasonal data from 1991 to 2021 in order to examine the relationship between financial market instability, fiscal policy, and production in Iran. Unlike the linear VAR model where effects of negative and positive shocks are symmetrical, the nonlinearity of the TVAR model shows that the size and direction of shocks impact how variables interact, thus leading to different outcomes. The findings revealed a nonlinear response of variables to incoming shocks. The TVAR model results, based on threshold effect tests in the first model (production response), identified an optimal threshold value of 0.04794. Periods below this threshold are categorized as low regime. The instantaneous response functions indicated that positive shocks in financial instability negatively impact GDP in both regimes. Generally, financial instability causes market uncertainty and a lack of transparency, leading to reduced investment and decreased economic growth. Additionally, positive shocks of fiscal policies (e.g., the debt-to-GDP ratio) decrease GDP in both regimes. The instantaneous reaction functions showed that a positive shock in financial instability reduces fiscal policy in both regimes. According to the results, a positive shock in fiscal policy increases financial instability in the first regime, while it decreases financial instability in the second regime.
