Shahryar Zaroki; Ahmadreza Ahmadi
Abstract
Crude oil and the rents derived from it can present both advantages and disadvantages for oil-rich countries. Numerous studies have examined the impact of oil rents on various variables such as economic growth, inflation, and financial development. Among these, the potential role of oil rents in ...
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Crude oil and the rents derived from it can present both advantages and disadvantages for oil-rich countries. Numerous studies have examined the impact of oil rents on various variables such as economic growth, inflation, and financial development. Among these, the potential role of oil rents in income inequality, particularly in light of the underground economy, appears to have been overlooked in previous domestic studies. To address this gap, the present research first calculates the relative size of the underground economy using a MIMIC method, revealing an average of 16.8% in Iran’s economy. Subsequently, employing a nonlinear autoregressive distributed lag (NARDL) approach, the study investigates and tests the effect of oil rents on income inequality while considering the underground economy over the period from 1978 to 2022. The long-run results indicate that positive shocks in oil rents are associated with a desirable (negative) effect on income inequality, while negative shocks lead to an undesirable (positive) effect. Furthermore, the underground economy acts as a double-edged sword; that is to say, an increase in the relative size of the underground economy has the potential to turn the favorable (negative) impact of positive oil rent shocks on income inequality into an unfavorable one, and conversely, it can transform the unfavorable (positive) impact of negative oil rent shocks on income inequality into a favorable one. Additionally, real GDP per capita exhibits an inverse U-shaped relationship with income inequality, while unemployment positively influences income inequality.
Introduction
A country’s progress toward social justice can be quantitatively assessed through indicators such as income distribution, poverty, and welfare. In recent years, rising concerns over income inequality have expanded the discourse on how natural resource rents—particularly oil revenues—shape economic growth and development. While resource abundance is often perceived as a blessing, its effects on economic development have been uneven and, at times, contradictory.
Since the 1973 oil shock, Iran’s economic performance has been closely tied to its natural resource wealth. Moreover, a historical review of oil price trends reveals significant volatility, making it an unreliable source for financing national expenditures. According to theoretical foundations, natural resource rents should enhance the economic and social welfare of local communities. Ross (2007) notes that surprisingly little information exists about the relationship between natural resources and income inequality. However, it appears that resource-rich countries are, on average, neither more nor less unequal. Countries with abundant natural resources are often considered fortunate because these resources are valuable capital that can be transformed into essential infrastructure, fostering economic development and progress. Among natural resources, mineral resources—particularly hydrocarbons such as oil and gas—hold exceptional importance.
The underground economy further complicates this relationship. As a parallel economic sector often linked to oil dependence, it diverts financial flows from formal oversight, undermining equitable wealth distribution. This not only deepens inequality but also erodes institutional quality and discourages human capital investment. In effect, overreliance on oil rents traps economies in cycles of distorted specialization and sluggish growth, perpetuating disparities.
Despite these dynamics, few studies have examined the asymmetric effects of oil rents on income inequality or the mediating role of the underground economy—a critical gap this study addresses. Focusing on Iran (1978–2022), we investigate two central questions: First, does oil rent have an asymmetric effect on income inequality? Second, does the size of the underground economy influence how oil rent affects income inequality, and if so, how?
Methods and Material
First, the relative size of the underground economy is calculated using the MIMIC method. The structural equation model illustrates the relationship between the unobservable latent variable and observed indicators and causes. This model is widely used in various social sciences and economics. The MIMIC model consists of two main components: a structural equation and a measurement equation. As mentioned in the introduction, the primary objective of this study is to analyze and examine the asymmetric effect of oil rents on income inequality, with a focus on the role of the relative size of the underground economy in Iran. Therefore, the research model is designed to investigate and explain how increases and decreases in oil rents impact income inequality, emphasizing the relative size of the underground economy. To elaborate further, the reason for employing an asymmetric model lies in the limitations of symmetric or linear models, where the absolute magnitude of the independent variable's effect during an upward trend is assumed to be identical to its effect during a downward trend. In other words, in a symmetric estimation of oil rents impact on income inequality, it is conventionally interpreted that if an increase in oil rents leads to a rise (or fall) in income inequality by units, then simultaneously, a decrease in oil rents would result in a reduction (or increase) in income inequality by units. However, what occurs in reality may differ, as the effect of increasing oil rents on income inequality might not be identical to that of decreasing oil rents. In other words, in Iran’s economy, it is expected that income inequality will respond differently to increases in oil rents compared to decreases. Considering the explanations provided, as well as the potential delay in the impact of explanatory variables on income inequality and the influence of other variables affecting income inequality, a nonlinear autoregressive distributed lag (NARDL) approach is utilized. The asymmetric model specification is based on the study by Shin et al. (2014), which addresses the asymmetry in the coefficient of an influencing factor on the dependent variable under conditions of boom and recession. Drawing insights from the work of Pesaran et al. (2001), they define a model referred to as the nonlinear autoregressive distributed lag (NARDL) model.
Results and Discussion
The findings of the study, based on the estimation of the research model in the long run, indicate that:
Firstly, positive shocks (increases) in oil rent have a favorable (negative) effect, while negative shocks (decreases) in oil rent have an unfavorable (positive) effect on income inequality. The difference in the magnitude of the impacts of positive and negative shocks highlights the asymmetric effect of oil rent on income inequality. Secondly, the favorable impact of increases in oil rent on income inequality diminishes as the size of the underground economy grows.
Thirdly, the unfavorable impact of decreases in oil rent also weakens when the size of the underground economy increases. In a general summary and more detailed explanation, it can be stated that the underground economy acts as a double-edged sword in the relationship between oil rent and income inequality. Specifically, an increase in the size of the underground economy from 12.43% during increases in oil rent and 14.93% during decreases in oil rent makes the favorable (negative) impact of positive shocks in oil rent on income inequality unfavorable and turns the unfavorable (positive) impact of negative shocks in oil rent on income inequality into a favorable one. The inverse relationship between increases in oil rent and income inequality in Iran can be explained through channels such as increased government consumption expenditures, transfer payments and subsidies to lower-income deciles, and improved human development for the poor via government social spending. Furthermore, the results from the research model indicate that when disregarding the size of the underground economy, the favorable impact of increases in oil rent is less significant than the unfavorable impact of decreases in oil rent on income inequality, which confirms the presence of asymmetry in effects. Other findings show that real GDP per capita has an inverted U-shaped effect on income inequality, while unemployment has a positive effect on it.
Conclusion
Given the findings of this study, it must be acknowledged that oil rents are an unreliable resource. Therefore, adopting policies to reduce the country’s budgetary dependence on rents derived from natural resources, including oil, is essential. Additionally, it should be emphasized that to maximize the favorable impact of oil rents on income inequality during positive shocks, policymakers must account for the relative size of the underground economy and implement measures to reduce its scale (e.g., streamlining government regulations and bureaucratic hurdles for formal business entry, reducing trade restrictions, fostering formal-sector employment through prudent management of oil revenues, etc.). Furthermore, since the adverse effect of oil rent declines—which lies beyond the managerial capacity of oil-producing countries (assuming the underground economy’s size is disregarded)—exceeds the favorable effect of oil rent increases, establishing a foreign exchange reserve or national development fund is imperative.
Esfandiar Jahangard; Mohammad Ghasemi Sheshdeh; Teymour Mohammadi; Farbod Jozani Kohan
Abstract
This study uses a three-period overlapping generations (OLG) model to investigate human capital productivity's impact on Iran's economic growth. The central question addresses how intergenerational transfers influence the productivity of human resources and, consequently, overall economic growth. ...
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This study uses a three-period overlapping generations (OLG) model to investigate human capital productivity's impact on Iran's economic growth. The central question addresses how intergenerational transfers influence the productivity of human resources and, consequently, overall economic growth. Employing an analytical-quantitative approach, the study uses seasonal data from 1991 to 2021. The model is estimated within a Dynamic Stochastic General Equilibrium (DSGE) framework. By integrating data from national accounts and household budgets, the study derives productivity levels of human resources across generations. The findings reveal that intra-family transfers related to consumption, education, and healthcare significantly enhance productivity. Moreover, the age group 25 to 64 years shows the strongest impact on economic growth, which is consistent with the life-cycle hypothesis as formulated by Ando and Modigliani, as well as the theoretical perspective provided by the National Transfer Accounts (NTA) framework.
Introduction
The relationship between demographic dynamics and macroeconomic outcomes has become an increasingly important topic in economic research. Among the various mechanisms connecting these domains, the role of intergenerational transfers in shaping human capital productivity is especially significant. This study focuses on the Iranian context, where a shift in population structure, along with institutional and fiscal challenges, has made the efficient use of human capital a key policy priority.
The central aim of this research is to assess intergenerational productivity through the lens of the National Transfer Accounts (NTA) framework. This approach allows for the quantification of how resources are allocated across age groups, highlighting differences in consumption, education, and healthcare. By identifying the age-specific patterns of resource use and output contribution, the study seeks to provide an empirical basis for measuring productivity across generations.
Furthermore, to understand how productivity responds to macroeconomic fluctuations, the study incorporates a Dynamic Stochastic General Equilibrium (DSGE) model tailored to Iran’s economy. The model integrates shocks in key areas such as household consumption, educational investment, and health expenditures, and tracks their effects across different generational cohorts. Through this dual-layered approach—linking micro-level intergenerational data with macro-level modeling—the research aims to answer a critical question: Which generation is most responsive to shocks in ways that affect human capital productivity?
Ultimately, the study provides not only a diagnostic tool for evaluating demographic-economic interactions but also a foundation for designing more targeted and effective policy interventions that consider the dynamic interplay between age structure, resource allocation, and economic growth.
Methods and Material
This study employs a hybrid modeling framework that combines National Transfer Accounts (NTA), the Overlapping Generations (OLG) model, and a Dynamic Stochastic General Equilibrium (DSGE) structure to assess the intergenerational dynamics of human capital productivity in Iran. The research integrates demographic structure with macroeconomic modeling to trace the effects of economic shocks on various age cohorts in terms of their productivity levels.
The OLG model used in this study features a three-period structure consisting of youth (15–24 years), working-age adults (25–64 years), and the elderly (65 years and older). This categorization aligns with the age classification defined in the NTA framework. Each cohort is subdivided by skill level, which determines their human capital endowments. Individuals enter the model at the age of 15 and progress through the stages of life, contributing to or benefiting from the economy through consumption, education, healthcare, and labor productivity.
To operationalize the model, we derive age-specific indicators for consumption, education, and health expenditures from household budget survey data. These micro-level estimates are then scaled using aggregate national account data to compute public and private intergenerational transfers. For example, to determine the public health transfer received by each age group, the proportional share of health-related household spending is multiplied by total government health expenditure. A similar technique is used to calculate age-disaggregated values for other transfer categories such as education and consumption.
The DSGE model is calibrated using quarterly macroeconomic data from 1991 to 2021. This framework enables us to incorporate random shocks to productivity, consumption, and fiscal policy, allowing for an analysis of the short- and long-term effects of these disturbances across different generations. The model builds upon the microfoundations of rational expectations and utility maximization, and follows the tradition established by Kydland and Prescott (1982), Clarida et al. (2002), and Smets and Wouters (2003). Technological shocks are modeled as a primary source of uncertainty, in line with the Real Business Cycle (RBC) literature.
Despite some limitations—such as the complexity of infinite-horizon modeling and the challenge of solving nonlinear systems—DSGE models remain the gold standard for macroeconomic policy simulation. This study utilizes a finite-horizon version of the model to capture the productivity responses of distinct age cohorts to economic shocks. By integrating NTA data into a DSGE structure, the research bridges microeconomic resource allocation with macroeconomic performance. It further distinguishes itself by evaluating how generational productivity changes in response to policy-driven and exogenous shocks, providing a novel analytical tool for demographic-economic research.
Results and Discussion
Although the calibration techniques of microeconomic and macroeconomic models slightly differ, the general approach in economic literature includes four key steps: selecting the model, defining the calibration objective, specifying the functional form, and adopting parameters estimated by other researchers or through original estimation. Table 2 presents the calibrated parameters and their estimation methods.
One of the crucial outputs of the Dynare software is the Markov Chain Monte Carlo (MCMC) diagnostic test, which confirms that there is no issue with the model’s parameter estimations and that the estimates are reliable. Dynare performs several Metropolis-Hastings simulations, starting each time from a different initial point. If the chains behave similarly and converge toward one another, the results are considered trustworthy. Dynare provides three diagnostic indices—Interval, m2, and m3—which represent the 80% confidence interval, variance, and third moment of the parameters, respectively. These are visualized in multivariate diagnostic plots, illustrating the eigenvalue-based diagnostics of the variance-covariance matrix for each parameter. These charts provide evidence of convergence and stability across all parameter moments. The x-axis in each chart shows the number of Metropolis-Hastings iterations, and the y-axis indicates the parameter moments. A lack of similarity across plots suggests incorrect priors and may warrant re-estimation or more iterations.
As shown in Figure 8, the curves converge toward each other, indicating a good model fit.
Table 1. Calibrated Parameters
Parameter Name
Symbol
Prior Distribution
Posterior Distribution
Distribution Type
Time Preference Rate
γ
0.968
0.967
Gamma
Labor Force Growth Rate
β
0.035
0.04
Beta
Social Security Tax Rate
γ
0.32
0.35
Gamma
Intertemporal Substitution Elasticity
γ
0.92
0.95
Gamma
Intra-period Substitution Elasticity
γ
0.79
0.81
Gamma
Leisure Preference Rate (Age 1–30)
γ
0.29
0.31
Gamma
Leisure Preference Rate (Age 31–55)
γ
1
1
Gamma
Productivity Growth Rate
β
0.015
0.02
Beta
Capital Share in Production
γ
0.53
0.61
Gamma
Private Household Consumption Transfer Rate
β
0.34
0.32
Beta
Private Household Health Transfer Rate
γ
0.18
0.19
Gamma
Private Household Education Transfer Rate
β
0.24
0.23
Beta
Public Consumption Transfer Rate
γ
0.29
0.28
Gamma
Public Health Transfer Rate
γ
0.37
0.38
Gamma
Public Education Transfer Rate
γ
0.44
0.39
Gamma
Source: Research Study
The dynamic behavior of economic growth variables in response to various shocks was examined using impulse response functions. Table 3 summarizes how different generational cohorts respond to intergenerational transfers in key domains—household consumption, education, and healthcare, as well as public transfers.
Overall, results indicate that household-based transfers are more effective and positively correlated with productivity and economic growth compared to public sector transfers. Households seem to allocate resources intergenerationally in a more optimal way, particularly in the domains of health and consumption. Conversely, public sector allocations often fail to produce the same economic impact, possibly due to inefficiencies in governance, planning limitations, and resource misallocation.
Table 2. Production Response to Various Intergenerational Transfer Shocks
Shock Type
Age 0–24
Age 25–64
Age 65+
All Age Groups
Household Consumption Transfer
Positive impact throughout
Positive impact throughout
Negative impact throughout
Positive impact throughout
Household Health Transfer
Initially negative, then positive
Positive throughout
Positive throughout
Positive throughout
Household Education Transfer
Negative throughout
Positive throughout
Negative throughout
Positive throughout
Public Consumption Transfer
Negative throughout
Positive throughout
Positive throughout
Positive throughout
Public Health Transfer
Initially negative, then positive
Initially negative, then positive
Negative throughout
Positive throughout
Public Education Transfer
Negative throughout
Initially negative, then positive
Negative throughout
Positive throughout
The findings suggest that households tend to allocate intergenerational resources more efficiently, leading to higher productivity across most generations. The public sector, in contrast, appears less effective in aligning transfers with economic growth objectives. These discrepancies may be attributed to governance inefficiencies, widespread corruption, and the lack of long-term strategic planning.
Conclusion
National Transfer Accounts (NTA) reflect the quantity and structure of economic flows across age groups and generations. These intergenerational flows are crucial as they embody a fundamental feature present in all societies. The findings of this study highlight that household-based transfers—particularly in consumption, education, and healthcare—are more effective than government-based transfers in enhancing human capital productivity across generations, thereby fostering economic growth.
The results reveal that the age group of 25 to 64 years contributes most significantly to economic growth, consistent with the life-cycle theory as proposed by Ando and Modigliani and further supported by the intergenerational perspective of the NTA framework.
Based on the empirical findings, the following policy recommendations are proposed:
Enhancing Public Transfer Efficiency:Given that public transfers in consumption, education, and healthcare are generally less efficient—especially outside the 25–64 age range—it is recommended that the government allocate resources more effectively in accordance with the productivity levels of different generations. Such alignment could enhance the efficiency of public spending and improve intergenerational productivity outcomes.
Facilitating Private Transfers:Since intergenerational transfers have a positive impact on labor productivity, and household-level transfers outperform public transfers in terms of effectiveness, it is recommended that the government minimize disruptions in private transfers by mechanizing and streamlining the transfer processes between households.
Extending the Demographic Dividen: Considering the relatively limited contribution of the retired population to economic growth and their impact on both the first and second demographic dividends, policies should be designed to delay the depletion of these dividends. Potential strategies include promoting financial literacy in retirement, extending work life in low-intensity occupations, increasing human capital among the elderly, leveraging gender dividends by expanding female labor force participation, and improving consumption and healthcare patterns among retirees. Additionally, long-term strategic foresight in retirement policy is essential.
Harnessing Youth Potential:On one hand, the young, educated population represents a latent advantage for growth and development; on the other hand, labor market limitations hinder their absorption, leading to rising unemployment and reduced youth productivity. Emphasis should be placed on fostering entrepreneurship among youth through legal, educational, and financial support. Encouraging youth-driven innovation, human resource planning, and investment in digital economic sectors—where younger generations demonstrate high adaptability—can help address this challenge.
Aligning with Macro-Level Population Policies:At the macro policy level, these recommendations align with several of the Supreme Leader’s population policy guidelines, especially clauses 6, 8, and 10, which emphasize the importance of leveraging both demographic dividends. These include increasing life expectancy, promoting health and nutrition, empowering the working-age population through vocational and entrepreneurial training, and supporting rural and border populations through investment and job creation. Additionally, prioritizing knowledge-based economic development—consistent with successful global experiences—can enable Iran to fully capitalize on its second demographic dividend for achieving sustainable economic growth.
Acknowledgments
The authors of this article sincerely express their gratitude to the editorial board and the esteemed members of the journal’s editorial team. Their support, attention to detail, and constructive guidance throughout the review and publication process have played a significant role in enhancing the scientific and editorial quality of this work. Undoubtedly, the valuable efforts of this dedicated team in advancing the journal’s academic mission and supporting researchers are worthy of appreciation and recognition.
Maryam Keyghobadi; Elaheh Sadat Akbarnia; Hamidreza Pirmorad; Ashraf Sadat Pasandideh
Abstract
The household sector represents the most significant component of electricity consumption, accounting for the majority of total energy use. In recent years, European nations have increasingly recognized households as key actors in energy governance, demonstrating their critical role in achieving ...
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The household sector represents the most significant component of electricity consumption, accounting for the majority of total energy use. In recent years, European nations have increasingly recognized households as key actors in energy governance, demonstrating their critical role in achieving sustainable consumption patterns. Extensive research has therefore focused on how to encourage more sustainable behavior among individuals.This trend is also relevant to Iran, where the household sector accounts for 50.8% of peak-time electricity demand, making it the most significant contributor to consumption during critical periods. As a result, developing effective behavioral policies and reforming consumption patterns in this sector requires regular, nationally representative research to understand how people behave across different segments of society. Therefore, this study investigates electricity consumption behaviors across household groups stratified by three distinct economical status categories. Through empirical analysis, we identify behavioral variations that inform evidence-based policy recommendations for promoting sustainable energy consumption patterns in Iran's residential sector.
Methods and Material
The statistical population of the current study was citizens over 18 years old across the country. Sampling was done with the online snowball method, and the link of the online questionnaire was distributed through various internet channels such as social networks, e-mail, etc., and 1081 samples were collected. The data analysis was done by SPSS software and the validity, subject, and questions of the research were confirmed by examining the theoretical foundations and choosing the conventional subjects and the approval of experts in the field of energy. The reliability of the consumption behavior variable has been obtained through Cronbach's alpha of 0.69
This energy consumption behavior survey, includes a set of behaviors that are performed by family members in different parts of the house. These behaviors have been examined according to the economical status of the household. The set of properties that are related to electricity consumption at home is considered for measuring the variable of the economical status of the household.
Results and Discussion
The average consumption behavior was 56.4873 and the average economical status was 58.2056. The economical status variable is divided into three ranges of high, medium and low economical status. 33% of the sample population was high, 60% medium and 7% low. Pearson's correlation and ANOVA test were used to investigate the relationship between economical status and behavior. The relationship between the economical status and behavior is -0.132, which indicates the inverse relationship between the two variables, so that as the economical status increases, the consumption behavior worsens. The results of the ANOVA test showed that the average difference in consumption behavior among the three economical statuses (high, medium, and low) has been confirmed, and the consumption behavior in low, medium, and high economical status has obtained a higher average, respectively. Also, the results showed that the best behaviors in the field of lighting were recorded in three groups, and the lighting behavior had the lowest average. The best behavior among the low economical status is cleaning behavior, and among the medium and high economical status is lighting.
Conclusion
The results of this research indicate that behavioral policymaking in the household sector should be based on knowing consumption behaviors and the motivations related to them. Although the policies of increasing prices in a gradual manner (based on consequence models that consider material incentives to be effective on behavior) may increase the revenues from consumption for the Ministry of Energy, it does not necessarily lead to a decrease in consumption. Because firstly, the behavior is related to the habits of the household lifestyle; secondly, with this type of interventions, behaviors are temporarily changed and after some time, consumption increases again. Because these behaviors are not internalized for consumers and they do not feel the need to change their behavior. Especially in inflationary conditions, the effect of the increase in tariffs becomes weaker and weaker.
In general, it is necessary to take into account the high consumption target community in the behavioral policy of the electricity and energy sector. While the recent programs in the country focus most on the less-consuming consumers. Finally, it should be kept in mind that any behavioral policy and consumption pattern modification program should be based on field and national researches; the cultural and climatic differences of different regions should be considered; plans should be tested on a trial and regional basis to identify their strengths and weaknesses and report the results of each national program after implementation and its effects.
Acknowledgments
We gratefully appreciate the assistance of all participants and colleagues who supported the data collection phase of this research.
Reza Taleblou; Parisa Mohajeri; Maedeh Samadi
Abstract
This study employs the Diebold-Yilmaz spillover index within the framework of a time-varying parameter vector autoregressive model (TVP-VAR) to analyze the dynamic connectedness between exchange rates and the Iranian stock market amidst the COVID-19 pandemic. Utilizing daily data spanning from ...
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This study employs the Diebold-Yilmaz spillover index within the framework of a time-varying parameter vector autoregressive model (TVP-VAR) to analyze the dynamic connectedness between exchange rates and the Iranian stock market amidst the COVID-19 pandemic. Utilizing daily data spanning from October 2014 to October 2023, we examine the volatility spillovers between the US dollar and the stock indices of eight industries, including "chemicals", "basic metals", "petroleum products", "extraction of metal ores", "agriculture", "sugar", "cement", and "ceramics". Our findings reveal that systemic risk, represented by total connectedness within the network, averaged approximately 50% before the onset of the COVID-19 pandemic. However, following the emergence of the pandemic, network connections intensified significantly, surpassing 70% at times. The US dollar variable exhibits the highest idiosyncratic risk (75.62%), while the indices of basic metal industries (34.52%) and metal ores (34.59%) demonstrate the lowest idiosyncratic risk. Analysis of the network dynamics indicates that volatility originating from export-oriented commodity industries, particularly basic metals, predominantly influences the US dollar variable, acting as a net transmitter of volatilities to smaller industries, notably ceramics. Moreover, the basic metal industry emerges as the primary transmitter of volatilities within the network, with the agricultural and ceramic industries identified as significant recipients of shocks.
Introduction
Financial asset markets are subject to volatility at one point or another due to domestic or global political, economic, and social events. It is clear that major events such as the COVID-19 pandemic can significantly alter the relationships between markets. In such circumstances, studying the dynamics of correlations and information flows between different assets and markets becomes important and provides investors, policymakers, and portfolio managers with deeper insights. In these circumstances, the two foreign exchange and stock markets react strongly to events and affect the economy. Therefore, this article aims to answer the following questions:
How do the dynamics of dollar rate volatility affect the returns of various stock market industry indices, and how do the dynamics of stock market industry index return volatility affect the dollar? How does the connectedness between the dollar rate and stock market industry indices change in the period before and after the COVID-19 outbreak?
Method
The present study uses a TVP-VAR approach. The method overcomes certain shortcomings of the connectedness criteria of standard VAR models, such as “the arbitrarily chosen rolling window size”, “missing observations”, and “parameters sensitive to outliers”.
Results
An examination of the dynamic spillovers of return volatilities between the exchange rate and the stock index of 8 listed industries, including "chemicals", "basic metals", "petroleum products", "metal ore", "agriculture", "sugar", "cement" and "ceramics" during the period from October 2014 to October 2023, shows:
The total connectedness index is around 53 percent, which indicates a relatively high systemic risk in the network.
The dynamics of the total directional net connectedness index indicate that each variable has been a net transmitter of shocks in some periods and a net receiver of shocks in others. However, in the overall period review, the basic metals, cement, chemical, metal ore, and petroleum products industries act as transmitters of shocks, and the agricultural, ceramic and sugar industries and dollar act as receivers of shocks in the network.
The dynamics of the total connectedness index during the period of study indicate a significant increase in this index after the COVID-19 pandemic, with the highest figure for the index also being experienced after the outbreak of this disease.
In the network, the basic metals industry is identified as the strongest transmitter of shocks, and the agricultural and ceramic industries are also the most important shock receivers. In addition, on average, the dollar is affected by the shocks of export-oriented commodity industries, especially basic metals, and has been a net transmitter of shocks to small-stock industries, especially ceramics.
Table 1. Averaged dynamic connectedness
USD
chemicals
petroleum
products
basic metals
metal ore
agriculture
sugar
cement
ceramics
FROM
USD
75.62
4.38
3.40
4.50
3.31
1.80
1.34
4.03
1.61
24.38
chemicals
3.89
36.35
10.54
15.82
15.01
4.02
3.02
7.39
3.94
63.65
petroleum
products
1.89
11.93
44.49
15.07
11.01
2.20
3.23
5.94
4.24
55.51
basic metals
2.85
14.06
12.19
34.52
19.71
3.01
3.23
6.90
3.52
65.48
metal ore
2.91
14.12
10.06
22.63
34.59
3.23
3.37
6.06
3.03
65.41
agriculture
2.62
6.01
4.76
4.30
5.17
56.28
6.80
9.09
4.98
43.72
sugar
1.92
6.44
4.55
4.68
4.08
6.11
51.87
11.49
8.86
48.13
cement
2.13
6.61
6.55
8.94
6.31
6.83
8.70
42.19
11.73
57.81
ceramics
2.66
5.17
4.55
5.64
4.75
4.98
9.36
15.58
47.32
52.68
TO
20.87
68.73
56.61
81.58
69.35
32.17
39.06
66.48
41.92
476.77
NET
-3.51
5.08
1.10
16.10
3.94
-11.55
-9.07
8.67
-10.76
52.97
NPDC
3
5
5
8
7
0
2
5
1
Figure 1. Dynamics of Total Connectedness Index
Figure 1. Net pairwise directional connectedness
Conclusion
This research provides valuable insights for policymakers in formulating growth-stimulating policies and designing preventive measures against systemic risk. Additionally, it offers investors an efficient tool for constructing optimal investment portfolios tailored to systemic risk considerations.
Acknowledgments
We would like to thank the esteemed editorial board for their efforts in improving this article.
Samira Ejtehadi; Hashem Zare; Mehrzad Ebrahimi; Mohammad Ali Aboutorabi
Abstract
This paper aims to explain the real-fiscal linkages by identifying the macroeconomic determinants of the operational fiscal deficit in Iran from 1972 to 2020 using the Dynamic Ordinary Least Squares (DOLS) method. The findings indicate that economic growth, inflation, centralization, the size of ...
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This paper aims to explain the real-fiscal linkages by identifying the macroeconomic determinants of the operational fiscal deficit in Iran from 1972 to 2020 using the Dynamic Ordinary Least Squares (DOLS) method. The findings indicate that economic growth, inflation, centralization, the size of the government in terms of efficiency, and the relative population of the employed have positive effects on the operational budget deficit in Iran. On the contrary, trade openness has had a negative effect. The common sense in economics regarding the positive effect of the budget deficit on inflation -primarily because it is often financed through money printing-, along with the key finding of this paper regarding the positive effect of inflation on the operational budget deficit, indicates the establishment of a “self-reinforcing vicious cycle” in Iran’s economy. Based on this, the overall policy implication of this paper is in support of the government’s “strict commitment” to budgetary discipline in conjunction with the design and implementation of a growth strategy based on fostering “human-capital-intensive” technological changes, a more open economy, more fiscal decentralization, minimizing government crowding-out and avoiding price distortions in factor markets, allowing the public sector to align with free market relative prices, and implementing comprehensive explicit complete indexation on both the fiscal revenues and expenditures sides.
Introduction
In conventional public sector economics, the Tanzi effect (1978) suggests that real tax revenues will decline as inflation rises, which in turn leads to an increase in the budget deficit during periods of high inflation. On the other hand, the Patinkin effect (1993) operates in the opposite manner. It predicts that at high inflation rates, the Patinkin effect will prevail over the Tanzi effect, resulting in a decrease in real government expenditures compared to a situation of zero inflation. Consequently, when inflation subsides, real government expenditures are expected to rise. This often leads to an underestimation of the fiscal adjustments needed after inflation has ended, which diminishes the incentive for governments to combat inflation and can even contribute to the persistence of high inflation.
Inflation can influence fiscal expenditures, either increasing or decreasing them - known as the Patinkin effect or its inverse - and it can also affect tax revenues in similar ways - referred to as the Tanzi effect or its inverse. As a result, at a given inflation rate, governments of varying sizes may adopt different budget plans. This means that the presence, absence, or reversal of the Tanzi effect, combined with the presence, absence, or reversal of the Patinkin effect, can lead to different and sometimes contradictory fiscal deficit situations across countries, even when their inflation rates are similar. Historically, there has been a consistent non-neutral relationship between inflation and budget deficits. In this context, Cardoso (1998) argues that inflation typically results in an operating budget deficit that is proportional to the amount of real seigniorage the government requires to finance that deficit.
Accordingly, examining whether inflation has been synergistic with the budget deficit in Iran’s economy or whether the government has used inflation to reduce its real budget deficit is of particular importance in analyzing the economics of government in Iran and providing political economy interpretations of government behavior.
This paper answers these questions: What is the effect of inflation on the operating budget deficit in Iran? In addition, how have other macroeconomic determinants affected the government's operating budget deficit in Iran?
Methods and Material
The research model is specified as follows:
(1)
where:
: represents the government operating budget deficit,
: is the GDP at current prices, at market prices,
: indicates the consumer price index.
Additionally, : is a vector of determinants affecting the government’s relative operating budget deficit. This vector will be added step by step to the initial specification and includes the following indicators:
Open: trade openness.
PD: Population density, serving as a proxy for fiscal preferences.
WPP: The ratio of the working-age population to the total population, which acts as a proxy for the demographic effects on the budget.
RPPG: the ratio of the government consumption-adjusted price index to the private consumption-adjusted price index, and indicative of government size.
The paper empirically identifies the macroeconomic determinants of Iran’s government’s operating budget deficit from 1972 to 2020 using the Dynamic Ordinary Least Squares (DOLS) method and adopts a specific-to-general modeling approach.
Results and Discussion
The key findings of this paper are:
a) Iran’s economic growth has resulted in a government budget deficit. Therefore, achieving fiscal discipline requires a growth strategy that is independent of government influence.
b) The positive effect of inflation on the operating budget deficit indicates the lack of full indexation in Iran's economy. Non-explicit incomplete indexation of revenues and expenses in the government's fiscal regulations has led to varying rates of indexing, with some items not indexed at all or over-indexed due to political pressures.
c) In a more open economy, government assessments will better reflect cost-benefit analyses that consider social benefits and global prices, improving budget efficiency and reducing fiscal imbalances - which is not observed in Iran’s relatively closed economy.
d) Decentralization can shift functions from the central government to local governments, particularly in infrastructure development. This reduces central government expenditures and enhances efficiency while easing budget pressures through balanced regional growth.
e) The government has worsened its budget imbalance by trying to create public sector jobs via financing or subsidizing job creation. This approach crowds out the private sector and encourages the use of capital-intensive technologies over human-capital-intensive ones, leading to higher unemployment among educated youth. As a result, there is increased pressure on the government to create jobs, further straining Iran’s operating budget deficit.
f) The positive effect of the ratio of the government consumption-adjusted price index to the private consumption-adjusted price index suggests that as the difference in prices of goods supplied by the government increases compared to those supplied by the private sector, government inefficiency also rises. This, in turn, worsens the operating budget deficit. In Iran’s economy, the primary reason for the persistent and widening imbalance in the government’s operating budget is the public sector’s failure to align with relative market prices.
Conclusion
On one hand, Political economy motives are widely recognized as a contributing factor to government budget deficits, which in turn can lead to inflation. These motives create a strong incentive for governments to finance budget shortfalls in the simplest way possible, often by printing money (cf. Friedman, 1971; Aghevli, 1977). On the other hand, based on our findings, increasing inflation also leads to increasing budget deficits. The two have created a self-reinforcing vicious circle in Iran’s economy that cannot be broken without identifying and analyzing the political economy motives that reinforce it.
The overall policy implication of the findings of this study is to support the design and implementation of a coherent economic growth strategy in conjunction with greater fiscal discipline and the establishment and maintenance of a balanced budget to which the government has a “tight commitment”.
Akbar Khodabakhshi; Mahdi Torkamani
Abstract
Water utilities provide one of the most crucial services to boost the health and welfare of communities. In Iran, urban and rural water utilities operated independently until 2019, with separate entities serving each province’s urban and rural populations. To enhance efficiency in 2019 ...
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Water utilities provide one of the most crucial services to boost the health and welfare of communities. In Iran, urban and rural water utilities operated independently until 2019, with separate entities serving each province’s urban and rural populations. To enhance efficiency in 2019 by law the rural water utilities were attached to the urban ones and provincial unified water utilities were formed. For water utilities, this brought about enormous changes in terms of organizational structure and scale of operation. In order to determine the efficiency effects of the change, this paper compares the efficiency of water utility services in each province before and after the unification. To do so, a non-parametric method for measuring efficiency in the form of Data Envelopment Analysis (DEA), with Variable Returns to Scale (VAR) was used. “Labor forces” and “assets” of the companies were taken as inputs, and “number of water connections” and the “number of wastewater connections” as outputs and the effects of the changes in the efficiency of all 31 provincial and 3 independent water utilities before and after unification were compared. Results show that the weighted average of efficiency in the whole water and wastewater sector was improved from .66 in 2018 to .75 in 2021, and unification has improved the average efficiency score in the water utility sector in Iran.
Introduction
In Iran, until 2019 water and wastewater utilities used to deliver water and sanitation services separately as different URBAN water utilities and RURAL water utilities. Hence in each province, there existed two different water utilities. In 2019 by law the rural water utilities were attached to the urban ones and provincial UNIFIED water utilities were formed. The unification was an enormous change in terms of organizational structure and scale of operation for water and wastewater services in the country. To determine the efficiency effects of the change, we compared the efficiency of water utility services in each province before and after the unification. Specifically, we were to answer the following question:
Did the unification of water utilities improve efficiency in the sector?
Methods and Material
For efficiency measurement in economic firms as decision-making units, there are different ways among which Data Envelopment Analysis (DEA) is one of the most popular. To answer the above question, the non-parametric method for measuring efficiency in the form of Data Envelopment Analysis (DEA) was used. Since a water and wastewater utility is a Natural Monopoly and there exist increasing returns to scale, we assumed Variable Returns to Scale (VAR). Among many other inputs in a water and wastewater utility, and similar to the explanation of production functions in most of the studies, we used “Labor forces” and “assets” of the companies for inputs as the proxies for labor and capital. For output, the issue is more sophisticated since namely, only the water distributed and wastewater collected are the final products. But in a country as big and diverse as Iran, much more can be regarded as output instead of water distributed and wastewater collected. The utilities have a lot to do to reach the final product any of which could be regarded as a proxy for the final product. These include “total water distributed”, “total wastewater collected”, “length of distribution network”, “number of water or wastewater connections”, “number of water or wastewater purification plants” and so on. Since the total water distributed is a function of water demand by water connections, and also it is affected by water resources available for the utilities to distribute, it seems that the best variables to take as the output are “Number of water connections” and the “number of wastewater connections” instead of total water distributed or total wastewater collected because as mentioned, where and when there are water shortages and in the times of water stress, water crises or drought, the water distributed is affected and further on, the wastewater collected is affected too while the water utility is still operating properly and the operation is not seen.
Results and Discussion
Measuring efficiency in water and wastewater companies in a country with diverse geographical areas of service is sophisticated since the selection of appropriate inputs and outputs must be made carefully with regard to the diversity of variables that can be taken as inputs and outputs. Having this point in mind and taking the Data Envelopment Analysis (DEA) technique, “total labor forces” and “total assets” as inputs and “number of water connections” and “number of wastewater connections” as outputs, the efficiency of the water and wastewater companies BEFORE and AFTER unification were calculated. Results show that the effect for all 31 provincial and 3 independent water and wastewater companies was not the same. The unification has had a positive effect in 11 provinces, a neutral effect on 9 provinces, and a negative effect on 14 provinces. However, comparing the weighted average and simple average of efficiency in the whole water and wastewater sector in the country shows the overall result has improved efficiency score.
Conclusion
The results show that although the effects of unification inside each province might be positive, neutral, or negative, but in terms of overall efficiency in the whole country, the unification has improved the average efficiency score in the water and wastewater companies in Iran.
