سعید کریمی پتانلار

The outbreak of the new coronavirus since December 2019 in Wuhan, China, caused many negative effects on countries around the world. This crisis was initially recognized only as a threat to public health; But with its epidemic in most countries of the world, it became a serious crisis for the global economy.The shock caused by the Covid-19 crisis has had various impacts on the economic situation of countries around the world. Income inequality is one of the most important areas affected by the crisis. Hence, the aim of this study is to investigate the effect of the shock caused by this crisis on income inequality for (22) developed countries and (46) developing countries during the years (2020 to 2022 AD) using a seasonal panel vector autoregression (PVAR) model. The results indicate that the Covid-19 crisis has increased income inequality in both developed and developing countries. What can be inferred from the results of the impact reaction functions is that with the onset of the crisis, the effects of the direct tax shock, the degree of trade openness, the strictness index and the rate of covid-19 infection on the Gini coefficient in both groups of countries have led to an increase in income inequality. Also, in developed countries, the effect of the human development index shock on the Gini coefficient is negative, but in developing countries, the effect is positive and has increased income inequality. The results of variance analysis of prediction error for both groups of countries show that the strictness index is the dominant factor in explaining the variance analysis of Gini coefficient prediction error.

In this article, the effects of oil revenue shocks on the constituent components of the government's expenditures during the period of 1990/04 to 2018/04 and tax revenues during the period of 1993/01 to 2018/04 in Iran are investigated. In this regard, in order to consider the structural instability in the parameters, time-varying parameter generalized vector autoregression (TVP-VAR) models have been used. Based on the results obtained from the first model of the research, the impact of oil income impulses on defense expenditure is estimated to be positive. Although the said effect quickly disappears in the later periods. Therefore, it can be said that the impact of oil revenue impulses on government defense expenses is temporary. Also, the effect of impulses on economic and social affairs expenditures is estimated to be positive. The impact of oil income impulses on public affairs expenses was initially positive, but it gradually decreased and reversed in later periods. The results of the second model of the research, in which the impact of oil revenue shocks on direct and indirect tax revenues is investigated. The impact of oil revenue impulses on direct tax revenues from the positive range is quickly placed in the negative range. On the opposite point, the impact of oil income impulses on indirect taxes starts from the negative range and then quickly moves to the positive range. Also, the impact of oil revenue impulses on indirect taxes can be considered positive.

considering the importance of oil shocks in Iran's economy, in this research, an attempt has been made to examine the effects of oil income shocks on the expenditure and income components of the government's general budget. in this regard, in order to consider structural instability in parameters, time-varying parameter vector autoregressive (TVP-VAR) models are used. this model allows the estimated coefficients vary over time. in this research, the seasonal data in period of 1990/02-2019/01 be used. the estimation results of the models indicate the positive and short-term effects of oil income shocks on current expenditures and construction expenditures. the estimation of the second model shows the negative impact of oil shocks on tax revenues and the positive impact on other government revenues. the results of reaction functions (IRF) also show that the mentioned effects have a short duration and are reversed in the next periods and disappear quickly. also, the estimation results of the models show that the impact of oil shocks on inflation has varied over time and changed from negative to positive after the income shock of 2005.

Corruption and the fight against its various forms have constantly been a concern of theorists and policymakers because corruption is one of the important obstacles to socio-economic development. Economists have issued warnings about the devastating consequences of financial corruption and have argued that financial corruption increases transaction costs, reduces investment incentives, and ultimately reduces economic growth. Political scientists have pointed out the political costs of corruption for societies and claimed that an increase in corruption leads to a decrease in public trust in the political system and the destruction of the government's legitimacy, and could have a negative impact on democracy and political development. The manner in which this phenomenon influences growth and development is that it typically leads to more inequality and loss of public trust in government. By reducing political accountability, it undermines democracy and good governance. The economic approach is useful to study the causes of financial corruption because the researchers will be able to pay close attention to the underlying motivations and rationality to explain this problem of corruption. The researchers will be able to explain and understand why some individuals make choices based on their preferences that results in financial corruption. Some individuals are more corruption-prone and willing to engage in corruption when the opportunity arises to maximize financial gains for their own personal use or act as agents of corruption in their institutional roles for collective gains. Equally important is the task of discussing the anti-corruption efforts to deter future corruption behaviors of individuals and to combat state-sponsored institutional corrupt practices. In order to formulate effective strategies and policies to win the fight against corruption, it is necessary to first identify and understand the causes of corruption.With a qualitative approach and within the framework of public choice theory, the authors analyze a collection of the most important empirical and theoretical work on the causes of corruption with the goal of finding suitable answers to the following research questions: 1. What are the prominent differences between economic and non-economic approaches to explain the causes of financial corruption? 2. Does the economic approach used to explain the causes of financial corruption have more explanatory power than the non-economic approaches? The research hypothesis assumes that the use of economic approaches (general choice theory) to study financial corruption is more effective in analyzing the financial corruption-development association. The essence of the general choice theory to explain the behaviors of individuals and political elites is that these individuals seek to maximize their own personal gains and/or the collective benefits of a particular group, party, class and family with no or little regard for the maximization of the accrued benefits for the society at large. A key question is, to what extent the corrupt individuals are rational actors, given that they make choices which are generally perceived as irrational by other individuals—who do not get involved in corrupt practices. A multitude of reasons might influence an individual to make a ‘rational’ decision to engage in financial corruption practices. Theoretically, he makes a rational choice, because his calculations indicate that the expected benefit of financial corruption exceeds the expected cost including the cost of being detected, arrested and punished for his illicit acts.The critics of the economic approach to explain financial corruption emphasize a score of economic and non-economic factors such as weak economic development, low levels of education, poor quality of the bureaucracy, reduced transparency in laws and tax regulations, misconduct of community leaders, and religious composition of the total population. The existence of ethnic-linguistic subgroups in a country, the low degree of democracy (indicated particularly by the lack of freedom of speech and the freedom of the press), and political instability have been emphasized in the non-economic approach to the study of financial corruption. However, the effects of the non-economic causes of financial corruption are indirectly through economic factors. The individuals generally base their decision-making on their cost-benefit analyses and if the gains exceed the cost, they get engage in corruption. In other words, the improved quality of bureaucracy and transparency do not necessarily prevent a person from committing acts of financial corruption, but the high quality of bureaucracy and the high degree of democracy (particularly freedom of the press and transparency) reduce financial corruption by increasing the cost of corruption behaviors. The results suggest that non-economic approaches have been useful in explaining causes and consequences of corruption to a certain degree, but economic approach is more effective for understanding the motivations of corruption and its consequences for economic and political development. These research findings are important for planning and implementing anti-corruption programs such as enforceable ethical code of conduct, and regulations to increase transparency and accountability for public officials.

The Covid-19 crisis was first recognized as a serious threat to public health around the world, but as it grew into a pandemic all over the globe, it inflicted enormous losses on the economies of many countries grappling with tackling its grip. The negative effect of this crisis has been different between countries and the role of governments turned to be a decisive one in dealing with it; The aim of this research has been to investigate the effect of the covid-19 shock on the public sectors of 19 developed and 24 developing countries for the period ranging from 2020 to 2022 using a panel vector autoregressive (PVAR) model run on seasonal data. The results show that the covid-19 crisis has led to an all the way down to an increase in healthcare expenditures, budget deficits, government size and a slump in tax revenues. What makes the patterns witnessed in these two groups of countries different is the degree of the effect the crisis had on aforementioned variables. The results show that overall, the developing countries have been affected the most by the crisis.

This study aims to model tax evasion and identify how these factors affect tax evasion. The current research is in the field of applied research. To achieve this purpose, the Bayesian averaging method has been used in the period from 1370 to 1399 in MATLAB 2021.In this research, 62 variables affecting tax evasion were included in the model and using the Bayesian averaging model approach, from 1 to 12 non-fragile variables affecting tax evasion were identified. The results show the fact that the inflation rate is the most non-fragile variable affecting tax evasion. Also, based on the results of the TVPFAVAR model, it was observed that the shock effect of macroeconomic variables (inflation, exchange rate, unemployment, budget deficit) on tax evasion was generally positive and strong, while the effect of cultural variables (tax culture, tax effort, tax morale), tax fairness and tax justice), generally has a small and negative effect on this variable.

The existence of a structural budget deficit in Iranian economy and the lack of fiscal discipline have raised concerns about the financial stability of governments among economists. In recent decades, fiscal rules have been considered as a way to establish fiscal discipline and financial sustainability of governments around the world. In this regard, the present study seeks to design a fiscal framework based on the three rules of debt ceiling, budget balance and expenditure for Iranian economy. The results of applying the stochastic simulation method show a high level of current public debt compared to the debt rule ceiling estimated by the model and the budget balance rule will be greatly effective in improving the future path of public debt. In other words, applying the budget balance rule reduces the fluctuations of the future path of public debt. It is also suggested to establish an institutional mechanism as a complementary institution with the aim of improving the performance and effectiveness of fiscal rules, especially for expenditures rule and ensuring their implementation

This study seeks to model tax evasion and identify how effective factors affect tax evasion in the Iranian economy. Recent models show the failure of traditional models; Models do not have enough ability to model hidden variables such as tax evasion. The present study considers this failure in identifying explanatory variables and experimental model design. To achieve this, the Bayesian averaging method has been used in the period 1370 to 1397 in MATLAB 2021.In this study, 62 variables affecting tax evasion were entered into the model, and using the Bayesian averaging model approach, 1 to 12 non-fragile variables affecting tax evasion were identified. The results show that inflation is the most fragile variable affecting tax evasion. As a result, in tax evasion modeling, inflation has the highest direct relationship with tax evasion; Also, based on the results, the most important variables affecting tax evasion in modeling tax evasion in order of priority are inflation, exchange rate, tax culture, unemployment, tax fairness, tax effort, budget deficit, tax morale, privatization, tax complexity, value-added ratio. The GDP services sector, fair tax system. According to the results, both political and cultural, and economic factors have a significant impact on tax evasion.

In this paper, the effect of social capital on the efficiency of government expenditures has been studied in the two sectors of education and health during the period 1364-1396. social capital has been estimated by The Multiple Causes-Impact (MIMIC) approach, and efficiency of government expenditures in both education and health is estimated by the Data Envelopment Analysis (DEA) and Bootstrap data envelopment analysis approaches. The effect of social capital on the efficiency of government expenditures are measured by the regression model of the deficit probe in both education and health.
 The results of estimating social capital show that the trend of social capital is declining by the method of  Multiple Indicators and Multiple Causes during the study period. Also, the efficiency scores of government expenditures has been measured by Data Envelopment Analysis and Bootstrap Data Envelopment Analysis in Iran. The results show that on average, public spending is inefficient in education and health.
Findings of the fractional probit model show, the effect of social capital is positive and significant on the efficiency of government spending in both education and health. The effect of per capita income, economic growth, government size, inflation and trade openness is different on efficiency of government expenditures in education and health sectors.
 For example, the impact of economic growth is positive on the efficiency of government education and health spending. While the effect of government size is negative on the efficiency of government education and health spending.

Inflation affects the state budget in both ways. Inflation, on the one hand, decreases the purchasing power of tax revenues, which is known as the tension effect. On the other hand, the inflationary burden of government expenditures and its obligations actually decreases, which is known as an antithetical effect. Meanwhile, it should be noted that inflation also affects the budget deficit of the state. In the present study, using a discrete wavelet converter with maximum matching and a vector of autoregressive vector autoregression, the interaction effects of inflation and deficit of government in two cases of deficit and total deficit in the economy of Iran in 1396: 1369: 1 is reviewed from a new angle. Results based on the wavelet converter show that in horizons for more than 8 years, the causal relationship is between the two types of budget deficit with bilateral inflation. Based on the results of the estimation of the autumnal regression model, the threshold vector in seasonal inflation is less than 5.7% of the total budget deficit in the face of inflationary swings, which reflects the dominance of the anti-tensile effect of the Tensi Is. In addition, the operating deficit, regardless of the situation, is from the threshold of positive reaction to the swing momentum.

Healthcare insurance coverage services in Iran are limited, and out-of-pocket costs are very high. Supplementary health insurance grants extra coverage and additional healthcare services in the presence of limited health insurance services to the individuals and protects them against huge healthcare costs. One of the obstacles to expanded health insurance schemes, especially in supplementary health insurance, is an undetermined willingness to pay (WTP) for these types of coverages. The objective of this study is to estimate WTP for supplementary health insurance. Data collected from small and medium enterprise employees in 7 areas Iran including Tehran, Shiraz, and Bandar-e Abbas in 2017 and the contingent valuation method and a logit regression model was implemented to analyze the data. Results show that WTP for supplementary health insurance is 70.23 thousand Tumans. Education level, employment status, real income, current health conditions, history of chronic disease, number of doctor visits, real healthcare costs, and satisfaction from healthcare services are all found to affect WTP for supplementary health insurance.

Environmental degradation can be caused by factors such as population growth, economic growth, energy intensity and income distribution. In this paper, the environmental impact of inequality in income distribution using time series data from the years 1357-1394, with Auto Regression methods Distributed Lag (ARDL) is investigated. Also, the causality relationship between the model variables has been investigated using the Toda-Yamamoto causality method. According to the results of the estimation of the research model, GDP per capita, Gini coefficient and total energy consumption per capita have a positive effect on CO2 emission, and the squared variables of GDP per capita and urbanization to population ratio have a negative effect. In the meantime, the most effective coefficient, GDP per capita is positive. Also The Kuznets environmental curve hypothesis is confirmed in Iran. The results of the causality test also show that there is only bidirectional causality between GDP per capita and carbon dioxide emissions. The one-way causal flow from the Gini coefficient logarithm, the per capita energy consumption logarithm, the urban-to-population ratio logarithmic to the CO2 emission logarithm are verified.

The aim of this article is to analyze the effect of shocks of fiscal consolidation policy on the macroeconomic variables in Iran. In this regard by using Factor Augmented Vector Auto Regression (FAVAR) method, the effect of shock types of deficit ratio to GDP on important macroeconomic variables including total real GDP growth, inflation, private consumption growth and investment growth over the period 1363: 1 -1394: 4 is investigated. The results of research models show that the effect of fiscal consolidation policy on the macroeconomic variables are different, and it is difficult to provide the same policy tool to affect all variables. The results obtained in one-year, two-year and four-year periods indicate that the fiscal consolidation policy cannot be identified during the one-year period. But in the two-year and four-year periods, the main instrument of fiscal consolidation is deficit-deflation and deficit-free oil. It should be noted that the consumption deficit is calculated as tax revenue minus the consumption expenditure of the government divided by GDP and the deficit without oil as the total state revenue (without oil revenue) minus current expenditures divided by GDP.

The aim of this article is to analyzing the effect of shocks of fiscal consolidation policy on the macroeconomic variables of Iran. In this regard by using Factor Augmented Vector Auto Regression (FAVAR) method the effect of shocks on government revenues and expenditures on important macroeconomic variables including total real GDP growth, inflation, private consumption growth and investment growth over the period 1984:1 -2015:4 is investigated.
The results of research models show that the effect of fiscal consolidation policy on the macroeconomic variables are different, and it is difficult to provide a same policy tool to effect all variables. Thus with emphasis on real GDP growth which is a major factor that affects other macroeconomic variables, it can be noted that in short term which consists of 4 seasons, reducing public expenditures and increasing government revenues lead to a reduction in production in response to a negative reaction to investment and private consumption and inflation will decrease. Therefore in the short term the suitable policy for fiscal consolidation is a combination of expenditure cut and income rising and in particular, the policy of reducing current expenditure and increasing import taxes. In the medium and long term, respectively consist of 8 and 16 seasons, real GDP growth responses positively to the expenditures cut policy, decline in current expenditures and social public expenditures is introduced as an instrument of fiscal consolidation policy.

This paper has examined the effect of corruption on the allocation of talent in Iran's economy during the period of 1984-2014 and for discovering the effect of unobservable factors as well as political, social and economic structural changes, the structural time series model approach has been used. The results of the research indicate that increasing in corruption, financial development, growth of consumption government size and the share of value added of services sector in the GDP have distorted the allocation of talent in Iran during the period of 1984-2014

Considering the importance of the relationship between government size and trade openness, this study has examined the nonlinearity effect of trade openness on the government size in Iran during the period 1991-2011. The results show that trade openness has an asymmetric effect on the government size in the form of a two regime model.Also, in the first regime (when trading volume is less than 39/53% of GDP), trade openness, consistent with the Efficiency Hypothesis, has negative effect on the government size. Whereas in the second regime (when trading volume is more than 39/53of GDP), trade openness, consistent with the Compensation Hypothesis, has positive effect on the government size. Finally, the results show that the size of government increases by increasing the share of government revenues and investment in GDP.

The purpose of this study is to evaluate the impact of economic globalization on government size in Iran's economy. An Autoregressive Distributed Lag (ARDL) modeling approach is employed to estimate empirical model using the time series data over the period 1973-2007. Trade openness and foreign direct investment are employed as indicators of trade and financial globalization, respectively. Moreover, some control variables are included in the empirical model. They comprise economic growth, industrialization and urbanization growth. The results of the paper confirm that trade openness has positive and statistically significant effect on the government size in Iran. This means an increase in trade openness leads to increase government spending. However, the findings show that the effect of financial globalization on government size is not statistically significant.