فصلنامه پژوهش ها و سیاست های اقتصادی
پیاپی 105 (بهار 1402)

One of the main reasons in economic recession is the liquidity constraints of economic firms. When external finance becomes expensive for firms, money demand will act as a buffer stock. Actually, firms reduce unfavorable effect of liquidity constraints by holding money. In this study, after extracting firms liquidity demand function based on micro foundations and creating an index for firms liquidity constraints, using seasonal data of 334 active corporates in the Tehran Stock Exchange during the period of 2006-1 to 2021-4, the experimental model of the research, including two simultaneous equations, is estimated by the two-stage least squares method. Estimation result indicates the positive relationship between firm's liquidity demand and the liquidity constraint index. So that one percent increase in the liquidity constraint index increases the liquidity demand of constrained firms by 3.4 percent, while the same coefficient for unconstrained firms is 1.5 percent. As expected inflation is one of the main variables in the firms' liquidity demand, one percent increase in the expected inflation increases the liquidity demand of both constrained and unconstrained firms respectively by 1.3 and 0.6 percent. Although the effect of the costs of production factors, such as wages, the cost of capital and the relative price of imported goods -including changes in world prices and exchange rates- on the index of liquidity constraints is positive and significant, but their impact on the constrained firms are more severe. In credit crunching condition, the liquidity constraints of constrained firms increase more. Therefore, to prevent instability in credit cycles, the policy maker should focus more on constrained firms and pay attention to the money demand of heterogeneous firms in effectiveness of monetary policies.

In this paper energy intensity changes in industries of Iran as a whole and for each province separately have been calculated in the period of 2005-2019. These changes are divided to structural and efficiency effects by using average distribution on the amount of changes in cross method. The results show that during this period, energy intensity has increased throughout the country and in all provinces, indicating the continuation of non-optimal behaviors in energy consumption. Decomposition of energy intensity changes into its components shows that structural effect in the country, especially changes in the combination of products, has led to an improvement in energy intensity. In contrast, the efficiency effect that means efficiency in energy consumption, has led to an increase in energy intensity throughout the country. According to the results of this study, the efficiency effect in most provinces except Ardabil, South Khorasan, North Khorasan, Mazandaran, Sistan and Baluchestan, Qazvin, Kurdistan, Kerman and Golestan has increased energy intensity. And structural effect in the provinces of East Azerbaijan, West Azerbaijan, Ardabil, Isfahan, Eelam, Tehran, Khorasan Razavi, Semnan, Fars, Qom, Kurdistan, Lorestan and Hamedan has reduced energy intensity. Improving industrial energy intensity in Iran requires drastic measures which include increasing energy prices proportionally to inflation rate for industrial uses, replacing obsolete and inefficient industrial processes by more efficient ones especially in energy intensive industries, technology transfer, creating energy audit units in energy intensive industries, developing mandatory standards and regulating energy uses in industrial processes and equipment.

As a measurement of risk, Value-at-Risk has always been attractive to researchers in the field of risk management and capital markets. This importance has always led them to develop models to increase the accuracy of VaR estimation. GARCH models are used to estimate conditional variances in parametric approaches of calculating VaR. In the latest developments, Hansen presented the Realized GARCH model using intra-day data. Regarding the recent high fluctuations of the Tehran Stock Exchange Index, the use of Realized GARCH models to compute VaR can increase the accuracy of forecasting. In this paper the three different distributions, Normal, T, and GED, are combined with conventional GARCH models, and the new Realized GARCH model. Next, the VaR of the Tehran Stock Exchange index is forecasted using the rolling window sampling method. And finally, the accuracy of predicted VaR has been evaluated and compared using a two-step Backtest method. The outcome of this study indicates that using the new Realized GARCH model in forecasting VaR will tend to result in more accurate estimates, whether at the 5% or 1% level.

One of the most important challenges of economic development in Iran is the heterogeneous spatial structure of regional employment rates. Determining the factors affecting the provincial unemployment and identifying the effects of spatial overflow between provinces- including industrial aggregation- can be considered in planning and policies in order to improve employment and reducing heterogeneous distribution of unemployment rates between regions. This measure becomes more important due to the distribution of economic activities with the changing conditions and also the wide differences in the distribution of unemployment rates in provinces of Iran. The main purpose of this study is to investigate the effect of industrial aggregation on unemployment rates in Iran provinces during the period 2007-2016 by using a combined spatial econometric approach. Findings of this study confirm the existence of spatial dependence in research data and show that industrial aggregation has a negative and significant effect on unemployment rates in Iran provinces. In other words, the industrial aggregation index has an inverse and negative effect on the unemployment rate in the province, itself, and also on its neighboring provinces.

One of the key issues in financial stability studies and prudential policies is systemic liquidity risk, in other words, the risk of liquidity problems at the same time and in several financial institutions. The fact that in the complex network of interbank market interconnections, the lack of liquidity is provided by spreading it between financial institutions, can lead to "systemic contagion" in the banking network. This research aims to investigate the existence of systemic contagion in the banking network of Iran and the effect of the Basel Committee's prudential regulations on interbank contagion based on the balance sheet data of 25 banks that are members of the interbank market in the years 2006-2018. For this purpose, based on the agent-based approach, Iran's banking network has been modeled and simulated. In this model, banks and the central bank are intelligent agents. Based on the obtained results, prudential regulatory requirements change banks' adaptive strategies, and banks put increasing the capital adequacy ratio on their agenda. In addition, this research shows that although the guidelines of the Basel Committee have succeeded in reducing contagion in the long run and making the banking network more stable, banks also reduce the supply of loans to the real sector, which can lead to a crunch in the economy.

The present study was conducted to investigate the effect of commodity group expenditures on the probability of urban household poverty at different levels of wealth. In this article, using the data of the household expenditure-income plan for the year 2019, the household poverty line was calculated based on the 66% average per capita expenditure method. The findings of the estimation of the research model based on pseudo-tabular data and random effects method in logistic regression in three levels of wealth show that the largest number of households are in the middle category of wealth. The gender and age variables of the head of the household have a greater effect on reducing the probability of poverty at the middle level, and also at low levels of wealth, the increase in educational levels reduces the probability of poverty to a greater extent. The direct effect of the household dimension is greater at low levels of wealth on the probability of poverty. Expenditure on food, drink and tobacco, housing and transportation at a low level of wealth has a stronger effect on increasing the probability of household poverty. Among the expenses of different commodity groups, communication expenses have the most positive effect on the probability of urban household poverty, which is greater at low levels of wealth. Entertainment expenses - cultural affairs in the low and high level of wealth do not have a significant effect on the probability of household poverty.

Financial evaluation of insurance companies has always been considered one of the important concerns in the development of insurance services and thus increasing insurance penetration in countries. On the other hand, the multiplicity of executions and factors affecting the success of insurance companies make the relevant evaluation factors and indicators have a certain complexity. The regulator should formulate its method of financial valuation based on the information it receives directly from insurance companies. To achieve this goal, it is necessary to explain the indicators in important areas and to weigh them according to their importance. Therefore, in this study, by analyzing the content of written documents and examining the indicators of rating agencies and analytical tools of world insurance regulators, the financial evaluation indicators of insurance companies were identified, and then the indicators were weighted using the Shanon entropy model. The results showed that the financial ratios have the necessary validity to evaluate the situation of insurance companies. Therefore, it is suggested to the supervisory institutions to complete and correct these indicators and take the necessary measures towards the requirements governing the disclosure of information related to these ratios, and in this way, the effectiveness of financial statement information in the process of making informed judgments and rational decision-making will increase.

In recent years the prospect of green jobs policies have become increasingly prominent, proposed to solve both the environmental challenges associated with global climate change and the persistent unemployment problems. This research seeks to determine the potential of green jobs in non-energy sectors using the multi-factor energy input-output method and input-output data table of 2016. The results show that the sectors related to the production of crops and horticulture, livestock products, forestry and fish products and fishery products have the highest potential for creating green jobs. In other words, these products have the lowest CO2 emissions per unit of energy jobs. Decision makers can support these sectors. On the other hand, non metallic mineral products, transportation services and mineral products have the highest rank in terms of the ability to create employment, respectively, and are in the lowest rank in terms of creating green jobs. So that transportation services have the least potential to create green jobs.

Determining the factors affecting the volatility and risk of the stock market by expanding the pricing models of capital assets has been the focus of researchers. One of the variables that has a close relationship with financial markets is block chain technology. Therefore, the present study investigated the effect of block chain technology on total and systematic risk volatility in 84 selected companies of the Iran`s stock market during April 2010 to August 2014 using Vector error correction model. The results of the study show that the systematic risk function in the first period has a positive reaction to the changes in blockchain technology, but after the second period, the impact of blockchain technology shocks on the systematic risk of companies has been positive with a constant slope. Also, since the first period, the total risk function has had a positive reaction to the changes in blockchain technology with an upward slope. Systematic risk and total risk functions have also reacted positively to the shocks of the companies' market share and the company's rate of return. The results of the variance analysis of the total risk and systematic risk functions show that in the systematic risk function, according to the asset return rate, blockchain technology and market share had the greatest effect on the changes in the risk function, and in the risk function, according to the market share, asset return rate and Block chain technology has had the greatest effect on the changes of the mentioned risk function.

This study investigates whether the increase in imports in oil countries (due to oil revenues) can mitigate the inflationary effect of liquidity growth or not. In this regard, a panel ARDL model is used to investigate the issue among 14 oil-exporting countries between 1970 and 2020, which is estimated by the Pooled Mean Group (PMG) method. According to the results of estimations, the effect of liquidity growth on inflation is positive and significant in the oil countries (both in the short and in the long run). The results show that increases in the ratio of imports reduce the effect of liquidity growth on inflation both in the short and the long run. Also, raising the oil revenues decrease the inflationary effect of liquidity growth in the long run. In other words, an increase in the supply of imported goods (because of a boom in oil revenues) leads to an increase in domestic money demand and partially neutralizes the inflationary effect of liquidity growth. Besides the panel regression, a regression analysis of Iranian economy data is used to test the hypothesis. These results also confirm that changes in the import ratio and oil income ratio explain the difference in liquidity growth and inflation.