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EXTENDED ABSTRACT INTRODUCTION In the last decade, concern about the environment has increased increasingly around the world. One of the serious environmental challenges is urban solid waste, the management of which has been raised as one of the main concerns of human societies. According to the World Bank, by 2025, more than 1.4 billion people will live in cities around the world, and each of them will generate an average of 1.42 kilograms of municipal waste per day. Estimates show that municipal waste worldwide triples every year. The annual generation of municipal waste worldwide has increased from 0.68 billion tons to 2.2 billion tons. Based on available data from countries up to 2012, the World Bank has published a report focusing on municipal solid waste generation. Waste is materials or objects that are discarded or thrown away. Solid waste is waste or discarded materials and objects obtained from industrial, commercial, mining, agricultural, and general daily activities (Ugwu, Ozoegwu & Ozor, 2020). Solid waste is one of the serious environmental issues in developed and developing countries. Solid waste management is a major challenge in urban areas around the world, especially in developing countries. The main reason for this challenge is the rapid population growth along with the expansion of cities, the reduction of financial resources, and the weakness of urban planning. Human activities and changes in lifestyle and consumption patterns have led to an increase in waste production rates (Bovard & ilanloo, 2019). Controlling environmental pollution, including waste, is an important part of human duty in maintaining human health, which has a special place in new sciences and techniques according to economic health standards. Waste production is inevitable in human daily life and population increase will increase it. Municipal solid waste is defined as waste generated by human, commercial, and construction activities that are collected and treated by municipalities (Xiao, Dong, Geng, Tian, Liu, & Li, 2020). The main composition of these wastes is almost the same in different countries of the world. However, the amount of production waste, density, and share of each part of it is different from country to country and city to city. This difference is caused by economic development, geographical location, weather conditions, and cultural and social considerations (Afshar Kazemi, Eftekhar & Omrani, 2014). About, 2.01 billion tons of municipal solid waste is produced annually in the world, of which at least 33% is not environmentally managed. Worldwide, waste generated per person per day averages 0.74 kg but varies widely from 0.11 to 4.54 kg. Of course, it is predicted that by 2050, the amount of waste produced in the world will increase to 3.40 billion tons, which is equivalent to 2 times the population growth in that year. The East Asia and Pacific region produces the most waste in the world at 23%, while this number for the Middle East countries is about 6%. Of course, it is expected that the total waste production in this region will more than double by 2050. It is worth noting that in these areas, more than half of the waste is discarded without reuse. This waste growth will bring many adverse environmental, health, and welfare consequences. Therefore, it requires basic measures.     METHODOLOGY The purpose of this study is to evaluate the efficiency of circular economies in Persian Gulf countries in terms of Municipal Solid Waste Management. This research is applied in terms of purpose and descriptive survey in terms of data collection. Its statistical population was formed from Persian Gulf countries. In this research, the per capita value of MSW production and the dimensions of the social progress index "basic human needs", "basics of well-being" and "opportunity" are used as input and recycling as output in the model. SPI indicators show how well society can cover the needs of its members and improve their quality of life. Data on MSW generation and recycling rates were obtained from the World Bank and data on the three SPI indicators were extracted from the Essential Social Progress website. The data of this research is for the year 2021. The DEA model was implemented in LINGO Softer.   FINDINGS The findings show that the countries of Kuwait (1), United Arab Emirates (0.952), Saudi Arabia (0.654) and Iran (0.453) respectively have the highest circular economy performance compared to other countries in the Persian Gulf. The aim of this study is to analyze the efficiency of DMUs from the perspective of variable returns to scale (VRS).   CONCLUSION The main purpose of this evaluation is the efficiency of circular economy in the Persian Gulf region in terms of urban solid waste management. The results show that Kuwait and the United Arab Emirates respectively have the highest circular economy performance compared to other areas of the Persian Gulf. Data analysis shows that according to the statistics of the World Bank, these three countries recycle 21% and 20% of manufactured products respectively. They have good performance compared to other input indicators. It should be noted that these results can be partially under the conditions of the Covid-19 pandemic. As, Iran will produce more solid food with more population and monitoring of health protocols. This could have caused it to fall to fourth place. Data analysis shows that production per capita in Iran is much lower than other countries. Iran has an average performance in terms of SPI indicators. But in terms of long-term performance, it has been ranked fourth. The reason for this is its very low recycling. Policymakers should use advertising, education, etc. to increase the collection rate of recyclable products. In order to improve their performance, the system needs to produce and at the same time increase the recycling rate. Education and public investment can help in this regard. Also, it should improve its performance in terms of SPI indicators. The province also improves access to basic medical care, food, water and housing. Also, they should provide access to basic education and even advanced education for those in the country who wish to increase their knowledge and skills. According to the results, it is suggested that other Persian Gulf areas improve their performance in recycling. The country's data shows that they recycle less than 10% of their production. It is suggested to evaluate the performance of the Persian Gulf with Europe for a better explanation. It is also suggested to use other indicators of reuse in calculating circular economy performance. Since it is new for environmental management and circular economy at the study level. This means that the special indicators of recycling evaluation and SPI indicators in previous years are different from previous years and practically will not reach a comparative output. For this purpose, it is suggested that future researchers study in different years with an interval of 5 years in the same field and compare the results of different years. However, there is no validity and reliability of this research. But more thought is needed in generalizing the results.

The labor market is one of the main markets in the national economy and the equilibrium of the labor market is one of the main concerns of policymakers in every country. Theoretical foundations and empirical studies show that labor demand is the main factor in creating employment and equilibrium in the labor market. This article evaluates the effect of fiscal policy on labor demand in Iran from 1976-2018. During this period, the government has implemented employment-generating projects, tax and insurance exemptions via annual development programs and budgets, and encouraged investment in areas with high unemployment rates. we examined the effect of current government expenditures, government development expenditures, and taxes to study the effect of government fiscal policies on labor demand. In this article, we estimate the dynamic function of labor demand using the ARDL technique. According to the theoretical foundations and empirical studies in the specified function, labor demand is a function of intermittent values and independent variables of Gross Domestic Product (GDP), real wages, capital stock, current government expenditures, government development expenditures, tax revenues, and dummy variables of imposed war and the UN Security Council sanction. The results showed that fiscal policy has not had a positive effect on labor demand in the Iranian labor market in the short and long term.

Financial statements are critical to users, as the increasing fraud cases have left behind irreversible impacts. Hence, this study aims to identify the appropriate financial ratios for fraud risk prediction in the financial statements of companies listed on the Tehran Stock Exchange within the 2014–2021 period. The study is based on data from 180 companies listed on the Tehran Stock Exchange, encompassing a total of 1440 financial statements. To select the most appropriate ratios for fraud risk prediction, all financial ratios were tested by three metaheuristic algorithms, i.e., genetic algorithm, grey wolf optimization, and particle swarm optimization. Metaheuristic and data mining methods were employed for data analysis, and these analyses were conducted using MATLAB R2020a (MATLAB 9.8). According to the research results, the fitness function yielded 0.2708 in particle swarm optimization (PSO). With an accuracy of 72.92% after 19 iterations, PSO was more accurate and converged faster than the other algorithms. It also extracted 11 financial ratios: total debts to total assets, working capital to total assets, stock to current asset, accounts receivables to sales, accounts receivables to total assets, gross income to total assets, net income to gross income, current assets to current debt, cash balance to current debt, retained earnings and loss to equity, and long-term debt to equity. The support vector machine (SVM) classifier was then employed for fraud risk detection at companies through the ratios extracted by the proposed algorithms. The accuracy and precision of financial ratios extracted by PSO and SVM were reported at 80,60% and 71,20%, respectively, which indicates the superiority of the proposed model to other models. Considering that the results obtained from the performance evaluation of financial ratios provided by PSO-SVM demonstrate the capability of this method in predicting the likelihood of fraud in financial statements, it can assist financial statement users. By incorporating these ratios about the performance of the target companies and comparing them with those of other companies, users can make more informed decisions in economic decision-making, investments, credit assessments, and more, ultimately minimizing potential losses and risks.

The main reason for people investing in the stock market is to make a profit, which requires accurate information about the stock market, price changes and predicting its future trend. Therefore, investors need powerful and reliable tools for forecasting Stock prices in the future. The main purpose of this study is to present a method based on wavelet denoising and dynamic time warping to identify the stock price pattern in the Tehran Stock Exchange. In this regard, first, using the wavelet denoising preprocessing step, noise is removed from the stock price time series, and then the extracted data is used as input to the dynamic time warping prediction model. MATLAB software version 9.11 was used to analyze the research data. The statistical population of the present study includes 3 shares among the shares of steel industry companies of Tehran Stock Exchange. The research was conducted in the period 1395 to 1398. The results show that the predictions obtained from the dynamic time warping method equipped with the wavelet denoising preprocessing step in comparison with the predictions obtained from the dynamic time warping method without the wavelet denoising preprocessing step in all three shares studied, have been associated with much less accuracy and error.

Sanctions increase managers' motivations to manage profits and the accumulation of bad news due to their negative impact on corporate profitability and cash flow. According to Jin and Myers (2006), this issue increases companies' stock price crash risk. The higher probability of stock price crashes indicates a stock price overvaluation. As a result, the expected return on such shares will be low. The current paper used the softmax model to calculate the probability of stock price crashes and the expected return calculated by the Fama-French three-factor model. The sample used in this paper includes 80 import- and export-oriented exchange companies from 2008-2021. The results of this paper indicate a positive and significant relationship between the sanctions variables and the probability of stock crashes. So, sanctions cause an increase in the accumulation of bad news and information asymmetry between managers and investors. The second part of the paper's results indicates a negative relationship between the probability of stock crashes and the expected return on the stocks in the Iranian capital market. Therefore, investors have relatively good analytical skills in the Iranian capital market due to its shallow depth and infrastructure problems. The results of this paper can be used in portfolio management to select stocks with a lower probability of crash and higher return.

The purpose of this study is to identify the effect of stock tendency to deal with fluctuations and price fluctuation thresholds in creating fluctuations. The statistical population of the present study is the companies listed on the Tehran Stock Exchange that were present in the stock exchange during the years 2005 to 2018. In order to confirm and reject the research hypothesis, Eviews software has been used. In Tehran Stock Exchange, following severe stock price fluctuations, the stock price fluctuation mechanism is used to limit severe stock price fluctuations, and according to certain periods, the range of stock price fluctuations changes and over time the range of fluctuations increases. The basis of trial and error has been determined and in a short period of time there have been many changes in the procedures related to the application of stock price fluctuations, without really measuring the impact of these decisions in the market and investors' reaction to changes in price fluctuations. Findings showed that the number of times each share hits the price fluctuation Yield fluctuation has a significant effect.slow efficiency fluctuations have a significant effect; And in line with the concepts of hyper-reactive theory, it can be justified, that is, after the price reaches the range of fluctuation, the trend reverses and the basis of the fluctuation limit changes; It has changed the volatility of stock returns based on jump and price continuity.