Uncertainty

Today, small and medium-sized enterprises (SMEs) play a key role in both developing and developed economies. However, the uncertainty of macroeconomic indicators, such as economic growth, may affect financing and investment of the SMEs in an economy. The present study explores the effect of the economic growth rate uncertainty on financing SMEs in Iran. To this end, the study has applied the Brownian motion approach to calculate the uncertainty of the economic growth rate. The study has also considered relevant data of the Iranian SMEs compiled by the Comprehensive Database of All Listed Companies (CODAL). We have examined the SMEs with less than 100 employees throughout 2011-2017. The empirical results show that the effect of the economic growth rate uncertainty on the selected Iranian SMEs financing has been negative and statistically significant, while it seems an effective challenge to such firms in order to finance their productive investment. JEL Classification:D81, G21, L25, E43.

Information flow is a key parameter in an economic activity and acts as the main factor in the appearance, stability and efficiency of capital markets. The purpose of this study is to investigate the effect of comparability and environmental uncertainty on the expected rate of return in oil, gas and petrochemical firms. The current study applies panel regression method estimator to investigate the relationship between comparability, environmental uncertainty, and the expected rate of return of 500 firm-year observations in oil, gas and petrochemical firms listed in Iran Securities and Stock exchanges for the period of 2009-2018. The results of the research show that the comparability and uncertainty has a significant effect on the expected rate of return. In other words, the results of the research show that the expected rate of return is a function of comparability and it varies in different levels of comparability. Key words: Comparability, Expected rate of return, Uncertainty

Iran is one of the most important oil and gas producing countries in the world with 153.8 billion barrels of crude oil and 33.5 billion cubic meters of gas has 9.3% and 18% share of total oil and gas reservoirs, respectively. Rich hydrocarbon reservoirs along with a special geographical location are of the most important competitive advantages of Iran. The oil value chain has a special place in the social, economic structure and level of development of Iran. In policy-making, especially in global equations and in the long run, where uncertainty is an integral part it is necessary to pay attention to this area. As a strategic knowledge, futures studies can play an important role in mapping the future. In current study, the possible and plausible futures of Iran's fossil energies (oil and gas) in the 2035 horizon are presented in the form of four scenarios. In an environment where variables are dynamic and constantly changing and uncertainty is high, using scenario building methods is preferable for long-term horizons. In this study, 30 drivers with high uncertainty and impact on the future of Iranian oil and gas were produced. Using the cross impact analysis model and the balanced impact model, out of 41,472 possible scenarios, 10 scenarios with maximum compatibility were obtained, that presented in four scenarios namely: clean scenario (low carbon), a bipolar Middle East scenario, a cooperation and development scenario, and finally a postponed dream scenario.

Two main issues occurring in the economy and largely affecting stock prices are uncertainties and asymmetric information which are influenced by many factors, and along these factors, affect the stock prices. In this study, using Cox, Ingersoll & Ross (CIR) model, we tried to investigate the relationship between theoretical price and stock price under the conditions of uncertainty and asymmetric information. Then, using the GLS panel method, the stock price relationship with these variables and the factors related to the firm performance, economic factors and industrial factors were investigated in Tehran stock exchange. The results indicated that a large part of stock price changes can be explained by two variables of uncertainty and asymmetric information, while other factors had significant effects on stock prices. The difference was that the factors related to the firm's performance and industry index had a positive effect and the macro-economic factors had a negative effect on stock prices. Finally, according to CIR model, asymmetric information and uncertainty in market ‎lead to delays in stock price adjustment, which can affect quality of corporate ‎governance principles‏.

Social capital is a relatively new concept in the social sciences and is one of the most important challenges of new era in a way that based on experts’ comments, the solution for all the problems of today’s modern world is social capital. To this end, one of the problems that managers of organizations particularly; service and manufacturing organizations have faced with today is lack of trust in accurate implementation of contract specifically implied contracts. If managers tend to control the whole organization for the accurate implementation of these contracts, it would lead to extravagant costs. One proper and certain way to solve this problem is to apply elements and components of social capital in organizations. By deploying scientists’ thoughts regarding social capital, the present research attempts to analyze the evidence of social capital reduction in banking industry and test its impact along with other forms of capital on GDP of the country. Findings of this study indicate that there is a significant and reverse relation between social capital reduction in banking industry and GDP. JEL Classifications: J24, E23, D81, E58

The Web has become the most important information source for most of us. Unfortunately, there is no guarantee for the correctness of information on the Web. Moreover, different websites often provide conflicting information on a subject. Several truth discovery methods have been proposed for various scenarios, and they have been successfully applied in diverse application domains. In this paper, we have attempted to answer the question whether the truth is relevant. We conducted an experimental study in which we analyzed and compared the results of two different truth discovery methods: Relevance-based sources ranking and Majority vote. We have found that the truth is not always held by the most relevant sources on the web. Sometimes the truth is given by the majority vote of the crowd. In addition, we have proposed a method of presenting the results of truth discovery with gradual degrees of belief. A method that allows to configure and target the desired level of trust.

INTRODUCTION: Since Iran is located in the semi-arid belt, it has faced such issues as drought, dust crisis, and intensified migration. The assessment of the effects of climate change includes identifying some key aspects of uncertainties used to estimate its impacts, such as uncertainties in the context of Atmosphere-Ocean General Circulation Models (AOGCMs): in regional-scale climatology, in statistical or dynamic downscaling methods, and parametric and structural uncertainties in different models. One of the most important sources of uncertainty in climate change is the use of different AOGCMs that produce different outputs for climate variables. METHODS: In this study, to investigate the uncertainty of AOGCM models, the downscaled data of the NASA Earth Exchange Global Daily Downscaled Projections dataset obtained from 21 AOGCMs with medium Representative Concentration Pathway4.5 scenario were downloaded from the NASA site for 81 cells in Hamadan Province, Iran. After the validation of the models, they were evaluated against the criteria of the coefficient of determination and model efficiency coefficient in comparison with the data of the Hamedan synoptic station in the statistical period of 1976-2005. To reduce the uncertainty of AOGCMs, the ensemble performance (EP) of models was used in Climate Data Operators software. FINDINGS: It was revealed that MRI-CGCM3, MPI-ESM-LR, BNU-ESM, ACCESS1-0, MIROC-ESM, MIROC-ESM-CHEM, and MPI-ESM-MR models had better performance than similar models. It was also found that IPSL-CM5A-LR, CNRM-CM5, CSIRO-Mk3-6-0, CESM1-BGC, and GFDL-ESM2M had the lowest correlation between observational and simulation data of mean monthly precipitation. CONCLUSION: According to the results, this method could provide a good estimate in the base period (1976-2005), compared to the data of the Hamedan synoptic station, and was more accurate compared to the single implementation method of each AOGCM model. The results of EP of models in the future period (2020-2049) showed that precipitation will not change considerably in the future and will increase by 0.23 mm. In addition, the average, maximum, and minimum annual temperatures will increase by 1.54°C, 1.7°C, and 1.40°C, respectively.

P urpose- Unproductive activities refer to economic activities which do not have a positive effect on GDP, but have high profit and returns, which can eliminate productive activities. This is a phenomenon that has occurred in Iran in the last three decades. The aim of the present study is to analyze the factors causing and spreading unproductive activities using Fumanat area as the context. Design/methodology/approach- The study area is Fumanat, one of the historical regions of Gilan. The type of research is qualitative. In order to collect the required data and information, we conducted the various steps: First, using secondary data, the study illustrated changes in the share of employment in the economic sectors of the region, changes in the area of agricultural land use, as well as changes in the level of built land use. Second, conducting interviews with different business owners of each household, the common activities of households were studied to determine the evolution of productive activities in the sample villages. The common activities of households and among them unproductive activities were identified by inductive method. In order to understand the factors affecting the creation and expansion of unproductive activities, the qualitative approach of grounded theory was used. Findings- The study indicates that in the mountain zone, 39.1 percent of jobs, in the foothill zone, 32.3 percent of jobs, in the plain zone, 41.9 percent of jobs and in the coastal zone, 30.2 percent of jobs, can be categorized as unproductive activities. The existence of uncertainty, lack of support for productive activities, the property rights issue, inadequate privatization and dysfunctional institution system affect the expansion of unproductive activities in the region. Originality/value- Various studies have examined productive and unproductive sides in economic endeavors, most of which considered them with a macro point of view. The present study tries to investigate the contextually of the factors underlying these changes in a rural space and community.