BACKGROUND AND OBJECTIVES: The estimate of reserved claims is based on the prediction of the final amount of claims that have not yet been settled and which the insurer has undertaken to pay. The Micro-level approach estimates the amount of each unsettled claim separately. In this context, the time taken to settle a claim is an important variable, as large claims usually take longer to settle and may not be paid in the relevant financial period. Non-payment of claims may be due to a lack of timely reporting, a high volume of cases or legal complications. Therefore, there may also be censored data. In this article, we use the copula function approach to model the dependency structure of the settlement duration and claim amount variables.METHODS: In this study, the amount of each unpaid claim is estimated separately using a Micro-level approach. For this purpose, the duration of the settlement of each claim is considered as a variable that depends on the amount of the claim. Based on the modeling of the dependency structure between the claim amount and the settlement duration using the copula function and using the general characteristics of the claims as predictor variables, each unpaid claim is estimated. The marginal distributions of the claim amount and the settlement period based on covariates explain the stochastic behavior of each of them and are modeled separately. In the copula function approach, the dependence structure of the variables can be considered separately from their marginal distributions. By choosing or constructing an acceptable and appropriate copula function with the dependence structure of the claim amount and the duration of its settlement, and taking into account the particular characteristics and conditions of inflation, the amount of an unpaid claim can be estimated more accurately. In this study, the accuracy of the estimation and the validity of the proposed model are evaluated using simulations.FINDINGS: The proposed method is implemented for the data collection of one of the insurance companies regarding the cases of the employer's professional liability claims in 8 years, from March 2013 to March 2021, which includes unpaid claims. In order to evaluate the error in estimating the claim amount with this method in this data set, 1000 samples are taken from the data whose claim amount is known and settled and each time a number similar to the actual number is censored, the known values are censored and their amount is estimated. Then the estimation error is calculated using the criteria mentioned in the article. And finally, it can be seen that the results have a good accuracy rate.CONCLUSION: In the article, it can be seen that the selected copula function has acceptable results for the estimation of reserved claims.

Many pieces of research have investigated the environmental variable including environmental beliefs, values, attitudes, knowledge, and behaviors among Iranian people, but their coverage has not gone beyond a few provinces. This research investigates the status of Iranian's environmental values (in Micro and macro level) in national level and gone beyond description by targeting explanation of Iranian's environmentalism. in this article, the research Method is secondary analysis that uses available data in World Values Survey (WVS) (in Micro level from Iranian size sample of 2667 persons and macro level from worldwide size sample of 257597 persons). The results show that among Iranians, mean of concern for quality of world environment is 3.61, mean of concern for Iran environment is 3.58, mean of environmental willingness is 2.43, and priority environment protection against economic growth is 0.47 that is good status in comparison with other world countries. Also, Schwartz's spiritual values, belief God are strangest explanations for Iranian environmentalism. Dominant social pattern toward environmental, among Iranians, is based on beliefs that support environment and this issue is both a favorable sign for performing supportive environmental policies that certainly accompany public willingness, and places Iran as a potential support for protecting environmental and natural sources International organizations.

Introduction: Post-traumatic stress disorder (PTSD) is a form of anxiety disorders. PTSD typically follows an exposure to severe stress. It is characterized by a particular clinical syndrome, including re-experiencing symptoms and alterations in arousal, avoidance, cognition, and mood conditions. Recent evidences propose that Micro-RNAs are crucial epigenetic players in mental disorders. It has been demonstrated that Micro-RNAs are promising non-invasive biomarkers for different mental health disorders. It has been reported that the levels of Micro-RNAs have been changed in psychotic diseases, including Alzheimer’s disease and PTSD.Conclusion: Micro-RNAs seem to play a role in pathophysiology of psychological diseases. In this article, we discussed the new findings suggesting a relationship between Micro-RNAs and PTSD as well as the possible roles of Micro-RNAs in diagnosis and treatment of this mental disorder.

Insurance companies usually use the chain-ladder method in their fi nancial statements to predict loss reserves. The chain-ladder method is based on aggregated data and development years of claims in run-off triangles. This triangle is a summary of an underlying data-set related to the development of individual claims. This paper used the framework of Position Dependent Marked Poisson Processes and statistical tools for recurrent events in individual claims for a method of reserve as a Micro-level stochastic loss reserve. Detailed information concerning damage occurrence time s, loss reporting delay times, intervals between payments, the values of their payments, and the final settlement times of claims are used to calculate the Micro-level reserves. To validate the new model, the data-set from an Iranian insurance company is considered. Using this data-set and the simulation of Micro-level stochastic loss reserving model, it was shown that the use of Micro-level stochastic loss reserving model is a close estimate to the real value of the required loss reserve in the future years.

This research is aimed at developing a model for measuring and comparison amount of supply and demand for different urban services from quality of life and equity perspectives, in urban built-up areas. This paper explains different steps of implementing the model as a tool for evaluating accessibility of residents to various services according to two main criteria: Land per capita and distance to services. In developing the model, geographic information system is used as a spatial planning support generator. The model has been tested in an urban area located in 7th regional municipality of Tehran, the capital city of Iran, and its result have been compared with outcomes of traditional techniques such as zoning. The results show that the model is effectively proper to clarify different levels of shortcoming in accessibility to urban land use services and improves accuracy of assessing the amount and location of the shortcomings. Developing such GIS-based Micro-level evaluation model and presenting different approach regarding single-facility and multi-facility’s characteristics of urban services are the specific originality of this research.

Objective: This article seeks to extend the concept of tax elasticity to corporate tax sensitivity. This issue is interpreted as corporate tax stickiness (changes in the corporate income tax to changes in the net income). In other words, in the sense of tax stickiness, the corporate income is analyzed instead of GDP, and the corporate income tax instead of government tax revenues. Theoretically, it is unlikely that the company's tax will always increase. In other words, when the company's income decreases, so does the tax. But given the stickiness of the tax, the pace of change between the two will be asymmetric. Tax policy is one of the most important factors affecting macroeconomic variables. Studying changes in tax revenue in response to variations in GDP is the key concept in this area. Based on the above argument, the main purpose of this study is to examine tax elasticity at a Micro level (called tax stickiness). The rate of change in corporate income tax is compared to changes in corporate income (profit). Tax stickiness exists when the rate of tax reduction is less than the rate of profit reduction. Method: In this study, data were collected from a sample of 284 companies listed on the Tehran Stock Exchange, TSE, in the period 2012-2019. Data were analyzed using a regression model. Result: The results showed that there is no tax stickiness in the studied companies. Also, the effects of the variables of economic growth and capital intensity are not significant. However, financial leverage can decrease tax stickiness. In the third and fourth hypotheses, the effects of economic growth and capital intensity on tax stickiness were tested. It is argued that in the conditions of economic growth and high capital intensity, the level of investment of the companies increases, and the tax revenue from capital raises. Given that there is no capital tax in the tax structure, the lack of effects of economic growth and capital intensity on tax stickiness in the companies under study can be justified. Conclusion: The reasons for the lack of effects of economic growth and capital intensity on tax stickiness can be attributed to government tax policies, reduction of reliance on corporate income tax in the studied years, and low attention to the capital taxation in the tax structure. On the other hand, tax stickiness can be attributed to the expertise of the TSE companies in tax planning compared to the non-TSE companies. In short, given the importance of tax revenue in the current condition of sanctions (reducing economic growth rates), it is desirable to allocate appropriate weight to capital tax in the state tax structure. The positive effects of revealing the uncertain tax situation and the motivation of managers' reward on tax avoidance, and the prominence of these features in the TSE companies compared to the non-TSE companies can be interpreted as non-stickiness of taxes. Also, in terms of the positive effects on tax avoidance, the lack of tax stickiness in the TSE companies can be attributed to the overconfidence of the managers of these companies. All these features can be the reasons for the non-sticking of income tax to the companies under study.