مهدی احراری

A review of empirical studies in the field of insurance of upstream oil and gas projects suggests that domestic insurance companies and insurance consortiums in Iran rely on the experience of reinsurance companies to determine premiums and risk conditions. Given the economic sanctions and restrictions on determining precise premiums and conditions for direct insurance and reinsurance of oil assets, it is necessary to establish a method to determine premiums even under normal circumstances that can be referred to international reinsurers. To address this need, the present study adopted an empirical method that uses risk-based valuation and the monetary value at risk (VaR), which covers a wide range of relevant oil and energy insurance aspects. The results showed that the research method can determine the premium of oil assets following international standards, taking into account expert opinions and other domestic considerations.IntroductionOil and gas continue to be among the primary sources of energy globally, hence a crucial and fundamental part of the world economy. The various sectors within this vast field offer significant capacities and resources at a large scale, including research, equipment, and resources for exploration, development, and utilization, as well as the derivatives in the real sector processes. In addition, transportation, exchanges, transactions, physical markets, and stock exchanges also play a significant role in this industry. The world economy is thus highly dependent, both directly and indirectly, on the oil and gas industry. It is evident that the global oil and gas industry involves a vast amount of capital and risk, which is more complex and extensive than one may imagine. The industry interacts with numerous sectors of the economy, with extensive links that exceed beyond a single field. Considering the relatively small share of oil and energy insurance in the portfolio of the insurance industry, there are various factors that prevent the entry of insurance services into this area on a significant scale. One significant obstacle is the lack of scientific studies on determining the value at risk for oil assets, which is a crucial factor in determining the volume and size of insurance premiums for insurable oil and gas assets. Using the valuation and estimation of monetary VaR of oil assets, the present study aimed to develop a method for insurance companies to determine the insurance premium of oil and gas assets. An example was provided to demonstrate the applicability of the proposed method in practice. Materials and MethodsTo conduct a risk-based valuation, the study employed Smith’s method as well as the method proposed by Knapp and Heij in order to estimate the value at risk for oil assets.The NPV for the valuation model of exploration and development risk will be as follows (Smith, 2004): (1)Where CF0 is the drilling cost,  is the probability of a failed well and {CF1, CF2... CFr} are the expected cash flows in case of success of the well and (i) is the discount rate.According to Knapp and Heij (2017), identifying risk factors, which are variables that pose a risk for an oil asset, is crucial in estimating the value at risk. The risk factors are evaluated based on their probability of occurrence.The monetary VaR is estimated based on the insurable value of a physical asset, which is typically the replacement cost or the actual cash value of the asset covered by standard insurance policies.To estimate the value at risk, two probabilities are combined, which are determined based on the total insurable value (TIV). For instance, if there are five risk groups denoted as j (j=1,...,5), vj represents the sum of the insurable value for each type. TIV is defined as the total of all five groups, as follows:            Furthermore, Pinc represents the probability of an event occurring within a year. Pj is the conditional probability of damage in group j occurring in relation to a particular event. Then monetary VaR is then defined as follows: (2)It is important to note that TIV is derived from the method proposed by Smith (2004), which can be used to assess the value of the entire property or its individual parts and components.The insurance rate and premium can be estimated on the basis of the model of exploration and development risk, along with the future discount rate. This estimation includes the initial cost (drilling or installation cost) CF0 and is given by the following equation:NPV, in Relation (1), is replaced by the future value (FV) or the total insurable value (TIV) of the oil asset.CFt = CF0: NPV is equivalent to book value or price determined by official experts or official pricing authorities.PDH: Probability of occurrence of major risks, which is considered equivalent to catastrophic risks leading to total damage.i: It represents risk insurance premium, which is equivalent to the probability of the occurrence of conventional risks that each oil asset faces according to its specific conditions.Now Relation (1) will be changed to Relation (3):  (3)Now monetary VaR is calculated as follows: (4)In equation (4), V is TIV, which is equivalent to FV calculated based on Relation (2).Results and DiscussionThe study used the information on the insurance policy of HP-2000 drilling rig of North Drilling Company.               Table 1 Information on the HP-2000 drilling rigThe value of the drilling rigReinsurance premium rateMarket premium rateInsurance premium12000.0040.00283.4(billion rials)  (million rials)* Source: issued insurance policyThe future value of the drilling rig for one year is described in the following table:Table 2 The future value of the drilling rigNPV iFV12000.00220.0032400(billion rials)  (billion rials)* Source: research resultsThe monetary VaR based on the future value at risk (FV), which is equivalent TIV, for the insured drilling rig is as follows according to Relation (2):Table 3 The monetary VaR of the drilling rigFV=TIV  MVR24000.00220.84.3(billion rials)  (million rials)* Source: research resultCatastrophe risk (Pinc) and the 5-fold decomposed risks of the oil rig are determined based on expert opinion, which will be the basis of monetary VaR estimation.The premium values ​​and the rate calculated based on the monetary VaR were compared to the premium values ​​in both cases of reinsurance and market (Table 4). Premium rate is obtained by dividing premium, which in the proposed methods is equal to Monetary VaR (MVR), by oil rig price.Table 4 Comparison of the insurance premium rate based on the MVR method with the reinsurance and market rateMVR rateReinsurance rateMarket rate0.00350.0040.0028* Source: research resultsConclusionThe present study highlighted the characteristics and significance of the oil, gas, and petrochemical industry within the global economy, emphasizing the extensive interactions of this industry with various sectors of the economy, particularly in the field of insurance.The study used a distinctively innovative methodology which combines Smith’s (2004) risk valuation of oil assets with Knapp and Heij’s (2012; 2017) monetary VaR approach to determine the insurance premium rate. The proposed research method allows for the determination of an insurance premium rate that is equivalent to international reinsurance rates, based on the factual, environmental, and market conditions. The study offers insurance and oil engineering experts the possibility of calculating an appropriate insurance premium rate for an oil project based on the identified risks using empirical and technical knowledge, as considered in the proposed method.

The efficiency of the insurance market is not permanent and absolute and the market is not always working properly and so-called economists often fail to allocate resources efficiently. The philosophy of business oversight that is shaped by the market and operates according to its rules is to identify the failures of the market mechanism that lead to market failure. Accordingly, supervision in the insurance industry is also focused on dealing with market failures in this area. In this paper, we examine the risk management in the insurance industry based on the methodological framework of the economics of transaction costs, from the perspective of the structure of the insurance market in Iran. The results of the analysis showed that the reality of the insurance market of the country has a significant deviation from the conventional and favorable economic frameworks, which is considered by the policymakers and legislators (Creating a conventional competitive environment free from insufficiency and failure); and in this unconventional environment, many market-based laws and regulations and policies not only don't reduce transaction costs to develop and expand insurance institutions but also reinforce divergent risk structures at the level of insurers and It will have anti-development and destructive effects.

Upstream and downstream activities of the oil industry have to deal with mitigating risks of material and human loss associated with the use of industry assets, including through insurance cover. One of the important issues in insuring oil assets, is determination the value at risk of the asset in question. The main purpose of the present study is to fill the gap in terms of a scientific methodology for estimating the monetary value at risk (MVR) of a petroleum property and thus help in setting the correct insurance premium for any given oil asset. We use our method to calculate the optimal value at risk of an oil asset insured by Iranian insurance companies. Our estimated result is close to the actual premium charged. It thus offers us a scientific method, with high accuracy, which can be used to calculate risk-based valuation of oil assests and the associated insurance premium estimate.

In this research, we develop a method for measuring resilience for Tehran’s ecosystem against air pollution. Resilience has been proxied by the largest Lyapunov exponent (LLE), so that the positive LLE, which indicates a chaotic system, implies a weak resilience. The data used in this study is the daily average of the Air Quality Index (AQI) in 1826 day for the period 1390-1394 (2000-2014). The results show a positive LLE in the AQI, implying a chaotic system. Therefore, resilience of Tehran’s ecosystem against air pollution can be considered weak, making it vulnerable in confronting with shocks. Hence, attention to resilience in economic decision-making and urban management is very important.

The role of customer relationship management as a strategic tool in development of manufacturing and service organizations, and also acquisition and retention customers in competitive industries, is undeniable. Identification, valuation and classification of customers and allocating resources to them based on their value for organization are the main concerns in customer relationship management. One of the most important tool in this direction, is calculating and predicting customer lifetime value (CLV). “CLV” is a value which is expected customer bring to the organization in specified period.
In this paper, calculating and predicting customer lifetime value is as a key tool in the implementation of customer relationship management in banking. The GMDH neural networks due to its high performance in terms of prediction, is applied and with genuine customer demographic and transactional information of a private Iranian bank , the CLV forecasting is evaluated. The results show that this tool can be used to accurately predict over 90% of customer lifetime value.

This paper attempts, to examine the key economic theories on the subject of fertility since Adam Smith until modern times, and also tries to present a proper division of the theories. Based on the findings of this study, classification the theories into micro and macro is the best classification, although, micro theories have more theoretical strength. However, micro theories are not totality of integrated and there are vast differences between them. On the other hand, there are commonly important criticism to the economic theory including economic theories of fertility, ignoring role of institutions. Actually, various studies of the institutionalists and cognitive scientists, show that assuming perfect rationality, that is the cornerstone of the economic approach, is not true; therefore, in analyzing the behavior of people, factors such as culture, ideology, common, etc. that institutionalists bring them under the institution definition, should be noted. It should also be considered in the analysis of fertility. Various studies have shown that institutions have important role in fertility, while that in economic analyzes this issue is neglected.

There are numerous studies on life insurance using different approaches; however, less attention has been paid to the methodological aspects of the issue from a cognitive point of view. This study is an effort to present a research method based on the recognition of different dimensions related to the issue of life insurance. The findings of this research based on theoretical and empirical studies, offer a combined methodology emphasized on institutional and cognitive analyses as well as designing a mechanism to clarify and analyze the issue of life insurance. According to the suggested methodology in this study, the presented strategies are based on cognitive analyses consisting of redesigning of methods, structures, and the strategic-operational objectives.

While many studies have been conducted regarding the analysis and risk assessment in the insurance, less attention has been paid to cognitive and objective aspects of uncertainty concept. The role of insurance companies to cover existing uncertainty in the framework of legal contracts can be crystallized. Thus, the measurement unit of dealing between insurer and insured is transaction. Imperfect and asymmetric information, in the form of bounded rationality, the greatest contribution to the creation of transaction costs due to adverse selection and moral hazard. Transaction cost economics approach, which is based on the new institutional economics approach, is the method for explication, analyzing, and prescription to reduce transaction costs (due to formal and informal institutions) and consequently the associated risks. There is much evidence that can be through deep underastanding of transaction cost concept and institutional factors, much of the relevant risks identified and the stability controled and managed. In addition, the role of government institution in risk management, in terms of Sovereign duties, Legislation and Policy in reducing transaction costs in downstream entities has fundamental importance. Therefore, risk management structure can be designed and organized based on transaction cost economics approch associated with Standard risk assessment system, can be designed and organized.

In general، energy prices، such as those of crude oil، are affected by deterministic events such as seasonal changes as well as non-deterministic events such as geopolitical events. It is the non-deterministic events which cause the prices to vary randomly and makes price prediction a difficult task. One could argue that these random changes act like noise which effects the deterministic variations in prices. In this paper، we employ the wavelet transform as a tool for smoothing and minimizing the noise presented in crude oil prices، and then investigate the effect of wavelet smoothing on oil price forecasting while using the GMDH neural network as the forecasting model. Furthermore، the Generalized Auto-Regressive Conditional Hetroscedasticity model is used for capturing time varying variance of crude oil price. In order to evaluate the proposed hybrid model، we employ crude oil spot price of New York and Los Angles markets. Results reveal that the prediction performance improves by more than 40% when the effect of noise is minimized and variance is captured by Auto-Regressive Conditional Hetroscedasticity model.

While many studies have been conducted regarding the relationship between life insurance and economic growth based on mainstream economics in the context of macroeconomic growth models, less attention has been paid to the aspects of its development. This paper tries to appraise the impact of life insurance development on national product. Accordingly the Human Development Index as an indicator, has been used for assessing the impact of life insurance on national product and the causal relationship between them is analyzed. The results indicated that there is a nonlinear two-way causal relationship between human development index and per capita life insurance. In addition, our results indicated a more significant effect of life insurance on human development in Iran.

Beyond the pessimistic perspective of the impact of population growth on economic growth, institutional approach which is in contrast with the mainstream neoclassical growth models, have presented different and somehow positive results. In this paper, we used hybrid GMDH neural networks and genetic algorithms, based on two variables: population growth and fertility, to model and predict GDP growth. The results showed that first; population growth has considerable effects on economic growth. Second, the economic growth is the short term (and non-linear) result of population growth. Moreover, GDP growth has been forecasted based on various scenarios of population growth and total fertility. The finding indicated that the best forecasting is related to low population scenario and slow increase total fertility scenario.

In this paper, laptop price estimator is developed by three approaches: Hedonic Regression, Artificial Neural Networks and ANN-GMDH. The data for this research is gathered from Tehran Bazar Reza and from laptops’ manufactures’ official websites. The results show that Artificial Neural networks’ model is the best estimator and its error is less than the other two estimators. Also, CPU Cache, DVDROM, Graphic Card Memory and Installed Windows on laptop positively affect the price of a laptop. By considering the result of this study, laptop importers can reach to more benefits by importing those laptops that have high willingness to pay by its buyers.

There are few theories that can explain social changes, especially total fertility, based on economic variables changes. Inglehart’s Cultural Revolution theory explains social changes that have been affected via economic variables. In this research, we forecast of total fertility of Iran based on the economic and social variables in three different economic scenarios includes; current trend continues, removal subsidies effects and prospect writ 2025. Our findings show that total fertility will decrease based on every economic scenario that is compatible with Inglehart’s Cultural Revolution theory.

This paper aims to find an approach for evaluating and ranking customers, in order to help a bank take effective and strategic decisions in providing services to each customer. Recognition of different ranks of customers based on financial, demographical, and residential features, as effective factors in Customer Lifetime Value (CLV), will help design an appropriate mechanism, which would provide each customer with customized services. In order to calculate the CLV and design such mechanism, the GMDH neural network methodology is used, where both residential and commercial type of demographical and financial variables for customers from two Iranian banks are used as the neural network inputs. Results reveal that financial variables have the most impact on the CLV.

In this paper an attempt is made to identify the rules that determine changes in oil prices behavior in order to better forecast the oil market. Rule extraction in this research is done by the GMDH (Group Method of Data Handling) algorithm according to the Fujimoto and Nakabayashi (2001) approach. The results confirm that while there are not any absolute rules in the oil prices behaviour, we can extract relative rules on frontier points in various position of the oil market.

Population growth is a phenomenon that may not be explained only by relying on economic factors. Thus, this article tries to explain population growth issue according to Inglehart-Welzel's Modernization and Cultural Change Theory besides economic factors. It also tries to take a multidisciplinary approach to project and model the strategic variable of population on the basis of socio-economic variables influencing it according to Inglehart's theory up to 2025 in the framework of three economic scenarios, i.e. continuing status quo, the effect of Subsidies Target-Orientation Law and the fulfillment of Iran 2025 Vision goals. The results show that population growth in each scenario follows a decreasing trend asserting Modernization and Cultural Change Theory on the embrace of post-materialistic values. Making the comprehensive population policies according to developmental and multidisciplinary perspectives is a must in Iran's strategic and long-run planning system in a way to project and analyze the future socio-economic and cultural situations.

This paper proposes a new forecasting model for investigating relationship between the price of crude oil، as an important energy source and GDP of the US، as the largest oil consumer، and the UK، as the oil producer. GMDH neural network and MLFF neural network approaches، which are both non-linear models، are employed to forecast GDP responses to the oil price changes. The results are compared with the results obtained by the ARIMA linear model. Using the annual data of these countries from 1952 to 2010، the empirical results indicate that the GMDH neural network using lagged GDP and oil prices yields the least error in forecasting for the US and the UK.

The phenomenon of globalization is one of the most debated issues facing countries in today’s world. There are many different opinions concerning this issue. Investigation of the extensive impacts of this process on different dimensions of human life in political, economic, social and cultural spheres has been preoccupying thinkers, politicians, economists and cultural experts around the world. This study has evaluated various effects of economic globalization on total labor demand broken into skilled and unskilled labor in Iran. In this study we use two models of ARDL and GMDH neural network and also two indexes of foreign direct investment and openness as indicators of globalization for investigating and forecasting the effects of globalization on the labor market. The study based on ARDL approach in the 1353-1385 period shows that globalization indexes have a positive impact on labor demand, but they do not have much impact on labor demand in the short run with this effect becoming increasingly significant in the long run. Also these impacts are greater on the demand of skilled labor than unskilled labor. Finally this study indicates that in all cases, GMDH neural network is a more efficient approach in forecasting employment impacts than ARDL.

In this article we use a GMDH neural network model for modeling and forecastinginflation in Iran based on fundamental and Technical methods. It is shown that theinflation lags, m1, m2, oil revenues and exchange rate of parallel market, are the mostinformative indicators about future price movements respectively.