Journal of Economic Modeling Research

---

---

The main purpose of this paper is to measure the multidimensional inequality index. To achieve this goal and answer of what trend inequality has gone through during the study period, using the data of the household expenditure income plan of the statistical center of Iran and also using the Bourguignon index, inequality was measured in several dimensions for the period 1984-2018. In addition, it should be noted that in this study, household expenditures were initially adjusted based on age composition and number of household members by calculating the equivalence scale. This adjustment was made possible by estimating the share of expenditures of different commodity groups by considering its functional form in the the quadratic almost ideal demand system (QUAIDS). Then, using data mining techniques and Principal Component Analysis(PCA), the weight of the studied dimensions in the analysis (income, education and health) was calculated and when measuring inequality, the degree of social aversion of inequality was considered in the form of two scenarios, zero and one. the results of this study indicate that the magnitude of multidimensional inequality per zero value for both the degree of social aversion of inequality parameter and the degree of substitution parameter based on the Bourguignon, index is between 0.28 and 0.41 in urban areas and between 0.26 and 0.41 in rural areas. fluctuations in the Bourguignon index and the Gini index of income have not necessarily been similar. The findings of this study also showed that the size of multidimensional inequality in rural areas is lower than urban areas in most of the years studied. There is an approximate similarity between its trend in urban and rural areas. Inequality in the 1980s was higher than in other periods (despite higher oil revenues than in the previous and subsequent periods and more government shares transferred than in previous periods), in the early 1390s, declined, and then increased again. Finally, the research findings indicate the failure of the egalitarian goals of development programs and thus emphasize the need for a fundamental review of the forthcoming programs with more attention to distribution by the market institution rather than the government.

---

After the victory of the Islamic Revolution and the capture of the spy nest, the West, and especially the United States, in addition to pursuing other tools, has also used the tools of sanctions and has implemented many sanctions against Iran. One type of sanctions is oil sanctions, which were imposed to force Iran to join the international community. The US and its allies' embargo on Iranian oil affects the variables of the Iranian and world economies. For this reason, a computable five-zone global trade model (GTAP) is used to calculate the implications of the game tree between the three independent actors of the United States, the European Union, and Iran. The closing of the GTAP model has been changed according to the assumptions used. The results show that the US, Iran and major oil buyers from Iran are damaged by the sanctions. This damage is exacerbated by increasing oil restrictions. With the escalation of sanctions, the European Union is also gaining negative welfare. In the Nash equilibrium, the United States and the European Union will choose weak sanctions, and Iran will try to circumvent the sanctions. Due to the economic costs of oil sanctions against Iran, the lack of full understanding between the United States and Europe, and Iran's efforts to circumvent sanctions, it seems that the United States will not be able to reduce Iran's oil exports to zero.

---

In the Iranian economy, which has experienced various sanctions, it was necessary to anticipate macroeconomic variables when imposing new sanctions. On the other hand, in the context of sanctions, it is possible to make a more accurate assessment of economic policies in order to be able to respond in a timely manner to these shocks and the need for appropriate planning and security against them. Therefore, in the present study, a macroeconomic model with Mixed-frequency data sampling  has been used,While having a high accuracy in prediction, it is possible that when new information about multivariate variables is obtained, based on it, the previous prediction for the dependent variable of the pattern is revised. The model consists of 27 behavioral equations, 8 communication equations and 33 definitional and union relations and the parameters of the model are estimated using time series data in the period 1338 to 1396. Predictive results show that the use of new observations in high frequency variables in the model has led to improved accuracy in predicting the endogenous variables of the model.

---

In recent decade in developing countries, lack of government budget or lack of access to modern technology, persuade governments to attract private sector participation in the economy. One of the most common methods is Public-Private Partnership agreements. The real implementation of this type of partnership needs to set contracts that satisfies preferences of both parties. This research aims to solve this problem using the solutions available in the Contracts Therory Knowledge. Theoretical modeling with analyzing public-private partnership model, provide an optimal model for BOT contract. We use library method to explain the basic contract and mathematical modeling  by MATLAB software with Particle Swarm Optimization to specify the parameters of utility functions and to provide optimal contract. 
The simulation results for an optimal contract were calculated using the supposed parameters (life time, incom, costs, future incoms discount rate, salvage value of project costs) 38 years (project utilization time), 78% (principal participation after transfer time), 45% (principal participation during the operation), 7% (riskes to the principal).

---

Purpose: The insurance penetration rate is one of the most important indicators used to evaluate the insurance industry of a country. This ratio is also a measure to compare the performance of the insurance industry between developed and developing countries. The aim of this research is to compare the insurance penetration rate and the factors affecting it in high and low income countries.

Methodology: The current research examines the effect of variables such as inflation rate, education, labor productivity, dependency ratio and income on the insurance penetration rate in the period 2011-2021 and using PMG and ARDL methods to derive short-term and long-term equations in 18 countries with income High and low income and the country of Iran pays.

Findings: The results obtained from the estimation of long-term PMG models in high-income countries indicate a positive effect of dependency ratio, income level and fertility level on the insurance penetration rate, as well as a negative effect of inflation rate and labor productivity on the dependent variable, also in selected countries with high income. All the variables, except for education and dependency ratio, which had a positive and significant effect on the insurance penetration rate, are statistically meaningless.   On the other hand, the findings from the estimation of the long-term ARDL model in Kesho Iran show the negative impact of the inflation rate on the insurance penetration rate and the positive impact of the education level, income level and dependency ratio on the insurance penetration rate.

---

Purpose: The aim of this study is to identify and classify insurance customers in order to identify the target population for increasing the profitability of insurance companies, achieving a balance in premium payments, and examining the health questionnaire as an indicator of policyholders' preferences. Moreover, designing a marketing strategy to optimize advertising efficiency.
Method: In this paper, five machine learning algorithms, namely Decision Tree, Random Forest, Support Vector Machine, Naive Bayes, and Logistic Regression, are used to classify customers into two categories: profit-generating and loss-generating. Data from a private insurance company is utilized, consisting of 2,897 observations collected from December 1400 to December 1401.
Findings: By utilizing machine learning methods and focusing on the target population, the chances of success can be increased. The presence of a small number of individuals who significantly reduce the profitability of insurance companies is evident. The pre-existing medical conditions of individuals have a considerable impact on their insurance usage and the damage caused to insurance companies.
Conclusion: Machine-learning methods can provide a comprehensive understanding of insurance customers and their needs. By identifying the target population, insurance companies can increase their profitability and satisfy their customers by addressing their specific demands

---

Based on the stylized fact, the behavior of price in financial markets is not a continuous process, but we observe jumps in the price that can be endogenous or exogenous. it is claimed that the source of exogenous jumps is news, and the source of endogenous jumps is internal interactions between the market agents.  Our goal is to extract these endogenous jumps as a function of the system state variable and time. First, by introducing the Langevin equation as the governing dynamics and linking its parameters with Kramers-Moyal coefficients, we show that these parameters can be extracted based on conditional moments. Next, we use the generalized Langevin equation to model the observed jumps in the data and show that in the new model, the drift coefficient is still equal to the first Kramers-Moyal coefficient, but the diffusion coefficient in this case is lower than the second Kramers-Moyal coefficient. In our model, the jump term consists of two components: jump rate and jump size. We show that these two new components can also be extracted based on Kramers-Moyal coefficients. Also, we introduce a practical criterion based on the fourth and sixth Kramers-Moyal coefficients to choose between the diffusion and jump-diffusion model. Applying the Kramers-Moyal method to extract the generalized Langevin equation shows that this method can accurately reconstruct the process. Tests to evaluate the accuracy of the reconstruction have been used from the information theory. In a practical application, we have extracted the price dynamics of an asset and then shown by simulation that this model is able to answer common statistical questions about stochastic processes with good accuracy. Also, by performing simulations, we show that this model has a good out-of-sample prediction ability. The potential function, which is calculated from the first KM coefficient, is a quadratic parabola for the studied process, and as a result, we have a stable equilibrium at the zero point.

---

     Investigating the spillover effect of logistics performance index on exports in free zones is considered one of the important cases for special attention in these areas, which in recent years has received less attention. Therefore, in this study, by using different methods of spatial panel data, to investigate the spillover effect of the logistics performance index among the seven existing free zones and based on six the performance indices of the logistics industry has been studied during the years 2014 to 2023. This study has investigated the performance of logistics on exports (which is a composite index and areas) in Iran’s free zones by using different spatial regression models. The present study was conducted with the panel data and it shows that findings of this study indicate that the effect of logistics performance index in the SDM model has been confirmed and logistics performance has a positive and significant effect on the export of free zones, so that the growth of logistics indicators in the country leads to growth and speed of exports in free zones. Moreover, investment, labor and the degree of openness of the economy have a positive and significant effect on the export value of free trade zones. Therefore, it is suggested that economic policy makers improve production and export capacity in these areas by improving the logistics, investment and employment performance index.

 

---

Although, input-output (I-O) and general equilibrium (CGE) models are systems based on interrelations between sectors and economic agents. However, they are very different in terms of design complexity, model solving techniques, required input data, outcomes, theorical structure and adopted assumptions.
Therefore, the results of simulating the effects of an economic policy using each of these models will definitely be different. But, avoiding complexity, difficult solving techniques, collecting large amount of data and so on, sometimes make us to use simpler, although less accurate, models. In this case, obviously, the assumptions and restrictions of the model are to be fully noticed, when interpreting the outcomes of simulation. Otherwise, incorrect decision making will be inevitable.In this paper, we assess the impact of price liberalization of electricity, distribution of natural Gas and water on the output and prices of the main sectors of Iran economy. This is done by using a I-O and a CGE, both designed by autors. The simulation is implemented by cutting subsidy payed to final and intermediate consumption of electricity, distribution of natural Gas and water. The outcomes are largely different regarding the amount and the direction of sectoral output and price changes. While the outcomes of I-O model are against this policy, the results of CGE model, in which total output and household consumption increase, are in favor of it. The rise of demand in tradeable agriculture and industries and mining are accompanied with more import, so that their new equilibrium output will be lesser. But, output of non-tradeable construction and low tradeable services increase. The increase of crude oil and natural gas are totaly exported.

---

Due to the position of meat products in the food pyramid and its importance in maintaining people's health and that economic sanctions can have a significant effect on meat consumption through the channel of increasing production costs and increasing the price of meat, the purpose of this research is to investigate the existence of failure There is a structure in the preferences of the meat consumption basket of urban households using the parametric approach and the switching regression framework developed by Ohtani and Katayama (1986) in the period of 2001-2013. The results show a structural failure (change) in preferences suddenly in 2017 and after the withdrawal of the United States from the JCPOA. The results show that after the withdrawal of the United States from the JCPOA, the price of chicken meat has decreased and the price of fish has increased, so that chicken meat has changed from an attractive product to an inelastic product. This result shows that consumers have become dependent on chicken meat and are willing to pay more to buy it. In such a situation, it is important to have adequate and optimal monitoring of the price of chicken meat, because people are forced to pay any price for chicken meat, and the changes of this product can cause the consumption basket of urban households to fluctuate greatly. Also, the estimation of income elasticity shows that chicken meat has changed from a necessary commodity to a luxury commodity after the sanctions. Therefore, to support consumers, it will be the right decision to use income tools and policies that lead to increasing the liquidity of urban households.
 

---

Employment is one of the most important issues that any country faces. Employment plays a vital role not only for individuals but also for the economy as a whole, and provides a deep understanding of the labor market conditions of an economy. In this regard, the minimum wage is an important factor that affects the labor market. The literature on the minimum wage uses two labor market models. The standard competitive model, which predicts that the minimum wage will have negative employment effects. In other words, under conditions of perfect competition, economic theory suggests that a higher minimum wage will lead to job losses, and noncompetitive labor market models, which predict that the minimum wage will have positive employment effects. However, it is generally unclear whether minimum wages have a positive or negative effect on employment, or are ineffective. Therefore, the aim of this study is to examine the effects of the real minimum wage on employment in Iran, within the framework of a multiple regression model and OLS estimation during the period 1379-1400. The results of the regression analysis show that the increase in the real minimum wage has a significant negative effect on employment, so that with a one-unit increase in the real minimum wage, employment decreases by about 0.37 units. Therefore, taking the above into account, it is suggested that the increase in the minimum wage should be made as proportionate as possible to the Labor productivity in the economy