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The Impact of Economic Complexity on Environmental Performance in the MENA Countries
Mr. Ramin Sepahvand, Dr Ali Sayehmiri, Mrs. Asma Shirkhani,
Volume 21, Issue 3 (9-2021)
Abstract
In recent years, economic complexity has played an important role in explaining and revealing the latent facts of the difference in economic growth among the poor and rich countries. In this study, first the effect of economic complexity on environmental performance is investigated in 18 countries of Middle East and North Africa(MENA) using two-stage least squares regression(2SLS) method during 2002-2018. Then, the Environmental Kuznets Curve hypothesis is examined in these countries. The results show an inverse and significant relationship between economic complexity index and environmental performance index, so that by increasing one unit of economic complexity index, environmental performance index decreases by more than 7 units. In addition, the results show that there is a positive relationship between per capita income and environmental performance index, while per capita income square has an inverse relationship with environmental performance index, so Kuznets hypothesis about these countries is not confirmed. Finally, the results indicate a positive relationship between population, urbanization, corruption control, agriculture and trade with environmental performance, while industrialization and education have a negative relationship with environmental performance in the MENA countries.
Futurism the Position of Urban Management in Business Development and Small Urban Businesses: Case Study of Small Manufacturing Businesses and Technical Services in Tehran
Dr Amirhosein Pourjohari,
Volume 22, Issue 3 (9-2022)
Abstract
In today's urban economy, small businesses have found a significant place. The nature and scale of the activities of this type of business cause different reactions to macro-external factors, so that some destructive forces for large businesses may lead to the growth and prosperity of small businesses or vice versa. Thus, urban management can act not as a directly influential force, but as a facilitator. In this study, by studying the macro-political, economic, social, technological, environmental and legal forces, the current situation and the type of influence of these forces are analyzed generally by PESTEL method. Then, using the TAIDA futurology method, the causal relationships between the existing trends and the main uncertainties are determined. The results of the studies show that the existence of economic sanctions and the multiplicity of laws are uncertainties, and future research scenarios can be presented. Accordingly, since the most likely future will be the resistive economy approach. As a result, eight strategies related to facilitator urban management can be presented that are sustainable in all scenarios. These include the realization of integrated management, creation of a support fund, support the domestic production, creation the business clusters at different levels, support the entrepreneurs, development of knowledge concepts and knowledge-based economics in relation to small businesses, development of infrastructure, technologies, production equipment and technical services in Tehran and supporting the development of clean technologies in polluting units.
 

Capacity Measurement of Capital Formation in Isfahan Province Based on Interregional Dynamic Input-Output Model
Mrs. Maryam Amini, Dr. Nematollah Akbari, Dr. Rozita Moayedfar, Dr. Fatemeh Bazzazan,
Volume 23, Issue 4 (12-2023)
Abstract
 The lack of statistical data at the regional level has led to the expansion of non-statistical methods for the regionalization of national input-output tables. The main idea of the current research is the regionalization of national dynamic input-output tables using the extension of the Charm method. This research using this non-statistical method provides an estimate of the sectoral capital matrix in the regional level, and finally, with the help of the numerical index of capital productivity and the Williamson’ capital index and comparing it with the relative advantage index, it measures the capacity of capital formation. Part of it is in Isfahan province. The results show that the industry sector with the largest share of output from the total output of the province has the lowest numerical index of capital productivity and the highest balanced diffusion effects of capital and the highest comparative advantage in 2015.
Introduction
One of the most efficient methods for examining intra-regional economic capacities is the use of intra-regional and inter-regional capital matrix. In Iran, due to the lack of sufficient statistical data, no attempt has been made to estimate the sectoral capital matrix in the regional level. The purpose of the current research is to regionalize the national dynamic input-output table with the help of expanding the CHARM non-statistical method and estimating the intra-regional and inter-regional capital matrix; to provide an analysis of the capital capacity of different economic sectors in the region with the help of these matrices. In the current research, among all the non-statistical regionalization methods of the national input-output tables, the Charm approach has been selected in accordance with the regional data. The reason for choosing Charm method is the existence of Cross Hauling in Isfahan province. One of the problems of Charm's method is the placement of national and regional technology coefficients. This simplifying assumption causes the intermediate demand within the region to increase and therefore the added value, which is estimated as a residual; it will be very small or even negative. For this purpose, the current research will regionalize the matrix of national technology coefficients with the help of spatial coefficients; to solve the problem. By estimating the regional capital matrix, an analysis of the final productivity of the sector's capital factor and inter-sector capital distribution will be presented, and the results of these sectors will be compared with the indicators of comparative advantage of the sector. Finally, the research questions will be answered:
  • Which effect will the adjustment of the national technology coefficients have on the added value of the province?
  • What is the capital matrix of the sector in Isfahan province?
  • Which sector in Isfahan province has the highest numerical index of capital productivity?
  • Which economic sectors in Isfahan province have more distribution of capital formation?
  • What are the economic sectors with the greatest comparative advantage in Isfahan province?
Methodology
At first, it is necessary to estimate the national capital matrix with the help of available data and simplifying assumptions. By estimating the national dynamic input-output table, we will have an estimate of the regional dynamic input-output table with the help of the extension of Charm method. To solve the problem of equality of national and regional technology coefficients, by multiplying the diagonal matrix of spatial coefficients in the matrix of national technology coefficients, we will obtain the spatial technology matrix of the region, and by multiplying this estimated matrix in the resulting diagonal matrix, we will obtain the regional technology matrix. Therefore, smaller regional coefficients will be estimated.
On the other hand, to estimate the intra-regional capital matrix, the difference ratio of the region's output in two periods is used to the same amount at the national level. In this case, the intra-regional capital matrix is estimated. A time interval of one year is considered. The reason for choosing this time interval is that the country's budget is one year and a huge part of the inter-sectoral investment in the region is done by the central government. To estimate the intra-regional capital matrix, the spatial ratio of the region's capital asset ownership to the entire country is used. Finally, by subtracting the national capital matrix from the intra-regional capital matrix, we will get an estimate of the correct inter-regional capital matrix. Finally, with the estimation of the capital matrix, the assessment of the capital formation capacity of the intra-regional sector of Isfahan province is carried out with the help of single-factor productivity analysis of capital and the Williamson index of capital and the estimation of the relative advantage index.
Results and Discussion
In the case that the coefficients of national technology are equal to regional technology, the added value is negatively estimated in four sectors, agriculture, mining, water and electricity, gas and construction. This is despite the fact that in the proposed method of the current research, these positive values are estimated. According to the capital matrix, the most productions were related to the industry, construction and agriculture sectors. Also, the most capital purchases were related to industry, services and real estate sectors. The highest level of sector productivity is related to the communication, mining and transportation sectors. One of the reasons for the increase in user productivity((L↑)/K ) of the sector is compared to other economic sectors. According to Wilsamson's index, the industrial sector, as a supply sector, has distributed its produced capital goods in a more balanced way among the demand sectors. Three sectors, industry, transportation and real estate, have the greatest comparative advantage according to both indicators. But none of the sectors has a high relative advantage.
Conclusion
In summary, the results show that the industry sector with the largest share of output from the total output of the province had low productivity in 2015. Meanwhile, according to Williamson's index, this sector has the most balanced emission effects with other economic sectors, and the results of the previous link also confirm this. Also, based on the RCA and SRCA indices, this sector has a comparative advantage. Therefore, paying attention to new investment in this sector and improving production technology can have good effects on the sector itself and ultimately on other economic sectors in the region.
  

Financing urban infrastructure in Iran's Metropolises with emphasis on city size: The Case of Isfahan Metropolis
Dr Nasrin Karimi, Dr Nematollah Akbari, Dr Shekoofeh Farahmand,
Volume 24, Issue 1 (3-2024)
Abstract
Introduction
Extensive and efficient infrastructure is critical for ensuring the effective functioning of the economy. Investing in public infrastructure represents an essential investment in economic development and standard of living of city residents. Therefore, it is necessary to find new methods of financing in providing services and developing urban infrastructure in metropolises and increasing the welfare of urban society. However, the current approach to revenue mobilization for cities is unlikely to meet the substantial financing needs. Instead, there is a need for a metropolitan public financing strategy that is integrated into national urban development plans and matches national development objectives. In the literature related to city finance, despite the importance of providing suitable urban infrastructures, the discussion about how to fund them, especially in Iran, is rarely done. Therefore, the purpose of this research is to provide a suitable model for providing financial sources for public infrastructure in metropolitan cities with an emphasis on Isfahan metropolis.
Methodology
In this research, a mathematical model for calculating the urbanization tax has been introduced, in which the cost recovery coefficients are related to the optimal size of the cities. Therefore, an equilibrium model is constructed based on cost-benefit analyses and applied to nine Iranian cities with population more than one million people. The panel data regression analysis was performed on a fourteen-year period (2006-2020) using the Transcendental Logarithmic (Translog) function. The obtained results are placed in the basic mathematical model. It should be noted that Excel2016 and Stata12 software were used to estimate the model and analyze the results.
Findings
The results of estimating the regression models related to determining the optimal size of the cities indicate that all the metropolises have exceeded their optimal size. Among the nine metropolitan cities studied, Kermanshah, Karaj and Qom have the largest excess population. Isfahan and Ahvaz have the lowest excess population. The results of calculating the urbanization tax for Isfahan Municipality indicate that the recovery of public infrastructure depreciation costs in the first year can generate more income than the income from property tax for Isfahan metropolis.
Discussion and Conclusion
Providing infrastructure and public services by municipalities for the urban population, especially in metropolises, is a very difficult task and requires access to capital facilities. However, the way to collect these funds and how to provide the infrastructure budget has been less attention. In order to provide public services and urban infrastructure, municipalities should collect the costs related to a certain infrastructure as much as possible from the individuals, companies, localities and groups that benefit from it.
Therefore, in this study, all the urban infrastructures of Isfahan metropolis are divided into three categories based on the benefits they create. The first category is infrastructures whose benefits are assigned to certain individuals and groups. The second category is infrastructures whose benefits are mostly limited to one place or a specific area within the city. The last category also includes those services and infrastructures whose benefits are allocated to the entire city and its residents.
The results show that about 38% of infrastructure costs in Isfahan metropolis are related to the third category. Considering the allocation of these infrastructures to all residents, their cost can be collected through the urbanization tax and according to the optimal size of the cities. The results related to the city size model show that the population of all Iranian metropolises has exceeded its optimal size, so it is suggested to continue receiving infrastructure costs until full recovery.
The results of this research emphasize that although the urban costs have decreased with the increase in population, the urban benefits have decreased more, and in general, diseconomies of scale have been created. However, people will not necessarily involve these diseconomies of scale that they bring to the city in their decisions related to work and migration. Therefore, it is recommended to receive these costs from them.

Economic Sanctions, Exchange Rate and Housing Supply and Demand
Mr Mahrdad Mahmoudian Zamaneh, Dr Morteza Ezzati, Dr Mohammad Jafari,
Volume 24, Issue 2 (5-2024)
Abstract
Introduction
The occurrence of various shocks affects economic variables and change their course over time. Knowing the effecst of such shocks on economic variables is necessary for proper policy making in the economy. Therefore, many researches are conducted in this field in the world. Policy-making without recognizing these effects can result into tremendous challenges. One of the most effective shocks in the Iranian economy is the sanctions, especially the nuclear ones, which have had extensive effects on the behavior of brokers and consequently on the country's economic variables.
Economic sanctions cause a change in the exchange rate by creating a chaotic atmosphere and confusion in the economy, followed by a change in the supply and demand of housing. Therefore, the purpose of this research is to investigate the effect of economic sanctions on the supply and demand of housing through the exchange rate channel. For this purpose, provincial seasonal data for the period of 2011-2021 have been used and Seemingly Unrelated Regression (SUR) model has been used to analyze the data.
Methodology
Different methods can be used to estimate the model of the equations of this study, such as single equation methods or methods of solving simultaneous equations, whose estimates are different. The most common methods of solving simultaneous equations are the two-stage and three-stage least squares regression methods, as well as Seemingly Unrelated Regression, which is used when there is a relationship between the error part of the equations or there is a simultaneous correlation. The method discussed in this research is Seemingly Unrelated Regression (SUR) model or Seemingly Unrelated Regression Equations (SURE), which was proposed in 1962 in econometrics.
Findings
The findings show that provincial gross domestic product, housing prices, and inflation have a positive effect on demand. The variables of stock market index, exchange rate and sanctions have had a negative effect on housing demand. On the supply side, housing price variables, the number of building permits issued, and inflation have a positive effect on the housing supply, while the exchange rate, sanctions, and the price of construction materials have a negative effect on the housing supply. Imports and embargoes have increased the exchange rate and exports have decreased the exchange rate. On this basis, the embargo has both a direct effect and an indirect effect through the exchange rate on the reduction of housing supply and demand.
Discussion and Conclusion
The estimation results for the first equation show that the variables are significant. It can also be said that provincial GDP, housing prices and general price level index have a positive effect on housing demand and with the increase of these variables, housing demand increases. According to the findings of the research and the analysis of the available data, the inverse relationship between the stock market index, the sanctions index and the exchange rate with housing demand is confirmed. So, with the growth of the stock market index, sanctions index and exchange rate, the demand for housing decreases.
In the preliminary results, the estimate for the second equation of the average effect of labor wages as a part of the production cost was not significant. But in estimates, the effect of the price of construction materials is significant. This variable was removed from the model. It can be said that one of the reasons for the non-significance of the wage variable is its low relative growth compared to the growth of housing prices and the growth of construction materials. On the other hand, the share of wages in housing construction costs is much lower than the costs of materials and other costs. This causes the wage rate in Iran to be less effective in housing supply. It can also be said that an increase in the provincial GDP, housing prices and the number of building permits issued increases housing supply.
The results of the third equation show that exports, imports, sanctions index, liquidity volume and provincial GDP explain 99% of exchange rate changes. It is worth mentioning that any increase in exports and sanctions index increases the exchange rate, but with the increase in imports, the exchange rate decreases, which shows the negative relationship between the exchange rate and imports. Since the exchange rate increases under the influence of the sanctions and the exchange rate has a negative effect on the housing demand, it can be said that sanctions have a direct effect on the economic activities of supply and demand due to the disruption of security, certainty and economic stability. Housing has an effect on the supply and demand of housing due to the change in the exchange rate

Urban Morphology and Public Transportation Demand with Special Emphasis on the Form of Urban Road Network
Mrs Zahra Pourahmad, Dr Babak Saffari, Dr Shekoofeh Farahmand,
Volume 24, Issue 3 (9-2024)
Abstract
Introduction
In recent years, the ever-increasing population growth and rampant use of personal transportation and daily trips have caused many problems in the field of transportation, including high fuel consumption, air pollution, noise, high density streets, reduced physical activity, etc. In many metroplolitan areas during the past decades, the sudden increase of motor vehicles has caused heavy street traffic in intra-city trips, and the main reason for this can be considered the weak relationship between urban morphology and transportation, in other words, urban forms that avoid pedestrians and encourage motor trips. Urban morphology is one of the most important and main factors that affect the demand for urban transportation. The quality of land use (density of residential units or their dispersion) forms the important basis of urban morphology. In the formation of urban morphology, natural and human factors play varried roles, among them road network is of paramount importance in construction and morphology of a city. Since urban morphology has a significant effect on urban transportation, how to establish a strong relationship between urban morphology and travel modes has has always been of great interst of researchers. This study is aiming at investigating the impact of morphology characteristics on urban transportation demand. In this research, features of urban morphology, such as overall residential density, connectivity index, and the average width of roads, with the help of demographic characteristics, such as population density, female and female working poulation, total working population etc., on demand for urban transportation have been ivestigated. These include four parameters such as creation of public and personal trips and attraction of public and personal trips on in 186 traffic areas of Isfahan city.
Methodology
This research has been conducted with a descriptive causal approach based on the data and information required in the study areas. To achieve the research goals, 186 traffic areas of Isfahan City have been studied. For analyzing the characteristics of urban morphology, including average width of roads, overall residential density, and connectivity index (street density), in the form of GIS maps have been investigated, and for demographic characteristics, the population and housing census map of Isfahan City was obtained and researched from the Deputy Planning and Human Capital Development Organization of Isfahan Municipality. Then, using the map of 186 traffic areas of Isfahan City, the amount of these variables was calculated and extracted by GIS software. Moreover, the information related to urban transportation demand based on public transportation demand, including public travel creation, public travel attraction, and personal transportation demand, including personal travel creation and personal travel attraction from the origin-destination matrix of the year 2021 of Isfahan city on a normal working day and at the peak hour of 7:00 to 8:00 a.m., the transportation and traffic department of Isfahan municipality has been obtained and used for evaluation. In the present research, in order to reach a complete and comprehensive answer, after extracting the data from GIS software, the Eviuse software was used. According to the number and nature of the research variables, the specification of the model is done using the multivariate regression method and the weighted least squares method. GIS software was also used for drawing the maps.
Findings
The research findings show that in the TSS and JSS models, with the increase in the average width of traffic areas, the creation and attraction of personal travel have also increased, and in the TSO and JSO models, the creation and attraction of public travel have decreased with the increase in the average width of traffic areas. In TSS model, the coefficient is negative and in JSO model, the coefficient is positive, which shows that with an increase in the overall residential density, the use of private transportation decreases and the use of public transportation increases. In terms of street density, which also indicates the connection index, the coefficient value is positive in TSS and negative in TSO model. The results also show that women in general use public transportation, but working women use private transportation more. The estimation of TSS model shows that as population is aging in the traffic areas of Isfahan City, the preferrence in using personal transportation has been rising. In JSS model, the parking variable has a direct relationship with the attraction of personal travel. In the personal travel attraction model, health-therapeutic use and commercial use have a direct relationship with the attraction of personal trips, and in the public travel attraction model, commercial, educational, and health-therapeutic uses have a direct relationship with the attraction of public trips. Finally, the increased number and  variety of the users will also increase intra-city trips.
Discussion and Conclusion
In this research, an attempt has been made to investigate the effect of urban morphology variables on urban transportation demand with a general perspective. The results of the estimation of the research models show that the widening of urban roads as a management policy for intra-city travel demand increases people's trips using personal transportation and as a result, increases the number of road users. Street density, which indicates the number of higher streets and therefore greater connectivity, has a direct relationship with citizens' use of private transportation. Residents of areas that have higher overall residential density and population density, which indicates denser urban fabric and more dispersion, are less likely to use personal transportation, and people in those areas prefer to use public transportation and walking options. Also, as the age of the residents of the area increases, they use private cars for their daily trips. Another examination of the results of the research indicates that areas with parking facility, will attract passengers who have used private transportation compared to the areas that do not have such possibility. In general, as the total working population increases in the areas, they use personal transportation to go to their workplace, and it can be said that the female population uses public transportation more for their daily trips. In the public travel attraction model, the positive coefficient of commercial use is higher than the coefficient of health-therapeutic use and educational use, and with the increase in the number of commercial uses, the attraction of public travel increases to a greater extent. In the personal travel absorption model, the effect value of the healthcare usage coefficient is higher than the commercial usage coefficient and it shows that with the increase in the number of healthcare usages, the absorption of personal travel will increase. Moreover, the increased number and  variety of the users will also increase intra-city trips.

Behavioral and Non-Behavioral Factors Affecting Housing Prices and Inflation in Iran
Dr Aliakbar Gholizadeh, Dr Shahla Samadipoour,
Volume 24, Issue 3 (9-2024)
Abstract 
  Introduction
Various dimensions of housing heterogeneity have gained relative popularity in recent years. The most essential aspect of housing heterogeneity is a set of differences including technical, governance, socio-economic, and ecological differences of each residential unit. The origin of these distinctions is an objective matter that is regarded as an essential aspect of the research framework, but is frequently overlooked in managerial decision-making. In the scientific community, the social, technical, and economic dimensions have received the most attention, whereas the role of the behavioral characteristics of investors in housing prices has received scant attention. Focusing on the aspects of behavioral economics theory, the present study analyzes the heterogeneity of the behavior of housing investors, as well as the internal and external factors influencing housing prices and their effects on inflation in Iran from 2011 to 2020.
Methodology
The primary objective of this article is to evaluate the effects of heterogeneous behavior of housing market investors on housing prices and the effects of heterogeneous behavior of housing market investors on inflation via housing prices. The following equation is used to determine the price of a house:
POH=f1(A1. A2.A3)                                                                                                                                                                                                                 (1)
In Equation 1, POH  represents the expense of housing, A1  is a vector of exogenous factors influencing housing prices, A2  is a vector of exogenous factors influencing housing prices, and A3  is a vector of investor behavioral variables in the housing sector.
Overoptimism and herding effect are considered to be two behavioral variables of housing sector investors: 
HBHt=1Tt=1T|et-em|                                                                                                                                                                                                              (2)
OCHt=QtSt                                                                                                                                                                                                                                  (3)
In equation 2, HBHt  represents the herding effect of investors in housing sector, et  represents the housing return at time t, and em  represents the average return of housing market. In equation 3, OCHt  represents overoptimism, Qt  represents the number of building permits issued, and St  represents the quantity of residential unit investment.
Inflation is also viewed as a function of housing prices and other macroeconomic factors according to the equation below:
INFR=f2(POH.B)                                                                                                                                                                                                                        (4)
In equation 5, INFR  represents inflation rate and B is a vector of independent variables influencing inflation.
Findings
During the period 2011-2020, land price, population growth rate, liquidity, and herding effect had a positive significant effect on housing prices in Iran, according to estimates. Conversely, the number of residential units constructed and the exchange rate has had a negative significant impact on housing prices in Iran; while, the variables of interest rate, per capita income growth rate, and overoptimism had nonsignificant effect on housing prices. Regarding the factors influencing inflation, the data also indicates that the housing price, exchange rate, and liquidity had a positive significant effect on Iran’s inflation rate between 2011 and 2020. In contrast, population growth and per capita income growth had a significant negative impact on inflation; while the interest rate had a negative but nonsignificant impact on Iran’s inflation rate over the period under review. Due to the nonsignificance of the effect of overoptimism on housing prices in the seemingly unrelated regression (SUR) model, it can be concluded that housing prices do not mediate the effect of overoptimism on inflation. Due to the significance of herding effect on housing prices, however, the mediating effect of housing prices and herding effect on inflation is confirmed.
Discussion and Conclusion
In this article, SUR was used to analyze the effects of behavioral and non-behavioral factors on housing prices and inflation in Iran from 2011 to 2020. The following results were obtained:
• An increase of 1% in internal factors affecting housing prices, such as land prices, the number of completed construction units, population growth rate, and per capita income, have resulted in respective increases of 1.19, -1.36, 0.59, and -0.015 in the Iranian housing costs.
• An increase of 1% in the behavioral factor of herding effect has resulted in a change of 0.77% in housing prices in Iran.
• A 1% increase in housing prices, currency prices, and liquidity has resulted in an inflation rate increase of 0.18%, 0.92%, and 0.17% in Iran, respectively. A 1% increase in the population growth rate and the per capita income growth rate has caused a decrease of 1.53% and 0.141% in inflation rate, respectively.
Through housing prices, the behavior of investors in the housing sector can indirectly influence the inflation rate. Considering the positive impacts of herding effect on housing prices and housing prices on inflation rate, it can be concluded that herding effect has a positive impact on inflation rate.
In accordance with the stated findings, the following policy recommendations are provided to prevent the rise in housing prices and inflation:
Considering the positive impact of herding effect on the housing price and, consequently, the inflation rate, it is necessary to take measures to control and reduce emotional and irrational behavior of investors in housing sector. Since the internal factors of land price and population growth rate have a positive effect on the housing price, while the number of completed construction units and per capita income have a negative effect on the housing price, it is recommended that government provide unused governmental lands and remove obstacles to complete half-finished buildings that have been halted for legal reasons, and assist in supplying more housing to reduce its price. In addition, government should help control housing demand and reduce demand pressure by adopting population control policies and establishing suitable working, health, and educational conditions for the villagers, to diminish immigration level.  

Unemployment and Crime in the Iranian Cities A Spatial Econometric Approach
Dr Elham Nobahar, Dr Seyed Kamal Sadeghi, Mr Hadi Kheirollahi Zaki,
Volume 24, Issue 3 (9-2024)
Abstract
Introduction
Crime is a multifaceted phenomenon that has always attracted the attention of economists, sociologists, lawyers and psychologists. Many experts and economic pioneers consider it necessary to achieve economic development to improve the level of security and reduce crime in the society. Since the occurrence of any phenomenon is affected by various factors, the occurrence of crime as an undesirable phenomenon is not excluded from this rule. Various economic, social and political factors affect crime in society. Identifying these factors can help a lot in the correct understanding and appropriate policy making in order to control and reduce the crime rate in the society. Meanwhile, one of the most important economic factors affecting crime is unemployment. Unemployment is one of the most important macroeconomic variables, which clearly affects many social phenomena, including crime. In this regard, the main goal of the present study is to investigate the relationship between unemployment and crime and to identify factors affecting crime in the Iranian cities. The statistical population of the current research is the cities of Iran and the time range under investigation is 2016.
Methodology
In this study, the spatial causality test was used to investigate the relationship between unemployment and crime. The first step in investigating the spatial causality relationship between the studied variables is to perform the spatial independence test of the variables. In the second step, the existence of spatial dependence between variables is examined. If both the investigated variables have a spatial structure and there is a spatial dependence between the two variables, then the spatial causality test is performed in the third step. In this study, the spatial econometric approach has also been used to estimate the crime model in the cities of Iran. In this regard, the presence of spatial effects in the model has been tested using Moran's I test, and then the most appropriate spatial regression model has been selected and estimated based on the Lagrange coefficient (LM) test and the LR diagnostic tests. The software packages used in this study are Matlab 2023, GeoDa 1.16 and Stata 15.
Findings
The results of the spatial tests show that both crime index and unemployment rate have a spatial structure and the spatial dependence between these two variables was also confirmed, so in the third step, the spatial causality has been tested. The results of spatial causality test indicate the existence of a two-way causality relationship between the crime index and the unemployment rate. In other words, unemployment was the cause of crime during the period under investigation, and unemployment also led to the occurrence and increase of crime. According to the results of the spatial causality test, the crime model of the Iranian cities was developed in terms of the unemployment variable and several control variables. In order to estimate the model, the presence of spatial effects was first investigated using Moran's I test. The results of this test indicate the presence of spatial effects in the model. Also, based on the results of the Lagrange coefficient and likelihood ratio tests, the Spatial Durbin Model (SDM) was chosen as the most appropriate method for estimating the model. The results of the estimation of the crime model indicate that the spatial lag coefficient is positive and significant at a high level, which indicates the existence of spatial dependence in the model. The positiveness of this coefficient shows that an increase in crime in one city causes an increase in crime in neighboring cities. Also, according to the results of the research, the variables of unemployment, industrialization, urbanization and divorce rate are the most important variables affecting crime rate. The results show positive and significant relationships between unemployment, urbanization, divorce rate, and crime. The industrialization variable also has a negative and significant effect on crime. Also, the spillover effect of the unemployment variable is negative and significant. Based on the results, the higher the unemployment rate and the urbanization rate in the cities, the crime rate will also increase in those cities. On the other hand, as cities move toward industrialization and the number of industrial enterprises in them increases, the rate of crime will decrease more.
Discussion and conclusion
The findings reveal that, unemployment is one of the most important variables affecting crime in the Iranian cities. So, it is recommended that authorities pay special attention to sustainable policies regarding employment and its proportional distribution in cities. Considering excessive growth of urbanization and its detrimental impact on rampant crime rates, it is suggested that statesmen and policy makers create more facilities and pay special attention to rural areas to provide reverse migration in order to prevent occurrence of various crimes, which are happenning due to population increase especially in informal settlements of larger cities.

Designing a Dynamic Model for Evaluating Construction Investment Projects A System Dynamics Approach
Dr Majid Moatamedi, Dr Mohammad Hossein Darvish Motevlli,
Volume 25, Issue 1 (3-2025)
Abstract
Aim and Introduction
The construction sector is one of the macroeconomic sectors that attracts a large amount of the country's liquidity every year. Investment in this sector is of paramount importance. Not taking into account the conditions of the investment field, possible events and influencing factors, actions and reactions of the market and society, when choosing construction projects, causes investors to have problems in reaching their goals. System dynamics is one of the most effective tools that provides the possibility to recognize and understand the laws governing the change processes of complex systems. Researches show that in Iran, especially in Tehran, the building and above all the housing as an economic commodity has characteristics that distinguish it from other commodities and complicate the analysis of supply and demand and market slow down. Therefore, the decision to invest in the construction sector can be considered a dynamic decision that various and different factors and variables are effective in this process. In this research, the dynamic simulation methodology of the system of investment in construction projects in Tehran has been analyzed and investigated which can be used as a support system for model-based decision.
Methodology
In terms of purpose, this research is exploratory and can be considered among applied research. The statistical population of the research includes experts who work in the field of building investment. To collect information, the library method and documents of investment companies in the field of construction have been used. The basic analytical method in this research is simulation using system dynamics methodology. Vansim software was used to model system dynamics.
Findings
The increase in real housing prices over the past years has been compared with the output of the simulation model. The results showed that these two values behave similar to each other. The error value of the model in the predicted value and the actual value is very small on average, which indicates the high accuracy of the model in predicting the behavior of the reference. The results of the simulation in the case where the population variable is unchanged and the birth and death rates are zero showed that after some time, the real demand will be zero and the number of available houses will reach a constant value, and the limit behavior of the model is as expected. The simulation results showed that in the case where the land price variable is very high, after some time, the real demand will be zero and the number of available houses will reach a constant value, and the limit behavio of the model is as expected. Therefore, since there is no demand, no houses will be built as a result. Based on the results of the simulation, the most important effects on investment tendencies in construction projects are based on price and profitability variables. With an increase in price, investment in construction increases, but on the other hand, an increase in price will result into increased capital demand. By reducing the capital demand to 5%, the price will decrease to a small amount and the investment in the construction projects will be significantly reduced. The reason for not reducing the price properly is the current inflation, which affects the price of land and other influencing factors. Based on this, the inflation reduction scenario was investigated. With a 15% decrease in inflation, we have seen a relatively significant price decrease and the investment rate has decreased very little. Therefore, the most important component in investment tendencies is the inflation rate and economic stability, the appropriate inflation rate causes a balanced process of price increase and balanced demand, and for this reason, investment is made with less risk, demand and proper profitability.
Discussion and Conclusion
In this research, various aspects of investment in construction projects have been studied with an analytical and multifaceted view. The simulation results showed that the price of building units and the price of land or old property will reach more than double the current value during the 5-year period of simulation. The annual real demand rate increases with a gentle slope from about 105 thousand cases to more than 117 thousand cases and then decreases to less than 84 thousand cases. The construction rate will be about 70 thousand units per year by the investors, and 116 thousand units per year will be invested during the 5-year period, which is due to the increase in capital demand. Based on this and taking into consideration the units demolished for renovation and some units removed from the service due to the exhaustion of the effector in demand and available within 5 years, in the end more than 400 thousand residential units will be added to the total construction units of the city. Based on the results and reports extracted from the simulation model, which shows the future conditions of the investment field of construction projects, along with the study of the performed scenarios, the decision makers can observe and check other changes in the system in case of changes in the variables. Eventually, fully informed decisions are recommended to be made based on investigations with a systemic approach

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