فهرست مطالب مرتضی حسن شاهی

Over the past decade, long-term memory processes have been an important part of time series analysis. Long-term memory has important applications in evaluating market performance and macroeconomic, financial, and accounting variables, while the researcher may in some cases have to convert data or in other words manipulate data, which is expected to provide some data features that are important in economic forecasting. Therefore, in this study, the effect of data conversion on long-term memory and structural dependency and finally the results of the study were investigated. For this purpose, the existence of long-term memory in raw and converted data is first tested. To understand the effect of long-term memory on structural dependence, the tail dependence coefficient between raw and manipulated data (seasonal data 1991 to 2018) is estimated; the results show that raw data have long-term memory, more tail dependence on the manipulated data. It changes the nature of the data and not only reduces their memory but also reduces animal dependency.

Inappropriate distribution of income and poverty is one of the problems of human societies and many studies have been conducted to find a solution to this, but less attention has been paid to the impact of Islamic taxes on income distribution. Therefore, in this study, the effect of Khums and Zakat on the improvement of income distribution has been investigated by Estimation of Lorenz curve equation coefficients and Gini coefficient of society using macroeconomic data for the period from 2000 to 2016. The results indicate a small effect of Zakat's revenues on income distribution (injections of Zakat's revenues to the first-decile income reduces the Gini coefficient by 1%) while Khums and Zakat reduce the Gini coefficient by 15% and lower the four lower income groups into the fifth decade And poverty is eradicated. According to the data, even in recent years the amount of khums and zakat is so high that it can reach the first five decades to the sixth decade.

Due to the undeniable effect of expenditures on macroeconomic variables, this research has been devoted to the theory of consumption, This research has been conducted to test the hypothesis of consumption, Brown, Dosebury, and Kuznets, Friedman, Huntaker-Taylor, and Jackson-Smith in Iran until the year 1981-2016. In this regard, two methods have been used: ARDL regression (due to the non-existence of some series) and then ht was Tail Dependence between with Clayton joint method. According to the results, the marginal propensity of consumption the Duznbery model is 83%, Friedman's model is 75.4% and the Jackson-Smith pattern is 74.4%. The marginal propensity of consumption shot-run is estimated to be 0.46 in Brown's pattern and 0.42 in the Hunter-Taylor pattern. The effect of past consumption habits on consumption (coefficient or adhesion) is 39%. That means an increase of 100 units in consumption will increase 39 units in the next year's consumption. The final desire to consume wealth is estimated to be between 0.19 and 0.25. Also, there is a Clayton-dependent relationship between data, and given Clayton's low dependence, then with increased revenue, increased consumption, but with lower income, consumption is not significantly reduced

Agricultural performance depends not only on the availability of physical resources and agricultural technologies, but also on the climate and environmental conditions prevailing on the farm. As the Earth's temperature rises, precipitation has become an unpredictable variable and has led to phenomena such as floods, droughts, etc. in addition, such phenomena have created a new sense of uncertainty for farmers with increasing uncertainty about the prediction of the future climate, and have faced producers with new types of climate problems. It is predicted that the frequency and severity of climate change will increase the challenges facing risk management, as atmospheric conditions (sudden and heavy rains, hurricanes, severe changes in air temperature and acid rain) affect the efficiency of production inputs (fertilizer, seed, pesticides, and so on). ...) Influential. Severe climate change during the growing season can cause serious damage to agriculture and affect farmers' decisions to allocate farm inputs and lead to reduced production and efficiency; Therefore, in analyzing the efficiency and financial and physical performance of the farm, in addition to the production inputs, we should also consider the climatic conditions in which the effect of spring rains on the technical efficiency of tomatoes is investigated.

Data from the crop year of 1395-1396 and The model used is a Modified Stochastic Production Frontier Approach (MSPF),with changes in the model so that in addition to the physical inputs of production, heavy rainfall during tomato growth and farm restoration costs (partial re-planting, part of the farm damaged by rainfall) Have been added to the the traditional model of Stochastic Production Frontier Approach (SPF) to estimate their impact on technical performance (in conventional models due to the lack of atmospheric variables, the estimated parameters are biased and the correlation between efficiency and bias is neglected and the bias bias causes the farm manager to decide. Conflicts d Wrong resource attribute and failed to make optimal use of resources). In addition, if the explanatory variables in the production function are correlated with the variables affecting technical performance and this correlation is ignored in the estimation of the production function parameters, it leads to biased estimates of the parameters thus avoiding this kind of correlation, Betis and Coeli's one-step approach is used to determine the factors affecting production efficiency, in which the technical efficiency of the fields is related to the socio-economic conditions of the farmers, management skills and demographic characteristics, etc.Eventually the Modified Stochastic Production Frontier Approach have been compared and the results have been compared with the traditional model of Stochastic Production Frontier Approach.

According to the results of the correlation coefficients estimated between production inputs and rainfall and farm repair costs, there is a relatively strong correlation between heavy rainfall, seed rate and labor force. Heavy rains increase the need for labor to compensate and repair the farm. Rainfall is also negatively correlated with pesticides, since it is washed off by rainfall and instead of being absorbed by pesticides, it is washed out and eliminated, and the farmer is aware of this problem and uses less pesticide during heavy rainfall. Precipitation has a negative effect on pests. Rain is positively correlated with fertilizer as expected, as rainfall can absorb fertilizer faster into the soil and root of the plant. Rain is positively associated with seed because heavy rains destroy the transplants and the farmer must re-transplant. Although the relationship between repair costs and rainfall was not positive but significant, it may be because some of the repair costs (more fertilizer, manpower and seed consumption) were in the three inputs. To test the effect of atmospheric factors on production and technical efficiency, the model parameters were estimated once without the presence of these variables and once added to the model. Comparison of the results from the application of these two models confirms that ignoring the atmospheric variables in the estimation of the technical efficiency leads to bias in the estimation parameters. According to another part of the

1- Heavy rainfall caused 100% damage to the farm resulting in technical efficiency reduction, 2- Adding atmospheric variables to the model (MSPF pattern), all input coefficients and technical efficiency change This reflects the impact of atmospheric variables on efficiency and production that were overlooked in previous studies. 3. The high technical efficiency difference estimated in the two models means that in the rainless model, the technical efficiency estimates are more biased, 4. Toxins Chemical in the SPF pattern has a significant relationship with production but in the MSPF model, the coefficient of this variable is not significant because it is likely to wash away the heavy pesticide precipitation and eliminate its effects. 5 - Interesting findings of this study Interaction between inputs And there is heavy rainfall so that heavy rainfall not only damages the farm but also reduces the efficiency of other inputssignificant.6- Proper use of inputs can increase technical efficiency by 14%, resulting in a 19% increase in production and an 11.6% decrease in production costs

Atmospheric factors, especially severe and short-term rains, reduce the technical efficiency and tomato production.

Pension schemes are one of the most important and essential tools for ensuring and securing a minimum for old age people’s standard of living. Hence, governments design and provide pension schemes. However, many challenges are faced by pension funds around the world. The most common type of pension schemes are Defined Benefit (DB). These type of pension schemes are running a significant deficit. Hence, experts attempt to reform the pension systems. Hybrid private pension plans are one of the most appropriate alternatives. Because of their unique characteristics, such as good governance, competitiveness and risk-based supervision, these types of plans are more efficient. Consequently, in this research we study the financial feasibility on the implementation of these plans. We investigate the financial feasibility using Fuzzy Cognitive Mapping (FCM) in order to identify factors affecting the sustainability of pension schemes. Then, We determine the effect of each factor on financial sustainability. Finally, using the methodology of system dynamics (SD), the model is simulated and tested. While twenty-year simulation results indicate unsustainability of DB plans, hybrid pension plan’s cash flow shows an incremental trend.

The doctor is a health care provider which is depreciated due to, work, accidents, environmental pollution and age and increases the demand for health services; many factors have an impact on the demand for health services; this study attempts to measure the impact of 18 of the most important ones.
The model used is the Generalized Logit and ANN. The population includes those who referred to Shiraz and Arsanjan hospitals in 1994. The sample consists of 100 patients and 100 patient patients (non-patient) and data Collected through questionnaires.
Findings: The results of model validity tests including fit of Goodness (Pearson and Deviance index), Parallel Regression, Maximum likelihood, and Newton-Raphson Algorithm indicate that the validity of the model is up to 84% confidence. According to the results, increase of 1% in visit, 2% of demand for services is reduced. The initial health and beliefs has the same interpretation of visit. An increase of one percent in premiums caused a decrease of 3.11% and increases one unit in health index, decrease of 1.3% and a one year increase in age, increase of 10%, and daily consumption of one cigarette, increases 0.04% in demand Health care.
According to the results, health, insurance, education and awareness of body anatomy have the greatest impact and smoking and job have the least impact on the demand for health care. With increasing age, education, insurance coverage, awareness and income, the demand for treatment increases. On the other hand, over time, education, awareness and per capita income are rising, so, the demand for these services will increase in the future.

Inappropriate distribution of income and poverty is one of the problems of human societies and many studies have been conducted to find a solution to this issue. But in these studies, less attention has been paid to the impact of Islamic taxes on income distribution. Therefore, in this study, by calculating the Gini coefficient of society using macroeconomic data for the period of 2000 to 2016 and estimating the gini coefficient of the sample Using detailed data of household income through parametric and nonparametric methods, the effect of zakat (potential) on improvement of the distribution of income has been investigated. In this regard, after calculating the amount of zakat (potential) in Iran, its assumed distribution among the first decile of income in Iran was investigated and ultimately its impact on income distribution was studied. The results of the application of parametric and nonparametric methods with households' micro data indicate a decrease of 2.1% in the Gini coefficient due to Zakat. The results of estimating the Gini coefficient by regression method also indicate a 3% decrease in the coefficient due to the distribution of zakat in the economy. Therefore, Zakat reduces the Gini coefficient and moves the community towards the Pareto's situation (according to the contract curve), thereby increasing social welfare (utility of society)

Present study has paid economic assessment of fish stocks and the fishing industry in the Persian Gulf and Oman Sea coast.Using the variables of time and effort As independent variables and the amount of catch per unit effort as the dependent variable, the estimated production function.The level of fishing effort and maximum sustainable yield and maximum economic yield was calculated using of Shepherd and Fox models.The results indicate The Persian Gulf was to effort capture fish too. so with a 31 percent reduction in fishing effort can reduce the cost of fishing And increased revenues and profits.

The aim of the present study was to determine the causality between economic growth and environmental quality. The variables under study were economic growth، government expenditure، openness degree of the economy، capital stock، population، average export of contaminants، and carbon dioxide (CO2) emissions during the time period from 1977 to 2010 for the Iranian economy. The results suggested that there is a two-way relationship between economic growth and environmental quality. Besides، economic growth was found to have the greatest impact on air pollution.

this study do the economic valuation this erea (as a desert tourism oriented) by using contingent valuation and travel costs. data required through the questionnaires were collected from visitors gather. The results show that the average willingness to pay for protection and development services desert for each individual, annual average of 11,092Toman and 31,875Toman to pay once to be, And people willing to pay for the expansion set to the depth of Shahdad Desert Lut is 23,950 Toman fee (once). For anyone visiting the region has cost 40,320 Toman, which is present this value increased to 46,000 Taman. Also, a willingness to pay per passenger with a distance to place his residence Shahdad Desert negative relationship, namely people who live in areas close to the desert to more value for are allowed. Those who have means of personal travel have had a higher WTP have had a higher WTP, which could indicate Desert service is being luxurious. Elderly and people with lower self WTP and higher educated people have expressed. Variables gender and family size do not have affect on WTP amount.

There are various views about deceision making for the model of growing crops in risky conditions such as: Motad Model, Inome - variance, grade2 planning, inseparable linear planning, and limited extreme risk model, Focus-Loss Model, and Target- motad. In this study, Target - Motad Model has been used as the optimum pattern of growing crops in Arsanjan. The results have been compared with those of Advanced Motad, linear planning and Grade 2 planning Models. The data have been gatherd from agriclture firms and Arsanjan Jahad cultivation Management for the years 1378 – 1384. After the estimation of about 60 optimum models risk of various objectives were determined. Using regression analysis, the corre laxion between output and risk was calculated. The results show that there is positive correlation between them. Increase in risk causes incrase in product of wheat and tomatoes and decrease in product of corn.

Arsanjan is located in northwest of Fars province. and is rich in agriculture & jungle. The major problem of this town is water Shortage The water is not enough for agriculture. However, power, mnistry is building a dam on the Sivand River in north west of Arsanjan to transfer 60 million cubes meters of the waters this river to this town. This is possible through digging canals from two different diretcions. Sivand dam - Arsanjan jungle – planting fiedls around the City and Village of Aliabad-e-Malek. Deivere dam of Hashtigan-Seidan & Farough Plain-agriculture Fields of and villages of Khobriz and shorab.Transfering warer through the second direction is less expensive. But the first area has less water and needs more digging. The second area has semi - salty soil & is not rich. In this research water demand & supply is estimated and the amount of a water Imported from this dam is accumalate with water resource and the excess welfare (consumer & producer surplus) of the population is measured. The results show that transfering water from the first direction is more economic. to do this research stone- Gary utility model to used & 2sls method & optimization agricultural instutions using linear plannig were used.