Presentation of the model direction determining effective economic variables on the multidimensional poverty index in Middle East countries in time (1995-2017)

The purpose of this study is to provide a model to determine the economic variables affecting the multidimensional poverty index in the Middle East in the period (1995-2017). The method of the present research is descriptive-analytical. The statistical population of this study is Middle Eastern countries. Data collection has been done using official statistical centers in different countries in cooperation with the Statistics Center of Iran. Data analysis was performed using Eviews and SPSS software version 21. Various variables were effective in estimating the multidimensional poverty index in Middle Eastern countries. But the variables of human capital, capital formation, foreign trade, inflation rate due to terrorist threats, gross domestic stability) were analyzed as the most important influential variables. The generalized torque (GMM) method was used to analyze the proposed model and tests such as Sargan, regression coefficient, Jarco-Braha test, Watson camera statistics were used. The results of multidimensional poverty index analysis in the Middle East using the period from 1995 to 2017 in terms of manpower index (balanced fluctuations), gross domestic stability (constant fluctuations), inflation due to terrorist threats (high fluctuations with steep slopes into increase poverty), capital formation (poverty reduction fluctuations), foreign trade (very large fluctuations to reduce poverty). The results of estimating the research model in the form of a dynamic model by the generalized torque (GMM) method showed that the probability value related to the validity of the null hypothesis that the coefficient of variables FI (t-1), foreign trade (trade), inflation) is zero. Due to terrorist threats (IN), CF capital formation, Gross Domestic Stability (INV), and Human capital (H), the fixed value of the model is equal to 0.062, 0.042, 0.025, 0.046, 042, respectively. 0.8, 0.844, is smaller than the probability of the first type error 0.05. Therefore, at this level of error, the significance of the effect of these variables and the presence of a constant value in the model is not denied. The explanation coefficient of the model is equal to 0.738 and is larger than the standard limit of 0.7. Therefore, predicting the multidimensional poverty variable in Middle Eastern countries according to the independent variables considered in the model has relatively high accuracy.