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EXTENDED ABSTRACTINTRODUCTION Human Development Index is a composite one to measure three criteria of longevity, access to knowledge and appropriate level of welfare. Since 2011, education, the combination of mean study years for adults (25 years of age and elder) and expected years of studying, life expectancy and income per capita have been considered as components of Human Development Index. Human Development Index is in fact the geometrical mean of these three indexes. This index is annually calculated for countries by the United Nations but not for their states, provinces, cities and regions. Therefore, researchers themselves must calculate this index for provinces for certain purposes. METHODOLOGYLack of such statistics is also a statistic deficit in Iran that has made regional and provincial researches limited and inaccurate. To remove this deficit in this research Khouzestan Human Development Indexes in the years 1996, 2006, 2011 and 2016 have been calculated using the latest formula. It needs to be mentioned that the simulation of Human Development Index is difficult and time consuming. Not paying attention to details can deviate the index. So in order to ensure the precision of calculations, the Human Development of the country has also been calculated and compared with the same index calculated by the United Nations for Iran in order to ensure the authenticity of Human Development Index in Khouzestan. The applied method was a simultaneous behavioral pattern which considers the changes in Human Development Index through components of the United Nations Human Development Index and also simultaneously predicts and includes it in Human Development Index. The estimation method is based on Stock and Watson (1993) Dynamic least squared method that is helpful for predicting variables. FINDINGSAccording to results, Khouzestan Human Development Index for the period 1990-2019 can be simulated. The related results are presented in table 1. Table 1. Simulation of Khuzestan Human Development IndexFor further investigation of the results of simulation with real data, the results of calculating simulation assessment criteria have been shown in table 2. The results verify the validity of simulation. Table 2. prediction error criteriaAs table 10 shows, Khouzestan Human Development Index had a slow rising trend up until 2005 but from 2006, there seems to be a jump or structural failure in Human Development Index. However, during 2016-2018 the trend reached a plateau and it seems to have reached its stabilized level. Also, based on this simulation Khouzestsan Human Development Index was in an average level up until 2008 but since 2009 it has reached its high. CONCLUSIONTo assess this hypothesis, in this research using the new formula Khouzestan Human Development Indexes for the years 1996, 2006, 2011 and 2016 were calculated. The results showed that the indexes of life expectancy and education in Khouzestan were in a worse situation than that of the country but the index of income (taking oil into account) was more than that of the country. The calculation of Khouzestan Human Development Index without oil showed a worse situation than that of the country.Based on results, Kouzestan Human Development Index reached from an average level in 1996 to a high level during 2006 to 2016. This is an acceptable growth. Also, Khouzestan Human Development Index without oil is lower than that of the national index and this represents the worse status of the province compared to the country.The results of simulating Human Development Index show that up until 1389, there was a slight rising trend but from this year on there has been a jump or failure. Moreover, Khouzestan Human Development Index was in an average level up to 1385 but it has reached a high one since 2010.

This article examines the effect of government size on the high, medium and low thresholds of the Gini coefficient in Iran. For this purpose, the auto regression model of soft fuzzy logistic transfer (FLSTAR) has been used for the period of 1997-2019. One of the reasons for using this model is flexibility in its application. The main focus of this paper is to calculate the Gini coefficient bands according to the size of government in the economy. Hence, we calculate the bands (high, middle and low) of the Gini coefficient. The study show that the threshold size of the government is equal 0.499. Findings of this research are applied in a real case which reveal that with increase of government share in economy the Gini coefficient increases as well. Therefore, the government should seriously pursue privatization policies.