Evaluation of Rural Poverty Indicators and Its' Affecting Factors in Iran

Poverty is prevalent in majority of the world's nations. If a country is not on the path of eliminating or reducing poverty, it will not be on the path of growth and development. Undoubtedly, the first step in planning of anti-poverty and reducing inequality for development of society is a good recognizing of poor people and poverty situations. To do so, it is necessary to define and use poverty indicators for measuring poverty, which can reveal the different aspects of poverty. Indeed, more precisely identifying the number and grade of households below the poverty line in different locations can help policymakers toward better planning. According to the statistics provided by the Statistical Centre of Iran, in recent years, due to the low level of income of villagers, it has been emphasized more on poverty issue in the rural sector than the urban sector, and the size and severity of poverty in rural areas have been more tangible. Income inequalities (using the Gini coefficient) have always been higher in rural areas than in urban areas. So in this regard, the main purpose of this study is to "survey the rural poverty indices and its affecting factors in rural areas of Iran". One of the most important concerns of governments is awareness of poverty and inequality in society to take action to improve the status of poverty and distribution of income. In this regard, it is important to determine the poverty line and poverty measurement indicators. In this study, poverty indicators were categorized into two categories of "Classical indicators", including "Head Quant Ratio", "Poverty Gap index", "Income Gap Ratio", "Kakwani Index", "Kakwani - Sen index", "Sen Index" and "Modern indicators", including "Gini coefficient index", "Atkinson index", "Araar Index", "DER Index", "Foster - Wolfon index", and "Steban Grading Ray Index". It should be noted that the classification of indices is done to simplify the subject, although the basis of this classification is the observance of the two "monotonicity axiom" and "transfer axiom" by the indexes, that is, the use or absence of polarization in the distribution of income (and inequality). The polarization distribution of a variable is the degree of distribution be distributed around a polar group. Many papers and studies have examined the difference between indices of inequality and polarized indicators and concluded that, in general, phenomena such as "middle class disappeared" or "boundary grouping" cannot be estimated by indices of inequality such as "Gini coefficient index". These topics require more robust and complete indicators that can also analyze the polarity of the data. the aim of this research is examining the situation of poverty and distribution of income “inequality”. Indicators of poverty measurement include modern and classical indicators then  the impact of some macroeconomics variables on poverty  has been investigated using data of income plan for households in rural areas in years 1987-2016, with Stata software and DASP package calculating classical indicators which includes: "Head Quant Ratio", "Poverty Gap", "Income Gap Ratio", "Kakwan index", "Severity Poverty of Sen", "Sen Poverty index" and modern indicators which includes: "Gini index", "Atkinson index", "Arrar index", "DER index", "Foster - Wolfson index, "Steban Gradin Ray index. In order to investigate the factors affecting poverty, firstly, between two linear and logarithmic functional forms, logarithmic forms are used as the appropriate form for running regression. In addition, White's powerful variance has been used to solve the heterogeneity variance problem. The results of regression estimation for factors affecting poverty indicators show that economic growth, fertility rate, unemployment, household size, time trend, rural population, agricultural producer price index, net capital agriculture and agricultural value added affect all six modern indicators of poverty. The result of indicators using income plan data for households in rural areas  for years 1987-2016, with Stata 14.0 software  and DASP 3.0 package shows that poverty increased in years 1987-1992 and 2012-2016 but decreased in 1993 till 2011. Reducing unemployment, controlling inflation and controlling the growth rate of rural populations are important factors affecting poverty. Increasing agricultural producers' prices will improve rural incomes and improve poverty, as well as increase in agricultural investment and increase in agricultural value added, which can have a major impact on rural welfare and poverty. It is also recommended that supportive policies based on spatial and regional differences should be developed and applied based on the difference in income deciles.