عنوان مقاله [English]
Spatial Correlation between socioeconomic variables and employment location quotient of Iranian farmer women Using ESDA
Nowadays, the power of countries is measured by their creative and efficient power, so they must make the best planning for their best investments. A society that seeks to achieve sustainable development must inevitably accept the active participation of all people in society and allow them to realize the development of their community. In this regard, rural women are the most invisible contributors to the economic process of society and the family. Current changes in the economic, social and cultural spheres of the countryside, despite the positive effects that have been made to improve the living conditions in the countryside, have reduced the active role of women in the field of production, and former rural women of the former producer are turning into consumer housewives. Not only does this not only negatively affect the economy of the countryside, but virtually eliminates a massive activist from the production process and boosts national economic growth. An overview of the perspectives and views on employment, especially the employment of women, shows that the country does not have a favorable situation in terms of employment, especially women's employment. Therefore, improving the employment of rural women can be seen as the key to the success of measures taken to improve the situation of rural communities. To gain benefit from women's talents and abilities in line with making maximum use of our human resources entails accurate and scientific study of their activities. Since half of the population of transitional society's lives in rural areas, and women make up one half of rural populations; one way of achieving these human resources is to study their economic activities in various arenas. According to Census of 2006, the rural women's share in employment is about 13 percent. But the undeniable fact is that on average about 40 percent of the labor force in agricultural activities are supplied by rural women. Since women make up half of the rural population, it is possible to accelerate the social and economic development of the country by identifying the factors influencing women’s participation and increasing their involvement according to local and regional circumstances. Focus on women specially farmer women who play an important role rural economic circle, could solve many problems in rural development in Iran. So, in this study we try to evaluate spatial model and effective causes of on these models using ESDA approaches by calculating employment location quotient of Iranian farmer women regarding county, distribution order and its spatial spread and finally evaluation of spatial relation between socioeconomic variables and calculated location quotient. Therefore some questions here come up: is there any significant spatial relation between socioeconomic variables and employment location quotient of Iranian farmer women? Dose the spatial relation between socioeconomic indexes with employment location quotient of Iranian farmer women at the level of Iranian counties?
Population and housing census of 2011 and EXCEL and GEODA data were used for analysis. First, LQ location quotient was used to determine basic actions in this sector. This method is used to identify basic labor force indifferent regions. Also, bivariate Moran was used to evaluate the relation between LQ and sociocultural variables. This test is necessary for zero hypothesis exam, the accidental spatial distribution in comparison with non-random (clustered or dispersed) distribution.
This situation was studied for women literacy index, unemployment rate and rustication rate. Accordingly, the present study attempted to conduct an economic base analysis of the spatial distribution of women’s employment in the agricultural sector via location quotient (LQ) and exploratory spatial data analysis (ESDA). Data were extracted from the 2011 General Population and Housing Census. Local indicators of spatial association (LISA) and Moran's I index of global spatial autocorrelation were used for analyzing the data as variants of the ESDA approach. Moran's I indicated that the spatial distribution of women’s employment via location quotient (LQ) in the agricultural sector was not random or sparse but clustered.
Results of local spatial autocorrelation between LQ and socioeconomic indexes suggests that the spatial relation between unemployment rate and LQ in rural regions of Iran is positive and significant; and most of Iranian rural regions follow the same relation. Based on the latter matter, LQ rises as unemployment rate increases and LQ tends toward basic employment and export of labor force. Spatial relation between literacy rate and LQ is negative and significant and follows a low-high model. So, in Iranian rural regions as literacy rate increases, LQ rises too and tends to basic employment and export of labor force. Also spatial relation between rustication rate and LQ is positive and significant and follows a low-low model. Based on this, in Iranian rural regions as rustication rate decreases, LQ is lessened and tends to non-basic employment and import of labor force.
The spatial distribution of economic activity via location quotient (LQ) and its relationship with social and economic indices (literacy rate, unemployment rate and pastoralism) in the rural areas of Iran via Moran's I does not follow a specific pattern. Instead, each area adopts a certain pattern of connections based on local and regional circumstances. The relations between socioeconomic indexes and LQ doesn’t have the same model, in a way that different Iranian regions follow different spatial relations. Therefore each region needs special programs. For example despite that local autocorrelation indicates positive and significant correlation with LQ, all Iranian rural regions didn’t follow this model, so that only southeastern and partly western counties of Iran followed a high-high model, but northwestern and some of Razavi Khorasan counties follow a low-low model; while Ardabil counties and many of Razavi Khorasan counties and northern counties of Kurdistan province follow a high-low model. Therefore, regarding the general correlation, it is impossible to give a common model for all of these regions; so a special program must be designed for each of the mentioned regions.
Key word: Rural Women, Employment, Spatial Analysis, Major Economic Activities, Villages in Iran
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