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Analysis, Modeling and Prediction of Employment Role in Regional Immigrations Case Study: Sistan & Balochestan
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Abstract: (9828 Views) |
| The relationship between employment and immigration in special levels of Systan & Balochestan including rural and urban regions is studied in the present paper with the purpose of analysis, modeling and prediction of employment role in immigration. Research method is analytical-descriptive with quantitative approach in which models of labor market, correlation and regression are used. Two variables(employment deficit and out-immigration) obtained from labor market model were introduced as independent and dependent variables in modeling process respectively and then their relationship was predicted. This research considers immigration as an outcome of geographical differences between supply and demand of labor force and indicates the worse labor market of rural regions than urban regions during five decades (1956-2006). There is a direct and strong relationship between employment deficit and out-immigration in rural and urban regions (correlation coefficient: 0.9). 90% of immigrations occurred in rural and urban regions during the five decades are characterized by employment deficit. It is predicted that when employment deficit in urban regions is eliminated completely and there isn’t employment surplus, these regions will accept immigrants (about 23000 people) and if this happens in rural regions, out-immigration will be diminished greatly about 500 people. Findings indicate that employment deficit is population pulled to the region and employment deficit is population driven from the region. So providing employment opportunities in the region through investment in providing new employment opportunities can be recognized as the most effective solution to prevent evacuation of rural and urban regions of the province. |
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| Keywords: Modeling, employment, migration, Labor market model, Sistan &, Balochestan province |
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Full-Text [PDF 498 kb]
(2425 Downloads)
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Type of Study: Research |
Subject:
Special
Received: 2014/04/21 | Accepted: 2014/04/21 | Published: 2014/04/21
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