Spatial Patterns of Female Labor Force Participation in Oman: A GIS-Based Modeling

Research output: Contribution to journalArticle

Abstract

In the past decade, the women's employment rate has increased in Gulf Cooperation Council (GCC) states as a result of improved female educational attainment and the expansion of the local market economy. A significant gender gap in labor force participation (LFP) rates has emerged, however, compared to other countries in the Middle East and North Africa. The main aim of this article is to model the spatial variations of female LFP rates across the northeastern part of Oman. A geographically weighted regression (GWR) technique, within the geographic information system platform, is used to address how the relationships between Omani female LFP rates and a set of explanatory variables vary across Omani subnational boundaries. GWR is a powerful approach that can facilitate the identification of areas with lower or higher female LFP rates and help in better understanding the predictors that are associated with women's employment in specific locations. In so doing, this work attempts to fill the gap in the geographic literature regarding the modeling of local spatial patterns of female employment in developing countries. The results show that the female LFP rate is significantly associated with different spatial measures and particularly the geographic distribution of female education. Interestingly, the percentage of female jobs in the public sector is found to have a substantial negative effect on female LFP rates, especially in urban areas. This can be attributed to the propensity of Omani women to work in governmental jobs and reduce their participation in private and other business sectors. The findings of this research analysis not only offer a more nuanced examination of female LFP rate patterns but also provide empirical evidence in support of locally tailored policies pertaining to the female labor force, which might help in increasing women's participation trends in the local economy across local communities.

Original languageEnglish
Pages (from-to)1-16
Number of pages16
JournalProfessional Geographer
DOIs
Publication statusAccepted/In press - Apr 23 2018

Fingerprint

labor force participation rate
female labor force
Oman
labor force participation
Geographical Information System
GIS
modeling
women's employment
womens employment
regression
participation
North Africa
local economy
East Africa
female education
labour force
market economy
Middle East
educational attainment
public sector

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Earth-Surface Processes

Cite this

Spatial Patterns of Female Labor Force Participation in Oman : A GIS-Based Modeling. / Mansour, Shawky.

In: Professional Geographer, 23.04.2018, p. 1-16.

Research output: Contribution to journalArticle

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