TY - JOUR
T1 - Spatial inequalities in education status and its determinants in Pakistan
T2 - A district-level modelling in the context of sustainable development Goal-4
AU - Sajjad, Muhammad
AU - Munir, Hasiba
AU - Kanwal, Shamsa
AU - Naqvi, Syed Ali Asad
N1 - Funding Information:
No specific funds were available for this research. The first author is thankful to all the institutes for the provisioning of relevant data to conduct this valuable study. The research is conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. All the data used for several analyses are freely available and the resources are mentioned within the paper.
Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/3
Y1 - 2022/3
N2 - Achieving Sustainable Development Goal (SDG)-4 prerequisites quality education provisioning. In this context, we present important insights and references for educational interventions/investments to be tailored to local necessities in Pakistan. Several spatial statistical models such as the Global Moran's I-based spatial autocorrelation, multivariate clustering, and the Cluster and Outlier model are used to explore geographic heterogeneities and patterns. Additionally, significant determinants among several socio-economic, spatio-environmental, and infrastructural variables are identified for education status (EdS) using regression. As a result, a large geographic inequality regarding EdS is found in Pakistan. While a strong spatial association is evident, the districts in northern Punjab are identified as significant hotspots—higher EdS clusters (∼22% of total districts, 95% confidence). Majority of the 44% poorly performing districts belong to Balochistan province (95% confidence). Overall, the educational status in Punjab is higher as compared with other provinces. We find that four out of seven potential factors (i.e., poverty, urbanization, electricity accessibility, and school infrastructure) are statistically significant determinants of EdS. Among these, poverty is the most strongly associated (mean coefficient value −18.848) factor to control EdS. The results have important implications to decision-making for immediate or gradual actions in the context of spatially equitable provisioning of quality education through an informed prioritization (i.e., low performing districts). Based on the findings, while rigorous measures are needed for low performing regions and the identified determinants to improve education status, this study sheds light on the mechanisms to achieve SDG4, consequently promoting human well-being through educating communities.
AB - Achieving Sustainable Development Goal (SDG)-4 prerequisites quality education provisioning. In this context, we present important insights and references for educational interventions/investments to be tailored to local necessities in Pakistan. Several spatial statistical models such as the Global Moran's I-based spatial autocorrelation, multivariate clustering, and the Cluster and Outlier model are used to explore geographic heterogeneities and patterns. Additionally, significant determinants among several socio-economic, spatio-environmental, and infrastructural variables are identified for education status (EdS) using regression. As a result, a large geographic inequality regarding EdS is found in Pakistan. While a strong spatial association is evident, the districts in northern Punjab are identified as significant hotspots—higher EdS clusters (∼22% of total districts, 95% confidence). Majority of the 44% poorly performing districts belong to Balochistan province (95% confidence). Overall, the educational status in Punjab is higher as compared with other provinces. We find that four out of seven potential factors (i.e., poverty, urbanization, electricity accessibility, and school infrastructure) are statistically significant determinants of EdS. Among these, poverty is the most strongly associated (mean coefficient value −18.848) factor to control EdS. The results have important implications to decision-making for immediate or gradual actions in the context of spatially equitable provisioning of quality education through an informed prioritization (i.e., low performing districts). Based on the findings, while rigorous measures are needed for low performing regions and the identified determinants to improve education status, this study sheds light on the mechanisms to achieve SDG4, consequently promoting human well-being through educating communities.
KW - SDG-4
KW - Quality education
KW - Spatial analysis
KW - GWR
KW - GIS
UR - http://www.scopus.com/inward/record.url?scp=85124913289&partnerID=8YFLogxK
U2 - 10.1016/j.apgeog.2022.102665
DO - 10.1016/j.apgeog.2022.102665
M3 - Journal article
SN - 0143-6228
VL - 140
JO - Applied Geography
JF - Applied Geography
M1 - 102665
ER -
