Network Analysis of Internal Migration across Districts in Pakistan

Migration within Pakistan's districts have different patterns which are influenced by various factors. However, a systematic analysis of these migration flows is missing, which limits understanding necessary for effective planning and policy formulation. This research aims to bridge this gap by employing complex network analysis to model and analyze district-to-district migration in Pakistan over an eight-year period. Using a one-mode weighted network approach, each district is represented as a node, with migration flows between districts represented as weighted links. This model will enable us to quantify and visualize migration connections, uncovering structural properties and regional disparities within the network. Both local and global network measures will be applied to understand structural properties while community detection will be done to examine its structural organization. Migration reasons are incorporated to capture the socio-economic factors of migration. The findings revealed key structural patterns: Karachi, Rawalpindi and Lahore emerged as major connectivity hubs with widespread links, while Karachi, Lahore and Peshawar stood out as volume hubs handling the largest migrant flows. Districts such as Awaran, Hattian Bala and Khizer were found to be the most accessible, whereas Larkana, Kashmore and Korangi acted as bridging districts linking different regions. At the global level, the migration network appeared sparse but structured, with a clustering coefficient of 0.6 indicating local group formation and a density of 0.3 suggesting that flows are concentrated along specific routes. Community detection revealed five distinct communities, two of which were dominated by Punjab districts, highlighting the province’s central role in shaping migration dynamics. Beyond these structural patterns, the analysis of reasons showed that family-related factors—particularly marriage and living with parents or spouse—accounted for the majority of migration, while job-related and return migration contributed comparatively less. Overall, internal migration in Pakistan follows structured hubs and regional clusters rather than random flows, providing valuable insights for policymakers to design targeted interventions, allocate resources efficiently, and promote balanced regional development.

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Publication Details

Journal
Sukkur IBA Journal of Computing and Mathematical Sciences
Published
2025-12-25
DOI
https://doi.org/10.30537/sjcms.v9i02.1741
Primary Topic
Regional Economics and Spatial Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

Network Analysis of Internal Migration across Districts in Pakistan

Abdul Waheed Mahesar, Noor-e-Iqra, Arjumand Bano Soomro
Sukkur IBA Journal of Computing and Mathematical Sciences
Regional Economics and Spatial Analysis
article

Network Analysis of Internal Migration across Districts in Pakistan

Abdul Waheed Mahesar, Noor-e-Iqra, Arjumand Bano Soomro
article en

Abstract

Migration within Pakistan's districts have different patterns which are influenced by various factors. However, a systematic analysis of these migration flows is missing, which limits understanding necessary for effective planning and policy formulation. This research aims to bridge this gap by employing complex network analysis to model and analyze district-to-district migration in Pakistan over an eight-year period. Using a one-mode weighted network approach, each district is represented as a node, with migration flows between districts represented as weighted links. This model will enable us to quantify and visualize migration connections, uncovering structural properties and regional disparities within the network. Both local and global network measures will be applied to understand structural properties while community detection will be done to examine its structural organization. Migration reasons are incorporated to capture the socio-economic factors of migration. The findings revealed key structural patterns: Karachi, Rawalpindi and Lahore emerged as major connectivity hubs with widespread links, while Karachi, Lahore and Peshawar stood out as volume hubs handling the largest migrant flows. Districts such as Awaran, Hattian Bala and Khizer were found to be the most accessible, whereas Larkana, Kashmore and Korangi acted as bridging districts linking different regions. At the global level, the migration network appeared sparse but structured, with a clustering coefficient of 0.6 indicating local group formation and a density of 0.3 suggesting that flows are concentrated along specific routes. Community detection revealed five distinct communities, two of which were dominated by Punjab districts, highlighting the province’s central role in shaping migration dynamics. Beyond these structural patterns, the analysis of reasons showed that family-related factors—particularly marriage and living with parents or spouse—accounted for the majority of migration, while job-related and return migration contributed comparatively less. Overall, internal migration in Pakistan follows structured hubs and regional clusters rather than random flows, providing valuable insights for policymakers to design targeted interventions, allocate resources efficiently, and promote balanced regional development.

Sukkur IBA Journal of Computing and Mathematical SciencesVol. 9(02)
University of Sindh (PK)
University of Sindh
Reduced inequalities
Openalex Percentile: Top 21%
Regional Economics and Spatial Analysis
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