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Inter and Intra-Regional Income Inequalities Attributable to Spatial Concentration in Pakistan

Author

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  • Tabassum Uzma

    (Applied Economics Research Centre, University of Karachi, Karachi, Pakistan.)

  • Nazeer Munazah

    (Applied Economics Research Centre, University of Karachi, Karachi, Pakistan.)

Abstract

Reducing inequality is essential to sustainable growth in regions. Due to varying geographic locations and locally formed development strategies, agglomeration disparities fluctuate among urban areas. This study is uniquely designed to measure the extent to which spatial agglomeration impairs inter and intra inequalities using two distinct techniques, Geographic Information System (GIS) and Propensity Score Matching (PSM). The results obtained from both analyses are in line with the theoretical framework established in the study. The results show that income growth is significantly impacted by the geographical concentration of industries. After matching, agglomerated regions have 22.5% higher average income than less agglomerated areas, which upsurges inter-regional disparities. Additionally, as income growth is unevenly distributed among inhabitants of the same region, inequalities in a treated regions are estimated to increase by approximately 2.5% more in comparison to the untreated regions that are relatively less concentrated, exacerbating intra-regional inequality.

Suggested Citation

  • Tabassum Uzma & Nazeer Munazah, 2025. "Inter and Intra-Regional Income Inequalities Attributable to Spatial Concentration in Pakistan," Zagreb International Review of Economics and Business, Sciendo, vol. 28(1), pages 103-124.
    • Handle: RePEc:vrs:zirebs:v:28:y:2025:i:1:p:103-124:n:1005
    DOI: 10.2478/zireb-2025-0005
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    References listed on IDEAS

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    4. Haroon Jamal, 2006. "Does Inequality Matter for Poverty Reduction? Evidence from Pakistan’s Poverty Trends," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 45(3), pages 439-459.
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    More about this item

    Keywords

    Income inequality; urban regions; Propensity Score Matching; Arc GIS;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • D30 - Microeconomics - - Distribution - - - General
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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