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Investment Dynamics In African Tech Startups: An Econometric Analysis

Author

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  • Aissa Hadjab

    (Faculty of Economic, Commercial, and Management Sciences, University of Msila, Algeria)

Abstract

This article aims to explore the investment dynamics of African tech startups through econometric analysis covering the geographical and sectoral distribution of capital, concentration levels, and organizational growth determinants. The study employs a methodology combining descriptive statistics, concentration indicators (such as the HH Index and the Gini coefficient), cluster analysis techniques (K-means and hierarchical clustering), spatial distribution measures (Location Quotient), and correspondence analysis. The findings reveal a significant concentration of funding in a limited number of countries and sectors, with the emergence of distinctive regional and sectoral clusters. Additionally, results indicate that funding size, geographic location, and sub-sector specialization are key drivers of growth. The study recommends implementing more balanced investment policies across regions and sectors and developing support mechanisms to foster greater geographic and sectoral diversity in the African tech entrepreneurship ecosystem.

Suggested Citation

  • Aissa Hadjab, 2025. "Investment Dynamics In African Tech Startups: An Econometric Analysis," Entrepreneurship, Faculty of Economics, SOUTH-WEST UNIVERSITY "NEOFIT RILSKI", BLAGOEVGRAD, vol. 13(2), pages 66-90.
    • Handle: RePEc:neo:epjour:v:13:y:2025:i:2:p:66-90
    DOI: 10.37708/ep.swu.v13i2.4
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    Keywords

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    JEL classification:

    • L26 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Entrepreneurship
    • O16 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Financial Markets; Saving and Capital Investment; Corporate Finance and Governance
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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