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The Past, Present, and Future of FDI: Towards a better Global Economics

Author

Listed:
  • Ullah, Sana

    (Quiad-i-Azam University, Islamabad, Pakistan.)

  • Usman, Ahmed

    (Government College University Faisalabad, Faisalabad, Pakistan.)

  • Imran, Muhammad

    (Federal Urdu University, arts, science and technology, Islamabad, Pakistan.)

Abstract

We document past, present, and future of FDI trend in recent decades that goes substantially beyond the advanced economies. This rigorous study also examines the influence of FDI on economic growth using macro variables for a global perspective. Six macro variables namely, FDI, physical capital, trade, human capital, labor force, and infrastructure were used in this study. We did a panel analysis on data from 2002 to 2017 and used rigorous two-way fixed effect model. This study finds that both FDI and trade openness enhance economic growth. Open door policies are more beneficial for the entire world; capital also plays a significant role in this process. Further, FDI plays a role with human capital but vocational training, skilled labor force and education are the most important factors to attract FDI. In the last decade, overall sub-Saharan African, EU and Central Asia, Latin America and Caribbean regions have observed a significant economic growth through FDI. The future of FDI in a high populated area is very gleaming. The overall result indicates that FDI accelerates economic growth in the globe.

Suggested Citation

  • Ullah, Sana & Usman, Ahmed & Imran, Muhammad, 2019. "The Past, Present, and Future of FDI: Towards a better Global Economics," Journal of Quantitative Methods, University of Management and Technology, Lahore, Pakistan, vol. 3(2), pages 28-44.
    • Handle: RePEc:ris:jqmumt:0026
    as

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    References listed on IDEAS

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    More about this item

    Keywords

    human capital; panel data; FDI;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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