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FDI, corruption and financial development around the world: A panel non-linear approach

Author

Listed:
  • Hadjila Krifa-Schneider

    (RIME-Lab - Recherche Interdisciplinaire en Management et Économie Lab - ULR 7396 - UA - Université d'Artois - Université de Lille)

  • Iuliana Matei

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Abdul Sattar

    (RIME-Lab - Recherche Interdisciplinaire en Management et Économie Lab - ULR 7396 - UA - Université d'Artois - Université de Lille, BUITEMS - Department of Management Sciences, Balochistan University of Information Technology [Quetta, Pakistan])

Abstract

The nexus between corruption and FDI has long been examined, but the literature remains inconclusive. Some studies have found that corruption deters FDI while others concluded the opposite. This paper revisits the FDI–corruption nexus by investigating the mediating role of financial development for 80 advanced and emerging economies over the 2003–2019 period. Using panel smooth transition regression and GMM models, we find a non-linear relationship between corruption and FDI driven by the financial development level of the destination country. In the advanced economies, less corruption means more FDI above a corruption threshold, whereas in emerging economies, corruption level is less important as the countries are more tolerant to it. We thus contribute to the extant literature a potential reconciliation of the theories stressing that corruption can ‘sand the wheels' and ‘grease the wheels' of FDI. A corrupt environment can, therefore, attract FDI, but is not a prudent long-term option.

Suggested Citation

  • Hadjila Krifa-Schneider & Iuliana Matei & Abdul Sattar, 2022. "FDI, corruption and financial development around the world: A panel non-linear approach," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-04085351, HAL.
    • Handle: RePEc:hal:cesptp:hal-04085351
    DOI: 10.1016/j.econmod.2022.105809
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    Cited by:

    1. Li, Qiang & An, Lian & Zhang, Ren, 2023. "Corruption drives brain drain: Cross-country evidence from machine learning," Economic Modelling, Elsevier, vol. 126(C).
    2. Chowdhury, Md Shahedur R. & Khraiche, Maroula & Boudreau, James W., 2023. "Corruption and stock market development: Developing vs. developed economies," International Review of Financial Analysis, Elsevier, vol. 89(C).
    3. Tao, Miaomiao & Dagestani, Abd Alwahed & Goh, Lim Thye & Zheng, Yuhang & Le, Wen, 2023. "Do China's anti-corruption efforts improve corporate productivity? A difference-in-difference exploration of Chinese listed enterprises," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).

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