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Structural Domestic Conditions, Regional and International Financial Integrations: Evidence from the MENA

  • Erdal Özmen ORCID logo and Fatma Taşdemir ORCID logo EMAIL logo
Published/Copyright: August 29, 2025
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Abstract

This paper investigates the effects of international (IFI) and regional financial integrations (RFI) on structural domestic conditions represented by financial development and governance in Middle East and North Africa economies (MENA) during the 1992–2020 period. The generalized method of moments estimation results suggest that too much IFI deters while higher levels of RFI, measured based on bilateral financial flows, promote financial development. High levels of IFI and RFI both tend to be positively associated with institutional quality and governance. The empirical findings in this paper propose that MENA economies should engage in structural reforms, encompassing liberalization of capital accounts, eliminating barriers to regional financial integration, enhancing the institutional environment and financial development. In this vein, policymakers may be suggested to formulate strategies with the goal of maximizing the beneficial effects of both international and regional financial integrations.

JEL Classification: F30; F40; F62; R10

Corresponding author: Fatma Taşdemir, Department of International Trade and Business, Sinop University, Sinop, Türkiye, E-mail:

Acknowledgements

This work was sponsored by the Economic Research Forum (ERF) and has benefited from both financial and intellectual support. The views expressed in this work are entirely those of the author(s) and should not be attributed to ERF, its Board of Trustees or donors. An earlier version of this paper was presented at the ERF 30th conference: Tragedies of Regional Conflicts and Promises of Peacebuilding. We thank conference participants and Chahir Zaki for their helpful comments and suggestions.

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: Not applicable.

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: Not applicable.

  7. Data availability: The data that support the findings of this study are available from the corresponding author upon request.

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Received: 2025-04-03
Accepted: 2025-08-11
Published Online: 2025-08-29

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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