The Use of Regression Panel Analysis with Fixed Effects in International Trade: The Example of Poverty in Africa

Abstract: This paper explores the application and potential of panel data regression analysis in international trade. By leveraging panel data, the authors aim to understand the impact of various economic factors on poverty rates in African countries. The study uses fixed effects models to analyze the relationship between gross domestic product (GDP) per capita, foreign direct investment (FDI) inflows, remittances, and export rates on the proportion of the working population living in poverty. The findings indicate that higher GDP per capita and increased remittances reduce poverty rates, whereas FDI inflows and export rates do not show a statistically significant impact. The paper underscores the importance of economic growth and remittances in poverty alleviation and calls for more nuanced strategies to address poverty in Africa effectively. Future research should investigate the structural aspects of exports and regional specificities to enhance the understanding of these dynamics.

10th International Scientific ERAZ Conference – ERAZ 2024 – Selected Papers: KNOWLEDGE BASED SUSTAINABLE DEVELOPMENT,  hybrid – online, virtually and in person, Lisbon, Portugal, June 6, 2024

ERAZ Selected Papers published by: Association of Economists and Managers of the Balkans – Belgrade, Serbia

ERAZ conference partners: Faculty of Logistics, University of Maribor, Maribor (Slovenia); University of National and World Economy – UNWE, Sofia (Bulgaria); Center for Political Research and Documentation (KEPET), Research Laboratory of the Department of Political Science of University of Crete (Greece); Institute of Public Finance – Zagreb (Croatia); Faculty of Tourism and Hospitality Ohrid, University of St. Kliment Ohridski from Bitola (North Macedonia)

ERAZ Conference 2024 Selected Papers: ISBN 978-86-80194-87-5, ISSN 2683-5568, DOI: https://doi.org/10.31410/ERAZ.S.P.2024

Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission. 

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