Foreign Direct Investment, Financial Development and Growth Convergence in ECOWAS
Publish place: Iranian Economic Review Journal، Vol: 25، Issue: 2
Publish Year: 1400
نوع سند: مقاله ژورنالی
زبان: English
View: 70
This Paper With 13 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_IER-25-2_008
تاریخ نمایه سازی: 21 مهر 1402
Abstract:
This study examines the tendency of low-income economies in ECOWAS to converge with their high-income neighbors. It extends the frontier of knowledge by ascertaining how quickly financial development (FD) and foreign direct investment (FDI) would stimulate growth, causing low-income ECOWAS member states to catch up. Also, the required threshold for FD and FDI required to facilitate convergence were computed. To achieve the above, fifteen ECOWAS member states were examined within the period ۱۹۹۰ to ۲۰۱۷ using panel data obtained from the World Development Indicators (WDI) ۲۰۱۸ database. The Fully Modified Ordinary Least Square (FMOLS) technique of analysis was utilized and the study found an absence of conditional convergence among ECOWAS member countries. More so, the FD-FDI threshold level required to aid conditional convergence is ۲۲.۸% and ۳.۷۷% respectively. Therefore to ensure convergence, the study recommends that low-income member states must thrive to attract FDI and seamless credit to the private sector.
Keywords:
conditional convergence , Financial Development , Foreign direct investment , Fully Modified OLS (FMOLS) , growth rate
Authors
Matthew Ogbuagu
Department of Economics, Faculty of Social Sciences, Federal University Oye-Ekiti, Ekiti, Nigeria
Onyebuchi Iwegbu
Department of Economics, Faculty of Social Sciences, University of Lagos, Akoka-Yaba, Lagos, Nigeria
Olufemi Saibu
Department of Economics, Faculty of Social Sciences, University of Lagos, Akoka-Yaba, Lagos, Nigeria
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :