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Comparative Analysis of Foreign Direct Investments and Remittances to Five English-Speaking West African Countries Using Statistical, Machine Learning and Deep learning Models

Submission Number: 194
Submission ID: 4445
Submission UUID: e18bfd70-92e4-44f4-8aca-98d22cc7b734
Submission URI: /form/project

Created: Mon, 03/25/2024 - 11:40
Completed: Mon, 03/25/2024 - 11:40
Changed: Thu, 11/07/2024 - 10:05

Remote IP address: 71.58.230.184
Submitted by: Carrie Brown
Language: English

Is draft: No
Webform: Project
Comparative Analysis of Foreign Direct Investments and Remittances to Five English-Speaking West African Countries Using Statistical, Machine Learning and Deep learning Models
CAREERS
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In Progress

Project Leader

Stanley Nwoji
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Project Personnel

Iheb Abdellatif
Nour Rashed
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Project Information

The five English-speaking West African countries, Ghana, Gambia, Liberia, Nigeria, and Sierra Leone
have benefited from both foreign direct investments and remittances from their citizens in diaspora.
Existing scholarship on remittances and foreign direct investments have been purely econometric with
particular emphasis on the relationship of these foreign sources of income with GDP of nations (Tahir,
Khan, & Shar, 2015; Comes, Bunduchi, Vasile, & Stefan, 2018; Minh, 2020; Salisu, 2020). This approach
has helped scholars and practitioners understand the impact of remittances and foreign direct investments
on the economy of nations. However, these studies have been made in silo and there is a dearth of
literature on the comparative analysis of the yearly inflow of foreign direct investments and remittances to
the five English-speaking West African countries. The assumptions are that migration from these
countries leads to brain drain (Idemudia & Boehnke, 2020; Awire & Okumagba, 2020; Fofack &
Akendung, 2020) and that these developing countries depend on foreign direct investments to exist
(Shittu, Yusuf, El Houssein, & Hassan, 2020; Appiah-Kubi, et al., 2020). This study will therefore
compare the inflow of foreign direct investments and remittances to this economic bloc to understand the
impact of both to the region. Moreover, the present studies are mostly done by using econometric models.
In this study, econometric, machine learning, and deep learning models will be used both to compare and
forecast foreign direct investments and remittances.

Project Information Subsection

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The student facilitator must have the following skills:
1. High emotional intelligence to work with other students, the mentor, and the PI.
2. Proficiency in modeling data using econometric, machine learning, and deep learning models.
3. Good writing and communication skills.
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CR-Penn State
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Yes
Already behind3Start date is flexible
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05/17/2024
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  • Milestone Title: Collect and Clean Data
    Milestone Description: Collection of historical data on foreign direct investments and remittances from the
    five English-speaking West African countries
    Cleaning and transformation of collected data
    Completion Date Goal: 2024-05-10
  • Milestone Title: Statistical Analysis
    Milestone Description: Comparative analysis of transformed data with statistical and econometric models
    Completion Date Goal: 2024-06-10
    Actual Completion Date: 2024-10-09
  • Milestone Title: Machine Learning Analysis
    Milestone Description: Comparative analysis of transformed data using machine learning and deep learning
    models
    Completion Date Goal: 2024-07-10
  • Milestone Title: Best Model Identification
    Milestone Description: Identification of the best model for the comparative analysis of FDI and remittances
    to the five English-speaking West African countries
    Completion Date Goal: 2024-08-10
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Final Report

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