Fiche du document
15 mars 2024
- 2403.10239
Mots-clés
Computer Science - Computation and Language Economics - Econometrics Physics - Physics and Society I.2.7 J.4 H.4.0Sujets proches
Scientific research Science research Science--Research Natural philosophy Philosophy, Natural Resultants Methods of analysis Analysis and chemistry Analytical methods Chemical analysis Analysis methods Analysis and examinationCiter ce document
A. Fronzetti Colladon et al., « A Big Data Approach to Understand Sub-national Determinants of FDI in Africa », arXiv - économie
Partage / Export
Résumé
Various macroeconomic and institutional factors hinder FDI inflows, including corruption, trade openness, access to finance, and political instability. Existing research mostly focuses on country-level data, with limited exploration of firm-level data, especially in developing countries. Recognizing this gap, recent calls for research emphasize the need for qualitative data analysis to delve into FDI determinants, particularly at the regional level. This paper proposes a novel methodology, based on text mining and social network analysis, to get information from more than 167,000 online news articles to quantify regional-level (sub-national) attributes affecting FDI ownership in African companies. Our analysis extends information on obstacles to industrial development as mapped by the World Bank Enterprise Surveys. Findings suggest that regional (sub-national) structural and institutional characteristics can play an important role in determining foreign ownership.