The Ellen Johnson-Sirleaf administration, which came to power in 2006 after the end of a nearly fifteen year civil war, has made foreign direct investment (FDI) the centerpiece of its growth and development strategy. However, unlike other governments that have sought to benefit from FDI through technology and knowledge transfers, the Liberian authorities have pursued a strategy of requiring that investors provide public goods in specific geographic areas. It is not clear if this strategy, which is designed to set in motion agglomeration processes, improves local economic growth outcomes. This paper presents first-of-its kind, quasi-experimental evidence on the economic impacts of natural resource sector FDI. We first construct a new dataset of more than 550 sub-nationally georeferenced natural resource concessions that the Liberian government granted to investors between 2004 and 2015 (Liberia Concessions Geocoded Research Release, Version 1.0); for the associated methodology, see An Open-Source Methodology for Tracking Natural Resource Concessions in Liberia: Version 1.0). We then merge these georeferenced investment data with survey- and satellite-based outcome and covariate data at the 1km x 1km grid cell level. We use remotely sensed data on nighttime light to measure local economic growth and propensity score matching methods to compare growth in otherwise similar locations with and without FDI. Our results suggest that, in general, natural resource concessions improve local economic growth outcomes. However, there is important variation across different types of concessions and concessionaires. Mining concessions outperform agricultural concessions, and concessions granted to Chinese investors outperform concessions granted to U.S. investors.
Funding: We thank Humanity United, the William and Flora Hewlett Foundation, and the International Growth Center for generous funding that made this study possible. This study was also indirectly made possible through a cooperative agreement (AID-OAA-A-12-00096) between USAID’s Global Development Lab and AidData at the College of William and Mary under the Higher Education Solutions Network (HESN) Program, as it supported the creation of a spatial data repository and extraction tool which we used to execute our data analysis. The views expressed here do not necessarily reflect the views of Humanity United, the International Growth Center, the William and Flora Hewlett Foundation, the College of William and Mary, USAID, or the United States Government.