Greenfield foreign direct investment: Social learning drives persistence

B-Tier
Journal: Journal of International Money and Finance
Year: 2022
Volume: 126
Issue: C

Score contribution per author:

0.503 = (α=2.01 / 4 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

This paper argues that the persistence of greenfield foreign direct investment (FDI) comes from information frictions. First, our simple social learning model shows that, through signaling effects, information frictions generate persistent greenfield FDI inflows. Second, we show empirically that the autoregressive coefficient of greenfield FDI increases in value with different proxies for information frictions, including six institutional and governance indicators and two common language measures. We also find that greenfield FDI persistence varies across industries. In particular, greenfield FDI by service firms is more persistent than that by manufacturing firms. Finally, our findings suggest that better governance, predictability, and transparency reduce information frictions and thereby avoiding drastic and persistent ups and downs in FDI.

Technical Details

RePEc Handle
repec:eee:jimfin:v:126:y:2022:i:c:s0261560622000444
Journal Field
International
Author Count
4
Added to Database
2026-01-25