Greenfield Foreign Direct Investment: Social Learning Drives Persistence

Joe Cho Yiu Ng*, Tommy Chao Hung Chan, Kwok Ping Tsang, Charles Ka Yui Leung

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

3 Citations (Scopus)

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.
Original languageEnglish
Article number102641
JournalJournal of International Money and Finance
Volume126
Online published5 Apr 2022
DOIs
Publication statusPublished - Sept 2022

Bibliographical note

Research Unit(s) information for this publication is provided by the author(s) concerned.

Research Keywords

  • Greenfield FDI
  • persistence
  • information
  • social learning

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