Greenfield foreign direct investment: Social learning drives persistence

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: ISER Discussion Paper ; No. 1171

Classification and Topics

• Classification: Wirtschaft ; Single Equation Models; Single Variables: Panel Data Models; Spatio-temporal Models ; Multinational Firms; International Business ; Firm Behavior: Theory ; Firm Behavior: Empirical Analysis
• Subject: Greenfield FDI ; persistence ; information ; social learning

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Ng, Joe Cho Yiu ; Chan, Chao Hung ; Tsang, Kwok Ping ; Leung, Charles Ka Yui
• Event: Veröffentlichung
• (who): Osaka University, Institute of Social and Economic Research (ISER)
• (where): Osaka
• (when): 2022

Further information

• Handle: http://hdl.handle.net/10419/263307
• Last update: 10.03.2025, 11:45 AM CET