Arbeitspapier

Greenfield foreign direct investment: Social learning drives persistence

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.

Language
Englisch

Bibliographic citation
Series: ISER Discussion Paper ; No. 1171

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

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

Handle
Last update
10.03.2025, 11:45 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Ng, Joe Cho Yiu
  • Chan, Chao Hung
  • Tsang, Kwok Ping
  • Leung, Charles Ka Yui
  • Osaka University, Institute of Social and Economic Research (ISER)

Time of origin

  • 2022

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