Document Type
Article
Source
Journal of Business and Retail Management Research
Publication Date
10-2016
ISSN
20566271
Volume
11
Issue
1
Abstract
Most of the existing literature in the FDI-political risk nexus has focused on the creation of economic models to assess foreign investment decisions in the presence of political risk. This is entirely legitimate and valuable as foreign investors are interested in assessing the political risk climate of their investment location. However, not much research has been done to assess how FDI could affect political risk. Globalization implies an increasing amount of cross-border investment and trade flows. For some countries, FDI is a huge component of their GDP. Since FDI is a composite bundle of capital stock, knowledge and technology (Balasubramanyam et al, 1996) and represents “International investment made with the objective of obtaining a lasting interest, by a resident entity in one economy in an enterprise resident in another economy” (OECD, 2000), we postulate that because of this stakeholder commitment, FDI could affect a country’s political risk level.
The management literature has it that political risk measures the stability of individual countries based on factors grounded in government, society, security, and the economy (Bremmer, 2005). We expand on this notion to investigate whether, and if so, how FDI affects political risk? We believe that the contribution of our study is specifically in examining this reverse relationship running from FDI to political risk. In this preliminary paper we test this hypothesis for a sample of thirty countries in various stages of economic development and regime types over the 1984-2012 period. Preliminary results indicate that countries with increased FDI inflows demonstrate decreased levels of political risk. Although there are variations across countries, country groups that are considered developed and full democracies tend to exhibit the lowest levels of political risk. Our ongoing research is examining a sample of 140 countries using both time series and panel data techniques.
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