Abstract
Prior research has demonstrated that corruption has largely negative effects on incoming international investments. What is less clear, however, is to what extent these negative effects are a product not of a host country’s absolute level of corruption, but of the relative distance to the home country’s degree of corruption. We define the Directional Corruption Distance (DCD) as the arithmetic difference between two countries’ corruption levels. Avoiding distorted FDI measures, we analyze the change in Research & Development Stock (RDS) representing more than 10,000 R&D centers of 500 technology-intensive MNCs taken from the Fortune 1000 list. Qualifying earlier research employing FDI as a dependent variable, we observe that countries of lower corruption are preferred destinations (Trading Up Hypothesis), but only under certain conditions. We further show that developed countries with lower degrees of corruption tend to prefer investments in other low-corruption countries (Comfort Hypothesis). High- corruption countries, conversely, do not exhibit this behavior and appear more open towards investment in other high-corruption countries (Familiarity Hypothesis). These findings underscore the influence of contextualizing variables in the origin of investments, and suggest extended research using firm-level field data to compensate for potential bias and flaws in FDI data.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
