Abstract
Political risk assessment, together with portfolio analysis, has become an important part of international business investment decision making. In this paper, by using different knowledge discovery techniques, we attempt to assess the relevance and actionability of 'good governance' indicators in political risk assessment. For that purpose, we have integrated good governance indicators data with political instability classification from the Political Instability Task Force (PITF) research. From this study, two models that capture the intuitive reasoning of investors have been developed. The usefulness of the models has been evaluated by comparison with factual investment data. Our findings suggest that quantitative indicators of good governance may provide the basis for accurate and meaningful models for the assessment and prediction of political risk.
| Original language | English |
|---|---|
| Pages (from-to) | 144-156 |
| Number of pages | 13 |
| Journal | Research in International Business and Finance |
| Volume | 23 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - Jun 2009 |
Keywords
- Data mining
- Good governance
- Investment risk
- Machine learning
- Political instability
- Statistical analysis
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