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Innovative methods in assessing political risk for business internationalization

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  • Rios-Morales, Ruth
  • Gamberger, Dragan
  • Smuc, Tom
  • Azuaje, Francisco

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.

Suggested Citation

  • Rios-Morales, Ruth & Gamberger, Dragan & Smuc, Tom & Azuaje, Francisco, 2009. "Innovative methods in assessing political risk for business internationalization," Research in International Business and Finance, Elsevier, vol. 23(2), pages 144-156, June.
    • Handle: RePEc:eee:riibaf:v:23:y:2009:i:2:p:144-156
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    Cited by:

    1. Jiayan YU & Jingqian ZHANG & Hee Eun SHIN & Jooan KONG, 2019. "Revisiting the Economic Crisis after a Decade: Statistical and Machine Learning Perspectives," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 2, pages 14-19.
    2. Jianping Li & Xiaolei Sun & Fei Wang & Dengsheng Wu, 2015. "Risk integration and optimization of oil-importing maritime system: a multi-objective programming approach," Annals of Operations Research, Springer, vol. 234(1), pages 57-76, November.
    3. Muhammad Azam & Muhammad Khan & Nasir Iqbal, 2012. "Impact of Political Risk and Uncertainty on FDI in South Asia," Transition Studies Review, Springer;Central Eastern European University Network (CEEUN), vol. 19(1), pages 59-77, September.
    4. Matkovskyy, Roman & Bouraoui, Taoufik & Hammami, Helmi, 2016. "Analysing the financial strength of Tunisia: An approach to estimate an index of financial safety," Research in International Business and Finance, Elsevier, vol. 38(C), pages 485-493.
    5. Liu, Chang & Sun, Xiaolei & Chen, Jianming & Li, Jianping, 2016. "Statistical properties of country risk ratings under oil price volatility: Evidence from selected oil-exporting countries," Energy Policy, Elsevier, vol. 92(C), pages 234-245.
    6. Prüfer, Jens & Prüfer, Patricia, 2018. "Data Science for Institutional and Organizational Economics," Other publications TiSEM 4392ac65-4fb6-4e9a-a92d-5, Tilburg University, School of Economics and Management.
    7. Jens Prüfer & Patricia Prüfer, 2018. "Data science for institutional and organizational economics," Chapters, in: Claude Ménard & Mary M. Shirley (ed.), A Research Agenda for New Institutional Economics, chapter 28, pages 248-259, Edward Elgar Publishing.
    8. Gozgor, Giray, 2018. "Determinants of the domestic credits in developing economies: The role of political risks," Research in International Business and Finance, Elsevier, vol. 46(C), pages 430-443.
    9. Prüfer, Jens & Prüfer, Patricia, 2018. "Data Science for Institutional and Organizational Economics," Other publications TiSEM 6d04f0fe-0bcd-4cf4-86f6-f, Tilburg University, School of Economics and Management.

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