Political risk quantification using fuzzy set approach

Sachs, T; Tiong, R and Wagner, D (2007) Political risk quantification using fuzzy set approach. Journal of Financial Management of Property and Construction, 12(2), pp. 107-126. ISSN 1366-4387

Abstract

Negative perceptions of political risk can prevent capital from being committed to support cross-border investment. Information about risks that impact infra-structure projects is often vague, imprecise, subjective, or ambiguous. Political risks in developing countries also often lack meaningful historical and numerical data. A novel fuzzy set approach for quantifying qualitative information on risks (QQIR) in structured finance transactions that bridges the gap between qualitative and quantitative risk assessment methods has been developed. The QQIR Method is validated empirically through the results of an international survey to determine the impact of perceived political risk on Asian infrastructure projects. The impact is measured by the effect on financial project criteria. The impact was assessed across 14 Asian countries and 14 infrastructure sectors. The survey findings are validated by triangulation of three data sets and employing non-parametric statistics. The validation shows that in 77.5% of all observations the QQIR Method produces mean results that are within 0.85 standard deviations of the absolute values, without elimination of any seemingly unusual or unreasonable responses or data. The validation also shows that with increasing perceived risks, the costs of equity investment, debt finance, and insurance also increase. The QQIR Method is thus a valid tool to quantify perceptions on risks. In this case it has been applied to political risks, but the Method is generic and may be applied to any problem set in which perceptions can be structured and assessed with opinions.

Item Type: Article
Uncontrolled Keywords: fuzzy sets; infrastructure; political risks; risk quantification; survey
Index terms: validation, triangulation, infrastructure sector, international survey, developing country, survey, insurance, risk assessment, debt finance, infrastructure project, statistics, quantification, fuzzy set, deviation
Subjects: research products and data, economic analysis, financial and cost management, research design and methodology, mathematical modelling, data collection methods, measurement and scaling, industry analysis, infrastructure and transport systems, decision-making and optimization, financial risk, development economics, professional development
Topics: International Construction, Business Strategy, Cost Management, Research Practice, Engineering Principles, Information Management
Descriptive scope: 4 PCEA

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