Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/164643
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dc.titleTHE RELATIONSHIP AND IMPLICATIONS OF GOVERNANCE INDICATORS ON SOVEREIGN RATINGS
dc.contributor.authorMARTIN WEI EN INDRAWATA
dc.date.accessioned2020-02-19T06:19:51Z
dc.date.available2020-02-19T06:19:51Z
dc.date.issued2019-11-01
dc.identifier.citationMARTIN WEI EN INDRAWATA (2019-11-01). THE RELATIONSHIP AND IMPLICATIONS OF GOVERNANCE INDICATORS ON SOVEREIGN RATINGS. ScholarBank@NUS Repository.
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/164643
dc.description.abstractThis thesis aims to determine which governance indicator(s) is the most significant in explaining variations in sovereign ratings. Previous studies into the general determinants of sovereign ratings have approximated the strong influence of political risk factors into the evaluation of sovereign ratings. However, the inclusion of political determinants has been mainly to avoid omitted variable bias in econometric analyses. In spite of existing scholarship, deeper scrutiny into political determinants have yet to be established. The puzzle remains: which is the most significant political determinant in explaining variations in sovereign ratings? Specifically, which is the most significant government effectiveness indicator? This thesis provides a qualitative and quantitative treatment of the research question, by first constructing a theoretical relationship between government effectiveness, sovereign risk, and variation in sovereign ratings. Thereafter, a linear panel regression model is used to study the relationship between governance indicators and sovereign ratings. Using Worldwide Governance Indicators (WGI) and sovereign ratings of up to 65 countries between 2005 and 2015, this thesis finds that the indicators of “Regulatory Quality” and “Political Stability” are the most significant explanatory variables for variability in sovereign ratings. Second, considering only WGIs and not macroeconomic variables, this thesis finds that the composite linear model explains more than 20% variability in sovereign ratings within the sampled observations.
dc.typeThesis
dc.contributor.departmentPOLITICAL SCIENCE
dc.contributor.supervisorMENNILLO GIULIA
dc.description.degreeBachelor's
dc.description.degreeconferredBACHELOR OF SOCIAL SCIENCES (HONOURS) IN POLITICAL SCIENCE
Appears in Collections:Bachelor's Theses

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