Uncertainty Avoidance and Country Risk Ratings - Dissertation Example

?Uncertainty Avoidance and Country Risk Ratings The purpose of this dissertation is to explore the relationship between country risk ratings, the economic measures associated with the likelihood of sovereign debt default   and Hofstede’s Uncertainty Avoidance score. The chapter will outline the details of the study undertaken to address the questions posed in chapter one. Recent research on the changing nature of country risk due to globalization and the inherent rise in the interconnectivity of national economies (Cleary & Malleret, 2007; Baytas & Leveen, 2009; Sheppard, 2002; GAO, 2010) has called attention to the requirement for reliable country risk ratings to guide investment as these ratings are utilized by financial analysts as a tool to indicate the likelihood of payment defaults by sovereign borrowers (Hoti, McAleer & Shareef, 2007). Despite the importance of these country risk ratings, the utility of these measures for predicting market volatility has been called into question (DiGregorio, 2005; Oetzel et al, 2001) while global debt crises have occurred that have been likened to a heart attack for the international financial system (Gokay & Whitman, 2010).  Current literature on country risk ratings indicates a focus on political, financial, and economic factors without inclusion of social or cultural factors (Miroshnik, 2002). This chapter presents the results from statistical correlations between the economic indicators and the previous year country risk ratings (Step 1) and between economic indicators and uncertainty avoidance scores (Step 2).  The correlation will then be determined for the same economic indicators and a combination of country risk ratings and uncertainty avoidance scores (Step 3). The results of correlation between uncertainty avoidance scores and country risk ratings will also be presented.   Description of the Population and Sample In selecting the sample size three factors into consideration and the study came up with a sample size which will consist of a total of 49 countries including Argentina, Australia, Austria, Belgium, Brazil, Canada, Chile, Colombia, Costa Rica, Denmark, Ecuador, El Salvador, Finland, France, Germany, Greece, Guatemala, Hong Kong, India, Indonesia, Iran, Ireland, Israel, Italy, Jamaica, Japan, Malaysia, Mexico, Netherlands, New Zealand, Norway, Pakistan, Panama, Peru, Philippines, Portugal, Singapore, South Africa, South Korea, Spain, Sweden, Switzerland, Taiwan, Thailand, Turkey, United Kingdom, United States, Uruguay, and Venezuela.  This sample surpasses the minimum required sample size as computed from G*Power, which should reduce the possibility of committing Type II errors when running the analyses.  Data from the samples will be collected from the International Country Risk Guide database, Euro money Country Risk score database, Hofstede Uncertainty Avoidance Index database, and the World Bank databases. Table 4.1 Economic indicators and the previous year country risk ratings.               Years compared   Predictors 2007 ? 2008 2007 ? 2009 2008 ? 2009 2008 ? 2010 2009 ? 2010               Euromoney .998*** .906*** .908***       Intl Country Risk Guide .982*** .959*** .965***       Economic indicators                         Export growth     .132     .090 -.240   Ratio current account to GDP     .878*** .826*** .910***   Growth foreign exchange     .039*** .181*** .695***   Inflation     .892*** .867*** .950***   GDP per capita     .994*** .991*** .994***   Combined indicators     .528*** .445** .732***   **p< .01, ***p< .001, all 2-tailed. Source: International Country Risk Guide database To confirm the applicability of factor analysis a t-test was carried out at 95% confidence level. The table above shows all the identified economic factors that could probably affect a country’s risk ratings. The test results are only significant if the p-value or the significance value of the test is lower than .05.  The t-test statistics (table above) shows that all identified motives were significant since the t-critical (.05) is less than the t-calculated for all motives. Table 4.2: Economic indicators and uncertainty avoidance scores       Predictors Economic indicators N   Euro money 2007 Intl Country Risk Guide 2007 Uncertainty Avoidance Combined indicators 2008 45 r= .427** .575*** -.447** Combined indicators 2009 45 r= .457** .627*** -.459** Combined indicators 2010 45 r= .642*** .686*** -.529***                                  p< .05,  **p< .01,  ***p< .001, all 2-tailed.   Source: Euro money 2007. The table above shows combined indicators of the years 2008, 2009 and 2010. The motives identified are all insignificant since the t-critical is greater than the t-calculated. This indicates economic indicators do not in any way affect a country’s uncertainty avoidance. Table 4.3: economic indicators and a combination of country risk ratings and uncertainty avoidance scores Dependent variable Step Predictor ? R2 R2 change Combined indicators 2008 1 ICRG 2007 .612*** .374***     2 ICRG 2007 .508***         Uncertainty avoid -.239 .420*** .046   Combined indicators 2009 1 ICRG 2008 .627*** .393***     2 ICRG 2008 .527***         Uncertainty avoid -.237 .439*** .046 Combined indicators 2010 1 ICRG 2009 .686*** .471***     2 ICRG 2009 .565***         Uncertainty avoid -.297* .544*** .073*   Source: International Country Risk Guide database   4.4 Summary and interpretations The research was motivated by uncertainty and country-risk ratings which have lead to great financial consequences that have hit economies across the world. Risks and in a country dictate the decision of individuals, firms and corporation to invest this is because profitability which is the main reason for a business is at stake. Economic indicators are very important components of country risks. From our findings are found to be significant in that economic risk is the significant change in the economic structure or growth rate that produces a major change in the expected return of investment. The research presents evidence that uncertainty avoidance influences risk taking for instance cultural influences where individuals are controlled by their various beliefs before engaging in investments of all kinds. The results identify various economic factors through which culture exerts its influence on risky investments decision-making.  Despite many believes that only economic factors are relevant in decision making the paper provides strong evidence of other factors for instance culture. These results are relevant to investors who can base their decisions accordingly.              5.0 CONCLUSION, LIMITATION AND RECOMMENDATIONS 5.1 Introduction In this chapter, the research discusses the main findings, draws conclusions and makes recommendations. The objectives of the study are to determine if there exists a statistically significant relationship between each of five economic indicators will determine the relationship between economic indicators and uncertainty avoidance scores and analyses will determine if there exists a statistically significant relationship between the same economic indicators and the same country risk ratings in combination with the uncertainty avoidance cultural dimension ratings. 5.2 Conclusion Risks can reduce the expected return on an investment and must be taken into consideration before investing in a country. Economic indicators are most commonly found to be significant in this research. Risks arise due to change in the economic factors of a country for instance a country with a high debt-to-GDP ratio may not be able to raise money as easily  to support itself this puts its economy at risk. Firms can also delay investments in terms of uncertainties; different societies react differently to risks due to their different practices. Financial crisis have large economic consequences because these periods are of heighted uncertainty, investments tend to decrease relative to economic factors in these places. 5.3 Recommendations There arises a need to conduct country risks and uncertainty avoidance surveys should be carried out in developing countries more since it is easier and involves less risk to invest in developing economies than in mature economies. This will also ensure growth of these economies put them in a better positions to compete in the global market. Read More