Academic journal article
By Meldrum, Duncan H.
Business Economics , Vol. 34, No. 3
Management teams usually have well-established methods to assess the riskiness of a business transaction or project in their home country. Move the project into another country, however, and another dimension of uncertainty overlays the analysis. This additional dimension, typically called country risk, encompasses the uncertainty of achieving expected financial results solely due to factors relating to the project's location in another country. Currency fluctuations, profit repatriation issues, macroeconomic performance, political or legal issues are just some of the factors that may create risk in cross-border transactions.
Country risk analysts need a comprehensive knowledge of international and macro economics as well as an understanding of the history and sociopolitical institutions in the target country to make a complete risk assessment. And while project risk usually lies outside the purview of country risk, analysts also need to know which country factors produce the greatest uncertainty for their company's proposed activities in a target country. For example, a short-term financial transaction or one-time equipment export to Brazil faces a much different country risk factor than does the construction of a plant in Brazil designed to produce a product for the MERCOSUR market for the next twenty years.
Country risk assessment often attempts to identify the impact of sociopolitical changes or relatively infrequent economic shocks that cannot be predicted from statistical analysis of country data. A full risk study therefore theoretically requires qualitative as well as quantitative assessment. The translation of theory to practice, however, suffers from a number of issues in a quantitatively oriented world. To meet the quantitative demand, many risk systems convert qualitative factors into numbers based on vague or nonexistent theoretical underpinnings, then combine these numbers into a single ad hoc risk measure. Other systems focus heavily on macroeconomic data measures, whether or not those measures theoretically relate to risk, and downplay qualitative issues for which no data exist.
Coplin and O'Leary (1994) describe in detail the construction methods of nine popular risk measures available by subscription or through publications. Their review suggests to me that the qualitative aspects tend to make risk assessment more art than science, with risk forecasts easily influenced by the subjective biases of the individual risk assessor. This bias potential appears especially high in those systems that turn qualitative assessments into numbers, then combine the numbers into a single risk measure. Users of externally acquired risk measures need to understand these biases as well as the theoretical underpinnings, horizon, and intended uses of the measure. For example, some risk measures designed to signal today's currency risk in Latin America show a lower risk than forward-looking measures of economic policy risk. This implies that the exporter to Brazil in the earlier example faces a lower risk than the owner of the new plant.
Finally, some truth-in-advertising: I am not a country risk expert. While I took a few graduate courses in country risk analysis, I spend a very small part of my time on country risk assessment. Our strategic planning process, however, requires the company's economics function to assess longer term country risk. Because I have been unable to find an external measure that meets all of our needs, I have developed a system to organize my thinking in a structured manner that approximates the way a theoretical country risk assessment might proceed. Complete risk assessments require significantly more resources than I have available, so I have been compelled to quantify some subjective factors in my system. I acknowledge the resulting limitations by using the system only to identify economic forecast risks and to flag countries or factors for more in-depth analysis. …