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Integrating political risk analysis

Despite its growing importance, political risk management is a relatively underdeveloped field. It requires comfort with qualitative assessment and more systematic integration with economic risk, argues Wells Fargo’s Richard Hamilton, CFA.

It is widely accepted that political risk is a growing concern for financial institutions, but political risk management as a discipline is much less developed than the fields of economic and market risk. Possible explanations include the relative difficulty of quantifying political risk, and that traditionally political risk has been viewed as the preserve of emerging rather than developed markets (the latter comprising a much larger proportion of companies’ exposure). This article published in CFA UK’s magazine Professional Investor (PI) outlines several concepts and tools that can be of value in political risk management, while also arguing that managing political risk in today’s environment requires greater reliance on (and comfort with) qualitative judgement and more systematic integration with economic risk.

Executive summary
• Although fine in theory, using structural features as a starting point for assessing political risk can promote a static and/or backward-looking view of political risk, which in many cases may be misleading.
• Incorporating cyclicality with structural features can help develop a more forward-looking view of political risk within a specific country or region.
• Electoral scenario planning, and technical analysis of financial markets are useful tools in identifying potential political (and economic) inflection points.


Most political risk frameworks incorporate some measure of a country’s structural political features, for example, the World Bank’s Worldwide Governance Indicators and Transparency International’s Corruption Perceptions Index. Despite methodological challenges of trying to quantify structural political factors, their quantitative and comparative nature is appealing. They can also be easily incorporated with other economic indicators which can reflect potential political instability, such as measures of inequality, volatility of growth/ inflation, youth unemployment, and percentage of workforce employed in primary sector etc.

Such structural indicators are valuable, but often viewed as insufficient, which is why they are frequently used in conjunction with some form of qualitative overlay. A qualitative overlay allows the analyst to notch a score or rating up or down based on their own view of a model’s quantitative output. Although fine in theory, using structural features as a starting point for assessing political risk can promote a static and/or backward-looking view of political risk, which in many cases may be misleading.

A more valuable starting point may therefore be to identify both structural and cyclical features of political risk. The cyclical nature of political risk in emerging markets is described in Sharma (2016)’s concept of ‘The Circle of Life’, where an initial period of political reform is followed by a growth boom, which leads to a period of complacency that eventually kills off reform, and causes another crisis. Such a trend may be most evident in emerging markets, but can also be seen (perhaps increasingly) in developed markets.

For instance, the ‘Circle of Life’ concept has parallels with Minsky (1992)’s financial instability hypothesis – periods of financial stability encourage excessive risk taking, thereby generating financial instability – which received renewed focus in the US and Europe following the global financial crisis. Indeed, the global financial crisis is arguably the main reason behind the current rise of populism and anti-globalisation sentiment being witnessed across Western democracies.

Incorporating cyclicality with structural features can help develop a more forward-looking view of political risk within a specific country or region. However, as alluded to above, it is almost impossible to view the political cycle as distinct from the economic cycle. As a result, a robust view of a country’s political risk profile requires an understanding of the reflexive nature of macroeconomics and politics. For example, both Turkey and South Africa are currently experiencing increased political risk, following a period of policy complacency (for example, lack of structural economic reforms aimed at boosting domestic productive capacity), which in turn followed a prolonged period of robust growth and capital inflows. However, significant differences economic and political structures imply variation in the likely severity and duration of the political cycle.


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Figure 2

In South Africa’s case, signs of political instability emerged earlier than in Turkey, as fallout from collapsing commodity prices stoked protest in the mining sector. Since then opposition to the government’s policy towards foreign mining firms has spread to broader protests against President Zuma’s administration and governance under the ANC. Turkey’s appears to be earlier in both the economic and political cycle than South Africa, although it’s weaker institutional setting (according to World Bank Governance Indicators) implies the cycle could be more prolonged and severe than that of South Africa.

The above may help predict changes (either positive or negative) in political stability at some point in the future, but it does not
necessarily help in timing those changes. Scheduled elections are therefore the most obvious inflection point for political change. While accurately predicting electoral outcomes is difficult, there is still significant value in the process of scenario planning around various outcomes, which can include mapping out likely policy trajectory in line with the expected economic trajectory.

Using the Italian Constitutional referendum as an example, Figure 2 shows a simplistic scenario tree which highlights likely (albeit contestable) scenarios in event of either a ‘Yes’ or ‘No’ vote. Through this process it becomes clear that regardless of the referendum’s outcome, Prime Minister Matteo Renzi’s government is unlikely to be in a strong position ahead of the next general election (currently scheduled for 2018). In other words, while a ‘Yes’ vote is currently seen as the least politically disruptive outcome for Italy and EU/eurozone, without material improvement in economic and banking sector stability and/or an event which severely diminishes support for the populist Five Star Movement (the first is looking unlikely, the second very hard to anticipate), Italy’s policy environment will likely remain unconducive to structural reform for the foreseeable future.

This referendum example is aimed at illustrating the potential value of ‘thinking through’ an electoral outcome, rather than simply viewing an election as a source of political risk. Such scenario planning is often complemented by including estimates of probability for various scenarios, although selecting probabilities is challenging, and can provide a misleading picture of likely outcomes. Moreover, if combined with results of similar analyses of other key elections (eg French and German elections), it can aid the development of internally-consistent view of regional policy trajectory, as well as help incorporate new information/developments when they arise.

In addition to electoral scenario planning, another useful tool for identifying potential political (and economic) inflection points is technical analysis of financial markets. While recognising the theoretical and methodological limitations of technical analysis (Lo & Hasanhodzic, 2010), it can help challenge consensus views on political stability, and more importantly help pinpoint when that consensus may be about to change. One such example is Brazil, when in late-2011/ early-2012 it was becoming increasingly apparent that the drivers of economic growth were weakening.

Brazil’s decade-long economic boom was evident in the long-term technical picture of the Brazilian real, which by late 2011/early 2012 had hit multi-decade highs of BRL1.5/USD. Real strength both reflected and was a symptom of Brazil’s imbalanced growth story – a highly-leveraged consumption model driven by cheap domestic credit and rampant capital inflows against the backdrop of a favourable global climate for commodity exporters. The steady erosion of domestic productive capacity combined with lower commodity prices implied that this growth model was increasingly unsustainable, and that real strength was unlikely to continue without exacerbating these imbalances. Therefore, once the currency broke through key technical support in early 2012 (see Figure 3), it was possible to anticipate with some degree of confidence that economic innstability was imminent, and that political fallout would follow given endemic corruption and the government’s large economic footprint.

To conclude, good political risk management requires greater comfort with qualitative analysis, and while the above concepts and tools are relatively simplistic, their application can still be rigorous. At the same time, political risk is just one component of country risk, and cannot be fully appreciated without understanding the interaction with the country’s economic profile.


Richard HamiltonRichard Hamilton, CFA, is deputy head of country risk analytics for Wells Fargo. Prior to joining the firm, he worked for seven years at BMI Research, now part of the Fitch Group, heading country risk teams for Latin America, Europe and most recently as head of BMI’s EMEA research team. He has also worked as a professor of international relations at Mexico’s Tecnológico de Monterrey, and has a masters degree in European politics.