In the latest edition of Global Horizons, Stephanie Kelly, Political Economist, outlines SLI’s analytical framework for assessing the factors that drive political risk and the potential consequences for investors. By identifying risk factors within two distinct categories, institutional and cyclical, it is possible to identify the key drivers of political risk events and build an investment view that takes these factors into account. The framework is especially useful for examining the key political events of 2017 and considering how likely they are to deliver further shocks to the status quo.
Executive summary
- Following a year of unexpected political events in advanced economies on both sides of the Atlantic, investors have become more aware of the impact of political risk on market outcomes. In this paper, we set out an analytical framework for assessing the drivers of that risk. We highlight how institutional risk factors shape the way political systems function, lay the foundations for economic and financial market activity, and interact with cyclical factors that influence government stability and the frequency of risk events.
- Using this framework, we identify electoral risk as a key form of political risk that played a leading role in market volatility in 2016 in the US, UK and Europe. We define the key variables that drive electoral risk, including the nature of the electoral system, voter ideology and polling accuracy. Our analysis shows that electorates in the advanced economies have become more fragmented and polling has become less accurate over the past three years; right-wing populist parties in particular have confounded pre-election opinion polls.
- Recent elections in Spain, Portugal and Ireland illustrate how political risk factors can lead to delayed and unstable government formation, creating heightened policy uncertainty and inefficient policymaking. Our econometric analysis shows that sustained increases in generic policy uncertainty can have meaningful effects on economic and market activity, although the impact can vary significantly across countries. In particular, GDP growth, equities and the real exchange rate in Europe appear to be more sensitive to economic policy uncertainty shocks than their US counterparts.
- In the presence of political risk, scenario analysis is an effective tool for considering the consequences of different political outcomes. In the case of the US election, our pre-election scenario analysis showed that individual and corporate income tax cuts were a likely consequence of Donald Trump winning the presidential election and Republicans retaining control of both the House of Representatives and the Senate. However, it also pointed to potential conflicts in other areas of policy as the president’s populist agenda rubbed against traditional congressional Republican priorities. Investors initially reacted favourably to the election result but tail risks from anti-growth trade and immigration policies remain acute.
- Our political risk framework and empirical findings can also be applied to the European elections that will take place in 2017. In France, the two-round French presidential system makes it difficult for non-centrist parties to win elections, but a surprise win for Marine Le Pen has the potential to create an existential crisis for both the Eurozone and the European Union. The German federal election, which is due in September, carries comparatively less risk. This is due to the smaller levels of support for right-wing populist parties, the country’s history of centrist coalition building and the fact that the most probable alternative to a Merkel-led government is an even more pro-European Social Democratic-led coalition government.
- Although national elections are not due in Italy until 2018, snap elections are possible after Matteo Renzi resigned in the wake of his defeat in December’s constitutional referendum. The rise of the populist Five Star Movement is keeping investors up at night, but changes to the electoral system are a moderating factor. Meanwhile, the Netherlands election has been flying below the radar somewhat. More generally, the probability that one of these European political risk events crystallises this year appears to be underestimated by investors.
Risky business
Many of the major market-moving events in the advanced economies during 2016 were politically driven: the UK referendum on EU membership, the US presidential election and the Italian constitutional referendum. Political uncertainties also cast a shadow over 2017 as investors weigh up the implications of a Trump presidency, the French presidential election, the German general election and the commencement of Brexit negotiations. Investors are more aware than ever of the powerful effect that these kinds of political events can have on economic and market outcomes, and the dangers of assuming that the status quo will be maintained. We have therefore developed an in-house framework for assessing political risk.
Our starting point is to adopt a simple taxonomy of political risk for investors, based on research into best practice in political risk analysis (see Figure 1). For investors, political risk is ostensibly the threat of a market-unfriendly outcome as a result of political factors. From an investment point of view, bottom-up investors (micro) and top-down investors (macro) are exposed to the same factors that drive political risk but the triggers within these categories can be different. Within both investor groups, there are two major aspects to consider when analysing political risk: institutional and cyclical. By understanding the institutional and cyclical factors driving a potential political risk event, investors can build their investment view taking into account political risk in a structured, holistic way.
Institutional risk factors arise from the structure of political and legislative institutions of a particular country. These can be internal (strength of institutions) or external (strength of transnational political constraints, e.g. EU membership). The factors that are widely incorporated into political risk scores produced by private and public research firms mostly fall into this subset. These ordinarily include voice and accountability, political stability and absence of violence, government effectiveness, quality of regulation, rule of law and control of corruption. The features of a country’s electoral system also deserve explicit mention: the voting system (proportional representation, first-past-the-post), election frequency as specified in legislation, the historical structure of governments (e.g. coalitions, majority, minority governments), historical voter turnout and historical polling accuracy all warrant inclusion as key institutional risk factors for investors. These components serve to lay the groundwork as to the type of country an investor is dealing with based on long-term, fairly static data and form the political foundation for economic and market performance.
Cyclical factors incorporate the time-sensitive, day-to-day aspects that contribute to political risk. Within this risk class, we identify three principal categories: elections, procedures and country rating. The former refers to the period of time until Election Day, election outcomes and government formation. As Election Day approaches, political uncertainty can be heightened as the risk that the outcome will be market-unfriendly becomes more immediate. The procedural factor refers to events that occur as a result of legislative negotiation and parliamentary policymaking. A number of aggregate political risk scores from private political risk firms also incorporate temporal risks along the same lines as these cyclical factors.
Critically, these political risk factors also interact and reinforce one another. Institutional factors provide the foundation upon which cyclical factors wax and wane; the stronger the institutional factors, the less extreme cyclical factors will tend to be in absolute terms. This is why advanced economy political risk on the whole tends to be lower and less volatile than in emerging markets, where the underlying institutions are less fully formed and transparent. That is not to underplay the relevance of political risk for developed markets. Indeed, it is political risk in the advanced economies that is more likely to be underestimated, as emerging market analysts have traditionally been more active in incorporating political risk into their research processes.
The advanced economies are also not immune from institutional political risks; in post-crisis Europe, we have seen political ideologies diverge over the future of the European Union and Eurozone integration amid significant institutional change. As the strength and complexity of these institutional uncertainties have built up, a confidence cliff has emerged. The potential for member state departure or the breakdown of the EU itself creates especially large downside risks for risk assets whose prices are dependent on the maintenance of the single currency of the Eurozone and the single market of the EU.
Measuring political risk
Unfortunately, investors can often be reactive with regards to political risks; becoming acutely aware of political risk only right before, or even worse after, the event. While some political risk events are sudden, most build over many months or even years. Being aware of the institutional and cyclical factors that drive the economic and market outlook and how these may change allows investors to evaluate and track political risk in a systematic way.
Aggregate political risk scores are a popular form of risk measurement. A number of public and private firms offer this kind of scoring system to reflect the political risk in the system, which can incorporate institutional and cyclical factors similar to the ones we outlined above. These scores, if well-constructed, can be informative as a scene-setting device or as an indicator of whether something fundamental has changed. However, they have important limitations for gauging political risk.
Firstly, the construction of risk scores is often based on an equal weighting of long-term institutional factors. These scores are built using databases that have variable and significant lags; an aggregate risk score constructed for 2016 can be based on a mix of data from a number of years, such that it does not reflect the current reality, let alone any consideration of the near future. The equal weighting also means that important legislative or institutional change that affects a specific investment strategy might not show up if all other things remain equal. In other words, the magnitude of the change for the strategy is not reflected in the final score. Secondly, political risk firms often rely on specialist analysts to provide qualitative score changes based on political events. While this is more time-sensitive than longer-term scores, the drawback is that the methodology is often unclear and subject to individual analyst bias.
Bearing in mind these limitations, scores can play a role in comparative work by looking at a snapshot of the institutional backdrop of a given country. The score sheet in Appendix 1 illustrates a selection of what we consider the most pertinent International Country Risk Group political risk scores, alongside our own scoring for electoral systems and transnational agreements. We carried out cluster analysis – a popular approach to statistical analysis among political scientists and economists that groups countries with similar political risk score profiles – in order to identify patterns across the countries we look at. Table 1 illustrates the five main clusters that emerged from the analysis.
Comparing the groups to their individual scores (see Appendix 1) we find that:
- Countries in Cluster 1 and 2 both exhibit high levels of transparency, transnational cooperation and representativeness. However, Cluster 1 is distinguished from Cluster 2 for having lower levels of governmental stability in an otherwise high ranking score set.
- Cluster 3 countries tend to have high levels of corruption and low levels of law and order relative to countries in the other clusters.
- Cluster 4 countries display high levels of governmental stability but poor representativeness, symptomatic of the quasi-authoritarian political systems in these states.
- Cluster 5 countries have a wide variation in their component scores, leaving their aggregate scores in the lower half of the country political risk distribution. For Italy, Greece, Czech Republic and Korea, weaknesses are most closely related to corruption; Spain, Portugal and Chile are more likely to suffer from governmental instability.
While this analysis is useful for identifying key institutional strengths and weaknesses within countries, and also sheds light on why the peripheral Eurozone countries have proved more vulnerable to crises, we advocate a more nuanced approach to political risk analysis. This combines qualitative and quantitative factors and is anchored in our political risk template, rather than just relying on aggregate scoring. The first step in the development of this template involves isolating the institutional and cyclical factors to identify the political risks as laid out in the taxonomy. The second step is to incorporate these political risk factors into the macro and policy outlook to allow a holistic and rational view of the political risks at play in markets.
Using the Political Risk Template: Electoral Risk
A useful example of how to utilise the political risk template, because it is a major source of concern for investors, is electoral risk (i.e. a specific form of political risk that arises around an election period). We know that asset prices are often volatile in the run-up to and in the wake of elections.The degree of uncertainty and risk of a market-unfriendly outcome result from how institutional and cyclical electoral risk factors interact. We identify the following as the most important electoral risk factors.
Institutional factors
The voting system in a democratic country is the way in which votes are collected and distributed. The main methods are first-past-the-post (as used in the UK and US), proportional representation (used in much of Western Europe, preferential voting (Australia), and hybrid systems. These voting systems favour different outcomes. First-past-the-post tends to benefit larger parties and single party majorities, often leading to more stability and policy predictability. Proportional representation is associated with a more even spread of votes and seats across parties, which benefits smaller parties and increases representativeness. It can lead to uncertainty immediately after elections while parties attempt to form coalitions, and those coalitions are not always stable. However, it may also reduce the risk of a more extreme marketunfriendly result, such as a majority for a Europhobic populist party. The frequency of elections influences the stability of the political and economic system. Investors prefer stability in government (unless that government is not considered marketfriendly) and a minimum time is often required for a policy course to be charted and implemented. Countries that are prone to governmental flux and frequent elections more often struggle to address structural issues or enact viable reforms.
The historical structure of governments – whether they tend towards majorities, minorities, or coalitions – has important implications for confidence in policy making. Minority governments can find it hard to enact legislation, while coalitions tend toward slow and incremental change. In countries without a history of coalition building, it can be very difficult for parties to adapt if they have no chance of ruling alone. This can make both government formation and policymaking difficult, heightening economic and market uncertainty.
Voter turnout, both in aggregate and of different demographic groups, is an indicator of engagement in the system and is particularly important when considering “what is changing”. In many recent elections, formerly unengaged voters have swung results, such as in the UK referendum (see Chart 1). Furthermore, older people are more likely to vote and parties that capture them are more likely to be successful.
The perceived quality and legitimacy of transnational and domestic institutions like the European Monetary Union, free trade agreements, electoral system, and government checks and balances, can dominate election campaigns. We have recently seen this play out in various European elections, the UK referendum and the US presidential election, with political party success made and broken on the basis of their attitudes to unpopular institutions.
Cyclical factors
The number of parties in the system with a significant share of public support during an election period influences pre-election political risk. In particular, risk is higher the larger the number of well-supported parties because it raises the likelihood of unstable coalition governments (see Chart 2).
The degree of ideological dispersion across the major parties in the system also influences pre-election political risk. In particular, the greater the dispersion, the greater the potential for change in the policy environment and the more difficult it is for coalitions to form and be sustained. The ideological dispersion of voters affects both the policies of parties, as they try to capture more of the electorate, and the election outcome itself. This factor also interacts with the number of parties: if there are lots of parties and voter ideology is widely dispersed, votes will be widely spread across parties, making a coalition much more likely than a single party majority. This also makes it harder for governments to develop and implement broadly supported policy reforms. Persistent ideological dispersion among voters can also encourage the creation of new parties or political leaders to satisfy voters on the ends of the spectrum.
Because polls are the key data points used by analysts in the run up to elections, polling accuracy is an element of cyclical political risk. The accuracy of polling in a country is a function of their frequency, variety and methodology. The more accurate polls are, the lower the chance of a shock on Election Day. However, polling should always be analysed probabilistically and used in conjunction with fundamental models, and now, with the advent of more sophisticated analytical tools, big data and artificial intelligence models that harness information from social media. This is particularly cogent given the difficulties capturing support for right-wing populist parties in recent years (see Box 1).
Box 1: Polling bias in the post-crisis world
In light of recent elections in both the UK and US, where pre-election polling gave an inaccurate steer about the final result, we were interested in whether there has been a more systematic tendency for polling to be biased across the major advanced economies in recent years. To answer this question we used a simple method of comparing pre-election polling averages (typically the last 6-10 polls conducted before the election) and the final share of the vote for both a country’s largest post-election party and its largest ‘populist’ party in elections since 2010.
Key takeaways:
- Populist parties increased their vote share in 7 out of the last 8 elections.
- The average gap between populist parties’ support in pre-election polls and their final vote share was 1.6%. For the victorious party, it was 0.6%.
- Right-wing populist parties (non-status quo outcomes in the case of referenda) outperformed their pre-election polling in nine relevant elections or referenda across 10 countries. This suggests a systematic under-reporting of right-wing populist support (Chart 3). Five out of these nine were greater than the typical margin of error.
- Conversely, polling has tended to be more accurate in those cases where the largest party was centrist; in 22 such cases, only five results were outside the normal margin of error.
- Polling accuracy appears to have been on a deteriorating trend since 2010 as most of the large polling misses have taken place since 2013 (see Chart 4).
Regional Case Study: post-crisis peripheral European fragmentation
The drivers of electoral risk are important not only in their own right but also in how they converge to produce policy and market-impacting outcomes. The rise of populist/non-mainstream parties on the left in a number of countries on the European periphery and the difficulties in government formation as a result is illustrative of a trend of political fragmentation in postcrisis countries. This has been facilitated by some of the institutional and cyclical risk factors we have noted.
Key characteristics: Before the crisis, political power in Spain, Portugal and Ireland had oscillated between traditional centreleft and centre-right parties despite the prevalence of proportional representation. Since the crisis, however, popular support has fragmented and proportional representation has facilitated split representation across a more ideologically dispersed set of parties. This has in turn has made it harder to build coalitions, leading to minority governments.
What has mattered in this sample of countries is the confluence of poor economic outcomes with institutional and cyclical political risk factors to drive specific political outcomes. In each country, government formation was delayed following the election result. In Ireland in 2016, it took 63 days to form a government, which was ultimately minority-led, compared with its post-1990 average of 20 days.
Meanwhile, in Portugal in 2015, the government took 58 days to be formed following the election, again resulting in a minority-led government (significantly longer than its 21 day average). Finally, Spain’s historic average is double that of Ireland and Portugal at 42 days. However, the country’s 2015 election smashed that record, with parties taking over 300 days to form a government. Once again, the ultimate outcome was a minority-led government as parties struggled to reach a coalition consensus.
There are a number of countries in Europe that at first pass seem similar to these countries, but are in reality missing one or more key cyclical or institutional factors from above, and so did not display the same post-election pattern. Take for example Greece, which fulfils some of these criteria; Syriza, a populist Eurosceptic party, came from nowhere to take vote share from mainstream parties in the wake of a prolonged recession and financial crisis. Indeed, Greece has suffered even more from the Eurozone’s institutional weaknesses than other peripheral countries. However, the voting system in Greece is semi-proportional, awarding 50 bonus seats to the largest party, which decreases the likelihood of a coalition government in the elections. Furthermore, only three parties enjoyed support levels above 10%, also lowering the likelihood of a coalition.
The UK also seems, at first, to fit some of these criteria, with the rise of UKIP as a populist party and the fragmentation of voter support. However, there have been important differences that have conditioned the political consequences of this. Most obviously, UKIP is a right-wing Europhobic party, whereas the populist parties that have arisen in the peripheral European countries we have studied have been of the extreme left. More importantly, the UK’s first-past-the-post system has made it much harder to translate popular support to parliamentary seats; UKIP’s 14% share of the vote in the 2015 general election resulted in only one MP in Westminster. This further illustrates how cyclical and structural factors interact to produce specific political outcomes. Critically though, short-run exclusion of UKIP from parliament, as a result of the electoral system, did not quell the concerns of voters with regards to the EU. This reflects a wider debate about the merits of including non-centrist parties in parliament; democratic systems that do not facilitate representation across the political spectrum may produce more marketfriendly outcomes in the short-term but this may come at the cost of the perceived democratic legitimacy of the system.
BOX 2: modelling the impact of policy uncertainty on developed economies
Economic theory suggests that uncertainty about political and policy outcomes can lead to delayed business investment, lower market sentiment and higher risk premia in asset prices. To test this proposition, we have undertaken a comparative empirical study of the impact of prolonged policy uncertainty on a selection of key economic and market variables in the UK, US and Europe. We estimated a series of structural vector auto regressions that account for the joint-determination between the selected variables and allow us to examine the impact of a policy uncertainty shock (see Appendix 2). The key variables we include are: GDP growth, domestic policy rates, inflation, 10-year government bond yields, national equities, global industrial production and real effective exchange rates.
Our main findings, confined to those results that proved robust to different specifications, are that:
- In the US, a persistent policy uncertainty shock is associated with lower GDP growth, equity prices, easier monetary policy and a weaker dollar.
- In Europe, the sign of the impact of policy uncertainty on the key variables is the same as in the US but the magnitude of effects is much larger, with the variables failing to return to their pre-shock levels even after 12 quarters. One reason for this may be the inadequacy of the political and policy responses to the initial uncertainty shock.
- In the UK, policy uncertainty shocks are more negative for the currency than in the Eurozone and US, while GDP growth is marginally positive in the first year before tracking down through the remaining quarters. This might help explain why UK growth has initially been so resilient in the face of last June’s referendum result.
It must be stressed that this measure of policy uncertainty incorporates political uncertainty but also monetary and fiscal policy uncertainty, which can be related but not necessarily mutually inclusive. As a result, identifying the precise form of policy uncertainty shock is impossible. Also, each country’s results are limited to past policy uncertainty shocks, which were products of the economic and political environment and time period in which they were produced. As such, future policy uncertainty shocks may influence economic and market outcomes differently.
Applying the political risk framework: the US case
This approach to political risk assessment is designed to give a framework for determining realistic ranges for political outcomes, by identifying and assessing the institutional and cyclical factors that are driving outcomes. It is not designed to be a predictive tool for election forecasting as uncertainty round any political event is driven in part by invisible or hard-to-capture factors, such as individual voter behaviour and non-public information. Instead, we use this framework to consider the potential for political risk events across different countries and the possible post-event outcomes. The 2016 US election provides a useful example of this approach.
The US election created considerable headlines in advance of polling day, given the competition between establishment Democrat Hilary Clinton and populist neophyte Donald Trump for the Republicans. Trump’s victory came as a surprise to a number of market and political commentators, and provided another example of the underreporting of right-wing populist support in polling, the impact of which was then magnified by the vagaries of the US Electoral College system.
Because our analysis in the run up to the result suggested that there was a meaningful probability that Donald Trump could win the election, we used the taxonomy to employ scenario analysis for a range of plausible outcomes and then assessed the policy outlook for each scenario. Importantly, we also took into account how the US system of checks and balances divides power across the executive (the President), the legislature (the House and Senate) and the judiciary, and thus shapes policy. The legislative branch devises the country’s laws and is made up of the House of Representatives (lower house) and the Senate (upper house). The president, who heads the executive branch, is, inter alia, responsible for signing or vetoing legislation, managing the government, issuing rules and regulations, commanding the armed forces and conducting diplomacy. The president can also propose legislation that must then be approved by Congress. The result is a system that requires agreement between Congress and the president to pass legislation.
In 2013, the inability of the Democratic president and Republican Congress to agree to a new budget plan led to a temporary federal government shutdown. This was because of the convergence of the institutional set-up of checks & balances and a key cyclical factor: party polarisation. Over the ten years to 2014, ideological polarisation in the US rose significantly relative to the previous decade, which made consensus building across the two major parties even harder to achieve. Our scenario analysis therefore incorporated the plausible presidential outcomes and the different combinations of executive and legislative makeup (see Table 3). Using this framework, we assessed the likely implications for US policy and growth under each scenario.
For example, ordinarily, the polarisation of the two parties would suggest that a ‘clean sweep’ for either party in both the White House and Congress would result in a more predictable and proactive policy environment than a power sharing regime. However, President-elect Trump was elected on a different policy platform to that of the majority of Republican congressional representatives, increasing uncertainty around the macroeconomic policy outlook. Our analysis before the election identified areas for potential agreement, highlighting in particular fiscal easing – although the magnitude of Trump and the GOP’s policy packages differed, the direction of travel was the same, making some form of expansion via tax cuts highly likely under a Republican clean sweep. Similarly, the regulatory environment under a Republican congress and presidency looked set to change in favour of deregulation.
Conversely, we identified that Trump’s aggressive trade protectionist stance was in contrast to many congressional Republicans, creating uncertainty about the direction of travel. Furthermore, we noted that Trump would have considerable executive power in the areas of trade, immigration and foreign policy where his pre-election policy proposals were less economic and market friendly. While an expansionary fiscal package has been the focal point of investor attention since the election, we continue to watch Trump’s rhetoric and action in these areas, where economic risks are larger than appears to be priced in.
A year of political risk in Europe
A steady stream of political risk events will also take place in 2017, including the French presidential election, and German and Dutch legislative elections. For all three elections, scenario analysis assessing a range of possible governmental compositions, using the pertinent institutional and cyclical risk factors, can provide a useful framework for testing possible policy and market outcomes. This approach avoids the pitfalls of election result forecasting that so often fail as a result of polling inaccuracy and personal bias, allowing investment professionals to take a holistic approach to thinking about political risk in markets.
Centralising institutions clash with the rising right in France
Our research suggests that the outlook for the French election hinges on the electoral system (institutional), polling accuracy (cyclical) and the deeper issues of security, immigration and the state of the economy. The presidential election will be run on a two-round system, which favours more centrist candidates. However, this result is far from guaranteed. Although historically the difference between polling and actual election results in France has been modest, our research on recent polling biases suggests that there is an increased risk of the right-wing Europhobic candidate Marine Le Pen achieving a better result than is currently predicted by polls. That said, recent opinion polls have tended to show the more mainstream candidates securing a share of the popular vote in the second round of voting, well beyond the polling biases against populist-right candidates in other recent elections. If polls continue to show these margins up until the election, a Le Pen win would be a major upset for beleaguered pollsters.
It is also important to keep in mind that whatever the result, the eventual president will need to select a cabinet to work with from the newly elected legislature. That makes it necessary for investors concerned about a potential ‘Frexit’ and the wider post-election policy agenda to understand the relative powers and potential combinations of president and parliament. Even if Le Pen does win the presidency, it is highly unlikely that her party will win a parliamentary majority, making ‘cohabitation’ – cross-party governing between president and legislature—the most likely result of such an event.
Where might populism prevail next?
The German elections are also likely to be watched carefully by investors due to the upswing in support for the populist right party Alternative für Deutschland (AfD). Meanwhile, the role that Chancellor Merkel plays in the next government will also be keenly monitored by market participants concerned about the longevity of the Eurozone. Although the rise in popularity of the AfD has fragmented support in German politics, the German system of proportional representation already carries a history of coalition building. The isolationist AfD is unlikely to be included in any such coalition, so while Angela Merkel’s Christian Democrat party is likely to lose vote share compared with the previous election, a mainstream grand coalition led by either the centre-right CDU/CSU or the centre-left SPD remain the most likely outcomes.
In Italy, a general election is not technically due until 2018 – although it may take place before then. The popularity of the populist Five Star Movement heightens electoral risk for investors in this beleaguered economy. Though changing the electoral system back to a more proportional procedure has reduced the risk of an extreme outcome in relative terms, it will also make it more difficult to deliver much needed structural reforms. In the Netherlands, the fragmentation of support within a similar system to Italy has flown lower on the investor radar, but the level of support for the populist Partij voor de Vrijheid in the run-up to the election echoes the cyclical political risk factors observed in Italy. In both cases, the populist party may garner the largest overall share of the vote but is likely to fall short of a majority; with few allies in the system, there are significant barriers to either party leading a government, although such an outcome cannot be ruled out.
Conclusion
In the wake of the election of populist candidate Donald Trump and the successful ‘vote leave’ campaign in the UK, political events are under the market microscope for 2017. It would be easy to assume that the 2016 results spell the beginning of a series of populist dominos across the developed world. However, while these events and wider popular opinion illustrate a strong populist undercurrent in the post-crisis era, each country remains anchored by domestic institutions and idiosyncratic cyclical dynamics.
By establishing an approach to political risk analysis that identifies parameters for evaluating risk and uses this information to establish ranges for the relevant policy outcomes, we can get to grips with the potential growth and market implications of a range of outcomes from political events before they even take place. It also serves as a springboard for our research agenda going forward, allowing us to dive deeper into the economic and political drivers of populism, policy responses by mainstream parties and the associated implications for globalisation and the broader economic agenda.
Appendix 1
Article by Stephanie Kelly, Standard Life Investments
See the full PDF below.
