Threat Monitor Addendum: The details of the US-China soft power monitor

In Parts 1, 2, and 3, we discuss the utility of a threat monitor to tracking issues that are of low probability but high impact. We used the example of China overtaking the United States in soft power. In this section we’ll get into why each factor was chosen to illustrate some of the decisions that can go into the construction of one such monitor.

There is one question that you might have about forecasting. How do we know if we’re right?

Chris OatesJuly 21, 2020political risk metrics, political forecasting

Threat Monitor Part 3: Simulating threats

Threat monitors are great for tracking low-probability / high-impact dangers that can creep up on an organization. In Part 2, we showed how to extend the idea into a forecasting model that challenges a team to think more critically about the future.

There is one question that you might have about forecasting. How do we know if we’re right?

Chris OatesJuly 21, 2020political risk metrics, political forecasting

Threat Monitor Part 2: Looking over the horizon

Threat monitors are a great way at tracking what’s happening in the present. They can also be great at seeing into the immediate future. The monitors described in Part 1 are very well suited to looking into the next 12 months and seeing what might happen.

So what do you do when you want to look further? If you’re concerned with longer-term investments, say, out to five years, how can a threat monitor work?

Chris OatesJuly 21, 2020political risk metrics, political forecasting

Threat Monitors Part 1: How to sense the rising waters

How can you track the untrackable?

That’s a question that affects not only political risk, but anyone in business or politics who has to deal with low probability, high impact risks. Often these exist in such a morass of qualitative information and reports written entirely in the subjunctive that knowing whether the risk has grown or shrunk recently is difficult to impossible.

Yet we still need to know how threatening these risks are and what direction they’re heading in. Just because they’re currently over the horizon doesn’t mean we should take our eye off them.

Chris OatesJuly 21, 2020political risk metrics, political forecasting

Massachusetts network theory and unconventional political data

CommonWealth magazine yesterday ran my article about using network theory to understand how cosponsorships in legislation indicate a social structure underlying the state government. Basically, we can take the web of legislators who have cosponsored bills with each other, treat that like a social network, and use some sociological methods to tease out some insights about what that social structure means.

MassachusettsChris OatesMay 1, 2020political risk metrics

How can we measure political risk when we can’t measure political risk?

A Martin Wolf column in the Financial Times earlier this month discusses how political risk, and political developments more generally, are impacting global markets. It’s a good article, but one odd item jumped out at me.

At the end of the article, Wolf includes a chart of the Geopolitical Risk (GPR) index, developed by Dario Caldara and Matteo Iacoviello, both economists at the Federal Reserve (more info in the paper “Measuring Geopolitical Risk” by Dario Caldara and Matteo Iacoviello at https://www2.bc.edu/matteo-iacoviello/gpr.htm).