An overview of forecasting for politics, conflict, and political violence

post by VipulNaik · 2014-06-24T22:10:39.093Z · LW · GW · Legacy · 0 comments

Contents

  Actors interested in making predictions about global politics
  Databases used in predictive analytics for global politics
  Global opinion polling and influence/sentiment measurement
  Some predictive algorithms
  Websites with a good overview of different datasets and predictive algorithms
  Blogs to follow
  Important people
  Journals
  Popular magazines
  Additional reading
None
No comments

Global politics is a high-stakes affair, and being able to predict it, prepare for it, and in some cases manipulate it, could be a game-changer. Political forecasting, construed broadly as forecasting of events that affect the structure of political systems and the configurations of political power, is therefore quite an important activity.

In relatively stable, prosperous, democratic, and developed countries, political forecasting largely involves two related forecasting activities:

The tools used here are relatively simple: public opinion (both on who people will vote for and what policies they want to see implemented) is tracked through opinion polls. For forecasts made far out in the future, the opinion poll results are combined with some models about how changing economic or political conditions are likely to affect people's voting choices. (In fact, as of the time of writing this post, the Wikipedia page on political forecasting somewhat narrowly defines it as election forecasting, thereby taking the perspective of a relatively stable democratic country).

A blog post on the SAS Business Forecasting blog reviews the main methods used in election forecasting, and compares their performance on US presidential elections. It identifies three broad categories of models that seem to make somewhat reliable and high-quality predictions:

When considering global politics, however, the narrow focus on public opinion and election performance is misguided, for two reasons. First, the interactions between nation-states are governed by rules somewhat different from those that govern local politics, and they often do not map easily to public opinion. Second, and more importantly, in many countries around the world, what transpires politically is far from an accurate reflection of majority public opinion. Of course, public opinion does affect political outcomes, even in dictatorships, but the nature of the relationship is more complex: the opinions of subsets of the population that have more of an ability to stage a coup matter more. Also, in some countries, there are centers of political power or activity that are not (officially) linked with the state. These include rebel groups, separatists, terrorists, and local militia. Even countries that do have elections may not necessarily have free and fair elections, so the outcome of the election may be governed more by who controls the polling apparatus than by what the people want.

This is not to suggest that most parts of the world are mired in continuous, frequent conflict. Many parts of the world, even poor parts and undemocratic parts, are generally peaceful most of the time. But threats of intergroup or interfactional violence play an important role in governing the trajectory of events, even if violence itself is rare.

The problem of predicting global politics is therefore tricky because it's not even clear what questions we should be asking. The simple question "who will win the election in 2014?" isn't good enough. Lots of other questions, such as "will the army stage a coup?" or "will the president be willing to have a free and fair election, or conduct a sham referendum to consolidate his power?" or "will the government purge <insert unpopular minority group here> from the big cities?" could be worth asking. And it's sometimes not even clear whether a question is worth asking until it has been answered in the affirmative.

For the purpose of this post, then, we will discuss together the domains of political forecasting (that largely involves election forecasting and public opinion forecasting) and the forecasting of conflicts, terrorism and international crises.

Actors interested in making predictions about global politics

So who gets in the business of trying to figure out how global politics will unfold? One obvious answer is: governments of other countries, partly with the goal of protecting the country's own economic interest in those other countries, and partly with humanitarian goals of avoiding the other country getting into violence. In addition, agencies whose goal is to combat terrorism are also interested in political developments that might create breeding grounds or support infrastructure for terrorism. Industries that depend on resources available only in a few countries are interested in making sure that those countries remain sufficiently stable that they can continue extracting the resources (and/or that they are on sufficiently good terms with the rulers that the resource extraction can continue despite the presence of conflict).

Some specific actors are listed below:

Databases used in predictive analytics for global politics

Database nameAreas coveredYear rangeAvailability and update frequency
Global Database of Events, Language, and Tone (GDELT) (GDELT project, Wikipedia) All political events, using CAMEO codes 1979-present Publicly available, updated daily
Integrated Conflict Early Warning System (ICEWS) (website, Wikipedia) All political events using CAMEO framework. However, unlike GDELT, follows a more traditional approach to event data in seeking to encode a chronology of events that reflects in some sense the putative ground truth of what occurred. ? Not publicly available, but was made available to forecasters for The Good Judgment Project
Armed Conflict Location and Event Data Project (ACLED) (website, Wikipedia) Armed conflicts 1997-present (for Africa), fewer years for South Asia Publicly available, updated daily
Uppsala Conflict Data Program/Peace Research Institute of Oslo (UCDP/PRIO) Armed Conflict Dataset (website, Wikipedia) Armed conflicts 1946-present (data collected live only since the 1970s) Publicly available, updated annually
Worldwide Atrocities Dataset (website, Wikipedia) Atrocities, i.e., the deliberate use of lethal violence against non-combatant civilians by actors engaged in a wider political or military conflict 1995-present, with a four-month embargo period Monthly (with a four-month embargo period)
Correlates of War (website, Wikipedia) Data sets on Militarized Interstate Disputes (MID), National Material Capabilities, World Religion, Formal Alliances, Territorial Change, Direct Contiguity, and many more (see here for a full list) Some of the data sets are available from about 1815 or 1816, the data sets proceed till about 2005 or 2006, but are likely to be updated to include later years. Unclear
International Crisis Behavior Project (website, Wikipedia) International crises, loosely defined as something that had the potential to lead to a conflict or war 1918-2007 A new version of the database is released every few years, adding more years at the end. The database remains a few years behind the times. For instance, as of June 2014, the most recent release is from July 2010 and covers data till 2007. All data is freely available online.
Global Terrorism Database (website, Wikipedia) All terrorist attacks 1970-2012, excluding 1993 (more years to be added) Approximately annually
Suicide Attack Database (website, Wikipedia) All suicide attacks 1982-2013 Approximately annually
Manifesto Project Database (earlier known as the Comparative Manifestos Project) (website, Wikipedia) Political manifestors and election performance of over 50 free democratic countries 1945 onward ?
Hatebase (website, Wikipedia) Instances of hate speech that might be predictors of potential violence or persecution Presumably 2013 onward, when it launched

Continuous, relies on user submissions, publicly available

Global opinion polling and influence/sentiment measurement

In addition to databases of political events, worldwide opinion polls are also useful in political forecasting. Examples of agencies that conduct worldwide opinion polls are:

In addition to opinion polling, other tools used to measure global public sentiment include analytics for web service usage. There has been considerable research on using information from sources such as Google Trends, Twitter, and Wikipedia. The United Nations Global Pulse (website, Wikipedia) is an example of an effort to use the digital trails of people to extract meaningful information.

Some predictive algorithms

How do we use the mass of structured and unstructured data to make smart political predictions? There are a number of people that claim to have good prediction strategies, but some of them have been debunked, while the jury on others is still out. Some examples are listed below.

Websites with a good overview of different datasets and predictive algorithms

The Forecasting Principles website has some interesting overviews related to the forecasting realm. The two relevant Special Interest Groups are:

Blogs to follow

Important people

Journals

To my knowledge, there are no journals exclusively devoted to forecasting, but the work of the people listed above has generally appeared in a relatively small set of journals, listed below.

There are also some journals devoted to forecasting in general (list to appear in a future post of mine) but as far as I can make out, very little of the conflict forecasting literature is published in such journals.

Popular magazines

Two magazine worth checking out for discussions of political science, that occasionally discuss issues related to forecasting, are:

Additional reading

On election forecasting (these links are supplementary to the links in the main text):

On global political forecasting and general considerations relevant to it:

UPDATE: I found what seems to be a fairly interesting and thorough paper titled Stepping into the future: the next generation of crisis forecasting models by some of the people listed here (specifically Michael D. Ward, Nils Metternich, and co-authors at the Ward Lab). I haven't had time to examine it closely. It includes a discussion of ICEWS.

 

 

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