Using open data to understand politics
Publication Date/Time
2022-07-07T12:30:00+00:00
Country
Europe
USING OPEN DATA TO UNDERSTAND POLITICS

Looking to attract readers, media fill their sites with polls, news
articles and opinions  about the latest political events. These
include elections. The message brought by different media outlets can
vary markedly and it can be hard to distinguish the ordinary from the
extraordinary. Open data  became a valuable tool to help put election
outcomes into the right context. 

For example, during the 2019 European elections, the Greens obtained
12% of the votes. One media outlet described this result as a surge of
support
[https://www.theguardian.com/politics/2019/may/26/greens-surge-as-parties-make-strongest-ever-showing-across-europe].
Comparing the 2019 and 2014 elections, the Greens did increase from 7%
to 12% of the vote. Is this a surge? How to best put this result into
context? 

Open data excels at providing objective facts about elections. Graphs
of election results over time visualise trends over time that people
can interpret for themselves. 

But the number of seats, an objective fact, can mask other more
subjective parts of these trends. For instance, has the political
position of green parties shifted? If so, this would put the results
into another context. 

The advantage of open data is that it helps capture this more
subjective side of election results. But still, be careful with
interpretations: data and political scientists collect data and
information on the positions of political parties. However,
classifying these positions is a subjective. What one data collector
classifies as "left-wing” might be seen as “centrist” to
another. This can result in a biased view. 

WHICH TYPES OF OPEN DATA ARE AVAILABLE TO EXAMINE ELECTION RESULTS?

Political scientists have constructed multiple open databases for
Europe’s election results. These includes information on how
political factions and coalitions have evolved over time.

ParlGov [https://www.parlgov.org/about/], for example, is a data
infrastructure for political science and contains information for the
European Union and most OECD members (37 countries), starting in 1900.
The database combines approximately 1700 parties, 1000 elections (9400
results), and 1600 cabinets (3900 parties). 

ParlGov scores parties on multiple dimensions, such as whether a party
is left-wing or right-wing. Each political party gets a score between
zero and ten for each dimension. Data for ParlGov comes from the
openly available Chapel Hill Expert Survey [https://www.chesdata.eu/]
(CHES), which estimates party positioning on European integration,
ideology and policy issues for national parties in the Member States. 

Another open data initiative, the Manifesto Project
[https://manifesto-project.wzb.eu/], analyses parties’ electoral
manifestos to measure parties’ policy positions. The database covers
over 1000 parties from 1945 until today in over 50 countries on five
continents. The Manifesto group coded each election programme per
written sentence. For example, if a sentence in an election manifesto
is positive about the military, then it gets classified as such. This
leads to a score to measure how positive or negative a party is on a
policy area. The micro data per sentence can be downloaded via APIs
(available for R and Stata) or as a CSV file. 

INSIGHTS FROM THE ACADEMIC WORLD: FROM DATA TO INTERPRETATION

The open data collected and provided by ParlGov helps researchers and
journalists observe trends and gain insights. Kayser and Rehmert
(2021) [https://onlinelibrary.wiley.com/doi/pdf/10.1111/lsq.12273],
for instance, analysed how coalition governments shift positions on
the environment if the probability of a green party joining the
coalition becomes higher (because, for example, they are higher in the
polls). They looked at data in nine European countries between 1990
and 2012. The researchers found that the more likely a green party may
join a coalition, the more likely the coalition government would have
a stricter environmental policy. 

Political scientists Funke, Schularick, and Trebesch (2015) also used
ParlGov for their article “Going to extremes: Politics after
financial crises, 1870–2014
[https://www.econstor.eu/bitstream/10419/123202/1/cesifo_wp5553.pdf]”.
Based on historic election data, they show that financial crises
trigger polarisation in countries and lead to electoral losses for
more moderate parties. Interestingly, this polarisation did not happen
after normal recessions or after other kinds of shocks, such as rising
energy prices or war. 

Insook Lee (2021)
[https://ideas.repec.org/a/hpe/journl/y2022v241i2p3-25.html] uses the
left- and right-wing positioning data from the Manifesto Project to
demonstrate how political polarisation leads to more government debt.
Moreover, she notices that the re-election chance for the ruling
political party decreases the higher the government debt. According to
the expert, parties that are more likely to win re-election are
generally more likely to lower government deficits and debts. 

DO IT YOURSELF: TAKE A LOOK AT HISTORICAL DATA TO GAIN INSIGHT IN
LONG-TERM TRENDS

Open data leads to academic insights, but it can help us all to better
understand electoral trends in our own country and others. 

One tool that visualises these trends is the ParlGov dashboard
[https://lukas-warode.shinyapps.io/ParlGov_Dashboard/] created by
Lukas Warode. It allows users to generate their own visualisations for
all European elections of the last 120 years. As an example, the
figure below shows the results of the 2021 elections in Germany with
the number of seats and the percentage of votes per party. The parties
are ordered from the political left to right, helping users understand
which parties might be likely to form a coalition. 
[https://data.europa.eu/sites/default/files/img/media/Image%201.png]
_Figure 1: Vote share per party, German elections 2021, retrieved from
ParlGov Dashboard_

Another feature of the dashboard lets users compare parties over time.
The figure below shows the results for Germany’s largest three
parties. The data shows that the traditional parties CDU and SPD have
been trending downward since the 1980s, whereas the Greens saw their
share of votes increase slowly between 1980 and 2020, making further
gains in the 2021 elections. 
[https://data.europa.eu/sites/default/files/img/media/Image%202.png]
_Figure 2: Historical share of the votes for CDU, SPD and the Greens,
retrieved from ParlGov Dashboard_
