Swedens election turnout at the EU Parliament elections in 1999 and 2004

Exercise A: “Election turnout at the European Parliament elections in 1999 and 2004”
Juan Archanco Galíndez, GIS & Spatial Analysis, Umeå Universitet 2008
INTRODUCTION

Election turnout throughout the European Member States has become a cause
for concern as the lowest turnout in the last 2004 elections can be seen as a divorce between
the citizens and the EU institutions.

AIM OF THE REPORT

The aim of this report is to study and analyze the election turnout at the
parliament election in 2004 as well as the change in the election turnout between the elections
of 1999 and 2004, both throughout Sweden’s municipalities by making the appropriate maps.

The elaborated maps are the following ones:

 #1: “2004 Turnout at European Parliament election”: Shows by municipalities the
different levels of turnouts at the European Parliament election in 2004.

 #2: “Evolution of turnout 1999 – 2004 European Parliament elections”: Shows the
change in election turnout between the elections of 1999 and 2004.


METHODOLOGY

The procedures for this exercise are rather simple.

First of all, we have to convert the provided layers with Sweden’s
municipalities, major lakes and the sea from the provided system of projections: CGS WGS
1984, to Swedish National System of projections: RT 90 2.5 gon West.

Once we have these features in a convenient system of projections, we need to
get the results of the European Parliament elections of 1999 and 2004. To do so, we point out
to the Swedish National Statistics Service website: www.scb.se. We scan through the
democracy subject area, and download the results from the mentioned elections in an excel
file by selecting all the national parties and all the municipalities.

We can now deal with the data easily by opening the .xls files with Microsoft’s
spreadsheet program. Now we sum up the votes from all the parties along with the invalid
votes in all the 289 different municipalities, and get the total of votes in each municipality. To
calculate the turnout however, we also need to know the total number of citizens entitled to
vote, so we add the number of non voters to the total number of votes. Now we can get the
turnout percentage using the following relation:

# Votes # Votes
Turnout (%) = * 100 = * 100
# Citizens entitled to vote (# Votes) + (# Non Voters)

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Analyzing this formula, it is not a big deal to notice that the turnout is directly
proportional to the total number of votes (people that went to vote the day of the elections,
even those with invalid votes). On the other side, the turnout is inversely proportional to the
total number of citizens entitled to vote. This number is the addition of the total votes and the
total number of citizens that did not bother to go and vote on the elections day. Therefore the
greater number of non voters, the lower the turnout in a certain municipality is. Finally we
sum up all the municipalities results and get the totals for Sweden as a country. This
information is not required in the exercise but it is useful for subsequent analysis in the report.

We have now all the data we need in order to represent in our maps the different
levels of turnout in the different Swedish municipalities. Unfortunately ArcMap is not able to
read .xls Excel files, for this reason, we need to convert them to .dbf files (Dbase files). We do
so, and join the table provided with the location of the different municipalities with our results
of turnout levels in these municipalities, making sure that the code for each municipality is the
same in both tables.

As stated in the downloaded table from SCB’s website “A new regional
grouping applied from January 1 1999. Parts of the municipality of Södertälje formed a new
municipality - Nykvarn”. Because of this, municipalities following the new one of Nykvarn
does not coincide with those provided by Arc Map (probably, because they were indexed
before the split of Södertälje). In order to work out this problem, we simply delete the results
of Nykvarn in our table. Now all the codes from the different municipalities should coincide
in both tables.

Another problem that comes up while dealing with excel tables and exporting
from .xls files to .dbf files, is the fact that when converting from one type of file to the other,
and joining the tables with Arc Map, the decimal digits may be wiped off. To address this
trouble you need to paste the data as value, rather than as a formula in excel. Also you need to
tell both, Excel and ArcMap how many decimal digits you want to show. In our maps we used
1 decimal in the second map so it’s more precise than the default whole number with no
decimals and whole numbers without decimal for maps #1 and #3.

We are now prepared to represent the different levels of turnout in each
municipality so that at first glimpse of any of the maps we can get an idea of how the different
levels of turnout are distributed throughout the different municipalities or how changed the
turnout from 1999 to 2004 elections. To do so, we use the following criterion and
classification in each of the 3 maps:

 #1: “2004 Turnout at European Parliament election”

Four classes using the Natural Breaks (Jenks) method as following:
Table #1: “2004 Turnout at European Parliament election”
Color Level of turnout # of municipalities % of the total
Red Very low (25% - 31%) 45 16%
Orange Low (32% - 36%) 141 49%
Light Green High (37% - 42%) 83 29%
Dark Green Very high (43% - 56%) 20 7%

2

Four classes using the Natural Breaks (Jenks) method slightly modified so that border
between the second and third class is zero:
Table #2: “Evolution of turnout 1999 – 2004 European Parliament elections”
Color Difference in Turnout # of municipalities % of the total
Red Big drop (-7,1% to -3,4%) 59 20%
Orange Small drop (-3,3% to 0,0%) 153 53%
Light Green Small rise (0,0% to 4,2%) 72 25%
Dark Green Big rise (4,2% to 14,5%) 5 2%

Four classes, almost the same as in table #1 so it is easier to compare both tables:
Table #3: “1999 Turnout at European Parliament election”
Color Level of turnout # of municipalities % of the total
Red Very low (26% - 31%) 29 10%
Orange Low (32% - 36%) 119 41%
Light Green High (37% - 42%) 117 40%
Dark Green Very high (43% - 59%) 24 8%

The reason for calculating the % of municipalities in each class in these three
tables is both, self curiosity and the fact that it can be useful for subsequent analysis in the
report. We have to take into consideration that this % represents that of the total of
municipalities but not the one of the total population. For example, in map #1 Malmö (in light
green with around 860000 inhabitants) Vs. Kiruna (in red, with around 23000 inhabitants) has
about 37 times more population although the extension of Kiruna municipality is more than
100 times bigger in extension. Having in mind that around 90% of Sweden’s population is
located in the one third south part of the country, those municipalities located in this part have
more importance, therefore we have to take them more into consideration the city of
Stockholm and surroundings as well as the urban areas of Göteborg and Malmö.

The reason for choosing 4 classes is that doing so, there is no “average class”
and therefore you can easily know if it has increased / decreased the turnout (map #2) or if it
is high or low turnout (maps #1 and #3).

The reason for choosing these colors is that red may be used for the “dangerous”
municipalities with low levels of turnout whereas those with green color may be regarded as
“positive” areas in the eyes of, for instance, a Euro Parliament member.

We have ready the 3 maps, but we need to improve their aspect, by following
these steps:

- Select an appropriate color for each class: Red for those “dangerous” areas where the
turnout is very low, orange for those with low levels of turnout, light green for those
with high levels of turnout, and dark green for the ones with the greatest levels of
participation. The same applies to the map of the evolution of turnout throughout the
1999 – 2004 period.
- Add an appropriate title, legend, north arrow, scale bar and scale text.
- Perform minor improvements, such as changing the style of the text, the location of
the different map elements and making their frame borders slightly rounded. The mean
value in each map can also be added to the legend.

Finally, we write down the report following the provided guidelines and structure.

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RESULTS AND ANALYSIS

 #1: “2004 Turnout at European Parliament election”

To the question: Is it possible to perceive any spatial variations?

We may answer yes and no at the same time. No because at first it may seem that there
is no pattern under this random tangle of colors. But if you analyze carefully you can guess
some trends and certain patterns:

 The lowest turnout areas (red, with 25% - 31%) are located basically in the middle and
in the south parts of the country (a lot of them in the west half). An exception is the
municipalities of Kiruna, Gällivare and Haparanda located in the northern most part of
Sweden. In all of these municipalities, the turnout is lower than 31% which means that
less than 1/3 of the electorate voted.

 The low turnout areas (orange, with 32% - 36%) are spread all around the country
randomly. In these municipalities just a bit more than 1 out of 3 persons entitled to
vote decided to do so. It is the biggest group with almost 50% of the municipalities.

 The “high” turnout areas (light, green with 37% - 42%), are also spread all around the
country almost randomly. Seems like the center part does not have municipalities with
high turnout except for Leksand and Falun. In these municipalities about 4 out of 10
persons entitled to vote decided to do so.

 The “very high” turnout areas (dark, green with 43% - 56%) are located at the south
with the exceptions of Bräcke, Ragunda and Umeå located at the middle-north part of
the country. These municipalities managed to get half of their electorate to vote.

 #2: “Evolution of turnout 1999 – 2004 European Parliament elections”

 The red areas (big drop in turnout) are located basically in the south-western part of
the country except for the municipality of Dorotea.

 The orange areas (small drop in turnout) are also spread all around the country,
although most of them are located, again, in the western part of Sweden.

 The light green areas (small rise in turnout), are also spread all around the country
almost randomly, and in contrast with the orange areas, it seems that most of them are
in the eastern part of the country.

 The dark green areas (big rise in turnout) consist of only 5 municipalities located in
the middle to east part of Sweden. A shocking example in this group is the
municipality of Ragunda with an increase of more tan 14%.

 #3: “1999 Turnout at European Parliament election”

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 Similar distribution to the one seen on map #1 with some exceptions, like those
municipalities located in the southwestern corner of Sweden (including Malmö) where
participation levels changed from middle-high in 1999 to middle-low levels in 2004.
DISCUSSION

Considering the results from previous page, we can formulate the following
hypothesis and their respective causes and also answer the following questions:

Has election turnout increased or decreased?

In broad strokes it has DECREASED. Specifically, the turnout has been lower
in 212 municipalities out of 289, which means that almost ¾ of Sweden’s municipalities
turned their back on the EU in the 2004 election.

Is the change distributed evenly over the country or can you see any spatial patterns?

No, the change is not evenly over the country, and yes, we can see some special-
spatial patterns. These are based mainly in map #2 and map #1, and are detailed among with
their possible causes.

Hypothesis #1

“The western municipalities and those bordering with Norway have lower levels of turnout
and their participation in the European elections has decreased in the 1999- 2004 period”

This is probably because of the cultural influence of Norway, a rich and prosperous
country and also a non-member of the EU.

Corollary to hypothesis #1

“The eastern municipalities and those bordering with Finland, as well as those in the Gulf of
Bothnia and Baltic Sea shore have higher levels of turnout and their participation in the
European elections has increased in the 1999- 2004 period”

This is probably because of the cultural influence of Finland, a member of the EU with
the € as national currency.

Hypothesis #2

“The southwestern municipalities have lower levels of turnout and their participation has
decreased in the 1999- 2004 period”

Probably because of the immigration problems and its influence in the public opinion
in this “hot-spot” the country, even though these areas are the closest ones to other EU
member like Denmark, Germany or Poland with a traditional low level of euro-skepticism.

Hypothesis #3

“The municipality of Umeå has a higher level than the rest of the municipalities in the area”

Specifically it has a turnout of 43% in 2004, far from the mean average of 36% of the country.

5

This is probably because of the fact that there a lot of students in the area, which are more pro-
EU than those ones with a low percentage of students in their population.

REFERENCE LIST, SOURCES & BIBLIOGRAPHY

This list shows the different types of sources that based or inspired me when writing
this report. Sorted in descending and subjective order of importance.

• “Getting to know ArcGis desktop” S.E., Tim Ormsby, 2004 > Text and reference book
while using ArcMap.

• www.scb.se > Sweden’s National Statistics website, source of official data used in the
maps’ tables.

• www.google.es > Main search engine to find webs, maps, images, pieces of news or e-
books:

 http://www.euractiv.com/en/elections/european-parliament-elections-2004-
results/article-117482 > European Parliament Elections 2004 results.
 http://en.wikipedia.org/wiki/European_Parliament_election,_2004
 http://www.lib.utexas.edu/maps/europe/sweden_pop_1973.jpg > (Swedish
population distribution).
 http://www.stockholmnews.com/more.aspx?nid=1675 > “Iraqi immigrants
crowd apartments” piece of news from the “Stockholm News” e-newspaper.
 http://dspace.mah.se/dspace/bitstream/2043/1219/1/Bevelander.pdf > (Current
Themes #2: Immigration patterns, economic integration and residential
segregation: Sweden in the late 20th century, Malmö University, 2004).

• http://www.wordreference.com/ > Main reference online dictionary Spanish / English,
used mostly for certain expression (e.g. turn the back on to somebody).

• http://iate.europa.eu/ > The EU's multilingual term base for legal translations.

• http://en.wikipedia.org/ & http://es.wikipedia.org/ > English & Spanish Versions of
the Wikipedia. Used to find out more about certain municipalities in Sweden.

• Last but not least I would like to greet and thank my Swedish corridor mates, specially
Anniken Gustaffson who helped me in the analyzing and interpreting of the maps
phase of the report as well as with ideas and opinions in relation with the different
hypothesis from the previous page… Thank you!!!

APPENDIX:

Maps shown in the following order:


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 #2: “Evolution of turnout 1999 – 2004 European Parliament elections”: Shows the
change in election turnout between the elections of 1999 and 2004.


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Swedens election turnout at the EU Parliament elections in 1999 and 2004

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Swedens election turnout at the EU Parliament elections in 1999 and 2004