High-value datasets – demography in the EU
Publication Date/Time
2023-06-13T07:00:00+00:00
Country
Europe
How to use high-value datasets to study population
This is part of a series of articles showcasing examples of high-value
datasets from their different thematic categories. High-value datasets
are defined by EU law based on their potential to provide essential
benefits to society, the environment and the economy. This series aims
to help readers find reliable and accurate information from official
sources relating to the availability of various high-value datasets
and to present this information through data visualisation. You can
see the article providing an overview of high-value datasets here
[https://data.europa.eu/en/publications/datastories/high-value-datasets-overview-through-visualisation].


Only datasets specifically defined by law can be considered high-value
datasets, and as such the data presented in the articles does not
necessarily fall under that definition. Instead, the data has been
chosen to be thematically adjacent to high-value datasets and to
showcase what can be done with information made available by official
EU bodies and EU Member States. The official list of high-value
datasets adopted on 12 December 2022 can be found in the legal
documents
[https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=PI_COM:C(2022)9562]
that define them and their characteristics. 

 

POPULATION AS A HIGH-VALUE DATASET

Data on demography plays a crucial role in understanding the world
around us. By analysing the population dynamics and demographic
trends, we can gain a better understanding of the social, economic and
other factors that affect us all.

This is why data on population was chosen to be included in the
‘statistics’ category of the high-value datasets. This dataset is
called ‘yearly population’ and its key variables are defined by
Regulation (EU) No 1260/2013 of the European Parliament and of the
Council
[https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex:32013R1260].
Other regulations involved are Implementing Regulation (EU) No
205/2014
[https://eur-lex.europa.eu/legal-content/EN/ALL/?uri=celex%3A32014R0205],
Regulation (EC) No 862/2007
[https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex:32007R0862]
and Regulation (EC) No 351/2010
[https://eur-lex.europa.eu/legal-content/en/ALL/?uri=CELEX%3A32010R0351].
[https://data.europa.eu/sites/default/files/img/media/7.demography4-01.png]
As specified in the annex to the implementing regulation
[https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=uriserv%3AOJ.L_.2023.019.01.0043.01.ENG]
mentioned above, the yearly population dataset includes three key
variables: population on 1 January, median age and old-age dependency
ratio.

Median age refers to the age that separates the population into two
equal halves, with half of the population being younger and the other
half being older than the median age. In other words, it is the age at
which half of the population is older and half is younger.

The old-age dependency ratio is the proportion of people aged 65 or
older to people aged 20 to 64 years old. A higher old-age dependency
ratio indicates a larger share of the population is composed of older
individuals who are more likely to require healthcare and other social
services. This indicator is used by policymakers and economists to
anticipate the impact of population aging on social security
programmes, healthcare systems and the labour market.

Several breakdowns are available for these key variables. The
population data can be disaggregated by sex and age, educational
attainment, citizenship, country of birth and human development
index – which according to the annex is ‘a regrouping of the
country of birth and country of citizenship’. For some of the
breakdowns, data is also offered up to the province (NUTS 3) level,
allowing for a more granular analysis. This is also true for the
median age and old-age dependency ratio indicators, while median age
data can also be disaggregated by sex.

The law requires specific breakdowns to be made available. For
example, it is mandatory for sex and age data to be available up to
the province level. Sex and age data must also have a ‘Human
Development Index’ disaggregation. As specified in the annex, Member
States that meet certain conditions set out in the regulation must
also offer other breakdowns such as citizenship or country of birth.
Other key variables have a simpler structure, and for median age and
the old-age dependency ratio, only data up to the province level or
disaggregated by sex must be offered.
[https://data.europa.eu/sites/default/files/img/media/7.demography4-02.png]
 

DEMOGRAPHIC DATA ON EUROSTAT

The population in the EU-27 aggregate has grown steadily since at
least 1990. In 1990, there were 418 million people living in those
countries, which went up to 446 million according to the latest
estimates
[https://ec.europa.eu/eurostat/databrowser/view/DEMO_R_PJANAGGR3__custom_5996843/default/table?lang=en]
for 2022.

However, the rate of population growth gradually slowed down over
time, and as Eurostat notes
[https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Population_and_population_change_statistics#EU_population_shows_a_slight_decrease_in_2021],
the EU population increased on average by about 0.7 million people
per year during the 2005–2022 period, compared with an average
increase of around 3.0 million people per year during the 1960s. This
trend reversal, combined with the severe toll of the COVID-19
pandemic, led to an actual population decrease that started in 2021
and was also observed in 2022.

Positive population changes are driven by births and immigration,
while negative changes are driven by deaths and emigration. Births
minus deaths make up an indicator called ‘natural change’, which
is basically the change in population excluding immigration and
emigration. 

The number of live births decreased progressively between 1960 and
1995, while the number of deaths slowly increased. The gap between
live births and deaths in the EU narrowed considerably from 1961
onwards, and the natural change of the population became negative in
2012, when the number of deaths surpassed the number of births.
Eurostat also highlights that ‘net migration in the EU increased
considerably from the mid-1980s and was the main determinant of
population growth since the 1990s’.

Eurostat data
[https://ec.europa.eu/eurostat/databrowser/view/DEMO_R_PJANAGGR3/default/table?lang=en&category=demo.demopreg]
can be used to analyse the population in each of the roughly 1 500
provinces
[https://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/administrative-units-statistical-units]
that make up the EU. This allows us to monitor regional and local
trends and determine which provinces are experiencing growth in their
population and which ones are shrinking.

Among the provinces in which population grew the most is Ilfov, an
area surrounding Bucharest (Romania), where inhabitants doubled over
the span of 19 years. In the same period, two Spanish provinces also
saw a large growth in their population, namely the islands of
Fuerteventura and Formentera. Several other provinces in Spain
experienced a similar trend, along with Luxembourg and Malta. On the
other hand, in the province of Vidin (north-western Bulgaria), the
population dropped by a little more than one third as compared to
2003, with a similar reduction (in percentage points terms) in the
Latgale province (eastern Latvia) and in two provinces in Lithuania:
Tauragė and Utena counties.

The following visualisation shows this change starting from 2003, a
year for which a large amount of province-level data is available.
[https://data.europa.eu/sites/default/files/img/media/7.demography4-03.png]
 

POPULATION DATA ON DATA.EUROPA.EU

Data concerning breakdowns of the yearly population high-value dataset
can also be found on data.europa.eu. National authorities can upload
their own data on the portal, which at times can reach an even higher
level of detail compared to the data available on Eurostat. For
example, a search on population age structure data, using the
appropriate
[https://data.europa.eu/data/datasets?query=population%20AND%20age&page=1]search
keyword, leads to a high number of results.

This way, it is possible to learn about people living in the
municipalities of Salzburg (Austria)
[https://data.europa.eu/data/datasets/f3148c9c-4e14-4258-b00f-b7695b75d480?locale=en],
in Portugal
[https://data.europa.eu/data/datasets/5ae9c6b1c8d8c9146a44cc70?locale=en]
or in Spain
[https://data.europa.eu/data/datasets/urn-ine-es-tabla-px-t20-e245-p08-02001?locale=en].
A dataset
[https://data.europa.eu/data/datasets/63ce5a88f6a32e536986f64a?locale=en]
uploaded by the French Ithéa Conseil makes it possible to study the
age structure of the population in French regions and cities. The
dataset was used in the following visualisation to show the
distribution of young and old people in the four largest French
cities.
[https://data.europa.eu/sites/default/files/img/media/7.demography4-04.png]
The marital status of the population is another field of particular
interest, and one where we observe significant changes over the years.
Data on this topic
[https://data.europa.eu/data/datasets?query=population%20AND%20marital&page=1&limit=10]
on the data.europa.eu portal can help us understand exactly how this
indicator has been changing.

Interesting datasets about this topic include the population of
Helsinki since 2004 by district and subregion
[https://data.europa.eu/data/datasets/b29d40aa-d675-4480-bd20-58fdda1fd0ef~~1?locale=en],
in Czechia from 2021 census data
[https://data.europa.eu/data/datasets/https-vdb-czso-cz-pll-eweb-lkod_ld-datova_sada-nazev-sldb2021_stav?locale=en],
or in Sweden since 2006
[https://data.europa.eu/data/datasets/http-catalog-scb-se-resource-ssd-medelfolkhandelse?locale=en].
One particularly insightful dataset
[https://data.europa.eu/data/datasets/4416-population-sex-age-and-marital-status-1-january-1950-2019?locale=en]
was uploaded by the data portal of the Dutch government and shows the
marital status of people in the Netherlands since 1950.

The following visualisation shows how the attitude of people to
marriage, singlehood and divorce changed over the span of the last
70 years.
[https://data.europa.eu/sites/default/files/img/media/7.demography4-05.png]
Another useful breakdown is about education. The educational
attainment of the EU population markedly increased over time, and
datasets
[https://data.europa.eu/data/datasets?query=population%20AND%20education&page=1&limit=10&locale=en]
on the data.europa.eu portal show how much.

One such example is a dataset
[https://data.europa.eu/data/datasets/http-www-bilbao-net-opendata-catalogo-dato-habitantes-distrito-barrio-estudios-2022?locale=en]
about the inhabitants of Bilbao (Spain), disaggregated by
neighbourhood and level of education. Another interesting dataset was
uploaded by the Czech National Open Data portal and includes 2021
educational level from census data
[https://data.europa.eu/data/datasets/https-vdb-czso-cz-pll-eweb-lkod_ld-datova_sada-nazev-sldb2021_vzdelani?locale=en].
[https://data.europa.eu/sites/default/files/img/media/7.demography4-06.png]
 

OTHER DEMOGRAPHIC DATA PROVIDERS

The two main sources of EU demographic data are Eurostat and national
authorities. National authorities make data available on their website
and some of it on the data.europa.eu portal as well, where its
description is translated into English and other languages.

Other EU bodies that focus on demography include the Commission’s
Directorate-General for Employment, Social Affairs and Inclusion
[https://ec.europa.eu/social/home.jsp?langId=en]. Using the
appropriate search keyword
[https://ec.europa.eu/social/main.jsp?advSearchKey=demography&mode=advancedSubmit&catId=22&doc_submit=&policyArea=0&policyAreaSub=0&country=0&year=0]
on their website, for example, leads to several documents and
publications about this topic, such as an analysis of fertility in
Finland
[https://ec.europa.eu/social/BlobServlet?docId=22045&langId=en] and
many others.

 

Download the data visualisations presented in this story
[https://gitlab.com/dataeuropa/data-provider-repository/-/blob/master/Data%20stories/HVD%20Data%20Stories/Demography/Demography-data-visualisations-png.zip]
and the data behind them
[https://gitlab.com/dataeuropa/data-provider-repository/-/blob/master/Data%20stories/HVD%20Data%20Stories/Demography/Data-Demography-data-story-13-6-2023.xlsx].

 

_Article by Davide Mancino_

_Data visualisations by Federica Fragapane_
