Czech Republic

Regions and Cities at a Glance

Regions and Cities at a Glance provides a comprehensive assessment of how regions and cities across the OECD are progressing in a number of aspects connected to economic development, health, well-being and the net zero-carbon transition. It presents indicators on individual regions and cities to assess disparities within countries and their evolution since the turn of the new millennium. Each indicator is illustrated by graphs and maps. The report covers all OECD countries and, where data is available, partner countries and economies.

The data in this note reflect different sub-national geographic levels in OECD countries:

  • Regions are classified on two territorial levels reflecting the administrative organisation of countries: large regions (TL2) and small regions (TL3). Small regions are classified according to their access to metropolitan areas (Fadic et al. 2019).

  • Functional urban areas consist of cities – defined as densely populated local units with at least 50 000 inhabitants – and adjacent local units connected to the city (commuting zones) in terms of commuting flows (Dijkstra, Poelman, and Veneri 2019). Metropolitan areas refer to functional urban areas above 250 000 inhabitants.

In addition, some indicators use the degree of urbanisation classification (OECD et al. 2021), which defines three types of areas:

  • Cities consist of contiguous grid cells that have a density of at least 1 500 inhabitants per km2 or are at least 50% built up, with a population of at least 50 000.
  • Towns and semi-dense areas consist of contiguous grid cells with a density of at least 300 inhabitants per km2 and are at least 3% built up, with a total population of at least 5 000.
  • Rural areas are cells that do not belong to a city or a town and semi-dense area. Most of these have a density below 300 inhabitants per km2.

Disclaimer: https://oecdcode.org/disclaimers/territories.html

Well-being, liveability and inclusion in regions

Regional well-being

The Czech Republic faces stark regional disparities across nine well-being dimensions, with the starkest disparities in terms of civic engagement, income and community.

Figure 7: Regional gaps in well-being

Note: Regional indices provide a first comparative glance of well-being in OECD regions. The figure shows the relative ranking of the regions with the best and worst outcomes in the eleven well-being dimensions, relative to all OECD regions. The eleven dimensions are ordered by decreasing regional disparities in the country. Each well-being dimension is measured by the indicators in the table below.

Relative to other OECD regions, the Czech Republic performs best in the education dimension, with most of Czech regions lying in the top 20% of OECD regions.

The top 20% of Czech regions rank above the OECD median region in 8 out of 14 well-being indicators, performing best in terms of population with at least upper secondary education.

Figure 8: How do the top and bottom regions fare on the well-being indicators?

Note: Regional well-being indices are affected by the availability and comparability of regional data across OECD countries. The indicators used to create the indices can therefore vary across OECD publications as new information becomes available. For more visuals, visit https://www.oecdregionalwellbeing.org.

The digital divide

Fixed Internet connections in Czech cities and rural areas deliver speeds significantly slower than the OECD average (-18% and -71%, respectively). This gap (53 percentage points) is larger than in most other OECD countries.

Figure 9: Speed of fixed Internet connections relative to the OECD average, by degree of urbanisation, 2020Q4

Note: Cities and rural areas are identified according to the degree of urbanisation (OECD et al. 2021). Internet speed measurements are based on speed tests performed by users around the globe via the Ookla Speedtest platform. As such, data may be subject to testing biases (e.g. fast connections being tested more frequently), or to strategic testing by ISPs in specific markets to boost averages. For a more comprehensive picture of Internet quality and connectivity across places, see OECD (2022), “Broadband networks of the future”.

Source: OECD calculations based on Speedtest by Ookla Global Fixed and Mobile Network Performance Maps for 2020Q4.

The average speed of fixed Internet connections is below the OECD average in all Czech regions. Within the country, residents of Prague, Northwest and Southeast experience the fastest connections.

Figure 10: Speed of fixed Internet connections relative to the OECD average, in large regions (2021Q4)

Relative poverty rates

In the Czech Republic, relative poverty rates2 range from 8% to 17% across regions. This 9 percentage point difference is less pronounced than the average difference observed across the 29 OECD countries with available data (16 percentage points).

Figure 11: Relative poverty rates in 2020

Note: The OECD median gives the median relative poverty rate observed in a sample made of 326 large regions (from 28 countries), and 28 small regions (from Denmark, Lithuania and the Slovak Republic). Data corresponds to 2020 or the latest available year.