Data Visualization
On March 11th, 2020, the WHO declared COVID-19 a pandemic. Already at this time, the director of the WHO pointed out, “This is not just a public health crisis, it is a crisis that will touch every sector.” [4]. Especially on unemployment, the crisis had a significant impact - Germany is experiencing the biggest social and economical crisis since World War II [5].
Consequently, the following page visualizes the impact of the COVID-19 pandemic on the change of unemployment, exemplary on Germany. Regarding monthly data from March 2020 until September 2020, the change of unemployment will be compared to the same indicator and period in 2019 to indicate whether there was an increase in unemployment in 2020 due to COVID-19. The analysis is based on different datasets from the “Bundesagentur für Arbeit” concerning the unemployment indicator and a dataset from the “Robert-Koch Institut” concerning COVID-19 cases. To get a holistic view, the analysis takes place from three different perspectives, namely the classification of regional effects on the labor market, implications on different industrial sectors, and, finally, a combination of both perspectives to enable a differentiative view on the impact of the COVID-19 pandemic on both levels, federal and industrial.
Are there regional differences regarding the impact of COVID-19 on the labour market?
Are there industrial differences regarding the impact of COVID-19 on the labour market?
Are there any correlations between the region and industry regarding the impact of COVID-19 on the labour market?
Throughout Germany the unemployment increased due to the COVID-19 crises. The so-called Corona-effect describes the increase in unemployment between March and September 2020 compared to the same time period of the previous year. It is apparent that the average change per federal state varies. While Rheinland-Pfalz and Sachsen-Anhalt have an average increase of unemployment of less than 10%, Berlin and Hamburg have the biggest change with over 30%. While the map displays a geographical perspective, the table shows the average change per federal state and the sparklines besides provide the development of the unemployment increase between March and September. Regional differences can be observed but there are no clear geographic patterns like a North-South gradient or an East-West gradient. This leads to the question of what causes the regional differences.
Region | Avg. Change | Development |
---|---|---|
Schleswig-Holstein | 24.25 | ![]() |
Mecklenburg-Vorpommern | 17.00 | ![]() |
Hamburg | 30.72 | ![]() |
Bremen | 24.55 | ![]() |
Niedersachsen | 18.60 | ![]() |
Sachsen-Anhalt | 07.43 | ![]() |
Brandenburg | 16.06 | ![]() |
Berlin | 36.15 | ![]() |
Nordrhein-Westfalen | 19.40 | ![]() |
Hessen | 28.35 | ![]() |
Thüringen | 12.39 | ![]() |
Sachsen | 17.34 | ![]() |
Rheinland-Pfalz | 07.29 | ![]() |
Saarland | 26.63 | ![]() |
Baden-Württemberg | 25.60 | ![]() |
Bayern | 28.08 | ![]() |
Data Source: [2] & [8] (Non-commercial usage allowed)
Trying to answer the previously mentioned question, a thesis is tracing back these regional differences to the industry structure of a region. Therefore, a region whose economy is characterized by industries which are strongly impacted by COVID-19 and its accompanying government measures, will show a significantly bigger percentage change in an increase of unemployment [6] . Industrial examples are Hospitality or the majority of services. In contrast, industries such as Finance and Insurance or Public Administration seem to be effected only a little compared to unemployment in 2019.
To get an interpretable overview on the impacts of COVID-19 on an industry, the number of employees subjected to social insurance needs to be taken into account. Therefore, the given bar chart shows the average size of an industry referring to the number of employees. The line chart on the right side visualizes the procentual change in the increase of unemployment of an industry compared to its size to get the realistic impact of the crisis. It is noticeable that in April 2020 particularly hospitality had an increase of 3.5%. Regarding its size of 1 Million employees subjected to social insurance, a significant number of 35.000 new unemployed people solely from the hospitality sector is visible. With respect to government measures to contain the pandemic, e.g. closing restaurants and bars from the end of March until the beginning of April, this increase can be explained. As an interactive feature, it is possible to click on a specific industry - either in the bar chart or in the line chart - to identify the impact on unemployment of a given government measure, which can be chosen in the drop down menu at the bottom of the described visualizations.
Data Source: [1] & [7] (Non-commercial usage allowed)
Finally, a heatmap combines the regional and industrial perspective by visualizing the change in the increase of unemployment per federal state and industry. It becomes apparent that especially Hospitality, Other Services and the Education/Health/Social Services Industry have high percentage changes. While Berlin suffered from a 74% increase in unemployment in Hospitality, Rheinland-Pfalz only showed a 15% change in the same industry. A click on a box in the heatmap gives further insights on the development of different industries in a federal state in an extra chart next to the heatmap. The bars show the number of COVID cases per month which can be directly compared to the line which represents the percentage change of the increase in unemployment. Looking again at the development of the Hospitality in Berlin makes clear that March and April had a high impact on the high mean value from above. This can be explained by the high COVID cases during these months and some government measures like the closing of the Gastronomy.
Data Source: [3] & [8] (Non-commercial usage allowed)
The presented visualizations give an indication of the development of the increase in unemployment during the COVID-19 pandemic. By looking at the regional and industrial factors, the development of this figure can be traced back to these in an exemplary way. Nonetheless, this is a simplified view which doesn’t take the influence and interdependence of further factors from the health industry, politics or economy into account. Therefore, the results give a first orientation but no clear statements of causes and effects.
[1] Bundesagentur für Arbeit (2020b): Arbeitsmarkt nach Branchen - Deutschland (Monatszahlen), online available at: https://statistik.arbeitsagentur.de/SiteGlobals/Forms/Suche/Einzelheftsuche_Formular.html?nn=20898&topic_f=tabelle-arbeitsmarkt-branchen [final call: 19.10.2020].
[2] Bundesagentur für Arbeit (2020c): Auswirkungen der Coronakrise auf den Arbeitsmarkt - Deutschland, West/Ost, Länder, Kreise und Agenturen für Arbeit (Monatszahlen), online available at: https://statistik.arbeitsagentur.de/SiteGlobals/Forms/Suche/Einzelheftsuche_Formular.html?nn=15024&r_f=ur_Deutschland&topic_f=corona-datenset-corona [final call: 16.10.2020].
[3] Nationale Plattform für geographische Daten (NPGEO) (2020): RKI Covid19, online available at: https://npgeo-corona-npgeo-de.hub.arcgis.com/datasets/dd4580c810204019a7b8eb3e0b329dd6_0/data [final call: 16.10.2020].
[4] Times (2020): World Health Organization Declared a COVID-19 'Pandemic", online available at: https://time.com/5791661/who-coronavirus-pandemic-declaration/ [last call: 22.10.2020].
[5] DW (2020): Corona-Krise: Entlassungen trotz Kurzarbeit, online available at: https://www.dw.com/de/corona-krise-entlassungen-trotz-kurzarbeit/a-53269059 [final call: 22.10.2020].
[6] Institut für Arbeitsmarkt- und Berufsforschung (2020): Warum der coronabedingte Anstieg der Arbeitslosigkeit in manchen Regionen deutlich höher ausfällt als in anderen, online available at: https://www.iab-forum.de/warum-der-coronabedingte-anstieg-der-arbeitslosigkeit-in-manchen-regionen-deutlich-hoeher-ausfaellt-als-in-anderen/ [final call: 22.10.2020].
[7] Bundesagentur für Arbeit (2020a): Eckwerte Arbeitsmarkt, online available at: https://statistik.arbeitsagentur.de/DE/Navigation/Statistiken/Interaktive-Angebote/Dashboard-Eckwerte-Arbeitsmarkt/Dashboard-Eckwerte-Arbeitsmarkt-Nav.html [final call: 21.10.2020].
[8] Bundesagentur für Arbeit (2020a): Eckwerte Arbeitsmarkt, online available at: https://statistik.arbeitsagentur.de/DE/Navigation/Statistiken/Interaktive-Angebote/Dashboard-Eckwerte-Arbeitsmarkt/Dashboard-Eckwerte-Arbeitsmarkt-Nav.html [final call: 21.10.2020].
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