The coronavirus (COVID-19) is affecting not only the health and daily life of the German population, but it is also having an impact on German businesses. Based on a survey conducted in May 2020 among 10,000 companies, almost ** percent of businesses in the hospitality industry stated they already notice the impact of the virus.

The Gross Domestic Product (GDP) in Germany stagnated 0 percent in the third quarter of 2025 over the previous quarter. This dataset provides the latest reported value for - Germany GDP Growth Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Germany recorded 3366432 Coronavirus Recovered since the epidemic began, according to the World Health Organization (WHO). In addition, Germany reported 106680 Coronavirus Deaths. This dataset includes a chart with historical data for Germany Coronavirus Recovered.

According to a survey conducted by the Centre for European Economic Research (ZEW), over three quarters of responding manufacturing companies stated that none of their employees had worked from home before the coronavirus (COVID-19) pandemic. During the pandemic, the share of companies that had none of their employees working remotely decreased to 54 percent (as of June 2020).

Germany recorded 38418899 Coronavirus Cases since the epidemic began, according to the World Health Organization (WHO). In addition, Germany reported 173834 Coronavirus Deaths. This dataset includes a chart with historical data for Germany Coronavirus Cases.

In 2020, companies in the German services sector stated that ** percent of their employees regularly worked from home during the coronavirus (COVID-19) pandemic. In the manufacturing sector, this was true for only ** percent of employees.

BackgroundCOVID-19 measures in Germany varied during the pandemic, and it seems natural that in addition to factors such as incidence, health system capacity, etc., these interventions and their social and economic consequences had an impact on the evolution of the population’s well-being. Since the beginning of the pandemic, there has been a suspicion that the health burden would fall mainly on population groups with a lower socio-economic status, and that COVID-19, including the policy measures, could therefore contribute to increasing social inequalities in health. We examine several indicators of well-being over the course of the pandemic, analyze the effect of the stringency of the measures on subjective well-being and the extent to which certain social groups were particularly affected.MethodsOur analyses are based on 2020 and 2021 data from the German Socio-Economic Panel (SOEP), complemented by various regional indicators, including the COVID-19 measures. Data on subjective well-being during the pandemic phases were regressed on the phases, socio-demographic, economic and health-related indicators, stringency of measures and other regional indicators in multi-level models with the district as the top level. Up to N = 29,871 observations in 401 districts were included.ResultsOverall, there was little decline in well-being up to the end of the observation period, and even some increase. When the effect of the stringency of the measures was taken into account, the changes were partially attenuated. However, stringency had little direct effect on well-being. People with disabilities and chronic pre-existing conditions were particularly affected by a reduction in well-being. In some cases, COVID-19 measures had slightly different effects in these groups.ConclusionThe effects of socio-economic indicators were not strong enough to suggest that lower social status is generally associated with a negative trend in well-being. According to our results, people with disabilities and chronic diseases, including severe obesity, should be given more attention in the future. A change in time-related outcomes when considering COVID-19 measures could indicate adjustment effects on well-being.

Total Covid deaths per million in Germany, March, 2023 The most recent value is 2052 total Covid deaths as of March 2023, an increase compared to the previous value of 2035 total Covid deaths. Historically, the average for Germany from February 2020 to March 2023 is 1112 total Covid deaths. The minimum of 0 total Covid deaths was recorded in February 2020, while the maximum of 2052 total Covid deaths was reached in March 2023. | TheGlobalEconomy.com

The “KOMPAKK index of economic sectors closure during the first wave of COVID-19” is a dataset on the German federal state-specific sector closures compiled from the original state decrees (March/April 2020). A large and growing number of studies shows the severe social and economic consequences of the governmental measures introduced to reduce the spread of the Covid-19 virus in March and April 2020 in Germany. However, we still lack a systematic analysis of intra-German differences in regulations and outcomes. The German federalist system leaves decisions over the implementation of decrees by the federal government to the federal states. This meant that the 16 states issued individual decrees over economic sector closure and social distancing measures during the course of the pandemic. We retrieved all decrees issued from 15.03.2020 to 17.04.2020 from the official website of each of the 16 federal states of Germany. All decrees used for generating the dataset are also available in the file “KOMPAKK_federalstatesdecrees.zip”.

Germany Coincident Economic Index: MoM data was reported at 0.000 % in Feb 2025. This records a decrease from the previous number of 0.097 % for Jan 2025. Germany Coincident Economic Index: MoM data is updated monthly, averaging 0.097 % from Feb 1965 (Median) to Feb 2025, with 721 observations. The data reached an all-time high of 5.516 % in Jan 1991 and a record low of -3.016 % in Apr 2020. Germany Coincident Economic Index: MoM data remains active status in CEIC and is reported by The Conference Board. The data is categorized under Global Database’s Germany – Table DE.The Conference Board: Leading Economic Index. [COVID-19-IMPACT]

Dataset and Codebook for: Rosman, T., Kerwer, M., Steinmetz, H., Chasiotis, A., Wedderhoff, O., Betsch, C., Bosnjak, M. (2021). Will COVID-19-related economic worries superimpose virus-related worries, reducing nonpharmaceutical intervention acceptance in Germany? A prospective pre-registered study. International Journal of Psychology, 56(4), 607-622. https://doi.org/10.1002/ijop.12753 Nonpharmaceutical interventions (NPI) such as stay-at-home orders aim at curbing the spread of the novel coronavirus, SARS-COV-2. In March 2020, a large proportion of the German population supported such interventions. In this article, we analyse whether the support for NPI dwindle with economic worries superimposing virus-related worries in the months to follow. We test seven pre-registered hypotheses using data from the German COSMO survey (Betsch, Wieler, Habersaat, et al. 2020), which regularly monitors behavioural and psychological factors related to the pandemic. The present article covers the period from March 24, 2020 to July 7, 2020 (N total = 13,094), and, in addition, includes a validation study providing evidence for the reliability and validity of the corresponding COSMO measures (N = 612). Results revealed that virus-related worries decreased over time, whereas economic worries remained largely constant. Moreover, the acceptance of NPIs considerably decreased over time. Virus-related worries were positively associated with acceptance of NPIs, whereas this relationship was negative regarding economic worries (albeit smaller and less consistent). Unexpectedly, no interactions between virus-related worries and economic worries were found. We conclude that individual differences in virus-related and economic threat perceptions related to COVID-19 play an important role in the acceptance of NPIs.

Socio-economic conditions and social attitudes are known to represent epidemiological determinants. Credible knowledge on socio-economic driving factors of the COVID-19 epidemic is still incomplete. Based on linear random effects regression, an ecological model is derived to estimate COVID-19 incidence in German rural/urban districts from local socio-economic factors and popularity of political parties in terms of their share of vote. Thereby, records provided by Germany's public health institute (Robert Koch Institute) of weekly notified 7-day incidences per 100,000 inhabitants per district from the outset of the epidemic in 2020 up to December 1, 2021, are used to construct the dependent variable. Local socio-economic conditions including share of votes, retrieved from the Federal Statistical Office of Germany, have been used as potential risk factors. Socio-economic parameters like per capita income, proportions of protection seekers and social benefit claimants, and educational level have negligible impact on incidence. To the contrary, incidence significantly increases with population density and we observe a strong association with vote shares. Popularity of the right-wing party Alternative for Germany (AfD) bears a considerable risk of increasing COVID-19 incidence both in terms of predicting the maximum incidences during three epidemic periods (alternatively, cumulative incidences over the periods are used to quantify the dependent variable) and in a time-continuous sense. Thus, districts with high AfD popularity rank on top in the time-average regarding COVID-19 incidence. The impact of the popularity of the Free Democrats (FDP) is markedly intermittent in the course of time showing two pronounced peaks in incidence but also occasional drops. A moderate risk emanates from popularities of the Green Party (GRÜNE) and the Christian Democratic Union (CDU/CSU) compared to the other parties with lowest risk level. In order to effectively combat the COVID-19 epidemic, public health policymakers are well-advised to account for social attitudes and behavioral patterns reflected in local popularities of political parties, which are conceived as proper surrogates for these attitudes. Whilst causal relations between social attitudes and the presence of parties remain obscure, the political landscape in terms of share of votes constitutes at least viable predictive “markers” relevant for public health policy making.

Syntax files to replicate the analyses in the paper "Socio‑economic status, comparisons of subjective affectedness and life satisfaction during the COVID‑19 pandemic in Germany" (https://doi.org/10.1007/s11205-025-03000-1) using the SOECBIAS-COVREF data: Beblo, Miriam, Jäger, Julian, Lohmann, Henning, Sattler-Bublitz, Elisabeth, & Wang, Hequn (2024). SOECBIAS-COVREF Data Set. GESIS, Cologne. Data File Version 2.0.0, https://doi.org/10.7802/2772 as well as NUTS-3 level data on COVID-19 cases and deaths by the Robert Koch Institute (https://www.arcgis.com/home/item.html?id=f10774f1c63e40168479a1feb6c7ca74, last accessed: 13.01.2023) and on short-time work by the Federal Employment Agency (https://statistik.arbeitsagentur.de/SiteGlobals/Forms/Suche/Einzelheftsuche_Formular.html?topic_f=kurzarbeit-endg, last accessed: 05.01.2024).

Abstract: This paper examines the role of social comparisons in evaluating the consequences of the COVID-19 pandemic in Germany between 2020 and 2022. Our approach drew on previous research concerning economic inequalities and reference groups, engaging with the broader literature on comparisons and subjective well-being. We hypothesized that individuals’ evaluations of their personal economic affectedness—what we term “subjective affectedness”—would be influenced not only by objective factors such as employment and income changes but also by their socioeconomic status at the onset of the pandemic. We primarily investigated how individuals evaluate their subjective affectedness in relation to others and how these evaluations varied according to their initial socioeconomic status. Additionally, we analyzed whether these comparisons influenced subjective well-being, specifically life satisfaction, during the pandemic. Our results show that individuals generally viewed themselves as economically less affected than others, including their immediate social circle, other people in Germany, and especially others in the EU. However, lower-status groups perceived both themselves and others as more affected and were more likely to assess themselves as more affected than others—even in the absence of objective factors such as job or income loss. Our findings suggest that individuals rely on personal reference groups, which leads to biased evaluations of others. Those who evaluated themselves as more affected than others also reported lower life satisfaction. Overall, our findings indicate that socioeconomic status played a crucial role in shaping evaluations and social comparisons during the pandemic.

The German Business Panel (GBP) is a data infrastructure that periodically surveys executives and key decision-makers in a representative sample of German firms, eliciting their perceptions, views, and expectations. The primary objective of the longitudinal panel study is to generate evidence on the role of accounting and tax regulation for companies. It is part of the Collaborative Research Center (SFB/TRR) Project-ID 403041268 – TRR 266 Accounting for Transparency. The 2020 GBP Covid-19 Survey focusses on the impact of the health crisis on firm´s key outcomes like revenues, profits, as well as perceptions, responses, and plans of decision makers. Questions elicit manager and firm characteristics, as well as perceptions on economic uncertainty, firm survival, government economic policy, take-up of government support, and managerial strategies to responds to the crisis as well as future investment and employment plans. The questionnaire includes various instruments with experimental variation. More information is available at gbpanel.org. The 2020 GBP Covid-19 Survey was conducted from July-October 2020 and from November-February 2021 on a rolling basis among a representative sample of decision makers of legally independent private and public businesses with economic activity in the Federal Republic of Germany. For each of the two survey periods, the sampling involved a two-stage procedure. First, a simple random sample was drawn, which was then in a second step randomly allocated according to a contact protocol to generate a rolling cross-section. The two rolling cross-sections together form a rolling panel. The survey was conducted by the German Business Panel team, Mannheim. Interviews were conducted using online computer-assisted web interviewing (CAWI). Parts of the interviews involved computer assisted telephone interviewing (CATI).

A recent study measuring the sentiment of German consumers towards sustainability and fashion during the Covid pandemic revealed that a large proportion stated they would be altering their fashion consumption habits; ** percent of those surveyed agreed with the statement “I will be throwing out fashion items less often”, ** percent agreed with the statement “I will be buying more high-quality items that can last longer” and ** percent agreed with “I will be repairing fashion items more rather than buying new ones”. However, ** percent, ** percent and ** percent of those consumers surveyed “disagreed” on the same respective statements.

Italian and German consumer perceptions

Studies also measured the opinions of German and Italian consumers as to how they thought fashion retailers should act in response to the pandemic. Over half of German consumers surveyed stated they believed the fashion industry should “care for the health of its employees”. Whereas ** percent stated fashion industries should “reduce their negative impact on the environment”. The perceptions of consumers in Italy towards the sustainability of fashion industries following the pandemic were noticeably different. ** percent of Italian consumers surveyed stated “my opinions about fashion retailers haven’t changed that much”. Furthermore, ** percent “neither agree* or disagree*” to the statement “coronavirus crisis has made my fashion consumption habits (i.e. purchases, repairs, or disposals of clothing items) more sustainable”.

Online revenues in fashion retail during Coronavirus pandemic

During the coronavirus pandemic, Italy and Germany also had markedly different rates of online ordering of fashion accessories. On April 19th, the rate of online purchases in Italy was *** percent higher than the year prior. Whereas in Germany during the same week, the rate of online purchases was half that of Italy’s and ** percent higher than the year prior.

Covid vaccinated people per hundred people in Germany, March, 2023 The most recent value is 77.82 Covid vaccinated people per hundred people as of March 2023, an increase compared to the previous value of 77.81 Covid vaccinated people per hundred people. Historically, the average for Germany from December 2020 to March 2023 is 61.74 Covid vaccinated people per hundred people. The minimum of 0.25 Covid vaccinated people per hundred people was recorded in December 2020, while the maximum of 77.82 Covid vaccinated people per hundred people was reached in March 2023. | TheGlobalEconomy.com

Total people vaccinated against Covid in Germany, March, 2023 The most recent value is 64900000 total people vaccinated as of March 2023, no change compared to the previous value of 64900000 total people vaccinated. Historically, the average for Germany from December 2020 to March 2023 is 51484855 total people vaccinated. The minimum of 206927 total people vaccinated was recorded in December 2020, while the maximum of 64900000 total people vaccinated was reached in November 2022. | TheGlobalEconomy.com

The COVID-19 pandemic has decelerated substantial parts of economic and human interaction. This paper estimates football matches’ contribution to the spread of COVID-19 during Germany’s second infection wave in summer and autumn 2020. Exploiting the exogenous fixture schedules of matches across German counties in an event study design, we estimate that one additional match in a county on average raises daily cases by between 0.34 to 0.71 cases per 100,000 inhabitants after three weeks. Hence, this implies an increase of the seven-day incidence per 100,000 inhabitants by around three to seven percent. We do not find qualitatively different results for a subsample of German top league matches with the strictest hygiene regulations or matches with higher occupancy levels. Notably, the found effect is mediated by the incidence level at the day of the match with very few infections for matches at a seven-day incidence below 25. Using mobile phone data, we identify strong increases in the local mobility as an underlying mechanism. We finally show that the ban of away fans successfully limited the spread of COVID-19 beyond county borders. Our results alert that even outdoor mass gatherings can remarkably cause infections.

Inflation Rate in Germany remained unchanged at 2.30 percent in November. This dataset provides the latest reported value for - Germany Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

We model the evolution of the number of individuals reported sick with COVID-19 in Germany. Our theoretical framework builds on a continuous time Markov chain with four states: healthy without infection, sick, healthy after recovery or despite infection but without symptoms, and deceased. Our quantitative solution matches the number of sick individuals up to the most recent observation and ends with a share of sick individuals following from infection rates and sickness probabilities. We employ this framework to study inter alia the expected peak of the number of sick individuals in Germany in a scenario without public regulation of social contacts. We also study the effects of public regulations. For all scenarios we report the expected end date of the CoV-2 epidemic.