Abstract
The COVID-19 pandemic has had severe social and economic consequences. Governments have implemented or expanded a number of policy measures to cope with these consequences. In the paper, we ask whether there is more support for general social policy measures to compensate for the new uncertainties arising from the pandemic. Using survey data collected in two panel waves in March and June/July 2020, we analyse how public welfare attitudes have changed during the first phase of the pandemic in Germany. In addition to the individual-level survey data, we use time-varying regional data on infection and unemployment rates. We provide descriptive results and employ fixed-effects regressions. Our results show small changes in welfare attitudes, but we do not find evidence for increased public support for general social policy measures.
About the authors
Henning Lohmann is Professor of Sociology, in particular Social Research Methods at University of Hamburg, Germany. His research interests include social inequality, in-work poverty, family, and the welfare state.
Hequn Wang is doctoral candidate and research assistant at the Chair of Sociology, in particular Social Research Methods, University of Hamburg, Germany. Her research interests include social inequality, perceptions, and welfare state attitudes.
Acknowledgements
We acknowledge funding from the Federal Ministry of Labour and Social Affairs within the framework of the FIS network. For support, comments, and suggestions, the authors thank Miriam Beblo, Elisabeth Bublitz, Julian Jäger, and the participants of the SAMF Annual Conference 2021 and the IAB Seminar ‘Corona’ Series. We are also grateful to the editors and two anonymous referees for their detailed comments.
Bibliography
Alesina, Alberto; Giuliano, Paola (2011): “Preferences for Redistribution”, in: Jess Benhabib; Alberto Bisin; Matthew 0. Jackson (eds.): Handbook of Social Economics. Volume 1. North-Holland: Elsevier, 93–131.10.1016/B978-0-444-53187-2.00004-8Search in Google Scholar
Alesina, Alberto; La Ferrara, Eliana (2005): “Preferences for Redistribution in the Land of Opportunities”, Iournal of Public Economics 89(5–6): 897–931.10.3386/w8267Search in Google Scholar
Anderson, Christopher J.; Hecht, Jason D. (2018): “The Preference for Europe: Public Opinion about European Integration since 1952”, European Union Politics 19(4): 617–638.10.1177/1465116518792306Search in Google Scholar
Beblo, Miriam; Bublitz, Elisabeth; Jäger, Julian; Lohmann, Henning; Wang, Hequn (2021): SOECBIAS data set: Socioeconomic data on income (mis-)perceptions and redistributive preferences in four EU Member States. Universität Hamburg, Working Paper, March 2021.Search in Google Scholar
Beetsma, Roel M. W. J.; Burgoon, Brian; Nicoli, Francesco; Ruijter, Anniek de; Vandenbroucke, Frank (2020): What Kind of EU Fiscal Capacity? Evidence from a Randomized Survey Experiment in Five European Countries in Times of Corona. CESifo Working Paper No. 8470, July 2020.Search in Google Scholar
Bénabou, Roland; Ok, Efe A. (2001): “Social Mobility and the Demand for Redistribution: The POUM Hypothesis”, The Quarterly Journal of Economics 116(2): 447–487.10.3386/w6795Search in Google Scholar
Beznoska, Martin; Niehues, Judith; Stockhausen, Maximilian (2021): “Verteilungsfolgen der Corona-Pandemie: Staatliche Sicherungssysteme und Hilfsmaßnahmen stabilisieren soziales Gefüge”, Wirtschaftsdienst 101(1): 17–21.10.1007/s10273-021-2819-3Search in Google Scholar
Bobzien, Licia; Kalleitner, Fabian (2020): “Attitudes towards European Financial Solidarity during the Covid-19 Pandemic: Evidence from a Net-Contributor Country”, European Societies 23(S1): 791–804.10.1080/14616696.2020.1836669Search in Google Scholar
Bundesagentur für Arbeit (2020): Arbeitslosenquoten – Zeitreihe (Monatszahlen). Statistik der Bundesagentur für Arbeit, Tabellen, June 2020.Search in Google Scholar
Bundesregierung (2020): Beschluss der Bundeskanzlerin sowie Regierungschefinnen und Regierungschefs der Länder vom 22.03.2020.Search in Google Scholar
Curtice, John (2020): “Will Covid-19 Change Attitudes towards the Welfare State? How the Public Might Swing in Favour of Improved Welfare Provision for Those of Working Age”, IPPR Progressive Review 27(1): 93–104.10.1111/newe.12185Search in Google Scholar
Cusack, Thomas; Iversen, Torben; Rehm, Philipp (2006): “Risks at Work: The Demand and Supply Sides of Government Redistribution”, Oxford Review of Economic Policy 22(3): 365–389.10.1093/oxrep/grj022Search in Google Scholar
Daniele, Gianmarco; Martinangeli, Andrea F. M.; Passarelli, Francesco; Sas, Willem; Wind-steiger, Lisa (2020): Wind of Change? Experimental Survey Evidence on the COVID-19 Shock and Socio-Political Attitudes in Europe. CESifo Working Paper No. 8517, Munich, August 2020.10.2139/ssrn.3671674Search in Google Scholar
Destatis, Statistisches Bundesamt (2021a): Statistik Dossier: Daten zur COVID-19-Pandemie, Ausgabe 01/2021.Search in Google Scholar
Destatis, Statistisches Bundesamt (2021b): Mobilitätsindikatoren auf Basis von Mobilfunkdaten. Experimentelle Daten. Download at: https://www.destatis.de/DE/Service/EXDAT/Datensaetze/mobilitaetsindikatoren-mobilfunkdaten.html#allgemeines%20Mobilit%C3%A4tsverhalten (access on 12/02/2021).Search in Google Scholar
Gerhards, Jürgen (2020): Europäische Solidarität in der Corona-Krise. Freie Universität Berlin, BSSE Working Paper No. 41, April 2020.Search in Google Scholar
Gonthier, Frederic (2017): “Parallel Publics? Support for Income Redistribution in Times of Economic Crisis”, European Journal of Political Research 56(1): 92–114.10.1111/1475-6765.12168Search in Google Scholar
Grabka, Markus M. (2021): “Einkommensungleichheit stagniert langfristig, sinkt aber während der Corona-Pandemie leicht”, DIW Wochenbericht Nr. 18/2021: 308–316.Search in Google Scholar
Grabka, Markus M.; Braband, Carsten; Göbler, Konstantin (2020): “Beschäftigte in Minijobs sind Verliererinnen der coronabedingten Rezession”, DIW Wochenbericht Nr. 45/2020: 842–847.Search in Google Scholar
Graeber, Daniel; Kritikos, Alexanders.; Seebauer, Johannes (2020a): COVID-19: A Crisis of the Female Self-Employed. DIW Berlin Discussion Paper No. 1903, October 5, 2020.Search in Google Scholar
Graeber, Daniel; Schmidt, Ulrich; Schröder, Carsten; Seebauer, Johannes (2020b): The Effect of a Major Pandemic on Risk Preferences – Evidence from Exposure to COVID-19. SSRN research paper, November 2020.10.2139/ssrn.3724461Search in Google Scholar
Häusermann, Silja; Kurer, Thomas; Schwander, Hanna (2015): “High-Skilled Outsiders? Labor Market Vulnerability, Education and Welfare State Preferences”, Socio-Economic Review 13(2): 235–258.10.1093/ser/mwu026Search in Google Scholar
Hipp, Lena; Bünning, Mareike (2021): “Parenthood as a Driver of Increased Gender Inequality during COVID-19? Exploratory Evidence from Germany”, European Societies 23(S1): S658– S673.10.1080/14616696.2020.1833229Search in Google Scholar
Holst, Hajo; Fessier, Agnes; Niehoff, Steffen (2021): “Covid-19, Social Class and Work Experience in Germany: Inequalities in Work-Related Health and Economic Risks”, European Societies 23(S1) : S495–S512.10.1080/14616696.2020.1828979Search in Google Scholar
Jaeger, Mads Meier (2006): “What Makes People Support Public Responsibility for Welfare Provision: Self-interest or Political Ideology? A Longitudinal Approach”, Acta Sociologica 49(3): 321–338.10.1177/0001699306067718Search in Google Scholar
Kohlrausch, Bettina; Zucco, Aline (2020): Die Corona-Krise trifft Frauen doppelt. Weniger Erwerbseinkommen und mehr Sorgearbeit. Hans-Böckler-Stiftung, Policy Brief WSI Nr. 40, May 2020.Search in Google Scholar
Kohlrausch, Bettina; Zucco, Aline; Hövermann, Andreas (2020): Verteilungsbericht 2020. Die Einkommensungleichheit wird durch die Corona-Krise noch weiter verstärkt. Hans-Böckler-Stiftung, WSI Report Nr. 62, November 2020.Search in Google Scholar
Kritikos, Alexander S.; Graeber, Daniel; Seebauer, Johannes (2020): “Corona-Pandemie wird zur Krise für Selbständige”, DIW aktuell Nr. 47, 12. Juni 2020.Search in Google Scholar
Kroeger, Philipp (2014): “Demand for Redistribution in the Wake of the Economic Crisis”, Economics and Business Letters 3(3): 156–165.10.17811/ebl.3.3.2014.156-165Search in Google Scholar
Margalit, Yotam (2013): “Explaining Social Policy Preferences: Evidence from the Great Recession”, American Political Science Review 107(1): 80–103.10.1017/S0003055412000603Search in Google Scholar
Margalit, Yotam (2019): “Political Responses to Economic Shocks”, Annual Review of Political Science 22(1): 277–295.10.1146/annurev-polisci-050517-110713Search in Google Scholar
Meitzer, Allan H.; Richard, Scott F. (1981): “A Rational Theory of the Size of Government”, Journal of Political Economy 89(5): 914–927.10.1086/261013Search in Google Scholar
Mughan, Anthony (2007): “Economic Insecurity and Welfare Preferences: A Micro-Level Analysis”, Comparative Politics 39(3): 293–310.Search in Google Scholar
Naumann, Elias; Buss, Christopher; Bähr, Johannes (2016): “How Unemployment Experience Affects Support for the Welfare State: A Real Panel Approach”, European Sociological Review 32(1): 81–92.10.1093/esr/jcv094Search in Google Scholar
Olivera, Javier (2014): “Preferences for Redistribution after the Economic Crisis”, Economics and Business Letters 3(3): 137–145.10.17811/ebl.3.3.2014.137-145Search in Google Scholar
Owens, Lindsay A.; Pedulla, David S. (2014): “Material Welfare and Changing Political Preferences: The Case of Support for Redistributive Social Policies”, Social Forces 92(3): 1087–1113.10.1093/sf/sot101Search in Google Scholar
Rees, Jonas; Papendick, Michael; Rees, Yann; Wäschle, Franziska; Zick, Andreas (2020): Erste Ergebnisse einer Online-Umfrage zur gesellschaftlichen Wahrnehmung des Umgangs mit der Corona-Pandemie in Deutschland. Institut für interdisziplinäre Konflikt- und Gewaltforschung (IKG).Search in Google Scholar
Rehm, Philipp (2009): “Risks and Redistribution. An Individual-Level Analysis”, Comparative Political Studies 42(7): 855–881.10.1177/0010414008330595Search in Google Scholar
Rehm, Philipp (2011): “Social Policy by Popular Demand”, World Politics 63(2): 271–299.10.1017/S0043887111000037Search in Google Scholar
RKI, Robert Koch-lnstitut (2020a): Coronavirus SARS-CoV-2. Gesamtübersicht der pro Tag ans RKI übermittelten Fälle, Todesfälle und 7-Tage-lnzidenzen nach Bundesland und Landkreis. Download at: https://www.rki.de/DE/Content/lnfAZ/N/Neuartiges_Corona-virus/Daten/Fallzahlen_Daten.html (access on 12/02/2021).Search in Google Scholar
RKI, Robert Koch-Institut (2020b): COVID-19 Datenhub. RKI Corona Landkreise. Download at: https://npgeo-corona-npgeo-de.hub.arcgis.com/datasets/917fc37a709542548cc3be077a786cl7_0/geoservice (access on 29/07/2020).Search in Google Scholar
Schröder, Carsten; Entringer, Theresa; Göbel, Jan; Grabka, Markus; Graeber, Daniel; Kröger, Hannes; Kroh, Martin; Kühne, Simon; Liebig, Stefan; Schupp, Jürgen; Seebauer, Johannes; Zinn, Sabine (2020): Covid-19 is Not Affecting All Working People Equally. DIW Berlin, SOEPpapers 1083–2020.Search in Google Scholar
Svallfors, Stefan (2004): “Class, Attitudes and the Welfare State: Sweden in Comparative Perspective”, Social Policy & Administration 38(2): 119–138.10.1111/j.1467-9515.2004.00381.xSearch in Google Scholar
Changes in employment, household income and work situation
Changes in household income and work situation by changes in employment | ||||
---|---|---|---|---|
Monthly net household income | Work situation | |||
Changes in employment | Total (in %) | Declined (in %) | Short-time work (in %) | Remote working (in %) |
Employed (unchanged) | 41.59 | 22.89 | 10.15 | 33.78 |
Own business (unchanged) | 5.64 | 48.68 | 4.40 | 32.80 |
Unemployed (unchanged) | 2.51 | 13.61 | - | - |
Employed/ own business - Short-time work | 3.45 | 84.29 | 85.74 | 22.17 |
Employed/ own business- Unemployed | 0.73 | 68.68 | - | 16.92 |
Other | 46.08 | 19.44 | 1.71 | 6.21 |
Total | 25.01 | 8.43 | 19.91 |
Note: n=957, weighted
Fixed-effects models: Welfare attitudes, alternative specification (3 periods)
Willingness to pay higher taxes and social insurance contributions | Attitudes towards responsibility of national government | |||||
---|---|---|---|---|---|---|
(1) | (2) | (3) | (1) | (2) | (3) | |
Period (Ref.: 17–26 March) |
||||||
6–7 March | 0.061 | 0.062 | 0.056 | 0.461 | 0.471 | 0.450 |
(0.086) | (0.086) | (0.092) | (0.514) | (0.513) | (0.550) | |
June/July | -0.038* | -0.040* | -0.048 | -0.131 | -0.179 | -0.175 |
(0.016) | (0.017) | (0.042) | (0.093) | (0.098) | (0.249) | |
Attitudes towards responsibility of EU | Support for EU-wide minimum wage | |||||
(1) | (2) | (3) | (1) | (2) | (3) | |
Period (Ref.: 17-26 March) |
||||||
6-7 March | -0.016 | -0.012 | -0.536 | 0.021 | 0.010 | 0.068 |
(0.583) | (0.581) | (0.622) | (0.213) | (0.213) | (0.228) | |
June/July | -0.338** | -0.356** | -0.769** | 0.105** | 0.093* | 0.111 |
(0.105) | (0.111) | (0.281) | (0.038) | (0.041) | (0.103) | |
Individual-level indicators | - | yes | yes | - | yes | yes |
Regional indicators | - | - | yes | - | - | yes |
N | 2052 | 2052 | 2052 | 2052 | 2052 | 2052 |
Note: Individual-level indicators: employment status, test/infection with COVID-19; regional indicators: district-level infection rate (7-day incidence), district-level unemployment rate; weighted; standard errors in parentheses; significance levels: ** = 0.01, * = 0.05
Fixed-effects models: Welfare attitudes, alternative specification (4 periods)
Willingness to pay higher taxes and social insurance contributions | Attitudes towards responsibility of national government | |||||
---|---|---|---|---|---|---|
(1) | (2) | (3) | (1) | (2) | (3) | |
Period | ||||||
(Ref.: 17–26 March) | ||||||
6–7 March | 0.055 | 0.057 | 0.055 | 0.458 | 0.467 | 0.449 |
(0.086) | (0.087) | (0.093) | (0.515) | (0.514) | (0.550) | |
22–26 March | -0.048 | -0.044 | -0.035 | -0.026 | -0.031 | -0.104 |
(0.048) | (0.048) | (0.052) | (0.286) | (0.286) | (0.309) | |
June/July | -0.044 ** | -0.045* | -0.050 | -0.134 | -0.183 | -0.179 |
(0.017) | (0.017) | (0.042) | (0.099) | (0.103) | (0.249) | |
Attitudes towards responsibility of EU | Support for EU-wide minimum wage | |||||
(1) | (2) | (3) | (1) | (2) | (3) | |
Period (Ref: 17–26 March) |
||||||
6–7 March | -0.023 | -0.025 | -0.535 | 0.029 | 0.017 | 0.068 |
(0.585) | (0.583) | (0.622) | (0.213) | (0.213) | (0.228) | |
22–26 March | -0.061 | -0.110 | -0.015 | 0.066 | 0.054 | 0.030 |
(0.325) | (0.324) | (0.349) | (0.119) | (0.119) | (0.128) | |
June/July | -0.345** | -0.368 ** | -0.769** | 0.113** | 0.099* | 0.112 |
(0.112) | (0.117) | (0.282) | (0.041) | (0.043) | (0.103) | |
Individual-level indicators | - | yes | yes | - | yes | yes |
Regional indicators | - | - | yes | - | - | yes |
N | 2052 | 2052 | 2052 | 2052 | 2052 | 2052 |
Note: Individual-level indicators: employment status, test/infection with COVID-19; regional indicators: district-level infection rate (7-day incidence), district-level unemployment rate; weighted; standard errors in parentheses; significance levels: ** = 0.01, * = 0.05
Fixed-effects models: Changes in welfare attitudes by test/infection with COVID-19
(1) | (2) | (3) | (4) | |
---|---|---|---|---|
Period | ||||
(Ref.: March 2020) | ||||
June/July 2020 | -0.054 | -0.214 | -0.735** | 0.099 |
(0.040) | (0.237) | (0.268) | (0.098) | |
Test/lnfection with COVID-19 | ||||
(Ref.: Not tested or infected) | ||||
Tested | 0.195 | 0.389 | -1.109 | -0.380 |
(0.209) | (1.241) | (1.402) | (0.515) | |
Infected, not tested | -0.024 | 2.000** | 0.586 | 0.100 |
(0.113) | (0.673) | (0.761) | (0.279) | |
Period x Test/infection with COVID-19 | ||||
(Ref.: June/July 2020 x Not tested or infected) | ||||
x Tested | -0.126 | -0.469 | 0.380 | 0.123 |
(0.199) | (1.184) | (1.338) | (0.491) | |
x Infected, not tested | -0.024 | -0.465 | 0.885* | 0.027 |
(0.060) | (0.357) | (0.403) | (0.148) | |
Constant | 0.608 *** | 5.339*** | 4.283 *** | 3.307*** |
(0.142) | (0.845) | (0.955) | (0.351) | |
r2 | 0.012 | 0.019 | 0.035 | 0.020 |
N | 2052 | 2052 | 2052 | 2052 |
Note: Respective dependent variable from column (1) to (4): willingness to pay higher taxes and social insurance contributions; attitudes towards responsibility of national government; attitudes towards responsibility of EU; and support for EU-wide minimum wage. Individual employment status as well as district-level infection rate (7-day incidence) and unemployment rate are controlled for in all models. Weighted, standard errors in parentheses, significance levels: *** = 0.001, ** = 0.01, * = 0.05.
© 2022 Walter de Gruyter GmbH, Berlin/Boston