Media coverage and pandemic behavior: Evidence from Sweden.

Publisher: Wiley Country of Publication: England NLM ID: 9306780 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1099-1050 (Electronic) Linking ISSN: 10579230 NLM ISO Abbreviation: Health Econ Subsets: MEDLINE

Original Publication: Chichester ; New York : Wiley, c1992-

COVID-19*/epidemiology ; Mass Media*; Humans ; Sweden ; Pandemics ; SARS-CoV-2 ; Newspapers as Topic ; Public Health ; Workplace

We study the effect of media coverage on individual behavior during a public health crisis. For this purpose, we collect a unique dataset of 200,000 newspaper articles about the Covid-19 pandemic from Sweden-one of the few countries that did not impose lockdowns or curfews. We show that mentions of Covid-19 significantly lowered the number of visits to workplaces and retail and recreation areas, while increasing the duration of stays in residential locations. Using two different identification strategies, we show that these effects are causal. The impacts are largest when Covid-19 news stories are more locally relevant, more visible and more factual. We find larger behavioral effects for articles that reference crisis managers (as opposed to medical experts) and contain explicit public health advice. These results have wider implications for the design of public communications and the value of the local media.
(© 2024 The Authors. Health Economics published by John Wiley & Sons Ltd.)

Alatas, V., Chandrasekhar, A. G., Mobius, M., Olken, B. A., & Paladines, C. (2021). Designing effective celebrity messaging: Results from a nationwide twitter experiment promoting vaccination in Indonesia. Working Paper.
Allcott, H., Boxell, L., Conway, J., Gentzkow, M., Thaler, M., & Yang, D. (2020). Polarization and public health: Partisan differences in social distancing during the coronavirus pandemic. Journal of Public Economics, 191, 104254. https://doi.org/10.1016/j.jpubeco.2020.104254.
Ananyev, M., Poyker, M., & Yuan, T. (2021). The safest time to fly: Pandemic response in the era of Fox news. Journal of Population Economics, 34, 775–802.
Ash, E., Galletta, S., Hangartner, D., Margalit, Y., & Pinna, M. (2020). The effect of Fox news on health behavior during COVID‐19. Working Paper.
Banerjee, A., Alsan, M., Breza, E., & Chandrasekhar, A. G. (2020). Messages on COVID‐19 prevention in India increased symptoms reporting and adherence to preventive behaviors among 25 million recipients with similar effects on non‐recipient members of their communities. National Bureau of Economic Research Working Paper 27496. Series: Working Paper Series.
Besley, T., & Dray, S. (2021). Pandemic responsiveness: Evidence from social distancing and lockdown policy during COVID‐19. Working Paper.
Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. Journal of Machine Learning Research, 3, 993–1022.
Bohlin, G., M. Bergman, and F. Brounéus. 2021. Allm’́anhetens syn på medierapporteringen om corona. In Journalistik i coronans tid. ed. Institutet för mediestudier, 144–155. Institutet för mediestudier.
Borri, N., Drago, F., Santantonio, C., & Sobbrio, F. (2021). The “great lockdown”: Inactive workers and mortality by covid‐19. Health Economics, 30(10), 2367–2382. https://doi.org/10.1002/hec.4383.
Bursztyn, L., Rao, A., Roth, C., & Yanagizawa‐Drott, D. (2020). Misinformation during a pandemic. Working Paper.
Ciminelli, G., & Garcia‐Mandicó, S. (2022). When and how do business shutdowns work? Evidence from Italy’s first COVID‐19 wave. Health Economics. forthcoming.
Claeson, M., & Hanson, S. (2021). COVID‐19 and the Swedish enigma. The Lancet, 397(10271), 259–261. https://doi.org/10.1016/s0140‐6736(20)32750‐1.
Colella, F., Lalive, R., Sakalli, S. O., & Mathias, T. (2019). Inference with arbitrary clustering. Working Paper.
Cornelson, K., & Miloucheva, B. (2022). Political polarization and cooperation during a pandemic. Health Economics. forthcoming.
Dahlberg, M., Edin, P.‐A., Grönqvist, E., Lyhagen, J., Östh, J., Siretskiy, A., & Toger, M. (2020). Effects of the COVID‐19 pandemic on population mobility under mild policies: Causal evidence from Sweden. Working paper.
Davison, W. P. (1983). The third‐person effect in communication. Public Opinion Quarterly, 47, 1–15. https://doi.org/10.1086/268763.
DellaVigna, S. (2009). Psychology and Economics: Evidence from the field. Journal of Economic Literature, 47(2), 315–372. https://doi.org/10.1257/jel.47.2.315.
DellaVigna, S., & Gentzkow, M. (2010). Persuasion: Empirical evidence. Annual Review of Economics, 2(1), 643–669. https://doi.org/10.1146/annurev.economics.102308.124309.
DellaVigna, S., & La Ferrara, E. (2015). Economic and social impacts of the media. In D. Strömberg, S. P. Anderson, & J. Waldfogel (Eds.), Handbook of media economics (Vol. 1, pp. 723–768). Elsevier.
Durante, R., Guiso, L., & Gulino, G. (2021). Asocial capital: Civic culture and social distancing during COVID‐19. Journal of Public Economics, 194, 104342. https://doi.org/10.1016/j.jpubeco.2020.104342.
Egorov, G., Enikolopov, R., Makarin, A., & Petrova, M. (2021). Divided we stay home: Social distancing and ethnic diversity. Journal of Public Economics, 194, 104328. https://doi.org/10.1016/j.jpubeco.2020.104328.
Eichengreen, B., Aksoy, C. G., & Saka, O. (2021). Revenge of the experts: Will COVID‐19 renew or diminish public trust in science? Journal of Public Economics, 193, 104343. https://doi.org/10.1016/j.jpubeco.2020.104343.
Fang, H., Wang, L., & Yang, Y. (2020). Human mobility restrictions and the spread of the novel coronavirus (2019‐nCoV) in China. Journal of Public Economics, 191, 104272. https://doi.org/10.1016/j.jpubeco.2020.104272.
FOHM. (2021a). Bekräftade fall i Sverige. Folkhälsomyndigheten.
FOHM. (2021b). Personer över 70 bör begränsa sociala kontakter tills vidare. Folkhälsomyndigheten.
Gabaix, X. (2019). Chapter 4 ‐ behavioral inattention. In B. Douglas Bernheim, S. DellaVigna, & D. Laibson (Eds.), Handbook of behavioral economics ‐ foundations and applications (Vol. 2, pp. 261–343). North‐Holland.
Garz, M., & Rickardsson, J. (2022). Ownership and media slant: Evidence from Swedish newspapers. Kyklos, 76(1), 18–40. https://doi.org/10.1111/kykl.12318.
Gentzkow, M., JesseShapiro, M., & Sinkinson, M. (2011). The effect of newspaper entry and exit on electoral politics. The American Economic Review, 101(7), 2980–3018. https://doi.org/10.1257/aer.101.7.2980.
Gentzkow, M., & Shapiro, J. M. (2010). What drives media slant? Evidence from US daily newspapers. Econometrica, 78, 35–71.
George, L., & Waldfogel, J. (2003). Who affects whom in daily newspaper markets? Journal of Political Economy, 111(4), 765–768. https://doi.org/10.1086/375380.
Glaeser, E. L., Gorback, C., & Redding, S. J. (2022). JUE insight: How much does COVID‐19 increase with mobility? Evidence from New York and four other U.S. Cities. Journal of Urban Economics, 127, 103292. https://doi.org/10.1016/j.jue.2020.103292.
Google. (2023). Covid‐19 community mobility reports. Retrieved from https://www.google.com/covid19/mobility/. Last accessed: Nov. 22 2023.
Islam, N., Shkolnikov, V. M., Acosta, R. J., Klimkin, I., Kawachi, I., Irizarry, R. A., Alicandro, G., Khunti, K., Yates, T., Jdanov, D. A., White, M., Lewington, S., & Lacey, B. (2021). Excess deaths associated with Covid‐19 pandemic in 2020: Age and sex disaggregated time series analysis in 29 high income countries. BMJ, 373, n1137. https://doi.org/10.1136/bmj.n1137.
Kim, E., Shepherd, M. E., & Clinton, J. D. (2020). The effect of big‐city news on rural America during the COVID‐19 pandemic. PNAS, 117(36), 22009–22014. https://doi.org/10.1073/pnas.2009384117.
Martin, G. J., & McCrain, J. (2019). Local news and national politics. American Political Science Review, 113(2), 372–384. https://doi.org/10.1017/s0003055418000965.
MPRT (2020). “Dagstidnings f’́orteckning 2020.” Myndigheten för press, radio och tv Annual Report.
Nickell, S. (1981). Biases in dynamic models with fixed effects. Econometrica, 49(6), 1417–1426. https://doi.org/10.2307/1911408.
Nivre, J., & Megyesi, B. (2007). Bootstrapping a Swedish treebank using cross‐corpus harmonization and annotation projection. Technical report.
Nordicom (2020). “Mediebarometern 2019.” Göteborgs universitet Annual Report.
Nouvellet, P., Bhatia, S., Cori, A., KylieAinslie, E. C., Baguelin, M., Bhatt, S., Boonyasiri, A., Brazeau, N. F., Cattarino, L., Cooper, L. V., Coupland, H., Cucunuba, Z. M., Cuomo‐Dannenburg, G., Amy, D., Djaafara, B. A., Dorigatti, I., Eales, O. D., Sabinevan Elsland, L., Nascimento, F. F., … Donnelly, C. A. (2021). Reduction in mobility and COVID‐19 transmission. Nature Communications, 12(1), 1090. https://doi.org/10.1038/s41467‐021‐21358‐2.
Orea, L., & Álvarez, I. C. (2022). How effective has the Spanish lockdown been to battle COVID‐19? A spatial analysis of the coronavirus propagation across provinces. Health Economics, 31(1), 154–173. https://doi.org/10.1002/hec.4437.
Pinna, M., Picard, L., & Goessmann, C. (2021). Cable news and COVID‐19 vaccine compliance. Working Paper.
Porter, M. F. (2001). Snowball: A language for stemming algorithms. Published online.
Prat, A., Strömberg, D., Arellano, M., & Dekel, E. (2013). The political economy of mass media. In D. Acemoglu (Ed.), Advances in economics and econometrics (pp. 135–187). Cambridge University Press.
Presstödsförordning. (1990). Presstödsförordning. Kulturdepartmentet SFS 1990: 524.
Sacerdote, B., Sehgal, R., & Cook, M. (2020). Importing political polarization? The electoral consequences of rising trade exposure. National Bureau of Economic Research. Working Paper 28110.
Sapienza, P., & Zingales, L. (2013). Economic experts versus average Americans. The American Economic Review, 103(3), 636–642. https://doi.org/10.1257/aer.103.3.636.
Shenoy, A., Sharma, B., Xu, G., Kapoor, R., Aiden Rho, H., & Sangha, K. (2022). God is in the rain: The impact of rainfall‐induced early social distancing on COVID‐19 outbreaks. Journal of Health Economics, 81, 102575. https://doi.org/10.1016/j.jhealeco.2021.102575.
Simonov, A., Sacher, S. K., Dubé, J.‐P. H., & Biswas, S. (2020). The persuasive effect of Fox news: Non‐compliance with social distancing during the covid‐19 pandemic. Working Paper.
Snyder, J. M., & Strömberg, D. (2010). Press coverage and political accountability. Journal of Political Economy, 118(2), 355–408. https://doi.org/10.1086/652903.
Straka, M., & Straková, J. (2017). Tokenizing, POS tagging, lemmatizing and parsing UD 2.0 with UDPipe (pp. 88–99). Association for Computational Linguistics.
Wakefield, M. A., Loken, B., & Hornik, R. C. (2010). Use of mass media campaigns to change health behaviour. The Lancet, 376(9748), 1261–1271. https://doi.org/10.1016/s0140‐6736(10)60809‐4.
Waldfogel, J. (2003). Preference externalities: An empirical study of who benefits whom in differentiated product markets. The RAND Journal of Economics, 34(3), 557–568. https://doi.org/10.2307/1593746.
Wu, Y., Mooring, T. A., & Linz, M. (2021). Policy and weather influences on mobility during the early US COVID‐19 pandemic. PNAS, 118(22), 1–8. https://doi.org/10.1073/pnas.2018185118.
Zhuang, M. (2022). Intergovernmental conflict and censorship: Evidence from China’s anti‐corruption campaign. Journal of the European Economic Association. forthcoming.

Keywords: Covid‐19; mobility; newspapers; persuasion; public health

Date Created: 20240229 Date Completed: 20240429 Latest Revision: 20240429

20240501

10.1002/hec.4814

38421732