Marcel Garz

Media | Digital Platforms | Political Economy

Vita

I am an associate professor of economics at Jönköping University. Most of my work focuses on news markets, especially from an empirical perspective. I am particularly interested in issues with cross-disciplinary implications, such as media slant, opinion diversity, and the role of digital platforms for the news industry and society at large. My research often involves methods supporting causal inference from observational data, as well as tools from computational linguistics and computer vision.

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Contact

Jönköping International Business School, Office B5015, Gjuterigatan 5, 55318 Jönköping, Sweden

Publications

Media Attention and Compliance with the European Court of Human Rights

With José Reis, 2024. Forthcoming in Journal of Conflict Resolution (working paper version).

Political viewpoint diversity in the news: Market and ownership conditions for a pluralistic media system

With Helle Sjøvaag and Mart Ots, 2023. Forthcoming in The International Journal of Press/Politics (replication data and code).

Data sharing and tax enforcement: Evidence from short-term rentals in Denmark

With Andrea Schneider, 2023. Regional Science and Urban Economics, 101 (working paper version, replication code).

Beware the community type: Engagement and growth in core vs. open online communities

With Thomas Cyron and Norbert Steigenberger, 2023. Forthcoming in Small Business Economics (replication data and code).

Cartels in the European Union, Antitrust Action, and Public Attention

With Sabrina Maaß. Journal of Economic Behavior & Organization, 186: 533-547, 2021 (online appendix; working paper versionreplication data and code).

Political Scandals, Newspapers, and the Election Cycle

With Jil Sörensen. Political Behavior, 43: 1017-1036, 2021 (working paper version; replication data and code).

Partisan Selective Engagement: Evidence from Facebook

With Jil Sörensen and Daniel Stone. Journal of Economic Behavior & Organization, 177: 91-108, 2020 (online appendix; working paper versionreplication data and code).

The Supply of Media Slant Across Outlets and Demand for Slant Within Outlets: Evidence from US Presidential Campaign News

With Gaurav Sood, Daniel Stone, and Justin Wallace. European Journal of Political Economy, 63: 1-22, 2020 (working paper version; replication data and code).

Cautionary Tales: Celebrities, the News Media, and Participation in Tax Amnesties

With Verena Pagels. Journal of Economic Behavior & Organization, 155: 288-300, 2018 (working paper versionreplication data and code).

The Online Market for Illegal Copies of Magazines: A German Case Study

With A. Rott and M. Wass von Czege. Journal of Broadcasting & Electronic Media, 59: 169–183, 2015.

Bad News Sells: The Demand for News Magazines and the Tone of Their Covers

With M. Arango-Kure and A. Rott. Journal of Media Economics, 27: 199–214, 2014.

Unemployment Expectations, Excessive Pessimism, and News Coverage

Journal of Economic Psychology, 34: 156–168, 2013.

Job Insecurity Perceptions and Media Coverage of Labor Market Policy

Journal of Labor Research, 33: 528–544, 2012.

Current

The Data Methods Initiative: A new online seminar series

Hosted by the Media, Management and Transformation Centre at Jönköping University, the newly-founded Data Methods Initiative organizes online seminars on social science research that applies tools from computational linguistics, computer vision, and machine learning. The seminars aim to strengthen methodological competencies, especially among early-career researchers, and promote the diversity of methods, especially for the analysis of texts, images, videos, and audio. The presentations cover topics in business and organization studies, economics, information systems, and others. The schedule for 2024 includes presentations by Mathilda Åkerlund (May 24), Ulrich Matter (Sep 4), Vejune Zemaityte (Oct 23), and Jukka Huhtamäki (Dec 4). The seminars feature a discussion of the research, as well as a look “behind the scenes”, where presenters share their practical experiences in working with a method. Registration for participation via https://www.datamethodsinitiative.org/.

Funding from Swedish Competition Authority

In a joint project entitled “Competition, multimarket contact, and quality of local newspaper coverage”, Mart Ots and I investigate the role of competition between media outlets for news quality. We use a combination of content analysis by human coders and machine-learning techniques to construct a large-scale measure of quality of Swedish newspaper coverage. We then investigate how news quality is related to different forms of market structure and market overlaps between newspaper companies, using plausibly exogenous changes in multimarket contact for causal inference. The project is funded by the Swedish Competition Authority over three years between 2023 and 2025.

Connecting computer science, linguistics, psychology, and economics

I joined a group of researchers that investigates media bias from a highly interdisciplinary perspective. The media bias group develops systems and large-scale datasets to automatically detect biased or unbalanced coverage, using methods from disciplines such as computer science, linguistics, psychology, and economics. The groups also devises new ways to visualize data, in an effort to better understand what types of bias appear in which context.

Media influence on vote choices

In a recent studyGreg Martin and I investigate how news about the economy influences voting decisions. We isolate the effect of the information environment from the effect of change in the underlying economic conditions themselves, by taking advantage of left-digit bias. We show that unemployment figures crossing a round-number “milestone” causes a discontinuous increase in the amount of media coverage devoted to unemployment conditions, and use this discontinuity to estimate the effect of attention to unemployment news on voting, holding constant the actual economic conditions on the ground. Milestone effects on incumbent US Governor vote shares are large and notably asymmetric: bad milestone events hurt roughly twice as much as good milestone events help.