Media Slant is Contagious: What We Can Conclude From This

Table of Links Abstract and 1 Introduction 2. Data 3. Measuring Media Slant and 3.1. Text pre-processing and featurization 3.2. Classifying transcripts by TV source 3.3. Text similarity between newspapers and TV stations and 3.4. Topic model 4. Econometric Framework 4.1. Instrumental variables specification 4.2. Instrument first stage and validity 5. Results 5.1. Main results 5.2. Robustness checks 6. Mechanisms and Heterogeneity 6.1. Local vs. national or international news content 6.2. Cable news media slant polarizes local newspapers 7. Conclusion and References Online Appendices A. Data Appendix A.1. Newspaper articles A.2. Alternative county matching of newspapers and A.3. Filtering of the article snippets A.4. Included prime-time TV shows and A.5. Summary statistics B. Methods Appendix, B.1. Text pre-processing and B.2. Bigrams most predictive for FNC or CNN/MSNBC B.3. Human validation of NLP model B.4. Distribution of Fox News similarity in newspapers and B.5. Example articles by Fox News similarity B.6. Topics from the newspaper-based LDA model C. Results Appendix C.1. First stage results and C.2. Instrument exogeneity C.3. Placebo: Content similarity in 1995/96 C.4. OLS results C.5. Reduced form results C.6. Sub-samples: Newspaper headquarters and other counties and C.7. Robustness: Alternative county matching C.8. Robustness: Historical circulation weights and C.9. Robustness: Relative circulation weights C.10. Robustness: Absolute and relative FNC viewership and C.11. Robustness: Dropping observations and clustering C.12. Mechanisms: Language features and topics C.13. Mechanisms: Descriptive Evidence on Demand Side C.14. Mechanisms: Slant contagion and polarization 7. Conclusion We document that partisan news messaging by large media organizations can spill over to smaller outlets. Specifically, the news messaging by U.S. cable TV channels influences local news reporting. Our evidence suggests that the newspapers shift the slant in their own local content, where direct copy-pasting from the TV channels is not possible (since the latter are nationally-oriented). Moreover, the exposure to the TV channels leads to a polarization of local news, where outlets that had already been pro-Republican in the pre-FNC/MSNBC era shift more towards FNC-like language. In contrast, outlets with a historically pro-Democrat leaning move towards CNN/MSNBClike language in response to higher FNC exposure. These findings add to concerns regarding increasing political polarization in the U.S. and beyond (e.g., Campbell, 2018; Carothers and O’Donohue, 2019). References Adena, M., Enikolopov, R., Petrova, M., Santarosa, V., and Zhuravskaya, E. (2015). Radio and the Rise of the Nazis in Prewar Germany. The Quarterly Journal of Economics, 130(4):1885–1939. Ash, E. and Galletta, S. (2023). How cable news reshaped local government. American Economic Journal: Applied Economics. Ash, E., Galletta, S., Hangartner, D., Margalit, Y., and Pinna, M. (2020). The Effect of Fox News on Health Behavior during COVID-19. Available at SSRN 3636762. Ash, E., Galletta, S., Pinna, M., and Warshaw, C. (2021). The Effect of Fox News Channel on US Elections: 2000-2020. Center for Law & Economics Working Paper Series, 2021(07). Ash, E. and Hansen, S. (2022). Text Algorithms in Economics. Annual Review of Economics. Ash, E. and Poyker, M. (2019). Conservative News Media and Criminal Justice: Evidence from Exposure to Fox News Channel. Columbia Business School Research Paper. Ashworth, S. and Shotts, K. W. (2010). Does Informative Media Commentary Reduce Politicians’ Incentives to Pander? Journal of Public Economics, 94(11-12):838–847. Athey, S., Tibshirani, J., and Wager, S. (2019). Generalized Random Rorests. The Annals of Statistics, 47(2):1148–1178. Blei, D. M., Ng, A. Y., and Jordan, M. I. (2003). Latent Dirichlet Allocation. Journal of Machine Learning Research, 3:993–1022. Bursztyn, L., Rao, A., Roth, C., and Yanagizawa-Drott, D. (2021). Opinions as Facts. Technical report, National Bureau of Economic Research. Bybee, L., Kelly, B. T., Manela, A., and Xiu, D. (2020). The Structure of Economic News. Technical report, National Bureau of Economic Research. Cagé, J., Hervé, N., and Mazoyer, B. (2020a). Social Media and Newsroom Production Decisions. Technical report, SSRN. Cagé, J., Hervé, N., and Viaud, M.-L. (2020b). The Production of Information in an Online World. The Review of Economic Studies, 87(5):2126–2164. Campbell, J. E. (2018). Polarized: Making sense of a divided America. Princeton University Press. Carothers, T. and O’Donohue, A. (2019). Democracies divided: The global challenge of political polarization. Brookings Institution Press. Chiang, C.-F. and Knight, B. G. (2011). Media Bias and Influence: Evidence from Newspaper Endorsements. Review of Economic Studies, 78(3):795–820. DellaVigna, S., Enikolopov, R., Mironova, V., Petrova, M., and Zhuravskaya, E. (2014). Cross-Border Media and Nationalism: Evidence from Serbian Radio in Croatia. American Economic Journal: Applied Economics, 6(3):103–32. DellaVigna, S. and Kaplan, E. (2007). The Fox News Effect: Media Bias and Voting. The Quarterly Journal of Economics, 122(3):1187–1234. Denny, M. J. and Spirling, A. (2018). Text Preprocessing for Unsupervised Learning: Why it Matters, When It Misleads, and What To Do About It. Political Analysis, 26(2):168–189. Djourelova, M. (2023). Persuasion Through Slanted Language: Evidence from the Media Coverage of Immigration. American Economic Review. Djourelova, M., Durante, R., and Martin, G. (2021). The Impact of Online Competition on Local Newspapers: Evidence from the Introduction of Craigslist. Cepr discussion paper no. dp16130, Centre for Economic Policy Research. Drago, F., Nannicini, T., and Sobbrio, F. (2014). Meet the Press: How Voters and Politicians Respond to Newspaper Entry and Exit. American Economic Journal: Applied Economics, 6(3):159–88. Enikolopov, R., Petrova, M., and Zhuravskaya, E. (2011). Media and Political Persuasion: Evidence from Russia. American Economic Review, 101(7):3253–3285. Evans, D. S. (2009). The Online Advertising Industry: Economics, Evolution, and Privacy. Journal of Economic Perspectives, 23(3):37–60. Gentzkow, M., Kelly, B., and Taddy, M. (2019a). Text as Data. Journal of Economic Literature, 57(3):535–74. Gentzkow, M. and Shapiro, J. M. (2010). What Drives Media Slant? Evidence from US Daily Newspapers. Econometrica, 78(1):35–71. Gentzkow, M., Shapiro, J. M., and Sinkinson, M. (2011). The Effect of Newspaper Entry and Exit on Electoral Politics. American Economic Review, 101(7):2980–3018. Gentzkow, M., Shapiro, J. M., and Sinkinson, M. (2014). Competition and Ideological Diversity: Historical Evidence from U.S. Newspapers. American Economic Review, 104(10):3073–3114. Gentzkow, M., Shapiro, J. M., and Stone, D. F. (2015). Media Bias in the Marketplace: Theory. In Anderson, S. P., Waldfogel, J., and Stroemberg, D., editors, Handbook of Media Economics, volume 1, pages 623–645. North-Holland. Gentzkow, M., Shapiro, J. M., and Taddy, M. (2019b). Measuring Group Differences in High-Dimensional Choices: Method and Application to Congressional Speech. Econometrica, 87(4):1307–1340. George, L. M. and Waldfogel, J. (2006). The New York Times and the Market for Local Newspapers. American Economic Review, 96(1):435–447. Gilens, M. and Hertzman, C. (2000). Corporate Ownership and News Bias: Newspaper Coverage of the 1996 Telecommunications Act. Journal of Politics, 62(2):369–386. Groseclose, T. and Milyo, J. (2005). A Measure of Media Bias. Quarterly Journal of Economics, 120(4):1191 – 1238. Hansen, S., McMahon, M., and Prat, A. (2018). Transparency and Deliberation within the FOMC: a Computational Linguistics Approach. The Quarterly Journal of Economics, 133(2):801–870. Harmon, M. and Muenchen, R. (2009). Semantic Framing in the Build-up to the Iraq War: Fox v. CNN and other U.S. Broadcast News Programs. ETC: A Review of General Semantics, 66(1):12–26. Hastie, T., Tibshirani, R., and Friedman, J. (2009). The Elements of Statistical Larning. Springer, New York, NY. Hatte, S., Madinier, E., and Zhuravskaya, E. (2021). Reading Twitter in the Newsroom: How Social Media Affects Traditional-Media Reporting of Conflicts. Technical report, SSRN. Hoffman, M., Bach, F. R., and Blei, D. M. (2010). Online Learning for Latent Dirichlet Allocation. In Advances in Neural Information Processing Systems, pages 856–864. Hopkins, D. J. and Ladd, J. M. (2014). The Consequences of Broader Media Choice: Evidence from the Expansion of Fox News. Quarterly Journal of Political Science, 9(1):115–135. Kleinberg, J., Lakkaraju, H., Leskovec, J., Ludwig, J., and Mullainathan, S. (2017). Human decisions and machine predictions. The Quarterly Journal of Economics, 133(1):237–293. Li, Z. and Martin, G. J. (2022). Media and Ideological Movements: How Fox News Built the Tea Party. Technical report, Working Paper. Martin, G. J. and McCrain, J. (2019). Local News and National Politics. American Political Science Review, 113(2):372–384. Martin, G. J. and Yurukoglu, A. (2017). Bias in Cable News: Persuasion and Polarization. American Economic Review, 107(9):2565–2599. Mastrorocco, N. and Ornaghi, A. (2020). Who Watches the Watchmen? Local News and Police Behaviour in the United States. Technical report, Trinity Economics Papers. Mullainathan, S. and Shleifer, A. (2005). The Market for News. American Economic Review, 95(4):1031–1053. Osnabrügge, M., Ash, E., and Morelli, M. (2021). Cross-Domain Topic Classification for Political Texts. Political Analysis. Peterson, A. and Spirling, A. (2018). Classification Accuracy as a Substantive Quantity of Interest: Measuring Polarization in Westminster Systems. Political Analysis, forthcoming. Prat, A. (2018). Media Power. Journal of Political Economy, 126(4):1747 – 1783. Prat, A. and Stroemberg, D. (2013). The Political Economy of Mass Media, volume 2 of Econometric Society Monographs, page 135–187. Cambridge University Press, Cambridge, UK. Puglisi, R. and Snyder, J. M. (2011). Newspaper Coverage of Political Scandals. The journal of politics, 73(3):931–950. Puglisi, R. and Snyder, J. M. (2015). Empirical Studies of Media Bias. In Anderson, S. P., Waldfogel, J., and Stroemberg, D., editors, Handbook of Media Economics, volume 1, pages 647–667. North-Holland. Rolnik, G., Cagé, J., Gans, J., Goodman, E., Knight, B., Prat, A., Schiffrin, A., and Raj, P. (2019). Protecting Journalism in the Age of Digital Platforms. Committee for the Study of Digital Platforms Media Subcommittee. Chicago: Stigler Center for the Study of the Economy and the State. University of Chicago Booth School of Business. Schroeder, E. and Stone, D. F. (2015). Fox News and Political Knowledge. Journal of Public Economics, 126:52–63. Simonov, A., Sacher, S., Dube, J.-P., and Biswas, S. (2022). Frontiers: The Persuasive Effect of Fox News: Noncompliance with Social Distancing During the COVID-19 Pandemic. Marketing Science, 41(2):230–242. Snyder, J. M. and Strömberg, D. (2010). Press Coverage and Political Accountability. Journal of Political Economy, 118(2):355–408. Stroemberg, D. (2015). Media and Politics. Annual Review of Economics, 7:173–205. Szeidl, A. and Szucs, F. (2021). Media Capture through Favor Exchange. Econometrica, 89:281–310. Yanagizawa-Drott, D. (2014). Propaganda and Conflict: Evidence from the Rwandan Genocide. The Quarterly Journal of Economics, 129(4):1947–1994. This paper is available on arxiv under CC 4.0 license. Authors: (1) Philine Widmer, ETH Zürich and philine.widmer@gess.ethz.ch; (2) Sergio Galletta, ETH Zürich and sergio.galletta@gess.ethz.ch; (3) Elliott Ash, ETH Zürich and ashe@ethz.ch. Table of Links Abstract and 1 Introduction 2. Data Abstract and 1 Introduction 2. Data 3. Measuring Media Slant and 3.1. Text pre-processing and featurization 3. Measuring Media Slant and 3.1. Text pre-processing and featurization 3.2. Classifying transcripts by TV source 3.2. Classifying transcripts by TV source 3.3. Text similarity between newspapers and TV stations and 3.4. Topic model 3.3. Text similarity between newspapers and TV stations and 3.4. Topic model 4. Econometric Framework 4.1. Instrumental variables specification 4.1. Instrumental variables specification 4.2. Instrument first stage and validity 4.2. Instrument first stage and validity 5. Results 5.1. Main results 5.1. Main results 5.2. Robustness checks 5.2. Robustness checks 6. Mechanisms and Heterogeneity 6.1. Local vs. national or international news content 6.1. Local vs. national or international news content 6.2. Cable news media slant polarizes local newspapers 6.2. Cable news media slant polarizes local newspapers 7. Conclusion and References 7. Conclusion and References Online Appendices Online Appendices A. Data Appendix A.1. Newspaper articles A.1. Newspaper articles A.2. Alternative county matching of newspapers and A.3. Filtering of the article snippets A.2. Alternative county matching of newspapers and A.3. Filtering of the article snippets A.4. Included prime-time TV shows and A.5. Summary statistics A.4. Included prime-time TV shows and A.5. Summary statistics B. Methods Appendix, B.1. Text pre-processing and B.2. Bigrams most predictive for FNC or CNN/MSNBC B. Methods Appendix, B.1. Text pre-processing and B.2. Bigrams most predictive for FNC or CNN/MSNBC B.3. Human validation of NLP model B.3. Human validation of NLP model B.4. Distribution of Fox News similarity in newspapers and B.5. Example articles by Fox News similarity B.4. Distribution of Fox News similarity in newspapers and B.5. Example articles by Fox News similarity B.6. Topics from the newspaper-based LDA model B.6. Topics from the newspaper-based LDA model C. Results Appendix C.1. First stage results and C.2. Instrument exogeneity C.1. First stage results and C.2. Instrument exogeneity C.3. Placebo: Content similarity in 1995/96 C.3. Placebo: Content similarity in 1995/96 C.4. OLS results C.4. OLS results C.5. Reduced form results C.5. Reduced form results C.6. Sub-samples: Newspaper headquarters and other counties and C.7. Robustness: Alternative county matching C.6. Sub-samples: Newspaper headquarters and other counties and C.7. Robustness: Alternative county matching C.8. Robustness: Historical circulation weights and C.9. Robustness: Relative circulation weights C.8. Robustness: Historical circulation weights and C.9. Robustness: Relative circulation weights C.10. Robustness: Absolute and relative FNC viewership and C.11. Robustness: Dropping observations and clustering C.10. Robustness: Absolute and relative FNC viewership and C.11. Robustness: Dropping observations and clustering C.12. Mechanisms: Language features and topics C.12. Mechanisms: Language features and topics C.13. Mechanisms: Descriptive Evidence on Demand Side C.13. Mechanisms: Descriptive Evidence on Demand Side C.14. Mechanisms: Slant contagion and polarization C.14. Mechanisms: Slant contagion and polarization 7. Conclusion We document that partisan news messaging by large media organizations can spill over to smaller outlets. Specifically, the news messaging by U.S. cable TV channels influences local news reporting. Our evidence suggests that the newspapers shift the slant in their own local content, where direct copy-pasting from the TV channels is not possible (since the latter are nationally-oriented). Moreover, the exposure to the TV channels leads to a polarization of local news, where outlets that had already been pro-Republican in the pre-FNC/MSNBC era shift more towards FNC-like language. In contrast, outlets with a historically pro-Democrat leaning move towards CNN/MSNBClike language in response to higher FNC exposure. These findings add to concerns regarding increasing political polarization in the U.S. and beyond (e.g., Campbell, 2018; Carothers and O’Donohue, 2019). References Adena, M., Enikolopov, R., Petrova, M., Santarosa, V., and Zhuravskaya, E. (2015). Radio and the Rise of the Nazis in Prewar Germany. The Quarterly Journal of Economics, 130(4):1885–1939. Ash, E. and Galletta, S. (2023). How cable news reshaped local government. American Economic Journal: Applied Economics. Ash, E., Galletta, S., Hangartner, D., Margalit, Y., and Pinna, M. (2020). The Effect of Fox News on Health Behavior during COVID-19. Available at SSRN 3636762. Ash, E., Galletta, S., Pinna, M., and Warshaw, C. (2021). The Effect of Fox News Channel on US Elections: 2000-2020. Center for Law & Economics Working Paper Series, 2021(07). Ash, E. and Hansen, S. (2022). Text Algorithms in Economics. Annual Review of Economics. Ash, E. and Poyker, M. (2019). Conservative News Media and Criminal Justice: Evidence from Exposure to Fox News Channel. Columbia Business School Research Paper. Ashworth, S. and Shotts, K. W. (2010). Does Informative Media Commentary Reduce Politicians’ Incentives to Pander? Journal of Public Economics, 94(11-12):838–847. Athey, S., Tibshirani, J., and Wager, S. (2019). Generalized Random Rorests. The Annals of Statistics, 47(2):1148–1178. Blei, D. M., Ng, A. Y., and Jordan, M. I. (2003). Latent Dirichlet Allocation. Journal of Machine Learning Research, 3:993–1022. Bursztyn, L., Rao, A., Roth, C., and Yanagizawa-Drott, D. (2021). Opinions as Facts. Technical report, National Bureau of Economic Research. Bybee, L., Kelly, B. T., Manela, A., and Xiu, D. (2020). The Structure of Economic News. Technical report, National Bureau of Economic Research. Cagé, J., Hervé, N., and Mazoyer, B. (2020a). Social Media and Newsroom Production Decisions. Technical report, SSRN. Cagé, J., Hervé, N., and Viaud, M.-L. (2020b). The Production of Information in an Online World. The Review of Economic Studies, 87(5):2126–2164. Campbell, J. E. (2018). Polarized: Making sense of a divided America. Princeton University Press. Carothers, T. and O’Donohue, A. (2019). Democracies divided: The global challenge of political polarization. Brookings Institution Press. Chiang, C.-F. and Knight, B. G. (2011). Media Bias and Influence: Evidence from Newspaper Endorsements. Review of Economic Studies, 78(3):795–820. DellaVigna, S., Enikolopov, R., Mironova, V., Petrova, M., and Zhuravskaya, E. (2014). Cross-Border Media and Nationalism: Evidence from Serbian Radio in Croatia. American Economic Journal: Applied Economics, 6(3):103–32. DellaVigna, S. and Kaplan, E. (2007). The Fox News Effect: Media Bias and Voting. The Quarterly Journal of Economics, 122(3):1187–1234. Denny, M. J. and Spirling, A. (2018). Text Preprocessing for Unsupervised Learning: Why it Matters, When It Misleads, and What To Do About It. Political Analysis, 26(2):168–189. Djourelova, M. (2023). Persuasion Through Slanted Language: Evidence from the Media Coverage of Immigration. American Economic Review. Djourelova, M., Durante, R., and Martin, G. (2021). The Impact of Online Competition on Local Newspapers: Evidence from the Introduction of Craigslist. Cepr discussion paper no. dp16130, Centre for Economic Policy Research. Drago, F., Nannicini, T., and Sobbrio, F. (2014). Meet the Press: How Voters and Politicians Respond to Newspaper Entry and Exit. American Economic Journal: Applied Economics, 6(3):159–88. Enikolopov, R., Petrova, M., and Zhuravskaya, E. (2011). Media and Political Persuasion: Evidence from Russia. American Economic Review, 101(7):3253–3285. Evans, D. S. (2009). The Online Advertising Industry: Economics, Evolution, and Privacy. Journal of Economic Perspectives, 23(3):37–60. Gentzkow, M., Kelly, B., and Taddy, M. (2019a). Text as Data. Journal of Economic Literature, 57(3):535–74. Gentzkow, M. and Shapiro, J. M. (2010). What Drives Media Slant? Evidence from US Daily Newspapers. Econometrica, 78(1):35–71. Gentzkow, M., Shapiro, J. M., and Sinkinson, M. (2011). The Effect of Newspaper Entry and Exit on Electoral Politics. American Economic Review, 101(7):2980–3018. Gentzkow, M., Shapiro, J. M., and Sinkinson, M. (2014). Competition and Ideological Diversity: Historical Evidence from U.S. Newspapers. American Economic Review, 104(10):3073–3114. Gentzkow, M., Shapiro, J. M., and Stone, D. F. (2015). Media Bias in the Marketplace: Theory. In Anderson, S. P., Waldfogel, J., and Stroemberg, D., editors, Handbook of Media Economics, volume 1, pages 623–645. North-Holland. Gentzkow, M., Shapiro, J. M., and Taddy, M. (2019b). Measuring Group Differences in High-Dimensional Choices: Method and Application to Congressional Speech. Econometrica, 87(4):1307–1340. George, L. M. and Waldfogel, J. (2006). The New York Times and the Market for Local Newspapers. American Economic Review, 96(1):435–447. Gilens, M. and Hertzman, C. (2000). Corporate Ownership and News Bias: Newspaper Coverage of the 1996 Telecommunications Act. Journal of Politics, 62(2):369–386. Groseclose, T. and Milyo, J. (2005). A Measure of Media Bias. Quarterly Journal of Economics, 120(4):1191 – 1238. Hansen, S., McMahon, M., and Prat, A. (2018). Transparency and Deliberation within the FOMC: a Computational Linguistics Approach. The Quarterly Journal of Economics, 133(2):801–870. Harmon, M. and Muenchen, R. (2009). Semantic Framing in the Build-up to the Iraq War: Fox v. CNN and other U.S. Broadcast News Programs. ETC: A Review of General Semantics, 66(1):12–26. Hastie, T., Tibshirani, R., and Friedman, J. (2009). The Elements of Statistical Larning. Springer, New York, NY. Hatte, S., Madinier, E., and Zhuravskaya, E. (2021). Reading Twitter in the Newsroom: How Social Media Affects Traditional-Media Reporting of Conflicts. Technical report, SSRN. Hoffman, M., Bach, F. R., and Blei, D. M. (2010). Online Learning for Latent Dirichlet Allocation. In Advances in Neural Information Processing Systems, pages 856–864. Hopkins, D. J. and Ladd, J. M. (2014). The Consequences of Broader Media Choice: Evidence from the Expansion of Fox News. Quarterly Journal of Political Science, 9(1):115–135. Kleinberg, J., Lakkaraju, H., Leskovec, J., Ludwig, J., and Mullainathan, S. (2017). Human decisions and machine predictions. The Quarterly Journal of Economics, 133(1):237–293. Li, Z. and Martin, G. J. (2022). Media and Ideological Movements: How Fox News Built the Tea Party. Technical report, Working Paper. Martin, G. J. and McCrain, J. (2019). Local News and National Politics. American Political Science Review, 113(2):372–384. Martin, G. J. and Yurukoglu, A. (2017). Bias in Cable News: Persuasion and Polarization. American Economic Review, 107(9):2565–2599. Mastrorocco, N. and Ornaghi, A. (2020). Who Watches the Watchmen? Local News and Police Behaviour in the United States. Technical report, Trinity Economics Papers. Mullainathan, S. and Shleifer, A. (2005). The Market for News. American Economic Review, 95(4):1031–1053. Osnabrügge, M., Ash, E., and Morelli, M. (2021). Cross-Domain Topic Classification for Political Texts. Political Analysis. Peterson, A. and Spirling, A. (2018). Classification Accuracy as a Substantive Quantity of Interest: Measuring Polarization in Westminster Systems. Political Analysis, forthcoming. Prat, A. (2018). Media Power. Journal of Political Economy, 126(4):1747 – 1783. Prat, A. and Stroemberg, D. (2013). The Political Economy of Mass Media, volume 2 of Econometric Society Monographs, page 135–187. Cambridge University Press, Cambridge, UK. Puglisi, R. and Snyder, J. M. (2011). Newspaper Coverage of Political Scandals. The journal of politics, 73(3):931–950. Puglisi, R. and Snyder, J. M. (2015). Empirical Studies of Media Bias. In Anderson, S. P., Waldfogel, J., and Stroemberg, D., editors, Handbook of Media Economics, volume 1, pages 647–667. North-Holland. Rolnik, G., Cagé, J., Gans, J., Goodman, E., Knight, B., Prat, A., Schiffrin, A., and Raj, P. (2019). Protecting Journalism in the Age of Digital Platforms. Committee for the Study of Digital Platforms Media Subcommittee. Chicago: Stigler Center for the Study of the Economy and the State. University of Chicago Booth School of Business. Schroeder, E. and Stone, D. F. (2015). Fox News and Political Knowledge. Journal of Public Economics, 126:52–63. Simonov, A., Sacher, S., Dube, J.-P., and Biswas, S. (2022). Frontiers: The Persuasive Effect of Fox News: Noncompliance with Social Distancing During the COVID-19 Pandemic. Marketing Science, 41(2):230–242. Snyder, J. M. and Strömberg, D. (2010). Press Coverage and Political Accountability. Journal of Political Economy, 118(2):355–408. Stroemberg, D. (2015). Media and Politics. Annual Review of Economics, 7:173–205. Szeidl, A. and Szucs, F. (2021). Media Capture through Favor Exchange. Econometrica, 89:281–310. Yanagizawa-Drott, D. (2014). Propaganda and Conflict: Evidence from the Rwandan Genocide. The Quarterly Journal of Economics, 129(4):1947–1994. This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv Authors: (1) Philine Widmer, ETH Zürich and philine.widmer@gess.ethz.ch; (2) Sergio Galletta, ETH Zürich and sergio.galletta@gess.ethz.ch; (3) Elliott Ash, ETH Zürich and ashe@ethz.ch. Authors: Authors: (1) Philine Widmer, ETH Zürich and philine.widmer@gess.ethz.ch; (2) Sergio Galletta, ETH Zürich and sergio.galletta@gess.ethz.ch; (3) Elliott Ash, ETH Zürich and ashe@ethz.ch.