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Media proliferation and partisan selective exposure

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Abstract

The number of Internet news media outlets has skyrocketed in recent years. We analyze the effects of media proliferation on electoral outcomes assuming voters may choose news that is too partisan, from an informational perspective, i.e., engage in partisan selective exposure. We find that if voters who prefer highly partisan news—either because they are truly ideologically extreme, or due to a tendency towards excessive selective exposure—are politically “important,” then proliferation is socially beneficial, as it makes these voters more likely to obtain informative news. Otherwise, proliferation still protects against very poor electoral outcomes that can occur when the number of outlets is small and the only media options are highly partisan. Our model’s overall implication is thus that, surprisingly, proliferation is socially beneficial regardless of the degree of selective exposure.

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Notes

  1. See Massing (2009) for a nice discussion of the decline of the traditional newspaper industry and growth of Internet news media outlets.

  2. Seventeen distinct websites were “most frequented” by at least two percent of readers of online news in 2008 (Pew Research Center 2008), and according to Drezner and Farrell (2008) there were an estimated 70 million blogs worldwide in May 2007. Although the majority are likely personal and not focused on news, there probably are thousands that mainly discuss politics. Baum and Groeling (2008) summarize evidence showing that blogs are more partisan than traditional news sources.

  3. See Iyengar and Hahn (2009) and Garrett (2009) for recent studies, both of which include fairly extensive literature reviews. Actually, even the introduction of Downs acknowledges the limitations of the rational choice assumption in the context of political analysis.

  4. See, e.g., Sunstein (2001), Drezner and Farrell (2008), Pariser (2011), or Obama (2010), who says, “Whereas most Americans used to get their news from the same three networks over dinner, or a few influential papers on Sunday morning, we now have the option to get our information from any number of blogs or websites or cable news shows. And this can have both a good and bad development for democracy.”

  5. It is also worth noting our assumption is consistent with the results of DellaVigna and Kaplan (2007), who discuss how voters may be unduly influenced by partisan media due to what they call “nonrational persuasion.”

  6. In addition to the studies cited above, see, e.g., Mutz and Martin (2001), Stroud (2008), Nie et al. (2010) and Gentzkow and Shapiro (2011). A related, but distinct, literature studies how changes in media technology may enable people to avoid political news altogether; see, e.g., Baum and Kernell (1999) and Prior (2005).

  7. Contributions include Strömberg (2004), Besley and Prat (2006), Andina-Díaz (2007), Bernhardt et al. (2008), Gasper (2009), Kendall (2010) and Duggan and Martinelli (2011). Bernhardt et al. study markets with many firms but do not focus on the welfare effects of the number of firms increasing. Other formal models of media markets that do not analyze political outcomes include Mullainathan and Shleifer (2005) and Gentzkow and Shapiro (2006).

  8. The framework of Nie et al. (2010) is very similar, but not formalized, and does not directly address electoral outcomes. Anand et al. (2007) consider a two-stage entry game that is similar to ours. Nagler (2007) analyzes Internet media assuming consumers face cognitive costs that increase with the size of the choice set, causing them to choose well known brands as the number of media alternatives grows. Neither of these papers analyze the electoral consequences of media proliferation.

  9. These papers focus on the role of media in providing incentives for government officials to take socially optimal actions, and the importance of the media’s independence from government for this role to be served.

  10. The prediction that extreme voters are more likely to get news when the media choice set expands is (admittedly somewhat loosely) consistent with the work of Nie et al. (2010), who find that people who consume Internet news are relatively ideologically extreme. Nie et al. also find that Internet media consumers are more likely to be interested in niche issues, behavior that our model does not take into account. We discuss this further in the concluding remarks.

  11. The intuition for why welfare is potentially very low with two outlets is robust to the number of outlets being generally “small;” the key is that the number of firms is not large enough to guarantee coverage of moderate editorial positions. The proof for this result is only for particular conditions on the model’s primitives, but numerical examples show the idea holds more generally.

  12. To be clear, β i is voter i’s preference after the realization of the shock Δ. β i can be thought of as the sum of a latent variable b i and Δ, in which the distribution of b across voters is F().

  13. It would not affect the welfare analysis if we instead assumed that any voter for whom no news outlet improves his voting decision—i.e., the most extreme voters—gets news or propaganda from the outlet or party whose editorial position is closest to his ideal cutoff.

  14. We assume that if a voter is indifferent between two media options, the voter chooses the more partisan option.

  15. This is a way of formalizing the Downsian idea that rational voters delegate the evaluation of policies to experts with goals similar to their own. The news consumption rule for moderate voters is linear, in the sense of being independent of the value of the particular political preference and whether the closest outlet is located to a voter’s right or left, due to the linearity of the utility function.

  16. We write \(\tilde{x}\) to denote the voters’ misperception of the variable x in general, so \(\tilde{x}=\rho x +(1-\rho)/2\).

  17. This assumption might seem more natural if we replaced the parties with extreme media outlets taking editorial positions of 0 or 1. Allowing for these outlets would complicate the equilibrium analysis, but would not affect the welfare results, as these outlets would serve the same purpose as the (uninformative) parties and thus not affect the information received by any voter. Thus our assumption that only parties take extreme positions, and voters misinterpret these positions, does not compromise the generality of the general welfare analysis.

  18. See, e.g., Simon (1987) and Kahneman et al. (1982) for background on satisficing and anchoring, respectively.

  19. Unless the median voter’s outlet is the most conservative outlet that reports l, and the median voter is the most conservative reader of that outlet, at least some voters who are more conservative than the median voter will vote L when the median voter does. Hence, it is a probability-zero event that only a weak majority votes L when the median voter does.

  20. We ignore news firm profits to focus on voter welfare. It would be difficult to compare these outcomes.

  21. Welfare loss is defined as the difference between voter utility with full information (i.e., when the voter observes θ himself or gets news from an outlet with editorial position equal to the voter’s ideal cutoff) and actual voter utility.

  22. See Durante and Knight (2012) for empirical evidence of this type of behavior; they found that when the center-right took control of the Italian government from the center-left, causing the slant of public television to move right, this shift attracted some new right-leaning viewers to public television, while left-leaning viewers defected for other, more leftist media sources.

  23. Given ζ i−1, ζ i is uniquely defined since f(ζ) is increasing when ζ is less than 0.5.

  24. Even if there are multiple equilibria, this one is highly plausible, as firm behavior in it is consistent with the empirical patterns in the new media discussed above (how media were more centrist when costs were higher, and have become more partisan as technology has evolved and the number of outlets has increased). Moreover, while it is important to understand equilibrium media behavior, we again note that many of our welfare analysis results do not depend on media outlets behaving as they do in any particular equilibrium.

  25. It is shown in the formal proof that it is subgame perfect for the entrant to take the original position of the deviating outlet.

  26. We would like to stress that our discussion relates to comparative statics. The results should not be interpreted as implying that as S declines over time existing media outlets will change their editorial positions or that entries always occur at the center during this process. A dynamic analysis of S declining is beyond the scope of this paper.

  27. Strictly speaking, the corollary holds only for almost all S as there is a measure-zero set of S where if \(\theta _{i}^{\ast}=0.5\), then either \(\theta_{i-1}^{\ast}\) or \(\theta _{i+1}^{\ast}\) (but not both) also equals 0.5

  28. The right-hand side includes the term \(\frac{1}{2\delta}\) as this is the density of Δ, but this does not affect the results.

  29. The centrist outlet (if there is one) is equi-distant from its two neighbors.

  30. To be more concrete, consider the case of the median voter having ideal cutoff of 0.5 and getting news from an outlet with position 0.3. Then the voter votes incorrectly only when θ∈[0.3,0.5] and her average utility then is −0.1. Her average utility from voting correctly would have been 0.1. Moreover, the probability of voting incorrectly is only Pr(θ∈[0.3,0.5])=0.2. So WL is only 0.2(0.1−(−0.1))=0.04. (Social) WL could be substantially higher than it is in the figure if ρ and δ were very small, or voters mistakenly chose news sources with politics on the other side of the spectrum from their own ideologies.

  31. Moreover, if voter preferences were bi-modal rather than single-peaked, then relatively extreme outlets would still have incentives to move toward the modes, so they would still locate closer to their moderate neighbors in equilibrium.

  32. The existing readership effects cancel when both outlets become marginally more partisan.

  33. In a previous version of the paper we analyzed a special case (where f is uniform and ρ=4δ) in detail, showing that welfare goes through well-defined cycles, with troughs and peaks that increase only if ρ is sufficiently high, as S goes to zero. Results are available on request.

  34. The fact that welfare in the limit is greater than monopoly welfare when ρ>0.5 actually holds for all δ, but we omit the details explaining this in the interest of brevity.

  35. Bloggers have already contributed to breaking several major news stories, such as the firing of US attorneys by the Bush administration in 2007 and the fact that the TV show 60 Minutes reported forged documents relating to Bush’s national guard service. See Massing (2009) for a good discussion of these issues. Gentzkow and Shapiro (2011) find evidence that vertical differentiation in online news is substantial, as most webpage visits go to large, centrist, presumably higher quality sites, which attract readers who also visit partisan liberal and conservative sites. This is also suggestive of proliferation being beneficial, or at least not harmful.

  36. In this case \(\frac{\partial \mathit{WL}}{\partial \theta_{i}}\) can be shown to equal (ρ/2)(θ i+1θ i−1)(θ i −(θ i+1+θ i−1)/2).

  37. For example, voters with ideal cutoffs of 0.49 and 0.51 should only vote differently 2% of the time. If they choose news from outlets with positions 0.4 and 0.6, due to low ρ, they will vote differently 20% of the time.

References

  • Anand, B., Di Tella, R., & Galetovic, A. (2007). Information or opinion? Media bias as product differentiation. Journal of Economics & Management Strategy, 16(3), 635–682.

    Article  Google Scholar 

  • Andina-Díaz, A. (2007). Reinforcement vs. change: the political influence of the media. Public Choice, 131(1), 65–81.

    Article  Google Scholar 

  • Baum, M. A., & Groeling, T. (2008). New media and the polarization of American political discourse. Political Communication, 25(4), 345–365.

    Article  Google Scholar 

  • Baum, M. A., & Kernell, S. (1999). Has cable ended the golden age of presidential television? The American Political Science Review, 93(1), 99–114.

    Article  Google Scholar 

  • Bernhardt, D., Krasa, S., & Polborn, M. (2008). Political polarization and the electoral effects of media bias. Journal of Public Economics, 92(5–6), 1092–1104.

    Article  Google Scholar 

  • Besley, T., & Prat, A. (2006). Handcuffs for the grabbing hand? Media capture and government accountability. American Economic Review, 96(3), 720–736.

    Article  Google Scholar 

  • Chan, J., & Suen, W. (2008). A spatial theory of news consumption and electoral competition. Review of Economic Studies, 75(3), 699–728.

    Article  Google Scholar 

  • Coyne, C. J., & Leeson, P. T. (2004). Read all about it! Understanding the role of media in economic development. Kyklos, 57(4), 21–44.

    Article  Google Scholar 

  • DellaVigna, S., & Kaplan, E. (2007). The Fox News effect: media bias and voting. The Quarterly Journal of Economics, 122(3), 699–728.

    Article  Google Scholar 

  • Downs, A. (1957). An economic theory of democracy. Reading: Addison-Wesley.

    Google Scholar 

  • Drezner, D. W., & Farrell, H. (2008). Introduction: blogs, politics and power: a special issue of Public Choice. Public Choice, 134(1), 1–13.

    Google Scholar 

  • Duggan, J., & Martinelli, C. (2011). A spatial theory of media slant and voter choice. Review of Economic Studies, 78(2), 640–666.

    Article  Google Scholar 

  • Durante, R., & Knight, B. (2012). Partisan control, media bias, and viewer responses: evidence from Berlusconi’s Italy. Journal of the European Economics Association. doi:10.1111/j.1542-4774.2011.01060.x.

    Google Scholar 

  • Garrett, R. K. (2009). Politically motivated reinforcement seeking: reframing the selective exposure debate. Journal of Communication, 59(4), 676–699.

    Article  Google Scholar 

  • Gasper, J. T. (2009). Reporting for sale: the market for news coverage. Public Choice, 141(3), 493–508.

    Article  Google Scholar 

  • Gentzkow, M., & Shapiro, J. M. (2006). Media bias and reputation. Journal of Political Economy, 114(2), 280–316.

    Article  Google Scholar 

  • Gentzkow, M., & Shapiro, J. M. (2011). Ideological segregation online and offline. The Quarterly Journal of Economics, 126(4), 1799–1839.

    Article  Google Scholar 

  • Iyengar, S., & Hahn, K. S. (2009). Red media, blue media: evidence of ideological selectivity in media use. Journal of Communication, 59(1), 19–39.

    Article  Google Scholar 

  • Kahneman, D., Slovic, P., & Tversky, A. (1982). Judgment under uncertainty: heuristics and biases. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Kendall, T. D. (2010). Strategic political commentary. Public Choice, 142(1), 151–175.

    Article  Google Scholar 

  • Leeson, P. T. (2008). Media freedom, political knowledge, and participation. Journal of Economic Perspectives, 22(2), 155–170.

    Article  Google Scholar 

  • Leeson, P. T., & Coyne, C. J. (2005). Manipulating the media. Institutions and Economic Development, 1(2), 67–92.

    Google Scholar 

  • Massing, M. (2009). The news about the Internet. The New York Review of Books. August 13, 2009.

  • Mullainathan, S., & Shleifer, A. (2005). The market for news. American Economic Review, 95(4), 1031–1053.

    Article  Google Scholar 

  • Munger, M. C. (2008). Blogging and political information: truth or truthiness? Public Choice, 134(1), 125–138.

    Google Scholar 

  • Mutz, D. C., & Martin, P. S. (2001). Facilitating communication across lines of political difference: the role of mass media. The American Political Science Review, 95(1), 97–114.

    Google Scholar 

  • Nagler, M. G. (2007). Understanding the Internet’s relevance to media ownership policy: a model of too many choices? The B. E. Journal of Economic Analysis & Policy (Topics), 7(1). Art. 29.

  • Nie, N. H., Miller, D. W. III, Golde, S., Butler, D. M., & Winneg, K. (2010). The world wide web and the US political news market. American Journal of Political Science, 54(2), 428–439.

    Article  Google Scholar 

  • Obama, B. H. (2010). Remarks by the President at University of Michigan Spring Commencement, May 1, 2010. http://www.whitehouse.gov/the-press-office/remarks-president-university-michigan-spring-commencement.

  • Pariser, E. (2011). The filter bubble: what the Internet is hiding from you. Baltimore: Penguin.

    Google Scholar 

  • Pew Research Center (2008). 2008 Pew Research Center for the people and the press news consumption and believability study.

  • Pew Research Center (2010). A pro-government, socially liberal generation: Democrats’ edge among millennials slips.

  • Prat, A., & Strömberg, D. (2011). The political economy of mass media (Working paper).

  • Prescott, E. C., & Visscher, M. (1977). Sequential location among firms with foresight. The Bell Journal of Economics, 8(2), 378–393.

    Article  Google Scholar 

  • Prior, M. (2005). News vs. entertainment: how increasing media choice widens gaps in political knowledge and turnout. American Journal of Political Science, 49(3), 577–592.

    Article  Google Scholar 

  • Prior, M. (2007). Post-broadcast democracy: how media choice increases inequality in political involvement and polarizes elections. Cambridge: Cambridge University Press.

    Google Scholar 

  • Radcliff, B. (1993). The structure of voter preferences. The Journal of Politics, 55(3), 714–719.

    Article  Google Scholar 

  • Simon, H. A. (1987). Satisficing. In: The new Palgrave: a dictionary of economics (Vol. 4, pp. 243–245). London: Macmillan.

    Google Scholar 

  • Strömberg, D. (2004). Mass media competition, political competition, and public policy. Review of Economic Studies, 71(1), 265–284.

    Article  Google Scholar 

  • Stroud, N. J. (2008). Media use and political predispositions: revisiting the concept of selective exposure. Political Behavior, 30(3), 341–366.

    Article  Google Scholar 

  • Sunstein, C. R. (2001). Republic.com. Princeton: Princeton University Press.

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Acknowledgements

We thank Nathan Larson, Alessandro Lizzeri, Matthew Nagler, Ruben Enikolopov and participants at the 2010 Econometric Society World Congress, 2010 Western Economic Association Conference and numerous seminars for helpful comments. Jimmy Chan acknowledges the support of Shanghai Dongfang Xuezhe Program, 211 Project for the Shanghai University of Finance and Economics, and the Shanghai Leading Academic Discipline Program, Program No. B801.

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Correspondence to Daniel F. Stone.

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Chan, J., Stone, D.F. Media proliferation and partisan selective exposure. Public Choice 156, 467–490 (2013). https://doi.org/10.1007/s11127-012-9928-x

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