The supply side of media bias

In my ECONS102 class, we cover economic explanations for media bias. Drawing on past research from Matthew Gentzkow and others, we demonstrate that there are demand-side explanations (media bias arises because of a bias in the preferences of the news-consuming public) and supply-side explanations (media bias arises because media firms segment the market, and focus on different segments). I even shared my teaching approach in this article published in the Journal of Economic Education in 2023 (ungated earlier version here).

I'm always on the lookout for more research in this space, which can add to our understanding (and potentially flesh out more details for my teaching of media bias). One example is this 2024 working paper by Tin Cheuk Leung and Koleman Strumpf (both Wake Forest University). They focus on the supply side of the media market, and their method:

...evaluates the factors which shape article duration on a newspaper’s digital homepage. Homepage articles have a privileged position, as it is the starting point for most readers which in turn drives views and shares of the featured articles. One of the most important editorial decisions is selecting how long each article remains at this prized location. After adjusting for demand-side effects using reader engagement data, we use prolonged homepage presence of ideologically slanted articles as indicative of supply-side biases.

Leung and Strumpf focus on articles in the New York Times (a more liberal media outlet) and the Wall Street Journal (a more conservative media outlet), using data from August 2021 to May 2023 for the NYT, and from October 2022 to May 2023 for the WSJ. They also look at data from Twitter (about 22 million tweets for the NYT sample, and about 2 million tweets for the WSJ sample). First, they use textual analysis to determine the sentiment and political leaning of each article from each of the media outlets. From this, they find:

...a liberal bias in NYT articles, with an average pro-Democrat score of 0.6 (where 1 represents full pro-Democrat alignment and 0 indicates complete pro-Republican alignment), while WSJ articles exhibited more neutrality, with an average score of 0.5.

Next, Leung and Strumpf look an article's presence on the homepage of each media outlet, and how that relates to tweet count (as a proxy measure of the article's popularity). Specifically, they evaluate:

...the causal impact of homepage presence on tweet count, using time-of-day homepage updating patterns as an instrumental variable... There are distinctive hours of the day in which there are large purges of homepage content, likely associated with editor shift changes. These hours occur throughout the day and so are unrelated to article newsworthiness though they do shape which articles are on the homepage. After instrumenting we find that tweet counts for articles increased significantly when featured on the homepage (35% increase for NYT articles and 162% for WSJ articles).

Unsurprisingly then, articles that appear on the homepage are more popular, receiving far more attention from the public. Next, Leung and Strumpf apply survival models to investigate the factors associated with how long an article remains on the media outlet's homepage. First, unsurprisingly, popularity matters:

A key finding from our analysis is the significant impact of demand-side factors. There is a strong negative relationship between tweet counts at t−1 (a proxy for article popularity) and the hazard rate (the likelihood of an article being removed from the homepage). For the NYT, a one standard deviation increase in log tweets (1.37) leads to 2.5% decrease in the hazard rate. This effect is even more pronounced for WSJ, where a one standard deviation in log tweets (1.09) leads to a 10.0% decrease in the hazard rate. This indicates that more popular articles, as measured by tweet counts, tend to remain on the homepage longer, underscoring the role of reader demand in determining homepage duration.

The 'hazard rate' is the rate at which an article is removed from the homepage. So, a lower hazard rate means that the article remains on the homepage for longer. The demand side (popularity) matters, but the supply side matters as well:

Supply-side factors are particularly influential for the NYT. A one-standard-deviation increase in an article’s pro-Democrat score, indicating its political slant, is associated with a 2% decrease in the hazard rate, which translates into approximately an additional 30 minutes of homepage exposure. This relationship holds across different news tones, suggesting that a wide range of NYT’s editorial decisions on homepage duration are influenced by the article’s political alignment....

For the WSJ, the influence of supply-side factors is generally negligible, both overall and for each news tone. The pro-Democrat scores of articles do not significantly affect their duration on the homepage, contrasting with the NYT, where political slant plays a noticeable role.

So, the NYT's approach to its homepage is affected by the supply side, but the WSJ's approach is not. Leung and Strumpf suggest that:

This suggests that the WSJ might prioritize profit-maximizing objectives over ideological considerations (recall demand-side effects are also larger for the WSJ).

That would be consistent with the models I teach in my ECONS102 class. A profit-maximising media firm should base its' decision about where to locate its content on the liberal-conservative scale based on the relative demand from the news-consuming public, and not at all based on the editorial preferences of the owners or editors. Leung and Strumpf are essentially suggesting that this is true of the WSJ, but not the NYT.

Interestingly though, sentiment matters as well:

The sentiment of an article, captured through abstract sentiment scores, is notably linked to its duration on the homepage. For the NYT, a one standard deviation increase in the abstract sentiment scores is associated with a 2% decrease in the hazard rate, indicating that more positively toned articles are likely to remain on the homepage longer. The effect is even more pronounced for the WSJ, where a similar increase in sentiment scores corresponds to a 4% decrease in the hazard rate.

Whatever happened to 'if it bleeds, it leads'? Since more positively framed news stays on the homepage for longer, that old mantra may be on the way out. Overall, it seems that both demand and supply sides affect which articles receive prominence on the homepage of the NYT, and that for the WSJ it is mostly the demand side. In the latest version of their paper [*], Leung and Strumpf conclude by noting the importance of understanding the supply side of media bias, in an era when local newspapers are closing, increasing the risk of media bias.

[HT: Marginal Revolution, last year]

*****

[*] In the January 2024 version of the paper, which is the one I read some time back, Leung and Strumpf had clearly used ChatGPT (or some other LLM) to write the conclusion, with hilarious results, including a 'rich tapestry', a 'symbiotic relationship', an 'intricate balance', a 'multifaceted realm', 'delving', and a 'deep dive'. Thankfully, the latest version appears to have resolved this issue.

The impact of Fox News on American democracy

In yesterday's post, I noted a number of opportunities for research on the economics of social media. At least one of those opportunities intersected with the impact of traditional media. So, I was interested to read this new article by Elliott Ash, Sergio Galletta, Matteo Pinna (all ETH Zurich), and Christopher Warshaw (George Washington University), published in the Journal of Public Economics (open access). They look at the impact of Fox News Channel on political ideology of voters, and voting outcomes in the US. Given the well-known right-wing nature of Fox News, it is reasonable to wonder whether it is having a political impact.

Identifying the causal impact of a television channel is somewhat challenging, because where viewership is higher that might be because there are more right-leaning voters. So, the causality might run from voters to viewership, rather than the other way around (reverse causality). However, Ash et al. make use of the fact that the channel number assigned to Fox News varies across markets, and that assignment is random (or, at least, it isn't related to the partisanship of the population in a particular television market). So, Ash et al. use channel position as an instrument for viewership (I'll come back to this point later). They then look at the political preferences of voters using data from:

...the 2000 and 2004 National Annenberg Election Survey (NAES) and the 2006–2020 Cooperative Congressional Election Study (CCES) surveys. Overall, we have data on the preferences of approximately 661,000 Americans.

They also look at the effect on presidential and down-ballot (senate, gubernatorial, and house) elections using a variety of election data sources. They find that:

...from 2006–2008 onwards, a lower Fox News Channel (FNC) position correlates with an increase in self-identified Republican viewers, significant at the 10% level initially and 5% in recent years. A one-standard-deviation drop in FNC’s channel position corresponds to a roughly one-percentage point rise in Republican self-identification... A one-standard-deviation decrease in FNC’s channel leads the average American’s ideological position to shift .03-.04 standard deviations to the right in recent years...

Looking across time, the results are not statistically significant (at the 5 percent level) until 2009-2012, or later, depending on the measure. Turning to presidential elections, Ash et al. find that:

Initially, in the 2000 and 2004 elections, FNC’s impact was minimal, likely due to its growing viewership. By 2008, a one-standard-deviation decrease in FNC’s channel position correlated with a 0.32 increase in the Republican vote share...

And on down-ballot elections:

Overall, the effects of FNC in down-ballot elections are qualitatively similar to, though less precise than, those in presidential elections. In House elections, we see a positive (Pro-Republican) coefficient on FNC for Republicans’ two-party vote share in 2012, and it becomes statistically significant starting 2018. Since around 2012, counties with one-standard-deviation lower FNC’s channel position have about .6 to 1.6 percentage point greater shares in Republican vote.

In Senate elections, we find a positive coefficient starting in 2006, which becomes statistically significant starting in 2014.23 Since then, there have been relatively consistent year-to-year effects of around .6 to .73 percentage points. In other words, a one standard deviation shift in FNC’s channel position increases Republican Senate candidates’ vote share by over half a percentage point.

In gubernatorial races, FNC had a small and statistically insignificant effect until the latter half of the 2010s. In recent elections, however, the effect of FNC in gubernatorial races is similar to Senate races — with a Republican vote share about .5 percentage points higher...

So, it is clear from the results that Fox News Channel is driving a rightward shift in the voting public, and this is having a clear effect on both presidential and down-ballot elections. Ash et al. conclude that:

Given the estimated effect sizes on presidential elections, for example, Fox News could have easily tipped the scales for Donald Trump in 2016.

Perhaps Donald Trump should think himself lucky that his 2022 feud with Fox News didn't escalate too much?

However, there is some reason for scepticism about these results. Although Ash et al. make a good case for their use of channel position as an instrument for viewership, it turns out that they didn't actually run a full instrumental variables analysis:

Ideally, we would provide first-stage and two-stage least-squares (2SLS) results for all years in our analysis. However, there are limitations in estimating and interpreting the 2SLS results. First, we only have data on both the endogenous regressor (FNC ratings) and channel positions for 2005, 2006, 2008, and 2020. Second, the first stage provides evidence that the typical variation induced by the channel positioning is somewhat limited, suggesting that the size of the 2SLS coefficients would be, by construction, unreasonable.

...our main analysis focuses on the reduced form, where the outcomes (e.g., vote shares) are regressed directly on the instrument (FNC channel position)...

So, while they have a good instrument, a lack of data prevents them from making the most of it. And so, I think we would need further evidence before we can conclude that these results demonstrate a causal effect of Fox News Channel on political outcomes in the US. It seems to me that the main holdup to doing a full instrumental variables analysis is not having all the viewership data from Nielsen. So perhaps some wealthy research institution needs to buy that data?

Nate Silver on the 'Indigo blob', media and politicians

In my ECONS102 class last week, we covered the economics of information. One aspect of that topic is to look at media bias. So, I was interested to read this post by Nate Silver from last month (which I only caught up to read this week). Silver notes at the start of the post that his core hypothesis is:

In American media and political discourse, there has been a fundamental asymmetry during the Trump Era. Left-progressives, liberals... centrists, and moderate or non-MAGA conservatives all share a common argumentative space. I call this space the Indigo Blob, because it’s somewhere between left-wing (blue) and centrist (purple). The space largely excludes MAGA/right-wing conservatives — around 30 percent... of the country.

The rest of the post is about the causes and consequences of the 'Indigo blob', and I encourage you to read the whole post. However, I want to focus in on this bit:

This graphic from a paper by Magdelena Wojcieszak, et. al. reflects the ideological position of different groups of Twitter users from 2016-2019. There’s a lot going on, so let me show you the figure first and then we can talk our way through it. 

Among politicians on Twitter, we see a traditional bimodal distribution with liberal and conservative peaks corresponding to the Democratic and Republican parties. But everything else is left-skewed. There’s not a clear distinction between left-wing and centrist news organizations — they’re all part of the Indigo Blob — and the right-wing media isn’t terribly well-represented. The same holds for journalists, although the right flank is even more attenuated. And Twitter’s users during this period skewed heavily left too, with liberals outnumbering conservatives roughly 3:1, according to Wojcieszak. Anyone who was active on the platform during this period knew that content satisfying to progressives and Democrats was more likely to be rewarded with likes and retweets.

I believe this contributed to the misestimation of the political preferences of the American public by journalists, Twitter-savvy politicians and others who were active on the platform.

I want to co-opt that figure to go in a slightly different direction, because it highlights two key facts about bias among journalists. These two key facts are well explained by some simple models of media bias. I'm not going to explain those models here, but they are described in this article I published earlier this year in the Journal of Economic Education (ungated earlier version here).

First, notice that the mass of journalists is mostly to the left of the centre. There is an overall bias in the media towards the liberal side of the spectrum (in that there are more media outlets and more journalists on the liberal blue side than on the conservative red side). However, notice that this follows the overall profile of Twitter users, albeit imperfectly. There are more Twitter users on the liberal blue side than on the conservative red side. So, to some extent it is understandable that journalists and media would be biased in this way. It reflects the characteristics of demand from the consumers of media. If there are more liberal media consumers, then there will be more liberal media suppliers.

Second, there is a distribution of media across the spectrum. Some media outlets and journalists lean liberal, and others lean conservative. Collectively, media outlets and journalists cover the range of views, but each media outlet (and to a lesser extent, each journalist) targets a relatively narrow audience within the spectrum. They don't tend to appeal to media consumers with views that are far from their own, because media consumers tend to prefer to consume news that accords with their own views - a behavioural economics concept known as confirmation bias.

The takeaway message from those two facts is that the media are biased. This isn't necessarily something to fear, but it is something to acknowledge and recognise. Possibly we should worry a bit more about the bias in the politicians? [*]

[HT: Marginal Revolution]

*****

[*] Of course, we should note that the population of Twitter users will not necessarily be representative of the population overall. So, perhaps media are biased relative to the population as a whole, and politicians are less biased than the media?

Natural disasters and news media bias

In ECON110, we discuss the economics of news media bias. In discussing bias, I explicitly discuss sensationalism (bias of the exceptional over the ordinary), recency bias (bias of the new over the status quo), and exaggerated influence of minority views (bias by “fair” representation of both sides of the argument). We then go on to discuss how the 'normal' operation of the media market introduces bias into the way news stories are reported. However, we don't really go into much detail on the consequences of new media bias.

A recent 2007 paper by Thomas Eisensee and David Strömberg (both University of Stockholm), published in the Quarterly Journal of Economics (ungated version here), provides an excellent example of the consequences of media coverage. In the paper, Eisensee and Strömberg look at how media coverage of natural disasters outside the U.S. affects the likelihood of disaster relief being given, using a dataset of 5,212 disasters over the period from 1968 to 2002. Specifically, they look at how news coverage of natural disasters is affected by coverage of other news stories (e.g. Olympics coverage), and how that affects whether or not the U.S. declares a natural disaster and provides aid. The news data is based on television evening news stories (ABC, CBS, NBC, and CNN).

They found that:

...2.4 extra minutes spent on the first three news segments (two standard deviations) decrease the probability that a disaster is covered in the news by four percentage points and the probability that the disaster receives relief by three percentage points. Recall that around 10 percent of all disasters are covered in the news and that 20 percent receive relief, and so the effects are sizeable... The estimated coefficients imply that a disaster occurring during the Olympics is 5 percent less likely to be in the news and 6 percent less likely to receive relief, on average.

The effects are especially large for disasters that are "marginally newsworthy" (those that would appear in the news if and only if there was little else happening that was newsworthy). More severe disasters (measured by the number of people killed or 'affected') are both more likely to receive news coverage and more likely to receive relief. However, the effects differ by the type and location of the disaster:

...we have computed the casualties ratio that would make media coverage equally likely, all else equal (controlling for the same factors as in the fixed effects regression). For example, for every person that dies in a volcano disaster, 38,920 people must die of food shortage to receive the same expected media coverage. The conclusion is that media induces extra relief to volcano and earthquake victims, at the expense of victims of epidemics, droughts, cold waves and food shortages...

The estimates suggest that it requires 45 times as many killed in an African disaster to achieve the same probability of media coverage as for a disaster in Europe. We conclude that media coverage induces extra U. S. relief to victims in Europe and on the American continent, at the expense of victims elsewhere.

In the Pacific, it requires 91 times as many killed to achieve the same probability of media coverage as for a disaster in Europe. In ECON110, we conclude that news media bias reflects the underlying bias in the news-consuming public (that prefers to consume news that is consistent with their own preferences and biases). I guess the U.S. news-consuming public cares less about people who die in famines or from natural disasters in the Pacific?

[HT: Marginal Revolution in July this year, but also see the excellent write-up in Our World in Data]

Book Review: Merchants of Doubt

I just finished reading the 2010 book by Naomi Oreskes and Erik M. Conway, Merchants of Doubt. The subtitle is "How a handful of scientists obscured the truth on issues from tobacco smoke to global warming" and is a pretty fair summary of the book. The authors have completed what appears to be a very thorough investigation of several scientists whose names keep appearing as combative opponents against the broad consensus views of scientists. The authors summarise their findings on pages 6-7:

In case after case, Fred Singer, Fred Seitz, and a handful of other scientists joined forces with think tanks and private corporations to challenge scientific evidence on a host of contemporary issues. In the early years, much of the money for this effort came from the tobacco industry; in later years, it came from foundations, think tanks, and the fossil fuel industry. They claimed the link between smoking and cancer remained unproven. They insisted that scientists were mistaken about the risks and limitations of SDI [the Strategic Defense Initiative, or Star Wars]. They argued that acid rain was caused by volcanoes, and so was the ozone hole. They charged that the Environmental Protection Agency had rigged the science surrounding secondhand smoke. Most recently - over the course of nearly two decades and against the face of mounting evidence - they dismissed the reality of global warming. First they claimed there was none, then they claimed it was just natural variation, and then they claimed that even if it was happening and it was our fault, it didn't matter because we could just adapt to it. In case after case, they steadfastly denied the existence of scientific agreement, even though they, themselves, were pretty much the only ones who disagreed.

The way that these scientists managed to get their views, and the appearance of a lack of consensus among scientists, was by exploiting journalistic balance required until the 1949 Fairness Doctrine. Under the doctrine, journalists in the U.S. are required to dedicate airtime or column space to present issues in a balanced manner, such as by presenting both sides of an argument. This sounds good in theory, but when one side of the argument consists of hundreds (or thousands) of scientists and the other side consists of a handful of naysayers, it is hard to see how this doctrine doesn't just reverse the bias in favour of the minority. And it was effective. The authors note (p.32):

...their ability to invoke the Fairness Doctrine to obtain time and space for their views in the mainstream media was crucial to the impact of their efforts.

This allowed these scientists to create doubt in the minds of policy-makers and the public, making it difficult for these groups to assess the veracity of scientific claims (and counterclaims):

"Doubt is our product," ran the infamous memo written by one tobacco industry executive in 1969, "since it is the best means of competing with the 'body of fact' that exists in the minds of the general public". The industry defended its primary product - tobacco - by manufacturing something else: doubt about its harm. (p.34)

The book goes through a narrative that is mostly chronological, with chapters devoted to tobacco from the 1950s to the 1970s, strategic defense (the Star Wars programme in the 1980s), acid rain and the ozone hole in the 1980s and 1990s, secondhand smoke in the 1990s, global warming from the 1990s onwards and the recent (at the time of writing the book) re-opened debate about DDT (a pesticide banned in the 1960s). Oreskes and Conway conclude that:

The link that unites the tobacco industry, conservative think tanks, and the scientists in our story is the defense of the free market.

Throughout our story, the people involved demanded the right to be heard, insisting that we - the public - had the right to hear both sides and that the media had an obligation to present it. They insisted that this was only fair and democratic. But were they attempting to preserve democracy? No. The issue was not free speech; it was free markets. It was the appropriate role of government in monitoring the marketplace. It was regulation. (p.248)

That may well be the case, but I was surprised that the authors singled out Thomas Schelling as one of their bad guys (in the climate change chapter), for identifying the importance of uncertainty in climate projections. And I was even more surprised that they also took issue with William Nordhaus:

What could be done to stop climate change? According to Nordhaus, not much. The most effective action would be to impose a large permanent carbon tax, but that would be hard to implement and enforce. (pp.178-179)

Later on, Oreskes and Conway go on to say:

A handful of economists in the late 1960s had realized that free market economics, focused as it was on consumption growth, was inherently destructive to the natural environment and to the ecosystems on which we all depend. (p.183)

One of those economists? William Nordhaus, though the authors don't note this. [*]

That gripe aside, this book was a really timely read, given the post-truth world we are currently living in, where it seems that even the most robust scientific findings are made to look questionable. If this book had been written now, I wonder if this passage would be even need to be re-written:

With the rise of radio, television, and now the Internet, it sometimes seems that anyone can have their opinion heard, quoted, and repeated, whether it is true or false, sensible or ridiculous, fair-minded or malicious. The Internet has created an information hall of mirrors, where any claim, no matter how preposterous, can be multiplied indefinitely. And on the Internet, disinformation never dies. (p.240)

For some more on this, I recommend this Tim Harford post (which, you will probably note, covers some of the same ground as the Merchants of Doubt book).

Overall, despite the minor gripe about Nordhaus and Schelling, I found this an excellent read. It also makes me think about the current situation in New Zealand with alcohol licensing and local alcohol policies, where the industry has funded some limited research. Food for thought.

*****

[*] This bit made me angry enough that the next book I am reading is Nordhaus's The Climate Casino. You can expect a review of that book in due course.