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  • Martin Fridson, CFA

Beware of Media's Negative Bias

A client recently brought our attention to a newspaper article with this alarming headline:

Next Crash Will Be ‘Worse Than the Great Depression’: Experts.” [1]

A bleak forecast indeed! At the low point in the 1930s, U.S. unemployment exceeded 20%. To put that figure into context, the peak unemployment rate during the severe recession of 2008-2009 was 10%.

What are investors to make of such a claim? How worried should they be?

The key to knowing how seriously to take an article of this sort is to understand how the financial press works. Reporters get rewarded for stories that generate buzz. Buzz is measurable nowadays by counting the number of hits that an article’s online version receives.

This system creates a strong incentive for financial journalists to accentuate the negative. Research by psychologists Daniel Kahneman and Amos Tversky has shown that investors exhibit risk aversion. They get more riled up by a loss than by missing a gain of the same magnitude. Journalists recognize this trait and observe that bearish article push more hot buttons than bullish ones. The preference for negative stories among news editors—on the business page and elsewhere—is expressed by the adage, “If it bleeds it leads.” Another factor that probably contributes to financial journalists’ negative bias is the knowledge that they will face greater criticism for encouraging readers to take a risk that turns out badly than they will for warning them away from risk-taking that pays off in spades. [2]

Overemphasis of bad news is not just a subjective impression held by marketers of financial products who would like press coverage to be bullish at all times. In 2017 Diego García of the University of Colorado at Boulder presented a conference paper that documented that journalists are more negative about market declines than they are about market rises. Garcia studied word choice in market reports in the New York Times and the Wall Street Journal from 1905 to 2005. He found that negative returns have a much bigger impact on the language in the articles than positive returns. For articles written a few days after the market moves, only negative moves influence media content.

Against this backdrop, let us consider the headline, “Next Crash Will Be ‘Worse Than the Great Depression’: Experts.” On the face of it, that means all experts think the next crash will be worse than the Great Depression. In reality, the article quotes a total of two experts. Hundreds of economists of comparable or greater stature predict no such thing.

As with any group of people attempting to scope out the future, a wide range of opinions exists among economic forecasters. The best short answer to the question, “How bad do economists think the next recession will be?” is the median forecast, possibly supplemented by some information regarding the opinions of those who are significantly more optimistic or pessimistic. Cherry-picking the two most dire forecasts out of dozens or hundreds presents a distorted picture of “what economists think.” But it generates a lot more buzz than a story headlined, “Economists Expect a Recession of Approximately Average Severity.”

Let’s consider the two experts that the New York Postarticle cites. The credentials of Peter Schiff, who explicitly predicts another Great Depression, don’t include a Ph.D. in economics. They don’t even include an undergraduate degree in the field. He received a B.S. with a double major in finance and accounting from University of California, Berkeley. Schiff then worked as a stockbroker. The stockbrokers I know are good at what they do and very personable, but I wouldn’t rely on them to forecast the economy.

It’s true that having formal training in economics is no guarantee of forecasting accuracy. Having no such training doesn’t improve your chances, though. Challenging the orthodoxy can be productive, but it depends on what the analyst proposes to put in its place.

Murray Gunn does have a masters degree in economics. But despite being quoted in the Post‘s scary article, he is not predicting a depression. Instead, Gunn predicts “the worst recession we have seen in 10 years.”

I’m not quite sure how to interpret that, since the last recession was essentially 10 years ago. One way to read the quotation is that any recession, even a mild one, will be the worst in 10 years because we haven’t had one for 10 years. In any case, there’s no indication that Gunn expects a decade-long depression in which GDP drops by 30%, it did in the 1930s. (During the Great Recession of a decade ago, by contrast, GDP fell by 4%.) One good reason not to expect a catastrophe comparable to the Great Depression is that the U.S. economy is much less concentrated in manufacturing than it was 80 years ago. Layoffs tend to be less drastic in today’s more service-oriented economy.

Let’s not minimize the problems of debt that the New York Postarticle recounts. But the reason that the last slump became the Great Recession, rather than a run-of-the-mill economic contraction, was that the banking system came close to collapse. Recessions wind up being especially harsh if they are preceded by financial crises. If economists were polled on the subject, a substantial majority would likely say that the regulatory reforms instituted in response to the Global Financial Crisis of 2007-2008 have greatly reduced the risk of a repeat. Banks must now hold more capital than formerly, making them better equipped to withstand the loan losses that inevitably accompany a cyclical downturn.

In conclusion, keeping a level head is essential to success in the financial markets. Unfortunately, some pundits encourage precisely the opposite approach with wildly bullish or cataclysmically bearish predictions. Their bombast gives newspapers more interesting copy than more sober—even if better supported—opinions. Investors need to be aware of this dynamic and avoid falling prey to the emotions that overheated punditry and reporting are designed to whip up.

[2] For a financial journalist’s view of the causes of negative bias, see

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