Contagion is strongest when people feel a personal tie to an individual in or at
the root of the story, whether a stock personality type or a real celebrity. For
example, the narrative that Donald J. Trump is a tough, brilliant dealmaker and a
self-made billionaire is at the core of an economic narrative that led to his
unlikely election as US president in 2016. Celebrities sometimes concoct their
own narratives, as in the case of Trump, but in many cases the celebrity’s name
is merely added to an older, weaker narrative to increase its contagion—as in the
story of the self-made man told many times over, each time with a different
celebrity. (I discuss many celebrity-based narratives throughout this book.)
Narrative economics demonstrates how popular stories change through time
to affect economic outcomes, including not only recessions and depressions, but
also other important economic phenomena. The idea that house prices can only
go up attaches to the stories of rich house flippers seen on television. The idea
that gold is the safest investment attaches to stories of war and depression. These
narratives have a contagious element, even if their attachment to any given
celebrity is tenuous.
Ultimately, narratives are major vectors of rapid change in culture, in
zeitgeist, and in economic behavior.4 Sometimes, narratives merge with fads and
crazes. Savvy marketers and promoters then amplify them in an attempt to profit
from them.
In addition to popular narratives, there are also professional narratives, shared
among communities of intellectuals, that contain complex ideas that subtly affect
broader social behavior. One such professional narrative, the random walk
theory of speculative prices, holds that prices in the stock market incorporate all
information, thus implying that attempts to beat the market are futile. This
narrative has an element of truth to it, as professional narratives generally do,
though there is now a professional literature that finds imperfections not
predicted by the theory.
Occasionally these professional narratives translate into popular narratives,
but the public often distorts these narratives. For example, one distorted
narrative states that a buy-and-hold strategy in the domestic stock market is the
best investment decision. That narrative conflicts with the professional canon,
despite the popular idea that the buy-and-hold strategy comes from scholarly
research. Like the popular interpretation of the random walk, some distorted
narratives have an economic impact for generations.
As with any kind of historical reconstruction, we cannot go back in time with

a sound recorder to capture the conversations that created and spread the
narratives, so we have to rely on indirect sources. However, we can now capture
the arc of contemporary narratives through social media and other tools, such as
Google Ngrams.

Better Forecasts of Major Future Events
Most contemporary economists tend to think that public narratives are “not our
field.” If you press them, they might suggest you check with other departments
of the university, such as the journalism and sociology departments. But scholars
in these other fields often find it difficult to tread in the land of economic theory,
thus leaving a gap between the study of narratives and their effects on economic
events.
No economist gave a credible forecast of the worldwide nature of the Great
Depression of the 1930s before it happened, and only a handful predicted the
peak of the US housing boom in 2005 or the “Great Recession” and “world
financial crisis” of 2007–9. Some economists in the late 1920s argued that
prosperity would reach new heights in the 1930s, while others argued the
opposite extreme: unemployment would remain high forever, because labor-
saving machinery would permanently replace jobs. But there seems to have been
no public economic forecast of the actual events: a decade of very high
unemployment and then a return to normal.
Traditionally, economists who study data have excelled in creating abstract
theoretical models and in analyzing short-run economic data. They can
accurately forecast macroeconomic changes a couple quarters into the future, but
for the past half century, their one-year forecasts have been on the whole
worthless. When assessing the probability that quarterly US GDP growth will be
negative one year in the future, their predictions have had no relation to actual
subsequent negative growth rates.5 There have been, according to a Fathom
Consulting study, 469 recessions (defined as a decline in a country’s GDP over a
year) in 194 countries forecasted since 1988 by the International Monetary Fund
in its biannual World Economic Outlook. In only 17 of these did they forecast a
recession in the preceding year. They predicted recessions that did not occur 47
times.6
One might think that this forecasting record is good relative to that of weather
forecasting, which is accurate for only a few days. But in economic decisions,
people typically think years ahead. They plan to send children to high school or
college for four years, and take out thirty-year home mortgages. So it is natural
to suppose that we would sometimes know that the next few years will be strong
or weak.