Chapter 7
Causality and Constellations
The goal of this book is to improve people’s ability to anticipate and deal with
major economic events, such as depressions, recessions, or secular (that is, long-
term) stagnation, by encouraging them to identify and incorporate into their
thinking the economic narratives that help to define these events. Before we can
forecast reliably, we need some understanding of these events’ true ultimate
causes. The key problem is determining what is a cause versus what is a
consequence.
Though modern economists tend to be very attentive to causality, as a general
rule they do not attach any causal significance to the invention of new narratives.
I want to argue here not only that causality exists, but also that it goes both ways:
new contagious narratives cause economic events, and economic events cause
changed narratives.
Of course, almost nothing beyond spots on the sun is purely an outside
influence on the economy (more on sunspots later in the chapter), but we can
think of new narratives as causative innovations, because each narrative
originates in the mind of a single individual (or as a collaboration among a few
people). Economic historian Joel Mokyr (2016) calls such an individual a
“cultural entrepreneur,” and he traces the concept back to philosopher and
polymath David Hume, who wrote in 1742:
What depends on a few persons is, in great measure, to be ascribed to chance,
or secret and unknown causes; what arises from a great number may often be
accounted for by determinate and known causes.1
Understanding the effects of the “few persons” who create contagious new
narratives is essential to formulating the foundations of a theory of narrative
economics.
The effects of a “few persons” sometimes work through the creation of
contagious new narratives. Though narratives are commonly connected with
celebrities, the “few persons” who invent a contagious narrative are usually not

famous, and often we will never know who they were. Later on, we can look for
celebrities attached to them, but we will usually not find their authors.
In this chapter we will consider the causal elements that make economic
narratives go viral—especially stories and storytelling—with the aim of
developing a better understanding of these narratives’ deep structure.

Direction of Causality
It is not easy to prove direction of causality between a narrative and the
economy. For example, did the stories of successful speculators and wild
enthusiasm for stocks that characterized the 1920s cause increased stock prices
and increased corporate earnings? Or did those increased earnings cause the
enthusiasm? Was the similar enthusiasm for Bitcoin after 2009 in any way
responsible for the increase in Bitcoin’s price? Or was Bitcoin’s increased value
just a logical reaction to news stories and new progress in the mathematical
theory of cryptography?
A problem in establishing direction of causality for major economic events is
that economists usually cannot run controlled experiments that accurately
simulate economic conditions at large. In contrast, laboratory scientists conduct
random trials, perhaps by administering a test drug to an experimental group and
a placebo to a control group, and then using statistical analysis to determine
whether the drug really causes patients to recover. The best economists can often
do is to look for events that might be deemed natural experiments. Henry W.
Farnam, in his 1912 presidential address before the American Economic
Association, addressed economists’ inability to conduct controlled experiments,
asserting nonetheless that the study of economic history can allow economists to
infer causality because random shocks have occurred through history, as when
governments embark on crazy economic policies. In fact, Farnam said, “The
economist is really fortunate in having experiments tried for him without
expense.”2
In their 1963 Monetary History of the United States, Milton Friedman and
Anna J. Schwartz gave three examples of what they called “quasi-controlled
experiments” to establish causal impact from monetary policy to the aggregate
economy: the large gold discoveries of 1897 to 1914, which expanded the money
supply, and the periods during and immediately after World War I and World
War II. We can debate whether these events were truly random exogenous
shocks (that is, not caused by the economy), but much more discussion on
inferring direction of causality with economic data has taken place since 1963.
The general conclusion is that it is indeed possible to infer causality even when
controlled experiments are impossible. New narratives might be interpreted as
exogenous, helping us identify additional quasi-controlled experiments. In fact,