stock market, since 1989. There are parallel surveys in Japan and China. Also,
Karl Case, and now Anne Kinsella Thompson, and I have been doing surveys of
US homebuyers and their perceptions of the market for single-family homes
since 1993. The early surveys received support from the US National Science
Foundation, with later surveys supported by the Whitebox Foundation and the
Yale School of Management. The questionnaires for these surveys include open-
ended questions with space that invites respondents to write a sentence or two.
The questions are designed to stimulate respondents to think about what is
motivating them, so that their responses can be analyzed in perpetuity. Since I
started these survey projects, I have seen other survey organizations pursue
sometimes similar objectives, and then stop. New survey tools like
SurveyMonkey and Qualtrics are encouraging a proliferation of surveys but not
a consistent strategy that is pursued over long periods of time.
As of this writing, there does not appear to be much support for the routine
collection of historical data in a form that will allow, decades hence, a truly
comprehensive study of the dynamics of economic narratives.

Tracking and Quantifying Narratives
Research today needs improvement in terms of tracking and quantifying
narratives. Researchers have trouble dealing with a set of often-conflicting
narratives with gradations and overlaps. Even the simplest epidemic model
shows that no narrative reaches everyone. In addition, the spread of a particular
narrative may be largely random. The meanings of words depend on context and
change through time. A story’s real meaning, which accounts for its virality, may
also change through time and is hard to track in the long run.
There is also the perpetual challenge of distinguishing between causation and
correlation. How do we distinguish between narratives that are associated with
economic behavior just because they are reporting on the behavior, and
narratives that create changes in economic behavior?22
Economic researchers have to grapple with the same issues that have troubled
literary theorists who try to list the basic stories in all of literature, who attempt
to distill what defines these stories and makes them contagious (see chapter 2).
At any time in history there are many contagious stories, and it is hard to sort
through them. Literary scholars run the risk of focusing on details of the stories
that are common just because the events are familiar in everyday life. They also
face the difficulty of accounting for changes through time in the list of stories.
Fortunately, research in semantic information and semiotics is advancing. For
example, machine translation allows a computer to select the meaning of a word
by looking at context, at adjacent words. The user asks, “What is the longest
river in South Africa?” and Siri provides a direct verbal answer (“The longest
river in South Africa is the Orange River”). Such search is now becoming well
established around the world.
However, semantic search may take a long time to reach the human mind’s
abilities to understand narratives. In the meantime, researchers can still quantify
the study of narratives by using multiple research assistants who receive explicit
instructions to read narratives and to classify and quantify them according to
their essential emotional driving force. Advances in psychology, neuroscience,
and artificial intelligence will also improve our sense of structure in narrative
economics. Companies like alexability. com (Alexandria), alpha-sense. com,
prattle.co, and quid. com are beginning to offer intelligent searches of public
documents and the media that could help organize information about shared

narratives.
As research methods advance, and as more social media data accumulate,
textual analysis will become a stronger force in economics. It may allow us to
move beyond 1930s-style models of income-consumption feedback and
Keynesian multipliers that are still influential today and get closer to all the
kinds of feedback that drive economic events. It will also help us better
understand the deliberate manipulations and deceptions we have experienced,
and it will help us formulate economic policies that take narratives into account.
We should be looking forward to better understanding the patterns of human
thinking about the forces that cause economies to boom at times and to stagnate
at others, to go through creative times and backward times, to go through phases
of compassion and phases of conspicuous consumption and self-promotion, to
experience periods of rapid progress and periods of regression. I hope this book
confirms the possibility of real progress in getting closer to the human reality
behind major economic events without sacrificing our commitment to sound
scholarship and systematic analysis.

Appendix: Applying Epidemic Models to Economic Narratives
Epidemiology, a subfield of medicine, developed most productively in the
twentieth century. Its greatest contribution, a mathematical theory of disease
epidemics, sheds powerful light on idea epidemics as they influence economic
events. We can adapt this theory to model the spread of economic narratives.