Angry at Inflation
Out-of-control consumer price inflation has occurred many times throughout history, and the phenomenon has always induced anger. The loss of purchasing power is extremely annoying. But the question is this: At whom should the public direct its anger? Anger narratives about inflation reflect the different circumstances of each inflationary period. By studying these narratives, we can see the effects of inflation and how they change through time.
The most extreme cases of inflation tend to happen during wars. When governments are in trouble, they may not be able to collect taxes fast enough to pay for the war, and in desperation they resort to the printing press for more money. But the stories may not resonate, and the public may not see or understand what is happening. That is, narratives that blame the government for the inflation may not be contagious during a war. Instead, it is more likely that people want to blame someone else. Businesspeople, who are staying home safely while others are fighting, are a natural target of narratives.
In chapter 17, we saw the remarkable epidemic of the word profiteer during and just after World War I. People were very angry that some businesspeople were made rich by the war, and the result was the imposition of an excess profits tax (not only during World War I but also during World War II). Such anger against the people who get rich during wartime is a perennial narrative, not limited to the twentieth century. For example, there was anger during the US Civil War (1861–65) at those who profited from the war, but it wasn’t directed at business tycoons creating inflation to make large profits. The narratives were different. Consider, for example, this sermon by Reverend George Richards of the First Congregational Church of Litchfield, Connecticut, on February 22, 1863:
How, in contrast with the greedy speculators, in office and out of it, who have prowled, like famished wolves, round our fields of carnage—stealing everything they could lay their hands on—robbing the national treasury—purloining from the camp-chest—pilfering from the wounded in the hospitals—appropriating to themselves the little comforts meant for the dying, if not stripping the very dead!15
During the 1917–23 German hyperinflation, the inflation rate was astronomical, and not due to any war. Prices in marks rose on the order of a trillionfold. And yet many people were unable to identify the malefactor who was causing inflation. Irving Fisher, an American economist who visited Germany at the time, found that Germans did not blame their own government, which had been printing money excessively. Fisher wrote:
The Germans thought of commodities as rising and thought of the American gold dollar as rising. They thought we [the United States] had somehow cornered the gold of the world and were charging an outrageous price for it.16
As of this writing, there is some suggestion of resurgence in the strength of labor unions, and of public support for them, in the United States. The wage-price spiral narrative does not seem poised to reappear. Inflation in the United States and other countries seems unusually tame. However, a mutation of the narrative could appear if inflation begins to creep up. The public tends to watch consumer prices closely, because of its constant repetition of purchases. The wage-price spiral narrative, or some variation on that theme, could again create a strong impulse for economic actors to try to get ahead of the inflation game. It could give them newfound zest in this effort by bringing a moral dimension into the mix, a perception of true evil in inflation, personified by certain celebrities or classes of people.
Perennial Narratives: A Summing Up
The list of nine narrative constellations in part III of this book offers a glimpse of the narrative forces that have driven economies into and out of booms and busts. One broad lesson that we may take from this list is the immense complexity of the narrative landscape. No simple index of public opinion, such as the Consumer Confidence Index, summarizes the “strength” of the economy. The various narratives that share the stage at any point have, in a biological analogy, many cellular receptors and signaling molecules. Modern communication means that new and different kinds of epidemics are possible, and economic forecasting requires close attention to many different narratives. Forecasting in the future will require a new attention to data that are becoming available, as we discuss in part IV.
Part IV
Advancing Narrative Economics
Chapter 19
Future Narratives, Future Research
Disease epidemiology has shown us that there will likely be repeats of variants of older epidemics in the future as reservoirs of old epidemics mutate or react to a changed environment to start a new wave of contagion. There will be new forms of influenza and new influenza epidemics. So, too, many of the narratives described in this book will become epidemic again, weaken after years have passed, and then rise more. The timing is unpredictable; unlike the hypothesized business “cycles,” narratives don’t recur at regular time intervals.
The studies in this book reveal powerful economic narratives of the past that are mostly inactive and sometimes largely forgotten today. However, they are not completely forgotten, and someone seeking a powerful story may rediscover them. The constellations may change, providing new context for, and thereby increasing the contagion rate of, an old narrative and developing the idea into a major epidemic, sometimes after a long time lag.
In this book, I have made unusually heavy use of paragraph-length quotes. I did so to give readers a historical sense of a past narrative that made an impact and might make an impact again if it is repeated in the same words. As with jokes or songs, to be effective a narrative has to be worded and delivered just right.
When it comes to predicting economic events, one becomes painfully aware that there is no exact science to understanding the impact of narratives on the economy. But there can be exact research methods that contribute to such an understanding. There is no exact science about how to evaluate novels or symphonies either, but there are exact methods that may provide information that contributes inspiration to those who involve themselves with such things. We have to avoid the “seductive allure” of superficial arguments about the economy using scientific analogies to lend a sense of precision to a theory that in fact may be of little substance.1 We need to keep the true scientific method in mind even when trying to use an essentially humanistic approach.
Let us proceed with some suggestions from the analysis in this book about future economic narratives, and how we can in the future direct research that allows a better, if inevitably imperfect, understanding of them.
Altered Forms and Circumstances
The perception from time to time of “economic strength” is driven by narratives, notably an other-people’s-confidence narrative (discussed in chapter 10) that is for those times outcompeting other, less optimistic narratives. All narratives have their own internal dynamics, and this “strength” may well be ephemeral. With the Great Recession of 2007–9, we saw a rapid drop in confidence and return of a 1929 stock market crash narrative (chapter 16). The same could happen swiftly again as a result of a small mutation in the narratives or change in circumstances.
The keep-up-with-the-Joneses narrative (discussed in chapter 11) seems especially strong at this writing in the United States. President Donald J. Trump models ostentatious living. In addition, there appears to be less generosity toward hungry families. There had been a distinct downtrend in US charitable giving for basic needs even before Trump’s presidency. Research at the Indiana University Lilly Family School of Philanthropy reveals a 29% decline in real, inflation-corrected, basic-needs charity from 2001 to 2014.2 These declines in the modesty and compassion narratives extend to a lower willingness to help the world’s emerging countries.
The intelligent machines narratives (chapters 13 and 14) are still much talked about, though they do not seem to have much economic impact at the moment. Machines do not seem to be very scary at the time of this writing, but should there be some adverse news about income inequality or unemployment, the contagion of scary forms of this narra
tive could reappear. A sudden increase in concerns about robots has happened before. A search on ProQuest News & Newspapers for articles containing both robot and jobs reveals that the number of articles almost tripled between the last six months of 2007 and the first six months of 2009. According to the National Bureau of Economic Research, December 2007 was the peak month before the Great Recession, and the recession ended in June 2009.
New Technology Will Change Contagion Rates and Recovery Rates
Notable changes in information technology, with changes in contagion rates and recovery rates, have occurred over the course of history. The early invention of printed books in China, the invention of Gutenberg’s printing press in the fifteenth century, the invention of newspapers in Europe in the seventeenth century, the invention of the telegraph and telephone in the nineteenth century, the invention of radio and television in the twentieth, and the rise of the Internet and social media have all fundamentally altered the nature of contagion, but to date there has been no systematic quantitative study of these inventions’ impact on contagion.
Social media and search engines have the potential to alter the fundamentals of contagion. In the past, ideas spread in a random, non-systematic way. Social media platforms make it possible for like-minded people with extremist views to find each other and further reinforce their unusual beliefs. Contagion is not slowed down by fact-checkers. In contrast, the Internet and social media allow ideas to be spread with central control that is nonetheless poorly visible. Designers of social media and search engines have the ability to alter the nature of contagion, and society is increasingly demanding that they do so to prevent devious use of the Internet and the spread of fake news.
But changing communications technology isn’t the only factor that can influence contagion rates. It isn’t always even the biggest factor.
Cultural factors are also at work. History has shown changes in face-to-face spoken word use that likely affect the nature of contagion. For example, in the 1800s, literature would be read aloud in the salon and in the family circle, fashions that were especially prominent in the middle of the nineteenth century. Both the salon and the family circle reading began to fade at the turn of the century, as the Washington Post noted in 1899:
Reading aloud to the children and in the family circle—how fast it is becoming one of the lost arts. What multitudes of children of former days were entertained, and instructed, by this practice, and how few there are who are so entertained and instructed nowadays. Children now, after being taught to read, join that great army which takes in the printed word, swiftly and silently. Most parents, doubtless, are too busy to spare time to educate their sons and daughters by reading to them, and as the children grow older they find their hours too crowded to devote any of them simply to listening. “What is the use” they would say, if asked. “Tastes differ, and we can read what we want in a fraction of the time that would be consumed if we had to sit still and hear it.3
However, as the salon and family circle faded, magazine clubs and book clubs took off into the twentieth century.
Another cultural factor altering the spread of narratives has been an international movement toward providing mentors for young people, with roots back to the Big Brothers (now Big Brothers and Big Sisters) movement starting in 1904, and later diversifying into an epidemic of sorts since around 1980. Having regular communications with successful or socially committed people helps a young person gain a sense of identity in the mentor’s life stories, or in stories that the mentor tells of others in the same circle.4 Mentoring groups are especially effective for women and minorities who may have felt little ownership of such stories.5
Two new phrases, influencer marketing (since 2015) and social media marketing (since 2009), have been gaining popularity. Marketing firms, notably shareablee. com and hawkemedia. com, offer influencer marketing, systematically finding influential people who allow marketing to them or with them via social media. Such sites should increase contagion rates for promoted stories and ideas.
Even as information technology is affecting the transmission of economic narratives that affect the human mind, it could conceivably go further and replace some of the ultimate decision-making process that individuals use. For example, we already have robo-advisers that offer advice on how much to consume and save and how much to put into the stock market versus other investments. The first robo-adviser was launched in 1996 with William Sharpe’s Financial Engines. Since then, automated advisers such as Schwab Intelligent Portfolios, Betterment, and Wealthfront have proliferated. There are other efforts to automate economic decisions too, such as target date funds, first attracting interest around 2007, that automatically rebalance a long-term investor’s portfolio based on a target retirement date. There are many other applications of algorithmic trading. Nonetheless, today, people write the programs and make the ultimate foundational decisions. Someday people may defer massively to machines for life decisions, in which case economic processes may be fundamentally altered. But that day appears likely still to be far-off.
Modeling technology’s effects on communications will be easier to trace when there is better science behind the spread of economic narratives. Already, our models show that it is not easy to predict these narratives and their effects. For example, the epidemic’s ultimate size may not change when an increase in the contagion parameter is matched by a corresponding change in the recovery parameter. Rather, the epidemic will just happen faster. We must integrate formal models of contagion into economic models to begin to understand the impact of such technology.
The Future of Research in Narrative Economics
It is very important, if we are ever to have a substantial understanding of the kinds of big economic events that have surprised us so often in the past, that we have some scientific methods of studying the narrative element of these, even if the science is not complete and still involves some human judgment. Otherwise the field will be left to prognosticators or prophets who give the whole enterprise a bad name.
Economic research has not emphasized the stories that people tell to one another and to themselves about their economic lives. The research misses any discernible meaning that appears in the form of narratives. By missing the popular narratives, it also misses possibly valid explanations of major economic changes.
If one searches newspapers of the twentieth century for contemporary explanations of recessions as they begin, one finds that most talk concerns leading indicators rather than ultimate causes. For example, economists tend to bring up central bank policy, or confidence indexes, or the level of unsold inventories. But if asked what caused the changes in these leading indicators, they are typically silent. It is usually changing narratives that account for these changes, but there is no professional consensus regarding the most impactful narratives through time. Economists are reluctant to bring up popular narratives that they have heard that seem important and relevant to forecasts, since their only source about the narratives is hearsay, friends’ or neighbors’ talk. They usually have no way of knowing whether similar narratives were extant in past economic events. So, in their analyses, they do not mention changing narratives at all, as if they did not exist.
We can already today learn something about popular economic narratives by counting words and phrases in the digitized texts that are available, but there has not been enough organized research to measure the strength of the competing narratives that combine and recombine over time to cause major economic events. Artificial intelligence can help with this—especially with unstructured data. The perennial narratives described in part III of this book are works in progress, not final and exhaustive quantifications of all truly important narratives.
Research on narrative economics has already begun and surely will continue, but will such research be done on a sufficient scale in the future? How effectively will substantial research on narrative economics use the large and growing amounts of digitized data? Will narrative economics help us
create better, more accurate economic models to forecast economic crises before they begin or get out of hand? To move forward, we need to recognize the importance of collecting better data and integrating lessons from data into existing economic models. We need to research issues that today are considered peripheral to economics, and we need to collaborate with non-economists, who have different perspectives. For example, we can incorporate mathematical insights from other fields, such as mathematical epidemiology, to create a link between mathematical economics and the humanities. We must expand the volume of available data and study many economic narratives together. We must account for changing narrative epidemics in our forecasting models.
A Place for Narrative Economics in Economic Theory
As we saw in chapter 3, narrative economics has been long neglected. That is likely partly because the relationship between narratives and economic outcomes is complex and varies over time. In addition, narratives’ impact on the economy is regularly mentioned in journalistic circles, but often without the demands of academic rigor. The public opinion of journalistic accounts of narratives may have been diminished by aggressive economic forecasts that proved wrong.
In addition, economists long assumed that people are consistent optimizers of a sensible utility function using all available information, with rational expectations. As we’ve noted, this theory omits some clearly important phenomena. Fortunately, the behavioral economics revolution of the last few decades has brought economic research closer to that of other social sciences. No longer do economists routinely assume that people always behave rationally.
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