Narrative Economics with Nobel Prize-winner Robert Shiller | LSE Online Event

Welcome everyone to this LSE online public lecture, which forms part of LSE's Shaping the Post-COVID World initiative. I'm Charlie Bean, and I'm presently a professor in the Economics Department at LSE. I'll be chairing tonight's lecture by Professor Robert Shiller, which is entitled Narrative Economics.

The event is being recorded, and hopefully, a podcast will be available online, providing we get no technical difficulties. Also, if you wish to address a question to our speaker tonight, you should use the Q&A function on Zoom. Please try to keep your question short and remember to include both your name and background.

Now, our speaker tonight really requires very little introduction from me. Robert Shiller is one of the world's leading economic thinkers, working mainly at the interface between behavioral economics, financial markets, and macroeconomics. Much of his work exposes the limitations of adopting a narrow rational man perspective on financial markets and the benefits that flow from introducing a much broader view of human behavior. Aside from almost 150 scientific papers in leading journals, he's published several major books. These include Macro Markets in 1993, that advanced the case for governments issuing GDP-linked bonds, and then in 2000, Irrational Exuberance, that foresaw some of the key drivers of the 2007-8 financial crisis. His most recent book, Narrative Economics, which he'll be talking about tonight, was published late last year but has just appeared in paperback, and it exposes the importance of stories in driving economic events and explores how beliefs can go viral in their impact. For his path-breaking work bringing new insights into the analysis of financial markets, Bob received the Nobel Prize in Economic Sciences in 2013, alongside Eugene Fama and Lars Hansen. He's presently the Sterling Professor of Economics at Yale University and served as President of the American Economic Association in 2016.

So, with no further ado, let me pass the floor to Professor Shiller.

Thank you, Charlie. I am, I'm here to talk about, uh, uh, some of the underpinnings of economic thought and an idea that we have missed, the, uh, insights that can be offered to us by reading about epidemiology. I wrote my book, Narrative Economics, before the COVID-19 epidemic was on anybody's mind. It was before the first outbreak. It was a surprise to me to see how relevant this epidemiology take was, because what is happening with the disease is analogous to what I think happens with ideas. This is not the idea that we can think of ideas as spreading by contagion is hardly new. Uh, for example, Gustave Le Bon, in his 1895 book, The Crowd, which talked about crowd psychology, talked about idea microbes, okay? Richard Dawkins later talked about what he called memes, which are ideas that spread like, like diseases. Well, these people have had a lot of impact on our thinking, but less so in economics, and even less than that in finance. So, my book and my talk today will be about, uh, trying to really appreciate the importance of, uh, of contagious narratives in explaining events, explaining changes in the economy, and in some sense, it's obvious that this is, uh, that there's a factor. How could it not be? But in another sense, I, I relish the opportunity to, to, to point out how many changed narratives are plausibly involved in economic events that economists often talk about in no other terms than the actions of the central bank and the monetary or the fiscal authority.

So, here's an outline of, uh, I have to get to my, um, share my presentation here. Um, so, uh, this takes me a second here, and I have a pointer, which you should be able to see. Okay. So, there's really three parts to my talk. First, there's some general, uh, introduction. Second, I want to talk about narratives, uh, that were, uh, important for the boom that, uh, economic rule that was, uh, substantially worldwide, but also especially in the United States, just before COVID-19. And then talk about, uh, what narratives have changed significantly, uh, since COVID-19. And this is very preliminary, because we've only had a few months under, under COVID-19. But it may repeat the, the basic theme is that we, we shouldn't be looking at economic fluctuations only in terms of data changes that we already have. We need to look at new data. We must start understanding how ordinary people, not economists, change, because they make most of the economic decisions that cause things to happen. And that, uh, this thinking is spread by changes in stories. People like human interest stories. It's an instinct. It's true in all human societies that they tell stories that involve people, that have morals or lessons. Those are called narratives, stories with morals or lessons attached to them. They might be witty, they might be fictional, they might be fake news. All those things are possibilities, but they all go into the human brain and are processed, leading to emotions and ideas about what should be done.

Now, I think we are at this turning point in history, a turning point much like the turning point that we saw around the time of the Great Depression, when we first got GDP data and unemployment data on a regular basis, and we started thinking in terms of modeling those time series. But the new data source we have now is our ability to search with search engines over digitized text. So we can look at newspapers, magazines, legal briefs, corporate reports, even personal diaries and church sermons to, uh, find out what people were thinking. So, COVID-19 is a sub-topic of my talk, as probably as an illustration, but also partly because I believe it interacts with popular economic narratives.

Okay, so let me start with the first part here. Oh, I should, I have a disclosure. Uh, at the beginning, I, I have a disclosure link, but, uh, the biggest, the thing I'm involved with that might be a conflict of interest is I am a consultant to Barclays Bank, right here in London, for you, on investment products. I also gave a similar talk in 2017 called Narrative Economics when I was president, just after I was president of the American Economic Association, and I gave a talk at the LSE on, on that book. I'm not gonna, I'm gonna try not to duplicate anything, and I have a lot of stuff to say about this, so it will be a different talk. The talk a year ago is online on Facebook, and then there's my book.

All right, so I'm going to start with, uh, COVID-19. Uh, this is a, a plot of, uh, the number of cases per day, uh, uh, of COVID-19 in the United Kingdom. It starts in early March and it has a hump shape, and it has what looks like a second wave coming up at the end. This is, this curve is often called the epidemic curve. We also have here a, a deaths curve, which shows COVID-19 deaths in the UK. I'm not trying to, uh, be of dismo for you. I picked the UK because you're mostly in the UK, I believe. You see here that, uh, it also is hump-shaped. It's also, the scale is lower because of, of course, there are fewer deaths than there are cases, but this is also called the epidemic curve. We're trying to flatten the curve, that means push it down and maybe delay, so that we'll develop a vaccine and, and a cure before you end up in the hospital.

Uh, so, but what, what I want to say is that my first intro was looking at these epidemic curves years ago, my intro to this topic, and thinking, you know, I've seen similar curves in economic variables. Is it possible that they're the same origin? That there's something similar? You know, I can't remember ever inviting a member of our School of Public Health at Yale here to a, a seminar in our Economics Department, but maybe we're similar disciplines, you know, epidemiology and economics. That's the thought. I haven't proven anything yet, or maybe I will not prove anything. It's an appeal to your inductive reasoning.

Here, the blue line on this chart is a Gross Domestic Product per capita in real terms in the United States, and it's plotted on a large scale. The vertical scale is logged, so that equal percentage changes look equally big. So that's GDP. It was, it was monthly back to 1948, and then it's annual before that. And then underneath it, in the orange line, I have consumption, that portion of GDP that goes into personal consumption, you know, food, beverages, entertainment, etc. So, what stands out to me first about this is that, uh, there's a lot of little wiggles that look like epidemic curves. Now, I know this is a bit of a leap, but I think that these various events might plausibly be attributed to epidemics of of ideas, and even possibly diseases, but I, I'm not going to push on that.

By the way, here we are right to this. This shows, I apologize for just showing mostly US data here in this talk. I can't redo and everything in terms of the UK, but I think it would be similar if you looked at different countries. Uh, uh, GDP has a certain pattern that that is, uh, similar across countries. So, what, what do we see here? We see, uh, there are a couple of big events. This is 1929, and then this is the Great Depression, and you can see that's the biggest drop we've ever had by a long shot. And then over here, we have a big drop. It's not quite Great Depression yet, but it has people worrying about that. We see the slow expansion. We, you know, we had a, this is the Great Recession here in 2007 through '09. It was worldwide, but I'm just showing US. You can see that GDP per capita went down, and it's been growing, okay, but it's kind of slow. It's not like a typical recovery. And this is the longest expansion in history. You can see that, well, there's some that are close, like that one. Uh, I, I think no, or this here is World War II. You can see our GDP and consumption went in opposite directions, not surprisingly. I think we can very well conclude that this GDP here jump was due to a narrative, and it was a skilled narrator by the name of Adolf Hitler, who was the most exquisitely, uh, amusing statement of an idea that went viral in some countries, and became a panic situation in other countries. So, if that is, if that is due, it really is, there's nothing physical that caused World War II. It was a narrative about, you know, the Third Reich and the, uh, Lebensraum and things like that. So why not this one? Why isn't the Great Depression also, it's big, why isn't that, why isn't that related to narratives? You don't hear that very much. So that's where I'm going. By the way, when I look at that chart, let me just, I'm going to plug a book by one of your professors, Richard Layard, but let me just say, when I, when I look at these wiggles, it seems like only the big events matter. It's the Great Depression, it's World War II, and it's right now, okay, the, uh, COVID-19 depression, that's not what they call it. These other wiggles are kind of small, you know, I mean, they're up and down like three percent from the trend. So, you know, I, I think that maybe we're, economists are barking up the wrong tree and worrying about those little wiggles. It's more about, uh, something else that, uh, I, and that would be, according to Layard, happiness. I'll, I'll leave that, this is his book, not mine, but I'm going to move on from there.

So, this is the real stock prices in the United States, S&P Composite Index from 1871 to the present. That was in my book. Actually, it was even, I've been publishing this data for a long time, and this is the underlying earnings in green for the series, but there's a lot of wiggles up and down. But if you look at the long path of earnings, it looks pretty trendy and stable. So, I'm inclined to think that all those wiggles were driven by something other than news about earnings. What was that? That's a key point here, which we'll try to answer.

This is home prices in the United States. It's an index that I created. It involves the Standard & Poor's Case-Shiller Home Price Index. It's nationwide, and you can see that home prices, uh, show a lot of volatility. And so, what's going on here? What drove this? That, you know, that there's a name for this boom. It's called the Baby Boom. It's the post-World War II boom. It goes way back to the narrative, I would say. Adolf Hitler calls this, maybe that's an oversimplification, but it was a relief from the end of the war, and it was the story that people were living. You can see that the price is more volatile than the rent. The rent series only starts in 1980. So, it's not like demand for housing is driving this. It's something else.

So, I wanted to just very quickly present, it's just a couple of slides here, a mathematical model. This I had in my lecture a year ago, that the epidemiologists use. This is called the SIR model. And it, the model is S is susceptible, the percent of the population is susceptible. I is a percent of the population infected, and R is a percentage of percentage of population who have now recovered and are immune. In this model, this is for disease modeling. In this model, it can only be used on the modeling of a disease that is never fatal. You can make a simple adjustment to put fatalities in, but the key equation is that the number of infectives grows because of contagion when when a susceptible meets an infected, which happens with a probability related to S times I. This is a contagion parameter, that's new infections. But there's also on the, we're also losing infections because people recover. That's the recovery rate times the numb, percent infected. So, an epidemic grows when the contagion is higher than the recovery, which happens for a while, and then it gets exhausted.

So, this is the, uh, the COVID-19 2020 model with these parameters, which roughly represent COVID-19. And you can see the black line is the epidemic curve for cases of, no, not for cases, it's the number infected. And the, uh, red line is the number of new cases. The orange line is the number of new cases. So, the epidemic curve falls out, right? The dotted line is a fraction of the population susceptible, and not everyone catches it. The dashed line is the percent who caught it and are now immune. It differs from COVID-19 in various ways. First of all, the contagion rate is not constant in COVID-19 because policies are intervening. Secondly, we've come nowhere close to this is called herd immunity, when there are no more new, uh, our cases.

So, I just wanted to give a quick example of an epidemic curve of an idea or a narrative. So, this is, I just did a search on, uh, uh, ProQuest News and Newspapers for English language newspapers that use the, no, I'm sorry, this is, this is Google Ngrams. This is books, not newspapers. I'm sorry. The, the books, uh, are, it's the percent, it's the percent of engrams or words in books that are, uh, represented by the, the pair "fair wage." So, you can see that the word "fair wage," nobody talked about, almost nobody. Something happened here, uh, in the 1830s, but it was an idea that grew through time for decades and peaked, you know, when the Great Depression. Exactly in the Great. There was a time when people were really bent out of shape about unfairness, and then it collapsed. The red line is another narrative epidemic that came in with Margaret Thatcher and Ronald Reagan, and sort of, this is "market wage." And so, the market wage wasn't even talked about. It's impersonal. So, labor unions went through the same movement. Now, labor economists will talk about labor movements, and that's an epidemic model already. Why do we have a movement? Why does it take place over decades? The labor movement started around 1880, it grew until the Great Depression, and then it came down.

Well, this is just a question from one of my surveys. I did this in 1997, asking what people think about in 1997 and compared ordinary people with economists. So, I asked them, what, what will happen when there's inflation and to your wage? And they have these four choices. One is extra profits for my employers. Two is my employer will be forced to raise my wage, too, because I, you know, he has to raise me to the market wage. Three, that my, uh, employer will be, is a fair and honest person and will raise my wage because it's proper. There's a huge difference, highlight, between ordinary civilians and economists on answers to two. Economists believe in those market forces, but these, these individuals were in the middle of, or in the late stages of, the fairness epidemic, fair wage epidemic, and they thought it's really, it's not about market forces. So, they don't think in terms of, they think in terms of fairness, at least at that time in history.

So, um, so narratives before, I have to make sure I have time for all of these narratives. The big thing that I emphasize in the book is that people are have need an accounting of all the narratives that are having an impact, because there are many of them at one point of time, and economists don't have any systematic framework to do that. So, they would avoid even mentioning, you know, one out of 20 narratives that were all having an impact on the economy, and they're, they're fuzzy-edged phenomena, and who knows? But let me just talk about narratives. I'm going to start with pre-COVID-19, but just pre, when the US stock market was growing remarkably fast and was setting new records, despite the slow recovery, and people were wondering why. So, I'm breaking the world of the economy up into three, four periods: 2003 to '07, before the Great Recession; 2007 to 2009, the Great Recession; 2009 to '14, the slow recovery and pessimistic but recovering start of the long expansion; and then, in 2014, the fourth period to 2020, when we set a record peacetime low unemployment rate in the United States. So, like the economy was prospering like never before. So, why do those things happen? Now, economists will naturally talk about monetary policy or about fiscal policy, and I'm not denying those things. I'm going to talk about what else we can talk about.

So, I have, I have 10 different narratives in the for the United States during that period. And the first one has to be Donald J. Trump. I assume you've heard of this man, but he dominates conversation. It's just amazing how much he dominates conversation here. He's done it better than other presidents. Obama got a lot of conversation because he was our first minority president. That's the orange line here. Did pretty well in generating conversation, but it's even higher with George Bush, who is a normal white male, generated very little discussion. It's the power of the narrative. These people made their impact through narratives associated with these names. As other narratives, a strong economy narrative. So, you can see that the term "strong economy" was, uh, was virtually never used, and then it goes through an epidemic curve like, until around 2000. Instead, they tend to talk more about speculation, over-speculation. Talk about that had been growing for 40 years or more than that, until it peaked around 1929. That's when the market crashed, and then it's been declining ever since. So, stories about speculation are less prominent at that time. So, now, one reason why we had a sense of a strong economy is we elected a man who, who exudes strength. 62% of news stories with that, that he mentioned "strong economy" also mentioned Donald Trump in 2017-2019. So, he's a strong man, right? He, he boasts, he looks big, he thinks big. In contrast, another president had a different narrative. Bill Clinton. He wrote a book called "Putting People First," and he was in a strong economy too, but they didn't mention him. It's like he didn't do it because he wasn't such a strong man. Maybe you might be disagreeing with my interpretations, but the, the numbers do speak that there is something happening relevant to the economy in these numbers.

Three is fake news. And this is Google Trends. Now, what I'm searching is searches on Google. And "fake news" was used occasionally over all these years from 2004, 2008, 2013, but it suddenly took off in the election of, uh, of Donald Trump. And they accused, people are accusing each other of lying or making up stories. This is a very important economic phenomenon because it's a destruction, a destroyer of trust. And trust, there's a literature on this, is important for economic success. You can't do business well if you think everybody's lying.

A Great Depression. This, I haven't updated it. It's from my book. Well, not the, it's talk about the Great Depression. The Great Depression in the 1930s is the biggest story, economic story of all. Nobody's talking about the crisis of 1907 or 1973-75 either. It's the Great Depression because it's been embellished, I would say, in stories. You can see what it did. It's been, the stories of the Great Depression was growing for decades and then exploded in 2007-2008 with the Great Front. So, the Great, in fact, they call it the Great Recession after the Great Depression. So, it's definitely narrative-based. Part of the, uh, part of the, uh, lessons of the Great Depression were supposedly about confidence. People started talking much more about business confidence and economic, and con, especially consumer confidence. The, uh, Great Depression, one important aspect of the story of the Great Depression is that people aren't spending because they're not confident, and the only way where people can get confident is if they, other people spend.

Trade wars and retaliatory tariffs. Here, I've searched, this is news and newspapers. I've searched for mentions of a trade war since 1800. And look at what's just happened. This is in since 2000. These are decadal. They used to talk about retaliatory tariffs, but not that much. We've just made "trade war" into a bigger thing than we've ever seen before.

Sustainability and frugality narratives have had an epidemic sort of thing since 2000, and it's faded somewhat, permitting other narratives to move into center stage. This is Greta Thunberg. Remember her? At the age of 16, she sailed across the Atlantic Ocean, thereby reducing the need for fuel, fossil fuel. So, where did she come from? She's only 16 years old in this photo. Somehow, she went viral, and her story. There's something that people like, are impressed by her. But I'm sure it's hard to define exactly what it is.

Okay, this is a fear of debt narratives that, uh, it's again, ProQuest News and Newspapers. There was a huge increase. There was a decline in fear of the dangers of being in debt in, uh, around 2006, and then it shot up to huge levels for a while. And then, starting in, in phase four of my list, we tended just to forget about it. And so, what were they talking about back here when it was really talked about a lot? So, I go over to newspapers, and I won't read all these, but it was human interest stories about people who went bankrupt, and, you know, with lessons: "We will never leverage up like that again." "The relief of knowing we're not in a bottomless hole has been great." So, there's these stories were were common then. So, it, it, it discouraged purchasing. It made for a very, it's long, slow recovery, I think.

Boomerang buyers was another thing that started to come in in 2014. People after they, uh, they were wiped out and lost their house was reclaimed by the lender, they managed to get back in again. That's the story, a narrative about the recovery.

There was also a "new normal" narrative that we will be in a recession almost indefinitely. This one was growing from at the time it, from the time of the normal of the Great Recession until, I guess this thing stops around 2018.

Real estate booms and real estate bubbles. We started talking about real estate bubbles in the 1990s. Before that, there was hardly any talk about real estate bubbles. They talked about real estate booms more than they talked about real estate bubbles. So, um, I, I, I try to figure out what's the difference between a real estate boom and a real estate bubble. So, I go back and I search old newspapers or old books. I found this nice little discussion about the difference between a bubble and a boom from 1887. Now, it's written in the con, it's written in 1915, but he's remembering the unforgettable real estate bubble of 1887. Do you remember that one? It was in the United States, centered on Los Angeles. I, back then, everybody knew about the great real estate bubble of 1887. They usually call it a boom, though. When I wrote an article for the Los Angeles Times, I was thinking of offering to write about the bubble of 1887, but I asked the editor, "Of course, everybody in Los Angeles knows about that, right?" He said, "I've never heard of it." I said, "I read it in your newspaper in 1887." There was a huge boom and bust in Southern California, and it, but he, he argues that "boom" is more reckless and masculine, and "bubble" is more feminine. I don't know. He's writing in 1915. It's a distinction they, we didn't want to say "bubble" until somehow just recently.

Artificial and artificial intelligence narratives. This is something that was exploding before this recent crisis. It's all, it tends often to be encouraging fear of your job being replaced by a computer. But there have been other swings. They're separate waves. The, the first epidemic was in the late 1950s. That's when computers were moving into the office place, and we see other waves. What explains these, uh, attention differentials, attention to, and what is, is this a more dangerous form than automation? I think it sounds more all-encompassing, artificial intelligence, and I think that these narratives might take off again. Well, they're taking off as of my latest data here.

So, now I want to come around to COVID-19. This has emerged as the number one topic, and it's the whole world. So, it, now you could blame it physically on the disease, but I, I think that there is also a narrative component to it that that affects how we, uh, react to the disease, and it's different in different countries. In the United States, for example, maybe in the UK too, I don't know, there's resistance to wearing face masks as effeminate or something like that. As our president, who made us very good at political judgment, President Trump, has been reappearing now without a face mask, even after all of this. So, it's become a political statement.

So, I'm going to divide this into four periods. This will be my conclusion. Let's talk about now. I'm going to switch to monthly data instead of annual, and I'm only going to look at 2020. So, we have pre-crisis, that's January of 2020. I date the crisis as beginning on January 30, 2020, when the World Health Organization called it a Public Health Emergency of International Concern. And then the COVID, the the stock market continued to grow even after, even after they said that, from January 30 to February 19, practically a month, about 20 days. Then C is the crash. C for crash, remember that. February 19th to March 23rd. So, it's a two-month, whole two-month, almost two-month long major drop in the stock market. And then there's the V-shaped recovery. That's D. So, if I just go ahead here, this shows the Standard & Poor's 500 index in the different phases. This is a, before the epidemic was even risk mentioned as a risk factor, the stock market was kind of flat. Then, once they announced it as an emergency, it was going up until February 19th. Then there was this big drop in the market to March 23rd. March 23rd was the date when the Fed announced a very, Federal Reserve announced a very expansionary monetary policy, and this is the path ever since, setting new record highs, and not in the very latest week, last week, but okay.

I'm just going to go through the, these are the narratives I've already talked about. Here are the narratives for right now, in 2020, and these should be very familiar to you now. Even though my, I have an American perspective, I know I read The Guardian regularly. I know that this is similar to what's going on in Britain and in Europe. So, coronavirus, 370,000 hits in one year. Those are 370,000 different news stories that mention the coronavirus. So, A, they did start talking about it in January before the WHO announcement, but not very much. B, this is the period when it was increasing up, even after they weren't talking about coronavirus that much. It suddenly leapt into attention in, uh, in C, which was the crash component. And then, this is, uh, D. I'm not sure I got my letters lined up exactly right. Here's a Google, not a Google Trends, it shows searches on Google. You can see that it was in somewhere around March of 2020 that people were searching for coronavirus. They didn't know what it meant. You know, there were news stories in January, but most people didn't even read them. Something about China, the other side of the world, some people are getting sick. They just didn't register. So, what we see is a movement of attention toward pandemics, which had already, people already knew what they were, and they needed to be reminded. What, what is this one? This is a pandemic again. A and B, the reason the market kept going up in B, uh, after the, the WHO announced it, January 30th, is because people still didn't, they still didn't register it. It wasn't real yet. It suddenly became real in March and April, and now it's fading. It's, you know, I, I don't know what to make of that. It's like a post-epidemic peak. There are human interest stories during phase C, when the market was dropping rapidly. So, I, I was particularly struck by this one. This young man, Wesen, who wrote the article, and this is in the Wall Street Journal, and these are some, he was visiting a girlfriend in China, and these are the locals. They're, they're hunting for worms to eat, worms and minerals. Okay, great story in a local creek. Oh, Donald Trump registers there. He only has 155,000 hits. So, coronavirus is the superstar of our narratives today, but Donald Trump is hanging in there very strong, not declining much at all. He's hanging in there because of his genius at renewing his contagion by constantly coming up with new, uh, gossip and staying within the bounds that he doesn't offend people. They're, they're, well, you know what I'm talking about.

I think global warming. So, this is, uh, this is, uh, Greta Thunberg again. In January, there was a lot more talk of global warming than there is since. So, it, it, it seems to be the stage is being pulled away from global warming. And with most recent data, even with the California wildfires, which are, to some people, extremely alarming. If you're in California, you'll know it, and it's talked about a great deal, but, uh, overall, it hasn't, we're too preoccupied with COVID-19. I did a search on poor Greta Thunberg. I think she's a very promising young woman, but she's turned 17 now. She's no longer so young. Not quite as good as a story, but her decline since January, this is January, this is February, this is March, it's quite precipitous. I think she can recover. She can make a second wave, but she has to reinvent herself. It just somehow is no longer a contagious story. There's Greta on board. Her chance, that was a pretty daring stunt, wasn't it? She had help. You can see, I guess those are her helpers. She didn't sail alone across the Atlantic Ocean, but it was a good story. They had a thunderstorm, and lightning was striking all around them, and her father remarked that they were more than a little scared out there.

This is, oh, now the American Dream. You probably don't hear about this so much in the UK, but it's an idea that America is a special place where honest enterprise is rewarded. And it hasn't really changed. It, I, I should have, but I should have shown the whole thing, but "American Dream" has been a narrative that's patriotically strong in the US, that has been growing since I was first, the term was first coined in 1931, and it's been an epidemic of long-term status. I think it's something that Donald Trump hooks on to. So, to understand the high level of the US stock market, has the highest price-earnings ratio in the world, at least my price-earnings ratio, CAPE, is the highest in the world. It has something to do with this thought that there's something especially, people are come to America because of the land of opportunity, ambitious people. And Trump hasn't keyed into that, but I don't see any real trend to that. There's the American Dream. Oh, yeah, this is what I meant to say. This, it started in 1931, and it's been growing as a source of pride and patriotic sentiment. A little downturn, but not significant. And I think it helps explain these high stock market at this time. It doesn't make any sense, you understand. It just goes to interpret Donald Trump as is like a tough businessman. He's running the country like a businessman, and it just sounds, it just draws attention to maybe these, right, even if you hate the guy, you might choose to invest in America.

American greatness. That, that one is, that's also just for 2020, but it's talked about, but not, not hugely. So, the Great Depression is another story that I think is, I mentioned before, it peaked. Uh, in this is January, February, March, and April and May, at the beginning of the recovery. At that time, people were starting talking about V-shaped recovery. They were talking about the Great Depression, but they were also thinking of the recovery afterwards. This is a New York Times article on the left that was published on the day of, on the morning of the day of the worst stock market drop in world history, October 19, 1987. And they show the Great Depression drop in the stock market below, and they compare it with the, uh, market in 1987. And they see it's starting to drop. This is a narrative that we're repeating, Great Depression again. In 2007, we were reacting. No, now this is just a few, a couple weeks ago, a similar comparison was made, not to the Great Depression, but to the, to the 1987, I'm sorry, 2007 to 2009 crisis. So, people always think back to something that they can remember. Great Depression is in their mind. The other thing that's in their mind, this is the other narrative, is the stock market decline of a dozen years ago. Also, quantitative easing and similar terms have taken a big jump recently. This is March of, uh, this year, right at the time that the market started its turn upward, and it's associated with human interest. All three of these people are, these are from left to right, Jerome Powell, Janet Yellen, and Ben Bernanke. Fed chairmen who have the most boring-looking of jobs, but somehow they've been lionized in the American Dream as important human interest figures.

The V-shaped recovery started to come up this year again. That's January, February, March, April, right after the drop in the stock market, and the recovery of imaging information about Great Depression. We saw a V-shaped recovery. It's not a common term. I researched it way back. It wasn't used by anybody that I could find until the 1950s, and then it was rare. Now it's become a much more prominent. I think I'm just about done here. This is my last slide, actually.

Now, I'm a little disorganized in looking at all these narratives, but I don't have a theoretical framework to organize them or some sort of pattern of mutation and contagion. But I think that we should see more attention, uh, to, to narratives in the future, given especially that we have so many better databases, and we could use things like focus groups to, to, also is an independent of that method to start to, uh, uh, find out what the narratives and morals are on our, what narratives are out there currently. A focus group is where an experimenter who's good at managing these groups takes a small group of people and asks them to discuss topics that he or she gives them, and put similar people together, and they, they're emboldened to reveal what they really think. And you try different groups and break down the population into different subgroups and say, what's motivating them, and what's that? This is used primarily, especially by marketing. It's also used in sociology. And we want to also integrate narratives into the existing models. This is just, I had a similar chart a year ago when I spoke about narrative economics, but this is the percent of articles in the JSTOR database that mentioned the word "focus group." And you can see it's sociology, two percent of their articles have "focus group" in them. And then, uh, anthropology, psychology, and anthropology. Again, the black, I'm sorry, again from last year, the black bars show all years, and the gray bars are just the most recent decade. And you can see that every discipline is referring more to focus groups. Every discipline shown, and economics and finance are also, but they're relatively meager. History drops down because they can't do focus group groups in history, so they can't, they would love to do focus groups in history if they could. So, I think that coming back to the, I've shown here a lot of narratives that maybe they should look familiar to you, but I've given you counts showing their relative importance, their questionable significance, sometime of what those counts really mean. But I think that with a careful attention to our understanding of human nature, as well as mathematical statistics, we can get a better idea of what's driving economic fluctuation. So, I will stop. Thank you very much.

Bob, that was, uh, absolutely fascinating, with a lot of food for thought. And it's prompted a lot of, uh, questions that I can see. Uh, a number of the questions, uh, home in on a sort of set of related issues, along the lines that, uh, some of these narratives are basically benign, some of the line or false, downright fake news, if you like. Some seem to matter, some may be less material. And then, finally, there may be a degree of reverse causation. So, the, the narratives are responding, or reflecting events, rather than actually causing them. And you've, you've sketched out, uh, lots of narratives here, but do we have a mechanism for sifting which ones are likely to be the most important and most salient? And do you have a, stories, hypotheses, the way with the way we should think about narratives emerging and then dying or being replaced?

Okay, those are deep questions, and I apologize for not having a complete answer. I'm sensing that we've got a new database, and we're going to see research on that, and it's something for, not one person, many people have to get involved in this. So, reverse causation is something that rings true to, uh, economists, because we're very interested in that. It's become a criticism of a lot of modeling, and I think that it's, it's a difficult thing to deal with, but not impossible. We have to, we have to be looking for the truth and what's really driving things, and we may end up using some of our human judgment to, uh, to infer that. Now, in other, in other social sciences, I mentioned this last year, I think they do controlled experiments. Now, we can do controlled experiments in economics, but maybe that is, but I haven't seen that about causality from narratives. So, so, for example, legal scholars will put, uh, their, uh, students into two groups, an experimental group and a control group, as a jury, and, and then have two different versions of the prosecution's comments, or information. One is an anemic version where everything is very polite and colorless, but has all the facts, and the other is a hyped version that doesn't present any different facts, but just hypes it. It makes colorful language, it includes extraneous detail that's colorful, and they find they get convictions more often with the hyped version. So, I believe that that's been shown. But, but it's a little bit harder to do a controlled experiment on viral narratives. It's a very competitive marketplace to get viral, and it's something about hitting a particular chord or something. So, reverse causation is hard to be handled in economics. I think we can do some controlled experiments to establish some things, and it's not just reverse causation, it's also the direction. Often, when I refer to, like, well, I can't know if I think of a good example right now, but it may be that it's very clear that the narrative is exogenous, like COVID-19 is initially not, it'd be caused by some transmission from bats to people or something like that, which is random. But we don't know which direction of effect. Does it make people sick, or does it make them inspired? And that's an ambiguity that we face. But I don't want to make the mistake of that there's a classic economist joke about an economist was searching under a lamppost for his keys, and a passerby comes and says, "So, did you lose your keys here?" And the economist says, "Ah, no, I don't think so, but the light is better here." So, so we don't want to make that mistake too often. When I'm advocating here, sounds a little bit like more of appreciation of historians. We don't have historians from the history department over to our department as often. So, when they make assertions about history, you can ask the same question, "How do you know that it's not somehow inverse causation?" But I, I bet when you read a good historian, that question doesn't always come into your mind. It must sometimes. It's, uh, it's slow progress. I, I think it involves some human judgment about reverse causation, and, uh, it may be, uh, somewhat disreputable part of economics for a long time to come. I just think I like the truth. I like to know what's really driving things, and I think it ultimately affects policymaking and forecasting as well.

Now, I have a, a couple of link questions here. There's one from Ted Crane of Lloyds Bank, credit risk forecasting and stress testing, who's interested in understanding what technologies researchers are using to quantitatively capture these ideas. And somewhat linked to that, Chandler Wilson, who's the Head of Data Science Innovation at a large global bank, wonders why firms are being so slow to move into this sort of space, to use these ideas.

Okay, as for the technology of inferring that's a big subject matter, and it's not something I can anticipate entirely. But I wanted to mention that maybe I should just talk a little bit about focus groups, which is a technology. There was a famous article by Robert K. Merton, who is actually the father of the economist Robert Merton, in the 1940s, with a co-author called "Focus Interviews." And there is a sort of technology outlined there for conducting focus, and he, he imagined to be one-on-one rather than a group. It's now typically more a group, I think, but there's something about, uh, listening attentively, listening for what ideas are brought up, and following up, I mean, ideas that you didn't expect would be coming to mind when you bring up a topic. But I think that there is something of a skill that some people have to run focus groups and to get people to open their hearts and tell them how they really think. And, uh, as for why firms are slow to move into narrative economics, well, they maybe they are not, in some dimensions at least. I'm thinking, uh, in terms of what they learn at the business school, in terms of marketing. We have a marketing department. So, the advertisements that they show on television, if you'll notice, tend to be advertisements in the form of a small skit, often humorous, amusing, attention-grabbing, involving real people like you or me. So, if they're advertising medicine, you would think that rational response theory would suggest, put the best scientists up, and the scientists will show graphs and tables about this medicine. They don't do that. That's not how people think. What they do is they show somebody just like you, they've got your demographics, who's saying, "You know, I took this medicine, and I feel great." And then they show his admiring grandchildren coming up to hug and kiss him, and they play soft music. They've done experiments on all these things, like music. Do you think they put music in for entertainment? Well, it's entertainment, but with a motive. It's been shown that ads are more effective if they have soft, pleasant music playing in the background. So, the other department that comes to my mind teaching business skills is the journalism department, and they will, I'm sure they always will tell you, you've got to learn not to present too many statistics and things like or charts in your news stories unless you can develop a human interest story around them. So, you know, it's not like businesses are, uh, using a narrative theory, uh, already. And let's hope they're doing it in an ethical way. You can manipulate. I have another book with George Akerlof called "Fishing for Fools: The Economics of Manipulation and Deception," and maybe we were a little critical of the business world, but not always. They often have a good heart and are, are just reflecting the reality of the situation that you've got to get people's attention somehow, and it's a very competitive world. So, the other question by, is Ted Crane, you said, yeah, I, I guess I've, yeah, I think I've answered as well as I can. I need both of those questions, right? Okay.

And I guess because of the time, this question needs to be the, the last one. This is from, uh, Azal Hussain, who's a PhD student here at LSE Economics. Would you agree that the rise of identity politics around the world primarily feeds off some kind of narrative?

Yes, it's a resurgence of identity politics. We had, I mentioned World War II, identity politics played a big, we had Benito Mussolini and other people who were, uh, people identify with that means they think that they are the same person, almost that they feel fundamental loyalty to a person. So, yeah, this is definitely something that's happening at this point in history. Uh, I, I'm not, I'm not a political scientist, and I'm sure they have many more insights than I can offer, but I'm thinking that there are, uh, there are, uh, examples of, I think the, the post-World War II distrust of charismatic figures is fading, just with forgetting about, uh, these people. Uh, I've told my students, watch a Mussolini speech or a Hitler speech with English translations. You can find them on the web, just so you have a sense of what caused that war. And then I thought maybe I shouldn't urge anyone to watch one of their speeches, he might like it too much. But that's identical. So, I think that there have been recent examples in, in history, of, uh, people who were well, who are, uh, uh, defining a new form of identity. I, I keep mentioning our own, uh, President Donald Trump. I'm avoiding your Prime Minister. I don't want to be offensive as a foreigner, although I actually admire both of those men. They're both geniuses at some, at some level. And it's not the average person who makes it to that lofty level. But, you know, we see, we see people who are copying other successful people. So, for example, Jair Bolsonaro in Brazil, the Brazilians call him the Brazilian Trump, and he does a lot of things that are suspiciously similar. So, it's like there are cultural similarities around, around the world, because we communicate. So, they're all on TikTok. All of our teenagers are on TikTok, and they're, they're sharing experiences with people in any country. And so, there is something about identity politics that's that is growing right now, and I can't, I can't be more eloquent than that about it.

Okay, well, thank you very much, Bob. That's been a really fascinating, uh, discussion, picking up on, uh, your book, uh, which is now available, uh, in paperback for those who haven't read it before in hardback, but, uh, there's some interesting themes there that you develop in the, uh, the context of the, uh, current pandemic that we're all living through. So, can I say thank you again, uh, from LSE for participating, and thank you also to everyone who tuned in to listen. Goodbye.

My pleasure.