Bonus: Three econ stories
Episode Transcript
CARDIFF GARCIA: Hi, I'm Cardiff Garcia, and this is a special bonus episode of The New Bazaar. On the most recent episode of The New Bazaar, I spoke with Tim Hardford, the author of The Data Detective, and the host of the Cautionary Tales Podcast. And our chat was all about the craft of economic storytelling. Well, on today's bonus episode, we are playing the very end of that conversation, which you did not hear in that previous episode, when we discussed the economic lessons of three actual stories that Tim has told in his writing and in his podcasting. And specifically on his podcast, Cautionary Tales. Which by the way, is great. So here is the chat. Hope you enjoy it.
CG: Well, having established the importance of storytelling, and having discussed something of the craft of storytelling, let's tell a few stories from Cautionary Tales and from The Data Detective. Uh, you ready?
TIM HARFORD: Yeah. Yeah, sure.
CG: Let's start with a recent episode of Cautionary Tales, which I thought was fantastic. And I would describe it as Tim Harford's true story of the fake story, of the fairytale of Hansel and Gretel. Um, and it's about the dangers of being credulous, uh, including for those who warn most aggressively against being credulous. So why don't we start there? Give us sorta the, the brief version of the story, the quote, unquote, and it's important that I put this in quotes the, "True story," of Hansel and Gretel.
TH: It's, yeah, it's, it's nested, eh, e- uh, there are, there are ... It's a real Russian doll this one. And in fact, the whole podcast was, was bracketed by a discussion of, of the movie Fargo and this tragedy that was associated with this movie, Fargo. So even without getting into Fargo, which we probably don't have time for. The, the, the Hansel and Gretel thing, so it's about this guy who, you know, living in Germany in the, the 1960s, um, suddenly recognizes this landscape. He's just walking through the woods. And he recognizes this landscape. It's like this sense of déjà vu. And he realizes it's a perfect, um, match for this beautiful illustration of this first edition of Grimms’ Fairy Tales. And he sees the, the illustrator has depicted this landscape. And the story that the illustrator was illustrating is Hansel and Gretel.
So this guy's like, uh, he's named Georg. Uh, Georg Ossegg. And he's like, "Oh, well. Um, what, what else in Hansel and Gretel is, is true?" And he goes on this long quest to try to figure out, "Let's just assume the story of Hansel and Gretel is actually history, not a fairy story. Can I find archeological evidence for this?" And he finds all sorts of things. He finds the tree that the woodcutter has tied a rope around to fool the kids into thinking that he's still chopping woods, and he's not. He finds, he finds the river that the children crossed. He finds the witch's cottage. Um, he finds a skeleton inside the ovens in the witch's cottage. This is where the, that Gretel pushed the witch into the oven, if you remember the story. And, and the witch burned. He f- he finds a recipe for gingerbread. Remember, it was a house made of gingerbread. He finds a recipe for gingerbread inside this locked steel box. And all this other stuff. He finds loads and loads of evidence and puts together this compelling case. Um, and his story is told in this book called, The Truth About Hansel and Gretel. And the great thing about The Truth About Hansel and Gretel is it's, sa- it's just a joke. The whole thing's a joke.
Georg Ossegg doesn't exist. Um, nobody ever did this stuff. If they did, I mean, e- whe- when you start looking at it closely, none of it makes any sense. A lot of this stuff is completely ridiculous. But The Truth About Hansel and Gretel, which is a book published by a gentleman called Hans Traxler, uh, who by the way was a f- satirist. And he wrote kind of, he did cartoons and, you know, sater- satirical comedy pieces. Um, when it was published, it was just this smash hit. And people took school trips to visit this part of Germany. And, uh, people wrote from around the world, expressing this i- interest in this new field of fairytale archeology that might've inspired the spirit of international cooperation. And then when he confessed that he'd made it all up, then people reported him to the police. And so it's, it's all about, um, you know, how we can convince ourselves of, of certain stories. Uh, it's about the role of satire. It's about what we believe and what we don't believe. And, and how can we be persuaded to be more skeptical when we should be more skeptical. And yes, and the whole thing is wrapped in this story of, of Fargo and, and, and there's a, there's another bait and switch there. Like, is this ... Did f- did Fargo cause someone's death, or not? And, and ha- who, who-
CG: Tragic story.
TH: Should we believe that or not? I mean, that's also an amazing story. But, yeah.
CG: Tim, here's what I learned, uh, from both the story of this book, The Truth About Hansel and Gretel, and the connection to what happened, you know, with the movie, Fargo. And we're not gonna get into that in detail. 'Cause probably 'cause I wanna leave people with some suspense about what's in this amazing episode of Cautionary Tales. What I learned was that if you label something the truth, okay? Even if it's, blatantly an act of, of fraud or satire, and it's just not un- and it's just not true at all. If you label something the truth, a lot of people will simply believe it. That a lot of people want to believe that, the fascinating story that's so mysterious and full of suspense is true. And it, that can be really quite dangerous to label something true when it's not.
TH: It, it, it can indeed. A- And, and, and of course the reverse is true. So you can label something fake news, when in fact it's true. And, and what's really going on here is that, uh, and Daniel Kahneman, the great behavioral scientist, author of Thinking Fast and Slow. Winner of the Nobel Memorial Prize in Economics. He, uh, said that when we're faced with a difficult question, we often substitute an easier question, and answer that, the easier question instead.
And we don't notice that we've made the substitution. And what's going on in both the cases of people falling for these satires, and in the case where people read a true story but think it's fake news is, we have this hard question, which is, "Is this true?" And we substitute the easier question, which is, "Does this ring true? Does this feel right? Does this sit well with my preconceptions?" And we don't notice that we've substituted our emotional kinda satisfaction with the story, uh, for the- this more rigorous process of actually trying to figure out whether it makes any sense.
Um, but we do that all the time. And that's one of the, the points that I tried to make in The Data Detective, is that so often, uh, just whether, whether something chimes with our emotions, is the basis on which we decide whether to believe or disbelieve it. Uh, whereas actually we should be willing to put in a little bit more hard work, and, and actually critically analyze this stuff. And, and that, and if we do, that hard work is actually its own reward. It's worth it to, to do that work. 'Cause actually, the, the world is much more satisfying when you engage with curiosity and get stuck in.
CG: Yeah. The story of Florence Nightingale is one that you touched upon a little bit earlier in our chat. She was of course the, the very famous British nurse and campaigner for better conditions in hospitals, military hospitals famously, and, and also civilian hospitals. And of course she was a statistical pioneer along with, as you mentioned, William Farr, the very famous statistician from the 19th century. There was something quite fascinating about Florence Nightingale as well, which is that she really knew how to use the tools of statistics and visualizations to wield influence, and not just to present something that was pretty and true. She actually made the case that like, this is what will get Queen Victoria and other prominent people to pay attention to her. That these beautifully designed, um, these beautifully designed visualizations combined with their statistical power is what will get the right people, the right audience to listen to her.
And that that would make a difference. So I, I just, I took away from this a lesson not just in the importance of storytelling. And not just in the importance of visual storytelling. But in the importance of having the right audience for your storytelling.
TH: She, she was very clear that this was the strategy. She would write ... Um, she wrote a lot of letters, like, like I guess a lot of Victorians. And in her letters, she was crystal clear that she was going to use these diagrams as part of the communication strategy. Yeah, there's, there's one letter where she, she lists all the people she's going to send this to. And it includes Victoria and, and Prince Albert.
Uh, but the, se- uh, the chief medical officers in the House of Lords and the House of Commons, and the ambassadors of all the crowned heads of Europe, and all of the magazines and the newspaper editors. They're all gonna get this stuff. And the, eh, there, there's one quote where she's very dismissive about Victoria. And she says, "We, we, we need to send the Queen this report. She may look at it, because it has pictures."
CG: This is like what people said about Donald Trump, right?
TH: Yeah. Yeah.
The thing is, it's, it's tru- it's revolutionary at the time. Particularly in, in, eh, the British statistical circles. The French were using some data visualization at this point. But the, you know, eh, uh, British statisticians would communicate through big tables of data. That just, "Here's all the data in a table." And, you know, eh, you maybe have to unfold the page and, and you have this huge kind of bit of paper spread out over your desk with all of these numbers on. But the idea that you would draw a picture of the data was really just not, not done.
And she understood that, eh, that a picture is worth a thousand words. And while her visualization, the, the most famous one is called The Rose Diagram. That visualization is, uh, I mean, it's not the first brilliant piece of data visualization. There are earlier ones in the history of data viz. But I think it is one of the first that was used, um, as, as a, a weapon in an argument. And, and it was decisive. So, eh, Nightingale was ... I mean, in a nutshell, she's arguing better hygiene really makes a huge difference. This is before germ theory. It's a controversial idea. A lotta doctors saying, "It doesn't really make any difference. People die of infectious diseases. There's nothing you can do really. Just suck it up."
Um, this is a precursor to all these arguments these days to whether it's worth bothering with masks or not. I mean, it's really that what goes around comes around. But Nightingale is fighting the medical establishment and the military establishment. She's arguing, "If you clean stuff up, ventilate fresh air, whitewash, scrub the floors, get dead horses out of the water supply, it really makes a difference. Scientifically, I can't prove that. But the statistics support that argument. And I will present the statistics in the form of a picture." And the picture is incredibly powerful. And the twist in the story is, did she cross a line? But, eh, does her picture really fairly depict the data? Or did she go too far in, in making her argument? I think we'd forgive her if she did, because she was right. And she saved millions of lives. But that, that's a, there's a question I leave people with as to whether she twisted things or not.
CG: Yeah. In other words, did she sort of exaggerate the claims that could be made in the statistics by putting together this very powerful, you know, data visualization, essentially? I mean, I guess this was the original data viz project, right? Uh, by presenting something that exaggerated the claims that could realistically be made. That's the question, right?
TH: My argument would be personally that I don't think she exaggerated anything. But she, she framed it so perfectly as to put all alternative explanations of what you were seeing out of people's minds. So they, they just weren't able to conjure alternative explanations for what was going on. Whereas if the data had been plotted in a more conventional way, you'd look at it and go, "Oh, yeah. Nightingale could be right. But it could also be this or that. That like there are other ... Maybe it's the weather." You know, but she just framed it so well. So I, for me, I think she probably stayed on the right side of the line. 'Cause she never distorted the data. But there's an ar- there is an argument, you could make an argument that she, she pushed it too far.
CG: I love that story. Let's close with one final story from The Data Detective, and also from Cautionary Tales. It's one that you and I have discussed before. But I love it so much, that I, I think it's worth revisiting. And it's the kind of intertwined lives of John Maynard Keynes and Irving Fisher. And by way of background, these were the two greatest economists in the world in the first quarter or so, the first third of the 20th century. And both of them were fabulously successful into the 1920s. Both of them made ill-advised bets, uh, on stocks and on investments in the years prior to the 1929 crash. Fisher famously lost his shirt in that crash right after, uh, right after, unfortunately making the, the famous claim that the stock market had reached a permanently high plateau.
And that is where the, the sort of knowledge of Fisher's life typically ends for most people. It's what happened next that you tell in The Data Detective. And, and it's what fascinates me too. Because Keynes also lost a bunch of money in the 1929 crash. But unlike Fisher, he didn't double down on the same mistakes. Whereas Fisher kept investing, he kept borrowing money to invest. And he kept losing money. Keynes pivoted. Um, what is the lesson we should learn about Fisher's doubling down, and Keynes doing something totally different afterwards?
TH: Yeah, I, I mean, I love the story of the, of these two men. Partly because they're in some ways so similar, and in some ways so different. You know, Keynes' last words are often said to have been, "I should've drunk more champagne." Because you know, Fisher didn't drink and was a big proponent of prohibition. So e- in some ways, their characters are very different, in some ways extremely similar. But a- what I wanted to do was just to explore ... Or fundamentally, they're in the same situation, they made the same mistake. How come Fisher loses everything, and Keynes dies a millionaire?
And it's really about Keynes' ability to change his mind. That's the s- that's the simple story. He changes his mind, and Fisher doesn't. But then you, then you go, "Well, why did Keynes change his mind? Why couldn't Fisher change his mind?" And then that's an exploration of, to what extent is it the context? To what extent is the character? And I think it's a bit of both. But Fisher was, I think, more exposed personally, but he was also more exposed reputationally. He'd been much more public about his forecasts. Which made it very difficult to row back.
Um, Keynes, eh, wh- mostly was making these forecasts in private. He's losing money in private. He's embarrassed in private. And so he can kind of, he can back away. That's partly what's going on. But it is also a difference in the two men's character, and how fundamentally predictable they thought the world was. Fisher was in many ways an absolute sort of quintessential economist. He paved the way for modern economics wi- which is highly mathematical. With his view that fundamentally, ev- you know, everything can be quantified, everything can be measured. Ultimately, everything can be forecast.
And Keynes always had this slightly different view that, "Well, yeah. Some stuff can be quantified. Some stuff can be measured. Some stuff can be forecast. But some stuff is just a game. Some stuff is just animal spirits. Some stuff you, you're never gonna get right. And, and if you get it wrong, don't beat yourself up. You know, just dust yourself down and try again." And I think that view that some parts of economic life are a- are just imponderable really helped him. Because when he did get things wrong, he just didn't take it so personally.
And I think both men were brilliant, and both men had really important insights into the way the world works. But if you want to forecast, I think, I think you stick with Keynes. Someone who is interested, is engaged, but, but doesn't take it too seriously. Because that enabled you to, to change your mind. Uh, and there, there was this wonderful comment about Fisher. Not made by Keynes, made by yet another forecaster. But the, this, this guy, a guy called Roger Babson, uh, said about Fisher, uh, "He, he's a splendid citizen. But his problem is he thinks the world is ruled by numbers. But it's really ruled by feelings." And I supposed the argument I'm making in The Data Detective is that it's ruled by both.
CG: Yeah, and I, in the case of Keynes and Fisher, the, the story of Fisher is so sad. Because it wasn't just that he doubled down and he lost all his money. I mean, he, he left in complete penury, dependent on relatives to survive. And died a kind of lonely and broken man. Keynes also, by the way, died, I think, prematurely in the 1940s. But as you said, uh, he was at least reported to have gone out on, you know, on a sort of on a note of like, "I wish I partied even more than I actually did." But the, the story of Keynes and Fisher also to me is one that's interesting in terms of how we perceive outcomes.
Because, you know, we know what happened to Keynes and Fisher now. And as we apply it to their story, you know, if things had gone the other direction, you know, if the stock market had bounced back, and Fisher had made all his money back. And Keynes had made a couple of wrong bets, we might be looking at Irving Fisher and thinking, "Well, there's a man of principle. There's a man of conviction who hangs tough during the difficult times. And wins out in the end." And we might be saying of Keynes, "Well, look at that flip-flopper." You know? "No convictions. No principles. Just kinda goes with the flow."
Uh, and we might be interpreting this story completely differently. Even though I do believe in the case that you make, which is that actually there's a tremendous virtue and mental flexibility. And in the ability especially to change your mind. The story itself in some ways could've turned out quite differently, if the world itself had turned out somewhat differently. Which who knows? It could have, right? And so I, I, I'm just, I'm fascinated by, by the way that we look at a story and we have these perceptions of the virtues and, and the deficiencies of, of characters. But a lot of that I also think is, is driven by what actually ended up happening, right?
TH: Uh, I think, you're, you're absolutely right. And it gets to an important point in this business of using stories to, to illustrate ideas about the world. So for me, it's important to, to, to get the facts straight. Like, what do you think is actually true about the world? What's the argument you're trying to make? Ideally, what does the evidence show? And the Fisher and Keynes story is actually wrapped around this quite deep and long-lasting body of evidence assembled by psychologists led by Philip Tetlock, about forecasting, and about what kind of character makes the best forecasts.
Um, what sort of habits of mind lead to the best forecasts. And it, and it could be true that somebody like Irving Fisher makes the best forecasts. Super smart, always going to the data, um, sticks to his principles, doesn't just blow in the wind. You know, he, he will, he will hang on and follow his, follow his convictions. He's determined. He's te- tenacious. Um, there are certainly stories you could tell where those characteristics lead to triumph. But what the research says, what the evidence says is, "No, eh, the better forecasters are the ones who change their minds quite a lot, who don't hang on too tightly to ideas. And who use a big sort of mix of different thinking styles." People who are much more like Keynes. So for me, I start with Tetlock's work, which he’s been doing since the mid 1980s. Uh, and is now very, very famous. Uh, and then go, "Okay. Great. I'm ga- I'm gonna find me some stories that... illustrate this." Or actually more a case of, I stumbled into the story of Fisher. I knew a little bit about Keynes. I read more about Keynes. And I was like, "Oh, wow. These two guys, this is the perfect illustration of what Tetlock's talking about. But I think you're, you're right. If you start with the story and say, "Well, what is, what universal principle about the world does this story teach?" Well, you're on dangerous ground, because it could've been a different story. And you can find different stories. So I try and start with the evidence, and then find the story.
CG: And that's all for today's bonus episode. We'll be posting links to the individual episodes of Cautionary Tales, where Tim tells the full version of these stories. In addition to a link to Tim's latest book, The Data Detective. The New Bazaar is a production of Bazaar Audio from me and executive producer Aimee Keane. Adriene Lilly is our sound engineer. And our music is by Scott Lane and DJ Harrison of Subflora Studio. Please follow or subscribe to The New Bazaar on your app of choice. And if you enjoyed today's show, leave us a review or tell a friend. If you wanna get in touch, I'm on Twitter as @CardiffGarcia. Or you can email us at hello@bazaaraudio.com. Thanks so much for listening. And we'll see you next week.
Having guided Cardiff through the craft of economic storytelling in the prior episode, Tim Harford returns to explain the lessons of three economic stories from his own podcast, “Cautionary Tales”.
Links:
- "The Truth about Hansel and Gretel"
- "Buried by the Wall Street Crash"
