 and comments from the public. And then Laura will have time to react. Unfortunately, I don't know your name, so I just can't point. Yeah, I wondered if you could consider, because the investment behavior is so deviant between the data and your model. And it seems like you could explore the justiniano's idea of the marginal efficiency of investment shock. And I mentioned that, because that proved very useful in work I did with Jonathan Eaton and Brent Nyman, where we needed a kind of real shock that would move investment spending around. And maybe it feels too easy, and yet it was kind of striking in your pictures where you want something that makes you, suddenly you don't want to invest. It's not so much that you lost capital. It's that you realized right then, if you invested, you probably wouldn't get very much, so. Okay, thank you, three over there. It seems to me that you are endowing your agents with a very inefficient technology to estimate tail risk. This kernel estimation, I don't think any econometrician would use a kernel estimation to estimate the tail. They would rather use extreme value theory and try to estimate the rate of decay of the distribution. So once you do that, my feeling, especially if you incorporate data up to the great depression, is that your estimate would be much less sensitive to the tail event. And would that have any implication also for the prediction of your macro model? Thank you, your neighbor. Also on the great depression. The great depression must have come as a surprise to those who experienced it and must have led to an update in people's perceived distributions. Why didn't we see the same pattern after the great depression? If you had extended your plot to a great depression, you would see that the economy reverts back to trend. And not only that, but it even overshoots it, a linear trend. Okay, the gentleman behind you. Thank you. As someone already said, I think what we all learned was that, that's why I'm convinced that's my narrative. What we learned is that we were not on the trend we thought we were on. This is very controversial by some, but I think it's compelling in case. And there is no, so I don't really understand why you said it couldn't be a surprise about TFP. I mean, I think a strong narrative is that during the boom, we overestimated TFP and then we realized that we did and now we're on a different trend. Now your result, your construction is excellent on explaining the fact that we understand now the downside of such a mistake and you're sitting there as a price data. But I think this interpretation is much easier to square with other facts. So I don't understand why you say you didn't want this to be a surprise about TFP. Maybe you're gonna explain. Okay, thank you very much. Any more questions, comments? I don't see any for the moment, so Laura, the floor is yours. So first, I wanna thank Alberto for a very thoughtful and very generous discussion. I think asset prices are tough to look at because they're a mix of things. Remember, firms here are delevering when risk goes up. They're reducing debt, right? And so that's gonna affect equity prices. It's gonna make equity more valuable. On the other hand, you've got more risk. So you got these two things moving in opposite directions. It's really hard to just look at price levels for either debt or equity and figure out what's gonna happen when the mix changes. The truth is it could go either way with a slightly different calibration and that's why we don't wanna rely on it. The VIX is low, the VIX is not uncertainty. The VIX is volatility. Volatility is not high in this model. It's high at the time of the financial crisis and then it's low again. The question of, do we know that we don't know? No. In this paper, they re-estimate the distribution and then take that as truth. Is that ideal no, it would be a lot harder model to do. And I'll tell you, we did some experiments with thinking about what if tomorrow you had a different distribution and what if two periods from now you had a different distribution and sampling all of those and seeing how different the policies were and there were very minute differences. But one thing we would miss that's important and actually this is based on work Pierre Collin Dufresne here has done which is if you know that estimates of a model are uncertain, it's a source of long run risk. So if we had a model where a long run risk were an important determinant of asset prices, that's where that assumption that we acknowledge our uncertainty about future distributions would bite. It would introduce knowledge of a new Martin Gale. Would if policy beliefs change, would that change things? Yes, and in fact that would be the role for policy here. It would be to have some policy that actually changed people's beliefs about the possibility of future tail events. If you could implement something that credibly removed the tail risk that would be effective here, but that's a big if. Thank you for the suggestion about the marginal value shocks. Why did the Great Depression not last? I'd say World War II. I don't know that I have much more to say about that. There certainly was some persistence of that shock. It dragged out for a while and then we entered a pre-war phase. And then lastly why didn't we do this for TFP? So two problems with TFP. One is the measured productivity shocks during this period were actually rather small. So we wouldn't get a lot of kick out of it. And the second is we wanted this to be consistent with asset prices because we wanted to use asset price data, options data as over identifying moments as evaluations of the theory. And most TFP driven models are very difficult to reconcile with asset prices. One of the reasons that Francois Guerrero wrote this model is that these capital quality shocks allow for there to be large variations in the returns to capital that with not so much macro volatility. And it's very difficult. I don't know whether these marginal value of capital shocks do that. They may, I'd have to look into that. But this was specifically constructed to have some meaningful thoughts about asset prices. That being said, no paper explains all the ups and downs of the asset market. Where that's an impossible barrier. I will not say that this tells us why we have such high asset prices today. There are a lot of things going on in the world and this is just hopefully one of them. Okay, thank you very much. Any, yes, another one please. So coming back to my point before. So I think when you say that the estimated TFP shocks were too small to have any action is because of the way they were estimated. Did not really allow the possibility that we had a mistake for several years running during the credit boom. Misunderstanding, overspending, would borrow money for something that we attribute to be actually TFP. So I think if we were to redo that calculation, it wouldn't be clear at all the day shocks were. The surprise perhaps was we thought for a number of years we were growing because there was rising productivity. Actually we're just borrowing and spending. Now if you recalculate the path, then you come to a different estimate of what might have been a mistake. I think that's, I mean, no, everybody knows that not an empiricist. But I think this is, someone should do it. That's possible. I did not want to invent a new way of measuring TFP. We took standard measures. We took utilization, adjusted. Those didn't seem to work. But what you don't know. So if we have the wrong way to measure because we have the wrong expectation and the wrong inference. And everybody does and everybody spans. And therefore, if everybody were right, our measure would be right. Then we discover we were wrong. That's the real discovery. And that's what produced the class. That's something you can do with your framework. Okay, thank you very much. Thank you back to your paper, Laura. So there seem to be sort of two thoughts. I should say there was maybe a minority that thought that there may be another crisis in the making. I'm thinking sort of about Ulrike, Mom and Yay's work on depression babies and the like. So could we, I know that you looked, there were some questions already on what happens if we were to extend the period to the Great Depression. But could we use your framework to actually sort of estimate how much memory loss there is in society? I think you could do that, no? Because it's something that has intrigued me. I think there are two camps there, but maybe one is very small and the other is very large, but maybe you could fit the data somehow. So we did some experiments where we discount old data. The behavioral foundations of that are a little questionable, but it is a question that comes up and it seemed an exercise worth doing. The short answer is about 1% per year discounting seems to generate, if we then include the fact that there was, there has been a financial crisis before in the Great Depression, that seemed to square with the size of the decline that we saw. Okay, so much about the Alzheimer's effect of society. Any more questions, one more please. I think also demographics should matter in the sense that if you have a reshuffling population that is growing very fast, the average memory should become shorter and shorter. So that is related also to why the Great Depression was showing less persistent perhaps because the growth of population was faster at the time. And the other is that prior to the Great Depression there were other rare events that were in the memory of people that were faced with the Great Depression. Whereas this great recession was preceded by the Great Moderation. So people were forgetting because of the Great Moderation. So I think all these features seems to be consistent. Thank you. Thank you, Mr. Blanchard. On the Great Depression and the Equity Premium, if you compute the Exxon to Equity Premium from 1929 on, it basically went up enormously just after the fall in the stock market. Between eight and 10% at that time. And then it slowly went down for about 30 years. And there's a well-known saying by Paul Samuelson which is that basically the memories of the Equity Premium disappeared one death at the time. And so I think it's very relevant to what you discussed. Yes, thank you. Okay, thank you very much. I don't see any more. So I thank both Laura and Alberto for the paper and for the discussion and all of you who asked questions. And so I think we learned now how transitory, even very small, unlikely events, but extreme events can change beliefs and also change macro outcomes. But at least this institution, as it was said, as a policy institution tries to change the beliefs of the people again and via statisticians hopefully supply all the data to change the beliefs in this sense so that you don't have wrong beliefs. With that, we move to coffee break. There are 22 minutes till 16.45 and the next session will start. So enjoy your coffee and thanks again for your questions and contributions. Thank you.