 So this is a paper about whether we need a new narrative about the 2008 financial crisis. And of course, a thief left. But it's kind of related to some of the micro issues that he was mentioning as not being that important for the macro. But so this work that I'm going to be presenting today is based on some new findings that I have in a paper with the Georgian Nosa in which in the paper, we were visiting this notion that some prime borrowers were mainly responsible for A, the boom in mortgage credit during the 2000s, but also the spike in defaults that we saw during the housing crisis. And in fact, we show and we sort of explain in the paper why we come to a different conclusion from a purely measurement issue, which I don't have time to sort of get into today. So I would encourage you to read that paper if you want all the details. But in fact, the distribution of mortgage credit during the boom was very similar to what it has been historically. So high credit score, high income borrowers got mortgages at similar rates as they did historically. And there wasn't a massive rise in mortgage credit towards borrowers who typically did not get defaults, did not get mortgages in the 90s or any time prior. And we're actually not the only ones to have shown this with different data. I think this has become a new sort of stylized fact about the boom in the 2000 that there wasn't this massive increase of credit to low quality borrowers. Let's put it this way. Instead, the distribution of mortgage debt was pretty standard by historical criteria. But we did see during the housing prices of 0.709 very high rates of mortgage default among prime and high quality borrowers. And so the question is, why did we see that because that was an historical anomaly. And in that paper, we first point out that actually most of the rising defaults by high quality borrowers in 0.709 periods was due to so-called real estate investors. So these are borrowers who have multiple first mortgages. And hence, they cannot live in all their homes. So at least some of their properties have to be investment properties. So this obviously raised a new agenda because investors have been somewhat neglected in the academic economic literature on a real estate housing market, partly because it's hard to find them and see who they are in the data. So we have a particular approach which I will explain a little bit later. Also, from a modeling perspective, it's already very hard to develop quantitative macro models with a real estate sector in equilibrium. If you throw in investors, it becomes even harder, which is what I'm trying to do in my current work. But it's sort of essential to think about a number of important questions that this new stylized facts sort of point to. In particular, what drives investor activity? Is it an increase in credit supply? Is it unrealistic house price expectations? Is it a response to housing demand, in particular geographical area, due to moving on the population towards, for example, urban center? What is the relation between investor activity and house price dynamics? Did investors' high default rate exacerbate the decline in consumption and employment that we saw that was associated with the housing crisis? And also, given the high default rate that I will document later in the talk associated with investor mortgages, should we regulate investor mortgages in a particular way? So these are the deep questions that arise once you realize the large role that investor had in the 07 and 9 crisis. So what I'm going to do for today, though, is I want to give you extensive evidence, which is going to be purely descriptive, on investors. In particular, who are they by income credit score and age? And there are some interesting facts there. How do borrowers become investors? So how do people transition from not being an investor to becoming an investor? And how do they transition out? And I'll show you that, essentially, there is an investor class. Some people just are investors, and they have a high churn over the numbers of first mortgages. And then how much do investors borrow? And I will show you that investors have much higher leverage, whichever way you measure it, than conventional borrowers who just have a mortgage for their primary residence. And they default at much higher rate. But particularly, I will show you that they tend to show symptoms of defaulting strategically, meaning they default, but it looks like they could continue paying on their mortgage. And then, if I have time, given that we're shortening the session a little bit, I'll talk a little bit about the spatial distribution of investors, where there's a huge amount of it originating. And I think that could be very informative to study more in detail to really understand some of the deep questions that this investor activities brings up. So very briefly, I use credit report data. In particular, it comes from the Experian Credit Bureau. So if you know what's in your credit report, you know what's in this data. So all types of consumer loans, except payday loans, your information on balances, number of products, whether you're delinquent, by how much you're delinquent, public record, and so on. It's quarterly. And my data starts in 2004, because when you buy the data, you can only go back into nine years. Credit bureaus have to destroy any data that's older, technically, than seven years. So what I have in my data is very much a function of when I bought it, which was 2015. So that's just to explain the start of the data. So how do we identify investors in this data? So the way we identify them in our first paper that used Equifax data and sort of following the literature, paper from my colleagues at the New York Fed, was to look for borrowers who have two or more first mortgages. And you know, a first mortgage is a primary lien on a property. So if you have two first mortgages, it means that you have two properties. Now what this misses is people who just buy houses cash, and they may have multiple properties, and they're not borrowing for any one of them. Obviously, we're going to miss those from the credit report data. And that's a limitation. On the other hand, if you're thinking about the effects of investors on the mortgage market and the fragility of the household sector and macroprudential policy, maybe you care less about these cash-only investors, though, of course, they would matter a lot for house price dynamics. And so we are not seeing those investors. So investors are borrowers that have two or more first mortgages. For some of the analysis, I'm going to break it up, two, three plus, and so on. And for some of the analysis, I'll just sponge anybody who has two or more. Of course, somebody with two first mortgages might have a vacation home, right? Or it might be a home for a relative, and so on. Three or more, that's actually where you see the most striking difference in behavior. So we're sort of more confident that at least one of those properties is an investment property. Now, so this is documented in our original paper. So where we have data going back to 99, but it turns out that the surge in investor activity actually started in late 2004. You don't see anything up until 2004. So let me give you a sense of this. So this is the fraction with only one of borrowers, with only one first mortgage. That would be the blue line, and it's measured on the left-hand axis here. And this is the fraction of borrowers with two or more first mortgages among borrowers that have at least one first mortgage. And you can see that this is measured on the right-hand side axis. And you can see that the fraction of so-called investors went from about 9% in 2004 to a peak of about 12% in just before the crisis. And then it declined dramatically. This is the log variation. So you can think about it as the percentage variation from the first quarter in the data. And this is the percentage increase in the fraction with one or more first mortgages, which was about 10% in the late part of the boom. But the percentage increase of those who we refer to as investors was nearly 25%, so twice as large. So this is just a surge in investor activity, which was a very stark phenomenon. And so if we break it up by number of first mortgages, again, this is the fraction of only two green line or three or more right line here in percentage terms. And this is the log variation of these fractions, which is a little bit hard to see. But this is just to show you that the increase in the fraction of three or more was nearly 40% over the short three-year period. Only two was about 15%. So there's this surge in investor activity. And the next thing that I want to show you, which is sort of an extension of what we have in our original paper, is the difference in default rates across investors and non-investors. So this is a fraction of borrowers. We'd only one first mortgage, blue line, that have a 90-day or more past due delinquency on any mortgage. And you can see that it goes up just before the crisis. And it peaks at about 2.25% here in 2009, early 2010. But if we look at investors, so people with two or more first mortgages, the rise is much higher. And the peak is nearly close to 4%. Now, if we look at foreclosures, the difference between investors and non-investors, and something I'll return to later, is even starker. So if we look at foreclosures for non-investors, obviously there's a rise. These are very high rates historically. But it's very modest compared to the rise in the foreclosure rate of investors, which reaches a peak of 1.5% here at the high prices. So what I want you to take away from this is there was a surge in investor activity. It was relatively large. But what's really striking here is the difference in default behavior between investors and non-investors, which is a very, very large difference. Now, if we look at the share of all delinquencies and all foreclosures driven by investors, remember that the investor share is about 15%. So the share of delinquencies by investors, which will be the screen line, and is measured on the left-hand side axis, you can see peaks are about 23% at the crisis, whereas 14% of all borrowers are investors. So the share of delinquencies is twice as large as the share of borrowers who have this feature. But if we look at the share of foreclosures, which is measured on the right-hand side axis here, you can see that the height of the crisis, the share of investor foreclosures was close to 50%. So 50% of all foreclosures were accounted for by about 30% to 14% of all borrowers. So that's a very, very stark difference in behavior. So let me give you a sense of who these investors are. So this is a share of investors by quintile of the household income distribution. And you can see that the share of investors is proportionately large in the top quintile. But you can also see, which is 16%, goes up to 18%, much, much lower, very large gap for the lower quintiles. You can also see that in percentage terms, the growth in investor activity was slightly larger for the lower income quintiles, though investor share is much higher for the higher income borrowers. If we look at it by credit score, so this is different types of credit score categories, you can see that most of the growth in investor activity was for prime and near-prime borrowers. So going back to the subprime narrative, near-prime borrowers are borrowers with a credit score from 600 to 660, so they are less than prime, but most of the growth was indeed for prime borrowers. And you can see that the income distribution of investors didn't change very much before the crisis. The only anomaly that we see in investor activity pre-crisis is the sharp rise in the fraction of investors who are young, or the fraction of young borrowers who become investors. So you can see this is by age. So the orange line is 20 to 29-year-old, all the way to 70 to 80-year-old. So most investors are middle-aged, perhaps not surprising. But what we see in the boom here, there's a nearly doubling of the rate at which young borrowers become investors, which is really interesting. So these are high-income young borrowers. Nonetheless, they might be less experienced and older investors that might drive some of the differences in being here. Now let me show you a little bit of information of how borrowers become investors. So to see this, I'm going to show you some evidence on the transition from a given number of mortgages, say 0, to another given number of mortgages, say 1. So 0 to 1 is you weren't a homeowner, you become a homeowner, and you borrow. 1 to 2, you become an investor. 3 plus, you become a more intense investor, if you want to put it this way. So this is the 0 to 1 transition. That's the red line. And the 0 to 2 plus transition, that's the blue line. You can see that the 0 to 1 is measured on the right axis. So actually, we don't see. We see a decline in these transitions over this period. But the 0 to 2 plus transition kind of rises here in 2004. So there's an intensification at the rate to which people go from having no mortgage to 2 or more mortgages. So these are the transition from 1 to 2 and from 1 to 3 plus. As you can see, 1 to 3 plus is a very small rate here. 1 to 2 is about 3%. And you can see that it drops dramatically during the crisis. But what I want to show you next, which I think is quite interesting, is the transitions from 2 to 3 and 3 to 4, which are measured on the right graph here. This is the graph from before, 1 to 2, 1 to 3 plus. What you can see is while these transitions are in the order of 3% and less than half of 1%, these transitions are respectively 5 and 11%. What does this tell us? If you already have two mortgages, you're much more likely to get three or more. And if you have three mortgages, you're very likely to get the fourth one. So this really seems like there is an investor class of people who essentially are investors. And so transition into a high number of first mortgages. And this may be driven by flipping behavior, but in any case, they are experts at this at some level. Whereas most borrowers just have one mortgage and they're very unlikely to transition to 2 or 3 or more. Now, let me show you what I think is the most striking results, which is the leverage as well as the default behavior, particularly the strategic behavior. So it turns out that investors borrow a lot more. This is obvious. They have multiple first mortgages, so they have higher mortgage balance. But they borrow more in different ways. So this is the average per mortgage balance by number of first mortgages, 1, 2, or 3 plus. So this is the per mortgage balance. So what you can see that investors, 2 and 3 plus, have much higher average balances on each mortgage than non-investors who only have one first mortgage. So not only do they have higher mortgage balances because they have more mortgages, but on average, they have larger mortgages. What's even more interesting is that investors, relative to non-investors, are more likely to have second mortgages. So this is the fraction that have a second mortgage by number of first mortgages. You can see that it's nearly 5 percentage point higher at the height of the boom, the propensity of investors who have a second mortgage versus non-investors. And this is the fraction that have HELOC lines. Again, this is twice as large, about 35% at the height of the boom for investors and non-investors. And perhaps most importantly, if we look at the payments on first mortgages and second mortgages, that's a fraction of their income at a monthly basis, for investors only on first mortgage, the payment to income ratio is about 35%, whereas it's about 16% for non-investors. And then when we go to second mortgages, so this is monthly payment to income for second mortgages is about 8% to 9% for investors and it's only about 6% for non-investors. This is conditional on having second mortgage. So all these measures tell us that investors are more highly leveraged than non-investors, which may perhaps then explain the difference in behavior. So I already in default behavior, I already showed you that investors default at higher rates, they have higher delinquency rates and they have higher foreclosure rates. What's really interesting is that investors who become delinquent have a much higher durability of transitioning into foreclosure as opposed to curing their delinquency. So this is a transition rate from a 90 day delinquency to foreclosure by number of first mortgages. So the green one is only one, red line is two and the purple line is three or more. So you can see that there's a stark difference here in the intensity to go from a mortgage delinquency that's quite severe, that 90 days, to a very severe mortgage delinquency which is a foreclosure leading to repossession. And what I'm also gonna show you is the fact that there is evidence suggesting that investors tend to default strategically. So the question related to that is how do we measure it in the data? So we use a measure that is sort of based on an industry practice or definition, which is to say the following. So you default strategically if it looks like you go from being current or having no delinquency to a severe delinquency on a mortgage but you have no other delinquency. Whereas you default because you're distressed if you show a number of different delinquencies on your credit reports on different types of products. The idea is if you go from being current to severely delinquents very fast just on your mortgages but you're able to make all your other payments maybe you have a reason to default on your mortgages but in fact you could indeed continue paying but you're able to make your other payments. And so this may be a strategic default on the mortgage. Obviously this is a proxy. It's not, we don't know. We can now ask these borrowers whether they default strategically. If we could they probably wouldn't tell us but it's a way to capture strategic behaviors opposed to distressed behavior. So this graph shows the share of all defaults that can be classified as strategic for borrowers that have only one versus two or versus three or more first mortgages. So you can see that for all borrowers there's an increase in the share of defaults that can be classified as strategic during the crisis but the share of strategic defaults especially for borrowers with three or more mortgages is disproportionately large compared to other borrowers. It goes from about 20 to 25% to a peak of 35% of all defaults for borrowers with more first mortgages possibly being considered strategic. What you see on the right-hand side here is the share of defaults that can be classified as distressed. And you can see that it's higher for borrowers with only one first mortgage and slightly lower for borrowers with two or more during the boom but as we get to the crisis the gap between investors and non-investors open up consistently with this gap here in the share of strategic defaults opening up. So given that I haven't shown you geographical information I'm just going to just conclude with the slide. So what do we know about investors? We know that they are substantially more leveraged and they are more likely to default strategically despite the fact that they look like they don't, they have high income, they have high credit score and they're not the types of borrowers that you would expect to default. Now going back to what policy questions this raises I would argue that it's really important to think about who is defaulting and why they're defaulting in order to structure policy responses to a crisis or an increase in defaults but also that the macro implications of investors versus a more general class of borrowers defaulting are also quite different. And so that's why I think we really need more research on the investors that seem to be very keen in sort of driving housing market behavior and equilibrium fluctuations in the housing market to understand what their role is better and thinking about policy that sort of focus them on them a little bit more. So let me go over the key takeaways from this paper. Stefana presented really well those key stylized facts and descriptive facts about investors. There are about 14% of all borrowers that had a much, much larger share of foreclosures than previously known. Almost 50% of foreclosures during the peak of the crisis in some months. And very interesting, they're way more likely to default strategically according to the definition or strategically default using the paper. Almost 35% of them at the peak of the crisis. And then more interesting stylized facts about the activity late in the cycle in high-density metro areas and in areas of high-priced fluctuations. And those key takeaways, remember, are related to subprime lending in the 2008 crisis. Do we need a new narrative? That's the title of the paper. I'm gonna do this discussion two ways. First, I'm gonna quickly go over a couple of things that could be improved in terms of the definition of those variables. They're not major criticisms, they're literally new work. There's an extra room to improve it. And they're related to the definition of those variables. First of all is the definition of investors at least to first mortgage transactions. I really like this definition. I think it's the best one that we have right now. And better than most other proxies used by other papers such as flippers or houses that are bought by companies that will piece or seize even when they're individuals, not just like homes for rent and so on. Now there are certain limitations. So you have a smaller, more limited set of investors just because of that. You don't have those companies. You don't have the more professional investors. I think you don't have the households that named themselves as an LOP or LLC, I think. So that's an issue. And I'm curious to know what's happening to those and if you can identify them somehow in your data. My own research, I found that they don't do things very differently than households and the prime borrowers, but I don't know. In addition to that, you're calling investors and I think that's okay. But then you have the set of homeowners that have vacation homes that have multiple homes because maybe they have multiple jobs in different cities or they have homes used by family members. And I think they're all in that mix. And I think it's important just to explain that in more detail and do as much as you can. And to provide robustness tests. And maybe even compare to the rest of the literature that used some of those definitions. Again, that I think they're not as good as yours, but it doesn't mean that you have a perfect metric here. And I have here some examples that can you identify flippers to the more professional investor that accepts similar behavior or not? I think it's very important. Second one is the definition of strategic default. It's defaulting on one mortgage and not in any other debt. This is a pretty stringent view of strategic default, which I like it too. I think that's the best one that we have so far. That's great. But again, it's a prox. We don't really observe the homeowners deciding what to do and how they're making those decisions and especially how they're considering what to do in a moment of potential crisis. And or because of some income shock or because they're seeing their investments not a team that return or they're afraid of additional fall in prices. So given that, there are different versions of the meaning of strategic. If you look at the old literature in all the theories, mostly about one household, one family, one job, word about negative equity, oh my God, I have too much debt in this house and there's all sorts of trade-offs related to consumption value at home and the hitting the credit score and so on. And in the paper, you talk a lot about it, how the investors have different incentives, but I'd like again to do more, to think about the theory a bit more, how given how there is a portfolio of houses versus one home, and incentives are so different. How should you think about it? Moreover, there may be different degrees of strategic default in your data than you classify, because sometimes it's not in any other depth. How about, you know, send the phone, send that? I think your data is so rich that you can have several versions of strategic default. And again, I'm really curious to see how they behave and what you can tell us about them. And then similarly, engage with the previous literature, like this paper by Gerard et al, where they also find very big effects that almost, if I remember well, almost half of the foreclosures were strategic in that paper as opposed to being a consequence of a job loss of a negative income shock. So in terms of the magnitudes, I think our paper more or less matched those results where your data's just much better than their work. And of course, you already talk about key policy implications. This is critical for any type of policy design, bailouts, and the feasibility, the desirability of them. Let me spend more time talking about the title of the paper. So the title of the paper is this new narrative, but it mostly talked about, you know, investors in part of it because of previous work that is focusing more on this new narrative. And that's the thing that's the most important message for this paper. What exactly is this old narrative? You know, if you need a new, you need it to describe the old one in more detail. And the old one, in my view, is starts with the popular press in all those media rants that came with the great recession, the initial, the crisis, pretty much blaming poor and minority followers because they're the first ones to the fall and to foreclose on their mortgages. Is that still alive? Probably yes, if anyone checked Twitter, especially, you know, the president saying all sorts of things about migrants and poor and minority is blaming them forever. Back then, the blame was, you know, housing crisis. Today, other things. Now, in the academic press, it's basically Mian and Sufi 2009. And Mian and Sufi was one of the early papers, the most cited paper, almost 2,000 citations. And they basically say, you know, that the mortgage crisis was caused by the exponential credit to those individuals, those families with low credit scores, mostly poor individuals and minorities, a lot of really high share of minorities. So, and that became the dominant academic view of what caused the housing crisis, the housing bust. Is it still alive? That's, the answer is more clear, is no. So that narrative is completely dead. It has been completely debunked, okay? And that's why we need a new narrative because this one is gone. And it's gone because of all those papers by a number of researchers, including Stefania and her co-authors, showing that, and that's what Stefania briefly mentioned at the beginning, the expansion of credit was widespread. What's a middle-class event? It was the investors' event. In very, very, very late in the cycle, credit was expanded towards poor people, minorities, people with low credit scores, okay? I have a couple of figures here. Part of, in my way, part of the problem is not that their chief's not here, it's not that he has a bad person, it's that there is, there definitely should not relate to the president. The research was done very, very early in the cycle. Even though it was published in 2009, the date was up to 2007. And there was a huge demand to produce a sudden answer about what was going on. And when there's this huge pressure to produce answer, that's what we do. We say, well, let's investigate this economic event with the data that we have. And that's what they did. So, but then the problem is in 2007, they had very, very limited data, only a few MSAs, only the data for subprime, they couldn't plot figures like this that shows the share of funding sources for all homes, not just recent transactions. And then when you do that in all those other papers in this work, you see that prime loans, the share of prime loans is increasing during the 2000s. Subprime loans is definitely increasing too from eight to 20%, but at the expense of subprime governmental loans. It's almost like a crowd out, one to one. That's just what happened. And again, in hindsight, with more time, we now know it is, it didn't know in 2009. And same thing with the foreclosures. So when Emmanuel and Sophie wrote that paper with the data in 2007, everything was still in the very beginning and they will deserve more foreclosures in the subprime sector at much higher rates. But then over time, the prime just dominated. You had way more foreclosures in the prime sector. And what Stefani is doing right now, he said, let's look at it in more details. Are those all households? They're all homeowners, or they're investors? Because maybe a really large fraction of those foreclosures, or we should blame, I'm not sure it blames the word, but blame on investors. And I think that that's a very important part of the new narrative. I don't think we still have a completely new narrative, even for the Great Depression, first to study it today, sign this paper. So I think for the Great Recession, in the years to come, I still see many papers and we'll cover many new facts about it and then try to figure out an overall theory to deal with the situation. But let me give you some facts and this is a very limited set of facts. See how complex the problem is. Those housing bonds actually started at the local level in the mid late 90s. Nothing started in 2004 or 2005. It's mid 90s. And in both coasts and spread over the country, it started with fundamental shocks, both related to supply constraints and real wage gains of the people that initially bought those homes. Now, it may have a small importance of behavioral factors and not even shielded, but the empirical work by Sue showed that some behavioral factors were important too. So it's not just fundamental, it has some behavioral on that too. The financial sector was important, credit was relevant, but it happened with a lag, a lag of at least two to three years. You have those local markets booming, prices increasing and only after that you have an increasing lending. And in many papers that's talking about it, including the subprime papers. And then very late to the party, and by the way, those financial sector contribute to exacerbate the boom. And then very late to the cycle, you have the investors, that's the paper by Stefania. You have speculation, this is the paper by the Fusco, Nathanson, Zwick. Stefania would be great if you could replicate some of those results and share data, because I have better data. They have a slightly different view from you. I think you're saying they come late in the cycle and that's what I wrote. I think they think it's a bit earlier. It would be nice to see that comparison. And then in worst of all, the poor people with the lowest credit scores and the minorities, they arrive to the party extremely late, buying homes for the most part in 2006. The worst possible year, because that was the peak of house prices, one year before the crisis, and they're the first ones to default. Stefania didn't show the data, but the foreclosure rates for minorities is extremely high in 2007, 2008, because guess what? They're the ones that lost their jobs first and bought the house the latest and suffered the most from the cycle. And now we're learning that the investors had more or less the same behavior, but those households was because of job loss, income loss, the investors more because of strategic default. And then you have other factors here. So it's a very complex story. It's a very complex cycle of facts. It takes a village. There's no such a thing as one paper. This is the paper that describes the whole thing or a theory that describes the whole thing we still don't have that are very far from that. It's gonna require a lot of time, a lot of new papers, a lot of replications, which means you really need to be a bit humble and present any type of early estimate or any type of estimate, because it's very likely that you're picking up a very small part of the story. And I think, you know, it's the finest in quality is doing a great job in providing more inputs to this narrative. I think it's great. Congratulations to the work that they're doing. I want to see more. But keep in mind is what there's still a lot to be learned about so many interconnected mechanisms, supply constraints, the many shocks for commercial market responses, investigative behavioral factors, a lot of heterogeneity in how all those agents behave, many spillovers, both geographic spillovers and across institutions and homeowners, all the governmental regulation interventions. In more and more, we're learning about the pieces and bits and pieces about this puzzle. If we actually get there, I hope it's not gonna take a hundred years or 200 years like the Great Depression, but I'm a bit optimistic, moving forward. Especially because of papers like, it's the finest. I just have a quick question. Do you think the investor activities is reflective of credit supply shocks or credit demand shocks or a combination of both? So I'm sorry, I may have missed something in the beginning. So the credit scores are for individuals, but we're also talking about households. So how do you reconcile those two? Because I was thinking about this, and I said, wait a minute, I have two first mortgages, I'm an investor, but my household has three. We don't view ourselves as homeowners. This is a messy issue. Two questions, and then one in the, yep. Yeah, I would just question the thought about the fact that non-investors are often people who have their mortgages for a long time and pay them off, therefore at the lower leverage, whereas investors tend to maximize leverage. And also, of course, people in my experience tend to try much harder to avoid default and foreclosure if they're actually living in the house, it's being foreclosed on psychologically. Okay, I'll actually start with the last question, if that's okay, because we sort of talk a lot about this in our original paper, and we argue that exactly one of the reasons why you should be expecting higher default rates for investors is that they don't have to pay the cost of having to move, having to relocate, having longer commutes, your kids have to change schools and so on. And actually, the industry is very well aware that on average, investors have higher default rates. So for GSEs, concept mortgages, if it's an investor mortgage, there's a pricing scheme that charges you higher rates of interest rates and insurance. And another reason why investors have higher default rates, they cannot protect investment properties in bankruptcy if they do become actually financially distressed and they might have incentive to leverage more. So that's, I think, if you are an investor, you would have a lower cost of default because of these reasons, and that's why one of the reasons why we observe higher default rates for investors. But then, going back here, but that's sort of a measurement issue. So this is individual level data. I have no way to match couples. So all the mortgage balances are adjusted for joint accounts. So I'm not double counting mortgages or mortgage balances, but if I see you in my credit report data, you're an individual with a certain credit score and there's a mortgage balance attached to you which is adjusted for joint accounts. So I'm getting certainly the level of balances and on the number of mortgages, right? I have no way to link households. So that's sort of like a measurement error if you want or issue problem, which is intrinsic to this data. There's not much I can do about it. With respect to your question, we do not actually take a stand or whether it's a credit supply or a credit demand shock. It could, so what is true is that in late 2004, exactly when investor activity surged, there was a big decline in the spread between mortgage rates and other long-term rates and in particular for non-conventional mortgages. And so this coincided as a timing factor with the surge in mortgage activity. So you could argue there was a credit supply shock and investors took advantage of it. You could also argue that given that the industry was very well that investor mortgages are more risky if there are unrealistic or over-optimistic housing price expectations and even if you make a risky mortgage, you don't think you're gonna lose much from it because house prices are gonna go up. You're going to give more favorable condition to a risky mortgage and that led to the surge in investor activity. With our data, we are not taking a stand on why that happened. What we argued that identifying who, if you want benefited or contributed to the boom and then who defaulted is really important for thinking about particularly policy responses and how we interpret other episodes. So right now there's actually has been a surge in investor activity in the last two or three years. It's somewhat different. There are more institutional investors and so on. But I think the fact that we were looked investors in the 2000 booths is shaping the fact that people are not particularly worried about the surge in investor activities. Though a lot of things look similar to what they did in the early 2000s. And other than that, if I can take a minute to just respond quickly. Very grateful for the comments. I just want to say something about identifying strategic default. So the way I was originally thinking about strategic default is that you defaulted just because your house was under water and it wasn't a viable financial investment anymore. But then the findings that I have on the high payment to income ratio for investors coming from the fact that they had so much such high leverage sort of got me to thinking that you could be strategic in defaulting because you can't make payments. And that would make it hard to distinguish a strategic default for an investor that has high monthly payments on all their debt products from maybe a low income household who loses their job or their hours are cut and are not able to make payments. So I think with better data perhaps we can make some progress on different types of strategic defaults or just defining strategic default better. And then I want to conclude with this issue of data because I think a lot, and this is sort of dovetails on what you know what Fernanda was talking about. We do not have good data in the United States because we either observe bars quite well like I do in my data or you observe lenders quite well or you observe products. So out A mortgages versus GSE mortgages we do not have a data set really where you can see all aspects at the same time. And I think this has caused a lot of the confusion because in the media very often subprime mortgages are mortgages made by non-conventional lenders that are listed in inside mortgage finances, a bunch of institutions who make non-conventional mortgages but they might make them to high credit score borrowers but because they're investor mortgages they're not gonna be GSE mortgages they're gonna be out A mortgages. And we do not have a good data set where you can see all the aspects. And I think this has really fueled the confusion with the debate about who borrowed, who defaulted, what types of loans and it would be great to just have better data.