 I'm Valerie Jenis, the Dean of the School of Social Ecology, and I want to welcome you all to this breakfast, which is the inaugural presentation of the Regional Progress Report put out by the Metropolitan Futures Initiative in the School of Social Ecology at UC Irvine. It's really a pleasure to be here to introduce this report because I think it's entirely fitting that the Metropolitan Futures Initiative and the particular report that you're going to hear about today comes from the School of Social Ecology at UCI. The School of Social Ecology is comprised of three departments and seven research centers, all of which share a common commitment to interdisciplinary research that is problem-driven and makes a difference in our communities and therefore makes a difference in our lives. And this report in many ways that you're going to hear about today exemplifies that commitment. Before we get started and get into the presentation, however, it's really my honor to introduce the Chancellor of the University of California, Irvine, Dr. Michael Drake. Many of you know Michael Drake in the audience. You know him as a nationally recognized academic and administrator. I know him as a passionate leader who cares immensely about the university and the larger community it serves. His history at the University of California goes back some 30 years. We were just making jokes about our age up here, so I'll say some 30 years, where he began as a medical student and thereafter became a noted ophthalmologist who served at the UC San Francisco School of Medicine as an administrator and as a leader, a physician, a scientist, a teacher, and an internationally known expert on glaucoma. In 2005, Chancellor Drake came to UC Irvine from the University of California Office of the President where he oversaw the health sciences for the system. At UCI, the Chancellor has ushered in what we call a new era of excellence. He's been at the helm as we've launched many new programs, for example, in public health, pharmaceutical sciences, and nursing sciences. As many of you know, he also is the leader as we open to the first new public law school in California in more than 40 years, and just earlier this month they graduated their first class. It was a wonderful success. More close to home for me as the Dean of the School of Social Ecology, under Chancellor Drake's leadership, we launched our new Masters of Public Policy Program this year with our first cohort of graduate students joining us last fall. To ensure support for all of these programs and all of the students and the communities they serve, Chancellor Drake has led the campus on a $1 billion campaign and has raised over $718 million towards that comprehensive campaign. Also under his leadership, the University has enjoyed increasing popularity as the University of Choice among students. This last year, UC Irvine received nearly 70,000 applications for admissions, including a record number of applications from out of state and international students. Likewise, the magnitude of the quality of research and the volume of research being done at UCI continues to soar under his leadership. Today you're going to hear just one example of that high quality research. Now as I anticipate turning the microphone over to the Chancellor and letting him tell you a little about the project here, I'm reminded of something that I appreciate immensely about the Chancellor. As a person well immersed in health issues, I'm always appreciative and grateful that he thinks about health in the grandest of terms and that includes thinking about the health and welfare of our communities. It is therefore entirely appropriate that he be here today to help introduce this initiative and this report, which shares that goal of caring about the health and welfare of our communities. It's really a pleasure to introduce you to Chancellor Michael Drake. Thank you very much, Dean, and good morning, everyone. Nice to see so many friends and colleagues in the audience. You know, Val was talking about the things that we do as a university and the progress that we've made and the sort of broad scope of our enterprise. And this is a propitious time for us. This is June of 2012 and we are thinking back to June of 1964, 48 years ago, but almost 50 years ago as we approached our 50th anniversary, our school opened for students in September of 1965. But the campus site was really dedicated in June 1964 and a few hundred yards from where we are. There was a waffling in the air and Marine One came in and Lyndon Johnson landed in a field that had 15,000 people in folding chairs. But before that, the only 15,000 or anything that had been there were rabbits or cows or whatever, so it was great to bring that many, many people. And we have some photographs from those days with Clark Kerr and Dan Aldridge Jr. and President Johnson. And there was a great sense of anticipation at this event set up in the field about what the university could be for the future. And I'm sure that many great things were said about what the university might be and what the community might be. So the theme of this morning, metropolitan future, is what the future of this metropolitan area might be. And I think our growth in the intervening years has really been a reflection of what that can be. My wife and I were traveling just a little bit ago and we were in Europe and driving a bit. And something that I say a lot was really visible. We have said in many of my talks that in the Middle Ages or times of antiquity that cities would tend to come up around rivers. And we were in a part of France that was there since Roman times. And you could see places where cities like Arles or whatever were on the edge of rivers or special places of rivers where river commerce was important. And then, so that's an antiquity. In the Middle Ages, cities tended to grow around cathedrals. So there'd be a great cathedral or there'd be a castle, a defendable place and a great city growing around that. And we saw some of those things. And thinking more of the modern era in this country, cities grew up around factories or factory towns or factory cities would grow up. And those would be the metropolitan areas. But today and in the future, cities really are going to grow around universities. They're going to grow around ideas. They're going to grow around people who are doing things to change and create the future. And that was the promise of this university when 50 years ago, those people put the spades in the ground and turned the pasture land and really turned it in to the foundation for what the university has been. And then our university, starting in 1965, the city of Irvine, coming along five years later. And we can look back now over nearly half a century and kind of get an idea of what we've done. And both the city and the university have wonderful growth. So the city for the eighth year, Mayor Kang has just informed us eighth year in a row, the safest major city in the United States. I also know by looking at things that we've done for a variety of reasons. If you look at the unemployment in our community, in our city and our community, they're much lower than the average of California or the rest of the country. Or if we look at the health status of California or of our city, much better than California or the rest of the country. An interesting quick datum there and it reflects a bit on what the Dean was saying. The life expectancy for people in the United States and for California is about 80 years. It's gone up. And there's some interesting ways to talk about that. That's a different talk. But it's about 80 years on average. If you look in California, though, there's a wide range of life expectancy. As a California average of about 80 years, there's the shortest life expectancy in California. If you look by zip code, and that's one way of looking at health data, you look at this zip code compared to that one, etc. So comparing by zip code, the shortest life expectancy in California is 73 years. And that's quite about a 10% lower life expectancy across a very large group of people. So it really is a really profound negative effect. And longest life expectancy in California is 88 years. Actually about 10% more than the average. And again, a real profound effect. The difference between them being about a 20% life expectancy. And that's in California in cities that are separated not by walls or rivers or anything, but just by zip codes. It's an incredible, incredible difference. And actually, if you look over development to go back to a life expectancy of more like 73 years, we'd have to, or let me say definitely to go from 88 years back to 73 to take 15 years off the average life expectancy to go from 80, which is the average back to 65. You'd have to go back about 80 years. Have to go back to the pre-antibiotic era to get to a time when the average person lived 15 years less than they do today. So that spread that we have is three or four generations worth of progress between the lowest and the highest in California. I should ask you all to guess the zip codes in which these, or the cities in which these zip codes occur. But I'll tell you, so the zip code with the lowest life expectancy is in Stockton. And you can imagine it's a depressed, relatively uneducated place with not a good employment opportunities or safety or water or all those kinds of things. The zip code with the longest life expectancy is Irvine. And then let me say, these things change bit by bit in a few other places that would vie for the longest. There are places in and around Palo Alto that would have very similar life expectancy as Irvine, vice versa. And then there are places like South Los Angeles and Oakland, which would have life expectancy and like Stockton. So there's no magic to that. What it says is that well-educated communities of people built up often around knowledge bases have been able to develop a series of circumstances and services and a way of life that has allowed people to thrive and do better than places where those things aren't available. So those are very, very important. Another measure that I'd love to share is the Times Higher Education, a periodical that I in fact didn't spend much time reading before last week. This is from Great Britain. Did a worldwide comparison of all the universities in the world that were 50 years of age or less. They compared, they looked at 400 universities and they looked at them, a variety of criteria, looked at them on the basis of their contribution to the broader world. So PhDs graduated awards for faculty citations that were quoted by other people, not based on reputation or athletics or things, but what the university has actually contributed to the knowledge base of the world. And they ranked world universities founded in the last half century. And in the world, UCR, if I was ranked fourth and number one in the United States of you, I would pause for applause. This is spontaneous applause, not a plan, but appropriate. And so the concept of starting something 50 years ago and then having a vision of what it might be for the future. And seeing them 50 years later, people in an entirely different part of the world said this is the best thing that's been done in the United States in the last half century in the field of higher education. And one of the best things that's been done in the world in the field of higher education in the last half century. And I must say that the places that did better, the universities in Korea and others, were really the focus of the national attention and the national budget quite heavily. We've been cut, as you know, these last several years, the places that were able to do better were those that continued with their funding stream. And so we want to reverse that so that when in a hundred years, the times higher education is looking back at the best universities founded in the last hundred years, we'll move up three or four places on that list. We're an inter-universities research and based on the principles of the Morrill Act of 1862, the act that founded the Land Grant University of our research is here to benefit the people of the region in which we live and to educate the sons and daughters of the broad population, middle class in particular, to be able to participate in society and be great contributing citizens. And today you're gonna hear a lot about how that research and how the things that we learn about ourselves can help us to predict and make a better future. So our job is to do our best to help bring together people to get good ideas, to do research, to develop a database to make our society flourish and to make a better future. We're really pleased at the way that it's gone these last 47 years. And we look forward very much to the way it's going to go over the next half century. In speaking specifically of the Metropolitan Futures Initiative, it takes on an interdisciplinary perspective, on issues that are critical to day-to-day living. Things like transportation, things like jobs, things like housing, things like crime, things like social equality within the community. And so I'm really pleased to have all of you here today to join in this conversation and to see the work that has been done. Let me now thank you for your time and attention and welcome back to the podium, my friend Valgenus. I think we should have moved that forward to Chancellor Drake on the backdrop. We're not mistaken for each other often, but I do like to keep the slides straight. Thanks Chancellor. Really appreciate that broad lead-in. Let me give you a more specific lead-in to the report today. The Metropolitan Futures Initiative, which is a larger initiative, is really the sponsor of today's Regional Progress Report which takes a look at both the spatial and the temporal, that is, over time dynamics of a five-county region in Southern California, namely our region, which happens to be the second most populous area in the United States. The report presented today, which you will learn, is based on the collection and examination of 14 different data sources concatenated and put together. It's what I call a Herculean effort to kind of amass what the Chancellor calls a knowledge base. The goal of the report is, in the first and last instance, to understand the dynamic relationships between demographics, transportation, housing, jobs, and crime safety. So you're gonna learn a lot about that. What's really amazing about this report is that it covers an incredible amount of territory, both geographic territory and topical territory. And also incredible about this report, if I could invite you to take the time to really read it, is that it moves beyond what we call a simple focus on static measures of the welfare of communities. And it provides an analysis of the inner relationships between these features of the community that do define our daily lives. In other words, by reading this report, you can see how the various parts of our community commingle and with what consequences for our lives. Now today, the lead author of the report will present some findings, only a small portion of the findings of the report that speak to the past and the present and allow us to think creatively and in a data-driven way about the future. For me, this becomes very important for both private and public decision makers. What's particularly exciting about the report for me is that it makes good on a central belief of mine and the mission of the School of Social Ecology that public policy decisions should be informed by empirical, systematic, verifiable, solid data. Our goal then is to offer this up to all of those who would share in that line of thinking. That said, before I introduce the speaker today, I do want to introduce all of those that have participated in the production of this report and in this event here today. So with those that have played some role in the MFI, just please stand up and so we could recognize everybody. In particular, I want to thank Professor Bessolo, Professor Bornet and Professor Houston who are collaborators on this report. And I want to recognize Victor Bracera, the director of the Community Outreach Partnership Center in the School of Social Ecology for all of his contributions. Now it's my pleasure to introduce the featured speaker and the lead author on the report, Professor John Hipp. John is an associate professor in the Department of Criminology Law and Society and he's the director of the General Social Ecology PhD program in the School of Social Ecology. John grew up in Southern California, Anaheim to be exact. So we always look to see how he presents Anaheim in these regional approaches. And he came back to UCI in 2006 after earning a PhD in sociology from the University of California, Chapel Hill. Since arriving at UCI, John's quickly emerged as a rising star in both the study of crime and the study of communities. He's an expert in all sorts of things including urban sociology and network analysis and I think you'll see where the benefit of that in this report. Just a few years ago he was formally recognized as the best young criminologist in the country when he received the Ruth Vaughn Shold Kavan young scholar award from the American Society of Criminology. When I nominated John for this award, I explained that even a cursory examination of his record reveals a scholarly record that is just explosive by every measure. Number of publications, the content, the quantity, the citations, he really is a young star at the University of California. A less cursory read of his record reveals why. His substantive expertise is both statistical and methodological and theoretical and substantive. He marries those two quite beautifully. Most relevant for our purposes here today, John is a leading researcher on the question of how neighborhoods at all levels of community life change over time, why some seem to improve, why some seem to decline and why others don't. His research along these lines is having a profound effect on how we understand in the literature what we call neighborhood effects for the social sciences writ large. I wanna say more personally, in addition to being a stellar scholar and a wonderful teacher, John is a incredible colleague. He's known as a team player. When we asked him to lead up the MFI, he said yes. And as is his style, he's typically willing to do whatever he's asked to do and to share it with the community. It's really my pleasure to introduce my colleague and my friend, Professor John Himmel. Perfect. Thank you very much, Dean Jenis, for that introduction. I also wanna thank the chancellor for hosting this event this morning. And I also wanna thank all of you for coming today. We really appreciate it. Understanding our region requires understanding how the pieces of our social world fit together. As Val said, a lot of my work focuses on neighborhoods, but to understand what goes on in neighborhoods, what we're suggesting with this report is that there's a need to understand the larger social world. And what complicates it even more is that there's various layers of governance that go on when trying to understand this big picture. For example, the co-location of jobs and housing along with the transportation networks that link them have implications for the transportation patterns that we observe in the region. Transportation patterns then have implications for the level of smog that we observe in the larger region. And then smog levels have, and then residents close to freeways have health implications for the residents in the region. Furthermore, the residential mobility patterns of residents in response to these issues can have consequences for demographic change in neighborhoods. And then this can have consequences for the public safety that we observe in communities. And then the quality of these communities can feed back into the larger system. So our challenge today is trying to get a little bit of understanding how all these pieces fit together in this complicated picture. And indeed, that was the goal of this entire project of the Metropolitan Futures Initiative. This here today is an initial report, but the plan is that this will be an ongoing project. This is not just one report, but it's something that we'll be continuing on. But for this particular report, it was a sort of, as Val mentioned, a rather large project, and it entailed over the last 18 months about five faculty, not about, there were five faculty, 10 graduate student researchers, six undergraduate researchers. As Val mentioned, one part of this was putting together this large concatenated data set, 14 different data sources, measuring different aspects of the social life. But as was mentioned, we're not just trying to collect social indicators here and say, you know, measuring how things are going on, but rather what we wanted to do is make these various data sources speak to one another. And how we do this, and this was statistical modeling that addresses the various questions that we pursue in the report. And so, as was mentioned, I'm here today just to present a small portion of these results. If you've seen the size of the report, you'd be grateful that I'm only presenting a small portion of them. We don't have that much time. But what we're hoping is that this will spur your interest in reading the entire report, or parts of it. What I'm gonna present today is gonna follow along four main themes. First, how do jobs and transportation interact? Second, what role does crime play in neighborhood change? Third, what role does race and diversity play in communities? And finally, we'll talk a bit about what effective foreclosures have on home values in communities. Just as sort of a preamble, I wanna just show a few maps charting some of the demographic change that's gone on in Southern California. Now, most of us are aware of this change that's occurred, but nonetheless, we wanna visually depict it. And on this map and the others that I'm gonna be showing, in general, this is the Southern California region here, the Five County region, which is what we focused on in the report. You can see we've cut off the less populated areas, not that because they're unimportant, but just for visual representation. This, to give you a reference, this is Orange County here, this is LA Ventura, and then Riverside and San Bernardino over here. And on this map and others that we'll be presenting, we've color coded it in that deeper shades of red represent higher values. So in this case, where we're looking at the percentage of Latinos, for instance, in a neighborhood, the darkest huge neighborhoods, 80 to 100% Latinos and then less beyond that. And what you see as we look, this is 1970, and as we move forward over time, you'll see the change both in the hue of, the general hue of the map, but also the spatial distribution. So where you see the spread of the Latino population going throughout the area. And of course, if we made comparable maps for other racial groups, you'd see similar changes going on. And what we're suggesting is these demographic changes sort of set the stage, if you will, for some of the analyses that I'm gonna be presenting later on in the report. But this is certainly a huge change that's occurred over this time period. So now to go back to our questions. Our first question was how do jobs and transportation interact? And in this part of the report, we used data on jobs in neighborhoods, and we also used a survey regarding travel behavior of residents throughout the region. It's important to emphasize that the old model 100 years ago, theoretical model they had out there was this idea of a concentric zone that all jobs were kind of in the main downtown area, and then a few jobs away from there. What we can see in Southern California is that's clearly not the case anymore, if it ever was. On this map, again, we have deeper shades of red are neighborhoods with a higher job density per square mile. But then we've also added to these yellow ones, which are the tracks that are in the top 5%. So these are very job intensive areas. So this is 1990 that we're looking at here. And of course, this is the downtown area. Here's through Brentwood and over towards the west side. Here's down into the South Bay area. And then then here's down in Orange County, what's very noticeable. Here's Irvine in particular, one of these top 5%, a lot of these neighborhoods down here and into this region here. When we move forward into 2000, we see even more of a presence of high job density in Irvine area, quite striking and quite apparent. As another part of one of our analyses we did is then we asked, we had yearly data and we asked which types of jobs, what explains why some neighborhoods will get more jobs rather than others. And one of the things we found was that the retail jobs tended to follow other jobs. That is to say, presence of white collar jobs in one year would lead to more retail or blue collar jobs the following year, but not so with retail jobs. They don't tend to generate other jobs. And here in the most recent time period, you can still see this strong presence of jobs down here in the Irvine area. A couple other things we found is one that places with more young adults tended to have higher percentages of white and blue collar jobs. But another particularly interesting finding was that population density tended to be lowest in areas that had more jobs, which has important implications for transportation patterns, which I wanna talk about next. When we looked at long distance trips throughout the region, we found that about 37% of the miles driven by people were on these long trips, which is defined as 30 miles or more. This pretty much matches what's found in the rest of the US, but what was notable is how different the transportation patterns are across the region. When you look at the city of Los Angeles or you look at Orange County, household vehicle mileage travel is below the average. And in contrast, when you look at San Bernardino County, it's above the average out there in the more extensive areas. But then we also asked who is more likely to log driving miles. And one possibility we asked and found some evidence that indeed people living in areas with more population density drive a little bit less. In fact, 10% more population density near you drive about 0.5% fewer miles. But a stronger effect we found in our analysis was the presence of jobs nearby. So if we took households, we drew a buffer around them and said, what if there's 10% more jobs in the area? We found that vehicle mileage dropped about 1.5%. And in fact, this was a nonlinear effect in the sense that if you have a real high density job area, which remember Irvine is, vehicle mileage dropped about 4%. So it was a strong impact of the location of nearby jobs on reducing driving behavior. We also asked about walking behavior. What percent of the time do people walk? And again, we found this very quite a bit over the region. Notably the area with the highest percentage of walking trips was downtown Los Angeles, which is as we know, it's gone undergone a lot of redevelopment over recent years. Now about 20% of trips there are by the mode of walking. Other areas with high percentages were Hollywood Hills, the Clermont area and South Central LA. In Orange County, it's worth mentioning that Irvine and Rancho Santa Margarita had the highest percentages of walking trips about 10%. In contrast, areas further out like Elsinore and Barstow, for instance, had the lowest percentage of walking trips. They're about 3% for them. Our next question was how does crime, what role does crime play in neighborhood change? And specifically we're asking, does it affect the presence of jobs and does it affect home values? First to kind of set the stage for you, this has been a large change in the amount of violent crime in the region. There's been a huge change over this time period throughout the US, but it's quite notable how much it's changing in the region as well. So for those aware of it, there was a big increase in crime up until about 1990 and then it's since been falling and we find that quite strongly here in the Southern California region. So this is 1960, red areas have the highest amount of violent crime and now we're moving forward. This is 1990, the worst of it, and now you see it becoming better as we get to the more recent years. So again, this pattern has changed over time. We saw this huge increase in violent crime and then a drop in it, but what consequences has this had at the neighborhood level? For instance, what effect does it have on jobs? One deed, cities with more violent crime do see a loss in jobs in these year by year analyses we're doing. So we asked more violent crime one year, what effect does it have on jobs and indeed they lost jobs the following year to give you an idea of the magnitude of this effect. Suppose we hypothetically took the city of Pomona which is a high crime city and we magically gave it Garden Grove violent crime rate which is considerably less. Pomona by our model would have about, have some more retail jobs and would have about 0.9% more white color jobs. It would be better just because of that change. Also in the year by year models we find they would, the model predicts that they would have more jobs because of that lower violent crime rate. So again, it has implications. When we asked about whether crime affects home sales prices, a similar story. Cities with increasing violent crime rates tended to have the lowest sales price appreciation. And again, these are year by year models that we were able to look at. So for example, if we looked at a city where the violent crime rate was increased about 10% over the previous 12 months, we'd find that home sales prices in the zip codes within that city were about 8% lower. Similar story for property crime, but much weaker effect. So property crime also decreases home values but violent crime has the effect is about eight times stronger. So it's a very impactful effect. But then we wanted to turn around and say, well, if crime is important, what explains why some cities have more crime than others? And so what we did is we estimated, again, we have many decades, we've got four decades, 70, 80, 90, and 2000. And we did two sets of models. One, we just did a snapshot and said at any point in time, what explains why some cities have more crime than others? And then some of the other models we asked, what explains why some cities will see a bigger increase over the next 10 years? And we found different things that some of our predictors were very robust, basically. And one of the really strong robust predictors was the presence of homeowners. That this has a very consistent negative effect on crime rates, it reduces it, if you will. So for example, if we took Norwalk, which is a city with an average level of home ownership and gave them the home ownership level of say Laguna Hills, their violent property crime rates would be about five to 15% less. And that's controlling for all these other characteristics in the model, density, poverty, all these other things, ownership makes a big difference. And likewise, they would see a larger decrease in property crime 10 years later because of the increased presence of homeowners. Another measure in our models that showed a very robust effect across all these decades was the presence of vacancies. Here the effect was the opposite. Presence of vacancies tend to increase crime rates in the snapshot as well as over time. So again, as another way to interpret this, if we take San Bernardino, a city that has a relatively high vacancy rate and somehow magically give it Tustin's vacancy rate, which is considerably lower, violent property crime would be about five to 10% less. And also we would see a smaller decrease, in smaller increases rather in violent property crime 10 years later. So again, would have these effects. So if ownership and vacancies have these very robust effects in our larger models, then what we found also was that some measures had robust non-effects, if you will. So again, we specified these models with the typical explainers of what explains why there's more crime in cities, such as poverty and population density, owners and vacancies. But we also then asked, well, what about the percent immigrants in a city? Does that have a positive effect on the level of crime? And in fact, across all of these models, we found no evidence that cities with more immigrants have more violent or property crime. We didn't find it when we did our snapshot models. We didn't find it when we looked at how crime changes over time. Just no evidence of it. But the only thing we did find is that in 1980, cities with more immigrants actually had lower property crime rates. So just no evidence for that. As another way to slice it, this graph is from 1990. We also, you'd see a similar one for 1980. There's a lot going on here. So let me try to walk you through it. If we look, I'm probably walking it, aren't I? On this side here, this right hand, so these lines are showing areas, the percentage of Latinos. So this is a city, rather, with a high percentage of Latinos. This is one with a low percentage. So this side, though, here, is showing high number of immigrants. And what you can see is as the percent of immigrants goes up, typically the amount of crime is going down in these models. This is property crime, in this case, here. If we look at each of these lines individually, this is a city with a very low percentage of Latinos. As you bring in more immigrants, no effect, no change in property crime. This is a city here, that appears with a high percentage of Latinos. If there's a lot of Latinos with no immigrants, this is second or third generation. You see somewhat higher rates of crime in these earlier years, 80 and 90. But as the percentage of immigrants goes up, the property crime is actually going down. So again, this we find in the earlier decades, then that, again, no evidence for immigrants increasing crime. This raises our next question. And what is the role of race and diversity in communities? And what we're gonna find in the crime models is that they show some very sharp changes over this time period. So whereas some of our models, I said, we found these really robust, either strong positive effects or non-effects, here we found some big changes over the time period. One thing we looked at was the presence of racial diversity or racial heterogeneity. For us, we measure it by looking at a city, and we broke the groups up into percent white, percent Asian, Latino, African American, and other race. And we created a measure of the amount of diversity in a city. So to think a high diversity city would have 20% of each of these groups, 20% whites, 20% Latinos, et cetera. Whereas a homogeneous city would be all of one group. So then what we wanted to ask is, what effect does this have on crime? Well, why? This is one of the more robust predictors of crime in the criminology literature, whether you measure heterogeneity at the neighborhood level, or you measure at the city or county level, always seems to be that more heterogeneity, more crime. And of course, that's not a trivial issue here in the Southern California region, given the increase in racial diversity over time. So this is 1980. And again, the red areas have higher levels of diversity. This is 1990, and here's 2000. So we're seeing this big increase in diversity in the cities across the region. What this means more crime, that's not a good thing. What do we find? Well, interesting, this is one of the measures we found a very big change over this time period. In the earlier decades, it was indeed the case that cities that had higher levels of heterogeneity indeed had more crime. But this changed in the two most recent decades that we had data for, 1990 and 2000. It turned out that those cities with more diversity, no more violent crime, and in fact had lower property crime rates. Again, taking into account all these other characteristics that might predict crime. In the dynamic models, a similar story. In the 1970s, cities with more diversity saw increasing crime rates, both violent property crime. But in the most recent decades, no such effect. So this is a very notable change that's taken place in the region. Our second assessment of the effect of race and communities was looking at racial diversity and home values. So again, here we're looking at what explains how home values change over time. And here again, we find a very notable change. When we look at the earlier years, and first we asked, what is the impact of the presence of racial ethnic minorities in neighborhoods? So in the earlier decades, if you took two neighborhoods that were similar in all these other characteristics that might explain changes in home values, and you gave one 10% more Latinos and another fewer Latinos. In the earlier decade, that neighborhood with more Latinos would see lower home value appreciation. Relatively, they'd fall four to 6% compared to other neighborhoods. That was in the 70s and 80s. In the 1990s, there was no effect. More Latinos was no effect on home values. And by the 2000s, in fact, this most recent decade, those neighborhoods saw a 1.3% greater increase in home value change. So that's a very sharp change over this time period. Similarly, if we took a hypothetical neighborhood, increased more African Americans. Again, in the 70s and 80s, those neighborhoods would see relatively fewer, less home value appreciation, about 2.5 to 4.5% less home value appreciation. But in the two most recent decades, no difference. So again, that's a very sharp change that's taken place over this time period, and something we can see by taking this long range view of the data. We also asked, what about the influx of these minority groups? What effect does that have on home values? And it's again a similar story of quite a striking change. During the 70s, 80s, and 90s, neighborhoods that had a large influx to be the blacks or Latinos had lower home value appreciation. Furthermore, neighborhoods that saw a large influx of these minority groups in adjacent areas also saw relatively falling home values. But when we look at the most recent decade, there's no evidence of this. Neighborhoods with more blacks or Latinos coming in or nearby did not see such a negative effect. So this is a sharp change. We then asked about the effect of racial diversity at the neighborhood level. Recall previously we were looking at diversity in cities and explained crime. Well now here we asked about diversity at the neighborhood level. Does that affect home value change over time? And again, a similar pattern here. In the earlier decades, 80s and 90s, neighborhoods with more diversity had lower home value appreciation over the subsequent decade. But in the most recent decade, more racial diversity actually saw higher home value appreciation. Again, taking account of all these other characteristics that might explain this change, the presence of heterogeneity has gone from this negative amenity, if you will, to a positive one. And then also when we measured the change in diversity over time in neighborhoods, again, a very large change. In the 60s, 70s, 80s, and 90s, neighborhoods that saw this greater increase in diversity had lower home value appreciation. But in the most recent decade, greater increase in diversity actually saw higher home value appreciation. So a very sharp change. I wanna turn to our last question, which is to say what effect do foreclosures have on home values? The foreclosure crisis, of course, is unprecedented. We're all well aware of it. There's many issues that come from it. It has an impact on home values, it impacts family life, impacts crime. We can think of this larger foreclosure crisis as an external shock that hits neighborhoods. So even if the household itself is not directly affected, it can be affected by what happens nearby. So if we're looking at this, we had quarterly data on foreclosure rates in zip codes in the Southern California area. So in these maps I'm gonna show you here starts in 2002. And again, deeper shades of red indicate areas with higher foreclosure rates. So this is going, we're going quarter by quarter. We're now into 2003. And this is before we've hit the big foreclosure crisis. We're up to 2004 now. Again, this is Orange County down here. This is LA and then you can see the Inland Empire here, which now we're into 2006. And suddenly you start to see this impact coming into this Inland Empire area. Now we're into 2007. We're starting to see some areas now, even in Orange County being impacted by this. Now we're into 2008. We can see it moving throughout the region. This spatial diffusion effect, if you will. Summer of 2009, by the time we get into 2009, the foreclosure rate is about 13 times higher than what it was in 2002. So a huge effect that has swept through the entire region. What effect does that have at the neighborhood level? Well, we found that it does indeed affect home values, probably somewhat unsurprisingly, but there's a deleterious consequence. That is 0.1 percentage point increase in foreclosures. We found that home sales prices fell about 0.6% the following month. So it's a very precise temporal measure we used and found this strong effect. We then also asked, does the effect of foreclosures have different effects on different types of neighborhoods, if you will. So one way we looked at this was looking at the racial composition of the neighborhoods that experienced foreclosure hits. This figure here is showing for neighborhoods as the percent black increases. We also did a model where we looked at the percent Latino changing. And it turns out if I plotted that figure, it'd be exactly the same as this one. So I'll talk about both of those at the same time, if you will. This red line here, this is an average neighborhood, if you will, taking account of all these other characteristics. What effect does foreclosures have? This is increasing foreclosure rate and this y-axis is the change in home values, home sales prices. And you see indeed more foreclosures, a greater decrease in values. This blue line is a neighborhood with fewer Latinos or blacks. This green line here is a neighborhood with more Latinos and blacks. And what you can see is this, that such a neighborhood as this is getting hit harder. Sales prices are hit harder by the same level of foreclosures. We also split the data and looked at it based on the income level of the neighborhood. And as you might expect, this has a big effect as well. In fact, even bigger effect. The magnitude of the effect is even stronger. So again, this is an average neighborhood here. This green line is a high-income neighborhood. And you can see the high-income neighborhood isn't affected very much. Prices aren't affected that much by higher levels of foreclosures. But you do see a strong effect on low-income neighborhoods. So these are the most vulnerable neighborhoods. When foreclosures hit here, sales prices get hit particularly hard. So the impact is not uniform across all the neighborhoods. Okay, so I need to wrap up here. We're running a little short on time. What have we learned today? Well, what we've been suggesting here is that there's substantial challenges that we face in the region. These challenges will transform where we live, where we work, where we learn, and where we play. And we see responses in multiple sectors, including the housing, transportation, and economic development sectors. It's also the case that we see responses at multiple scales. There are state mandates that reduce driving and emissions. There are regional plans to concentrate growth near transit. And there are community plans which support sustainability goals. But then the challenge that we face is how do we achieve all these goals? What we've suggested in the region, of course, there have been major new transit investments and there's been a lot of housing development near transit. And as part of this report, we asked what neighborhood factors help reduce driving? What we found that indeed population density matters some. It does tend to reduce driving behavior, but it also appeared that the presence of jobs nearby has a particularly strong impact on driving behavior. We also found the community context matters. Crime impacts jobs and home values. But then the question, what are the causes of crime? And we suggested that it may not be the same old story. For example, we found evidence of racial heterogeneity, at least in our data, no longer appeared to increase crime. Now, why do we see that change? We can't say it for sure. We just note this change. Future studies would need to say why did this change occur? Is this the action of groups and communities that changed this? Why has this change occurred? There's a challenge for how to reduce crime. Our model showed that homeowners decrease crime, vacancies increase crime. You can see a bit of a challenge there from a policy point of view, having to do with housing policies and financial availability policies, if you will, in the issues around those foreclosures, right? Making credit more available increases the number of homeowners. That's a good thing for levels of crime, but to the extent that homeowners turn into foreclosures, turns into vacancies, that becomes a negative thing. So you can see there's a need to thread the needle on certain policies. But furthermore, given this negative effect of vacancies on crime, you can see that we need policies that address how to deal with vacancies. A positive aspect is that we've suggested that transformation may be a strength for us. And of course, there's a lot of transformations that are taking place. There's diverse economic needs of people in the region. There's growing ethnic communities and there's public education and social services challenges that are needed. How will this growth and racial ethnic transformations impact our communities? We found some important evidence in that regard. One, we found no evidence that immigration increases crime rates, something to be aware of. Another key finding was that the appreciation for home values that used to be associated with the presence of minorities in neighborhoods no longer appears present. That's a hopeful change. And we also found evidence of racial diversity which used to have a negative effect that actually seems to increase home values. Those are important changes that we observe. So let me conclude. Enacting useful policy is challenging and to do so we need to understand the social context and all of its complexity. We have emphasized here that these pieces move together which makes it challenging to understand them. This suggests the need for better information. Actually better and more useful information means better decisions. Our intention of this initial progress report and future additions that we wish to come out with is that we can help inform some of these decisions. Our results demonstrate the many ways that our daily lives are inherently connected and suggest that our future is dependent on increased cooperation. The MFI in that regard hopes to facilitate a series of public dialogues next year to document ideas and experiences on these and related questions. Our intention is then to analyze and organize these conversations to help key stakeholder groups and the public at large to better understand common interests and how they create possible new opportunities for problem solving and working together. Thank you very much for your time. I guess we have some time so we'll open it up to questions from the audience. Yes. So you're asking whether it's causal versus correlation and what was the last part? Oh, causal versus correlation. So was there an attempt to kind of tease out some of the additional variables that might just say, well, this isn't really the major factor. There are other things that come to play, such as in transportation, walking. Yeah, that's a great question. Indeed, that was our goal. So some of the analyses were descriptive, kind of showing what is the change that's taking place. But when we tried to actually do some models to talk about some of these changes that have taken place over time, there's always challenges with the language of causality. It's always a fun one in academia, right? We get ourselves tied up with it. Some people think the only way you can talk about causalities if you actually have an experimental design, of course that's very difficult to do in the social world. But for us, we were trying to move beyond simply a very simple, just correlational analysis in the sense that a couple ways. One, yes, we were indeed trying to take into account the various other measures that might explain these things. For example, in the models looking at sales price changes, we were trying to take into account what are the various characteristics of neighborhoods that might explain why you would see a change in home values over time. But second, what we're doing in almost all of these models when we could, and this is the advantage of longitudinal data, is we can at least look at temporal changes. So you can imagine some of these things if you look at one point in time, like foreclosures and home values, the sea that you co-occur maybe isn't so such convincing evidence. For us, the advantage is for some of these analyses, we actually had quarterly data, or some of them was even monthly data. So we can look and say, okay, if you see more foreclosures one month, what happens to the sales prices the next month? So while that's not a perfect experimental design in the sense that we're not randomly assigning foreclosures to neighborhoods, it's giving us a lot more evidence for the process than you would if you just simply did a snapshot at one point in time and said, what's the effect going on? So yeah, it's a great question and that's something we're trying to address. And I would emphasize that the longitudinal data gives us a way to really try to address that a little better than maybe it would normally be the case. Well, I think we did look at, you mean did we look at poverty unemployment rates for having an effect? We did, like for explaining, when I talked a lot about different results, but for example, talking about what explains which cities have more crime, we looked at both of those in there. The interesting thing about unemployment in criminologists are where this is the large debate in the literature. What we found was the same thing as others is that basically unemployment seems to have no relationship with crime. And I know this is always a puzzle, I was getting calls when the downturn kind of first hit a few years ago in the newspaper, what's gonna happen to our crime rate and unemployment's going up. And why is that the case, criminologists wrestle with that? There's competing arguments why it should raise or should lower crime, but we found the same thing, that more unemployment didn't affect crime. An interesting thing about poverty, though, is that was another measure. Again, I don't have time to talk about all the results that the teachers are kind of looking at. More, look at the report a little closer. But poverty also showed a bit of a change over time. That when we looked at the earlier decades, higher poverty rates, indeed, higher rates of crime. And of course you want to take that into account because that's an obvious possible explanation of where there's more crime in areas. It was a non-linear effect in the sense that as poverty went up, crime went up, although it kind of ended the level off once you got to a certain high level of poverty, anymore just didn't seem to make any difference. But that was something that also changed in the more recent decades that poverty didn't seem to be associated with levels of crime. So it sort of changed over time. But we were definitely trying to take that into account in the model, definitely. Because people that are undocumented do not want to report crime. I know having worked with people that have undocumented status say, well, I really don't want to open my mouth and say something because, and so how do you take that into account in your crime data place? Yeah, that's an excellent question and that is a huge challenge because the data we're using here was uniform crime report data which comes from city police departments, basically is what we have police departments report to us. And for a lot of things, that data's not so bad but there's certain idiosyncratic challenges with it and that's certainly one. It's an interesting point to raise because I did previously, I did some work up in the South LA area. We were looking at intergroup violence between Latinos and African Americans, for instance. And there you still have this same challenge of under-reporting sort of thing but there we were finding this pattern is that Latino immigrants tended to be victimized a lot which is kind of the story you were just saying. And it's interesting to that, to the extent that's the case, although that would, that's not quite the story that's typically given. It's not that, oh, immigrants are causing us trouble because they're coming here and being victimized over and over. The story is typically immigrants are coming here and committing crime. So it's a little different process in that way. How to account for that is always a challenge whenever you have under-reporting and crime. And that's just a challenge, how to do that. You got David? Yes, I could be wrong, but I think the ratio of red housing departments in Irvine is probably relatively high. How do you account for the fact that the crime is nevertheless so very low? And a corollary to that is that it might a, someone in cities conclude that there should be no rental housing and that should be integral to the policy as a result of which homeowners would enjoy higher value and they're less crime. Right. Yeah, it's always a bit, I mean, that's, there's a great question. There's a challenge to, on the one hand modeling and saying, okay, the model, I'll let the data tell me what the data tells you. And then the second challenge is what are the policy implications of that? That would be one is you could try to extrapolate it for and say, oh, therefore let's get rid of all renters in communities and that would change things. Of course, there's a need then to kind of step back and say, why is it that the percent of homeowners has this negative effect on crime? What is it about homeowners that makes crime less prevalent in those cities? And that becomes the deeper question to ask, right? It's clearly it's a proxy for something else per se. Now, it might be a proxy for a type of housing, maybe that's it, that the lower density affects the level of crime. It may be a proxy for the types of attitudes and that's a story sometimes people give that homeowners are more invested in the community therefore are more involved in trying to reduce crime. But for this analysis, we couldn't say what is it that brings that about, which would be a need to move forward and try to assess what that is. So trying to extrapolate and say, okay, get rid of all renters is not a direction we'd want to go in. The other, you raise an interesting point that as well that Irvine does indeed have a rather low crime right here to say at least the lowest of all major cities in the U.S. And why that's the case? I'm always, I'm a little embarrassed to admit that I don't quite know, I'm a criminologist here and we kind of, when I talk to colleagues I kind of joke about OEM and Irvine but, you know, studying crime, what sort of study? There isn't much. But the retort to that is to say, well, what is it about Irvine that results in such low amounts of crime? And that's, I mean, that's one, certainly for me professionally, that's embarrassed to admit that I haven't done it yet. I've only been here a few years but that's something I wanna understand a little better. Why is, what is going on here? That explains that. There's a lot of competing theories but I can't say for sure. A statement from a council member, city of Irvine, I would give you an answer why Irvine is such an abstinent law. City, good policymaking, good policing. We have our mayor here and as a city council member and we are very proud that we have achieved eight years straight as a safety city in America. Among many interesting information you have presented, the one very important element I think that you have missed out in terms of relating all that correlation to crime rates versus home values as we all entire council believe in is that we also reflect our policy that is quality of education, school quality. I think Irvine is characterized as good schools. If you ask people on the street, why did you move to Irvine? Unscientific answer will be eight out of 10 people will say we came to Irvine for good schools. So what does the good schools mean in terms of home values and less crime and also city policymaking, we also try to keep it that way, good schools. Obviously the schools do have their budget and I was a school board member myself for six years and I moved on to a city council and about the mentality of a city council we feel schools are part of, integral part of the city so therefore we try to participate and help a school district and budget ones as much as possible. So I think that is the element you need to include the school quality is probably one of the most important factors in affecting home values and crime rates. Yeah, let me just, yeah, make a couple comments real quick because it allows a little jumping off point. I think it's a great point that education is an incredibly important issue. One for us is we're collecting data over this long period of time and here's a real kind of boring kind of answer is that it's hard to collect school quality data over a long period of time. That said, what you touch on is directions we wanna go with this. So in a sense, we're trying to study the whole world with this report but we can't possibly do that but there are certain directions we wanna go to in future reports and you've touched on one. When we had our earliest planning for this there was two key areas we wanted to go in and we said, okay we can't do it in this report but we wanna do it in future ones. One of which was educational quality and what are the implications. That, it's harder to get data way back in time but we can get data more recently in more recent years and so that's a direction we want to go. The second and just is health issues which you saw, there weren't health issues here. That's something we definitely wanna do in future reports. Again, it's a scope issue what we can study in any one given report but these are things that we want to pursue as we go forward with it so I really appreciate those great points. And our council member, Choi, I'm at a very good point about Irvine but in general the rental, when it comes to rental, I'll say apartment units about one third of the entire housing stock. However, when it comes to rental versus ownership, it's half and half. And out of that, the affordable housing, our goal is to have about 10% of the entire house in a housing stock. This is a very unique opportunity that we can offer you is that not only the education is a very integral part of our success, however, the integration of diversity speaks for itself, not only reduce the rate of the crime because as you heard, we've been recognized as the safest city in the United States, eight years in a row. And 2010 and 11 being the lowest in part one crime per capita in the history of Irvine, 41 years. So this is something that the community is very proud of, having that recognition distinction, but it is about the ownership that everyone lives and play and work here, take that ownership in pride. And that makes it quite a bit of a difference. I want to ask you, what do you feel of the values that you allude to with respect to values of housing? Can you identify or kind of separate out and bring into the report the 10 or 12 years we've been dealing with in housing, which is really an abnormal period? I mean, the places that showed up on your map, houses were being built and they never had been built and they're being built because of the available money at subprime. And the whole housing market for 10 years has been abnormal, but I just wonder if you can incorporate or should incorporate in years to take a deeper look at that period. Yeah, that's a wonderful idea. Yeah, we tried, yeah, one point early on, we thought we would just stop the report, looking at home values in 2000 because it's just such a mess, or well, a mess from an academic point of view. It's the real world out there. So our thought was to boldly move forward and try to address that in some ways. We had sales price data and that sort of thing in neighborhoods. It is, in some ways, to me, as someone who's a statistical model or someone approaches these things, to me it's a huge challenge to try to address that because it's been, there have been huge changes. That would be an area, again, for future reports. Our thinking has been that for future reports we want to go into certain issues in depth and I alluded to education as one we might want to do. The role of health might be one, but another one that would make a lot of sense would be to try to understand the home value market and all the parts of it that you listed. So I'll look when we're there, yeah. Those are things we would like to pursue in more depth in future reports. I think I'm getting cut off here. Well, save one minute for a few closing comments. We may not have started on time, but we're gonna be known as a school that knows how to end on time. It's so fascinating for me to sit in the front row and listen to John's presentation and I'm always affirmed when he says it's a huge challenge, it's a huge challenge. A, he's a very sophisticated researcher. He has an incredible team and I think that kind of modesty tells you what good hands, the data and the thoughtfulness that goes into this. One of the things that I look forward to is meeting the challenges he keeps talking about and from my point of view, those challenges have to do with effectively bringing together the research talent at the University of California in the School of Social Ecology in particular, the very people that stood up earlier in my introduction and also ensuring that we have the level of community support and engagement that makes it not just an intellectual or academic exercise, but makes it a contribution to the community and to allow Irvine and all of the other communities continue to move forward in what are obviously some shared goals for the betterment of our communities. That said, I wanna thank all of you for coming because the dialogue and the engagement is as important as the research and we will be talking with you more as the next report unfolds and as we proceed to build the database and talk about our communities locally, city-wise, county-wise and regionally. So with that said, I wanna thank John Hib and the others who made this possible today and everybody's welcome to stay around and chat more but when we say it ends at 9.30, it does. Thanks guys.