 Hello, everyone. Welcome. This is our sixth lecture. Can you believe time is really flying? So I would like to just now ask Beth Wood, our program chair to please introduce today's speaker, Beth. Thanks Carol. We have a really interesting and very relevant talk in store for us today by Peter Nelson. And I hope you'll all feel free to submit your questions at any time during the lecture or during the Q&A. In the queue, you just hit the Q&A button on the bottom of your screen type in your question that send and it will be waiting for us there when we get to the Q&A. Peter earned his BA in geography from Dartmouth, his master's in PhD in geography from the University of Washington. In 1999, he joined the faculty at Middlebury College where he is currently a professor of geography. He teaches courses there on population issues, the global economy, and the rural United States. His research focuses on migration to rural communities and rural gentrification with funding from the National Science Foundation. So it's a great pleasure to welcome Peter Nelson to Triple E today. Take it away, Peter. All right, let me share my screen here that I assume that's working. Okay, thanks Beth and thanks to Triple E for inviting me. I do enjoy giving these talks. And in particular, I enjoy talking about demographic trends in New England and Vermont to Vermonters. So, I think we're going to have some fun over the next 45 minutes or so. This particular invitation was nice because it gave me a nudge to return to some of my earlier analyses and update them with results from the most recent Census 2020 data that's come out. So today, what I'd like to do, I'd like to do three things, three or four things. First, I hope to highlight patterns of demographic change across New England as a region. Focusing on states from Connecticut up north through Maine. And I want to unpack that demographic change by looking separately at the different drivers of demographic change, births, deaths, and migration. And I should note that my comments today focus. And when it comes to migration focus on domestic migration movement around within the United States. I don't look necessarily at immigration or movement into the United States from from outside. Then in the second part of my talk I'm going to drill down and look specifically at what's going on in Vermont. In the final section, I'm going to share some of my current research, which people have been particularly interested in, in that I've been looking at what evidence there is of people moving into rural areas in New England and Vermont. And sharing the COVID-19 pandemic, because we've all heard of these stories of urban refugees fleeing to the countryside. And I'm trying to figure out if there's ways for us to assess the extent to which that is happening, and the geographies of where it is happening. My approach today relies primarily on using maps, I am a geographer after all. I do graphs sprinkled in, but I primarily use maps, and I try to use a consistent color scheme so it's easy for you even if you can't read the specific legends on the maps, the color scheme is consistent in that green colors tend to represent growth or things that are kind of demographically positive. And shades of red represent decline or things that are demographically negative or below average. For my regional analysis, I focus on counties as my units. When I shift to Vermont, I focus on towns, or they're called county subdivisions. So we get a kind of finer scale geography, when we shift to the analysis specifically in Vermont. And I hope you'll leave today. With two primary takeaways I'm kind of cutting to the end right away. I want you to leave with this with an understanding of the striking difference in golf that's emerging between urban and rural New England. That plays itself out regionally. And it also plays itself out within Vermont. Beth indicated that many of many of you in the audience today are reside in Chittenden County. Well, Chittenden County and its neighboring counties are really unique in the context of Vermont. So there's urban metropolitan Burlington, and then there's the rest of the count, rest of the state. And the second takeaway is, is one that you'll, you'll quickly observe and that's a rapid and dramatic aging of New England's population. The population is as a region it's quite old, and in Vermont it's particularly old Vermont is now the second oldest state in the country behind main, another one of our neighbors. So, very quickly, we'll start with this kind of regional overview, focusing on those drivers of demographic change births, deaths and migration. And then we'll drill down looking specifically at Vermont. And last we'll look at some of this more recent work, looking at what does the available evidence suggest about migration into the region during the COVID-19 pandemic. Okay, so that's where we're headed. I hope that I can keep my comments to about 40 minutes. And then it's always fun to have a little bit of a chit chat and dialogue afterwards. So let's start with a very simple graph showing rates of population change over the last three decades for the six states that make up New England. Connecticut, Massachusetts, Maine, New Hampshire, Rhode Island, Vermont, and each bar represents a growth rate for the 90s, the 2000s and the 2010s respectively. And what you'll see very quickly when looking at this graph is growth across the region has generally slowed over the last three decades. And the exception to that is in Massachusetts, where growth in the 19, in the most recent decade exceeds that of the growth rates in earlier decades. We contrast that with a place like New Hampshire. New Hampshire was the fastest growing state in the region in the 1990s, but in subsequent decades that growth has slowed down, but it still remains one of the more rapidly growing rates. If we look to the furthest right set of bars on this graph, we come to Vermont, and we can see Vermont in the 1990s was the second fastest growing state in the region. But that growth has really slowed down. In the most recent decade, Vermont grew about 2.8%. We've seen the biggest slowdown of growth is Connecticut, where it almost didn't grow at all during the most recent decade. If we look at these growth patterns spatially using a series of what we call choropleth maps, we've got the 90s, we've got the 2000s, and we've got 2010 going from left to right here. In the 1990s and see rapid growth at the county scale was rather widespread in the 1990s. I'll remind you that green represents positive rates of growth, red represents negative rates of growth, and then the varying intensities of those colors indicate greater degrees of growth or decline. In the 1990s, the vast majority of counties were growing at greater than 3%. Every county in Vermont enjoyed positive growth in the 1990s, all but one county in New Hampshire enjoyed positive growth in the 1990s. The main is the place in the 1990s with perhaps the most consistent or the largest number of counties that was experiencing population decline, but growth was pretty widespread. We start to see things change in the first decade of this century. At Vermont in particular, we see this north to south gradation, where the northern part of the state maintains fairly rapid growth of greater than 3%. The central band throughout the state had slower growth than it did in the 1990s. And then as you move south, you start to see a really slow growth or population decline in counties like Rutland or Windsor County. We advance one more decade to the most recent decade. And here we can really see the emergence of this urban to rural difference, where we've got this continuous band of population loss, population decline, running through the central and most rural portion of the region from western mass through southern Vermont across northern New Hampshire, and through most of Maine, we have population declines of greater than one, often greater than 3%. Contrast that with the more metropolitan or more urban portions of the region. And then around the greater Boston area, we see pockets of growth we've got Boston and then we've got this suburban ring that extends even up into New Hampshire and Maine. We've got Fairfield County Connecticut, which is essentially a suburb of New York City. And then we've got the greater Burlington area, Chittenden, Franklin, and the islands, north of, north of Burlington. And so the state has experienced population decline. So we really see a separating of urban and rural emerging in the most recent decade. Or when we try to unpack this growth, I'm going to use to structure this what demographers and population geographers called the basic demographic equation. In unpack any population change in any given place, a county, a state, a country, etc. Any population change is the sum of the births in that place minus deaths, plus people that have moved in minus people that have moved out. So we've got this component of population change that's natural increase or the balance of births and deaths. And then we've got this component of population change that's in migration and out migration. So as I unpack this county level analysis, I'm going to use these two pieces, births and deaths on the one hand, and in migration and out migration, on the other hand, as a way to try to see what's driving this population change. So first, let's look at this natural increase this indicator of natural increase or the balance of births and deaths. So this series of maps presents what we call the birth to death ratio, or births and the numerator of this metric, and deaths in the denominator. For example, births over deaths. If that ratio, and we express this per 100 so if that ratio is greater than 100. It means in that county, there are more births than deaths. And if that ratio is less than 100. In that county, it means that there are more deaths than births, or that county is experiencing what we might call natural decrease. So if we look in the 1990s. We see almost every county, all but five counties in the region, we're enjoying natural increase there were more births than deaths. Some variation between those urban areas and rural areas, there's higher numbers of births than deaths in and around Boston, in and around Burlington, the suburbs of New York City. And then you as you get into the more remote areas. Northern New Hampshire out on the Cape Cod, far down East Maine deaths outnumber births. A decade into the first decade of the 2000s, and we start to see the, those counties that are experiencing natural decrease. We start to see more counties experiencing natural decrease. Western Mass in Southern Vermont starts to experience natural decrease. Natural decrease accelerates in Northern New Hampshire, and we see it in the Northeast Kingdom. And we see more counties in Maine experience natural decrease. And those areas experiencing natural increase again, are centered in these more urban or metropolitan portions of the region. Advance one more decade to the most recently completed decade. And we see really stark differences between those urban and rural areas across the region. All but two counties in Maine are experiencing natural decrease. Most of Southern Vermont, and the Northeast Kingdom is experiencing natural decrease. And we start to see natural decrease, even in places like Connecticut places that haven't seen any natural decrease in the preceding two decades. And we see this sort of widening golf emerge between urban and rural in over time from the 90s into the most recently completed decade. So, I'm going to ask you a quick question here. And I'll give you maybe a minute or 90 seconds to think on this and put some of your responses in the question and answer. And I'm going to ask you a question in function. Why might births outnumber deaths in these more urban places. What factors might contribute to higher numbers of births than deaths in these more urban places. And then Beth can read out some of some of the people's responses to this question. Yeah, I'll give you maybe 90 seconds. All right, Beth, do you want to share some, some of the responses it looks like there's things coming into chat and coming into the Q&A. Yes, yes. Okay. People living longer, younger young people moving to town from rural populations in urban areas younger and also have access to better medical care, higher income in urban areas. Younger people where employment is highest older population in rural areas out of childbearing age decreases in income and fewer jobs, jobs, salaries, higher education, natural beauty, the lake, higher salaries and more employment opportunities younger population. Baby boomers children are leaving and then their children leave. All right. Well, those are good responses. And the one of the real reason there's a couple couple reasons why we see these larger numbers of births and many of the responses. Kind of illuminate this or suggest this cities tend to be younger. And we know younger people have children and older people don't have children. And migration exacerbates this difference. Younger people that come of age in a more rural area, at least initially tend to move to cities, increasing the proportion young in cities, which increases the number of births. And why are on top of that, the fact that immigration tends to be directed towards cities and immigrants tend to be younger. Immigrants arrive. They tend to arrive in crime childbearing years, and the immigrant populations tend to have larger families. So you've got this combination of factors, the age structure, economic differences, and increasingly diverse cities that further contribute to these differences between natural increase in the urban areas and natural decrease in the rural areas. And those differences are only going to widen over time. And that's the reason for providing those answers. Now let's move to the second half of that demographic equation or look at migration across the region. So here we've got same color scheme. And I'm showing net migration for the 90s, the 2000s. Net migration is just the balance of in and out migration so where it's positive. There's more people moving in than moving out, and where it's negative. There's more people moving out than moving in. And similar to the birth to death ratio. In the 1990s. So the net migration experience was positive net migration, though there were more places that were experiencing negative net migration than a natural decrease. But if we look in Vermont, for example, only three out of Vermont's 14 counties had net out migration in the 1990s. And one county in New Hampshire had net in migration. All of the main coast had net in migration but you see net out migration in the most remote parts of Maine. If we move to the 2000s. We again to see more widespread net out migration in Vermont. The whole southern half of the state and much of the Champlain Valley had net out migration. Almost all of Massachusetts, with a few exceptions had net out migration. And the places with positive net migration, interestingly, tend to be what we call more amenity destinations along the coast of Maine, into the mountains of New Hampshire, into the northern mountains in Vermont. And that amenity driven migration becomes even more amplified in the 2010s, where we have positive net migration, really only following the coastal areas. And then the white mountains through like Franconia notch and the Lake Winni Pasaki region in New Hampshire, south of Boston out on the Cape Cod. In Vermont, all but three counties in the 2000s experienced net out migration and take a look at Connecticut and Rhode Island. And Connecticut and Rhode Island, every county had more people moving out than moving in. So, what does this result in this combination of demographic factors of dropping birth rates, decreasing net migration, meaning more counties experiencing out migration, results in a dramatically aging region. So I'm going to present some pictures of that aging. And then we're going to place that aging in a broader demographic context. So here I have by decade, just the proportion of the population under age 19, or you might think of this as the school age population. And in 1990. And you'll put this in some context in a slide or two. In 1990, many counties across the region, most counties across the region had a relatively small share of their population under age 19. And that's kind of puzzling if I've made the argument that the region is getting progressively older. It seems like in 1990 it was pretty old. If a large share of the population was under a small share of the population was under 19. You'll see what that what's what's driving that in just a second. By 2000, the situation has reversed dramatically. Almost every county in the region has more than one out of every four resident under the age of 19. And that shifts markedly in the net over the next two decades over the next 20 years. Whereas today, as of the last census. We're seeing an age structure at least in terms of the proportion of the population under age 19 resembling what it looked like in 1990. I don't know the implications of that. I don't know how many of you in Chittenden County. Follow the news in a place like Addison County directly to yourself, or having big debates in Addison County about the closing of our really small rural schools. It's because we're seeing decreasing numbers and shares of this population under age 19. This is where we see relatively large shares of the population under 19 are in these suburban counties like Fairfield County, and in the ring around Boston. Well, why might this be happening. What are some of the broader demographic shifts that might explain this decreasing share of the population under age 19. And why are the 2000 and 2010 years so different. This requires us to look more broadly at the aging of the baby boom population and the aging of the baby boom echo or the baby boomers children. So this graph shows on the x axis year. And along the y axis to indications of fertility per births the solid line is the total number of births per 1000 people. And the dotted line represents a fertility rate which is the births per woman of childbearing age. So it's kind of an indication of how many babies, each woman would have during her childbearing years basically between the ages of 20 and 40 essentially. And you can see between 1946 and 1964. We see this really rapid increase in live births. This is that post war baby boom. That's so famous that many of you are probably numbers of this baby boomer population. Both by increasing numbers of births and women, each having more children per woman. So at the height of the baby boom in the mid 1950s, the total fertility rate was over 3.6. The average woman was having 3.6 children. Today, our total fertility rate is about 1.7. So the fertility behavior and the total number of births was considerably larger. Another way to put this in perspective is in 2020, the year for which we have the most recent data, the United States saw 3.6 million births. We had a population of about 330 million, which leads to a birth rate of about 11. In 1960, the United States saw 4.25 million live births. So more than half a million more than in 2020. But the total population of the United States in 1960 was 181 million, almost half of what it is today. So we had more births and half the population. So how does this understanding of the baby boom, this huge birth cohort, 70 million plus boomers are out there. As they're aging through their life course, how does it help us understand the aging of this region? Well, if we look at this proportion of the population under age 19, I want you to think about how old the baby boomers are in each of these decades. And how old their children might be during each of these decades. So just think for a minute, you don't have to enter anything in chat. But how old were the boomers in 1990, 2000, 2010, and 2020? If they were born between 46 and 64, you didn't know you'd have to do math during this lecture. So you thought about that for 10 seconds or so. In 1990, those boomers were in their mid 20s to mid 40s. Okay. So if they're in their mid 20s to their mid 40s, some of them haven't even started having kids. The oldest boomers have probably started having kids and their kids are, you know, maybe between five and maybe 15. But by 2000, the boomers, those 70 million boomers are in their mid 30s to their mid 50s. So in 1990, what we see is the boomers have aged out of the school age population. So they're now no longer in the numerator of this ratio, the percent under age 19. But they are in the denominator. In 2000, the boomers clearly aren't under age 19. Most of them have had their kids. So the baby boom echo is now completely under the age of 19, almost. So here, this large share of the population under age 19 is reflecting that baby boom echo. But by 2010, that baby boom echo is starting to age out of the school age population. And the boomers are also out of the school age population. And by 2020, both the boomers and the baby boom echo are now out of that school age population. So we've got a really large denominator. And because we've seen a drop in births, we're not replacing it with populations in the numerator. So you can guess what's happening to the age structure. We're getting a smaller young population. And here we've got the inverse of that. Looking at the old population, the popular part of me, the more mature population, the proportion of the population over age 65. In 1990, the boomers haven't hit age 65. And we see only one county in the entire region, Cape Cod, has a population where one in five residents is over the age of 65. We see increasing shares of green as we move from decade to decade as that boomer population ages. Into those silver years we might call them. To the point now where in 2020, almost every county in Maine has more than 17% of its population over age 65. And quite a few have more than one in five residents over age 65. And once more, here we see really different urban populations in and around Boston and Burlington, compared to this rural swath, kind of following the mountains from western mass through southern Vermont through northern New Hampshire, and all through where the population is 20% or more of the population is over age 65. Today, there's 30 counties in the region that surpassed that 20% threshold. In 1990 there was one. So the region is getting quite a bit older. So so far, I hope you've gained an appreciation for this changing age structure and this widening gap between urban and rural across the region. Let's drill down to look at what's going on in Vermont a little more explicitly. And here I switch my scales of analysis to towns, rather than counties. So we've got a map of Vermont. Again, showing in red or in pink towns that experienced population decrease. And in varying intensities of green towns that were experiencing population increase. And as was reflected in the 1990s. There was widespread population growth at the town scale in the 1990s. The majority of towns in all counties across the state were experiencing population growth. There were a few pockets of population defined, but it was really uncommon. In 2000. That starts to change. If we look at southern Vermont, we see larger contiguous collections of towns experiencing population decrease. There's less of this change on this map in the 2000s, and the areas that were growing. The growth has slowed. There's less of this dark green in this map on the 2000s, then there was in the 1990s. And if we progress to the most recent decade, the 2010s. Just take a look at both the southern four counties. In the southern half of the state and then in the northeastern quadrant of the state. The majority of towns in those counties are experiencing population decrease contrast that with Chittenden County, and at least Western Franklin County. Again, there isn't as rapid increase. But growth is widespread. There's only a few instances of population decline in this area in and around Burlington. So here is where we're beginning to see that evidence of two Vermont's emerging. We've got the northern Champlain Valley, and then the rest of Vermont. And then the rest of Vermont. Another way to look at this is, this is by decade. The proportion of towns in any given county that were experiencing green and growth or red decline. In the 1990s, in every county, 75% of the towns were growing. That's what this line here this line, this top line going across marks the 75% line. In the 2000s, we have four counties that that pop up as counties where the majority of towns are decreasing. They're experiencing population loss, even in places like Grand Isle and Franklin County. We're seeing increasing numbers of towns in those counties experience population decline. And in the most recent decade. Nine of the states 14 counties saw a majority of their towns decreasing. So population loss has become rather widespread. The only county, which has fewer than 10% of its towns decreasing is Chittenden County. All right, well let's unpack what's driving some of these changes. And unfortunately, we can't get to this fine town scale geography, because those data just don't exist. But this just shows over time, births within Vermont deaths within Vermont, the balance of births and deaths and migration. So what have we seen, but we've seen dropping birth rates. We've seen thankfully, stable death rates so the population slow down is not because more people are dying. But it's driven more by decreasing births, which results in decreasing natural increase, and this shift from net in migration to net out migration. The most recent decade is the one in which Vermont saw net out migration. But that net out migration is not happening uniformly across all age groups. But rather, it's happening amongst the primary working age population. We've maintained positive net migration for the population under age 15. Though the geography of that is focused almost exclusively on Chittenden County. The biggest turnaround in migration is for the populations age 25 to 44. So something has happened in the state. That's caused population migration to shift from being a net gainer of 25 to 44 year olds in the 1970s to a net loser of population age 25 to 44 in the 2000s. Other age bands have remained relatively stable. If we look very quickly at the geography of this. This is the net migration of those 25 to 44 year olds that age band that showed the biggest turnaround from net gain to net loss. In the 1980s, we saw many counties experiencing positive gains of the 25 to 44 year olds. In the 1990s, pretty similar, but by 2000, by the 2000s only four counties were seeing net gains and 25 to 44 year olds. Now if we look at the younger population, the 15 to 24 year olds. We see a real clear spatial focusing of the migration of these young populations into two counties, Chittenden and Addison counties. The state has lost 15 to 24 year olds, either through migration into Chittenden and Addison or through migration out of the state to other destinations altogether. So regionally, we've seen a widespread population slow down with birth to death ratios decreasing and in many cases, we've got counties experiencing natural decrease. Urban areas are becoming younger and more diverse. And in contrast, the rural population is concentrating in non metropolitan and more remote rural regions. These patterns play out in similar ways in Vermont with fairly widespread population decline at both the county scale and the town scale. And it's really driven by shifting out migration for that middle aged population. Once again, this results in a relatively young Chittenden County and Greater Burlington area population and an older rural interland within the state. So now let's quickly turn. I know I've exceeded 40 minutes, but I should be able to get through these last couple of slides and just a few just a few minutes. Let's quickly turn to what the evidence might suggest about movement into the state and into the region since the onset of the COVID-19 pandemic two years ago or two plus years ago. The popular press has seized on this. So we've seen stories in the New York Times in Vermont bigger in the Washington Post and on vpr about this, this great American migration as people presumably fled the city for the countryside. And as somebody who studied urban to rural migration for the last three decades. This is pretty exciting for me. The problem is, we don't have really good data to assess this kind of migration. The census was done in 2020. So it could barely barely. It doesn't ask a migration question anymore. It impacted the census itself. And even if it did ask a migration question, any movement was going to be happening after April 1 2020, which is the data which we take account. So we have to turn to some alternative data source. So what I've been working with our mobile phone data. Whether we like it or not, we're carrying around in our pockets really good geolocators. And when we agree to the terms and conditions to download any number of apps, we're agreeing to have our location tracked. So these private sector firms are monetizing your location. And one of the things they do is they assign every mobile phone to a usual home location. And they report the number of phones by usual home location at say, the town, or the county level. So I've taken data from this company safe graph, and I've aggregated their counts of mobile phones by county and by census tract. And I'm going to different census tracts are statistical areas. And then I calculate change in those mobile devices. And I'm going to report that those changes at the county scale and the track scale for New England so we can begin to unpack what's going on. Okay. So the first set of geographies I'm going to use our geography geographic aggregations produced by the CDC the Center for Disease Control, where they report the large metro core counties like where Providence is and where Boston is in orange they have a classification of counties which are essentially the suburbs of those large metro counties. They've got metropolitan areas like Portland, Maine. They've got small metro areas like Burlington, Vermont. They've got these things called micropolitan areas which are small cities like Bennington or Lebanon, New Hampshire. So those are in these lightest shade green and then the dark shaded green are the most rural counties. So on the next graph I'm going to show you essentially change in these devices month by month over the course of the pandemic, these graphs are really busy. So I'm going to quickly walk you through some of the interpretations. But they're divided. The panels are divided by these geographic aggregations large metro all the way down to non core or most rural. All right. If the bars are positive. It means devices are moving into those counties. If the bars are negative. It means devices are moving out of those counties. So in blue. We've got the pre pandemic. This is June 2019 through December 2019. So the six months leading up to the pre pandemic. And we see some shifts, you know, positive and negative in the large metro positive and negative in the most rural areas, slight positives in the suburban areas, etc. During the first months of the pandemic. We see increasingly negative shifts in the largest metro devices were leaving the biggest metropolitan areas of the region. These are the Burlington's. I mean, not the Berlin is the Boston's. In these other areas. We see pretty small shifts some positive some negative but they're not that far from zero, particularly after March. What happened two years ago we'd all like to forget it but we can't. That was when we were ordered to stay at home, not go anywhere. If you crossed a state line you had to quarantine for two months it was really in two weeks. It was really hard to move around. So, during this period of these stringent travel restrictions, we see very little movement. By late summer, you know, September, October, November. We start to release some of those travel restrictions. And where are the devices going where do we see the biggest surge in devices. But why axes on these is all the same, the biggest surgeon devices is happening in these small metro. Micro politics and most rural areas. The most new devices are showing up in areas within what we describe down the urban hierarchy. So there's some evidence of movement down the urban hierarchy, initiated by the pandemic but really accelerating as the pandemic has progressed. And the last way to look at this is at the sub county level. I'm going to speed through this a little bit quickly. But the previous analysis used counties as our units. So if you're a county in a metropolitan area, this is a map of metro areas in New York State. I grew up here in Rochester, New York, in a suburb of Rochester, New York. But all of these six counties are designated as Metro. So in the previous slide they'd all be treated the same. This is the landscape around where I grew up. So even though it's designated as metropolitan. It's distinctly rural, it's suburban or even rural. And even in micropolitan counties. So Washington County is a micropolitan county because it contains an urban center of over 10,000 and Barry. But these are photographs of the landscape in Washington County, a decidedly rural place. So in my last aggregation of this mobile phone device data. I use these sub county classifications of five five groups, the Metro core is like the downtown urban area, the downtown Burlington. The micro core is the downtown Barry, or the downtown Rutland, the urban areas of our small cities. We've got completely rural. Or these areas, like shaded in dark green, the commuter shed. The less dense commuter shed feeding into the urban core of Burlington. All right. So this is the same color schema, the same type of analysis, but looking at those census tracks rather than counties. And I'm just going to draw your attention to a couple things here. First, we see shifts out of that metropolitan core. As we go from March 2020 through the summer months. So this is really the most urban areas of Boston, we see persistent and consistent negative shifts devices were leaving those areas. Initially, where were they headed. The initial movement was into the suburbs. Those less dense tracks that had large shares of commuters going into either the Metro core, or commuting into the core urban areas of the downtown of the small cities the Brattle boroughs the kings, the berries, the Lebanon New Hampshire's. But I think most interestingly, as the pandemic has persisted throughout New England. The largest positive shifts through July 2021 have been into the micropolitan core, which are those urban tracks in our region's small cities. Or into the completely rural tracks, the rural tracks that don't have commuting large commuting anywhere. So these are the, the more remote rural portions of our region. Other areas have seen much more modest shifts as the pandemic has persisted, whether it's the suburbs of the metro areas, the suburbs of the micro areas, and the more persistent growth, at least according to these mobile, this mobile device data is happening into the remote rural regions, and the downtowns of our smallest cities. So to wrap up, Vermont and New England face some demographic challenges. We've seen slowing birth rates and aging population. This is leading to more places experiencing natural decrease layer on top of that. The shift from the region as an destination for in migration to now being an origin for out migration leads to a rapidly aging population and a widening golf between the urban and rural portions of the region and of Vermont as a state. Although there's some optimism or hope, because the evidence suggests that we have seen some renewed population growth prompted by the COVID-19 pandemic. The question is, is that going to persist are people going to stay, or will we see a gradual gradual return to the urban centers as the pandemic subsides. And I apologize I talked for seven more minutes than I had anticipated, but I would love to answer some questions if people have them. We have a few questions for you. What is their growth in the under 19s in Caledonia County around St. Johnsbury in the 2010s and 2020s that seems surprising. When there's also a high population over 65 visit that the young people are not moving out of there. My guess there is that I haven't unpacked the change in any specific county. So I'm, I'm just speculating there. My guess there, it would be that we've got really small numbers. So when you've got really small numbers, small, a small change can lead to a pretty large relative change. So, you have to be a little wary when you look at perceived large percentage changes. When your denominator itself is really small because a shift of five to seven can lead to a really large relative change. Right, right. Okay. And I think we have time for at least one more question. Why is Vermont scroll flat in the 2000s and 2010s. It's the only New England station, a state where that occurred. I think, I mean, that's the thing that we're hearing debated right now. People argue that it's, we have a, we have a mountains of when you compare it to say New Hampshire, it's a very expensive place to live. It's harder to build new housing and housing and that puts an upward pressure on housing costs. So we haven't seen increase in housing stock to accommodate a growing population. I think that's, that's particularly difficult. Yeah, I think that I think that we also, you know, a place like New Hampshire has really benefited from spillover from Boston. Because a lot of, when you look at, you know, the growth of New Hampshire, you really can't separate that from the growth of the expansion of Boston. So as, as the like 128 court or around Boston developed in the 80s and 90s that led to more growth in Nashua and Manchester. We don't have an adjacent region that's spilling over into Vermont. So the first thing we really have now is the upper valley. And you're starting to see some of that around Hartford and White River Junction, and those places you're seeing more growth in that region I wouldn't be surprised if that area got reclassified as metropolitan after this last census it may have surpassed the threshold that's required to designate that as Metro. Well, you've given us so much to think about and so much to watch for in the future. Thank you so much Peter. Yeah, I'm happy to stay on for a few more minutes if people have anything else they want to ask. We have a hard stop at three o'clock unfortunately because this is being recorded for TV show so. Okay, sorry about that. No, that was wonderful Peter thank you just exactly what I was looking for terrific. We'll see you all and enjoy the snow tomorrow. Yeah, our last one. Well everybody. Thank you Peter. Bye bye.