First of all, I’d like to express my personal
thanks to all of the people that have contributed to this report both financially from our sponsors
and many of whom are here today and some of whom are going to be on our panel and also
to my colleagues in the Childress Klein Center for Real Estate Kip Womack and Daniel Wright.
You’ve also contributed to this report and also to some of our graduate students: Sean
Brunson, John Bush, Sammy Jackson and Robert Gouljar who’ve all produced various parts
of the report and we’ll try and talk about it. So what we want to do today is talk about
the high level summary of our report. The report is on our website (realestate.uncc.edu)
and we gave out USB drives with the report on it so hopefully all got a copy of that.
It’s about an 80 page report since they said I can only have one hour and not four, I won’t
go through the entire report. I won’t have that opportunity. But what it will do I hope
is give you an insight as to what we’re showing and then you can go and look at your own leisure
to what is actually in the report. So without any further ado, let me get started. And what
I want to do first is ,see if I can get this to click, OK. There we get. So what I want
to first you just talk about what our goals are.
What is we’re trying to do with the report and what we’re not trying to do. So, I think
if the mic is working I’d rather walk around a little bit. So what we’re trying to do is
give you a comprehensive overview of what’s happening in all the housing markets in Charlotte.
So we’re gonna be dealing with identifying the trends that are happening. We’re going
to talk about the owner occupied the rental and the low income markets. We’re going to
also be talking about some context as to what’s happening in Charlotte compared to a selected
set of cities that are our competitors both regionally and nationally. Now, I’ll tell
you in the report, we look at regional competitors and national competitors today. I’m only gonna
talk about the national competitors here for time and then the more interesting ones to
talk about anyway. So the other thing I want to point out is we’re focused on housing data
and analysis. So we’re trying to tell you what is happening. We’re not doing policy.
We’re not trying to tell you what should be happening. We’re trying to say given the way
things are now here’s what we think is happening. Here’s why we think it’s happening and what
we think will happen to some degree in the future. Our panelists are free to talk about
policy and I think several of them will because they’re more in that arena than we are. We’re
just trying to tell you the public what is actually occurring. So the other thing is,
when I was first approached about doing this it really came out of some work that a number
of people did as part of the Evergreen Task Force which really focused on Mecklenburg
County and the city of Charlotte as we started talking about doing this project.
We realize that you really have to look at this in a regional manner. Part of what is
happening right now in Charlotte you can see this in the data. You can see it in the way
housing prices are moving together is the various counties in the region are becoming
more integrated at least our housing markets are and in fact that’s something that we think
will accelerate and will accelerate primarily because two gargantuan highway projects are
finishing the widening of 85 all the way through Cabarrus and Rowan counties is basically done.
So if you think about it if you go back to 2005 they started widening 85 up through basically
485. Then we’ve got about six months of break and they start another widening and that took
another five miles and then now it’s all the way through Cabarrus county. What that means
is for the first time in 10 to 15 years. 85 doesn’t have a rolling traffic block on it.
And in terms of construction 77 will also soon be completed. So we’re told. And but
when that happens what that means is the relative costs of commuting is going to become lower.
And so what happens then is the integration of these housing markets becomes even greater.
So we felt it was important that we look at the region. And so we wanted to keep it local.
And so for that reason we chose to look at the counties in Mecklenburg County in the
seven counties that physically touch it. So that gives us Cabarrus, Gaston, Iredell,
Lincoln, Mecklenburg, Union, Lancaster and York. So that’s gonna be the set. We talk
about there are times we’ll talk about the Charlotte region. That is what we’re referring
to there. Other times we’ll have to look especially to comparisons with other cities where we’ll
have to look at the Metropolitan Statistical Area. That’s a 13 county region. We’ll try
to be very clear when we’re talking about one versus the other. So what are the key
takeaways. You know I’m from the south. I speak a little slow. I know that. So just
in case or make sure you know what the main points are. So what are the key What key things.
Well first of all a large part of the economic growth of our region has historically been
attributable to its low cost of living. That is primarily been through our low cost of
housing. That is something that’s at risk. That may be threatened primarily because the
population of Charlotte the Charlotte region is growing faster than the number of housing
units we have. And that’s a trend that’s been going on for several years now. That contributes
to prices going up and supply becoming constrained. This supply squeeze propagates downward. Wealthier
people can more easily buy down and renovate and gentrify than less wealthy people can
buy up. It’s a lot easier for some it makes a lot of money to buy a cheaper house and
somebody who doesn’t make a lot of money and buy an expensive house.
So when you have supply constraints what happens is people buy down and that means the biggest
binding of that constraint occurs at the lowest end of the housing spectrum. And we’re gonna
see some fairly dramatic evidence that that is what has been happening in the Charlotte
region at least since 2010 any increase in supply is an important point. Any increase
in supply even if it’s high end actually reduces the challenges on affordability because it
takes that pressure off for wealthier people to buy down. So any increase in supply actually
helps this problem obviously and where we get very low income and low income affordable
housing is even better. But any increase in supply helps the lack of starter home price
properties which I would argue is a pretty significant problem right now is reducing
the ability of people to transition into ownership away from renting at a more so today than
we have seen in the past. And now there is some evidence that the current generation
millennials actually have a preference for renting. I understand that. But even taking
that into account we strongly suspect that supply constraint is keeping more people in
the rental market that would normally be transitioning to ownership than we have seen historically.
This increase in prices is affecting both owner occupied and rental properties home
or housing prices are simply rising and the rising fairly rapidly rising faster than inflation
in this region. So just a couple of things to start with.
Some numbers will need to reference throughout the day. If we look at this eight county region
that we’re talking about we have about two and a half million people in it. We’ve got
about five hundred seventy two thousand owner occupied housing about 300,000 rental units.
Our rental units means any form of renting single family duplexes quad Plexus boats whatever
it is. Essentially it’s got about seventy two thousand vacant properties. We’re gonna
talk about that. You have to have vacant properties in region to absorb incoming growth. Okay.
And we’re gonna see there’s a big drop in the vacant properties in this region. That’s
another way of thinking about this by is how do we allocate or what’s the mix of people
owning and renting and so forth. So of these 900000 total housing units. 663,000 are single
family detached homes. So one thing that tells you is there are five hundred seventy thousand
unoccupied six hundred sixty three thousand single family. There are a lot of people that
are renting single family homes much bigger percentage and frankly I understood before
I did this research. We have about 200000 thousand living in multi-family units and
about 60 thousand living in mobile homes. That’s a larger number in the surrounding
counties and in Mecklenburg but still a sizable proportion. So let’s get to the big trends
we’re going to identify non major trends that we see in the market. Okay. So we’re going
to cleverly label them Trend 1 through 9. So the first one is land prices are rising.
Why do we care about land prices. Well we care about land prices because you can’t build
a house without land and it’s a fundamental component of housing. And so what tends to
happen is when land prices go up house prices go up more. So part of what happens then is
rising land prices would tend to direct the market to higher density usages. What that
means is you’ll tend to find subdivisions with smaller lots. What you think about it
rise if you have to build. If you think about there sort of an equilibrium level of price
that people want to pay for a house. If the price of how land gets more expensive. The
only choice you have is you can try and maintain that price point if you use less the land
which means you put him on smaller lots. That’s why lots today are so much smaller than lots
20,30, 40 years ago lands more expensive. The other thing it’s gonna do is continue
to make houses get taller is less land but build up. The other thing that will happen
in the rental markets is we’ll have a move towards higher density rental properties.
And so again you’ll have apartment complexes that are taller and denser. Rising land prices
will also tend to direct consumers to commute to more affordable land. This is an important
point when you raise the price of land of housing in general it makes commuting relatively
cheaper. It’s just like saying “Hey we’re gonna make
it less costly for you in relative terms to commute”. We know that happens so land prices
matter a lot. So we’re going to show a set of maps here. Now we did not do this data
to be really clear this is some data that has a recent paper published by four economists
at the Federal Housing Finance Administration up in Washington one of them is at Rutgers
University. What they’ve done is for the entire country. So it’s a masterful piece of work.
They have gone and they’ve estimated the value of one acre of land that is ready to be developed
for a house. So this is land that is entitled meaning that it’s a piece of land that literally
if you bought you could start building tomorrow. You’ve got all the permissions you need. So
this is not an acre of land where you’re going out you’re buying from a farmer to start the
process of converting to a subdivision. This will be like going and buying a retail level
piece of land they’ve estimates for every county in the country and actually for a lot
of zip codes too. We’re going to take them want the ones that we care about the eight
counties in this region. And this was mapped by my graduate student, Robert Gouljar, sitting
down here in the front row, and did a great job with it. And what you can see is the pricing
so you got the chart over here saying the various prices in 2012 Mecklenburg had the
highest value and spoiler Mecklenburg is always going to have the highest land value of one
hundred fifty six thousand dollars for an acre this by the way is very consistent with
some data that Jennifer Gooch at Metro Study gave us in this in the report where they come
through a completely different methodology. They actually come to almost the same dollar
amount. So it’s a really amazing convergence between the two lowest was in Lincoln County
at about forty five thousand. So let’s look at what happens next year. Well Mecklenburg
goes to 160, Lincoln stayed about the same we’re up to the following following year.
We now see Lincoln’s actually gone up in price Mecklenburg up to one 162,015 Mecklenburg
is up to one hundred seventy four thousand two thousand sixteen hundred eighty six thousand.
2017 the last year in their study were just under two hundred thousand dollars for an
acre. That’s a big price change over a five year window. OK. In fact if we go to the next
slide what we’ve done is we’ve taken the 2012 versus the two thousand seventeen value for
each of the eight counties in the region. And so what you can see is essentially the
value of the land has gone up in Mecklenburg County by about 33 percent. Now about a third
that’s going to directly translate into housing prices. This gets you to a large part of why
housing prices are changing. And what’s interesting is they’re going up in all the counties you’re
going to see this kind of consistently over and over the other counties are doing a lot
of what is happening in Mecklenburg and one that went down was Lincoln and we suspect
that’s mostly because there aren’t that many transactions that they were able to use to
do the estimation now. So if land prices are increasing that’s our
trend one. What is our trend two this may be the most important graph. If you understand
housing in the Charlotte market this is fundamentally telling us something really important. The
black lines the bars are population of eight county region has come for the American Community
Survey which is a U.S. Census Bureau product. And basically what we’ve had happen is since
2010 we’ve had the population grow from a little over two million to just a little under
two hundred fifty two point five million the blue bars are the total housing units. So
that’s everything that single family that’s rental as public is any sort of housing at
all mobile homes etc. You can see just eyeballing it that obviously it’s not growing at the
same rate. In fact housing and it’s our population is growing at about 2.0 3 percent per year.
Housing is growing at one point three four percent. You can’t do that forever right.
Ultimately you will have a problem. I mean how do markets respond we have tightening
supply which is what this is saying respond responder prices go up. Ultimately prices
will get high enough that people will start saying well, I don’t want to live in Charlotte,
it’s too expensive. And so that will that will end the problem of people moving here.
I don’t think that’s what we want. I think we want a growing dynamic place. And so that
means we got to think about how do we as a community produce more overall housing.
Now we’re not cherry picking numbers. OK. I’m using 2010 because that’s kind of a convenient
point using the American Community Survey data but you could go back to 2000 and even
into the 90s see largely the same trend. So let’s put this in the context of the two thousand
seven through 2017 period. I’m actually going back a little bit further. I’m trying to capture
the boom when we had a lot of building. We’ve had population growth of about 22 percent.
We’ve had housing unit growth of about 14 percent. Now you may say well a population
is that the same thing is households. In essence it is OK. Because the size of households in
this region has stayed steady at about two point sixty five. We have a graph of that
in report. It fluctuates a little bit year to year but there’s been no major change.
In other words household size hasn’t gotten builders that hasn’t gotten bigger. So pretty
much population growth and total household growth is is the same. OK. At least the same
rates we’ve had. So does raise the question how you house these people. Right. Well we’ve
housing because we’ve taken up most of the slack in our housing markets. We’ve absorbed
vacancies. We’ve absorbed about 22000 vacant units since 2010. That’s not the same. You
know it’s not the same units that were there in 2010. But what’s happening is we’re not
building quite as many new housing units as we have people moved to the region.
So we’ve had a reduction in the number of vacant units. Now you got to remember you
have to have vacant units to absorb new people moving into the region new households forming
from people growing up getting married start to have their own families except for so you
know ideally you think well you don’t have any vacant units. Well you can’t do that if
you’re going to be a growing dynamic region you have to have some. And the reality is
we’ve really probably absorbed as many as we can and that is shown frankly by the fact
that prices are rising to some degree that decrease in vacant units is a measure of the
degree to which we are under building as a community. So this is an important theme that
we’re going to be kind of talking about over and over as we go through the talk. So as
an economist I start getting out one other thing. So this is the first of a series of
graphs will show that the rest are at the end of the slot but where we want to compare
Charlotte’s vacancy in this case to our national competitors now get through how it chose national
competitors a little bit later but they’re basically Atlanta Austin Cincinnati Denver
Indianapolis Memphis Nashville Portland Sacramento San Antonio Tampa in the country as a whole.
We have about a 12 percent vacant unit right. That’s pretty steady. That doesn’t fluctuate
a whole lot over time. If you look at this what you’ll recognize
is Charlotte always being green so it’s easy for you to see and since we are UNC Charlotte,
I made it green. So Charlotte here has about an 8 percent slightly over 8 percent vacancy
rate. The only cities with lower vacancy rates are Denver Portland which I realize are spelled
“Portaland”, but it’s really Portland, and Nashville which is essentially the same
as us. I want you to keep in mind Portland and Denver because later on we go show some
stats about them. I think you’re going to kind of knock your socks off but we have a
lower vacancy rate in Atlanta. We have a lower vacancy rate than Indianapolis Memphis and
others. So this is an important thing that says we are getting way below the national
average. And that’s part of why we’re here. So this is this is an issue again as we start
talking about this I want to move into some of the individual types of housing. So so
far I’ve talked about housing units. Now I want to talk about owner occupied housing
and then we’ll move into rental and then eventually we’ll move into the comparisons. So if we
talk about owner occupied housing the first thing we want to talk about is a measure of
supply. Because our argument I’m making is that supply is constrained. This is a graph
in there to two lines. This is a graph of the supply for the Charlotte region which
is the top line in a graph push for Mecklenburg which is the bottom line is a measure that
we’re calling the months inventory months supply of inventory.
So what we’re doing is we’re trying to scale because the size of the city has changed.
So we’re trying to scale down the inventory by how much of what we sell in a given month.
So this data is coming from the Charlotte Regional realtors association multiple listing
service. They gave us complete access to the MLS. This study could not have been done without
them and we really appreciate the work they did for this is tremendous and says how much
they supported us in doing this. So what we have here is going back to 2005 so we went
back that far because I wanted to show you what was happening even during the peak of
the boom during the peak of the housing boom. We had about 8 8 to 9 months supply in housing
by the way. You’ll notice that there’s kind of this general weakness to the graph as because
we have seasonality and housing prices are in housing sales you know a lot of people
don’t really want to sell their home during the holidays. And so you tend to get a dip
in November December January. It’s cold. People want to move too. And then guess what. School’s
out June. Lot of people move then. So you get a lot of transactions now. So what happens
then is during the boom years really to the peak of the boom in late 2006 you had six
months then okay the bust happens and it got to be pretty high 18 months supply.
But look at what has happened since then we’re down to three months supply and in fact if
you look at the lower end of that distribution is under Joe was coming at one point seventy
with him at one point is under two months. So this says there is a low supply now. Well
look at this record. This is these are homes listed for sale on the MLS. That does miss
a couple of things. It misses homes that aren’t sold to the MLS and probably the biggest source
of those be direct new construction sales from builders to consumers. Those may not
not all of those go through but we don’t think that’s material. We don’t think that materially
changes anything. The other thing you may say is Well gee is this because people are
going to offer pad or other sorts things. Now we don’t think so. I’ll show you why we
don’t think so. This graph. This is the number of sales. Now we don’t scale this. This is
just the raw number of sales. But you can see again the black line is the region as
a whole the blue line is Mecklenburg County. But look we’re selling more homes today than
we’re than we sold during the boom now. Population is bigger. We get that. But what’s happening
is you’re seeing a constrained supply and people are buying more homes than ever. So
what that tells you is happening is homes aren’t staying on the market very long.
And in fact if you in the report we have another measure which is the average days on market
and it’s under 90 days. OK. Which is really low by historical standards. So what we observe
happening then is the decreasing inventory of homes for sale coupled with an increasing
number of cells. Sales tell us that the supply of housing is low relative to demand. So again
this is a saying there’s an issue of supply. We still have very hefty demand so as an economist
I care about price because that’s a clear signal to me from the market as to what’s
going on. So this is we’ve got four lines up here. The two solid lines are the average
home price for homes sold through the MLS. The dotted lines are dash lines or the median
home prices. They’re different. They’re always going to be different I’ll show you why. Look
at some of the distributional aspects in a few minutes. But here’s the thing. This is
going back to 2005 average home price in both Charlotte and the region was about 200000
median home prices about one hundred and fifty thousand. I want you to keep that number in
mind. That’s an important number for someone one day later during the peak of the boom.
Yeah it’s a price increase but it was actually fairly mild in the Charlotte area certainly
compared to areas like L.A. or San Francisco or other places. Then we had the bust prices
just kind of leveled off. Right. Individual an individual house may
have gone down a lot but. But broadly speaking prices just kind of low it out. We just had
fewer sales since the peak sort of the trough which happened here in terms of price in 2009
that the trough occurred in nominal dollars and this is in nominal dollars in 2009. If
you do an inflation adjustment the trough actually occurred in 2011 we did both. We
do this both in nominal and real dollars in the report. I’m going to show you a nominal
cause frankly that’s what most of us actually care about because that’s what we buy things.
You can see from 2009 through roughly 12 prices didn’t change a lot. But then look look at
what’s happening both in median and mean where they’re accelerating now. In fact if we go
from the trough to today in median in nominal dollars we’ve had four point seven eight percent
annual growth rate for the average home. The median is about the same. OK. That’s a lot
that’s healthy healthy growth but it doesn’t tell the whole story because it’s only looking
at two points of that distribution the median and the mean we really want to look at. I
think something a little more telling which is look at the whole distribution so we’ve
done it. So what we have done in my graduate student Shawn Bronson did this and probably
about forty five different ways that asked me to do this.
But what we have done is we’ve taken the entire distribution of home sales and we’ve created
histogram so we’ve we’ve budgeted it into ten thousand dollar increments. And then what
we’ve done is we’ve shown the frequency of each increment to in 2005. We have this distribution.
There’s a few things I want to point out about it. First of all it’s not symmetrical right.
We kind of tend to think anything with distribution you think of a normal distribution that smooth
bell curve. This does not exhibit that property. This is much more like a log normal distribution.
What that means is that all these numbers way out here even there aren’t a lot of them.
This fellow is six hundred thousand or so. Tends to pull the average far to the right.
And the median is going to be half way in this distribution which is going to be at
this point right about here. But what’s at stake. I think the most interesting is look
at the bucket that occurs most frequently. So that’s kind like you said that shows a
random home just throw a dart board. Random home which bucket is it most likely to wind
up in and that’s the most picked one. That’s one where you had the most occurrences I’ve
labeled that green because I want you to be able to keep your eye on it in 2005 by the
way statistically it’s called the mode number back into stats classes mean median mode.
Yeah I’d forgotten what that was to. But it’s the mode. So we’ve got one hundred and thirty
thousand is the most peaked point of this distribution in 2005 let’s walk it forward
every year 2006. We’re at the peak of the boom and all you see happening right is a
little bit of a little bit of more stuff happening on the right. 2007 comes along okay. Home
sales starting to fall. We’re starting to enter the recession 2008. It’s a rough time.
Okay so rough time is gonna get worse two thousand nine ten eleven. Now once you’ll
notice something that green line it has not moved still one hundred and thirty thousand.
That’s the mode. Look at what has happened to the left of that mode right. You see a
lot of homes. Well a large percentage of homes selling to the left of one hundred and thirty
thousand 2012 starting to get a little rebound. Starting to see some growth 2013 2014. We’re
almost looking like that distribution in 2005 right at least a lot more peaked again. Look
at that mode. Hundred and thirty thousand hasn’t changed from 2005 through the entire
recession into the recovery in 2014. The mode house price was in one hundred and thirty
thousand range. Nothing has changed. Now watch 2015 shift to the right for the first time
2016 2017 and finally 2018 I drew a red line at one hundred thirty thousand so the Green
Line is still the mode. Hundred and thirty thousand stolen is is was
the mode in 2014 it’s one hundred and ninety thousand in 2018. You’re talking about a fifty
thousand dollar difference. Sixty thousand dollars difference in four years. That’s a
big change. That’s distribution only a big change. By the way we did not put the several
hundred a year homes in the million dollar range just because it made the graph hard
to see. Didn’t change anything at all. So here’s this amazing statistic to me. Remember
I said hundred fifty thousand dollars was the me the median home price in 2005. I don’t
know about you but for me I always kind of thought of one hundred fifty thousand and
the starter home seemed about right. Frankly it was aspirational for me when I actually
did buy my first starter home in the 90s. But in every year prior to 2014 at least for
data we have gone back to 2005 35 percent or more of homes that sold sold for one hundred
fifty thousand dollars or less 2018 met County 13 percent. That is saying that the starter
home market is way above hundred fifty thousand now. In fact you’d have to go. I don’t want
to throws a precise number on it but it’s gonna be north of 200 maybe make this. So
here we plotted out the percentage of homes that sold for one hundred and fifty thousand
dollars or less each year. And you can see it’s getting really hard to find that hundred
and fifty thousand dollar home want to show you another thing.
So I had my grad student Shawn Bronson. Create a map for us. This is a heat map. No it’s
not saying rain’s coming. Probably is but yeah I thought Brad Panovich was really cool
and I always want to have a color radar so here’s my chance. So this is a heat map so
we’ve intentionally blurred so you can’t identify individual homes. It’s a heat map with 150
thousand dollar homes and where they sold in Mecklenburg County essentially. Basically
this is for eighty five running around the whole thing. OK you see it. Five OK. We’re
probably not shocked. Myers Park didn’t have a lot of those. OK but you’re going out Independence
are a lot. There’s a lot up in the university area. There’s a lot out long 85. There’s a
fair amount even down in the kind of Ballantine ish area and Roe certainly the 2018 gone OK.
They’re just gone. I mean there’s some there’s some but there’s not many. Actually did this
review with hundred thousand dollar prices and literally just didn’t see enough to make
it interesting. So this is a dramatic change. This tell and by the way I’ve chosen to work
with Mecklenburg County really Charlotte here not to pick on them. I did it because it’s
what you can see if we do this at any scale. You get the same effect. OK so this is not
saying there’s great cheap housing we had over in Gaston or Cabarrus or Iredell.
This is true everywhere what we’ve done here is something that I think
what’s even more telling is we’ve taken in two thousand and eleven. We took the 10th
percentile. We took the distribution of homes. We said let’s find the home. That is where
90 percent of homes are more expensive. That’s a 10th percentile of the distribution. And
then we’re gonna look at the home that’s got 75 percent of homes are more expensive that
sold I guess the 25th percentile the median seventy fifth percent on the 19th. Then let’s
look at the 10th percentile in two thousand eighty 25th etc. So it’s not the same home.
When we really clear on that saying the 10th percentile home price if you do that the 10th
percentile home price and you say it’s the same basically for the Mac Mecklenburg County
or the region as a whole has had an annual price change of 16 percent median is more
around six six and a half nine percent house four percent. In other words this is counties
showing what I was talking about earlier which is the the price compression is affecting
the lowest end of the distribution the most right. This is where we’re saying is harder.
The price changes have hit the low end of the distribution the most that directly affects
affordability okay. Really understand what this means we’ll look and try to bring into
this real terms. So what we’re doing is what we’re going to ask the question for somebody
with a given income. What price home could they afford. And then
what percentage of homes sold could they get in 2018. So we make some assumptions and we
go through the calculations in in the report. But what we’re trying to do is we know we
assume that they have to pay utilities. We assume they have to pay property tax. We’ve
seen that a product mortgage insurance and they’re using a 95 percent loan to value ratio
mortgage which is probably a generous assumption so based on this we can calculate how much
house they could afford and not spend more than 30 percent of their total income on the
house. When you talk about the housing research literature that no 30 percent spent on housing
is generally considered the barrier to affordability through let’s say something as cost burden.
If they spend more than 30 percent so we’re asking for these different folks. What does
being able to buy a house and not be cost burden look like so go back to the distribution.
And so this is a distribution 2018 except I’ve locked off everything about six hundred
thousand just so it’s a little easier to see. So we want just to be clear, we went to the
North Carolina star jobs database which you can go look at yourself as a publication the
North Carolina Department of Commerce and they give us the median income for a whole
bunch of professions we probably have 15 or 20 of them in the report but just look at
a few of them here. The saw the lowest what we went with was a
hairdresser. Median income was twenty two thousand nine hundred dollars. That’s about
50 percent more than minimum wage that person could in 2018 given interest rates and all
the other things you have to pay afford a home forty three thousand nine hundred sixty
six dollars and not be cost burdened. That’s zero point two percent of the distribution.
That’s that black line. That’s what they can buy. OK they’re not bond homes. They’re in
the rental market. We don’t find that shocking. Let’s look at some other things. So let’s
look at a firefighter now. Most of us think of a firefighter as a permanent career job
right. It’s a civil servant job but it’s certainly one we assume let you have a decent quality
of life. Median income. Now I will say this is the state median so for five years experience
by the way is higher in that county. I know that because there’s some supplements at urban
areas yet but it still gives you a pretty good idea of where we’re talking affordable
house seventy eight thousand six hundred sixty dollars three percent of homes sold very hard
go to the next teacher police officer. They both median incomes. Elementary school teacher.
Median income was within one hundred dollars or so of each others about forty two thousand
affordable home one hundred twenty two thousand less you have about eight percent of the distribution
of homes. So again these are jobs that you think of
as career long term professional jobs. We expect people in those sorts of jobs to be
able to live in housing. That’s permanent housing. They can live in permanent houses
can be permanent rental housing to a large degree. If we go up a little bit more librarians
fifty thousand lets them get about 17 percent of the income the homes registered nurse fifty
eight thousand less and get to 30 percent go to an accountant. Some of best friends
are accountants. They get about two hundred fifteen thousand of homes about 40 percent
of affordable homes go to a civil engineer as opposed uncivil engineer pleasant engineer
I like to think so. Seventy two thousand median income for a home up to about 240000. Put
this in here because that gets you to about 50 percent by the median home. So basically
to be a civil engineer you need a master’s degree about the median and pretty high tech.
Just because I was getting depressed, was to take to get really out there, we needed
a pharmacist. They they get paid median income about one hundred twenty four thousand to
get you about 87 percent of the thing. Now of course the thing is the reality is many
of us especially if you’re relatively young would buy more than that you take the cost
burdening and the theory that for a few years would be cost burden but your salary will
go up over time. So we know people will actually buy more when
they’re younger they’ll take that cost burden on. But it’s clear there are groups of people
that we have traditionally thought of as being middle class who are getting priced out of
the out of the homeownership market right now. And that’s a supply issue because again
if you roll these numbers back to 2005 you’ll find they got much more much higher percentage
of the total distribution so let’s move to the rental markets. So we talked about the
rental markets again 60 something percent of people live in owner occupied housing.
But we saw a sizable number of people that live in rental housing about 300000 people
are households in the eight county region. First thing I want to show you is the distribution
because again I was a little surprised about this 40 percent of people that rent housing
live in single family homes and that number has stayed relatively fixed for a long time.
It’s gone up a little bit in the last few years but that’s about 12 percent of the total
population lives in rental single family housing that has traditionally been a larger percentage
in these suburban counties which isn’t really that surprising because you get especially
in the rural parts of some of those counties there aren’t any apartment complexes but it’s
still a large percentage. We’ve got about 9 percent living in duplex type pile housing
about 40 another 40 percent in different types of apartments and about 7 percent of the regional
population live in mobile homes. 10 percent of the rental market is mobile
homes. We don’t have quite the same data for rental. There’s not a single consolidated
source as good as the MLS is when the owner occupied side. So we’ll look at a couple of
measures in which rents have gone up so we’ll start with the American Community Survey.
They ask everybody who rents in the survey say how much did you pay in rent last year
per month two thousand ten. This was that distribution we lopped off everything under
350 because it’s not good relevant and they don’t go beyond two thousand in their questioning.
We know in downtown Charlotte there are apartments that go for that. This includes apartments.
It includes single family housing and so it’s everything. So this is a distribution. You
can kind of see this little bit by modal and that you got a lot of people in the six hundred
dollar range. And then another group kind of out here in the 800 to 1000 range let’s
look at the last year for which I have data from census which is 2017 that’s what it looks
like. That’s a big change right. And so what you can see is there’s just been this kind
of massive shift that way. Right. Nearly 25 percent of our nearly 20 percent of respondents
are now reporting a thousand twelve hundred dollars a month. Now obviously there’s been
a little bit of inflation not a lot. This is again as I said everything that you see
is driving prices upward. We have been very fortunate that we’ve had
a lot of apartment growth in this region. So this as you go back to 2000. This is coming
from co-star which is the best source of data for apartments. So this is now not looking
at single family or anything. This is apartments. So you can see the eight counties in value
like co-star collects data on virtually every apartment complex with 40 or more units in
it. They collect a lot of data on unit complexes that are smaller but it’s not universal. So
we are probably missing some some 10 and 15 unit apartment complexes. We’re just nobody
collects that sort of data. So we had about one hundred thousand units. Right. Two thousand.
Now we have one hundred sixty ish thousand something like that Fiat in the ones that
are probably undercounted the small ones that probably boost us up to 180. Be my guess you
can see that we’ve had a pretty sharp increase since 2011. Right. If if you kind of look
at the top of that line you see it just really kicks up right then. These are rents. And
so we’re looking at three different levels of rent. Rent for an apartment now in a apartment
is going to be your your nicest apartments typically biggest newest best location best
amenities kind of the place that we all aspire to live in. And what you can see is that prices
gone up to again per co-star between between 13 and 14 hundred dollars a month.
Average. There’s a lot of variance in that B which is gonna be a little bit older stock
a little less desirable location little fewer amenities. Again you’ve had a lot of growth
and in fact four point six percent since 2010. Growth sounds an awful lot like the median
home price over that time period. That’s not a that’s not a surprise. These are close substitutes
for each of C units which are going to be the lower quality older typically not very
good neighborhoods perhaps once you remember something median rent is somewhere between
850 and nine hundred bucks. That’s an important number to keep in mind. Couple of things I
want to point out again you’ve got growth of 3 percent in a unit at the very top of
the distribution in the bottom part of the distribution have actually had slightly higher
rents and in fact look at something interesting look at the aliens. We don’t have that many
apartment complexes in Charlotte in 2000 but look at actually what happened. It actually
went up down and stayed down for quite a while before starting to rise again for the B and
C units. If you go back to 2000 even in real terms even adjusting for inflation they’re
higher today than they were then. That’s not true for a units for a unit. It’s actually
cheaper to rent one today in Charlotte than it was in 2000 in real inflation adjusted
dollars not by much but a little bit. OK so I talked about cost burdening costs
burdening again for we’re defining that to be spending more than 30 percent of your gross
income on housing plus utilities that percentage in the Charlotte region is about 45 percent
among renters. That’s a really big number. Now we’re fortunate this is showing that since
2010 it has actually trended down. That’s because things have gotten cheaper because
2010 you’re in the recession. So a lot of people had really it’s more of an income issue
right. But you’re looking at all renters. Forty five percent or so or cost burden. That’s
a large number so obviously in addition to sort of the general rental market we want
to talk a little bit about subsidized housing in the sense of subsidized public housing
kind of three major components to that. There’s low income tax credit housing. There is housing
choice voucher housing which is federally assisted housing and then there’s also owned
public housing which isn’t a very large component now to be really clear we have very little
control over this in the region because most of these are set by the federal government
La Tech housing for example the total number of tax credits that are available are set
by the federal government. When we talk about housing choice vouchers the number of vouchers
is set by the federal government even though we administer it locally. It’s actually all
funded by HUD. It’s not funded by the cities region of the state.
So just keep that in mind as we as we talk about this. But if we look at La Tech units
to begin with so low income housing tax credit and the way that works in case you’re not
familiar with if you’re a real estate developer and you want to build a low income housing
tax credit unit what you do is you apply to the federal government and they will say to
you fine. What we will do is if you agree that you will for 30 years put either 40 percent
of your units in that complex available to people who make 60 percent or less of the
area median income or 20 percent for people who make below things the 30th percent from
saying that right 30 percent of area median income then we’re going to give you a tax
credit that you can sell and that’s how you can raise equity for this property. So it’s
a financing mechanism in the region there about 15000 units meaning apartments that
are under the LA Tech program. That’s roughly split evenly between Mecklenburg and the eight
surrounding counties. So a theme you’ll notice as you read our report is that almost everything
is 50/50 between Charlotte and the seven surrounding counties. Their populations are the same.
It’s just that it’s a little less dense in the surrounding counties. So in addition to
that we looked at some data that Fulton Meachem’s group the Charlotte Housing Authority gave
us to try and understand what does the population of lower income residents look like.
So in housing choice voucher programs it sharp Charlotte Housing Authority get about eighty
four hundred households of those it’s about twenty thousand people average annual household
wage nine seven hundred dollars or about eight hundred and fourteen dollars a month. Remember
what I said the average price of a c apartment unit was but a 850. It’s literally more than
they make in a month. Average total household income is about fifteen thousand. That includes
assistance they’re they’re receiving there is essentially no market based housing units
that can be afforded those House levels. Now we can we can talk about why their incomes
are so low there. There obviously is way beyond the scope of what I can do. But the fact of
the matter is as a society we have a lot of people who are in that price range and that
income level. We have to decide how we’re going to house them. This is the distribution
to HUD maintains a database of all low income housing tax credit properties in the region.
Had Robert. Map them for us saying See there’s a lot in Mecklenburg County actually quite
a few in Cabarrus down in York and in Gaston not so many in Union, Lancaster, Iredell or
Lincoln so we also have the just play them out by county just enroll numbers so this
is the number of units in each county. And again if you add up the other seven counties
are roughly equal to what Mecklenburg house so even if you add on top of that Housing
Choice Voucher Program said double switch you got doesn’t quite double say it did.
You’re still talking maybe you’re up to fifteen sixteen thousand units in the Charlotte in
Mecklenburg County. How many households have income of 15000 thousand or less in this region.
This is coming from the American Community Survey that’s it. That’s a large number. Now
I gotta be honest. Not all of those folks are people who would traditionally think of
as being underprivileged. Graduate students tend to fall in that category. Okay we’re
not worried about them so much. Okay but I can tell you there are not a lot of graduate
students in Gaston County so this is mostly the folks that are not able to earn income
above this. There is demand and people at the City of Charlotte have done a great job,
thank you. Trying to estimate the precise numbers of folks that are there are underserved
right now. Don’t have any criticism of their their methodologies or anything. We’re really
not trying to get there eat ourselves but we’re just saying there’s a big demand there’s
a large proportion of the population that is underserved and that essentially there’s
no reasonable expectation you’re gonna have purely market driven outcomes they’re going
to house them. This is the distribution of peers. This came directly from the Charlotte
housing authority and this is a distribution of where people getting vouchers live they
think he’s spread out really throughout the entire city and these go into general apartment
complexes that are willing to accept the voucher. So this can be really nice places that folks
were living. So again we can look in each county and ask
how many apartment complexes are set to themselves be the complex that has a housing choice vouchers
because basically a voucher can can either be with the individual in which case wherever
they move the voucher follows them or it can be based on the complex in which the person
is living and the person moves it stays in that complex and Mecklenburg County there
a little over 50 complexes that have project based vouchers. What’s interesting to me is
you look at some of the other counties and by the way, this is set by the federal government.
So this is not something that local government can really affect. But what’s interesting
is Cabarrus and Gaston as a percentage of population have more it’s kind of an interesting
interesting point. OK so trend nine there’s a pressing need for low income rental housing
be it public or private. It’s just we clearly need go through some quick comparisons. That
time I had at this point the report has kind of feeling depressed. Geeze, it is expensive
and therefore I can’t have 300 people come into a room and then leave just all dragging
and so let’s just say there’s some reason for hope. So what we’re gonna do is we’re
go back we’re going to look at several key metrics how Charlotte compares to other regions
and so we’re going to have to do this at the MSA level because we don’t have the micro
data we would need to really draw what’s happening in Charlotte with the comparable area in these
other areas. So we’re now looking at the MSA That’s a 13
county region. And it means some of the numbers are gonna be lower because a lot of those
exurban counties are really rural. OK great people but they are rural. Again, going to
look at what we are calling our national competitors set we chose these primarily based on population.
We tried to find a set of communities that were similar in size to Charlotte or were
obviously close by national competitors like Atlanta. Obviously Atlanta is twice the size
of us were more than twice the size of us. But you know Austin Texas is about our size
Cincinnati and Denver’s a little bit bigger. We wanted some geographic diversity to say
could see what’s happening across the entire country. So what do we see start with land
remember I said to look at Denver and Portland look at that Portland Oregon one acre of land
for residential use over one point three million things seem a lot better in Charlotte off
time tell you. Yeah. Portland I get. Okay if you had been there a nice city but it’s
got a lot of geography that constrains where you can build. All right. River all sorts
of water. Denver you got the mountains to the west. There’s a lot of prairie to the
east. You start talking about other cities so Austin Texas. There’s nothing that prevents
that city from growing. OK. I don’t really understand the economics of why they have
such high rents and maybe Matthew McConaughey is buying a lot of land there.
But if you look at Charlotte you look at cities like Cincinnati Indianapolis Memphis Nashville
we’re growing but we’re growing at about the national rate. In other words increasing land
prices are happening everywhere. Listen every major metropolitan area. Well what about home
prices. Well we’re not as low. Right. If you look at again Portland Sacramento they’re
up into the median home prices 350 to 400000. Median. We don’t want to get there. Right.
Remember Denver Portland and Nashville had the lowest vacancy rates. And you see that
translating into higher and higher home prices you look at the growth rates you realize we’re
growing our home prices are growing pretty rapidly compared to most of the competitors
with the exception again of places that are just kind of into hyper growth mode in terms
of prices one of the measures. So one of the problems with this this graph is it doesn’t
take in fact there could be differences in earning power. So one of the most common measures
people used to trying to adjust for that is something called the median multiple. What
we do is we take the median home price. We divide it by the median household income for
the year. In essence what it’s doing is it saying how many years doesn’t median earner
have to work to be able to pay for the median home if they didn’t spend money on anything
else. Generally less than three is considered affordable between three and four is moderately
unaffordable under five is severely unaffordable greater than five is extremely unaffordable
and I don’t know what’s worse when you get to six.
OK. Challenge for adjectives. Well here’s what we got. And so what we’ve done is a it
in 2013 and 2017 why 13. I’ll tell you why. It’s because we’re using MSA data in 2000
between 2012 and 2013 the Census Bureau redefined the Charlotte MSA. It expanded it when it
did that. It screwed up all the numbers for us. So I’m just trying to use the most consistent
set of numbers I can. So Charlotte to that. So the lighter bar will be 2013 2017 is the
solid bar which you can see as we’re in the moderately unaffordable range and it’s getting
worse but you’d start looking at some of these sitting in Portland Sacramento there there.
Their having to come up with that next adjective because you don’t know what they’re doing
essentially in some cities like Tampa are very rapidly getting worse so they’re having
a problem there with both a decrease and increasing housing prices nationally and some decreasing
income. So there’s still a little depressed basic what’s happened in Charlotte is our
housing prices have risen just a little bit faster than our incomes. And so it’s not that
our housing prices are so much better than our incomes actually have gone up since 2013.
If we look at median rents and annualize median rent growth you’ll see that we’re pretty high
against the NSA as well certainly. Eight hundred but you see where we’re kind of in the upper
third. The median rents. So again a lot of lot of interesting points here.
We’ve had pretty pretty solid percentage growth as well. OK so let me summarize because we’re
just about out of time. Charlotte region has long benefited from having good low cost of
living. Lot of that’s coming from low cost of housing some challenges that we face land
prices are rising. That’s really the core that’s where you really start having if land
prices are rising it’s hard to keep anything else from rising populations growing faster
than the number of housing units house prices have increased the most at the very low end
of the distribution. This is that compression I was talking about that’s making it harder
and harder to think about what that starter home looks like apartment growth is helping
but relative to the entire market there’s not been enough because prices are still going
up middle income affordability is threatened there’s not enough low income affordable housing
and that’s a big problem. But all hope is not lost. We still maintain a pretty competitive
economy in a pretty competitive housing market relative to our national peers.