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SOFT LANDING LIKELY;
Borrowers Should Limit Risks
By Mark Milner, Senior Vice President and Chief Risk Officer, PMI Mortgage Insurance Co.
In This Issue
How to Choose
a Mortgage:
Consider Benefits
and Risks
Local Economic Patterns
and MSA Indicators
Job Growth Due
to Real Estate
At first glance, the numbers are striking: 11 metropolitan areas now
face a 50% or greater risk of price declines, appreciation has slowed in
many of the top markets, and affordability remains a significant challenge
for American families in regions where appreciation has been high.
PMI MORTGAGE INSURANCE CO. WINTER 2006
& ECONOMIC
REAL ESTATE
TRENDS
With a closer look, however,
it’s clear that there are no
surprises with this quarter’s
U.S. Market Risk Index. What we’re
seeing is what we’ve known was
coming—a moderating of appreciation
that, over time, is likely to bring prices
back into line with the economic fundamentals
that support them, particularly
incomes.
Why is this happening? The short
answer is because it had to. In many
markets, we’ve seen record home
price appreciation for the last few years.
Take San Diego, CA, with appreciation
of 27% from the third quarter of 2003
to the third quarter of 2004, Riverside,
CA, with just under 30%, and Las
Vegas, NV, leading the nation at 36%
appreciation year over year.
(continued on page 2)
U.S. Home Price Appreciation
OFHEO Home Price Index, select measures of appreciation
2
(continued on page 10)
Borrowers Should Limit Risks (continued from page 1)
These increases were unsustainable because people’s
incomes can’t support the kinds of home prices that result.
And this quarter’s data shows us that, in fact, appreciation is
moderating in many of these markets—slowing to under 11%
in San Diego, 18% in Riverside, and about 13% in Las Vegas.
It’s likely that this slowing will persist because the double-digit
appreciation we continue to see in many markets is still high
by historical standards of 4% to 6% per year. But because the
national and regional economies remain strong, providing a
counterbalance to slowing appreciation, at this point we
believe a soft landing is the most likely outcome.
What does this mean for American consumers? We all need
to become risk managers, by evaluating our financial situation,
assessing our exposure to the risks that are out there, and limiting
them where we can. Here’s what I mean. When you take
out a mortgage and buy a house, you take on a number of different
risks. There’s geographic risk—do you live in an area
where prices are likely to decline? There’s property risk—is
the house you bought solid? There’s the risk inherent in your
mortgage product—does it expose you to payment shock risk
by building in a big increase in your payment down the road,
or to interest rate risk?
Geographic risk is mostly out of our control. We can limit our
risk by choosing a neighborhood that suits our needs and
those of our family, but beyond that we live where we live
because that’s where our jobs or families are. In other words,
most of us can’t move from a higher risk area to a lower risk
one just to lower our geographic risk. Property risk is something
most of us already manage pretty well—that’s what
inspections are for. That leaves the risk inherent in the mortgage
product we choose.
Using best- and worst-case scenarios for interest rates, the
charts on page 4-5 compare the payment shock that can occur
with different loan products because the product adjusts with
short-term interest rates, has a built in payment adjustment
(such as when an interest-only period expires), or both. The
charts also compare equity build up over time.
Recent underwriting guidance released for comment by federal
banking and thrift regulators indicated the risks these
products contain has raised concerns at high levels not only
for the safety and soundness of our lending institutions, but
also the impact on consumers’ financial health, particularly if
they don’t fully understand the risks they are taking on. While
it’s too early to predict the final form this guidance will take, its
release is indicative of the magnitude of risks in the market.
With markets returning to a more normal rate of appreciation,
we’re going to have to earn our equity the old fashioned way:
by paying down our mortgages and experiencing slow and
steady appreciation over time. And that, combined with the
fact that interest rates appear to be headed up, means that
it’s a good time to take another look at a fixed rate loan,
which lets you limit the total risk you take on when you buy
a house. u
3
Local Economic Patterns
and MSA Indicators
The table on pages 6 and 7 represents PMI’s view on
house price risk for the 50 largest U.S. metropolitan
statistical areas (MSAs). The U.S. Market Risk Index
scores were estimated using third quarter 2005 house
price data provided by the Office of Federal Housing
Enterprise Oversight (OFHEO), employment data published
by the Bureau of Labor Statistics (BLS), and the
Affordability Index calculated by PMI. The table shows
the average Risk Index score has increased from 218 to
261, meaning the nation’s 50 largest metropolitan markets
now have, on average, a 26% chance of experiencing
a house price decline within two years. The main
reasons for this increase in risk are a slowdown in price
appreciation and lower affordability in most MSAs.
Eleven MSAs now have more than a 50% chance of
house price decline, compared to only five MSAs in the
previous quarter.
According to the data released by OFHEO, U.S. home
prices have appreciated 12% from Q3’04 to Q3’05,
down slightly from 14% reported for the previous four
quarters. Our table also shows that house prices in the 50
largest markets experienced average price appreciation of
11.1% (compared to 12.9% last quarter and 13% four quarters
ago). Only 12 MSAs had price growth below the 25-year
historical national average of 5.2% (the same as last quarter
and down from 14 MSAs four quarters ago). While home
prices nationwide continue to appreciate rapidly, regional
analysis shows a slowing trend in appreciation in select housing
markets. Only 6 MSAs experienced price growth of 20%
or higher, compared to 12 MSAs last quarter, and 21 out of the
25 riskiest MSAs have experienced a slowing of appreciation
(indicated by negative acceleration on the chart), led by Las
Vegas, NV, followed by San Diego, CA. Price deceleration has
occurred mostly in markets that have enjoyed rapid appreciation
over the last several quarters, and we believe this is a
WEST
MIDWEST SOUTH
NORTHEAST
Regional Home Price Appreciation
by Census Division, percent change over previous four quarters as of third quarter 2005
(continued on page 10)
Year 1 1,551 1,672 1,169 1,940
Year 2 1,551 1,672 1,243 1,940
Year 3 1,551 1,672 1,322 1,940
Year 4 1,919 1,672 1,407 1,755
Year 5 1,919 1,672 1,499 1,755
Year 6 1,734 1,672 2,228 1,755
Payment Shock 11.8% 0.0% 90.6% -9.5%
Balance Paid 9,349 17,371 -24,718 18,989
Equity Buildup 74,345 82,367 40,278 83,985
5.75 5.75/7.25 6.25 6.25
Option ARM 30-year FRM Interest Only 3/1 Piggyback 3/1
ARM/HELOC
Rate Assumptions (%)
(Fully-Indexed Rates)
Monthly Payment
End of Year 5
Best Case
TABLE 1.
MONTHLY MORTGAGE PAYMENT AND RATE - BEST CASE SCENARIO
4
Consumers face a dizzying array of mortgages today, with different
advantages and disadvantages.
The tables here and on the facing page show how four of the most popular
loans—an interest-only (IO) loan, a “piggyback,” a payment option
adjustable rate mortgage (Option ARM) making the minimum payment
(less than the interest owed, so the principal balance increases), and a 30-
year fixed rate mortgage (FRM)—would be affected in different interest
rate scenarios.
In all cases, we assume a $300,000 home price, purchased with a 5% down
payment and a mortgage for the remainder (a combined loan-to-value (CLTV)
ratio of 95%) and home price appreciation of 4% per year. Because of the
low down payment, the interest-only, option ARM, and 30-year fixed rate
mortgages carry mortgage insurance. The piggyback, instead, uses a home
equity line of credit (HELOC) to make up for the low down payment.1
Table 1, the “best case” scenario, assumes that interest rates remain
unchanged for the next six years. Under this scenario:
n The interest-only loan sees a payment shock in year four, when the interest-
only period expires (and a subsequent drop in year six, when enough
equity has accumulated to cancel mortgage insurance).
n The option ARM sees gradually increasing minimum payments for the first
five years resulting in a higher loan balance and a significant payment shock
in year six when the loan is recast and fully amortizing payments are required.
n The 30-year FRM sees a payment drop due to the cancellation of mortgage
insurance in year four—earlier than the IO because equity builds faster
with the 30-year FRM.
n While the monthly payment is lower on the IO, piggyback, and option
ARM, a borrower will build equity faster with the 30-year FRM. After five
years of making just the minimum payment, the principal balance due on
the option ARM has increased (shown in the chart as a negative number).
0
500
1000
1500
2000
2500
3000
0 12 24 36 48 60 72 84 96 108
30YR FRM
Best Scenario - I/O 3/1
Best Scenario - HYB 3/1 + HELOC
Best Scenario - Option ARM
0
30
60
90
120
150
180
0 12 24 36 48 60 72 84 96 108
30YR FRM
Best Scenario - I/O 3/1
Best Scenario - HYB 3/1 + HELOC
Best Scenario - Option ARM
-30
-20
-10
0
10
20
30
40
0 12 24 36 48 60 72 84 96 108
30YR FRM
Best Scenario - I/O 3/1
Best Scenario - HYB 3/1 + HELOC
Best Scenario - Option ARM
Consider Benefits and Risks
H O W T O C H O O S E A M O R T G A G E :
Months
Months
Thousands
Months
Thousands
EQUITY BUILD-UP WITH PRICE APPRECIATION
BALANCE PAID
1 MI rate on interest-only, option ARM, and 30-year FRM is 0.78%. For option ARM, minimum payment option (with starting rate of 1.5% and annual increase of 7.5%) is selected until the loan
is recast in year six or at 115% of original loan amount.
MONTHLY PAYMENT
Year 1 1,551 1,672 1,169 1,940
Year 2 1,551 1,710 1,243 1,940
Year 3 1,551 1,747 1,322 1,940
Year 4 2,482 2,239 1,407 1,755
Year 5 2,678 2,435 3,140 1,755
Year 6 2,493 2,473 3,142 1,755
Payment Shock 60.8% 47.9% 168.8% -9.5%
Balance Paid 5,231 14,045 -41,624 18,989
Equity Buildup 70,227 79,040 23,372 83,985
Year 1 5.75 5.75/7.25 6.25 6.25
Year 2 6.75 6.75/8.25 7.25 6.25
Year 3 7.75 7.75/9.25 8.25 6.25
Year 4 8.75 8.75/10.25 9.25 6.25
Year 5 9.75 9.75/11.25 9.95 6.25
Year 6 9.75 9.75/12.25 9.95 6.25
30-year FRM Interest Only 3/1 Piggyback 3/1
ARM/HELOC
Worst Case
Option ARM
Rate Assumptions (%)
(Fully-Indexed Rates)
Monthly Payment
End of Year 5
TABLE 2.
MONTHLY MORTGAGE PAYMENT AND RATE - WORST CASE SCENARIO
Table 2, the “worst case” scenario, assumes that interest rates rise 1%
per year for the next four years2 and shows the payment shock and interest
rate shock that would result. Under this scenario:
n The IO loan experiences a payment shock of 61% in year four, when the
loan begins to amortize and the interest rate increases, and another 8%
in year five, before dropping back in year six when mortgage insurance
is cancelled.
n The piggyback sees payment shock of 48% over five years, beginning
in year two when the floating rate on the HELOC begins to adjust and
increasing in year four when the fixed period on the first loan expires.
n The option ARM sees the same gradually increasing minimum payments
through the first four years, but then sees a payment shock of
almost 170% in year five when amortizing payments meet higher interest
rates, as well as a substantially higher loan balance because of
increased negative amortization.
n Under this scenario, the 30-year FRM compares favorably on monthly
payments beginning in year four, when the payment drops due to the
cancellation of MI (and the payments on the other loans increase). And
again, a borrower will build equity faster with the 30-year FRM.
n Option ARM, piggyback, and IO borrowers may plan on refinancing
before the payment shock hits, but if the credit environment changes
and credit becomes less available, they may not be able to get the loan
they want.
Most experts don’t think it’s likely that interest rates will remain
unchanged for the next six years, as shown in Table 1. Neither do they
expect them to increase as dramatically as is shown in Table 2. What’s the
right choice? It depends on a borrower’s personal financial situation,
including their expectations for the future and their tolerance for risk. In
any case, it is important that consumers fully understand the potential benefits
and risks of the mortgage choices they consider, and choose the one
that is right for them and their family. u
0
500
1000
1500
2000
2500
3000
3500
4000
0 12 24 36 48 60 72 84 96 108
30YR FRM
Worst Scenario - I/O 3/1
Worst Scenario - HYB 3/1 + HELOC
Worst Scenario - Option ARM
0
30
60
90
120
150
180
0 12 24 36 48 60 72 84 96 108
30YR FRM
Worst Scenario - I/O 3/1
Worst Scenario - HYB 3/1 + HELOC
Worst Scenario - Option ARM
-60
-50
-40
-30
-20
-10
0
10
20
30
40
0 12 24 36 48 60 72 84 96 108
30YR FRM
Worst Scenario - I/O 3/1
Worst Scenario - HYB 3/1 + HELOC
Worst Scenario - Option ARM
MONTHLY PAYMENT
EQUITY BUILD-UP WITH PRICE APPRECIATION
BALANCE PAID
5
Months
Thousands
Months
Months
Thousands
2 The interest rate assumption for the option ARM is an increase of .7% in year five because the initial interest rate is higher.
MSA
San Diego-Carlsbad-San Marcos, CA 588 27.08% 10.81% -16.27%
Santa Ana-Anaheim-Irvine, CA 579 27.93% 14.55% -13.38%
Boston-Quincy, MA 573 13.68% 6.93% -6.76%
Nassau-Suffolk, NY 573 18.08% 11.90% -6.18%
Oakland-Fremont-Hayward, CA 558 18.58% 18.27% -0.32%
Sacramento-Arden-Arcade-Roseville, CA 554 24.04% 17.75% -6.29%
Riverside-San Bernardino-Ontario, CA 553 29.73% 18.05% -11.68%
Providence-New Bedford-Fall River, RI-MA 550 18.76% 10.35% -8.41%
Los Angeles-Long Beach-Glendale, CA 533 27.68% 17.23% -10.45%
San Jose-Sunnyvale-Santa Clara, CA 530 13.60% 16.91% 3.32%
San Francisco-San Mateo-Redwood City, CA 507 15.02% 14.70% -0.32%
Cambridge-Newton-Framingham, MA 497 11.35% 7.13% -4.22%
Edison, NJ 473 17.83% 12.73% -5.10%
New York-Wayne-White Plains, NY-NJ 447 17.84% 12.72% -5.12%
Las Vegas-Paradise, NV 418 35.95% 12.90% -23.04%
Fort Lauderdale-Pompano Beach-Deerfield Beach, FL 378 21.60% 23.55% 1.96%
Newark-Union, NJ-PA 365 15.97% 11.75% -4.22%
Washington-Arlington-Alexandria, DC-VA-MD-WV 345 22.12% 19.33% -2.79%
Detroit-Livonia-Dearborn, MI 324 3.68% 2.45% -1.23%
Miami-Miami Beach-Kendall, FL 303 20.33% 21.02% 0.69%
Minneapolis-St. Paul-Bloomington, MN-WI 260 10.82% 7.14% -3.68%
Tampa-St. Petersburg-Clearwater, FL 259 16.57% 20.01% 3.44%
Baltimore-Towson, MD 217 20.18% 17.44% -2.74%
Virginia Beach-Norfolk-Newport News, VA-NC 209 20.68% 20.04% -0.64%
Warren-Farmington Hills-Troy, MI 181 4.60% 3.28% -1.32%
New Orleans-Metairie-Kenner, LA 156 8.87% 7.55% -1.32%
Denver-Aurora, CO 155 4.04% 4.03% -0.02%
Chicago-Naperville-Joliet, IL 148 11.65% 8.66% -2.99%
Orlando, FL 137 14.97% 24.71% 9.75%
Phoenix-Mesa-Scottdale, AZ 118 13.64% 29.54% 15.90%
Atlanta-Sandy Springs-Marietta, GA 114 4.70% 5.21% 0.52%
Seattle-Bellevue-Everett, WA 103 10.61% 13.58% 2.97%
Portland-Vancouver-Beaverton, OR-WA 102 10.25% 16.12% 5.87%
Philadelphia, PA 98 16.86% 12.01% -4.84%
St. Louis, MO-IL 91 9.36% 6.88% -2.47%
Kansas City, MO-KS 89 6.06% 5.00% -1.06%
Austin-Round Rock, TX 85 1.90% 6.28% 4.38%
Milwaukee-Waukesha-West Allis, WI 82 12.09% 8.19% -3.90%
Charlotte-Gastonia-Concord, NC-SC 79 3.08% 4.42% 1.33%
Houston-Baytown-Sugar Land, TX 77 4.16% 4.45% 0.28%
Dallas-Plano-Irving, TX 77 2.42% 4.10% 1.67%
Fort Worth-Arlington, TX 69 2.78% 3.80% 1.02%
Cleveland-Elyria-Mentor, OH 67 4.20% 4.00% -0.20%
San Antonio, TX 64 6.12% 7.02% 0.90%
Columbus, OH 64 4.87% 4.68% -0.19%
Nashville-Davidson-Murfreesboro, TN 62 5.42% 7.01% 1.59%
Cincinnati-Middletown, OH-KY-IN 61 5.19% 4.73% -0.46%
Indianapolis, IN 58 3.12% 4.55% 1.43%
Memphis, TN-MS-AR 57 3.89% 5.46% 1.58%
Pittsburgh, PA 56 6.14% 5.23% -0.90%
HOME PRICES
Appreciation2
Acceleration3
2003Q3:2004Q3 2004Q3:2005Q3
RISK MEASURES
Risk Index1
METROPOLITAN AREA ECONOMIC
1.40% 4.30% 0.11% 73.88
1.64% 3.80% -0.06% 70.83
0.88% 4.59% 0.78% 83.08
0.87% 4.30% 0.45% 75.77
1.56% 5.00% 0.34% 72.30
1.57% 4.60% -0.12% 72.08
1.89% 5.33% -0.25% 68.99
0.78% 5.37% 0.66% 83.84
1.04% 5.07% -1.07% 70.44
-0.33% 5.40% 0.02% 76.91
1.10% 4.57% 0.33% 82.41
0.88% 3.96% 0.52% 91.52
1.04% 3.87% -0.30% 83.49
1.08% 5.27% -0.96% 82.56
7.05% 4.17% -0.83% 84.74
4.09% 3.67% -0.99% 68.15
-0.72% 4.40% -0.30% 91.35
2.91% 3.53% 0.16% 88.74
-1.30% 8.87% 2.91% 101.91
2.03% 4.67% -1.32% 73.55
1.28% 3.43% 0.11% 93.44
2.59% 3.77% -0.31% 81.73
1.15% 4.57% 0.25% 98.53
1.12% 4.20% 0.76% 98.39
-0.73% 6.03% 1.60% 107.49
-42.69% 9.30% 4.38% 118.45
1.70% 5.13% 1.11% 110.23
1.18% 6.20% 0.69% 101.59
4.62% 3.53% -0.50% 86.20
4.39% 4.33% 0.21% 83.32
1.04% 5.40% 1.64% 113.14
2.16% 4.67% -0.38% 101.99
2.23% 5.93% 0.04% 98.24
0.39% 4.93% 0.24% 106.27
0.64% 5.27% 0.89% 114.65
0.98% 5.33% 1.07% 117.68
2.01% 4.30% 0.28% 125.51
0.17% 4.80% 0.35% 114.23
2.97% 5.33% 0.96% 132.59
1.73% 5.47% 0.34% 131.03
1.15% 5.10% 0.36% 130.90
1.16% 4.93% 0.48% 135.72
-0.23% 5.63% 1.05% 127.31
1.67% 4.80% 0.30% 134.58
0.75% 5.07% 1.29% 131.59
1.45% 4.13% 0.55% 125.77
0.63% 5.20% 1.00% 132.74
0.35% 4.60% 1.34% 137.42
1.54% 6.00% 1.55% 137.89
0.11% 5.07% 0.17% 135.65
LABOR MARKETS
Employment Growth4 Unemployment Rate 2005Q3
2004M09:2005M09 Local5 Local De-meaned6
AFFORDABILITY
Index7
(1995Q1=100)
1. The Market Risk Index score translates to a percentage that predicts
the probability of a house price decline over the next two
years. For example, a Risk Index score of 100 means there is a
10% chance that house prices in that MSA will fall in two years.
2. Appreciation measures increases in home prices for the previous
and current year (based on quarterly OFHEO HPI). Research indicates
that house price growth is very persistent in the short run:
a year of low appreciation is likely followed by another year of low
appreciation. Consequently, low or negative appreciation in the
past year is a sign of impending trouble. The Risk Index score will
thus vary inversely with last year’s appreciation.
3. Using previous and current year appreciation, acceleration measures
the change in home price appreciation. For example, consider
a metropolitan area where the property value of a typical house
was $100,000 at the end of 2000, $110,000 in 2001, and
$111,100 in 2002. Home price appreciation for this area is 10% for
the year 2001 and 1% for the year 2002. Because the appreciation
rate dropped by 9% points from the year 2000 to the year
2001, home price acceleration is minus 9% points at the end of
2002. The model interprets negative home price acceleration
(slowing growth) as a warning sign that home prices may be
close to their peak and likely to fall soon. Accordingly, the Risk
Index score increases as home price acceleration declines, other
things equal.
4. The employment growth rate is calculated with Bureau of Labor
Statistics total non-agricultural employment monthly observations,
from the indicated months (12-month growth rate). Lower
employment growth is a sign of weakness in the local economy;
therefore, the Risk Index score increases as employment growth
falls.
5. The local unemployment rate is calculated with Bureau of Labor
Statistics MSA-wide quarterly averages, not seasonally adjusted.
6. The de-meaned unemployment rate indicates the current
unemployment rate compared to its past rate. For example, a demeaned
unemployment rate of 1% for the calendar year 2005
means that the current unemployment rate is 1% higher than the
five-year average from 1999 to 2003. The higher the de-meaned
unemployment rate, the higher the Risk Index score.
7. Using median household income, home price appreciation, and
the cost of the 30-year fixed rate mortgage (FRM), PMI’s
Affordability Index (AI) measures the change in home purchasing
power over time according to how affordable homes are today
compared to 1995. An AI score above 100 means homes are
more affordable; a score below 100 means they are less affordable.
For example, an AI score of 110 means that if your monthly
mortgage payment took 30% of your monthly income in 1995,
today it takes only 27% (a change of 10% based on the original
ratio of 30%). Conversely, an AI score of 90 means that the share
of your monthly income taken by your monthly mortgage has
increased to 33%. The higher the AI, the less vulnerable a
housing market is to local economic shock (and hence the lower
is the Risk Index score). The AI score is calculated as
AIt º (It/QIt )/(I95/QI95) where subscript t denotes the current
quarter, It measures household income, and QIt represents qualifying
income index defined as
where r denotes the 30-year FRM, 0.80 is LTV, and 4*12*[.] represents
index of the annual mortgage payment under a 25%
mortgage payment-to-income threshold.
QIt º HPI*0.80*4*12* r
12
(1 + r )
360
12
(1 + r )
360
- 1
12
INDICATORS As of January 2006
8
The PMI U.S. Market Risk Index is based on home price
appreciation and acceleration, job growth and unemployment,
and affordability. From these statistics, the model
generates a risk score that predicts the likelihood of a
price decline within two years’ time.
Employment growth generally acts as a positive factor in
the model that produces the PMI Risk Index. In other
words, other factors being equal, when job growth in an
area is strong, an area’s risk of price decline is lower.
But what happens when an area’s job growth is due to a
single industry, or heavily concentrated in a small number
of industries? Given recent attention to the connection
between the nation’s generally healthy economy and the
recent real estate boom—for example, Lehman Brothers
estimates that one-third of the past year’s U.S. economic
growth was a consequence of the housing boom—we
thought we’d take a look at the question through another lens.
The graph below compares how employment in various
MSAs has been affected by the real estate boom. We’ve
done this by taking the categories of construction and real
estate from Bureau of Labor Statistics job growth data
and calculating the percentage of jobs these categories
accounted for compared to the national average five years
ago, and then the percentage of growth in these categories
from 2000 to 2005 compared to the national average.
The upper right quadrant of the graph contains the areas
that were above the national average in 2000 and grew
more than the national average from 2000 to 2005.
Within this quadrant Las Vegas, NV, and Riverside,
Sacramento, San Diego, Santa Ana, and Oakland, all in
CA, stand out as areas that have relatively high Risk Index
Scores, as well as employment bases that are more
closely linked to the housing and real estate market than
the national average. Phoenix, AZ, Fort Lauderdale and
Orlando, FL, Virginia Beach, VA, and Washington, D.C. are
notable because while their Risk Index scores are currently
moderate, their economic health is closely linked to
the housing and real estate sector because of the nature
of their employment base.
MSAs depicted on the right side of the graph, and particularly
in the upper right quadrant, may be subject to
greater risk due to the correlation between these job categories
and the risks captured in the risk index. A slowdown
in home price appreciation or a drop in prices could
be compounded by job losses in the local real estate and
construction sectors thereby driving or exacerbating a
downturn. We believe this is a factor to keep in mind
when considering geographic house price risk. u
Concentration of Real Estate-Related Jobs May Add Risk
Kansas City, MO, St. Louis, MO, and Memphis, TN are not included in the chart because employment data on real estate services is not available.
9
The above U.S map marks in color the geographic distribution
of house-price risk for all 50 U.S. states and the District of
Columbia. The color codes rank order the 10 riskiest states in red
(11 including the District), followed by the next 10 riskiest states
in tan, white, light blue, and the 10 least risky states in aqua. As
in the previous quarter, California and the Northeastern states
top our list. The Pacific Division posted the fastest gain in risk by
60 points bringing it within 1 point of New England, followed by
New England with a 51-point increase. The East South Central
and West South Central divisions posted slight increases. (This
presentation is based on the data for all 379 MSAs available in
the appendix at:
http://www.pmigroup.com/newsroom/publications.html)
TABLE 1: CENSUS REGION RISK INDEX
Division Risk Index
New England 437
Pacific 436
Middle Atlantic 289
South Atlantic 189
Mountain 136
West North Central 121
East North Central 121
West South Central 72
East South Central 63
OR
WA MT
WY
ID
NV
AZ
CO
UT
ND MN
SD
NE IA
MO KS
TX
LA
AR
HI
AK
AL
TN
KY
MS
WI
IL IN
MI
NY
NJ
GA
FL
NC
SC
WV
VA
RI
ME VT
NH
MA
PA
WEST MIDWEST NORTHEAST
NM
OK
CT
Pacific Mountain West North Central East North Central Middle Atlantic New England
West South Central East South Central South Atlantic
DE
MD
DC
OH
Top 10 11-20 21-30 31-40 Bottom 10
CA
SOUTH
Geographic Distribution of
HOUSE PRICE RISK
reversion toward the long-term average. This phenomenon,
however, is not consistent across the nation as Florida housing
markets continue to heat up, and Phoenix’s home prices
are growing at 30% with an acceleration rate of 16%. In addition,
housing markets in the Pacific Northwest and Texas continue
to gain strength.
The top 10 riskiest MSAs remain unchanged, but some have
shifted in position. The Risk Index values in these MSAs have
all increased between 22 (Boston, MA) and 98 (Sacramento,
CA) points. San Diego now leads the nation in house-price risk
followed by Santa Ana, CA and Boston, which had previously
been ranked No. 1. While underlying economic drivers
remained strong and price appreciation remained in the double
digits in most of the top-ranked MSAs, the speed of appreciation
has slowed significantly. All Southern California MSAs
have followed similar growth patterns as appreciation rates
have dropped from a high of 30% for the year ending in Q3’04
to 19-23% in the year ending in Q2’05 and to 10-15% in the
year ending in Q3’05. Because prices are still appreciating
much faster than incomes, affordability has continued to
worsen. Several quarters of strong appreciation have put
Riverside, CA’s affordability index below 70, a significant drop
from 92 six quarters ago. Affordability in other Southern
California MSAs is only slightly better.
Las Vegas was the top performer in price appreciation from
Q2’04 to Q1’05 only to be replaced by Phoenix, AZ starting in
Q2’05. These MSAs, however, show a sharp contrast in
house price growth as well as movement in house price risk
this quarter. While Las Vegas had the highest price deceleration
in the nation at –23%, Phoenix had the highest price
acceleration at 16%. Deceleration in Las Vegas has increased
the area’s risk score from 197 to 418, and its ranking from No.
22 to No.15. Phoenix’s risk score, in contrast, has increased
only slightly from 93 to 118, and its ranking has moved up by
just one spot to No. 30.
Although strong housing and labor markets have kept house
price risk relatively low in Phoenix, the market is becoming
increasingly less affordable, indicated by the Affordability
Index which, at 83, is equivalent to those of Boston and
Providence, RI, both of which are ranked in the top 10 on the
Risk Index. Phoenix’s appreciation in the year ending in Q3’05
nearly matches the extraordinary appreciation rate observed
last year in Las Vegas. It is uncertain to what extent home
prices in Phoenix may follow those in Las Vegas, which have
begun decelerating, but it is clear that the current rate of
appreciation is not sustainable. We expect Phoenix’s risk
score to increase unless income rises rapidly. Without that,
continued appreciation will drive affordability down, thereby
increasing risk. Slowing appreciation without income growth
supporting affordability will also increase the area’s risk score.
Another regional concentration of MSAs with low affordability
is located in Florida, headed by Fort Lauderdale, FL, whose
affordability index dropped below 70 this quarter. Fort
Lauderdale has enjoyed several quarters of strong home price
growth and a booming economy, but affordability is low, and
the 20% appreciation experienced in the year ending in Q3’05
has increased the area’s risk of price declines. Risk Index
scores in Southern Florida’s MSAs increased in Q3’05 (288 to
378 in Fort Lauderdale, 206 to 303 in Miami), but their relative
rankings remain at No. 16 and No. 20, respectively. Risk Index
scores also increased in Tampa and Orlando (by 58 and 26,
respectively), but their rankings declined slightly. Although
Florida’s housing markets remain robust, with the highest
house price gains after Phoenix, AZ, the area may experience
increasing price pressure in the future. The areas have relatively
higher concentrations of condos and investment properties
compared to the rest of the United States, and these
properties are generally subject to greater price fluctuations.
In addition, the areas’ strong economies are partially supported
by high employment growth in construction and real estate
10
Local Economic Patterns (continued from page 3)
(continued on page 11)
11
service industries (see sidebar on Job Growth Due to Real
Estate on page 8).
Price growth in the Northeast and New York regions never
reached the levels enjoyed in Southern California, Las Vegas,
and Florida, but prices still enjoyed 10-18% annual growth
beginning in 2000. These continuous gains in property values
outpaced income growth and resulted in divergence from the
natural growth trend line, which has decreased affordability.
Recent quarters have seen a slight decline in price appreciation.
While Boston has relinquished the No. 1 position on the
Risk Index to San Diego, Boston’s Risk Index value has
increased again from 551 to 573. Price appreciation has
dropped to 6.8 percent, much closer to the long-term average.
The last time Boston experienced this small a change in
appreciation was mid-1998. House price appreciation in New
York and New Jersey MSAs has also decelerated to 11-12%,
which has increased these areas’ Risk Index scores. Of the
Northeastern MSAs, Newark, NJ saw the largest increase in
its Risk Index score, up 133 points from 232 to 365. New
York’s score has risen by 115 points to 447, while Edison, NJ
has seen its score rise by 111 points to 473.
Texas housing markets continue to appear healthy and are
rebounding from the slow price growth they experienced earlier
this decade. House prices in most Texas MSAs had grown
below the 25-year national average since the middle of 2001,
which led to improved affordability. The growing economy in
Austin, TX experienced price growth of 6.3% from Q3’04 to
Q3’05, up from 1.9% the previous year; its Risk Index score
has thus dropped from 91 to 85. Dallas also saw a decrease in
its Risk Index score, from 81 to 77.
Rankings of Detroit, MI, and Warren, MI, have declined from 15
to 19 and 23 to 25, respectively, but Risk Index values
changed very little for Detroit and increased slightly for
Warren. Both MSAs continue to lose jobs, with more possible
job cuts on the horizon due to the struggling auto industry.
While affordability is relatively high and keeps these areas’
Risk Index scores relatively lower than some of the coastal
MSAs, these two areas saw the lowest house price appreciation
rates among the 50 largest housing markets, growing
2.5% and 3.3% over the last 12 months.
Comment on New Orleans Market:
This is the first issue of the Economic & Real Estate Trends
(ERET) report that measures the impact of Hurricane Katrina
on the affected areas in terms of house price risk. Because of
a 43% year-to-year drop in employment growth and a sharp
increase in its unemployment rate, the Risk Index score for
New Orleans has climbed from 67 to 156 and the ranking from
No. 42 to No. 26. Because the drastic changes in labor statistics
are attributed to economic shock due to the natural disaster,
house price risk may be heightened for this quarter. With
severe damage to the region’s infrastructure and permanent
job loss, employment growth may stay weak for the next several
months, but good housing affordability and job creation
anticipated with the rebuilding of the city will favor the area’s
long-term prospects. A temporary housing shortage may create
a short-term price bidding war in the area and nearby
MSAs, which may lead to price fluctuation over the next few
years. The effect of the hurricane outside of the affected
areas is less evident, but surrounding areas may see growth
in housing markets and employment due to relocation of businesses
and households. If they occur, these impacts will likely
occur more slowly and to a lesser extent than in the areas
directly affected.u
Local Economic Patterns (continued from page 10)
800.966.4PMI (4764)
www.pmigroup.com
PMI 205 (01/06)
Please contact your PMI representative
for more information or printed versions.
The ERET report will be produced quarterly.
You may acquire a pdf version online:
http://www.pmigroup.com/newsroom/publications.html
METROPOLITAN AREA ECONOMIC
INDICATORS STATISTICAL MODEL OVERVIEW
The Market Risk Index is based on the results of applying
a statistical model to data on local economic conditions,
income, and interest rates, as well as judgmental
adjustments in order to reflect information that goes
beyond the Risk Index’s quantitative scope. For each
Metropolitan Statistical Area (MSA) or Metropolitan
Statistical Area Division (MSAD), the statistical model
estimates the probability that an index of metropolitanarea-
wide home prices will decline over the next two
years (eight quarters), with an index value of 100 implying
a 10% probability of falling house prices.
The Risk Index uses information on past house price growth
and variables measuring local employment and
unemployment, as well as local income measures and
interest rates. The Risk Index is determined by the following
variables: (i) Home Price Appreciation, (ii) Home Price
Acceleration, (iii) Employment Growth, (iv) the De-meaned
Unemployment Rate, which we define as the difference of
the local Unemployment Rate from its average in recent
years, and (v) PMI’s proprietary Affordability Index.
Home prices are measured with a Repeat Sales Index
provided by the Office of Federal Housing Enterprise
Oversight (OFHEO). This method follows homes that are
sold repeatedly over the observation period and uses the
change in the purchase prices to construct a price index.
The index is based on data from Fannie Mae and Freddie
Mac and covers only homes financed with loans securitized
by these two companies. Consequently, this index does not
apply to high-end properties requiring jumbo loans.
Periodically, we may re-estimate our model to update the
statistical parameters with the latest available data. We
also may make adjustments from time to time to account
for general macroeconomic developments that are not
captured by our model.
Cautionary Statement: Statements in this document that are not historical facts or that relate to future plans, events or performance are ‘forward-looking’ statements within the
meaning of the Private Securities Litigation Reform Act of 1995. These forward-looking statements include, but are not limited to, PMI’s U.S. Market Risk Index and any related discussion,
and statements relating to the possible soft landing of the U.S. housing market as well as future economic and housing market conditions. Forward-looking statements are subject to a
number of risks and uncertainties including but not limited to, the following factors: changes in economic conditions, economic recession or slowdowns, adverse changes in consumer
confidence, declining housing values, higher unemployment, deteriorating borrower credit, changes in interest rates, the effects of Hurricanes Katrina and Rita or other natural disasters,
or a combination of these factors. Readers are cautioned that any statements with respect to future economic and housing market conditions are based upon current economic conditions
and, therefore, are inherently uncertain and highly subject to the changes in the factors enumerated above. Other risk and uncertainties are discussed in the Company’s filings with the
Securities and Exchange Commission, including our report on Form 10-K for the year ended December 31, 2004 and our report on Form 10-Q for the quarter ended September 30, 2005.
© PMI Mortgage Insurance Co. 2006