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FRBSF ECONOMIC LeTTer
2010-22

July 19, 2010

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Mortgage Prepayments and Changing Underwriting Standards
William Hedberg and John Krainer
Despite historically low mortgage interest rates, borrower prepayments have been lower than expected over the past
year. For example, a model based on prepayment data from 2000 through the beginning of 2009 predicts a prepayment
rate for the first quarter of 2010 roughly twice as high as the observed rate. It can be conjectured that current low
prepayment rates reflect the influence of factors specific to the housing bust, including a significant tightening of lending
terms for certain borrowers, weak housing demand, and high foreclosure rates.

All mortgage borrowers have the option of prepaying their loans, possibly with a penalty, even if they do
not intend to sell their homes. In almost all cases in which a home is not sold, prepayment is associated
with refinancing the underlying mortgage. Borrowers might have a number of motives for refinancing.
Most obviously, mortgage interest rates may have declined enough to make refinancing worthwhile. In
such cases, the borrower can lower the discounted present value of the payment liability by switching
into a lower rate.
However, the refinancing decision is not quite as straightforward as simply comparing the present value
of the remaining mortgage balance under the existing rate with that of a new mortgage under the
current market rate, net of transaction costs. Like any financial option, timing is important. If you
refinance today, the decision may preclude you from refinancing at a later date when rates might be
even lower. Thus, some measure of mortgage interest rate volatility is also necessary for calculating the
advantage of refinancing (see Agarwal, Driscoll, and Laibson 2008 for a mortgage calculator that factors
in these considerations).
In general, mortgage borrowers are sensitive to interest rate changes. If we look at prepayments over
time, as measured by the Mortgage Bankers Association’s refinancing index, we see a negative
relationship between the overall level of interest rates and the level of refinancing activity (see Figure
1).
Despite this basic relationship in the
aggregate data, the mortgage finance
literature is replete with empirical

Figure 1

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Federal Reserve Bank San Francisco | Mortgage Prepayments and Changing Underwriting Standards |

evidence documenting how individual
mortgage borrowers often don’t follow
optimal prepayment strategies. Many
borrowers don’t prepay and refinance
when it is advantageous to do so (see
Green and LaCour-Little 1999). Similarly,
there is also evidence that some
borrowers prepay even when it would not
seem to be optimal. This has led
observers to consider a wider array of
prepayment motives than simply reducing
the interest rate on the remaining
principal balance. It is possible that some
borrowers prepay their mortgages not just
to refinance and lower their rate, but also
to extract equity. This behavior may be
more closely related to liquidity needs,
such as financing college for their children,
than to the level of interest rates.

Mortgage interest rate and refinance index

Source: FAME database.

Additionally, house price appreciation adds to borrower wealth and can have the effect of reducing a
borrower’s loan-to-value ratio. If borrowers are comfortable with a certain level of leverage, then
changes in house prices may prompt them to prepay even though there is little incentive to do so from
the narrower perspective of interest costs. Likewise, house price declines effectively raise loan-to-value
ratios and thus tend to depress refinancing because borrowers may no longer have enough equity to
qualify for the same kind of loan they previously took out.
Of course, one of the main reasons for prepaying a mortgage is the sale of the home, which is not
related to refinancing. Job changes may force borrowers to move. Young households may trade up to
more expensive homes. Older households may downsize. Household members may experience job loss,
divorce, or other life events that induce them to sell their homes. All of these motives might lead to
mortgage prepayment for reasons that have nothing to do with interest rates or house prices alone (see
Green and Shoven 1986 for a discussion of how individual borrower characteristics are important for
explaining prepayments).
Using data to explain the recent mortgage prepayment behavior
Despite the complex set of factors that govern mortgage prepayment decisions, the broad swings in
prepayment behavior can be captured reasonably well using a simple statistical model that takes into
account the factors noted above. Formally, we use here what is known as a competing risks survival
model. The survival risks are “competing” in the sense that mortgages can terminate in two different
ways: borrowers can prepay, or they can go into default or foreclosure. We use loan-level data from LPS
Applied Analytics, specifically a random sample of 75,784 first-lien owner-occupied mortgages with
closing dates from January 2000 to March 2010. We identify prepayments as events in which mortgage
balances are paid off in full without foreclosure taking place. Because of possible differences between
borrowers who take out adjustable-rate mortgages and fixed-rate mortgages, we ran the two groups
through our model separately. In addition to current loan-to-value ratios and the difference between
existing mortgage interest rates and market rates, we also include a measure of interest rate volatility
(a term premium) as well as control variables for mortgage characteristics such as jumbo, subprime,
and low-documentation loans. Additionally, we control for the types of investors that own the loan, in
the event that mortgages sold to private investors differ in hard-to-measure ways from mortgages
owned or guaranteed by Fannie Mae or Freddie Mac. Finally, we include the unemployment rate for the

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Federal Reserve Bank San Francisco | Mortgage Prepayments and Changing Underwriting Standards |

metropolitan statistical area in which a home is located.
As expected, the most important variables in predicting prepayment rates relate to the costs of
mortgages. In our sample, we find subprime mortgage borrowers are much less likely to prepay than
prime mortgage borrowers. In addition, jumbo mortgage borrowers are less likely to prepay than
conforming mortgage borrowers. We also find mortgages held by private investors are less likely to be
prepaid than mortgages held by Fannie Mae or Freddie Mac.
In Figure 2, actual fixed-rate mortgage
prepayment rates are plotted side-by-side
with rates predicted by our model starting
in the third quarter of 2000. Thus, for
example, in the first quarter of 2002,
approximately 6.5% of all fixed-rate
mortgages in our sample were predicted
to prepay. This calculation is done by
computing the prepayment probability for
each mortgage in the sample and then
averaging these probabilities to get an
expected prepayment rate. The thin blue
line in Figure 2 is the actual prepayment
rate, which was a little below 5.75% for
the first quarter of 2002.

Figure 2
Fixed-rate mortgage prepayment rates

Overall, the model appears to capture the
basic patterns in the data. Specifically,
predicted prepayment rates track actual
Source: LPS Analytics and authors’ calculations.
prepayment rates in 2003 when mortgage
interest rates fell. The model doesn’t
capture the full magnitude of the high prepayments in 2003–2004, either because borrowers were even
more sensitive to rate declines during those years than this simple model indicates or because
borrowers were in part basing their prepayment decisions on liquidity needs, which are difficult to
measure. This period coincides with a housing market boom and the high prepayment rates may also
reflect the strong housing demand at that time as households traded up.
The vertical line toward the right margin of Figure 2 marks the end of the sample period used for
estimating the model. To the right of the vertical line, we fix the model parameters and feed in actual
interest rates, house prices, and unemployment rates for the mortgages that were still current at the
end of the estimation period and beyond. Technically, the predicted prepayment rates between the
second quarter of 2009 and the first quarter of 2010 are not forecasts because the variables used to
construct the predictions for this period are known. But the model does not incorporate data on
prepayment rates and other variables over the past year.
We chose to estimate the model based on previous-period data because of the possibility that mortgage
markets have undergone a regime shift. Indeed, since the summer of 2008, Fannie Mae and Freddie
Mac both went into conservatorship, the nonagency securitization market effectively shut down, and
bank lending standards tightened amid financial crisis. So the predicted prepayment rates for the
current period are predicated on the kind of prepayment experience we might have expected if rates
and house prices followed their actual paths and the seismic changes in the mortgage market had not
occurred.
The notable thing about the model’s out-of-sample prediction is that it diverges from the actual
prepayment rate. Given the current values of the variables that go into the prepayment model, we

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Federal Reserve Bank San Francisco | Mortgage Prepayments and Changing Underwriting Standards |

would expect the prepayment rate for the fixed-rate mortgages in our sample to be 5.26% in the first
quarter of 2010. In fact, the prepayment rate was closer to 2.5% in that period for both fixed and
adjustable-rate mortgages, which are not shown in Figure 2. Given the number of mortgages
outstanding in the first quarter of 2010, this translates into about 1.2 million mortgages not prepaid that
the model predicts would have been prepaid. Evidently, the usual rise in prepayments that accompanies
a prolonged period of low interest rates was offset by some other factor or combination of factors.
House price declines are not likely to be
the culprit because these changes are
Figure 3
accounted for in the model. Since the
Difference in prepayment rate by state
overall model fit is fairly good, something
outside the model is apparently holding
down prepayment rates. This deviation is
also consistent with a relative tightening
of conditions in the mortgage market.
Indeed, our measure of the value of the
prepayment option is largely driven by
how far a benchmark interest rate has
fallen relative to borrowers’ current
interest rates. It may be that these
existing rates were abnormally cheap
relative to the benchmark rate at the time
of origination. It could also be that more
borrowers were able to get low rates that
are no longer available to as many
Note: Actual refinance rate minus model’s prediction.
borrowers in our sample because of
tighter lending standards. Another
possibility is that the low prepayment
rates are related to the current high mortgage default rates. With housing market conditions so weak,
as borrowers fall behind on their mortgages, they may be finding it difficult to sell their homes and avoid
default. Indeed, we can use this same basic model to predict the mortgage default rate over this same
time period. This exercise would indicate that actual default or foreclosure rates are currently higher
than predicted by the model.
Figure 3 shows the difference by state of our model’s predicted prepayment rate minus the actual
prepayment rate. Our model predicted 3­
to 8% more prepayments in California than there actually
were from the second quarter of 2009 through the first quarter of 2010. Unsurprisingly, California,
Nevada, and Arizona, three states with very high mortgage default rates, had significantly fewer
prepayments than our model predicts.
Conclusion
Mortgage interest rates are currently at historically low levels. Despite attractive rates, we have not seen
the level of mortgage prepayment that would normally be expected. This seems to reflect the presence
of a number of unusual factors that a standard mortgage prepayment model cannot capture. These
missing factors may include a possible tightening of mortgage terms for borrowers who previously
enjoyed much easier access to credit, and weak housing demand that is suppressing the trade-up
market and preventing distressed borrowers from selling their houses and avoiding foreclosure.
William Hedberg is a research associate at the Federal Reserve Bank of San Francisco.
John Krainer is senior economist at the Federal Reserve Bank of San Francisco.

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Federal Reserve Bank San Francisco | Mortgage Prepayments and Changing Underwriting Standards |

References
Agarwal, Sumit, John Driscoll, and David Laibson. 2008. “Optimal Mortgage Refinancing: A Closed Form
Solution.”
Harvard University and NBER working paper.
Green, Jerry, and John Shoven. 1986. “The Effects of Interest Rates on Mortgage Prepayments.”
Journal of Money, Credit, and Banking 18(1), 41–59.
Green, Richard, and Michael LaCour-Little. 1999. “Some Truths about Ostriches: Who Doesn’t Prepay
Their Mortgages and Why They Don’t.”
Journal of Housing Economics 8(3), pp. 233–248.
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