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Deficiency Judgements and Borrower Maintenance

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					               Deficiency Judgments and Borrower Maintenance:
                             Theory and Evidence



                         John Harding,* Thomas J. Miceli,** and C.F. Sirmans*




                   Journal of Housing Economics, 9(4), December 2000, 267-286




                                                       Abstract

It is well known when property rights to an asset are divided, individual rightholders may have adequate incentives
to invest in proper maintenance. In this paper, we examine how mortgage laws affect the nature of the lender’s
claim to the house, and how that claim in turn affects the incentives of borrowers to invest in home maintenance.
The specific law that we examine concerns the right of lenders to pursue a borrower’s non-housing wealth in the
event of default if the value of the house is less than the mortgage balance. Most states allow lenders to collect such
“deficiency judgments,” while others either prohibit, or make it difficult to obtain them. The theoretical model
developed in this paper predicts that borrowers will maintain at a higher rate when lenders are allowed to seek
deficiency judgments. Intuitively, when borrowers’ non-housing wealth is at risk, whey have an incentive to invest
more in maintenance in order to reduce the likelihood that the value of the property will fall below the mortgage
balance. We attempt to measure this effect using data on household maintenance obtained from the American
Housing Survey along with information on differences in mortgage laws across states. We estimate a three equation
simultaneous system relating maintenance expenditures, house value, and mortgage rates. The results provide
confirmation that variation in mortgage laws affect homeowner maintenance in the manner predicted by the theory.

                                                   January 2000

                              *Department of Finance and Real Estate Center
                                   School of Business Administration
                                       University of Connecticut
                                           Storrs, CT 06269


                                         **Department of Economics
                                          University of Connecticut
                                             Storrs, CT 06269
                                                                                                     1


          Deficiency Judgments and Borrower Maintenance: Theory and Evidence



                                          I. Introduction

       It is well known that when property rights to an asset are divided, individual rightholders

may have inadequate incentives to invest in proper maintenance. This is true when ownership is

divided at a point in time (as with joint ownership), or over time (as in a leasing arrangement). It

is also true when the asset is used as collateral for a loan--as when a homebuyer purchases a

house with a mortgage--for in that case, the lender has a claim on the asset in the event of

default. In this paper, we examine how mortgage laws affect the nature of the lender’s claim to

the house, and how that claim in turn affects the incentives of borrowers to invest in home

maintenance.

       The specific law that we examine concerns the right of lenders to pursue a borrower’s

non-housing wealth in the event of default if the value of the house is less than the mortgage

balance. Most states allow lenders to collect such “deficiency judgments,” while others either

prohibit, or make it difficult to obtain them. The theoretical model developed in this paper

predicts that borrowers will maintain at a higher rate when lenders are allowed to seek deficiency

judgments. Intuitively, when borrowers’ non-housing wealth is at risk, they have an incentive to

invest more in maintenance in order to reduce the likelihood that the value of the property will

fall below the mortgage balance.

       It should be noted that the reduced incentive to invest when deficiency judgments are

prohibited is partially offset by the law of waste, which allows lenders to seek compensation for

abuse of the mortgaged property. However, courts traditionally have been unwilling to uphold a

claim of waste for mere failure to maintain (what Stein (1998: p. 1211) calls “passive waste”),

and further, courts tend to be skeptical of lenders’ efforts to use the law of waste to circumvent
                                                                                                                2


anti-deficiency judgment statutes (Burke, 1989: pp. 394-395).1 Ultimately, therefore, we expect

the availability of deficiency judgments to have the predicted positive effect on maintenance.

        We attempt to measure this effect using data on household maintenance obtained from

the American Housing Survey along with information on differences in mortgage laws across

states. We estimate a three equation simultaneous system relating maintenance expenditures,

house value, and mortgage rates. The results provide confirmation that variation in mortgage

laws affect homeowner maintenance in the manner predicted by the theory.

        The remainder of the paper is organized as follows. Section II sets up the model and

derives the first-best level of maintenance, which serves as a benchmark. Section III then

examines the impact of mortgage laws by comparing the maintenance level of borrowers when

deficiency judgments are allowed and when they are prohibited. Section IV provides an

empirical test of the predictions of the model. Finally, Section V offers concluding remarks.

                              II. The Model and First-Best Maintenance

        As a benchmark, we begin by deriving the optimal maintenance level of an owner-

occupier who does not have a mortgage. Since there is no risk of default, the owner will

internalize the full costs and benefits of his maintenance. Thus, the resulting level of

maintenance is first-best.

        We consider a risk-neutral homeowner who maximizes a two-period utility function of

the form2

         EU = x + v(h(m)) + δE ( w) ,                                                           (1)



1
  See Stein (1998) for a discussion of those situations in which lenders have been allowed by courts to recover
against a borrower’s assets under the law of waste, despite anti-deficiency judgment provisions in the loan. His
analysis, however, is primarily in the context of commercial loans.
2
  See, for example, Henderson and Ioannides (1983). Since our focus is on the maintenance decisions of borrowers,
we ignore risk-sharing aspects of the mortgage contract.
                                                                                                   3


where x is non-housing consumption in period one, v(h(m)) is the value of housing services as a

function of housing quality (v′>0, v″<0), w is second period wealth, and δ is the discount rate.

Housing quality depends on maintenance expenditures, m, (h′>0, h″<0), which we view as a

one-time investment, made in period one.

       The first period budget constraint is given by y1 = x + m +P0, where y1 is first period

income (wealth), and P0 is the purchase price of the house (a sunk cost). Second period wealth is

defined to be w=y2+Ph(m), where y2 is second period income (non-housing wealth), and P is the

second period market value of a unit of housing. We assume that y2 is known but that P is a

random variable from the perspective of period one, which accounts for the expectations operator

in (1). Note that period one maintenance expenditures affect both the value of housing for

consumption in period one, and the market value of housing as a store of wealth in period two.

       Substituting the budget constraint and definition of wealth into (1) yields

        EU = y1 − m − P0 + v(h(m)) + δE[ y 2 + Ph(m)] .                              (2)

The owner’s problem is to choose maintenance to maximize (2). The resulting first-order

condition for optimal maintenance, m*, is

       [v ′ + δE ( P )]h ′ = 1 .                                                     (3)

This condition says that the homeowner should equate the marginal benefit of maintenance—

consisting of the marginal consumption benefit plus the marginal benefit on housing wealth—to

the marginal cost ($1). Equation (3) will serve as the benchmark for the analysis of borrower

incentives under different mortgage laws.
                                                                                                    4


                     III. The Impact of Mortgage Laws on Borrower Maintenance

           Suppose now that the homeowner/borrower purchases the house at the beginning of

period one with a mortgage in the amount L3 and must repay L(1+r) in period two, where r is the

mortgage interest rate. We assume that y2<L(1+r) so that the borrower must sell (or refinance)

the house in order to pay off the mortgage. Depending on the realized value of P, three

outcomes are possible: (1) Ph(m)≥L(1+r): the proceeds from the sale are sufficient to cover the

mortgage; (2) y2+Ph(m)≥L(1+r)>Ph(m): the proceeds from the sale are insufficient to cover the

mortgage, but the proceeds plus the borrower’s non-housing wealth are sufficient; and (3)

y2+Ph(m)<L(1+r): the proceeds from the sale plus the borrower’s non-housing wealth are

insufficient to cover the mortgage.

           Our interest is in what happens in cases two and three. Specifically, does the lender have

the right to seek a deficiency judgment against the borrower’s non-housing wealth in the event

that the sale price fails to cover the mortgage balance? So-called recourse mortgages permit

deficiency judgments, whereas non-recourse mortgages do not (Gibson, Karp, and Klayman,

1992: Ch. 18). In the next two sections we examine the period-one maintenance incentives of

borrowers under both types of mortgages.

                                       A. Deficiency Judgments Allowed

           Forty-two states in the U.S. allow deficiency judgments, meaning that lenders can seek

to cover any deficit at foreclosure out of the borrower’s non-housing wealth, y2 (State Legislative

Topics, 1992). Thus, when Ph(m)<L(1+r), borrowers are liable up to the full amount of their

period two resources of y2+Ph(m). As a result, their period two wealth is

max[ y 2 + Ph(m) − L(1 + r ),0] , while lenders receive revenue of max[ L(1 + r ), y 2 + Ph(m)] .


3
    We assume for simplicity that the homeowner finances 100% of the purchase price.
                                                                                                                  5


Figure 1 graphs borrower wealth (bold solid line) and lender revenue (bold dashed line) as

functions of the sale price, Ph(m) (given m). Note that the horizontal segment of the borrower’s

wealth at zero reflects the fact that the latter’s liability is limited to his second period wealth

(including non-housing wealth) in the event of a deficit. This is the key with respect to borrower

maintenance incentives.

           The borrower’s expected utility when deficiency judgments are allowed is given by

                                              ∞
            EU D = y1 − m + v (h( m)) + δ ò [ y 2 + Ph( m) − L(1 + r )]dF ( P ) ,                   (4)
                                              A



where F(P) is the distribution function of P, and A ≡ [ L(1 + r ) − y 2 ] / h(m) . The integral term

represents expected wealth in period two, where the lower bound of A>0 reflects the limited

liability of borrowers in the event of a deficit.4 Note, however, that the right of lenders to seek

deficiency judgments against y2 in effect reduces this lower bound (i.e., ∂A/∂y2<0). This turns

out to have an important effect on borrower incentives.

           Optimal first period maintenance is found by differentiating (4) with respect to m to

obtain

                   ∞
           [v ′ + δ ò PdF ( P)]h ′ = 1 .                                                            (5)
                   A


Let mD denote the solution to this condition. Comparing (5) and (3) shows that mD<m*, given

A>0.5 Further, maintenance is decreasing the greater is the range of limited liability. The reason

is that the borrower fully internalizes the marginal benefit of maintenance over the range where

P>A because his wealth is increasing dollar-for-dollar in the value of the house over this range.

In contrast, his wealth is zero, and hence independent of m, over the range where P<A. Thus, it is


4
    Thus, the kink in the borrower’s wealth in Figure 1 corresponds to A. That is, at the kink Ph(m)=L(1+r)-y2.
5
    Note, in particular, that if A=0, (5) reduces to (3).
                                                                                                                 6


the borrower’s limited liability in the default state that leads to undermaintenance. And, as noted

above, the fact that the lender has recourse to the borrower’s non-housing assets reduces the

range of limited liability and hence results in a higher level of maintenance.

                                    B. Deficiency Judgments Not Allowed

        Eight states prohibit, or at least make it difficult for lenders to seek, deficiency judgments

against borrowers in the event of a deficit at foreclosure.6 The lender’s recovery is therefore

limited to Ph(m) even when this amount falls short of L(1+r). (We assume for now that lenders

charge the same rate of interest regardless of whether or not they can seek deficiency judgments.)

As a result, the borrower’s period two wealth is y2+ max[ Ph(m) − L(1 + r ),0] , and the lender’s

revenue is max[ L(1 + r ), Ph(m)] . Figure 2 graphs these values, again as a function of Ph(m).

Note that the range of limited liability (the horizontal segment of the borrower’s wealth at y2) is

larger here compared to Figure 1 due to the prohibition on deficiency judgments, given m. Thus,

for any level of maintenance, the range of P over which there is a deficit (which in this model is

equivalent to default) is larger here than when deficiency judgments are allowed.7

        Proceeding as above, we can write the borrower’s expected utility in this case as

                                                 ∞
         EU N = y1 − m + v(h(m)) + δ { y 2 + ò [Ph(m) − L(1 + r )]dF ( P )} ,                   (6)
                                                  B


where B ≡ L(1 + r ) / h( m) . The first order condition for optimal maintenance in this case,

denoted mN, is given by

                 ∞
         [v ′ + δ ò PdF ( P)]h ′ = 1 .                                                          (7)
                 B



6
  The eight states are Alaska, Arizona, California, Minnesota, Montana, North Dakota, Oregon, and Washington.
Alaska, California, and Minnesota allow deficiency judgments when the lender uses judicial proceedings against the
borrower, but this rarely occurs according to the Mortgage Bankers Association (State Legislative Topics, 1992).
7
  Jones (1993) finds evidence that prohibition of deficiency judgments in some Canadian provinces increases the
incidence of default.
                                                                                                                     7


Note that this expression differs from (5) only in that the lower bound of the integral is B rather

than A, where B>A reflects the prohibition of deficiency judgments in this case.8 Thus, the

integral term in (5) is larger than the corresponding term in (7), implying that mN<mD<m* , or,

the borrower invests in a lower level of maintenance in the absence of deficiency judgments, all

else equal.

         The loss in the value of the house due to reduced maintenance (given P) is given by

Ph(mD)-Ph(mN).9 Note that this reduction in value reinforces the higher probability of default in

the absence of deficiency judgments.

                                   C. Impact of Interest Rate Adjustments

         To this point, we have assumed that the interest rates were the same regardless of whether

or not deficiency judgments were allowed. This allowed us to isolate the impact of differences

in mortgage laws on borrower maintenance without worrying about the effects of interest rate

adjustments aimed at equalizing lender profits. In this section, we briefly examine the nature of

these second-order effects and show that they reinforce the first-order effects derived above.

         We first examine the impact of changes in the interest rate on borrower maintenance in

the two cases. From the implicit function rule, we know that

         ∂mi / ∂r = (∂ 2 EU i / ∂mi ∂r ) /( −∂ 2 EU i / ∂mi2 ) ,         i=D, N,

where the denominator of this expression is positive by the second-order condition. It follows

that sign(∂mi / ∂r ) = sign(∂ 2 EU i / ∂mi ∂r ) . Differentiating (5) and (7) therefore shows that

         ∂mi
             < 0,          i = D, N .                                                               (8)
          ∂r



8
 The kink in the borrower’s wealth in Figure 2 thus corresponds to B.
9
 Stein (1998: p. 1244) proposes a rule that would allow lenders to recover this loss in the event of default under
non-recourse commercial loans.
                                                                                                                  8


Thus, maintenance is decreasing in r in both cases. Intuitively, an increase in r increases the

range of borrower limited liability (i.e., it makes a deficit more likely), thereby reducing the

marginal benefit of maintenance.

           Now consider the expected return to lenders under the two types of mortgages. When

deficiency judgments are allowed, the lender’s expected revenue is

                   A
            RD = ò [ y 2 + Ph( m)]dF ( P ) + [1 − F ( A)]L(1 + r ) .                                  (9)
                   0


Similarly, when deficiency judgments are prohibited, the lender’s expected return is

                    B
             R N = ò Ph(m)dF ( P) + [1 − F ( B)]L(1 + r ) .                                           (10)
                    0


Differentiating these expressions with respect to r and m yields the following partial effects:

            ∂Ri               ∂Ri
                > 0,              >0           i=D, N.                                                (11)
             ∂r               ∂m

Thus, lenders’ returns are increasing in the interest rate and borrower maintenance in both cases.

           In an equilibrium in which lenders are willing to offer both types of mortgages, the

returns must be equal.10 Using (9) and (10), we find that

                          B
            RD − RN = {ò [ L(1 + r ) − Ph( m)]dF ( P ) + F ( A) y 2 } > 0 .                           (12)
                          A


Thus, the return is higher when deficiency judgments are allowed, holding r and m fixed. This

reflects the advantage to lenders’ of having recourse to borrowers’ non-housing wealth in the

event of default. This difference in lender returns, however, cannot persist in equilibrium, given

a national market for mortgages. In order to achieve equality, suppose that we (arbitrarily) fix rD




10
     This assumes that the costs of originating a mortgage are roughly the same regardless of the legal regime.
                                                                                                                    9


and, given (11) and (12), increase rN. From (8) and (11), however, there is a second-order effect

through borrower maintenance, yielding a total effect on RN of

         dR N ∂R N æ ∂R N öæ ∂m N ö
             =    +ç      ÷ç      ÷,                                                               (13)
          dr   ∂r è ∂m øè ∂r ø

which is ambiguous in sign. If we assume, however, that the maintenance effect is small, then

(13) is positive,11 and equalization of the returns to the two types of mortgages implies that

rN>rD. This conclusion is consistent with Meador’s (1982) finding that mortgage rates are

higher in states that prohibit deficiency judgments (all else equal).12

         Note that the interest rate effect therefore reinforces the earlier finding of a higher level

of maintenance when deficiency judgments are allowed. Specifically, we showed above that

mD>mN for given r. Thus, if we increase rN while holding rD fixed, mN will fall further below mD

(given (8)). Thus, even allowing for variation in interest rates, the prediction that borrowers

invest in greater maintenance when deficiency judgments are allowed remains unambiguous.

                                             IV. Empirical Results

                                                      A. Data

         We use the American Housing Survey (AHS) to test the predictions of the model. The AHS

is a biannual national survey of approximately 50,000 households conducted by the U. S. Bureau of

the Census. It consists of a panel data set that follows selected housing units over time. In each

survey year (1985 through 1995) the Census Bureau collects information about the neighborhood,

the home, the household, and occupancy costs. Of particular interest for this study, the AHS asks

11
   Suppose, for example, that lenders are competitive and set r to maximize the expected utility of borrowers subject
to a profit constraint and the fact that borrowers choose m optimally given r. Forming the appropriate Lagrangian
and differentiating with respect to r yields the first-order condition:
∂EU/∂r+(∂EU/∂m)(∂m/∂r)+λ[∂R/∂r+(∂R/∂m)(∂m/∂r)]=0, where λ is the Lagrange multiplier. Note that the second
term equals zero by the Envelope Theorem (given optimal borrower maintenance). Thus, since ∂EU/∂r<0, the
expression in brackets (which coincides with (13)) must be positive.
                                                                                                                  10


households to report how much they spent on regular maintenance, major repairs (e.g., new roof),

and improvements (e.g., kitchen or bath upgrades) during the last two years.13

        We use the data from five national surveys (1985 through 1993) and limit the sample to

owner occupied single-family houses. 14 We further limit the sample to households with a single

active first mortgage loan originated at the time the homeowner bought the house. In order to

control for the differences in mortgage laws that vary by state, we limit the sample to houses in

identified PMSAs.15 We further limit the sample to homes purchased since 1975 so that we can use

the Freddie Mac MSA house price indices and interest rates at the time of loan origination. Using

the PMSA identifier and State Legislative Topics (1992) Volume 3: Foreclosure, Bankruptcy and

Late Payments, we identify the mortgage law applicable to each observation. After screening for

complete information on relevant variables, we are left with a sample of 6,847 observations.16

                                                   B. Variables

        The literature on homeowner maintenance provides little guidance on the selection of

explanatory variables in a model of maintenance expenditures. Dildine and Massey (1974) and

Vorst (1987) study maintenance in the context of an optimal control problem -- i.e., selecting the

optimal level of maintenance and holding period for rental properties. These models and earlier

qualitative literature (see, for example, Muth [1969] and Lowry [1960]) suggest that the rate of


12
   Also see Stein (1998: p. 1218) who notes that commercial lenders typically require a higher interest rate for non-
recourse loans.
13
   Regular maintenance expenses are reported for the most recent twelve months. Major repairs and improvements are
reported as totals for the last two years (i.e., since the last survey).
14
 We exclude condominium units because the survey does not report information on association spending on
maintenance or project characteristics.
15
   The AHS does not identify the state on all records. A subset of each year’s sample reports the PMSA within
which the property is located.
  16
     In addition to deleting observations with missing date, we excluded very low value homes (<$5,000) and imposed
"reasonability" screens on data describing the estimated house value and mortgage debt. For example, we excluded
observations with estimated current loan-to-value ratios greater than 5 as likely containing data errors.
                                                                                                                    11


change in quality of the structure and neighborhood should influence maintenance expenses. It is

also clear, however, that maintenance and value are jointly endogenous: maintenance expenditures

affect value and value influences maintenance.

         The theoretical discussion above suggests the following three-equation simultaneous system

relating maintenance, value, and mortgage rate:

         Maintenance=f(Value, Rate, Hm, Om, M)                                                               (14)

         Value=f(Maintenance, Hv, Rv)                                                                        (15)

         Rate=f(Maintenance, L, Rr, M).                                                                      (16)

In each equation, the capital letters with superscripts indicate a vector of house characteristics (H),

owner characteristics (O), regional and neighborhood characteristics (R), mortgage loan

characteristics (L), and mortgage law variables (M). Table 1 presents the complete vectors for

each group of variables. The superscript on each vector indicates that only selected variables from

each group are included in the different equations. Equation (14) allows both value and the

mortgage rate to affect maintenance. The interest rate is included because, as noted, a higher

interest rate increases the range of limited liability for the borrower. The value equation is a

traditional hedonic model based on the premise that the value of a bundled good reflects the product

of attributes and shadow prices of those attributes. The dependent variable is the homeowner’s

estimate of the current house value. 17 Maintenance enters as an offset to depreciation, and also

because our measure of maintenance expenditures includes spending on additions. Under this view,




17
  Kiel and Zabel (1999) report that, although homeowners tend to overvalue their homes by about 5%, the difference
between homeowner estimates and sales prices are not correlated with characteristics of the house, its occupants or
neighborhood. The home values reported in the AHS are top coded at the 97th percentile of the full sample in a given
survey year. A total of 377 observations were top coded.
                                                                                                                     12


neither owner characteristics nor the mortgage rate on the loan used to purchase the house affects

the value.18

         The rate equation is based primarily on the term structure of interest rates at the time the

loan was originated.19 This equation allows for anticipated maintenance to influence the mortgage

rate. The latter effect is justified by the assumption that lenders implicitly make an estimate of how

well a particular buyer will maintain property serving as collateral for a loan in assessing the overall

riskiness of the loan.

         We include in Hm, the vector of house characteristics entering the maintenance equation, the

borrower’s estimate of current house value, and the three categorical indicators of structure age. We

expect higher maintenance expenditures to be associated with higher value and older homes. The

vector Om includes measures of the age, income, wealth, education, experience with

homeownership, and time in the house. If maintenance is a normal good, we expect to find a

positive relationship between income and maintenance. We measure income using the total salary

income reported for the two highest earners in the household and an indicator variable signaling that

the head of household receives social security income.20 The AHS data provides very limited

information about household wealth. We use two proxies: the number of automobiles and trucks

owned by members of the household and whether or not the household maintains a savings account.

As with income, we expect higher wealth to be associated with higher expenditures on maintenance.

         Homeowner age, education, and experience with homeownership may be correlated with

unobserved income and wealth, but may also have a direct effect. We expect that older

homeowners may be less able to maintain their homes, and first-time homeowners may be less

18
   We excluded “seller” originated loans from our sample. All loans are made by third party financial institutions
and therefore there is less risk that below-market rates are capitalized into the selling price.
19
   The month of origination is not recorded in the AHS data for loans originated in the period from 1975 through
1978. The origination month was set to June for these observations.
                                                                                                                   13


informed about good maintenance practices. Tenure in the home could affect maintenance if recent

buyers are “house poor” and have limited discretionary resources for maintenance.21 Tenure in the

current home is measured with two categorical variables indicating time in house of 1-2 years and

2-5 years. The excluded category is longer than five years.

         The only loan characteristic included in Lm is the interest rate on the loan. We do not

include any regional or neighborhood variables in the maintenance equation, although these

variables can influence maintenance indirectly through their effect on value.

         The vector M includes an indicator variable identifying those properties that are in states

where deficiency judgments are granted when the lender follows the normal foreclosure

procedure.22 Our theory indicates that when lenders have recourse to other assets of the borrower in

the event of default, the borrower bears more of the true cost of overutilization and will tend to

spend more on maintaining the property. We also control for borrower equity with an indicator that

takes on a value of one when the borrower’s current loan-to-value ratio exceeds 90%.23 We

estimate the current market value of the home using the original purchase price and the change in

the Freddie Mac house price index for the PMSA. This estimate of value (and the resulting

indicator value) avoids the potential endogeneity between homeowner-estimated value and past

maintenance expenditures. We use the original loan amount24 as the numerator to estimate the




20
  We do not have complete data on other sources of income or the amount of social security income.
21
  The transfer of the property and the associated new mortgage provides an opportunity to finance repairs if buyers
demand that sellers bring the home to a standard quality level as part of the sale negotiation.
22
   Some states, including California, do not allow deficiency judgments unless the lender uses a judicial procedure
instead of the standard power of sale process. The judicial procedure is rarely used, and California is categorized
here as a non-recourse state based on the normal procedures used by lenders.
23
   After allowing for normal sales and closing costs, owners with loan-to-value ratio greater than 90% have
essentially no recoverable equity in the house.
24
   The AHS data does not include current loan balance nor does it provide sufficient information to calculate a pro-
forma balance without a significant loss of sample size.
                                                                                                                    14


current loan-to-value ratio. When the loan-to-value ratio is low, the borrower bears almost all the

costs of overutilization, regardless of the local mortgage law.

         Although the vectors of house characteristics and regional variables included in the value

equation are drawn from the list in Table 1, the specific elements are different from those in the

maintenance equation. Following the customary structure of hedonic models, Hv includes the size

of the home (measured in square feet), the number of rooms, and the number of bathrooms in

addition to the categorical age variables. Demographic variables are generally not included on the

right hand side of traditional hedonic equations and so are excluded here. We control for local price

differences using a set of PMSA indicators. We suppress the coefficients for these indicator

variables in our results. Rm also includes an indicator of dissatisfaction with the neighborhood on

the premise that local amenities are capitalized into house prices, and an indicator that the property

is in a location designated as a central city. A sequence of indicator variables for the different years

is used to capture shifts in shadow prices over time.

         The interest rate equation is based primarily on the assumption that mortgage rates track

market conditions. Consequently, Lr includes the ten-year government bond rate in the origination

month and the yield curve slope (measured as the ten-year government bond rate less the three-

month bill rate). In addition, Lr includes an indicator that the original loan to value ratio exceeded

the 80% threshold at the time of origination.25 We include three regional indicators in Rr because

there is evidence of regional variations in rates during the period these loans were originated.26



25
   The original loan-to-value ratio used in this equation is based on the purchase price of the home and not the
current estimate of value that was used in the current loan-to-value ratio in the maintenance equation. We use 80%
as the threshold in the rate equation because the secondary market for mortgages traditionally differentiates high risk
and low risk mortgages using the 80% threshold.
26
   Longbrake and Peterson (1979) reported that mortgage rates in the 1970s averaged approximately 100 basis points
lower in the Northeast region than in the West and South regions. More recent studies (e.g. Jameson, Shilling and
Sirmans [1990] and Jud and Eppley [1991]) suggest that while the growth of the secondary market has reduced
regional differences, local conditions remain significant in determining mortgage rates.
                                                                                                       15


                                                         C. Results

            Table 2 reports our results. Three stage ordinary least squares was used for the

estimation.27 The natural log of maintenance expenditures28 and house values were used

throughout. The house characteristics enter the maintenance equation with the expected signs

and significance. Maintenance expenses are higher with higher valued and older homes. Higher

income, higher wealth, and more education are associated with higher maintenance expenditures.

First-time homeowners and those who have just moved into their homes spend less on

maintenance. The coefficient on the mortgage rate is negative, as predicted, but not significant.

The imprecision in measuring this effect is not surprising given the small effect the mortgage

rate, r, has on the range of limited liability and is consistent with the expectation that the rate

effect would be smaller than the deficiency-judgment effect.

            The mortgage law effects are reported near the bottom of Table 2. As expected,

homeowners in states that permit deficiency judgments spend approximately 19% more ($ 470)

on maintenance of their homes than do homeowners in non-recourse states. The sign on the

recourse indicator variable is positive and significant at the 5% level. The coefficient on the

indicator of no recoverable equity is negative and very significant. This is consistent with the

earlier results of Harding, Miceli and Sirmans (1999) that when homeowners do not expect to

enjoy the future benefits of maintenance, they spend less.

            The other equations are of less direct interest but are presented here for completeness.

The results in the value equation are generally consistent with previously published hedonic

results. House value and size are positively associated. The PMSA indicators are jointly very

significant, and prices are generally lower in central cities and unsatisfactory neighborhoods. As

27
     The first stage regression results are not reported here but are available from the authors.
                                                                                                                   16


predicted, the coefficient on maintenance is positive and very significant. The mortgage rate

equation shows that the government bond rate is the major factor determining mortgage rates.

The sign on loan-to-value is positive, consistent with theory. The regional variables indicate that

during this time period mortgage rates were somewhat lower in the East than in the other

regions. The negative coefficient on maintenance is consistent with the expectation that lenders

charge lower rates when the borrower is expected to maintain the house at a higher rate.

         Overall, the empirical results confirm that maintenance expenditures, value, and

mortgage rates form an interrelated system. Further, the estimated coefficients on the mortgage

law effects are consistent with the theoretical prediction.

                                                 V. Conclusion

         This paper has presented a theoretical and empirical analysis of the impact of variation in

mortgage laws on household maintenance decisions. The specific law we examined concerned

the right of lenders to seek deficiency judgments against a borrower’s non-housing wealth in the

event that the house value falls below the mortgage balance. The theory predicted that

homeowners would invest in greater maintenance when lenders have this right. The reason is

that homeowners have more to lose in the event of a deficit, so they will invest in greater

maintenance in order to reduce the likelihood that the market value of the house will fall below

the mortgage balance.

         We tested this prediction using data from the American Housing Survey and information

on cross-state variation in mortgage laws. Because maintenance, house value, and mortgage

rates are inter-related, we estimated a system comprising three simultaneous equations using

three stage OLS. The results showed that homeowners in states where deficiency judgments are


28
  In calculating the natural log of maintenance expenses, we added $1 to all reported amounts to assure that the
dependent variable is well defined.
                                                                                            17


allowed invested at a higher rate, and the effect was significant, thereby confirming the

predictions of the theory.
                                                                                               18


                                         References

Burke, D. (1989) Law of Federal Mortgage Documents, Boston: Little-Brown.

Dildine, L. and F. Massey (1974) “Dynamic Model of Private Incentives to Housing
Maintenance,” Southern Economic Journal 40: 631-639.

Gibson, F., J. Karp, and E. Klayman (1992) Real Estate Law, 3rd Edition, Chicago: Dearborn.

Harding, J., T. Miceli, and C.F. Sirmans (1999) “Do Owners Take Better Care of Their Housing
than Renters?” manuscript, Department of Finance, University of Connecticut.

Henderson, J.V. and Y. Ioannides (1983) “A Model of Housing Tenure Choice,” American
Economic Review 73: 98-113.

Jameson, M., J. Shilling, and C.F. Sirmans (1990) “Regional Variation of Mortgage Yields and
Simultaneity Bias,” The Journal of Financial Research 13(3): 211-219.

Jones, L (1993) “Deficiency Judgments and the Exercise of the Default Option in Home
Mortgage Loans,” Journal of Law and Economics 36: 115-138.

Jud, D. and D. Eppley (1991) “Regional Differences in Mortgage Rates: An Updated
Examination,” Journal of Housing Economics 1: 127-139.

Kiel, K. and J. Zabel (1999) “The Accuracy of Owner-Provided House Values: The 1978-1991
American Housing Survey,” Real Estate Economics 27: 263-298.

Longbrake, W. and M. Peterson (1979) “Regional and Inter-regional Variations in Mortgage
Loan Rates,” Journal of Economics and Business 31:75-83.

Lowry, I. (1960) “Filtering and Housing Standards: A Conceptual Analysis,” Land Economics
36: 362-370.

Meador, M. (1982) “The Effects of Mortgage Laws on Home Mortgage Rates,” Journal of
Economics and Business 34: 143-148.

Muth, R. (1974) Cities and Housing, Chicago: Univ. of Chicago Press.

State Legislative Topics (1992) Volume 3: Foreclosure, Bankruptcy, Late Payments, L.
McKenna, ed., Washington, DC: Mortgage Bankers Association.

Stein, G. (1998) “The Scope of the Borrower’s Liability in a Nonrecourse Real Estate Loan,”
Washington and Lee Law Review 55: 1207-1284.

Vorst, A. (1987) “Optimal Housing Maintenance Under Uncertainty,” Journal of Urban
Economics 21: 209-227.
                                                                                       19




    $                                      Ph(m)+y2



                                            Ph(m)


                                             Ph(m)+y2-L(1+r)

L(1+r)

                                                                   Borrower
    y2                                                             Lender




                                                    Ph(m)




         Figure 1: Borrower and lender wealth when deficiency judgments are allowed.
                                                                                          20




   $


                                                 Ph (m)



                                                   Ph(m)+y2-L(1+r)

L(1+r)


                                                                     Borrower
   y2                                                                Lender




                                                    Ph(m)




         Figure 2: Borrower and lender wealth when deficiency judgments are prohibited.
                                                                                                                     21
                                                    Table 1
                                         Summary Statistics
                     6847 Owner-Occupied Single Family Houses from 1985-1993 AHS

  Category                 Variable                            Mean        Std. Dev       Min           Max
             Maintenance Expenditures                        $2,467.81     $3,978.00      $0.00      $54,985.00
House Characteristics
             Homeowner Estimate of Value**                     $129,940        $78,336    $ 5,000    $   350,000
                  % Value Top Coded                                 5.51%
                 Age of Structure (yrs)                                26.7          20.2          0            83
                  % 1-5 years old                                  10.44%        --           --           --
                  % 5-10 years old                                 12.20%        --           --           --
                  % 10-15 years old                                13.52%        --           --           --
                 Size (sq ft)                                         2,106           878        200          5000
                 Number of Rooms                                        6.8           1.6          2            16
                 Number of Bathrooms                                    2.2           0.9          1            12
Region & Neighborhood Characteristics
                  % in Western Region                              21.70%        --           --           --
                 % in Southern Region                              27.43%        --           --           --
                 % in Midwest Region                               28.30%        --           --           --
                 % In Central City                                 34.56%        --           --           --
                 % In Unsatisfactory Neighborhood                   2.31%        --           --           --
Homeowner Characteristics
                 Age : Head of Household (yrs)                         42.0          11.2         16            88
                 Salary Income                                    $47,120        $30,425          $0      $200,000
                 % Receiving Soc Security                          10.85%        --           --           --
                 Mortgage Payment                               $ 744.94 $         427.32 $ 52.00 $ 2,000.00
                 Education*
                  % High School or Less                             6.28%        --           --           --
                  % College or More                                46.69%        --           --           --
                 Time in Home (yrs)                                     6.3           4.5          1            19
                  % In Home Less Than 2 Years                      24.86%        --           --           --
                  % In Home 2-5 Years                              26.84%        --           --           --
                 % First Time Owner                                39.64%        --           --           --
Wealth of Homeowner
                 Number of Vehicles                                     2.1           0.9          0             8
                 Savings (1=Yes)                                   95.40%        --           --           --
Loan & Market Characteristics
                 10 Yr. Treasury Rate at Orig.                       9.18%     1.94%        5.33%       15.32%
                 Yield Curve Slope                                  1.85%      1.30%       -2.65%        4.42%
                 Interest Rate on Mortgage                          9.78%      1.69%        4.00%       20.00%
                 % Loan-to-Value Ratio> .80                        45.52%        --           --           --
Incentives
                 % with Loan-to-Value Ratio>.9                      7.45%        --           --           --
                 % Deficiency Judgment Allowed                     78.94%        --           --           --
* The excluded category is some college education without a degree.
** House value is top coded at the 97th percentile of the full year's sample. 377 observations were top coded.
This table presents the summary statistics of a sample drawn from the 1985-1993 AHS surveys.
The sample was restricted to owner occupied single family (attached and detached) houses
where the owner also currently has an outstanding mortgage loan.
 The observations were distributed over time as follows: 1985- 1,593; 1987-1,184;
1989-1,447; 1992-1,319; 1993- 1,304.
                                                                                                                                                          22
                                                                        Table 2
                            Three Stage OLS Estimation of Contractual Effects on Maintenance Expenditures
                                                     Maintenance               Value                         Interest Rate
                                              Coefficient   t-statistic    Coefficient  t-statistic   Coefficient    t-statistic
House Characteristics
                                                                                     b
       ln(Estimated Value)                                  0.1741            2.01
                                                                                                                        a
       Top Code Indicator                                                                      0.3006           12.86
       Age of Structure
                                                                                     a                                  a
        1-5 years                                          -2.6978          -23.27             0.4030           14.00
                                                                                     a                                  a
        5-10 years                                         -1.1249          -10.83             0.1489            7.47
                                                                                     a                                  b
        10-15 years                                        -0.5006           -5.05             0.0390            2.22
                                                                                                                        a
       Size (sq ft)                                                                            0.0001           17.47
                                                                                                                        a
       Number of Rooms                                                                         0.0725           17.62
                                                                                                                        a
       Number of Baths                                                                         0.1019           14.50
                                                                                                                        a                             a
       Maintenance Expenditures                                                                0.0939           10.41            -0.1358     -7.99

Region & Neighborhood Characteristics
       West                                                                                                                       0.0267      0.28
                                                                                                                                                      c
       South                                                                                                                     -0.0947     -1.77
       Midwest                                                                                                                    0.0330      0.64
                                                                                                                        a
       Central City Location                                                                  -0.0511           -4.14
                                                                                                                        a
       Unsatisfactory Neighborhood                                                            -0.2665           -8.38
       Year Indicator (1985=Base)
                                                                                                                        a
       1987                                                                                    0.1184            7.73
                                                                                                                        a
       1989                                                                                    0.2407           16.51
                                                                                                                        a
       1991                                                                                    0.2720           18.17
                                                                                                                        a
       1993                                                                                    0.2544           16.12

Homeowner Characteristics
                                                                                     a
       Age : Head of Household                             -0.0121           -3.42
                                                                                     a
       Salary Income ($,000)                                0.0133           10.98
       Education
                                                                                     b
        High School or Less                                -0.2941           -2.39
                                                                                     a
        College or More                                     0.4881            7.49
       Time in Home
                                                                                     a
       1-2 years                                           -0.3118           -3.75
                                                                                     a
       2-5 years                                            0.2788            3.53
                                                                                     a
       First Time Owner                                    -0.5182           -7.65
                                                                                     a
       Receiving Soc Security                               0.3737            3.39

Wealth of Homeowner
       Number of Vehicles                                   0.0559            1.64
                                                                                     a
       Savings (1=Yes)                                      1.1248            7.77

Loan & Market Characteristics
                                                                                                                                                      a
       10 Yr. Treasury Rate at Orig.                                                                                              0.4058     43.16
                                                                                                                                                      a
       Yield Curve Slope                                                                                                         -0.0456      -3.29
       Interest Rate on Mortgage                           -0.0173           -0.51                                               --        --
                                                                                                                                                      a
       Original LTV Ratio > 80%                                                                                                   0.1686       4.58

Mortgage Law Incentives
                                                                                     a
       Current LTV Ratio > 90%                             -0.4507           -3.93
                                                                                     b
       Deficiency Judgments Allowed                         0.1867            2.19                                                0.0524      0.60
                                                                                     a                                  a                             a
Constant                                                    3.1218            2.82             9.4907           86.88             6.8421    41.47

       Number of Observations                                6847                               6847                               6847
        2
       χ                                                   1168.84                            8582.86                            1916.55
       P-Value                                              0.0000                             0.0000                             0.0000

       a=significant at the 1% level; b=significant at the 5% level; c=significant at the 10% level.
       Table 2 presents the results of three stage OLS estimation of the system of equations describing maintenmance, value,
       and mortgage rate. The natural log of maintenance and value are used throughout. Original LTV is the ratio of original
       loan amount to purchase price. Current LTV is the ratio of original loan amout to the estimated current market value of
       the house. A joint test of the PMSA indicators rejects the null hypothesis of no effect at the 1% level.

				
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