House Journal Value of Appreciation Housing Research among Older Volume Homeowners 8, Issue 2 201 Fannie Mae Foundation 1997. All Rights Reserved. House Value Appreciation among Older Homeowners: Implications for Reverse Mortgage Programs Roberto G. Quercia* Abstract Four factors are key to the long-term viability of reverse mortgage programs: expected interest rates, borrower longevity, dropout rates, and house value appreciation. Data from the 1968 89 Panel Study of Income Dynamics are used to estimate house value appreciation and dropout rates and thus assess the accuracy of the assumptions in a major reverse mortgage program, the Home Equity Conversion Mortgage (HECM) demonstration program of the Federal Housing Administration (FHA). Older homeowners (age 62 or older) those who would qualify to participate in the FHA program experienced appreciation in line with program assumptions. In contrast, housing-rich, incomepoor homeowners age 71 or older those who most resemble actual HECM borrowers experienced appreciation lower than assumed. FHA s expected dropout rate is significantly lower than those estimated. The use of a dropout rate lower than actually occurs may compensate for lower-thanexpected appreciation and thus increase the program s long-term viability. Keywords: reverse mortgages; elderly homeowners; house value appreciation; equity conversion Introduction The ability to access home equity is important to the well-being of many older homeowners. This is because after retirement, most older homeowners have the bulk of their nonpension wealth accumulated during working years in the form of home equity (Mayer and Simons 1994). This home equity can provide the resources needed to compensate for the decline in earnings that commonly accompanies retirement. In this way, homeowners can use the accumulated wealth in the home to pay for medical expenditures and other necessities. Older homeowners can access their home equity through a number of housing adjustment mechanisms. They can sell the home and move to a smaller one, thus liberating some home equity, or they can access home equity in place without moving by undertaking one of the so-called nonmoving housing adjustment mechanisms (Quercia and Rohe 1992). One such mechanism is home equity conversion through a reverse mortgage (RM). In an RM program, lenders make cash advances to qualified older homeowners against their home equity. Lenders rely on the anticipated value of the home as a source of repayment for both principal and accumulated interest. A program s greatest risk is the * Roberto G. Quercia is an Assistant Professor of City and Regional Planning at the University of North Carolina at Chapel Hill. The research reported on here was supported by a National Institute on Aging fellowship at the University of California, Berkeley. The author gratefully acknowledges Ed Szymanoski and Kathleen Thomas for their helpful comments and suggestions.
202 Roberto G. Quercia potential shortfall between the value of the property and the value of the debt when it comes due, which may occur when borrowers move, sell the property, or die. Because of the nonrecourse nature of these loans, the success of an RM program will be closely related to the future levels of mortgage debt and property values (Szymanoski 1990). Accurate estimation of the future value of homes is key to the long-term viability of RM programs, the number of which has more than tripled since 1989 (Merrill, Finkel, and Kutty 1994). Two programs are worth mentioning: the Federal Housing Administration (FHA) Home Equity Conversion Mortgage (HECM) demonstration program, which provides RM insurance, and the Fannie Mae Home Keeper program, which provides a secondary market outlet for RMs. The strength and magnitude of the institutions involved could allow these two programs to be catalysts for the industry, as they have been in the development and evolution of the forward mortgage market over the past five decades. The importance of these and other RM programs can be expected to increase for several reasons. First, the aging of America will continue to accelerate as baby boomers enter their retirement years. The growing number of older homeowners will increase the demand for initiatives, such as RMs, that allow older Americans to convert equity into cash and to age in place. Second, home equity will continue to be the major source of accumulated nonpension wealth for retiring homeowners. Finally, from a policy perspective, private sector RMs may be ideal instruments because they do not burden public budgets. 1 Given that assumptions about house value appreciation are fundamental to the success of RM initiatives, the central goal of this article is to examine the appreciation experienced by older homeowners from 1968 to 1989 and compare it with the appreciation assumed in a major RM program. FHA s HECM program is selected for this comparison because it may play a crucial role in the development of the RM industry and because the necessary information is available. 2 Because the amount of home equity that can be accessed is directly related to the proportion of participants likely to drop out of an RM program over time, the dropout rate assumption in the FHA program is also examined. The article is divided into three sections. First, the key assumptions in the FHA RM program are described, including its assumptions about house appreciation and dropout rates. Second, actual patterns of house value appreciation and dropout rates experienced by older homeowners from the Panel Study of Income Dynamics (PSID) are compared with those expected under the FHA assumptions. Finally, the empirical findings are used to derive implications for the FHA program and other RM programs. 1 Some analysts believe that the demand for RMs does not exist. For instance, on the basis of their empirical analysis, Venti and Wise (1990) contend that few elderly homeowners access home equity by moving to less valuable homes; they conclude that older homeowners are unwilling to access equity from their homes in any way. See Quercia and Rohe (1992) for a contrary finding. 2 Unfortunately, because the information needed is proprietary, the Fannie Mae program was not included in the analysis.
House Value Appreciation among Older Homeowners 203 FHA RM Program The FHA RM program, established by the Housing and Community Development Act of 1987, provides mortgage insurance to lenders who make cash advances secured by an RM and note to homeowners ages 62 and older who own their homes free and clear. The program requires lenders to offer three basic HECM types: line of credit, term, and tenure. In all cases, borrowers are allowed to remain in their homes until they sell them, move, or die. 3 The FHA insurance protects both the borrower and the lender. Borrowers are protected against lenders inability to continue loan disbursement or payments over time. The insurance premium consists of two parts, both paid by borrowers: (1) an up-front premium of 2 percent of the adjusted property value that is, the appraised value or the maximum mortgage amount on a one-unit residence as established in the FHA Section 203(b) program, whichever is less and (2) a monthly premium of 1/12 of the annual rate of 0.5 percent of the outstanding principal balance, which accrues to the outstanding balance. Both parts can be financed. Lenders are protected against shortfalls between the value of the property and the value of the loan when it comes due. The program insures lenders up to a maximum loan limit for properties valued at or below the maximum adjusted property value in the FHA Section 203(b) program. 4 The main risk for the program is that when a loan comes due, the value of the property will be insufficient to repay the loan fully. In the FHA program, four factors are considered in estimating the maximum loan size (i.e., the amount of equity that may be accessed). First, the current and expected interest rates are considered; a higher rate leads to a smaller loan (i.e., a smaller proportion of the equity can be accessed). 5 Because the unpaid interest accumulates rapidly over time until the reverse loan comes due, higher interest rates mean that more of the accessed equity must be devoted to loan repayment (i.e., accumulated unpaid interest). Second, how long borrowers are likely to live is a key consideration. A longer life results in a smaller loan because the loan comes due when the borrower dies. FHA uses the 1979 81 U.S. decennial life table for white females as the source of life expectancy information to calculate the maximum loan size (U.S. Public Health Service 1985). This is a conservative assumption, since this group is the one with the longest life expectancy. Also, the life tables do not differentiate between owners and renters, who may have different life expectancies. Third, the proportion of borrowers likely to drop out of the program for reasons other than death is also considered. A lower dropout rate results in a smaller loan because borrowers 3 Fannie Mae s Home Keeper program offers two options: line of credit and tenure. Refer to Case and Schnare (1994) for a full description of FHA s HECM program and to Fannie Mae (1996) for a description of the Home Keeper program. 4 Loan limits in the FHA program vary geographically, ranging from $78,660 in rural areas to $155,250 in higher-cost urban areas. The loan limit in the Fannie Mae program is $207,000. Both programs have higher limits in Hawaii; Fannie Mae also has a higher limit in Alaska (Fannie Mae 1996). 5 This is called the principal limit in the FHA program.
204 Roberto G. Quercia are expected to live longer in their units, which delays the time when loans come due. On the basis of work by Jacobs (1988), FHA assumes that one-third of older homeowners will drop out of the program before they turn 100 years old. FHA did not test the accuracy of this assumption. Last, and most important, the value of the home and the expected appreciation are key considerations. A lower value to begin with or a lower appreciation over time results in a smaller loan. FHA assumes that house value appreciation is described by a geometric Brownian motion (GBM) process with a 4 percent mean or drift and a 10 percent standard deviation of the mean for all properties in the program. Specifically, the house value at any time (H T ) is estimated as a function of the origination value of the home H 0, the time T, the expected mean appreciation m, and the standard deviation of the appreciation s, so that H T = H 0 exp[mt + B(T)]. B(T) is the standard Brownian motion, or Wiener process, with expected value 0 and standard deviation T (Szymanoski 1994). If m is 4 percent and s is 10 percent, the annual change in average appreciation is about 4.6 percent. The accuracy of the GBM assumption is key to the long-term viability of the FHA program. The program s central model is very sensitive to small changes in the assumed mean appreciation rate (Szymanoski 1990). Sensitivity analysis indicates that an appreciation rate 1 percentage point lower than the assumed 4 percent causes expected losses in the program to increase by 26 percent if the other parameter is held constant. 6 This same analysis indicates that the model is less sensitive to changes in the assumed 10 percent standard deviation (Szymanoski 1990). FHA assessed the accuracy of its appreciation assumption in two ways. First, data from the American Housing Survey (AHS) were used to compare the assumption with the historical appreciation of single-family homes in the owner-occupied market. Second, FHA compared the assumed appreciation with previous work on the topic for consistency. In both cases, the assumption was found to be appropriate (Szymanoski 1990). This conclusion, however, may not be accurate. First, the historical appreciation of all single-family homes in the owner-occupied market might not be representative of the appreciation of housing owned by older homeowners likely to participate in the FHA program. A case can be made that such housing represents a distinct submarket. The homeowners likely to participate in an RM program are those who are oldest, have low incomes, and have substantial home equity (Merrill, Finkel, and Kutty 1994), and their housing may constitute a distinct submarket on the basis of geographic location and dwelling characteristics. As long-time neighborhood residents, these oldest homeowners may live in naturally occurring geographic clusters, which could be characterized by similar appreciation trends. Also, these homeowners may occupy dwellings that are similar in characteristics such as number of rooms, amenities, and structure age because they were built around the same time. If they do constitute a distinct submarket, these 6 The program can remain viable with a lower appreciation rate if other parameters change in a favorable way. For instance, the 1994 evaluation concludes that the HECM program can remain viable with a 3 percent appreciation because of prevailing lower-than-expected interest rates and the number of properties in the program with values above the FHA 203(b) limits (Edward J. Szymanoski, Jr., personal communication, 1994).
House Value Appreciation among Older Homeowners 205 oldest homeowners may experience appreciation rates different from that of the average homeowner. 7 Second, the assessment of FHA s appreciation assumption based on previous work may not be fully adequate. Typically, previous work has relied on the use of indices to estimate house value appreciation. The use of indices has allowed researchers to estimate changes in value while holding housing quality and characteristics constant. 8 Unfortunately, published constant-quality price indices may not reflect the maintenance and repair behavior of many older homeowners, a behavior likely to affect appreciation over time. Older homeowners who participate in the HECM program must have their homes in good repair at origination. This may change over time, however, especially for the oldest housing-rich, income-poor homeowners. Lacking a meaningful source of earnings, these households are likely to use HECM proceeds for expenses other than maintenance and repairs and thus lower the market value of their homes over time through continued omission of necessary maintenance (Guttentag 1975). This contention is supported by the 1992 HECM evaluation (U.S. Department of Housing and Urban Development [HUD] 1992), which reported that most HECM borrowers were expected to use loan proceeds to cover unforeseen or ordinary living expenses (i.e., things other than regular repairs and maintenance). Thus, the oldest housing-rich, income-poor homeowners, those who have the most to gain from participating in an RM program, are likely to experience appreciation rates unlike those captured in the published literature on constant-quality indices. Two recent studies that have looked at the aggregate housing appreciation expected for the 1990 2010 period are worth noting. These studies have attempted to measure the effect of demographic changes, especially the aging of the baby boom generation, on aggregate housing demand and house values. In the most publicized of these studies, Mankiw and Weil (1989) project that the decline in the growth of aggregate housing demand is expected to result in a 47 percent decline in values by 2010. However, this result has been widely criticized. For instance, Pitkin and Myers (1994) conclude that Mankiw and Weil overstate the 1990 2010 decline in the growth of aggregate housing demand by 45 percent in comparison with more appropriate estimates. Interestingly, it is not whether the growth in aggregate housing demand will decline that seems to be in question, but the magnitude of the decline. In any case, regardless of the way this issue is ultimately settled in the empirical literature, the fact remains that the aging of the baby boom generation will likely affect the appreciation of housing owned by older homeowners in the years to come. For all these reasons, it is not clear that the FHA assumption is appropriate to capture the house value appreciation of the oldest homeowners likely to participate in the HECM program. To address this issue, this study examines the house value appreciation experienced by older homeowners over the 1968 89 period relative to the appreciation assumed in the FHA program. The accuracy of the dropout rate assumed in the FHA program is also examined. Because of the direct relationship between the dropout rate 7 There is empirical substantiation for this contention. Poterba (1991) found that since 1979, house prices have declined in real terms in many submarkets but increased in others. 8 For example, see Case and Shiller (1989), Gau (1984, 1985), and Linneman (1986) for a discussion on the use of house price indices to test efficiency in housing markets and the implication of this for house value appreciation.
206 Roberto G. Quercia and the amount of equity that can be accessed, the use of a dropout rate lower than actually occurs can compensate for an appreciation rate below expectations. The Study Period: 1968 to 1989 The empirical analysis is based on PSID data from the 1968 89 period, a time of important demographic and economic changes. Demographically, the baby boom generation entered the housing market, a fact that affected the type and amount of housing demanded and supplied (Hughes and Sternlieb 1987). Economically, two of the most severe recessions in history took place in the middle of the period. Nevertheless, the initial part of the study period was a period of relative stability. During the earlier years (1968 70), there was an expansion of the business cycle that had started in 1961. Housing starts, a key economic indicator, averaged about 1.4 million units annually during this period (table 1). From 1971 to 1973, the economic expansion continued, with housing starts almost reaching more than 2 million annually, until the beginning of the 1974 75 depression (Hughes and Sternlieb 1987). During the second half of the study period, the economic environment was much less stable. Housing starts dropped to 1.2 million annually in 1975. Two years later, in the 1977 78 recovery, they reached 2 million annually. Housing starts plummeted again in the 1979 82 recession, reaching a low of about 1 million annually in 1982. Two years later, housing starts were up 70 percent, to about 1.7 million. Housing starts peaked at 1.8 million in 1986 and reached a low of 1.4 million again in 1989. Housing starts bottomed out in 1991, at 1.0 million. In 1994, housing starts reached 1.475 million, similar to the 1968 level (HUD 1996). Interest rates varied greatly over the study period (table 1). Rates on a conventional 30-year mortgage averaged about 7.8 percent at the beginning of the study period, peaked at more than 16 percent in 1981, and declined until 1993, when they reached a low of 7.16 percent. Rates have increased since then to reach 8.5 percent in the fourth quarter of 1994 (HUD 1996). The end of the 1979 82 recession marked the beginning of a phase characterized by disinflation. Five years of economic expansion were followed by a recession that bottomed out in 1991. In addition, the 1980s saw a restructuring in which housing became just one of the components of a financial system that is now worldwide in scope (Hughes and Sternlieb 1987). To sum up, the availability of data from the 1968 89 period allows for the examination of house appreciation trends over a long period. But the unstable economic environment during the second half of the study period may limit any inferences that can be made about the future based on the 1978 89 data. Moreover, the next decades will see dramatic changes as the baby boom generation continues to age. In 1994, 37 million people in the United States were 62 years old or older; by 2020, the number is expected to be 66 million (Mayer and Simons 1994). This growth is likely to affect the housing market in unique ways (Mankiw and Weil 1989; Pitkin and Myers 1994), thus limiting the inferences that can be made about the future based on any past data. Nevertheless, the use of panel data
House Value Appreciation among Older Homeowners 207 Table 1. Key Economic Indicators, 1968 to 1989 Mortgage Interest Rates, Housing Starts 30-Year Fixed-Rate Year (Millions of Units) Conventional 1968 1.51 7.12 1969 1.47 7.99 1970 1.43 8.52 1971 2.05 7.75 1972 2.36 7.38 1973 2.05 8.04 1974 1.34 9.19 1975 1.16 9.04 1976 1.54 8.88 1977 1.99 8.84 1978 2.02 9.63 1979 1.75 11.19 1980 1.29 13.77 1981 1.04 16.63 1982 1.06 16.09 1983 1.70 13.23 1984 1.75 13.87 1985 1.70 12.42 1986 1.81 10.18 1987 1.62 10.20 1988 1.50 10.33 1989 1.38 10.32 Source: HUD (1996), except for the 1968 71 interest rates (U.S. Bureau of the Census 1973). from the 1968 89 period offers a unique opportunity to examine the house value appreciation experienced by older homeowners over a number of housing and business cycles. Moreover, the strength of the data lies also in the ability to examine appreciation rates for different types of cohorts of older homeowners.
208 Roberto G. Quercia Data PSID began in 1968 as a follow-up to a federal program designed to assess how well the War on Poverty was succeeding. PSID began by interviewing a representative sample of 4,802 households in 1968 and reinterviewing them every year. Over time, other households were added to the study; these included, for instance, new households formed by family members of the original households. In 1968, the study included 520 homeowners who were 62 years old or older. As of 1989, PSID had collected 22 years of data from a sample of nearly 16,000 households, a third of which were homeowners in that age range. PSID data are used to examine the house value appreciation experienced by older homeowners over the 1968 89 period and to compare this appreciation with that assumed in the FHA RM program. To complement this examination, the accuracy of FHA s dropout rate assumption is also examined. This analysis is descriptive. Throughout the analysis, t statistics are used to compare mean PSID house values at the end of the study period with the values expected under the FHA assumption. Means, rather than medians, are used because they better reflect extreme values. From a lender s perspective, it is the overall burden of risk that matters, and this is better captured by the mean. 9 The appreciation rates are reported for the country as a whole. Although it would have been more desirable to capture the geographic variation of value appreciation, data limitations precluded such computation. 10 The PSID sample is not large enough to be broken down to capture geographic variation, especially for the oldest housing-rich, income-poor homeowners. Using the 1989 AHS national survey, Merrill, Finkel, and Kutty (1994) report that older homeowners are more likely to live in the South, followed by the Midwest, Northwest, and West (36, 27, 22, and 14 percent, respectively). They also report that those likely to participate in an RM program, homeowners 71 years old or older with low incomes and substantial home equity, are more likely to live in the Northeast, followed by the West, South, and Midwest (49, 21, 21, and 9 percent, respectively). These figures suggest that the U.S.-wide statistics presented below may conceal wide geographic variations. The appreciation rates estimated from the PSID data are based on changes in house values over time. Two issues are worth mentioning. First, as with other data sets, the house values in PSID are self-reported by the owner-occupant, a fact that may lead to under- or overestimation. Second, house value is used rather than net equity (house value minus mortgage debt), but this does not weaken the study findings because the goal is to examine the house value appreciation experienced by older homeowners, not their equity buildup. 9 The use of medians instead of means would likely show lower appreciation rates among PSID homeowners. The median value for existing homes in the United States went from $20,100 in 1968 to $93,100 in 1989, while the mean went from $22,300 in 1968 to $118,100 in 1989 (HUD 1996). Thus, the use of means is conservative in that it is more likely to show appreciation rates in line with FHA assumptions. 10 The reporting of U.S.-wide statistics is consistent with other studies that also rely on national data sets (e.g., Mayer and Simons 1994).
House Value Appreciation among Older Homeowners 209 The analysis is limited to single-family detached units. Unfortunately, data limitations make it impossible to assess the state of repair and housing conditions of the properties. This may be an important omission, since homes must be in good repair to qualify for the FHA program. Thus the analysis includes homes that, at the start, would not qualify for loans because of poor physical condition. Including these ineligible units in the analysis may bias the computed appreciation rates downward. Methodology House Value Appreciation The house value appreciation experienced by four separate cohorts of older homeowners is examined so that differences can be observed between cohorts entering the program at different points in the business and housing cycle. The four cohorts represent groups becoming eligible for the program at crucial points in the business and housing cycles: 1968, 1973, 1979, and 1983. The 1979 cohort is considered the worst case because that year marked the beginning of the 1979 82 recession, when consumer prices also rose to postwar highs. The cohort examination is limited to nonmoving households that did not experience a change in household head except when a wife became the head after the death of her husband. This examination is done for two groups of older homeowners. The first, called the 62+ group, consists of homeowners 62 years old or older who would be eligible for HECM participation. This group is included in the appreciation analysis. That is, the house value appreciation of the 1968 cohort of 62+ homeowners is examined over the 1968 89 period, that of the 1973 cohort over the 1973 89 period, that of the 1979 cohort over the 1979 89 period, and that of the 1983 cohort over the 1983 89 period. The appreciation rate experienced by each cohort is contrasted with the comparable rate estimated under the FHA assumptions. The second group, referred to as HRIP 71+, consists of housing-rich, income-poor homeowners 71 years old or older. It is also examined for the different cohort years. These oldest homeowners were considered housing rich if they owned homes valued above the 50th percentile; they were considered income poor if they had incomes below the 50th percentile. The HRIP 71+ group was chosen for a detailed examination because it resembles the participants of the HECM program, who tend to be old, to own highvalued homes, and to have low incomes. Again, the appreciation rate experienced by these homeowners is contrasted with the comparable rate estimated under the FHA assumptions. A word must be said about how the HRIP 71+ group of homeowners was selected. The determination of the potential demand for RMs is a topic heavily debated in the empirical literature (e.g., Mayer and Simons 1994; Merrill, Finkel, and Kutty 1994; Scholen 1993). There is agreement, however, that older homeowners with low incomes and substantial equity have the most to gain from participating in an RM program. On average, household wealth does not decrease significantly until homeowners reach age 71 (Mayer and Simons 1994, figure 1). This suggests that in the aggregate, homeowners 71 and older have the most to gain from accessing the wealth in their homes. The median equity and income are
210 Roberto G. Quercia used to determine whether a homeowner is housing rich and income poor partly because of considerations of sample size. More restrictive criteria were examined, but these resulted in samples too small for analysis. Ultimately, as mentioned above, the HRIP 71+ group was selected because it most resembles the actual RM borrowers in the FHA program. Dropout Rate The cohort size, the percentage of PSID older homeowners who continue to use the home as the principal residence, is estimated for each of the cohort years. The cohort size at the end of the study period is then compared with the size that could be expected under FHA assumptions. FHA assumes that one-third of older homeowners will drop out of the program (i.e., stop using the home as the principal residence for reasons other than death) before they turn 100 years of age. Because FHA has not provided expected annual dropout rates, 1.1 percent of the original FHA participants are assumed to drop out of the program every year, representing one-third of the sample over 28 years (from 62 to 100 years of age). Empirical Analysis Characteristics of the PSID Sample and HECM Participants The characteristics of older homeowners in PSID are compared with those of FHA borrowers and with those of older homeowners in the 1989 AHS in table 2. As expected, given the aging of the population, the median age of 1968 PSID 62+ homeowners is less than that of the 1989 AHS cohort. The median age of 77 years among the 1968 HRIP 71+ homeowners is close to that of FHA borrowers. For the most part, the PSID 62+ and AHS samples do not differ significantly from each other in other demographic variables, but they both differ from the FHA sample. Older homeowners in both the PSID 62+ and the AHS samples have higher incomes and own lower-valued homes than FHA borrowers. The 1989 AHS median property value is also significantly higher than the 1968 PSID 62+ value $65,944, in real 1990 dollars, compared with $35,000. This difference reflects the fact that house value appreciation significantly exceeded increases in the overall cost of living during the study period, which was the measure used to convert all 1968 figures. By definition, homeowners in the HRIP 71+ PSID subsample have higher-valued homes and lower incomes than those in the 62+ sample. Household composition in the AHS and FHA samples and the two PSID samples, 62+ and HRIP 71+, is also presented in table 2. Among all older homeowners 62 years old or older, more than one-quarter are females living alone, while about two-thirds live with others. In contrast, more than half the FHA borrowers are females living alone. Overall, the demographic characteristics of the FHA borrowers are closer to those in the 1968 HRIP 71+ PSID subsample than to those in the two general samples.
House Value Appreciation among Older Homeowners 211 Table 2. Characteristics of Older Homeowners: PSID, FHA, and AHS 1968 PSID AHS FHA Home- HRIP Borrowers owners 62+ 71+ (62+) (62+) Number in sample 519 43 2,520 Median age (years) 70.4 77.0 76.7 73 Median annual income (1990 $) 15,430 6,921 7,572 16,545 Household type (%) Female living alone 28.8 40.6 56.5 28.7 Male living alone 7.3 18.6 14.3 7.2 Living with others 63.8 40.6 29.2 64.1 Race (%) Nonminority 90.6 93.8 95.6 91.6 Minority 8.8 6.3 3.4 8.4 Median property value (1990 $) 35,000 54,783 103,000 65,944 Source: FHA and AHS statistics are from HUD (1992, exhibits 2-1 and 2-3). Note: Percentages for nonminority and minority homeowners do not always sum to 100 because race was not recorded for a number of older homeowners. It is interesting to note the differences in minority presence across the samples. Both the PSID 62+ and the AHS samples show a higher minority presence than the PSID 71+ and the FHA samples. In fact, the FHA sample has the lowest minority presence of all samples, 3.4 percent. Although this may suggest that the FHA program could be better targeted to reach more minority households, the PSID 71+ number suggests that the proportion of minority households that have the most to gain from participating in an RM program is lower than in the population as whole. The 62+ Group House Values. House values for the 1968, 1973, 1979, and 1983 cohorts, together with the values expected under FHA assumptions, are presented in table 3 and figure 1. (All values in figure 1 have been standardized to 1 for comparison.) Most values for individual cohort years are above the FHA line, indicating the appropriateness of the FHA assumption. Members of the 62+ group who owned their homes in 1968 experienced a 6.76 percent average appreciation over the study period; the standard deviation of this change is 5.81 percent. The comparable average appreciation figures are 7.61 percent for the 1973 cohort, 5.78 percent for the 1979 cohort, and 5.31 percent for the 1983 cohort, with
212 Roberto G. Quercia Table 3. House Value for 62+ Group ($), from PSID Data and under FHA Assumptions 1968 Cohort 1973 Cohort 1979 Cohort 1983 Cohort Year PSID FHA PSID FHA PSID FHA PSID FHA 1968 14,366 14,366 NA NA NA NA NA NA 1969 14,804 15,027 NA NA NA NA NA NA 1970 15,241 15,719 NA NA NA NA NA NA 1971 15,544 16,442 NA NA NA NA NA NA 1972 16,335 17,199 NA NA NA NA NA NA 1973 17,851 17,991 18,798 18,798 NA NA NA NA 1974 19,366 18,819 20,102 19,663 NA NA NA NA 1975 21,087 19,685 22,298 20,568 NA NA NA NA 1976 22,910 20,591 23,922 21,515 NA NA NA NA 1977 25,230 21,539 27,601 22,505 NA NA NA NA 1978 29,810 22,530 29,367 23,541 NA NA NA NA 1979 34,706 23,567 34,431 24,625 36,935 36,935 NA NA 1980 36,328 24,652 36,197 25,758 40,182 38,635 NA NA 1981 41,968 25,787 40,944 26,944 43,637 40,413 NA NA 1982 44,578 26,974 43,971 28,184 46,798 42,273 NA NA 1983 44,494 28,215 44,754 29,481 47,556 44,219 55,717 51,774 1984 45,303 29,514 46,368 30,838 50,661 46,255 57,846 54,157 1985 51,656 30,872 52,647 32,257 55,383 48,384 64,130 56,650 1986 52,087 32,293 53,529 33,742 55,344 50,611 65,023 59,257 1987 55,802 33,780 58,906 35,295 61,054 52,940 71,237 61,985 1988 58,409 35,335 61,158 36,920 63,654 55,377 74,344 64,838 1989 55,042 36,961 59,610 38,619 64,391 57,926 75,741 67,822 Annual change 6.76% 4.60% 7.61% 4.60% 5.78% 4.60% 5.31% 4.60% Standard deviation of annual change 5.81% NA 5.30% NA 3.57% NA 3.63% NA Note: NA = not applicable.
House Value Appreciation among Older Homeowners 213 Figure 1. Cohort House Value by Year, PSID Homeowners (62+) and FHA 0 5 10 15 20 Years FHA 1968 1973 1979 1983 4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 Value Index
214 Roberto G. Quercia standard deviations of 5.30, 3.57, and 3.63 percent, respectively. Statistically, the terminal value for each cohort is significantly higher than the corresponding FHA value. Cohort Sizes. The percentage of participants remaining in the program for each PSID cohort sample and under the FHA assumptions is presented in table 4 and figure 2. The actual dropout rates by cohort are significantly higher than the rates assumed in the FHA program. The 1968 cohort declined from 452 to 71 households, a dropout rate of 84 percent. This is much higher than the 22 percent assumed under the program. The dropout rates of the other three cohorts are also higher than assumed. The 1973 cohort declined from 546 to 173 households, a dropout rate of 68 percent, compared with an assumed decline of 17 percent. The 1979 cohort declined from 644 to 342 households, or 47 percent, compared with an assumed decline of 11 percent. The 1983 cohort declined from 650 to 440 households, or 32 percent, compared with an assumed decline of 6 percent. The HRIP 71+ Group House Values. The values of homes owned by the HRIP 71+ group, those who most resemble actual RM borrowers in the FHA program, are presented in table 5 and figure 3. These values are compared with what could have been expected under FHA assumptions. (All values in figure 3 have been standardized to 1 for comparison.) The pattern here is not as clear as that in figure 2. Earlier cohorts appear to have experienced appreciation rates in line with program assumptions. The 1968 cohort experienced a 3.48 percent appreciation. (The volatility in the line depicting values for the 1968 cohort is due to the rapid decline in cohort size over time. With declining cohort size, the loss of a small number of homeowners in a year can result in dramatic changes in average values.) Similarly, the 1973 cohort experienced a 4.43 percent appreciation. In contrast, the appreciation experienced by later cohorts is notably lower: 0.05 and 0.55 percent for the 1979 and 1983 cohorts, respectively. The standard deviations of the annual percent change are 29.96, 13.67, 20.68, and 7.13 percent for the 1968, 1973, 1979, and 1983 cohorts, respectively. Once these standard deviations are taken into consideration, none of the appreciation values is statistically different from the comparable FHA values, except for the values of the 1979 cohort, for which the appreciation rate is significantly lower than the FHA assumption. Cohort Sizes. As expected, table 6 shows that dropout rates among the HRIP 71+ group are greater than those among older homeowners in general, which in turn are much higher than those assumed in the FHA program. This is depicted graphically in figure 4. The 1968 cohort declined from 32 households to 1 household, or 97 percent, compared with the assumed 22 percent. The 1973 cohort declined from 48 to 6 households, or 88 percent, compared with the assumed 17 percent. The 1979 cohort declined from 19 to 5 households, or 74 percent, compared with the assumed 11 percent. The 1983 cohort declined from 21 to 9 households, or 57 percent, compared with the assumed 6 percent.
House Value Appreciation among Older Homeowners 215 Table 4. Percentage of Homeowners Remaining in Program for 62+ Group, from PSID Data and under FHA Assumptions 1968 Cohort 1973 Cohort 1979 Cohort 1983 Cohort Year PSID FHA PSID FHA PSID FHA PSID FHA 1968 100 100 NA NA NA NA NA NA 1969 89 99 NA NA NA NA NA NA 1970 78 98 NA NA NA NA NA NA 1971 72 97 NA NA NA NA NA NA 1972 67 96 NA NA NA NA NA NA 1973 66 95 100 100 NA NA NA NA 1974 62 94 96 99 NA NA NA NA 1975 57 93 91 98 NA NA NA NA 1976 53 91 84 97 NA NA NA NA 1977 49 90 77 96 NA NA NA NA 1978 46 89 74 95 NA NA NA NA 1979 43 88 70 94 100 100 NA NA 1980 38 87 65 93 94 99 NA NA 1981 36 86 62 91 87 98 NA NA 1982 34 85 57 90 84 97 NA NA 1983 32 84 55 89 80 96 100 100 1984 29 83 51 88 75 95 93 99 1985 25 82 45 87 69 94 86 98 1986 23 81 42 86 67 93 82 97 1987 21 80 39 85 62 91 78 96 1988 18 79 34 84 58 90 73 95 1989 16 78 32 83 53 89 70 94 Dropout rate 84 22 68 17 47 11 30 6 Note: NA = not applicable.
216 Roberto G. Quercia Figure 2. Cohort Size by Year, PSID Homeowners (62+) and FHA 0 5 10 15 20 Years FHA 1968 1973 1979 1983 100% 90% 80% 70% 60% 50% 40% Cohort Size 30% 20% 10% 0%
House Value Appreciation among Older Homeowners 217 Table 5. House Value for HRIP 71+ Group ($), from PSID Data and under FHA Assumptions 1968 Cohort 1973 Cohort 1979 Cohort 1983 Cohort Year PSID FHA PSID FHA PSID FHA PSID FHA 1968 21,631 21,340 NA NA NA NA NA NA 1969 20,605 22,322 NA NA NA NA NA NA 1970 20,802 23,350 NA NA NA NA NA NA 1971 21,580 24,424 NA NA NA NA NA NA 1972 19,608 25,549 NA NA NA NA NA NA 1973 24,100 26,725 25,486 25,486 NA NA NA NA 1974 28,591 27,955 25,180 26,659 NA NA NA NA 1975 21,302 29,241 22,129 27,886 NA NA NA NA 1976 30,366 30,587 25,151 29,170 NA NA NA NA 1977 24,961 31,995 27,880 30,512 NA NA NA NA 1978 33,484 33,468 33,254 31,917 NA NA NA NA 1979 32,700 35,008 33,333 33,386 42,761 43,569 NA NA 1980 43,285 36,620 38,974 34,922 33,524 45,574 NA NA 1981 49,271 38,305 39,420 36,530 34,317 47,672 NA NA 1982 37,885 40,068 42,500 38,211 43,307 49,866 NA NA 1983 40,008 41,912 45,879 39,970 38,551 52,162 65,309 65,309 1984 28,079 43,842 46,089 41,810 28,790 54,562 60,914 68,315 1985 18,667 45,860 47,196 43,734 36,044 57,074 63,413 71,459 1986 28,000 47,970 43,357 45,747 25,576 59,701 60,841 74,749 1987 47,500 50,178 53,400 47,853 21,699 62,449 69,755 78,189 1988 30,500 52,488 36,550 50,055 27,226 65,323 68,869 81,788 1989 18,000 54,904 44,157 52,359 32,400 68,330 66,516 85,552 Annual change 3.48% 4.60% 4.43% 4.60% 0.05% 4.60% 0.55% 4.60% Standard deviation of annual change 29.96% NA 13.67% NA 20.68% NA 7.13% NA Note: NA = not applicable.
218 Roberto G. Quercia Figure 3. Cohort House Value by Year, HRIP PSID Homeowners (71+) and FHA 0 5 10 15 20 Years FHA 1968 1973 1979 1983 3.0 2.5 2.0 1.5 1.0 0.5 0.0 Value Index
House Value Appreciation among Older Homeowners 219 Table 6. Percentage of Homeowners Remaining in Program for HRIP 71+ Group, from PSID Data and under FHA Assumptions 1968 Cohort 1973 Cohort 1979 Cohort 1983 Cohort Year PSID FHA PSID FHA PSID FHA PSID FHA 1968 100 100 NA NA NA NA NA NA 1969 91 99 NA NA NA NA NA NA 1970 81 98 NA NA NA NA NA NA 1971 81 97 NA NA NA NA NA NA 1972 72 96 NA NA NA NA NA NA 1973 63 95 100 100 NA NA NA NA 1974 56 94 85 99 NA NA NA NA 1975 47 93 67 98 NA NA NA NA 1976 34 91 63 97 NA NA NA NA 1977 31 90 52 96 NA NA NA NA 1978 22 89 44 95 NA NA NA NA 1979 19 88 40 94 100 100 NA NA 1980 16 87 31 93 79 99 NA NA 1981 13 86 29 91 74 98 NA NA 1982 9 85 25 90 68 97 NA NA 1983 9 84 23 89 63 96 100 100 1984 9 83 23 88 63 95 90 99 1985 9 82 21 87 58 94 71 98 1986 6 81 15 86 53 93 71 97 1987 6 80 10 85 42 91 62 96 1988 6 79 10 84 26 90 52 95 1989 3 78 10 83 26 89 47 94 Dropout rate 97 22 90 17 74 11 53 6 Note: NA = not applicable.
220 Roberto G. Quercia Figure 4. Cohort Size by Year, HRIP PSID Homeowners (71+) and FHA 0 5 10 15 20 Years FHA 1968 1973 1979 1983 100% 90% 80% 70% 60% 50% 40% Cohort Size 30% 20% 10% 0%
House Value Appreciation among Older Homeowners 221 Summing Up In this study, the house value appreciation experienced by older homeowners was examined for the 1968 89 period. This appreciation was then compared with the appreciation assumption in one major RM program, FHA s program. For older homeowners eligible to participate in the FHA program, those 62 years old or older, the annual house value appreciation is consistent with the FHA assumption. Although appropriate for older homeowners in general, the FHA value appreciation assumption may not be appropriate for many housing-rich, income-poor homeowners over age 71, those most likely to participate in the FHA program. Specifically, the assumption does not seem to be appropriate to describe the appreciation experience of the 1979 cohort, perhaps because that cohort represents the worst-case scenario. House value appreciation peaked in 1979 and declined afterward. From this perspective, the unique circumstances of the late 1970s may explain why that cohort s appreciation is below expectations. Another possibility is that the 1979 cohort may be the first in a line of cohorts with appreciation below expectations. Poterba (1991) found that real house values have actually declined in many housing submarkets since the late 1970s. From this perspective, the appreciation experience of the 1979 cohort may not be unique but may reflect a trend that has characterized some submarkets since the late 1970s. It is not possible to assess whether the experience of the 1983 cohort is in line with this contention, because the 1983 cohort is the one with the smallest number of observation years (five years). The long-term appreciation experience for the 1983 cohort may be different from its shortterm experience. This is an area where additional research is needed. The dropout rate assumption in the FHA program was examined also. The findings indicate that dropout rates may be higher than assumed by FHA. The assumption of low dropout rates in the FHA program may have a twofold impact. On the one hand, the use of a dropout rate lower than actually occurs limits the amount of home equity that program participants can access. Using a more realistic dropout rate would increase the maximum loan size and thus the amount of equity that can be accessed. On the other hand, the use of a higher dropout rate may jeopardize the long-term viability of the program, because the use of a lower dropout rate could compensate for lower-thanassumed house value appreciation. This conclusion, however, must be qualified. An RM initiative, such as the FHA program, may itself lower the expected dropout rate if it gives older homeowners the resources to afford to live in their homes longer before they have to move. This effect was not taken into consideration when the PSID dropout rates were estimated. The effect of program implementation on dropout rates is an area where future research is needed. In the long run, all key assumptions in an RM program are likely to be revised as new research becomes available. For instance, on the basis of prior research supporting the GBM assumption, value appreciation can be expected to follow historical trends. Under this scenario, the FHA program can be expected to remain viable. On the basis of this and other recent work, however, house value appreciation may be lower than historical trends would suggest, particularly if the houses owned by the oldest housing-rich, income-poor
222 Roberto G. Quercia homeowners represent a distinct submarket. Under this scenario, the FHA program may have to be revised to remain viable. Similarly, the contention that older homeowners are unwilling to decrease home equity by any means must be reconciled with the fact that they may access home equity by omitting necessary maintenance and repairs over time. Such behavior is likely to affect the potential demand for RMs as well as the long-term viability of an RM program that assumes that older homeowners will maintain their homes in good repair after obtaining RM loans. Ultimately, only additional research is likely to settle all these issues. Obviously, the accuracy of the house value appreciation assumption will be affected by the long-term accuracy of all other assumptions in the program. For instance, the 1994 evaluation of the FHA program indicates that the program would remain viable with a 3 percent annual appreciation, instead of the 4 percent originally thought necessary. The risk is reduced because almost half the properties in the program have values above FHA s Section 203(b) limits, making it less likely that home equity will be insufficient to repay loans when they come due. Moreover, interest rate declines during the 1992 95 period helped keep interest accruals down. As long as interest rates remain lower than originally expected, the program may remain viable in spite of lower-than-expected appreciation rates. However, the advantageous circumstances that have allowed the FHA program to remain viable under conditions other than those assumed may not continue in the future. For instance, for homeowners who own homes valued above the FHA limits, the recently introduced Fannie Mae Home Keeper program offers the opportunity to access more equity than the FHA program does. These households may be better off with an RM from the Fannie Mae program, but the selected withdrawal of these households from the FHA program could well damage its viability. This is an area for future research. In addition, although interest rates continue to remain low in relative terms, they have been inching up, and it is unclear whether they will remain low in the long term. References Case, Bradford, and Ann B. Schnare. 1994. Preliminary Evaluation of the HECM Reverse Mortgage Program. AREUEA Journal 22(2):301 46. Case, Karl E., and Robert J. Shiller. 1989. The Efficiency of the Market for Single-Family Homes. American Economic Review 79(1):125 37. Fannie Mae. 1996. Money from Home: A Consumer s Guide to Reverse Mortgage Options. Washington, DC. Gau, George W. 1984. Weak Form Tests of the Efficiency of Real Estate Investment Markets. Financial Review 19(4):301 20. Gau, George W. 1985. Public Information and Abnormal Returns in Real Estate Investment. AREUEA Journal 13(1):15 31. Guttentag, Jack M. 1975. Creating New Financial Instruments for the Aged. New York: New York University, Graduate School of Business Administration, Center for the Study of Financial Institutions.
House Value Appreciation among Older Homeowners 223 Hughes, James W., and George Sternlieb. 1987. The Dynamics of America s Housing. New Brunswick, NJ: Rutgers University, Center for Urban Policy Research. Jacobs, Bruce. 1988. Moveout Rates of Potential Reverse Mortgage Borrowers: Some Initial Estimates. Unpublished paper. University of Rochester. Linneman, Peter. 1986. An Empirical Test of the Efficiency of the Housing Market. Journal of Urban Economics 20(3):140 54. Mankiw, N. Gregory, and David N. Weil. 1989. The Baby Boom, the Baby Bust, and the Housing Market. Regional Science and Urban Economics 19:259 80. Mayer, Christopher J., and Katerina Simons. 1994. Reverse Mortgages and the Liquidity of Housing Wealth. AREUEA Journal 22(2):235 55. Merrill, Sally R., Meryl Finkel, and Nandinee K. Kutty. 1994. Potential Beneficiaries from Reverse Mortgage Products for the Elderly. AREUEA Journal 22(2):257 99. Pitkin, John R., and Dowell Myers. 1994. The Specification of Demographic Effects on Housing Demand: Avoiding the Age-Cohort Fallacy. Journal of Housing Economics 3(3):240 50. Poterba, James M. 1991. House Price Dynamics: The Role of Tax Policy and Demography. Brookings Papers on Economic Activity 2:143 203. Quercia, Roberto G., and William M. Rohe. 1992. Housing Adjustment among Older Homeowners. Urban Affairs Quarterly 28(1):104 25. Scholen, Ken. 1993. Consumer Response to Reverse Mortgages. Paper presented at Fannie Mae Roundtable Discussion on Reverse Mortgages, Washington, DC. Szymanoski, Edward J., Jr. 1990. The FHA Home Equity Conversion Mortgage Insurance Demonstration: A Model to Calculate Borrower Payments and Insurance Risk. Washington, DC: U.S. Department of Housing and Urban Development. Szymanoski, Edward J., Jr. 1994. Risk and the Home Equity Conversion Mortgage. AREUEA Journal 22(2):347 66. U.S. Bureau of the Census. 1973. Statistical Abstract of the United States, 1973. Washington, DC: U.S. Government Printing Office. U.S. Department of Housing and Urban Development. 1992. Preliminary Evaluation of the Home Equity Conversion Mortgage Insurance Demonstration. Washington, DC. U.S. Department of Housing and Urban Development. 1996. U.S. Housing Market Conditions: 1st Quarter 1996. Washington, DC. U.S. Public Health Service. 1985. U.S. Decennial Life Tables for 1979 81. Vol. 1, No. 1, U.S. Life Tables. Washington, DC: U.S. Government Printing Office. Venti, Steven F., and David A. Wise. 1990. But They Don t Want to Reduce Housing Equity. In Issues in the Economics of Aging, ed. David A. Wise, 13 29. Chicago: University of Chicago Press.
224 Roberto G. Quercia