Housing Finance and Tax Reform Can Expand Affordable Rental Options

by Bill Apgar
Senior Scholar

Today, when more than one in three American households live in rental housing, ongoing erosion in renter incomes combined with ever rising rents has pushed the number of renter households paying excessive shares of income for housing to record levels.  Unfortunately, efforts to expand the supply of affordable rental housing remain mired in congressional wrangling over budget deficits and failure to reach consensus over how best to reform the nation’s housing finance sector. Although proposed changes to the single-family mortgage sector have captured most of the headlines, equally important reforms are now being discussed that will fundamentally alter the regulation of multifamily housing finance, including the operations of the Federal Housing Administration (FHA) and the government-sponsored enterprises (GSEs), as well as tax and subsidy mechanisms to expand affordable rental housing options through the Low Income Housing Tax Credit (LIHTC), public housing, and rental assistance programs.

As I discussed in my recent research brief, The Changing Landscape for Multifamily Finance, tax reform can play an important role in balancing the national budget and reducing the national debt. But in seeking to create a path forward, Congress should be careful not to short circuit tax expenditures that reduce the cost of capital for multifamily rental production and that enable developers to offer units at rents affordable to lower-income households. As one of the nation’s largest corporate tax expenditures, however, LIHTC is vulnerable to elimination or substantial cuts to help pay for lower corporate tax rates or any one of several deficit-reduction proposals now under consideration.

Supporters argue that LIHTC is a premier example of a successful public-private partnership. When combined with housing vouchers or other forms of rental assistance, the tax credit plays an important role in providing decent housing that is affordable to the nation’s poor. Opponents, however, counter that LIHTC’s complex rules scare away many financially-motivated private developers.  Moreover, critics contend that all too often LIHTC’s benefits go to moderate-income, as opposed to the nation’s lowest income, renters.

To improve the program’s ability to assist a broader range of renters, it is important to expand the ability of developers to combine LIHTC resources with housing vouchers or other tenant-based subsidies.  Currently, LIHTC requires developers to meet one of two standards: either 20 percent of units must be rent-restricted and occupied by tenants with incomes less than 50 percent of area median income (AMI).  Alternatively, at least 40 percent must be rent-restricted and occupied by tenants with incomes less than 60 percent of AMI. For this purpose, “rent-restricted” means that the tenant pays no more than 30 percent of their monthly income on rent. 

In practice, these criteria have led to multifamily housing developments that serve a very narrow band of tenants with incomes falling between 40 and 60 percent of AMI.  One proposal to extend the reach of the LIHTC program to serve more of the nation’s lowest income renters would require LIHTC developments to serve a larger share of households with incomes less than 40 percent of AMI while limiting the number of residents earning more than of 80 percent of AMI living in LITHC developments.  Another would award additional project-based housing vouchers to developments that have at least 30 percent of units occupied by tenants with incomes of less than 30 percent of AMI.  

Similarly, efforts to reform FHA and the housing GSEs must link access to government guarantees to requirements that a substantial portion (say, 60 percent) of the total rental housing units in developments are affordable to households earning 80 percent or less of AMI.   Such proposals would encourage developers to more aggressively search out available rental assistance options, and in doing so widen the income band of residents able to affordably live in LIHTC and other rental housing developments. Mixed-income buildings that offer rental housing options serving a broad range of incomes are especially important in low income communities that are being revitalized and/or are located in sparsely populated areas. These proposals could be structured to be revenue neutral, but would be enhanced by increasing the funding for housing vouchers and other rental assistance efforts

In another recent effort to harness private capital to expand the supply of affordable housing, HUD’s Rental Assistance Demonstration (RAD) program was designed to stem the loss of public housing and certain other at-risk, federally assisted properties. The program allows owners to pledge a portion of cash flow derived from existing long-term, project-based Section 8 contracts as collateral to support public and private lending to make much-needed improvements. At a time when the backlog of public housing repairs stands at $25.6 billion and other federally assisted properties have yet to recover fully from the Great Recession, RAD helps both public and private owners of multifamily housing address critical rehabilitation needs by borrowing against their future income streams on the private market. 

Market fundamentals suggest that the multifamily finance sector should remain strong in the near term. Coordination of rules governing utilization of existing long-term, project-based Section 8 contracts with ongoing GSE and tax policy reform efforts could unleash private sector expertise to serve broader segments of today’s renters. This would help turn the energy of the multifamily finance sector toward reducing the rental cost burdens that undermine the well-being of millions of US households. 

A Disappointing Report on Recent Household Growth Leads to More Questions than Answers

by Dan McCue
Research Manager

Although household growth is the major driver of housing demand, getting an accurate picture of recent trends in this measure is difficult, especially when Census surveys show conflicting trends.   On January 31, the most recent Housing Vacancy Survey (HVS) was released with Q4 numbers and some annual data for 2013.  As one of the few surveys that provide timely measures of household growth, the release was much anticipated in hopes that it would shed more light on trends of a recovery seen elsewhere in the housing market, but the results were disappointing, if not somewhat confusing. 

In its recent release, the HVS reported annual household growth of just 448,800 in 2013.  This represents a 48 percent drop in household growth relative to that from 2012 and marked the lowest annual household growth measure since 2008, in the depths of the Great Recession (Figure 1).

Source: US Census Bureau, Housing Vacancy Survey

In September we noted that the HVS was showing a disconcerting slowdown in household growth after finally having picked up in 2012.  With the annual number now in, this low measure of household growth in the HVS is puzzling, at odds with an assortment of other housing market indicators that have been painting a more positive picture for housing overall.  In particular, the drop in household growth did not mesh with several other trends:

• The much higher 1.375 million annual growth reported in the 2013 Current Population Survey Annual Social and Economic Supplement (CPS/ASEC);
• The same, steady increase in jobs in 2013 as during the previous year; and
• Increased momentum in the housing market, including a further decline in vacancy rates, an increase in new home sales, and an increase in housing construction during the year.

The divergent measure of household growth from the HVS is also troubling because while the HVS is known to have a downward bias in its estimated count of households, it has been useful in tracking short-term trends in that it provides more timely estimates than other sources and has generally been subject to less sampling error.  Indeed, while the CPS/ASEC and HVS both originate from monthly CPS surveys, the HVS annual household growth number is a 12-month rolling average of year over year growth, whereas annual growth in the CPS/ASEC is year over year growth for the single March survey, making it more volatile and less reflective of trends throughout the entire year.

But this is not the only—or most important—source of difference between HVS and CPS/ASEC household counts.  These two surveys differ more fundamentally in that CPS/ASEC arrives at its estimate of households based on weights derived from estimates of the total population and the share who are heads of household, while the HVS estimates households using weights that add up to estimates of the total housing units in the country, with the household count derived as the number of housing units that are not vacant (see Note on Table 3).  During census years, the CPS/ASEC head-counting method has generally produced totals much closer to the decennial Census –the Census Bureau’s benchmark survey of people and housing--while the HVS stock-controlled method has generally produced estimates that are lower by around 3-4 million households. This suggests the HVS household estimates are generally biased lower to begin with.

With its household estimates pinned to estimates of the housing stock, the surprisingly low HVS household growth estimate may be at least in part due to overly low estimates of growth in the total housing stock.  As shown in Figure 2, over the past few years, the total housing stock estimate used by the HVS has been growing slowly and very steadily since 2011, gaining around 350,000 units a year.  At the same time the Census Bureau’s New Residential Construction surveys show a significant upturn in the number of new housing units completed in 2012 and 2013, reaching 762,000 units.  In order for the HVS estimates of changes in the housing stock to be accurate, this would suggest a surge in demolitions that roughly offset the recent surge in new construction, which seems unlikely. 

Source: JCHS tabulations of US Census Bureau, Housing Vacancy Survey and New Residential Construction data.

There is a third census survey from which household growth can be measured, the American Community Survey (ACS), that might shed more light on the recent trend. The ACS is not as timely, however, and the results for 2013 are not due to be released until late 2014.  Still, for 2012 the ACS reported household growth levels in between the HVS and CPS counts (978,000), suggesting it might prove a moderate and viable tie-breaker between the other two surveys on the direction of the recent trend. But since the ACS household estimates are linked to the same housing stock estimates as the HVS chances are the ACS, too, will be subject to a downward bias.

Overall, the discrepancies in these surveys are troubling given the importance of household growth as an indicator of the health of the economy and the housing market.  For the time being, housing analysts are flying in the dark on this key metric.

Although the Population is Rapidly Aging, Young Adults Will Still Drive the Demand for New Housing

by George Masnick
Fellow

Hardly a day goes by when we are not reminded about how rapidly our population will age over the next several decades as the baby boom crosses the 65+ threshold.  For housing analysts, an aging population is often thought of as the key demographic trend that will drive housing consumption over the next 20 years.  This shift in age structure does not, however, mean that elderly population growth will be the primary driver of the demand for newly built housing.  While most of the population growth will take place among the elderly, that increase, for the most part, does not represent people active in the housing market. Younger age groups will not experience much population growth, but this is because, among those under 35, large cohorts are replacing other large cohorts – sometimes a bit smaller and sometimes a bit bigger.  But most of the members of these large younger cohorts will enter the housing market for the first time in their 20s and 30s.  They will consume most of the newly built housing.  Here are the details.

The aging of the United States population is dramatically shown in Figure 1.  Between 1970 and 2010, most adult population growth took place in the under 65 age groups.  Starting in 2010, aging baby boomers begin to shift most of the population growth to the over 65 age groups.  Each decade during the past 40 years (the leading edge of the baby boom, those born 1946-1955) has provided the biggest share of population growth of any 10-year age group (lower panel of Table 1 cells highlighted in yellow).  In the 1970s, baby boomers created growth among young adults, gradually shifting the growth to older and older age groups in successive decades.  The dominance of baby boomers in the population growth equation will persist until sometime after 2030 when they begin to reach the end of their lives in large numbers.

Source: Decennial Census data and Census Bureau 2012 Middle Series Population Projections.

Notes: Shaded cells represent largest 10-year cohort in each decade (green) and largest growth (yellow).
Source: Decennial Census counts and 2012 Census Bureau middle series population projections.

Many are quick to conclude that, since population growth drives most of the demand for new housing construction, we must primarily build for the elderly.  The problem with this logic is that elderly population growth does not represent new additions to the population, and most elderly are already housed quite comfortably and show little inclination to move to a different residence. Strong elderly population growth is simply the aging of a large cohort replacing the smaller cohort that came before them - they are not new people entering the housing market.  As I’ve discussed in a previous post, for the remainder of this decade and the next, elderly baby boomers will largely age in place.  Fewer than 4 percent of the population over the age of 65 changed residence in 2012-13.  Over 80 percent of the elderly live in owner-occupied housing.  For those 65+ living in owner-occupied housing, the annual mobility rate is now about 2 percent.

Source: 2013 Current Population Survey, Table 7.

As I mentioned earlier, movers can be thought of as driving the demand for new housing since non-movers by definition stay in their current homes.  While the number of people over age 65 is growing rapidly, given the very low mobility rates of this population the number of movers that are elderly will still be small.  Multiplying the average size of each 10-year age group of adults (upper panel of Table 1) by the average percentage who change residence each year will give the annual number or persons in each age group that are expected to move over the decade.  In the 2000-2010 decade, these movers, or recent occupants, were clearly dominated by young adults age 25-34 (Figure 3).  This cohort does not have the largest population; it is about 5 million less in number compared to the baby boomers age 45-54 in 2010 (upper panel of Table 1). But at over 40 million, its size is substantial.  Having the highest rate of geographic mobility, 25-34 year olds accounted for almost three times as many recent occupants during the 2000-2010 decade as the largest baby boom cohort.  Each year during that decade, persons over the age of 65 averaged only 6.2 percent of total moves (8.5 percent in 2013).  Such low representation of the elderly among movers will persist for the foreseeable future. That share is projected to increase only slightly during the next two decades to an average of about 10 percent in 2020-2030 in spite of the large projected growth in the 65+ population.  Note that these projections likely bias upward the estimates of demand for new market housing by the elderly because the resident population used as a base in the projections include the elderly living in nursing homes and prisons.

Notes: Recent Occupancy numbers = average number of persons in age group during decade x average annual age-specific annual mobility rate.  Number of persons is average of numbers at beginning and end of decade.  Average annual mobility rate is the mean of the age-specific rates at the beginning and end of decade. Projections hold mobility rates constant at 2013 levels.

Source: see Table 1 and Figure 2.

In keeping with their lower mobility rates, older adults are underrepresented in newly built housing.  Households over the age of 65 in 2011 accounted for 22.1 percent of all households, but just 14.4 percent of occupants of units built since 2000 (Figure 4).  Among all owner heads of households, 26.9 percent were over the age of 65, but just 14.7 percent were heads in owner units built since 2000.  However, older households do account for a larger share of heads of households living in new rental units: 13.4 percent of renter heads are elderly, nearly equal to their 13.6 percent share of occupied rental units built since 2000.  This greater parity in representation of the elderly in newer rental units is consistent with the higher mobility rates of older renters compared to older owners.

                                                          

Source: Joint Center tabulations of 2011 American Housing Survey.

As the large baby boom cohorts age into the 65+ age groups, will they increase the share of elderly who live in newer housing?  An increase proportional to their growing share of the adult population (adjusted for their lower mobility rates) is certainly expected.  For example, according to recent Joint Center household projections, the elderly accounted for 23.3 percent of all households in 2014, increasing to 26.4 percent in 2020 and to 31.5 percent in 2030 when all baby boomers are over the age of 65.  If the elderly maintain their share of households living in newer units at current levels, about 20 percent of newly built units in 2030 will be occupied by heads over the age of 65.  But to increase the share of newly built housing occupied by the elderly significantly above that figure, tomorrow’s elderly will need to relocate out of older housing at higher rates than we now observe. 

For the next 15+ years, helping the elderly achieve a better fit with their housing will largely involve initiatives to support aging in place. The need for assisted living facilities and nursing homes will gradually increase as the baby boom ages, but the greatest increases will take place after 2030. Whether the elderly are likely to increase their mobility rates within market housing in the near-term future is worth considering.  Public and private efforts to provide housing that better serves the needs of an aging population could spur greater mobility among those ages 65+.  However, there are a host of demographic, social and economic characteristics of baby boomers that argue for less, not more, geographic mobility among the next generation of elderly. This topic will be the subject of a future blog post.   

Energy Cost Burdens in Rental Housing

by Michael Carliner
Fellow

The recent Joint Center report, America's Rental Housing: Evolving Markets and Needs, reiterates the extent of severe cost burdens faced by renters, especially those with low incomes.  A research brief I prepared in connection with the report documents the large share of the cost of rental housing attributable to the cost of energy, particularly for low-income renters.

Among renters who pay for all utilities, payments for energy represented a median of 13 percent of gross rents (rent plus utilities).  Energy expenses are nearly as high for low-income renters as for high-income renters, and consequently account for larger share of gross rents and of incomes for those with low incomes. Median monthly energy expense for those paying all utilities in 2011 was $116 for those with annual incomes of less than $15,000, compared to $151 for renter households with incomes over $75,000 (Figure 1).  This partly reflects the fact that energy use is a necessity, but it is also due to lower energy efficiency in the housing occupied by low-income renters.

(Click chart to enlarge)

Values shown for income, expenses, and energy use are medians
Source: American Housing Survey 2011

About a quarter of renters have some or all of their utilities included in their rent. For those renters, the cost of energy may not be visible, but it represents a major component of the operating cost for their housing, and tenants ultimately pay that cost with their rents.  Even where renters pay directly for energy used within their individual units, energy costs for common areas and facilities are a substantial component of the operating cost for the property and are reflected in rents. Among all multifamily rental properties, payments for energy by property owners represent about 9 percent of rent receipts.

Rental housing generally uses more energy, relative to living area, than owner-occupied housing. Newer homes are generally more energy-efficient than older ones.  Energy use per square foot is particularly high among the nearly 7 million multifamily rentals built before 1960 (Figure 2).  There has been substantial investment in older owner-occupied housing over the years to improve efficiency, but not as much for multifamily rentals.  Older single-family rentals, many of which were owner-occupied in the past, use less energy per square foot than older multifamily rentals, but still use more energy per square foot than owner-occupied single-family homes.

Data in thousands of BTUs
Source: DOE Energy Information Administration, 2009 Residential Energy Consumption Survey

For the majority of renters who directly pay for the energy used in their homes, the amount used reflects the quality of insulation in the structures and on the efficiency of the equipment. Efficiency depends on investments made by the owners of the properties, who may not be motivated to invest in efficiency improvements if they don't pay the bills for usage.  This separation between investment decisions and usage costs has been described as a "split incentive" situation and is a central issue in renters' energy costs. Another type of split incentive arises when the owner pays the bills but the tenant controls the temperature and the lights.

My research brief discusses several policy options for overcoming the split incentive problem where the tenants pay for utilities.  These include regulations mandating energy efficiency and subsidies for investments in efficiency.  The most promising approach, however, may be to make energy efficiency more transparent, so that renters can easily anticipate energy cost in choosing where to live.  If that makes occupancy rates and rental income more dependent on efficiency, property owners would have a greater incentive to invest in efficiency.  Several localities have recently established requirements for benchmarking and disclosing energy expenses in rental properties, providing a test of whether that will lead to an easing of renters' energy cost burdens.

Split incentive problems are not the only source of energy inefficiency and excessive energy cost burdens in rental housing.  The research reported in the brief, and earlier research cited there, indicates that in rental properties with utilities included in the rent, where the owner has a greater incentive to invest in efficiency, insulation quality and equipment efficiency is not consistently better than in rentals where the tenant pays for utilities, once variables such as regional climate and age of the structure are accounted for.  Whether or not utilities are included in the rent, rental housing does not generally include efficiency characteristics comparable to owner-occupied housing.  Other factors are evidently also involved.  The paper suggests, for example, that the financial resources of rental property owners may be a constraint.  Moreover, government programs such as the DOE Weatherization Assistance Program are designed in such a way that assistance goes primarily to owner-occupied housing, even though the low-income households that are the intended beneficiaries are mostly renters.

Double Digit Growth in Remodeling Spending Expected Through Mid-Year

by Abbe Will
Research Analyst

The home remodeling market should see strong growth in 2014, according to our latest Leading Indicator of Remodeling Activity (LIRA).  The double-digit gains in annual home improvement spending projected for the first half of the year should moderate some to just under 10 percent by the third quarter.

The ongoing growth that we’ve seen in home prices, housing starts, and existing home sales is also being reflected in home improvement activity. As owners gain more confidence in the housing market, they are likely to undertake home improvements that they have deferred.  However, the strong growth for this cycle may start to ebb a bit beginning around midyear.  By that time, we’ll be approaching the pre-recessionary levels of spending, and with borrowing costs starting to creep back up, growth rates are likely to slow some.  (Click chart to enlarge.)

For more information about the LIRA, including how it is calculated, visit the Joint Center website.