There are indications of a housing affordability problem in the United States.

As in the past, exclusionary zoning appears to be having a significant negative effect on housing affordability. There appears, however, to be a greater emerging threat. The rapid adoption of exclusionary planning policies, through smart growth, already appears to be severely impacting affordability and has great potential to do much more to make housing less affordable. At the same time, smart growth does not appear to have compensating benefits for eligible recipients of housing assistance or for housing assistance programs in general.

This report reviews broad economic indicators of housing affordability and the impact of exclusionary policies on housing affordability (exclusionary zoning and smart growth).

The findings are summarized below (Table ES-1).

Indicators of Housing Affordability

Finding 2.1: Lowest quintile incomes continue to rise at a slower rate than average, but the rate of increase has improved substantially in recent years.

Historically, incomes of the lowest quintile households tend to rise at a rate less than average. By far the strongest lowest quintile income increases in recent years have been registered since the enactment of welfare reform, as income levels for the lowest quintile rose at more than double the rate of any similar period since 1980.

Finding 2.2: The actual demand for housing subsidies is not known due to discrepancies among federal income and expenditure reporting systems.

Generally, households that must spend more than 30 percent of their income on rent are eligible for federal housing assistance. But, because there are widely varying indicators of income, the extent of the housing assistance need cannot be definitively known. The Bureau of Labor Statistics (BLS) Consumer Expenditure Survey indicates that lowest income quintile households spend 2.3 times their income and that expenditures exceed income in quintiles two and three. The Bureau of the Census, based upon the Current Population Survey (CPS), estimates lowest quintile incomes somewhat higher, but still well below the expenditure level reported by BLS (expenditures are 1.7 times CPS income). It seems implausible that low-income households are spending 1.7 times their income every year.

Most housing assistance demand estimates use CPS figures. If, for example, the BLS expenditure estimate is a more accurate indicator of average household income, then the extent of the housing affordability problem would be considerably less.

Finding 2.3: Home ownership is generally increasing, and increasing most rapidly among minority households.

During the 1990s, the nation enjoyed the most widespread gains in home ownership since the 1950s, and now stands at a record level. At the same time, minority home ownership has been rising at three times the rate of White-Non-Hispanics.

Finding 2.4: Owner occupied housing affordability has declined somewhat over the past decade. However, housing affordability has dropped significantly in some states and metropolitan areas.

House values rose 20 percent relative to income in the 1990s. In some states and metropolitan areas, affordability increased substantially. However, in others there was a serious decline. The least affordable areas are all in California, the Boston area, the New York metropolitan area and Portland, Oregon, where the median income household cannot afford more than one-half of the homes.

Finding 2.5: Rents have remained comparatively constant in relation to low-income household income in the last decade.

There is some variation in the experience with rental costs relative to income. Some measures indicate slight declines in affordability, while others indicate slight improvements. Most measures, however, indicate that a slight improvement in affordability in the last five years.

Finding 2.6: There are indications of a shortage of affordable housing units, especially in particular geographical areas.

Rental vacancy rates have fallen slightly at the national level over the past decade. However, there have been sharp drops in vacancy rates in a number of metropolitan areas. Vacancy rates are especially low in California and in the New York and Boston metropolitan areas, the same areas that exhibit some of the most severe owner occupant housing affordability problems.

Finding 2.7: The indicators outlined above do not indicate a significant nation-wide housing affordability problem. However, there are indications of serious problems in some areas.

The broad indicators of affordability indicate a somewhat mixed situation. Incomes are rising and rents are generally stable. Moreover, it is possible that, due to income reporting discrepancies, the extent of unmet housing assistance need may be less than previously estimated. On the other hand, vacancy rates have fallen significantly in some areas, likely indicating a shortage of rental units, while housing affordability has remains low in some areas and has declined sharply in others.

Barriers to Housing Affordability

Exclusionary zoning and growth controls were cited in the early 1990s Kemp Commission report as significant barriers to housing affordability. Exclusionary zoning remains so, but growth controls, in the form of so-called “smart growth” policies that ration development and land, have emerged as a more serious threat, due to their broad and rapid adoption.

Smart growth has arisen as a reaction to urban sprawl, the spatial expansion of US urban areas that has occurred since World War II, as urban populations have increased (and urban population densities have declined). What is not understood by many US observers, however, is that urban sprawl is occurring virtually everywhere that affluence is rising, and that the relative rate of sprawl (density reduction) is actually greater in Europe, Asia, Canada and Australia, than it has been in the United States.

Finding 3.1: As noted in the Kemp Commission report, exclusionary zoning continues to limit housing.

Exclusionary zoning, the practice of limiting entry into local housing markets by lower income and particular ethnic populations continues to be a barrier to housing affordability. This can be accomplished by requiring lower densities than the market would produce or even by outrightly prohibiting low-income housing such as apartment units. One frequently occurring practice is the prohibition on lower cost housing types, such as manufactured housing and modular housing. Some of the most notable exclusionary zoning problems are in the Boston and New York metropolitan areas, which are among the nation’s least affordable markets.

Finding 3.22: Smart growth’s development impact fee strategy reduces housing affordability.

The smart growth exclusionary planning strategy of development impact fees creates substantial barriers to housing affordability and impose disproportionate costs on low-income households.

Many communities have implemented development impact fees, which are assessed on new single family and multiple unit residences to finance new infrastructure. This practice has replaced reliance on general taxation and bonding, which was the historical approach to infrastructure finance. While there are arguments for making development “pay for itself,” this particular strategy has increased the cost of housing in areas where it is used. A University of Chicago study found that, in the Chicago area, development impact fees increased the cost of all housing, not just the cost of new housing. In the San Francisco Bay area, development impact fees reach nearly $65,000 per new owner occupied unit, and more than $40,000 for rental units. In one community development impact fees are equal to $0.62 per $1.00 of rental unit construction value. Development impact fees ration both owner occupied and multiple unit housing, thereby raising prices and impairing affordability. The impact on affordable housing is regressive, since development impact fees are the same, regardless of the value of unit being constructed.

Finding 3.23:  Smart growth’s land rationing, especially urban growth boundaries reduces housing affordability.

Consistent with economic theory, rationing land, especially through the smart growth exclusionary planning strategy of urban growth boundaries, increases housing costs and reduces affordability. Because lower income households are more financially vulnerable, they shoulder a disproportionately greater share of the burden.

A number of areas have adopted “smart growth” strategies that ration the amount of land available for development. Examples are urban growth boundaries, down zoning, and other strategies that artificially reduce the amount of land available for development. This has had the effect of reducing competition, thereby increasing the cost of the factors of production, limiting housing supply and reducing affordability. A case in point is the Portland (Oregon) area, where the National Association of Homebuilders Housing Opportunity Index has declined 44.5 percent (percentage of homes in the area affordable to the median income household) in the last 10 years. Portland had by far the steepest affordability drop among major metropolitan areas. Similarly, Bureau of the Census data indicates that Oregon, with its statewide exclusionary planning (smart growth) laws, led the nation from 1990 to 2000 in both housing value escalation and the increase of housing values relative to incomes (both by a wide margin). The upward cost pressures of land rationing on the single family housing market also tend to increase rents, increasing housing burdens for both recipients of housing assistance and those eligible for whom there is insufficient public funding for finance.

Finding 3.24: Smart growth is associated with lower overall lower home ownership rates and lower Black home ownership rates.

Lower overall home ownership rates and lower Black home ownership rates are associated with areas more consistent with the higher densities that smart growth requires.

A fundamental requirement of smart growth is higher population densities. Yet, higher population densities are associated with lower levels of home ownership. Recent research also indicates that Black home ownership is lower and Black dwelling unit size is smaller in areas with higher population densities. The higher costs that are associated with smart growth have the potential to increase the number of households eligible for housing assistance, to make it more costly to serve present recipients, and, as a result, to reduce the number of households that can be served.

Finding 3.25: Smart growth is associated with higher household expenditures.

Lower overall household expenditures are associated with metropolitan areas that sprawl more, which benefits all income classes and makes it possible to serve more households with housing assistance.

As would be expected, expenditures for transportation are higher in areas that sprawl more. But the lower housing costs in the more sprawling areas more than compensate for the transportation cost differential. Food costs are also lower where there is more sprawl. The higher costs associated with smart growth have the potential to increase the number of household eligible for housing assistance, to make it more costly to serve present recipients, and, as a result, to reduce the number of households that can be served.

Finding 3.26: Smart growth is associated with greater traffic congestion, longer commute times and more intense air pollution.

Contrary to popular perception, traffic congestion and air pollution are less intense in areas that sprawl more. This is indicated by both the US and international evidence.

Transit is generally slower than the automobile; even where high levels of transit are available. As a result, journey to work travel times are less in more sprawling areas, including for low-income workers.

Similarly, the hope urban areas might be redeveloped to better match jobs and residences, leading to a fundamental change in travel patterns, is unrealistic. Fundamentally, the transportation demand reducing objective of “walkability,” “transit-oriented development” and “mixed-use” urban designs is likely to have no more than marginal impacts. Modern urban areas are large employment and shopping markets. The compartmentalization that these schools of urban design would require is simply at odds with how people choose to live, work and shop. In the modern urban area, people often choose to work or shop at areas that are not particularly close to where they live. The same is true of low-income households. It makes little sense to expect that changes in the urban form can bring jobs and shopping closer to people when people seem disinclined to shop or work at the closest locations today.

Even if there were a broad commitment to the required and significant land use changes, the conversion process would take many decades for material change to occur, and a serious vision of the changes that would be required and how they would be achieved has not been articulated. In the much more dense and more transit-oriented urban areas of Europe that might be looked to as models, virtually all growth in recent decades has been in the suburbs, which rely principally on the automobile. The political and economic reality is that there is no prospect for redesigning urban areas in a manner that materially improves employment mobility opportunities for eligible recipients assistance in the near future. Further, the often tax-supported trend toward infill development in central cities could displace low-income households, forcing them to move to areas farther from employment and transit service.

Low-income employees have work trips that are similar in duration to that of all commuters and are only marginally more highly represented among workers traveling more than one-hour each way to work.

Finding 3.27: Smart growth is associated with reduced accessibility to labor markets, especially for low-income households.

Low-income households are most likely to achieve their employment potential if their geographical labor market is larger, rather than smaller. The automobile generally provides access to the largest possible labor market.

The lowest income households that are eligible for housing assistance have generally less access to automobiles than other households. For decades, the overwhelming majority of new jobs have been created outside the urban cores. On average, 90 percent of urban jobs are now outside downtown areas. Generally, these jobs are simply not accessible by transit in a reasonable travel time (if at all) to the overwhelming majority of residential locations in the urban area.

Because of slower transit speeds, the labor market available to the average automobile commuter is approximately five times the area available to the average transit commuter. The most important objective for improving low-income access to larger labor markets is to increase automobile availability.

The high cost of transit makes it impossible to provide the comparatively rapid mobility throughout a large urban area that is available by car. The political and economic reality is that financing present levels of transit service is a challenge in many metropolitan areas and implementation of the transit service levels that would bring a material improvement for eligible recipients is inconceivable. It makes more sense to improved income mobility by encouraging automobile ownership than to vainly seek reformation of an urban form toward the end of bringing jobs and shopping to low income people.

Finding 3.28: Because it is not feasible to negate its affordability destroying impacts, smart growth works at cross-purposes to the nation's housing assistance programs.

Even today, the nation does not remotely provide the funding level that would be required if all households eligible for housing assistance in fact received housing assistance. Moreover, there seems to be no short-term likelihood that substantially greater funding will be provided. Smart growth imposes affordability losses across the income spectrum, not just on low-income households. It is not feasible to design housing subsidy programs that would compensate in any systematic or comprehensive way for the housing affordability loss generated by smart growth. At whatever level of public expenditure, exclusionary planning must reduce the number of households for which housing assistance can be afforded.

Widespread adoption of exclusionary planning is likely to reduce home ownership levels and could reverse the substantial progress toward the national goal of greater home ownership. This burden will fall most on lower income households, which are disproportionately ethnic minorities. Thus, an indirect impact of exclusionary planning could be to reverse progress toward another national goal, integrating minority households into the economic mainstream. Smart growth could render the present home ownership level unsustainable, much less additional progress.

The inevitable affordability destroying impacts of smart growth (exclusionary planning) are at their root inconsistent with policies that would seek to ensure adequate shelter for all.

Finding 3.29: Smart growth’s exclusionary planning policies, especially development impact fees and urban growth boundaries, could represent a principal threat to housing affordability.

Economic theory indicates that, all things being equal, policies that ration (create shortages) raise prices. Excessive regulation, discouraging economic activity (such as development) and rationing factors of production (such as land) all create shortages. By artificially driving up the cost of housing, exclusionary zoning and exclusionary planning at least partially nullify housing assistance expenditures, thereby increasing the need for housing assistance.

Exclusionary planning is likely to drive development from areas that have adopted smart growth to areas that have not. It could even result in the rise of informal, substandard housing communities outside the highly regulated areas, and induce further sprawl and driving. Finally, smart growth could result in the emergence of two classes of metropolitan areas --- the more elite that adopt the exclusionary planning policies that artificially raise housing prices and the less elite, which do not.

• Home ownership rates are lower.

• Low-income household home ownership rates are lower.

• Black home ownership rates are disproportionately lower.

• Cost of living expenditures are higher.

• Work trips take longer

• Traffic congestion is greater

• Air pollution is more intense

These are not outcomes that improve the quality of life, whether for the population in general or eligible recipients of housing assistance in particular. The rapid adoption of smart growth, because of its inconsistency with economic dynamics, is likely to significantly reduce housing affordability.

Policy Options:

Based upon the analysis above, the following policy options are suggested to encourage improved housing affordability:

Income Estimation:

·        The U.S. Department of Commerce, the U.S. Department of Labor and the U.S. Department of Housing and Urban Development could establish a process for determining the cause of these disparate estimates and propose methods by which accurate and consistent data can be developed and routinely reported by both reporting systems.

·        Once the more accurate system is in place, US Department of Housing and Urban Development could prepare an estimate of the number of households eligible for housing assistance.

Exclusionary Planning (Smart Growth) and Exclusionary Zoning

• The Secretary of Housing and Urban Development could recommend to the President the issuance of an executive order reaffirming the fundamental commitment of the U.S. Government to continued home ownership expansion and housing opportunities for all. The order could review the progress toward increasing home ownership among the population in general and with respect to minorities in particular. The executive order should, within the constraints of applicable law, forbid the use federal funding by federal departments and agencies for programs that promote smart growth policies that would ration land or development (such as urban growth boundaries or development impact fees) and are thereby likely to reduce housing affordability.

• The U.S. Department of Housing and Urban Development could publish an Urban Development and Housing Affordability Guide Book for local communities on the negative impacts of regulatory barriers to housing affordability, with particular emphasis on the impacts of exclusionary zoning and smart growth’s exclusionary planning policies. The Urban Development and Housing Affordability Guide Book could include information with respect to the quality of life impacts of smart growth policies for eligible recipients of housing assistance.

• The U.S. Department of Housing and Urban Development could prohibit the use of research and technical assistance funding for the support of projects and programs that contribute to the problem of housing affordability, such as exclusionary zoning, and exclusionary planning (land rationing and development impact fees)

• The U.S. Department of Housing and Urban Development could establish and maintain a comprehensive, locality specific database of regulatory barriers such as urban growth boundaries, other land rationing initiatives, development impact fees (including amounts) and any other such provisions inconsistent with the established economic principle that rationing leads to higher prices and reduced housing affordability. Once such a database is developed, the US Department of Housing and Urban Development could produce an annual report on progress toward removing regulatory barriers to affordability and develop policy options (actual federal and models for states and localities) to encourage removal of barriers to affordability.