Until recently, a foreclosure on an owner-occupied home in the United States was a relatively rare event. According to data from the Mortgage Bankers Association (MBA), foreclosure proceedings were initiated on approximately 0.3 percent of all owner-occupied housing units with a mortgage in each quarter from 1979:Q1 through 2006:Q2 (figure 1). Since mid-year 2006, foreclosure proceedings have more than tripled and now occur at the rate of at least 1 percent per quarter.

To place these percentages in context, in the 27 ⅟2 year period between 1979 and mid-2006, a cumulative total of 7.5 million foreclosure proceedings had been initiated at a rate of 275,000 per year. In the 3 ⅟2 year period between mid-2006 and year-end 2009, 6 million foreclosure proceedings had been initiated, at a rate of 1.7 million per year, a more than six-fold increase. The conditions for high foreclosure rates are in place for at least the next two years, suggesting that another 4 to 5 million owner-occupied homes will enter into foreclosure in 2010 and 2011.

What is a Foreclosure?

A house is seized by a mortgage lender in a foreclosure proceeding after three steps have occurred. First, the homeowner fails to make contractually obligated mortgage payments, a condition commonly known as default. If homeowners fail to make one or two monthly payments, they are known as 30- and 60-days delinquent, respectively. In many of these cases, the homeowner “self-cures” by making the missed payment(s) in full and paying an additional (contractually pre-specified) penalty. A homeowner who misses three consecutive monthly payments is known as 90-days delinquent, and the probability increases that the house will end up in foreclosure (Tanta 2007).

In the second step, the lender initiates foreclosure proceedings. This process varies by state and can take between 6 and 18 months to complete. In the third and final step, the court system assigns the ownership of the house back to the mortgage lender. In some states, after a foreclosure occurs lenders may try to obtain a “deficiency judgment,” which implies that the foreclosed homeowner must compensate the lender in an amount equal to the difference between the value of the house after the foreclosure and the outstanding loan balance of the mortgage (Ghent and Kudlyak 2009).

What Factors Lead to Foreclosure?

We learn about the root causes of foreclosure by first exploring how foreclosure rates vary across places and over time. Figure 2 shows a graph of 90-day delinquency rates by state in the second quarter of 2009, when the 90-day delinquent rate ranged from 1 percent to 6.5 percent. Two variables explain almost three-quarters of the cross-sectional variation in delinquency rates across states: (1) the statewide unemployment rate in August 2009; and (2) the percentage change in house prices over the three-year period from 2006:Q2 to 2009:Q2.

Table 1 shows the highest and lowest five states in terms of foreclosure rates in 2009:Q2. The states with the steepest declines in house prices and highest unemployment rates have the highest percentage of seriously delinquent borrowers. The two states with the most disparate outcomes are Nevada and North Dakota. In Nevada, house prices fell almost 50 percent; the unemployment rate was 13.2 percent in August 2009; and the 90-day delinquency rate on mortgages was 6.5 percent. In North Dakota, homes appreciated by almost 11 percent; the unemployment rate was a low 4.3 percent; and the 90-day delinquency rate on mortgages was only 1.0 percent.

Figure 3 shows the time-series patterns of the nationwide 90-day delinquency rate, the national unemployment rate less 4 percent, and an index of commonly tracked house prices known as the Case-Shiller-Weiss (CSW) index. The vertical line on the graph at 2006:Q2 marks the height of the housing boom. Over the 2006:Q2–2007:Q4 period, nationwide 90-day delinquency rates started rising after house prices started to decline, despite relatively stable unemployment rates. During the recession, unemployment increased, house prices continued to fall, and the 90-day delinquency rate rose dramatically.

Both figures 2 and 3 suggest that foreclosures are associated with two “triggers”—falling house prices and rising unemployment rates. The double-trigger theory of foreclosures posits that the potential for a foreclosure is highest when (1) a homeowner is “under water,” meaning the house is worth less than the outstanding loan balance of the mortgage (plus any applicable fees); and (2) the homeowner experiences a significant disruption to income, such as unemployment, divorce, or a health event. In addition to the aggregated state-level and nationwide data shown here, the double-trigger theory of foreclosures has been shown to fit foreclosure patterns in loan-level data sets as well (Foote, Gerardi, and Willen 2010).

The double-trigger theory suggests that being under water is a necessary condition for a foreclosure, because it means the homeowner cannot sell the house unless he or she is willing to write the mortgage holder a check at closing to make up the difference of the value of the house and the outstanding loan balance of the mortgage. Recent estimates by the First American Core Logic company suggest that more than 10.5 million properties—20 percent of all residential properties with mortgages—are currently under water; many of them were purchased between 2005 and 2007.

Figure 4 shows that house prices have declined by 40 percent in nominal terms (50 percent after accounting for overall consumer price inflation) from the peak of the housing market in 2006:Q2 through the end of 2009. Standard underwriting calls for a homeowner to make a 20 percent down payment on a house. Given the decline in house prices, homeowners who bought at the peak of the market using a standard down payment are still approximately 33 percent under water. For example, if a homeowner buys a house for $100,000 with an $80,000 mortgage at origination and it then loses 40 percent of value, it is worth only $60,000. The house is now 33 percent under water ($80,000 – $60,000) / $60,000.

Most economists believe that being under water is not a sufficient condition to lead to a foreclosure, although there is some debate on this issue (Goodman et al. 2009; Foote et al. 2010). As long as the house value is not too far below the outstanding loan balance of the mortgage, there is a nontrivial probability that the house will appreciate such that its price will be greater than the mortgage in a reasonable amount of time, and this probability has value called “option value.” Given this value, and given that foreclosure is costly for homeowners, economic theory suggests that many homeowners who are under water should not “optimally” default on their mortgage. In many cases, the available data support this prediction.

Once a homeowner is under water, however, the data suggest that an additional shock to a homeowner’s income strongly increases the odds of foreclosure. Consider the experience of a homeowner who is under water and suddenly loses his or her main source of income due to unemployment or illness. In this case, the house is worth less than the mortgage, so the owner cannot sell or pull equity from the house. Furthermore, the homeowner has reduced income, so after depleting savings cannot make the mortgage payment in full.

To illustrate the quantitative relevance of this point, table 2 shows state-level maximum unemployment benefits (UI) and average mortgage payments for the set of ten states shown in table 1. In many states, UI benefits are not large enough for a one-income family to make a full mortgage payment. In all states, the average mortgage payment consumes a sizeable percentage of monthly UI benefits, leaving little income for food, transportation, clothing, health care, and other essentials.

Should Foreclosures Be Prevented?

A foreclosure seems like a simple transfer of an asset (the house) from the current equity holder (the borrower) to the current debt holder (the mortgage holder), which occurs whenever the borrower defaults on a mortgage obligation. If a foreclosure is just a simple transfer of assets across agents in the economy, then a case can be made that society should not care about foreclosures, the same way that normal people typically do not care how many electric guitars trade hands on eBay in any given month.

However, a case can be made that foreclosures are an undesirable outcome for society in some cases. Many economists think that foreclosures have externalities, meaning people not directly involved in the foreclosure process bear costs every time a house enters foreclosure. For example, foreclosures are estimated to reduce the resale value of nearby homes (Lin, Rosenblatt, and Yao 2007). In addition, foreclosures are associated with other costs that may be socially undesirable, such as the well-being of children (Kingsley, Smith, and Price 2009).

Has the Government Prevented Foreclosures?

Since 2007, the federal government has established initiatives and put into place a set of policies to try to reduce foreclosures. One of the first major initiatives, called Hope for Homeowners, was established in the spring of 2008. This program tried to address the first trigger directly to reduce the number of homeowners who were under water by encouraging institutions and investors holding mortgages to “write down” principal on those mortgages until homeowners were no longer under water. Participation in the program by mortgage holders was voluntary, and the program was structured in such a way that few mortgage holders participated (Cordell et al. 2009). For example, only one person received assistance in the first six months of the program’s launch (Arnold 2009).

In February 2009, the Obama administration announced another major initiative to reduce foreclosures, the Home Affordable Modification Program (HAMP) program, funded with $73 billion of TARP money. Implicit in the HAMP program is the notion that delinquencies and foreclosures have occurred because mortgages underwritten during the housing boom were often exotic, expensive, and ultimately unaffordable.

Until recently, HAMP’s solution to reduce foreclosures was to modify the terms of these mortgages (by reducing the interest rate, extending the amortization period, and offering some forbearance) for the purposes of making the mortgage “affordable,” meaning the mortgage payment would not exceed 31 percent of the borrower’s income after the mortgage was modified. As originally written, the HAMP program did not require the mortgage lender to reduce any of the borrower’s mortgage balance, and many unemployed did not qualify to receive a mortgage modification.

Figure 5 shows data from the Mortgage Bankers Association on 90-day delinquency rates for subprime adjustable-rate mortgages and prime fixed-rate mortgages over the 1998–2009 period. It is clear that subprime adjustable-rate mortgages are much more likely to be seriously delinquent than prime fixed-rate mortgages. These data might help explain why policy makers crafting the HAMP program have, until recently, focused on refinancing people out of exotic or expensive mortgages and into more conventional or less expensive mortgages as a method of reducing aggregate foreclosure rates.

These policy makers might have presumed that refinancing people from mortgages associated with high default rates to mortgages associated with low default rates would, by construction, reduce the overall default rate on all mortgages. There are two problems with this logic. First, people most likely to default are least likely to get a prime mortgage. This implies the mortgage choice at origination may be indicative of the underlying default risk of the borrower. In other words, defaults of subprime mortgages are high because, in some cases, subprime mortgage borrowers had high default risk and could only get a subprime mortgage.

Second, and more important, the recent data suggest that the majority of mortgages currently in default are not subprime mortgages (table 3). Given the current situation, it seems that a program designed to reduce foreclosures in the aggregate should focus on the inherent reasons that households with good mortgages or good credit are defaulting: the double-trigger theory.

Will We Have More Foreclosures?

Both foreclosure triggers are still in place. Unemployment rates are high, and the Congressional Budget Office (2010) is forecasting the national unemployment rate will remain above 9.0 percent in both 2010 and 2011. And, many homeowners are still under water. Assuming that house prices and housing rents will increase at the same rate over the next few years—not an unreasonable assumption given the behavior of historical rent and price data prior to 1996 (Davis, Lehnert, and Martin 2008)—then house prices should be expected to rise in nominal terms by somewhere between 1 and 2.5 percent per year for the next two years. Given the slow expected pace of house-price growth, many homes now under water will continue to be under water in two years.

Against this gloomy backdrop, Congress and the Obama administration have taken steps recently to prevent more foreclosures. First, on March 26, the administration revised the HAMP program so that the recently unemployed will be offered between three and six months of payment reductions (forbearance). This adjustment to HAMP is in line with the recommendations of a well-known plan to reduce foreclosures, written by economists at the Federal Reserve Board and the Federal Reserve Bank of Boston, commonly called the Boston Fed plan (Foote et al. 2009). It is also similar to an existing plan in the State of Pennsylvania that makes loans to unemployed homeowners to enable them to pay their mortgage, called HEMAP. In addition, mortgage investors will be subsidized by the HAMP program for writing down principal when borrowers are under water.

Second, the Obama administration has set up a “Hardest-Hit” fund distributing $2.1 billion to state housing finance agencies in ten states with severe house price decline and high unemployment rates. The state agencies are free to design programs to reduce foreclosures, subject to some guidelines (Housing Finance Agency 2010).

My colleagues and I have worked on foreclosure relief policy and are hopeful these new initiatives—the modification to HAMP and the Hardest-Hit fund—might significantly reduce foreclosure activity over the next few years.

About the Author

Morris A. Davis is an associate professor in the department of real estate and urban land economics at the University of Wisconsin School of Business, and a fellow at the Lincoln Institute of Land Policy. He was one of the authors of the Wisconsin Unemployment and Foreclosure Relief Plan, which was designed to reduce foreclosure activity of the unemployed. He also maintains and updates the Lincoln Institute Web site database on Land and Property Values in the U.S. (http://www.lincolninst.edu/subcenters/land-values).

Acknowledgments

I have benefited greatly from conversations, help, and advice from Chris Foote, Jeff Fuhrer, Kris Gerardi, Eileen Mauskopf, François Ortalo-Magné, Erwan Quintin, Steve Malpezzi, and Paul Willen. All mistakes and errors are my own.

References

Arnold, Chris. 2009. Investors support overhauling homeowner program. NPR broadcast, April 16. www.npr.org/templates/story/story.php?storyId=103148855

Congressional Budget Office. 2010. Current Budget Projections: Selected Tables from CBO’s Budget and Economic Outlook, Table E-1 (January). www.cbo.gov/ftpdocs/108xx/doc10871/economicprojections.pdf

Cordell, Larry, Karen Dynan, Andreas Lehnert, Eileen Mauskopf, and Nellie Liang. 2009. The incentives of mortgage servicers: Myths and realities. Uniform Commerical Code Law Journal 41: 347–374.

Davis, Morris A., Andreas Lehnert, and Robert F. Martin. 2008. The rent-price ratio for the aggregate stock of owner-occupied housing. Review of Income and Wealth 54(2): 279–284.

Foote, Christopher, Jeff Fuhrer, Eileen Mauskopf, and Paul Willen. 2009. A proposal to help distressed homeowners: A government payment-sharing plan. Public Policy Brief No. 09-1. Boston: Federal Reserve Bank of Boston. www.bos.frb.org/economic/ppb/2009/ppb091.htm.

Foote, Christopher, Kristopher Gerardi, Lorenz Goette, and Paul Willen. 2010. Reducing foreclosures: No easy answers. NBER Macroeconomics Annual 24(1): 89–138.

Foote, Christopher, Kristopher Gerardi, and Paul Willen. 2010. Should modifications ‘re-equify’ borrowers? A look at the data. Real Estate Research Blog, March 2. http://realestateresearch.frbatlanta.org/rer/2010/03/should-modifications-reequify-borrowers-a-look-at-the-data.html#more

Ghent, Andra C., and Marianna Kudlyak. 2009. Recourse and residential mortgage default: Theory and evidence from U.S. states. Working Paper No. 09-10. Richmond, VA: Federal Reserve Bank of Richmond.

Goodman, Laurie, Roger Ashworth, Brian Landy, and Ke Yin. 2009. Negative equity trumps unemployment in predicting defaults. Amherst Mortgage Insight, November 23: 1–8.

Housing Finance Agency. 2010. Innovation Fund for the Hardest-Hit Housing Markets (HFA Hardest-Hit Fund): Frequently asked questions, March 5. http://makinghomeaffordable.gov/docs/HFA%20FAQ%20–%20030510%20FINAL%20%28Clean%29.pdf

Kingsley, G. Thomas, Robin E. Smith, and David Price. 2009. The impacts of foreclosures on families and communities. Washington, DC: The Urban Institute.

Lin, Zhenguo, Eric Rosenblatt, and Vincent W. Yao. 2007. Spillover effects of foreclosures on neighborhood property values. The Journal of Real Estate Finance and Economics 38(4): 387–407.

Tanta. 2007. Delinquencies and defaults for ubernerds. Calculated Risk Blog, July 6. www.calculatedriskblog.com/2007/07/delinquencies-and-defaults-for.html

Sally Powers has been a visiting fellow in the Department of Valuation and Taxation at the Lincoln Institute of Land Policy since 2009. She was director of assessment for the City of Cambridge for thirteen years until 2001, when she became an international consultant. That work has taken her to Kosovo, Montenegro, South Africa, the Kyrgyz Republic, and Turkmenistan, among other countries, where she has participated in projects on property taxation, market value revaluations, and establishment of a valuation profession for a transition economy.

Her career as an assessment administrator and consultant has involved all aspects of property taxation: legal framework, property appraisal, value defense, local government finance, tax policy, project planning and execution, public information, software specification and testing, cadastral/GIS (geographic information systems) mapping and analysis platforms, and tax collection and enforcement. Her research interests focus on mass appraisal, specifically the application of econometric techniques to analyze market activity and develop models to estimate the market value of properties that have not sold. She has written on topics as diverse as appraisal modeling, implementation of the local property tax in Kosovo, and property tax collection strategies.

Powers received her bachelor’s degree in anthropology from the University of Chicago, and she holds a Master of Science degree from the Boston College Carroll School of Management.

LAND LINES: How does your work fit within the research and education program of the Lincoln Institute?

SALLY POWERS: The Lincoln Institute is a leader in property tax policy, and its work influences the local government officials responsible for the property tax in thousands of jurisdictions across the United States and internationally. The Department of Valuation and Taxation presents a variety of conferences, seminars, and courses for property tax professionals, and I have served as faculty for a number of these programs since the 1990s. I’m also involved in working directly with local tax practitioners and in research projects that will continue to challenge the conventional wisdom about the property tax.

LAND LINES: What are some of your current projects?

SALLY POWERS: One major project deals with a joint venture between the Lincoln Institute and the George Washington Institute of Public Policy to create a free, downloadable property tax database for all 50 U.S. states and the District of Columbia. The Significant Features of the Property Tax Web site was launched in June 2009, and the information is updated every year to keep current with changes in the legislation that regulates the property tax in each state.

We regularly expand the subject matter to be included, and have made the site a central access point for information about the property tax from a variety of federal, state, and scholarly sources. For example, the only nationwide study of effective tax rates is published by the Minnesota Taxpayers Association, and this publication is now available for downloading from the Significant Features site. The next topic we plan to organize for presentation on the Web site is the various forms of property classification for tax purposes.

LAND LINES: Can you clarify what an effective tax rate and classification mean, and why they are important aspects of this database?

SALLY POWERS: The property tax rate by itself does not explain much about the property tax burden in a particular community or provide any basis for comparison across jurisdictions. A high tax rate may simply reflect low property values, and a low tax rate may reflect very high values. Effective tax rates are calculated by comparing the amount of the property tax bill for a property to its market value, which may or may not be the same or even close to its assessed value. Effective tax rates, where they are available, thus make it possible to understand the impact of a tax bill intuitively and to make better informed cross-jurisdictional comparisons.

Classification of property is undertaken by many states, either legislatively or in the state’s constitution, to identify property categories based on use, the most common uses being residential, commercial, and industrial. In some states the classifications are applied for identification and reporting purposes only. However, it is employed more frequently to tax favored classes at lower rates than other classes. The most favored classes are generally residential and agricultural uses.

LAND LINES: Based on your research, how well is the property tax holding up as a primary local revenue source during the current recession?

SALLY POWERS: There are two major components to a property tax bill: the property value and the tax rate, as discussed above. In states where local tax jurisdictions are not encumbered with extreme limits on tax rates, the property tax can be quite resilient, because when values decrease the tax rate may be increased. In addition, the value always represents an assessment as of a specific date prior to the issuance of the tax bill. It is not unusual for this assessment date to be a year and a half or more before the date of issuance of tax bills. This “assessment lag” gives local jurisdictions a cushion in times of rapidly changing markets, with time to plan for the eventual change in the level of assessed values and to investigate other local revenue sources. To date, research on property tax revenues during the current down-turn has borne out these features of the property tax.

LAND LINES: It’s clear that the American property tax is a complex affair. How does this compare to your experience in other countries?

SALLY POWERS: International experience with the property tax varies greatly, depending on the maturity of the property tax system, the culture, and the legal underpinnings for the tax. The projects I worked on in Eastern Europe were introducing a market value based property tax. Political leaders and central and local public officials had no difficulty with the concept of market value. Valuation methods were uncomplicated and directly related to sales. A common theme in the U.S. and many other countries, however, is the desire to make the burden of the property tax smaller for residences than for businesses. Some of the proposed formulas to provide tax relief are extremely complicated, such as relating property value to household size and ages of household members.

LAND LINES: How widespread is the property tax?

SALLY POWERS: It is quite surprising how many countries assess some form of tax or fee on property or property rights. Another Lincoln Institute project I am working on is the African Tax Institute (ATI), a joint venture with the University of South Africa at Pretoria. More than ten research fellows at ATI have visited one or more of 38 countries to develop in-depth reports on the various forms of tax on property (Franzsen and Youngman 2009). Most of those reports and supplemental appendices are posted on the Lincoln Institute Web site as working papers. In every country studied the researchers found some sort of tax or fee on ownership or use of property. In many countries all land is owned by the government, but the rights to use the land are owned by individuals and companies that pay fees and taxes on their use rights.

In countries of the former Yugoslavia, for example, the property tax is a familiar concept. In the early 1990s, the Federal Republic of Yugoslavia established a privatization program that transferred ownership of government-owned apartment flats to individual owners. An annual tax was assessed on the owners, based on the characteristics of the property.

LAND LINES: Can you describe more about your interest and experience in econometrics applied to property market data.

SALLY POWERS: I was plunged into multiple regression analysis on my very first property tax job for the City of Boston in 1982. I was part of the team hired to use statistical analysis to develop models (formulas) that could be applied to property data to estimate market value. I was fortunate because the city hired some of the top experts in this emerging field to train us in these methods. Since then, both as an assessor and later as a consultant, I have continued to use econometric tools to estimate market value for property tax application.

It has been fascinating to participate in the increasing sophistication and effectiveness of CAMA (computer assisted mass appraisal) to generate AVMs (automated valuation models). The biggest leap in this technology takes advantage of GIS capabilities to analyze location and property value. I am looking into an econometric tool for CAMA application that analyzes data around median values rather than the mean. This is interesting because the current statistical standards for value accuracy and uniformity are calculated around the median because, compared to the mean, it measures average value with less bias from extremely high or low values.

LAND LINES: Do you have any other observations about the Institute’s work in the current volatile realm of property taxation?

SALLY POWERS: As a visiting fellow at the Lincoln Institute, I have found it especially gratifying to see the increasing public interest in the Significant Features of the Property Tax database. The Web site has been cited by many scholars in the field of local public finance, and the authors of two papers presented at recent Institute seminars used data from the site for their analyses.

Adding to its Web-based resources, the Lincoln Institute has produced more than 10 online courses on such diverse topics as property tax policy, modern valuation technologies, property tax reform in Massachusetts, and introduction of the property tax in transition economies. The IAAO (International Association of Assessing Officers), the leading membership organization for tax assessors and other property tax professionals, has recognized the value of these courses, and now its members can receive continuing education credit for taking them.

Finally, the Institute has inspired more economists to become interested in property tax valuation and equity issues. For example, economists from the University of Illinois and Florida State University are conducting studies of assessment equity that introduce contemporary econometric tools to both display and analyze patterns of overvaluation and undervaluation of property in assessing jurisdictions.

Visiting fellow Dan McMillen (2011), working with a rich data-set that includes the City of Chicago, will present his analysis and conclusions at the next annual conference of the IAAO. I will be on hand to help make his innovative findings accessible not only to the statistical analysts in the audience, but also to property tax assessors who are interested in improving values in their own jurisdictions.

References

Franzsen, Riel C. D., and Joan M. Youngman. 2009. Mapping property taxes in Africa. Land Lines 21(3): 8-13.

McMillen, Daniel P. 2011. Assessment regressivity: A tale of two Illinois counties. Land Lines 23(1): 9-15.

Significant Features of the Property Tax. www.lincolninst.edu/subcenters/significant-features-property-tax

Over the past several decades, the structure of the U.S. economy has changed as it experienced a continuing reduction of overall employment in manufacturing and ongoing growth in the service sector, especially services involving knowledge workers. The geographic distribution of activity has also changed as population has continued to shift from the seasonal Northeast and Midwest to the warmer South and West. Finally, within metropolitan areas, populations and employment moved from cities to the suburbs as trucking and automobile travel became ubiquitous. These three trends have left many cities in the Northeast and Midwest with much smaller populations, weaker economies, fewer manufacturing jobs, and an inability to offset lost employment opportunities with gains from sectors that are expanding nationally. These are today’s legacy cities, which often have excess infrastructure capacity, underutilized housing stocks, and fiscal stress related to past obligations from public sectors now greatly diminished in size. A recent Lincoln Institute policy focus report, Regenerating America’s Legacy Cities, by Alan Mallach and Lavea Brachman, reviews the performance of a sample of these urban areas and identifies steps the more successful cities have taken to produce stronger outcomes.

While the declines of legacy cities have common causes, their economic performance has become quite diverse in recent decades, as some have delivered much stronger economic, institutional, and fiscal results than others. All legacy cities have an array of assets including infrastructure, neighborhoods, institutions, populations, and ongoing economic activity. Differences in their comparative performance are related to how local policies and leadership have leveraged existing inventories of these assets. In particular, recovering legacy cities have built upon and expanded existing institutions in research, medicine, health, and education. They have also exploited the growing interest in urban neighborhoods where it is easy to walk to stores and restaurants, and where residential densities are higher than those in most suburban communities. Recovering cities also typically have maintained or attracted more educated residents and have seen growth in knowledge-related activities.

Legacy cities that have seen their economies begin to transform and grow again have not necessarily experienced population increases. The population of most legacy cities peaked in the mid-20th century and then declined. Buffalo and St. Louis, for example, had lower populations in 2000 than in 1900. Sometimes the decline in city populations is offset by suburban growth, so that metropolitan populations do not decline. But some successful legacy cities, such as Pittsburgh, have experienced modest population declines even at the metropolitan level. Changing the composition of city populations and economic activity is more important for success than population growth alone.

The successful recovery of legacy cities normally has not resulted from megaprojects that focus on redevelopment, but on the accretion of many small steps with a large cumulative impact—an approach Mallach and Brachman have dubbed “strategic incrementalism.” Their research shows that successful legacy cities have pursued such an approach continually and relentlessly. The key elements of strategic incrementalism require the evolution of new forms for a city’s physical organization, economic components, governance, and linkages to its surrounding region. Physically, the practice involves focusing on the city’s central core, its key neighborhoods, and the management of vacant land. Economically, it involves restoring the economic role of the city based on its comparative advantages and existing assets, sharing the benefits of growth with its population, and strengthening connections to the city’s region. Cities also must strengthen their governance and address the flow of services and fiscal resources between the city and the municipalities in the greater metropolitan area.

Legacy cities have declined over many decades, and recovery will take time and require patience. While the performance of some, such as Camden, NJ, continues to deteriorate, others show signs of progress. In Pittsburgh, Philadelphia, Milwaukee, and other legacy cities on the rebound, economic performance has improved, and the rates of unemployment, crime, and poverty have fallen below national averages despite the fact that populations remain well below their peak 60 years ago.

For additional information on the determinants of legacy city success, see http://www.lincolninst.edu/pubs/2215_Regenerating-America-s-Legacy-Cities.

The property tax is the most widely unpopular tax in America. States have responded to this public opposition by enacting a range of tax relief policies, especially for homeowners (Cabral and Hoxby 2012). Among the most commonly adopted programs are homestead exemptions and property tax credits; all but three states have at least one of these programs. But despite their broad use and their potentially large impact on the distribution of property tax burdens, there has been remarkably little data available on the tax savings generated by property tax exemptions and credits.

Two new resources, available through the Lincoln Institute’s Significant Features of the Property Tax subcenter, begin to fill this need. These tables provide information for each state on the share of homeowners eligible for these programs and the level of tax savings they receive, as well as an analysis of how eligibility and benefits vary across the income distribution (see box 1, p. 26). This article draws on these resources to provide the first national study of property tax exemptions and credits with estimates of tax savings from these programs. With this information, policy makers have a critical tool to evaluate and improve the effectiveness of their property tax relief programs.

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Box 1: State-by-State Details on Property Tax Exemptions and Credits

The Significant Features of the Property Tax sub-center provides three key resources with information on property tax exemptions and credits in all 50 states; it is accessible at www.lincolninst.edu/subcenters/significant-features-property-tax.

Tax Savings from Property Tax Exemptions and Credits

This online Excel file includes estimates of tax savings from programs in individual states (see abbreviated example below), plus overview tables that make it easy to compare across states. For each program, the file provides estimates of the number of eligible homeowners and the median benefit, as well as a distributional analysis by income quintile. This is the first time that detailed data are available for most of these programs.

Summary Table on Exemptions and Credits

This online Excel file includes a set of tables for 167 programs displaying the value of exemptions expressed in terms of market value; criteria related to age, disability, income, and veteran status; the type of taxes affected (i.e., school or county taxes); whether the tax loss is borne by state or local governments; local options; and more. The summary table makes it easy to conduct quantitative analysis of these programs or make quick state-by-state comparisons. The information in these tables was used to generate the tax savings estimates.

Residential Property Tax Relief

This section of the Significant Features website includes detailed descriptions of property tax exemptions and credits, which were used to create the online Summary Table on Exemptions and Credits. It also describes other types of property tax relief, such as circuit breakers and tax deferral programs.

Notes: Total tax savings from the Senior and Disabled Property Tax Homestead Exemption ($392M) is less than the combined total of the programs for Seniors ($378M) and the Disabled ($22M), because homeowners who are 65+ and disabled cannot claim the exemption twice. The online Summary Table shows that the Senior and Disabled Exemption is a $25,000 exemption for homeowners who are 65+ or disabled; the two Rollback programs are percentage exemptions of 2.5% and 10% for all owner-occupied residences. Source: Lincoln Institute of Land Policy (2015).

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How Property Tax Exemptions and Credits Work

Property tax relief programs come in a variety of forms. Homestead exemptions reduce the amount of property value subject to taxation, either by a fixed dollar amount or by a percentage of home value. Property tax credits, in contrast, directly reduce the homeowner’s tax bill by a fixed dollar amount or certain percentage.

As table 1 illustrates, programs designed to provide identical benefits to owners of $200,000 homes have widely different impacts on homeowners with higher- and lower-valued properties. Given a 1% tax rate, a $20,000 flat dollar exemption reduces property taxes for each homeowner by $200 ($20,000 x 1%). This program has a progressive impact on the property tax distribution because lower-income households tend to have less valuable homes, and the exemption represents a larger share of their home values. In this case, the $20,000 exemption reduces property taxes by 20% on the $100,000 home, 10% on the $200,000 home, and 5% on the $400,000 home.

A percentage exemption, in contrast, provides the same percentage reduction in taxes for all three homeowners—in this example, 10%. In dollar terms, however, percentage exemptions favor owners with higher-valued homes: a 10% across-the-board reduction lowers property taxes by only $100 on the $100,000 home but $400 on the $400,000 home.

In the case of flat dollar credits, homeowners with lower-valued homes usually receive the largest tax cuts in percentage terms. In contrast, the percentage tax credit again provides the owner of the $400,000 home the largest tax cut in dollar terms.

An important feature of property tax exemptions and percentage credits is that the dollar reduction (but not the percentage reduction) in taxes increases with tax rates. For instance, if the homes in table 1 were subject to a 2% tax rate, the dollar savings to their owners would double under the $20,000 exemption, 10% exemption, and 10% credit. While the dollar savings from flat dollar credits do not vary with tax rates, the percentage savings to homeowners decrease as tax rates rise.

Critical Features of Exemptions and Credits

The design of homestead exemption and property tax credit programs varies significantly across the 50 states. Figure 1 (p. 28) summarizes the number and share of state programs with the following key characteristics.

Benefit Calculation

Perhaps the most important feature of property tax relief programs is how benefits are calculated. In 2012, 59% of state programs provided flat dollar exemptions, 19% provided percentage exemptions, and the final fifth used property tax credits or other more complicated formulas to determine the amount of tax relief for each homeowner.

While the programs work in similar ways, their effects differ dramatically. As the examples in table 1 show, flat dollar exemptions and credits make the property tax distribution more progressive, while percentage exemptions and credits do not. As a result, to provide a certain level of tax relief for the median homeowner, percentage exemptions are more expensive than other programs because they result in larger property tax cuts for owners of higher-valued homes. Instead of changing the distribution of property taxes among homeowners, percentage exemptions are primarily a way to shift the tax burden away from homeowners as a group to businesses, renters, and owners of second homes.

State vs. Local Funding

The ultimate impact of exemptions and credits on property tax bills depends on how the programs are funded. Figure 1 shows that in 2012 only 28% of these programs included full state reimbursement to cover local revenue losses, while 57% had local governments bear revenue losses on their own. For 15% of programs, state and local governments shared the revenue loss in some way. (Broad-based programs for all homeowners or all seniors are more likely to receive state funding than programs for smaller groups such as veterans or the disabled. In 2012, 43% of tax relief programs for all homeowners or seniors were state-funded, 48% were locally-funded, and the rest split the revenue loss [Lincoln Institute of Land Policy 2014].)

The primary argument in favor of state funding of property tax exemptions and credits is that it can help mitigate disparities in property wealth across localities. Poorer communities and those without a significant business tax base typically have higher property tax rates, and these communities receive more funds per homeowner under state-funded programs. Without this assistance, communities with higher tax rates will experience larger revenue losses from tax relief programs unless they increase tax rates even further.

Seniors vs. All Age Groups

A number of states provide property tax relief for seniors. In 2012, more than a third favored seniors in some way: seven had statewide programs solely for this group, while 11 also covered younger homeowners but provided higher benefits for older homeowners. Other states provided either the same level of benefits for homeowners of all ages (15 states) or did not have broad-based programs (18 states).

Common arguments for targeting senior homeowners is that property taxes account for a larger share of their incomes, and local governments spend less on seniors than on younger homeowners with school-aged children. While it is true that property taxes account for a larger share of income for seniors than for working-age homeowners, the two groups devote nearly identical shares of their incomes to total housing costs because seniors are far less likely to have mortgages (Bowman et al. 2009, 11). In addition, property taxes are payments for public services, not user fees (Kenyon 2007, 36). Younger households without children in public schools do not benefit from property tax relief under these programs. The preferential tax treatment of seniors may simply reflect the fact that older households are a politically powerful group that votes in high numbers.

Estimating the Benefits of Exemptions and Credits

To estimate tax savings from homestead exemptions and property tax credits, the first step was to create the online Summary Table on Exemptions and Credits, which describes the key features of each program (see box 1 for description). These data draw almost entirely from the Residential Property Tax Relief Programs section of the Lincoln Institute’s Significant Features of the Property Tax database.

The second step was to combine this information with household-level data from the 2008–2012 American Community Survey (ACS). This nationally representative survey has data on more than 6.5 million U.S. households, including the household characteristics that determine program eligibility (age, income, disability, veteran status, etc.) and level of benefits received (home values and property tax bills). For a full explanation of the methodology used to estimate tax savings from exemptions and credits, see Langley (2015).

It is important to note that the estimates reported here are gross property tax savings. Tax relief programs often lead to higher property tax rates, especially under locally-funded programs where jurisdictions raise tax rates to offset the drop in the tax base from the exemptions. Estimates of net property tax savings would be lower in those communities, because the higher tax rates offset some of the direct tax relief provided from exemptions and credits.

Figure 2 shows that total property tax relief from homestead exemptions and property tax credits varies widely across states, but is generally small relative to total property tax revenues. In 14 of the 45 states with these programs, total savings are less than 0.5% of property tax revenues; in 27 states, the savings are less than 2.5%. At the same time, though, tax savings in nine states equal or exceed 10% of total property tax revenues. Indiana’s program is particularly generous, offering all homeowners a $45,000 exemption, then an additional 35% exemption for the first $600,000 in assessed value and a 25% exemption for value above $600,000.

Tax Savings for Different Types of Programs

Most states have more than one property tax exemption or credit program, with different programs targeting different groups of taxpayers—typically all homeowners, seniors, veterans, or the disabled. Figure 3 presents estimates on the share of homeowners eligible for these programs, along with the level of tax savings they receive.

Homeowners

Programs in 26 states are for nearly all homeowners, but usually limited to owner-occupied primary residences. In the typical state with these programs, the median homeowner receives a 12.5% cut in property taxes. On the high end, however, the median property tax cut was at least 25% in more than a quarter of states with these programs.

Seniors

Property tax relief programs in 18 states target older homeowners (typically at least age 65). These programs are much more generous than those covering all homeowners, with a median tax reduction of nearly 30% in the typical state. More than half of these programs provide a median tax cut of at least 25%, while only a sixth of them provide a median tax savings of less than 10%.

In the median state, 19.6% of homeowners are eligible for the programs, but eligibility rates vary greatly across states depending on whether there is an income ceiling. In the seven states that provide property tax relief to seniors regardless of income, 25–30% of homeowners are typically eligible. But in seven states with low income cutoffs ($10,000 to $30,000), only 5–10% of homeowners qualify. The other four states with property tax relief programs for seniors do not fit neatly into these two categories because they have higher income ceilings, strict wealth limits, or other eligibility criteria.

Veterans

State programs for veterans are more common than for any other group of homeowners, although eligibility is often limited to those who are disabled. Indeed, only 10 states provide property tax exemptions or credits for all veterans, even those without disabilities. In the median state with these programs, the typical beneficiary receives a property tax cut of just 3.2%.

There are 31 states that provide property tax exemptions or credits to veterans with service-connected disabilities. Because of the disability requirement, most veterans are ineligible for the programs. Indeed, only 15% of veterans qualify in the typical state. Overall, just 0.6% of homeowners are eligible for these programs in the median state.

Moreover, most of the 31 programs base eligibility and benefit levels on disability ratings from the Department of Veterans Affairs. Just seven states have programs for all partially disabled veterans, and veterans with lower disability ratings typically receive modest tax savings. On the other hand, 18 states restrict eligibility to veterans who are permanently and totally disabled. These programs benefit a very small share of veterans, but they usually provide a full 100% exemption.

Disabled

Programs in 23 states cover disabled homeowners, but really target two distinct groups: disabled homeowners and blind homeowners. In 2012, 12 states had programs for disabled homeowners, seven states had programs for the blind, and five states covered both groups. Programs for the disabled typically require beneficiaries to be permanently and totally disabled, but exact criteria vary. In the median state, 2.3% of homeowners are eligible for these programs and they receive a median property tax cut of 21%.

Conclusion

Homestead exemptions and property tax credits are an important part of the property tax system. These programs are used in nearly all states and can make the distribution of property taxes significantly more progressive. It is therefore critical that policymakers have good data on the property tax relief that these programs actually provide.

New research makes this information available for the first time. Using the Lincoln Institute’s Significant Features of the Property Tax subcenter, policymakers can easily compare key features of property tax exemption and credit programs across states, and see estimates of eligibility and tax savings. These data make it possible to evaluate the impacts of property tax exemptions and credits in their particular states as well as find ideas for program improvements.

Adam H. Langley is Senior Research Analyst at the Lincoln Institute of Land Policy. Special thanks go to Andrew Reschovsky, who provided extensive comments on this article and other related papers.

References

Bowman, John H., Daphne A. Kenyon, Adam Langley, and Bethany P. Paquin. 2009. Property Tax Circuit Breakers: Fair and Cost-Effective Relief for Taxpayers. Cambridge, MA: Lincoln Institute of Land Policy.

Cabral, Marika, and Caroline Hoxby. 2012. “The Hated Property Tax: Salience, Tax Rates, and Tax Revolts.” Cambridge, MA: National Bureau of Economic Research. Working paper 18514. November.

Kenyon, Daphne A. 2007. The Property Tax-School Funding Dilemma. Cambridge, MA: Lincoln Institute of Land Policy.

Langley, Adam H. 2015. “Estimating Tax Savings from Homestead Exemptions and Property Tax Credits.” Working paper. Cambridge, MA: Lincoln Institute of Land Policy.

Lincoln Institute of Land Policy. 2014. Significant Features of the Property Tax. Residential Property Tax Relief Programs: Summary Table on Exemptions and Credits in 2012. www.lincolninst.edu/subcenters/significant-features-property-tax/Report_Residential_Property_Tax_Relief_Programs.aspx

Lincoln Institute of Land Policy. 2015. Significant Features of the Property Tax. Tax Savings from Property Tax Exemptions and Credits in 2012. www.lincolninst.edu/subcenters/significant-features-property-tax/Report_Residential_Property_Tax_Relief_Programs.aspx