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A critical aspect of the property tax, but one that is rarely addressed in public debate, is its “economic incidence,” or who actually bears the burden of the tax, as opposed to its statutory incidence, or who literally pays the tax. For example, a landlord might pay a property tax bill, but if some of the tax is offset with a rent increase, then the tenant bears that part of the tax burden. Not surprisingly, estimates of the economic incidence of taxes depend on the relative responsiveness of supply and demand to tax-induced price changes—factors that explain the extent to which consumers and businesses can change their behavior to avoid the tax.
The economic incidence of a tax is also affected by the phenomenon of “capitalization”—changes in asset prices that reflect the discounted present values of the economic effects of future tax and/or public expenditure changes. For example, an increase in property taxes, holding expenditures constant, might be capitalized into land or house values. The prices of these assets might fall by the present value of the projected increase in future taxes, whereas increases in expenditures, holding property taxes constant, might have offsetting effects.
These capitalization effects should include the effects of other tax-induced price changes, such as changes in future housing or land rents. In principle, the economic incidence of all of these capitalization effects is on the owners of land and housing at the time of the imposition of the tax, when the effects are “capitalized” as one-time changes in the prices of these assets. These price changes also significantly affect the ultimate economic burden of the tax on subsequent purchasers.
Benefit Tax versus Capital Tax Views
The complexity of measuring all of these effects implies that determining the economic incidence of taxes is one of the most difficult problems in public finance, and the property tax is no exception. Indeed, the debate over the incidence of the residential property tax has raged for at least the last thirty years, and is still far from resolved. Professional opinion on the incidence of the tax is generally divided between the “benefit tax” view and the “new” or “capital tax” view (Zodrow 2001).
Under the benefit tax view, the property tax is considered a user charge for public services received. It thus serves the function of a local head tax or benefit tax as envisioned by Tiebout (1956) in his celebrated analysis of how interjurisdictional competition coupled with consumer mobility can lead to the efficient provision of local public services. The implications for taxpayers are threefold. First, as a benefit tax the property tax is simply a payment for public services received, analogous to purchases of goods and services for private markets. Second, because the property tax functions as a market price, its use implies that local public services are provided efficiently. Third, the property tax, like all benefit taxes, results in no redistribution of income across households and thus has no impact on the distribution of income.
By comparison, under the capital tax view derived by Mieszkowski (1972) and elaborated by Zodrow and Mieszkowski (1986b), the property tax is a tax on the use of capital and thus inefficiently distorts resource allocation by driving capital investment out of high tax jurisdictions and into low tax jurisdictions. The capital tax view divides the incidence of the property tax into two components. The national average tax burden is in effect a “profits tax” borne by all capital owners, including homeowners, businesses, and investors. The local or “excise tax” components of property tax rates that fall above or below the national average are borne locally through changes in land rents, wages, or housing prices.
The incidence effects of local taxes that are higher and lower than the national average tend to cancel one another in the aggregate. Therefore, the profits tax effect is the main factor determining the incidence and distributional effects of the property tax. From the perspective of any single taxing jurisdiction, however, the burden of local expenditures financed by the property tax tends to be borne primarily by local residents.
The capital tax view has different implications for taxpayers in all three of the areas noted above for the benefit tax view. First, the tax has some significant benefit aspects in that local tax increases tend to be borne by local residents. Second, the tax inefficiently distorts housing consumption decisions; moreover, use of the local property tax can also lead to inefficient underprovision of local public services if government officials, concerned about tax-induced loss of investment, then reduce the level of public services (Zodrow and Mieszkowski 1986a). Third, because the primary effect of nationwide use of the property tax is a reduction in after-tax returns to capital owners, it is a highly progressive tax. Nevertheless, from the perspective of a single taxing jurisdiction, the local tax is not borne by capital owners as a whole but rather by local residents and is a roughly proportional tax. (See Table 1 for a summary of these two views.)
Capitalization and the Incidence of the Property Tax
My recent research sponsored by the Lincoln Institute has focused on a single but critical aspect of this long-standing debate. Dating back to the seminal work of Oates (1969), empirical evidence of the interjurisdictional capitalization of the discounted values of local property taxes and public services into house prices has been interpreted as offering support for the idea that property taxes can be viewed as payments for local public services received, consistent with the benefit tax view.
This notion was extended to the case of intrajurisdictional capitalization in the pathbreaking work of Hamilton (1976). In this model, which is characterized by perfectly mobile households with heterogeneous demands for housing and fixed housing supplies, intrajurisdictional fiscal capitalization converts the local property tax into a pure benefit tax, even though all houses are not identical. Specifically, high-value homes sell at a discount that reflects the capitalized present value of their “fiscal differential”—the present value of the excess of future taxes paid relative to public services received.
Similarly, low-value homes should sell at a premium that reflects the capitalized present value of the extent to which future taxes paid are less than the value of public services received. As a result, all households “pay for what they get” in public services, and the property tax is an efficient benefit tax. Capitalization thus implies that it is futile to follow the conventional strategy of buying a low-value home in a high-value community in order to receive local services at relatively low cost.
In supporting the idea that the combination of strict zoning regulations and fiscal capitalization converts the property tax into a benefit tax, Fischel (2001) interprets the extensive literature on the capitalization of property taxes and public services as demonstrating that fiscal “capitalization is everywhere.” He concludes that empirical support of fiscal capitalization provides compelling evidence that the benefit tax view accurately describes the effects of the property tax. Fischel makes this argument in the context of a model in which local governments are analogous to municipal corporations that maximize the house values of “homeowner-voter shareholders” who strive to protect their housing investments.
The central result of my research is that even if empirical evidence of the phenomenon of fiscal capitalization implies that it is indeed “everywhere,” such evidence does not establish the validity of the benefit tax view. Rather, my model shows that if one adopts all of the admittedly stringent assumptions of the benefit tax view, complete intrajurisdictional land value fiscal capitalization is also entirely consistent with, and indeed predicted by, the capital tax view of the property tax.
When combined with earlier results that demonstrate that interjurisdictional capitalization is also consistent with the capital tax view, my research results imply that the widely observed phenomenon of property tax capitalization provides little if any grounds for distinguishing between the capital tax and benefit tax views. That is, capitalization does not tell us whether the property tax should be viewed primarily as a progressive tax on all capital that inefficiently distorts decisions regarding housing consumption (the capital tax view), or an efficient user charge that has no effects on the distribution of income (the benefit tax view).
A Reconstruction of the Benefit Tax View
My research begins by reconstructing the Tiebout-Hamilton benefit tax view within the context of a partial equilibrium version of the standard differential tax incidence model, which focuses on the effects of use of the property tax in a single taxing jurisdiction. This approach is necessary because the derivations of the benefit tax and capital tax views of the property tax are based on somewhat different theoretical approaches.
Hamilton’s benefit tax view model characterizes the properties of an economy in equilibrium, with local public services financed by residential property taxes rather than the head taxes assumed by Tiebout. In contrast, the derivations of the capital tax view, such as those in Mieszkowski (1972) and Zodrow and Mieszkowski (1986b), are based on the differential tax incidence analysis pioneered by Harberger (1962). Under this approach, the effects of the property tax are analyzed by first constructing an initial equilibrium with either no taxes or only nondistortionary lump-sum taxes, and then introducing property taxes and analyzing their effects.
To facilitate a comparison of the two views, my analysis begins by deriving all of the benefit tax view results obtained in Hamilton’s model of intrajurisdictional fiscal capitalization within the context of a differential tax incidence model, one that is typical of the capital tax view but nevertheless makes the essential—and admittedly rather stringent—assumptions characteristic of derivations of the benefit tax view. In particular, households are perfectly mobile across competing local jurisdictions with an exogenous source of income, and there are a sufficient number of jurisdictions to satisfy all tastes for local public services.
Following Hamilton, the model has two different types of households, one of which demands relatively larger houses. Initially, the local economy is assumed to be in a Tiebout equilibrium, with local public services as well as housing and the composite good provided at efficient levels, and with local public services being financed by uniform head taxes per household. The fixed supply of land within a jurisdiction is used either for large houses for “high demanders” or small houses for “low demanders.”
Property taxes on all land and capital within the jurisdiction are then introduced into the model, with the revenues used to reduce the level of head taxation while holding the level of public services per capita fixed. Zoning is also introduced, by assuming that the amounts of land used for large and small houses are fixed. This is a weak version of the approach followed by Hamilton, who assumes fully developed communities and thus precludes any change in land or capital allocated to the two types of housing. Indeed, some form of land use zoning is required for any capitalization to occur since, in the absence of zoning, all land within the jurisdiction would in the long run sell for the same price and there would be no capitalization (Ross and Yinger 1999). In this derivation of the benefit view, housing capital is also assumed to be fixed, as in Hamilton’s analysis.
The effects of introducing property taxes on both housing capital and land in this initial equilibrium are identical to those predicted by Hamilton. First, for large homes, which experience a disproportionately larger increase in property taxes, the resulting negative fiscal differential is fully capitalized into lower housing prices. Similarly, small houses sell at a premium that exactly reflects the negative fiscal differential between total property taxes paid and the associated benefits of the tax change as measured by the reduction in head taxes.
Second, the net change in land values due to capitalization in a heterogeneous jurisdiction is zero; that is, the aggregate amount of the discount in land prices for larger homes equals the aggregate amount of the premium in land prices for smaller homes. Third, the price of each type of housing rises by just enough to offset the cost of the public services that must be financed with property taxes.
To sum up, all of the benefit tax view results obtained by Hamilton are obtained within the context of a partial equilibrium differential tax incidence model of a single taxing jurisdiction that is comprised of households that are homogeneous with respect to demands for public services, but heterogeneous with respect to demands for housing. Once again, capitalization implies that the property tax is a benefit tax. Accordingly, the combination of property tax payments and capitalization effects implies that (1) taxpayers pay for all their local public services; (2) both housing and local public services are consumed at efficient levels; and (3) the property tax results in no redistribution of income.
Capitalization Under the Capital Tax View
Converting this model to accommodate a version of the capital tax view is straightforward. Recall, however, that this approach considers the effects of the property tax from the perspective of a single taxing jurisdiction, which is modeled as a small open economy that faces a perfectly elastic supply of capital. Since the net rate of return to capital is fixed by assumption, the effect of nationwide use of the property tax on the return to capital cannot be analyzed. Nevertheless, within the single taxing jurisdiction framework the effects of the property tax on the allocation of housing capital, as well as the effects of this tax-induced reallocation on all other variables, including the changes in land prices that are the focus of the analysis, can still be derived.
The key distinction between the benefit tax and capital tax views of the property tax is that under the latter approach the stocks of housing capital are not assumed to be fixed (although the zoning assumption of fixed land supplies for the two types of housing is maintained). That is, under the capital tax view, which clearly reflects a relatively long-run view of incidence, households can reduce their housing consumption in response to an increase in the property tax.
Given these assumptions, the implications of the capital tax version of the model are as follows. First, capital flows out of the production of large houses where property taxes are high relative to benefits received, and into the production of smaller homes where the property tax bill is low relative to benefits received. This reallocation of housing capital is an important factor in determining incidence—who ultimately pays the property tax. The analysis shows that land rents unambiguously increase for land used for small houses and decrease for land used for large houses, and it is these changes in land rents that are capitalized into land prices. The key result is that these land value capitalization effects under the capital tax view are precisely the same as those calculated previously under the benefit tax view. Thus, the existence of capitalization does not help resolve the critical issue of whether the benefit view or the capital tax view more accurately describes the incidence and economic effects of the property tax.
The other results derived in Hamilton’s model obtain in this capital tax model as well. The net effect of property tax capitalization on aggregate land value within the taxing jurisdiction is zero. Similarly, the effects of the property tax on housing prices—which rise by an amount just sufficient to offset the value of public services received—are also identical under the two models, implying that housing prices for smaller homes increase proportionately more than prices for larger homes.
Despite this distortion of the allocation of housing capital under the capital tax view, the local effects of use of the property tax still have some very important features that are characteristic of a benefit tax. For example, residents pay for net local public services received (those not financed with head taxes) in the form of higher housing prices. Simultaneously, fiscal differentials are capitalized into land values, so that the net effect of the property tax burden and land value capitalization is that future purchasers of both types of houses effectively pay for what they get in public services.
Thus, the essential difference between the two views of the property tax is that, under the capital tax view, land value capitalization occurs due to capital reallocations across housing types, implying inefficiency in the housing market. Under the benefit tax view, capitalization occurs with respect to fixed housing capital stocks, and there is no distortion of the allocation of housing capital. For example, if a local government finances an increase in public expenditures with additional property taxes, the resulting capitalization effects are the same under both views (and cause the same gains and losses at the time of implementation). However, the capital tax view implies that in the long run housing demands will decline, while housing consumption remains unchanged under the benefit tax view.
My model also shows that under the capital tax view per capita housing consumption declines unambiguously for both types of households, which is the standard result that the property tax causes an inefficient reduction in housing consumption. In addition, the number of households that purchase small houses unambiguously increases, while the net effect on the number of households that purchase large houses is theoretically ambiguous, and the total population in the jurisdiction increases.
Conclusion
This analysis shows that, within the context of a partial equilibrium analytical framework characterized by assumptions typical of the benefit view of the property tax, intrajurisdictional capitalization into land values of fiscal differentials is entirely consistent with, and indeed predicted by, the capital tax view of the property tax. Earlier results demonstrate that interjurisdictional capitalization is also consistent with the capital tax view (Kotlikoff and Summers 1987). Together, these results suggest, counter to the claims of benefit tax proponents, that empirical evidence supporting full capitalization of property taxes in land values—either within or across jurisdictions—provides little if any evidence that allows researchers to distinguish between the capital tax and benefit tax views.
Instead, the key issue is whether the zoning restrictions or other mechanisms stressed by proponents of the benefit tax view are sufficiently binding to preclude the long-run adjustments in housing capital predicted by the capital tax view. This issue promises to be a fertile topic for future research, which may help clarify the answer to the long-standing and critical question of who pays the residential property tax.
George R. Zodrow is professor of economics and Rice Scholar in the Tax and Expenditure Policy Program of the Baker Institute for Public Policy at Rice University in Houston, Texas.
References
Fischel, William A. 2001. Municipal corporations, homeowners and the benefit view of the property tax. In Property taxation and local government finance, Wallace E. Oates, ed., 33–77. Cambridge MA: Lincoln Institute of Land Policy.
Hamilton, Bruce W. 1976. Capitalization of intrajurisdictional differences in local tax prices. American Economic Review, 66 (5): 743–753.
Harberger, Arnold C. 1962. The incidence of the corporate income tax. Journal of Political Economy, 70 (3): 215–240.
Kotlikoff, Laurence J., and Lawrence H. Summers. 1987. Tax incidence. In Handbook of Public Economics, Volume I, Alan J. Auerbach and Martin S. Feldstein, eds., 1043–1092. Amsterdam: North Holland.
Mieszkowski, Peter. 1972. The property tax: An excise tax or a profits tax? Journal of Public Economics 1 (1): 73–96.
Oates, Wallace E. 1969. The effects of property taxes and local public spending on property values: An empirical study of tax capitalization and the Tiebout hypothesis. Journal of Political Economy, 77 (6): 957–961.
Ross, Stephen, and John Yinger. 1999. Sorting and voting: A review of the literature on urban public finance. In Handbook of Regional and Urban Economics, Volume 3, Paul Cheshire and Edwin S. Mills, eds., 2001–2060. Amsterdam: North Holland.
Tiebout, Charles M. 1956. A pure theory of local expenditures. Journal of Political Economy, 64 (5): 416–424.
Zodrow, George R. 2001. Reflections on the new view and the benefit view of the property tax. In Property taxation and local government finance, Wallace E. Oates, ed., 79–111. Cambridge MA: Lincoln Institute of Land Policy.
Zodrow, George R. and Peter Mieszkowski. 1986a. Pigou, Tiebout, property taxation and the under-provision of local public goods. Journal of Urban Economics, 19 (3): 356–370.
———. 1986b. The new view of the property tax: A reformulation. Regional Science and Urban Economics, 16 (3): 309–327
Editor’s note: The Lincoln Institute published a new report on tax increment financing in September, 2018.
Tax increment financing (TIF) is an alluring tool that allows municipalities to promote economic development by earmarking property tax revenue from increases in assessed values within a designated TIF district. Proponents point to evidence that assessed property value within TIF districts generally grows much faster than in the rest of the municipality and infer that TIF benefits the entire municipality. Our own empirical analysis, using data from Illinois, suggests to the contrary that the non-TIF areas of municipalities that use TIF grow no more rapidly, and perhaps more slowly, than similar municipalities that do not use TIF. An important finding is that TIF has different impacts when land use is considered. For example, commercial TIF districts tend to decrease commercial development in the non-TIF portion of the municipality.
Designating a TIF District
The rules for tax increment financing, and even its name, vary across the 48 states in which the practice is authorized. The designation usually requires a finding that an area is “blighted” or “underdeveloped” and that development would not take place “but for” the public expenditure or subsidy. It is only a bit of an overstatement to characterize the “blight” and “but for” findings as merely pro forma exercises, since specialized consultants can produce the needed evidence in almost all cases. In most states, the requirement for these findings does little to restrict the location of TIF districts.
TIF expenditures are often debt financed in anticipation of future tax revenues. The practice dates to California in 1952, where it started as an innovative way of raising local matching funds for federal grants. TIF became increasingly popular in the 1980s and 1990s, when there were declines in subsidies for local economic development from federal grants, state grants, and federal tax subsidies (especially industrial development bonds). In many cases TIF is “the only game in town” for financing local economic development.
The basic rules of the game are illustrated in Figure 1. The top panel shows a land area view of a hypothetical municipality. The area on the western border is designated a TIF district and its assessed value is measured. The lower panel of Figure 1 shows the base-year property values in the TIF (B) and the non-TIF (N) areas. At a later point in time, assessed property values have grown to include the increment (I) in the TIF district and growth (G) in the non-TIF area of the municipality.
Tax increment financing carves out the increment (I) and reserves it for the exclusive use of the economic development authority, while the base-year assessed value (B) stays in the local government tax base. Thus,
Impacts on Overlapping Governments and Non-TIF Areas
The value increment (I) is the tax base of the TIF district. In most states (like Illinois, but unlike Massachusetts) there are multiple overlapping local governments, e.g., the municipality, school district, community college district, county, township, park district, library district, and other special districts. Figure 2 illustrates this situation with the school district representing all the nonmunicipal governments. To understand the economics and politics of TIF, it is crucial to note that while the municipality makes the TIF adoption decision, the TIF area value is part of the tax base of the school district and other local governments as well. Moreover, the TIF district gets revenues from the increment times the combined tax rate for all local governments together. The following hypothetical tax rates for a group of local governments overlapping a TIF district are close to the average proportions in Illinois.
Municipal tax rate = 0.15 %
School district tax rate = 0.60 %
Other governments’ tax rate = 0.25 %
Combined tax rate = 1.00 %
For each 15 cents of its own would-be tax revenues the municipality puts on the line, the school district and other local governments contribute another 85 cents. Thus, there may be an incentive for municipalities to “capture” revenue from growth that would have occurred in the absence of TIF (to collect taxes that would have gone to school districts). Or, municipal decision makers may favor inefficient economic development strategies that do not result in public benefits worth the full cost, since their own cost is only 15 cents on the dollar. TIF proponents would counter that nothing is captured, because the increment to the tax base would not exist “but for” the TIF authority expenditure. That argument, of course, turns on what would have happened to property values in the absence of TIF.
If, as municipalities are often required to assert when they adopt TIF, all of the increment is attributable to the activities of the TIF development authority, then TIF is fair, in that the school district is not giving up any would-be revenues. If, as critics of TIF sometimes assert or assume, none of the increment is attributable to the TIF and all of the new property value growth would have occurred anyway, then the result is just a reallocation of tax revenues by which municipalities win and school districts lose.
The impact of TIF on growth in property values requires a careful reading of the evidence. It is wrong, as those who look only at growth within the TIF district in effect do, to assume to know the answer. Part of the solution is to use appropriate tools to statistically control for other determinants of growth.
It is also necessary to take into account the potential for reverse causality. We want to know the extent to which TIF adoption causes growth. But the causation could go the other way; anticipated growth in property values could lead to TIF adoption if municipalities attempt to capture revenues from overlapping governments. Or there could be reverse causation bias if TIF is adopted in desperation by municipal decision makers in areas where low growth is anticipated. Either way we should ask: Are the municipalities that adopt TIF systematically different from those that do not? If the municipalities are systematically different, we must statistically disentangle the effect of that difference from the effect of the TIF using a technique that corrects for what economists call “sample selection bias.”
Impacts on Growth and Property Values
There are two sides to any government budget: revenues and expenditures. As a revenue-side mechanism, TIF is a way of earmarking tax revenues for a particular purpose, in this case local economic development. The effectiveness of economic development expenditures depends on opportunities, incentives, and planning skills that are specific to each local area and each project. By combining data from a large number of TIF and non-TIF municipalities, we can ask: On average and overall, is TIF adoption associated with increased growth in municipal property values? We have addressed this question in two research studies, both of which use statistical controls for the other determinants of growth and for reverse causation due to sample selection bias.
The first study (Dye and Merriman 2000) uses data from 235 Chicago area municipalities and covers preadoption, TIF adoption (or not), and postadoption time periods. We control for the selection bias (reverse causation) problem by first predicting which municipalities adopt TIF and then using that information (a statistic called the inverse Mills ratio) when estimating the effect of TIF adoption on property values in a second stage. Use of selection bias correction was first applied to the study of TIF by John Anderson (1990) and is now standard practice.
Our estimates of the impact of TIF have a number of additional variables controlling for home-rule status, the combined tax rate, population, income per capita, poverty rate, nonresidential share of equalized assessed value (EAV), EAV per square mile, distance to the Chicago loop, and county of location. We found that property values in TIF-adopting municipalities grew at the same rate as or even less rapidly than in nonadopting municipalities. The study design did not get at this directly, but the offset seemed to come from smaller growth in non-TIF area of the municipality (lower G).
Our findings were a surprise to those, especially nonacademics, who naively had inferred TIF caused growth by observing growth within a TIF district (I) without any statistical controls for the other determinants of growth (in I or G). Our findings were quite threatening to those with an interest in TIF, such as local economic development officers who spend the earmarked funds or TIF consultants who are paid for documenting findings of “blight” or “but for.” Our findings were also at odds with an Indiana study that found a positive effect of TIF adoption on housing values (Man and Rosentraub 1998).
Because our findings were controversial, because the effect of TIF was unsettled in the academic literature, and particularly because we wanted to pursue the possibility of a negative cross relationship between growth in the TIF district (I) and growth outside the TIF district (G), we undertook a second study (Dye and Merriman 2003). In addition we wanted to look at whether there are different TIF effects when more municipalities are included and different types of land uses are considered. We used three different data sets: property value data for 246 municipalities in the six-county Chicago area; less complete property value data for 1,242 municipalities in all 102 Illinois counties; and property value data for 247 TIF districts in the six-county Chicago area.
For the six-county sample (similar to our earlier study, but with more years and more municipalities), Table 1 presents the pre- and postadoption growth rates for the TIF-adopting and nonadopting municipalities. These calculations are from raw data, before any statistical controls for other growth determinants or corrections for selection bias. The first row compares EAV growth rates of the TIF-adopting and nonadopting municipalities in the period before any of them adopted TIF. EAV grew slightly faster for municipalities that would later adopt TIF.
The second row shows that in the period after TIF adoptions took place, gross-of-TIF EAV grew less rapidly for TIF adopters. The last row shows that the net-of-TIF EAV growth rate for TIF adopters was even lower, suggesting that growth (I) in the TIF district may come at the expense of property values outside the development area (G). In summary, if we make no statistical adjustment for the effects of other determinants, TIF adopters grew more slowly than nonadopters.
When we use the more recent six-county data in a multivariate regression model with statistical controls for local characteristics and sample selection, we no longer get the earlier provocative result of a significantly negative impact of TIF adoption on growth, but we still find no positive impact of TIF adoption on the growth in citywide property values. Any growth in the TIF district is offset by declines elsewhere.
The second study was designed with particular attention to land use. The property value data is broken into three land use types: residential, commercial, and industrial. Each TIF district also is identified by one of five development purpose types: central business district (CBD), commercial, industrial, housing, and other or mixed purpose. Thus, we can look separately at growth in municipal EAV by type of land use and type of TIF. Unfortunately, the data do not record EAV by land use within TIF districts, so we must settle for the growth in the tax base that is available to local governments. Most of the estimates of effects by land use type are not significantly different than zero. However, commercial and industrial TIF districts both show a significantly negative impact on growth in commercial assessed values outside the district.
The second study also extends the analysis to all 102 Illinois counties, which results in a much larger sample of municipalities (see Table 2). The TIF-base EAV (B) is unavailable, so we look at growth in available EAV. The simple means from the larger sample again suggest a negative effect of TIF on growth in property values. When we use this all-county sample to estimate the impact of TIF in a multivariate regression with statistical controls for other growth determinants and for TIF selection, there is a significantly negative impact of TIF adoption on growth in overall available (non-TIF) property values. This revives the earlier hypothesis that TIF adoption actually reduces property values in the larger community.
When we run separate regressions for available EAV growth by type of land use for the all-county sample, we see more evidence of a zero or negative impact of TIF on property value growth. Again, there is a significant “cannibalization” of commercial EAV outside the TIF district from commercial development within the TIF district.
The TIF district sample of the second study includes 247 TIF districts in 100 different municipalities in the six-county Chicago area. We match TIF base (B) and TIF increment (I) in each year to information for the host municipality. The key results are:
Conclusion
Tax increment financing is an alluring tool. TIF districts grow much faster than other areas in their host municipalities. TIF boosters or naive analysts might point to this as evidence of the success of tax increment financing, but they would be wrong. Observing high growth in an area targeted for development is unremarkable. The issues we have studied are (1) whether the targeting causes the growth or merely signals that growth is coming; and (2) whether the growth in the targeted area comes at the expense of other parts of the same municipality. We find evidence that the non-TIF areas of municipalities that use TIF grow no more rapidly, and perhaps more slowly, than similar municipalities that do not use TIF.
Policy makers should use TIF with caution. It is, after all, merely a way of financing economic development and does not change the opportunities for development or the skills of those doing the development planning. Moreover, policy makers should pay careful attention to land use when TIF is being considered. Our evidence shows that commercial TIF districts reduce commercial property value growth in the non-TIF part of the same municipality. This is not terribly surprising, given that much of commercial property is retailing and most retail trade needs to be located close to its customer base. That is, if you subsidize a store in one location there will be less demand to have a store in a nearby location. Industrial land use, in theory, is different. Industrial goods are mostly exported and sold outside the local area, so a local offset would not be expected. Our evidence is generally consistent with this prediction of no offset in industrial property growth in non-TIF areas of the same municipality.
Richard F. Dye is a visiting fellow at the Lincoln Institute of Land Policy in 2005–2006. He is also the Ernest A. Johnson Professor of Economics at Lake Forest College, Lake Forest, Illinois, and adjunct professor at the Institute of Government and Public Affairs, University of Illinois.
David F. Merriman is professor of economics at Loyola University of Chicago and adjunct professor at the Institute of Government and Public Affairs, University of Illinois.
References
Anderson, John E. 1990. Tax increment financing: Municipal adoption and growth. National Tax Journal 43: 155–163.
Dye, Richard F., and David F. Merriman. 2000. The effects of tax increment financing on economic development. Journal of Urban Economics 47: 306–328.
———. 2003. The effect of tax increment financing on land use, in Dick Netzer (ed.), The property tax, land use, and land-use regulation. Cheltenham, UK: Edward Elgar, 37–61.
Dye, Richard F., and Jeffrey O. Sundberg. 1998. A model of tax increment financing adoption incentives. Growth and Change 29: 90–110.
Johnson, Craig L., and Joyce Y. Man (eds.). 2001. Tax increment financing and economic development: Uses, structures and impact. Albany: State University of New York Press.
Man, Joyce Y., and Mark S. Rosentraub. 1998. Tax increment financing: Municipal adoption and effects on property value growth. Public Finance Review 26: 523–547.
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Although property taxes continue to be a fundamental and important revenue source for local government, they also remain exceptionally controversial. Still, the topic of property taxation seems to be one for which improved education and understanding is especially necessary.
Public policy changes often have unintended consequences—side effects, feedback effects, benefits to individuals not in the target group, unexpected costs, perverse incentives, new opportunities to game the system, and the like. Early experiences with assessment limitation measures reveal an unanticipated result: some property owners seemingly targeted to benefit from lower assessments may be harmed instead.
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The property tax is, in my view, a good local tax, though it is far from perfect. Relative to the other tax bases available to local government, I think the property tax gets high marks, in spite of some telling but, in part, misplaced criticism.
Traditional Tax Theory
Public finance economists have historically evaluated taxes in terms of their efficiency properties, their incidence and their ease of administration. From the perspective of economic efficiency, the basic issue is the extent to which a tax introduces distortions into the economic system, thereby creating an “excess burden” in addition to the basic burden of payment of the tax. On this matter, there is currently a lively controversy. On one side, Bruce Hamilton, William Fischel and others argue (persuasively, I believe) that local property taxation, in conjunction with local zoning ordinances, produces what is effectively a system of benefit taxation that promotes efficient location and fiscal decisions on the part of households. On the opposing side, Peter Mieszkwoski and George Zodrow view local tax differentials much like excise taxes, which have a distorting effect on local decisions and tend to discourage the use of capital. Thus, the case for property taxation purely on efficiency grounds is not altogether clear (although it probably gets better marks than other available tax bases aside from user charges).
As to the incidence of the tax, the older view of the property tax, which saw it simply as an excise tax on housing and business structures, suggested that it was a regressive tax: housing expenditure, it was claimed, took a larger fraction of income from poorer rather than from wealthier households. Later studies of the income elasticity of demand for housing cast some doubt on this proposition. The finding that housing expenditure is roughly proportional to permanent income suggested that property taxation was something more akin to a proportional tax relative to income.
The more recent and so-called “new view” of the property tax sees the average tax rate across communities as essentially a tax on capital; as such, it is likely to be quite progressive in its incidence. The differentials across communities are another matter: they may function like excise taxes on specific factors, but overall this approach suggests that the property tax is likely to be a good deal more progressive than, say, a sales tax. The third issue, the administration of the property tax, raises one troublesome matter. Since housing units are sold only infrequently, tax liabilities must be based on an estimated or “assessed” value. The vagaries of assessment practices have been the source of some unhappiness with the tax, as the ratio of assessed value to true market value can sometimes vary widely within a single taxing jurisdiction. Reforms and improvement of assessment practices, however, have gone some distance in mitigating this problem.
A Public-Choice Perspective
The public-choice approach to issues in public finance has focused attention on another dimension of tax systems: their role in promoting effective decision making in the public sector. In this framework, a critical function of a tax system is to provide an accurate set of signals, or “tax-prices,” that make clear to local taxpayer-voters the costs of public programs on which they must make decisions. In a local context, this implies that the local tax system should generate tax bills that are highly visible and that provide a reasonable indication of costs so that individuals have a clear sense of the financial commitment implied by proposed programs of public expenditure. If taxes are largely hidden or don’t reflect the cost of local services, they are unlikely to provide the information needed for good fiscal decisions. For example, if a local government were to finance its budget through a local corporation income tax, the residents would have little idea of the true cost of local public programs to their household. Hidden taxes with uncertain incidence are not conducive to good fiscal choices. From this vantage point, the local property tax comes off quite well as a source of local revenues. Property tax bills are highly visible and they promote a high degree of voter awareness of the cost of local programs. In fact, local property tax rates are often tied directly to proposed programs on which the voters must decide in a local referendum. It is this high degree of visibility that, I think, explains much of the unpopularity of the tax!
The local property tax thus appears to function well in its public-choice role of providing a reasonably accurate set of tax-prices to residents. There is, however, one important reservation here: renters. Owner-occupants receive regular property tax bills that indicate the cost to them of the local services they receive, but occupants of rental dwellings receive no such tax bills. Under the present administration of the property tax, tax bills go to the owner of the unit, not the occupant, so that renters never see the exact amount of property tax assessed on their residence. This does not, of course, mean that renters avoid the burden of the property tax. There is good reason to believe that property taxes on rental units are (eventually at least) shifted onto tenants. The point is that renters do not face the same visible tax-prices that confront owner-occupants.
Moreover, there is considerable evidence to suggest that renters behave as if they think they pay no local property taxes. They appear to provide much more support for public expenditure programs than they would if they owned their own homes and knew exactly what they paid in property taxes. The impact of this “renter illusion” on local public budgets needs to be studied further. If it is large, there may be a strong case for reforming the administration of the tax so that property tax bills go directly to occupants rather than to landlords.
Interjurisdictional Fiscal Inequality
Over the past three decades, systems of local property taxation have been the subject of intense public attack accompanied in some instances by court decisions requiring their replacement or reform. The basis for these attacks is primarily an equity issue arising from disparities in the size of the tax base across different localities. In several states, the system of school finance, based on local property taxes, has been declared unconstitutional because of the sometimes large differences in the property tax base per pupil across local school districts; this can result in large differences in per-pupil expenditure. A little reflection, however, suggests that this problem of disparities is not a problem intrinsic to the property tax per se. It is really a result of virtually any system that relies heavily on local taxation. A system of local sales or income taxes, for example, would surely involve major disparities in tax bases across local jurisdictions-probably at least as large as those associated with local property taxes.
The basic point is that fiscal and other economic conditions vary across local areas. (This, incidentally, is a major rationale for local finance: to cater to these differences!) Thus, taxable resources at the local level are bound to vary significantly across jurisdictions. We may well wish to provide additional support to fiscally weak jurisdictions through some kind of intergovernmental fiscal assistance, but this will be true whether local tax systems rely on property taxation or some other local tax base.
Alternative Local Tax Bases
Two major tax bases offer themselves as alternatives: sales taxes and income taxes. Both, however, have serious shortcomings as the primary source of tax revenues in a nation of many small local governments.
The base of a local sales tax is likely to vary dramatically across local jurisdictions. Communities that are largely residential would have small bases and would have to set a relatively high rate to generate the requisite revenues. Significant sales tax differentials would give rise to costly trips among jurisdictions, as consumers seek to purchase goods and services in jurisdictions with low tax rates. Moreover, sales taxes do not get very good marks on a fairness or ability-to-pay criterion. In addition, they do not stack up at all well on the public-choice criterion of providing the electorate with accurate and visible signals of the costs of public programs. Income taxes have a good deal more appeal on equity grounds, although most state and local income taxes are not very progressive. They also have the advantage of visibility. But, like sales taxes, they encounter the mobility problem to some extent. A jurisdiction that opts for relatively high income tax rates runs the risk of deterring the entry of new households, especially those with above-average incomes that would face relatively large tax payments.
More generally, there is something to be said for avoiding excessive reliance in the economy as a whole on a single tax instrument. The federal and many state governments rely on income taxation as a primary source of revenue, and there is considerable concern that marginal tax rates on income have become sufficiently high to discourage various sorts of productive activity. From this perspective, local government may contribute to an improved overall tax system by avoiding heavy use of income taxation and staying instead with the revenue source that has been historically its own-the property tax.
The other appealing source of local revenues is user fees, which represent a form of benefit taxation and provide almost a kind of market test for the provision of the service. The problem is that they are limited in their application. It may be possible to charge for the use of certain public services like refuse collection, but it is much more difficult to employ charges for collectively consumed services like police protection and local roads. Fees can be used to finance a limited number of local services, but they cannot supplant the need for a major local tax.
For local fiscal choice to have real meaning, it is essential that local residents bear the costs of their decisions to adjust levels of local services. The populace must be in a position to weigh the benefits of public programs against their costs. For this to occur, local governments must have their own revenue systems with some discretion over tax rates. There is surely some scope for mitigating fiscal disparities across jurisdictions with an appropriately designed system of equalizing intergovernmental grants. However, the grants must not be so large as to undermine local fiscal autonomy, and they should, in principle, be lump-sum in form so that localities bear the cost of their fiscal decisions at the margin.
The question here is which of the available tax bases offers the greatest promise for effective local fiscal decision making. In my view, it is the property tax.
Wallace E. Oates is professor of economics at the University of Maryland and University Fellow at Resources for the Future in Washington, D.C. He is also a member of the Lincoln Institute Board of Directors. This article is adapted from a longer paper that he prepared for the Institute’s Fall 1998 Chairman’s Roundtable on property taxation and that he also presented as the Founder’s Day Lecture in January 1999. The original paper will be published in the Institute’s 1999 Annual Review.
References
Fischel, William. “Property Taxation and the Tiebout Model: Evidence for the Benefit View from Zoning and Voting,” Journal of Economic Literature 30 (March 1992): 171-7.
Hamilton, Bruce W. “Capitalization of Intrajurisdictional Differences in Local Tax Prices,” American Economic Review 66 (Dec. 1976): 743-53.
Mieszkowski, Peter, and Zodrow, George R. “Taxation and the Tiebout Model: The Differential Effects of Head Taxes, Taxes on Land, Rents, and Property Taxes,” Journal of Economic Literature 27 (Sept. 1989): 1098-1146.
Oates, Wallace E. “On the Nature and Measurement of Fiscal Illusion: A Survey,” in G. Brennan et al., eds., Taxation and Fiscal Federalism (Sydney: Australian National University Press, 1988): 65-83.
—. “The Theory and Rationale of Local Property Taxation,” in Therese J. McGuire and Dana Wolfe Naimark, eds., State and Local Finance for the 1990’s: A Case Study of Arizona (Tempe, Arizona: School of Public Affairs, Arizona State University, 1991): 407-24.
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Históricamente, las comunidades con alta concentración de instituciones sin fines de lucro, como hospitales, universidades y museos, han tenido que enfrentar problemas fiscales debido a la menor base gravable por la presencia de estas propiedades exentas de impuestos.
Para Boston, Massachusetts, este impacto ha sido particularmente severo, dada la preponderancia de propiedades exentas de impuestos combinada con una gran dependencia del impuesto sobre la propiedad para sus ingresos municipales. A partir de la década de 1970, Boston comenzó a solicitar pagos de sus organizaciones sin fines de lucro como una manera de compensar la pérdida de ingresos y la creciente demanda de servicios públicos asociadas con las instituciones que alberga en su seno.
Si bien estos pagos en lugar de impuestos (Payments in Lieu of Taxes, o PILOT) se han ido ampliando a lo argo del tiempo, la ciudad de Boston permanecía insatisfecha con su programa PILOT. Los ingresos del programa PILOT representaban una pequeña parte del presupuesto general de la ciudad, y el tamaño de las contribuciones de las instituciones sin fines de lucro ha sido muy variable. Desde 2008, Boston ha desarrollado e implementado una nueva estrategia para su programa PILOT que ha recibido considerable atención a nivel nacional. Este artículo examina las condiciones que condujeron al desarrollo de un nuevo programa PILOT en Boston, describe su estrategia e informa sobre la experiencia de la ciudad en su primer año 1completo de implementación.
Restricciones sobre la base imponible de Boston
Tradicionalmente Boston ha estado en el centro de todos los debates acerca de los programas PILOT. La confluencia de varias fuerzas políticas, fiscales y demográficas ha creado una mezcla volátil para la ciudad y sus instituciones sin fines de lucro. Boston es el centro económico y cultural de Nueva Inglaterra y alberga algunos de los hospitales y universidades más renombrados del mundo. Como capital del estado de Massachusetts, Boston también cuenta con una gran cantidad de edificios y establecimientos gubernamentales. Uno de sus desafíos más inusuales es su pequeño tamaño geográfico en comparación con su área metropolitana. Boston es la vigesimo-segunda ciudad más grande por población, pero representa la décima más grande por área metropolitana. En consecuencia, las instituciones exentas del pago de impuestos que prestan servicio a toda el área metropolitana están concentradas dentro de los límites relativamente pequeños de la ciudad. De hecho, más del 50 por ciento de la superficie de Boston está exento del pago de impuestos (figura 1).
Boston también tiene una estructura de ingresos que es única entre las demás ciudades de su envergadura, principalmente porque no cobra impuestos sobre los ingresos, nóminas, ventas ni ninguna otra fuente de ingresos significativa. En lugar de ello, Boston depende en gran medida del impuesto sobre la propiedad, que representa dos tercios de todos los ingresos de la ciudad (figura 2). Si bien Nueva York y Chicago también cuentan con una gran cantidad de propiedades institucionales exentas del impuesto sobre la propiedad, estas ciudades sí aplican tributos sobre los ingresos, las ventas y otras actividades económicas generadas por las universidades, los hospitales y otras instituciones de gran envergadura sin fines de lucro. En contraste, Boston no recibe ningún ingreso directo de la actividad económica generada por este vibrante sector sin fines de lucro.
Más aún, el crecimiento del impuesto sobre la propiedad en Boston está restringido por las cláusulas de la Propuesta 2½, que impone un límite legal sobre el nivel de los impuestos sobre la propiedad. La limitación más significativa es que el valor de dicho impuesto en las propiedades existentes sólo puede aumentar un 2,5 por ciento por año. El otro límite importante de la Propuesta 2½ es que la tasa global efectiva del impuesto no puede superar el 2,5 por ciento de la valuación fiscal de la propiedad. La tasa de Boston, 1,8 por ciento, está muy por debajo de este límite, de manera que esta cláusula no influye tanto como en otras comunidades de Massachusetts en lo que se refiere a las propiedades exentas del pago de impuestos. El impacto combinado de la concentración de propiedades exentas de impuestos, el alto grado de dependencia del impuesto sobre la propiedad, y los límites al crecimiento de este tributo debido a la Propuesta 2½ ha dado como resultado un impacto fiscal más profundo en Boston que en la mayoría de las otras ciudades.
Conciliación de los beneficios y costos de las instituciones sin fines de lucro
A pesar de estos impactos fiscales, Boston tiene afortunadamente un vibrante sector sin fines de lucro. La ciudad alberga a algunos de los hospitales y universidades más prestigiosos del mundo, que brindan atención sanitaria, investigación y educación excepcionales a sus clientes. Además de cumplir con sus misiones caritativas, estas instituciones de gran envergadura generan un nivel significativo de actividad económica, que constituye la espina dorsal de la economía de Boston, basada en el conocimiento. La industria de atención a la salud por sí sola genera 125.000 puestos de empleo en Boston.
Hay una desconexión económica, sin embargo, entre los beneficios brindados por las instituciones sin fines de lucro y el costo de eximir sus propiedades del pago de impuestos. Los beneficios de las instituciones sin fines de lucro de Boston no se circunscriben a los límites de la ciudad; los beneficios educativos, científicos y culturales se extienden a la región, al estado, al país y, en muchos casos, al mundo entero. No obstante, el costo de proporcionar servicios públicos a estas instituciones y la pérdida de ingresos debido a las exenciones del pago de impuestos recaen exclusivamente sobre los contribuyentes de Boston.
Este punto es crítico para comprender la importancia del programa PILOT para una ciudad como Boston. Muchos observadores creen que el interés actual en PILOT se debe a los problemas fiscales de corto plazo asociados con la reciente recesión. De acuerdo a esta corriente de opinión, una vez que la economía se recupere y las perspectivas municipales se aclaren, la presión por implementar programas PILOT disminuirá. La experiencia de Boston contradice esta aseveración. La ciudad ha lidiado con el impacto fiscal causado por su sector sin fines de lucro durante un largo período de tiempo, tanto en situaciones fiscales buenas como malas. Hay una desconexión fundamental entre los beneficios institucionales y los costos fiscales y, en última instancia, es aquí donde reside el origen de este debate. Hasta que estos beneficios y costos se concilien, la tensión financiera entre la ciudad y sus instituciones sin fines de lucro continuará.
Cómo medir el impacto fiscal de las propiedades exentas del pago de impuestos
El impacto de las propiedades exentas del pago de impuestos sobre la ciudad en su conjunto, ha sido desde hace tiempo el centro de un acalorado debate en Boston. Una pregunta frecuentemente planteada es la de cuánto pagarían las instituciones sin fines de lucro en caso de que sus propiedades fueran plenamente gravables. Durante mucho tiempo esta pregunta no pudo responderse. Como las propiedades exentas no pagaban impuestos sobre la propiedad, la ciudad tenía muy poco incentivo para mantener datos y valuaciones exactas y al día de las propiedades institucionales. No obstante, el interés constante del impacto fiscal de las propiedades exentas exigió que se diera respuesta a esta pregunta.
Dada la escasez de recursos disponibles para iniciar un proyecto de valuación de las propiedades exentas, Boston tuvo que recurrir a métodos creativos para generar valuaciones confiables, minimizando al mismo tiempo el costo de recopilación de datos. La ciudad contaba con un tipo particular de declaración de impuestos que las instituciones sin fines de lucro tienen que presentar todos los años, como también amplia autoridad legal para solicitar a los dueños de estas propiedades los datos necesarios para valuar sus propiedades.
Boston pudo utilizar estas herramientas para recopilar información detallada sobre las propiedades de las instituciones sin fines de lucro, en particular sus características físicas (superficie, edad, condición) y el uso dado a las mismas. La mayoría de las instituciones principales cuenta con datos exactos sobre sus propiedades. Una vez que los tasadores tuvieron acceso a estos datos, pudieron introducir la información en el sistema de valuación masiva asistida por computadora (computer-assisted mass appraisal, o CAMA) de la ciudad para determinar su valuación. Se realizaron después inspecciones de los predios para verificar la información proporcionada por las instituciones y comprobar la exactitud y fiabilidad de las valuaciones generadas por el sistema CAMA.
Las valuaciones resultantes se compartieron luego con las instituciones. Se entregó a cada una de ellas los detalles de las estimaciones de valuación de sus bienes inmuebles, y se les dio la oportunidad de reunirse con los tasadores para revisar los resultados y exponer cualquier duda al respecto. La ciudad incorporó los comentarios de las instituciones para completar la valuación final de las propiedades. Dado que este fue el primer intento que hizo la ciudad para generar valuaciones de las propiedades sin fines de lucro, esta revisión conjunta resultó valiosa para verificar la calidad de los datos, y también permitió compartir los resultados preliminares del impacto sobre los ingresos municipales de las propiedades exentas de cada institución.
El análisis, completado en 2009, reveló que las propiedades de instituciones educativas y médicas exentas del pago del impuesto hubieran generado US$347,9 millones en ingresos si fueran gravables (Ciudad de Boston, 2010). Para poner este monto en perspectiva, hubiera sido el equivalente a aproximadamente un cuarto de todos los gravámenes tributarios de la ciudad en el año fiscal 2009, que ascendieron a US$1.400 millones, y a aproximadamente la mitad de los ingresos generados por las propiedades de oficina, comercios minoristas y hoteles que pagan tributos comerciales (figura 3).
Comité de trabajo del programa PILOT
Una vez que se utilizó la información de las valuaciones para determinar la cantidad de impuestos que cada institución pagaría si no estuviera exenta, se descubrieron varias deficiencias del programa PILOT actual. Si bien el programa anterior fue considerado uno de los más exitosos programas PILOT del país, la cantidad de ingresos recaudados fue pequeña comparada con los ingresos que las propiedades exentas hubieran generado si fueran gravables. Los pagos PILOT de instituciones educativas y médicas en 2009 ascendieron a US$14,5 millones, o sea un 4,2 por ciento de lo que las instituciones hubieran pagado si las propiedades fueran gravables, y solo un 1 por ciento de los gravámenes tributarios totales de la ciudad. Además, el nivel de participación varió mucho entre las distintas instituciones. Algunas instituciones realizaron contribuciones sustanciales bajo el programa, mientras que otras realizaron pagos limitados o decidieron no participar en absoluto.
Para resolver estos problemas, el alcalde de Boston, Thomas M. Menino, nombró un comité de trabajo que revisara el programa PILOT con la petición de:
El comité de trabajo del programa PILOT estuvo compuesto por una amplia gama de participantes: dos líderes de universidades locales, dos de hospitales sin fines de lucro, y dos de la comunidad empresarial de Boston además de un representante del concejo municipal, uno de los sindicatos del sector público y otro de las organizaciones comunitarias. El comité de trabajo se reunió a lo largo dos años para explorar tanto los beneficios como los costos para Boston de albergar a sus instituciones sin fines de lucro, y cómo se deberían considerarse estos factores en el proceso del programa PILOT. Uno de los puntos clave del debate fue cómo asegurar que las instituciones contribuyeran al programa sobre una base consistente. En diciembre de 2010, el comité de trabajo recomendó al alcalde Menino las siguientes pautas para el programa PILOT.
El programa PILOT debería seguir siendo voluntario
Los miembros del comité de trabajo se persuadieron de que una exigencia legal o legislativa de participar en el programa PILOT iría en contra del espíritu de alianza entre la ciudad y sus instituciones sin fines de lucro. Esta alianza es crítica para alentar una participación amplia y uniforme.
Todas las instituciones sin fines de lucro deberían participar
Gran parte del debate sobre PILOT se había concentrado anteriormente en los hospitales y las universidades. El comité de trabajo, sin embargo, propuso que todas las instituciones sin fines de lucro que poseían bienes inmuebles exentos del pago de impuestos en Boston deberían contribuir al programa PILOT. Para proteger a las instituciones más pequeñas con menos recursos, el programa PILOT se limitó a aquellas cuyas propiedades se habían valuado en más de US$15 millones.
Cómo deter minar los pagos del programa PILOT
Se consideraron muchas alternativas para establecer las bases de contribución del programa PILOT, incluida la consideración de una cuota por estudiante o cama de hospital, o de un cargo proporcional a la superficie de suelo o superficie edificada. El comité de trabajo determinó que la manera más equitativa sería la de un cargo proporcional al valor de las instituciones en su totalidad, lo cual reflejaría su tamaño y de la calidad de sus propiedades inmuebles. Hubo un consenso general en que las instituciones sin fines de lucro deberían contribuir con el monto necesario para compensar su consumo de servicios esenciales, como protección policial y servicio de bomberos, y de servicios públicos, como limpieza de calles y remoción de nieve. Estos servicios consumen aproximadamente un 25 por ciento del presupuesto de Boston, y el comité de trabajo determinó entonces que una contribución al programa PILOT del 25 por ciento del monto tributable total de la institución sería razonable.
Crédito por beneficios a la comunidad
El beneficio público proporcionado por las instituciones sin fines de lucro fue un punto central del comité de trabajo, el cual recomendó que estas instituciones recibieran un crédito de hasta el 50 por ciento en sus contribuciones al programa PILOT por los beneficios brindados a la comunidad. Este crédito reconocía las contribuciones significativas en servicios efectuadas por las instituciones sin fines de lucro, los cuales benefician directamente a los residentes de Boston. El monto del crédito se limitó al 50 por ciento de las contribuciones al programa PILOT para asegurar que las instituciones pagaran un monto significativo en dinero. No obstante, el comité de trabajo expresó que, en caso de presentarse una oportunidad excepcional para un cierto programa o servicio, este límite del 50 por ciento podría excederse a discreción de la ciudad.
Si bien el comité de trabajo no ofreció detalles específicos sobre los servicios que podrían hacerse acreedores a un crédito en el programa PILOT, proporcionó pautas generales sobre los tipos de servicios que serían elegibles. Para ello, los servicios comunitarios deben beneficiar directamente a los residentes de la ciudad de Boston, respaldar la misión y las prioridades de la ciudad, ofrecer maneras de colaboración entre la ciudad y las instituciones sin fines de lucro para alcanzar metas comunes, y ser cuantificables.
Período de introducción
Finalmente, el comité de trabajo recomendó que la nueva fórmula del programa PILOT se introdujera a lo largo de un período no menor de cinco años. Dado el cambio en el alcance del programa PILOT de la ciudad, el comité de trabajo entendió que las instituciones iban a requerir tiempo para realizar todos los ajustes necesarios en sus presupuestos y planes financieros para adaptarse a las mayores contribuciones del programa PILOT.
Implementación del nuevo programa PILOT
Cuando el alcalde Menino aceptó las recomendaciones del comité de trabajo en diciembre de 2010, la ciudad tuvo que elaborar un plan para implementar el nuevo programa PILOT. Primero se enviaron cartas a todas las instituciones que cumplían con los criterios del programa. Cada carta incluyó una copia de las nuevas pautas del programa PILOT y un análisis detallado del cálculo del monto que la ciudad iba a solicitar con la nueva fórmula. La carta también indicó que la ciudad iba a solicitar una reunión con cada institución en los meses siguientes para intercambiar ideas sobre el nuevo programa.
Estas reuniones fueron un paso fundamental en la implementación del programa, al brindar un foro para que cada institución pudiera hacer preguntas sobre el programa y expresar sus preocupaciones. Si bien estas sesiones fueron diseñadas originalmente para proporcionar información a las instituciones sobre el nuevo programa, también sirvieron para que la ciudad recogiera las opiniones de las instituciones, lo cual a su vez sirvió de guía para la puesta en marcha del programa.
El anterior programa PILOT de la ciudad incluía contratos que fijaban los términos del compromiso de cada institución con el programa PILOT. Si bien los contratos eran útiles como referencia, su valor como instrumento legal era cuestionable, ya que los pagos del programa PILOT seguían siendo voluntarios. Por ejemplo, la ciudad nunca intentó forzar pagos bajo los términos de un contrato PILOT. Cuando la ciudad tuvo que decidir usar o no contratos en el programa nuevo, la perspectiva de negociar, escribir y ejecutar más de 40 contratos con las distintas instituciones resultó abrumadora. Dado que las pautas ya proporcionaban los detalles de la participación solicitada a cada institución, la ciudad decidió usar estos documentos como referencia en su relación con las instituciones y obvió la necesidad de elaborar contratos individuales.
Experiencia del primer año del programa
En octubre de 2011 se enviaron las solicitudes de pago de las primeras cuotas para el año fiscal 2012 a todas las instituciones participantes, y los resultados fueron sorprendentes. La ciudad recaudó un total de US$19,5 millones en pagos en efectivo, un aumento del 28,4 por ciento sobre la recaudación del año fiscal 2011, realizada según el programa PILOT anterior. Esto monto superó el 90 por ciento de lo solicitado por la ciudad, reflejando un nivel de participación extraordinario en este primer año de un programa nuevo y voluntario (figura 4). Boston también recibió un nivel equivalente de contribuciones en servicios comunitarios provistos por las instituciones sin fines de lucro, en línea con las pautas del programa PILOT.
Un componente clave del éxito inicial del programa fue el énfasis en promover un espíritu de alianza entre la ciudad y sus instituciones. Debido a su experiencia previa, la ciudad comprendió que una actitud de confrontamiento no sería efectiva en el corto o largo plazo. Al mismo tiempo, las instituciones tuvieron que reconocer que, en su calidad de organizaciones caritativas, debían rendir cuentas a las comunidades que las albergaban. Esta rendición de cuentas fue facilitada en parte por el alto grado de transparencia del proceso. Las reuniones del comité de trabajo fueron abiertas al público, y los materiales utilizados en las deliberaciones fueron publicados en el sitio web de la ciudad.
Este tema de transparencia continuó en la fase de implementación del programa. La información con el detalle de la participación de cada institución en el programa, los pagos en efectivo y los servicios comunitarios provistos también se publicaron en el sitio web de la ciudad. Las instituciones que no participaron plenamente del programa también tuvieron la oportunidad de comunicar sus razones. También se divulgaron detalles específicos sobre los servicios comunitarios proporcionados por las instituciones, lo que les ofreció una oportunidad para destacar y promover sus valiosas contribuciones de servicio.
La importancia de los servicios comunitarios
En sus intercambios con los líderes de las instituciones sin fines de lucro durante la implementación del nuevo programa, la ciudad descubrió que las instituciones tenían una clara preferencia por brindar servicios comunitarios en vez de hacer pagos en efectivo. Dado que los servicios son parte esencial de las misiones caritativas de la mayoría de las instituciones sin fines de lucro, esto no fue una sorpresa. Por otro lado, la ciudad generalmente prefiere los pagos en efectivo, ya que le otorgan flexibilidad para asignar recursos para satisfacer las necesidades más prioritarias de la comunidad.
Para conciliar estas dos preferencias divergentes, la ciudad ha reconocido que tiene que seguir desarrollando su capacidad para alinear la porción de servicios del programa PILOT con sus propias demandas de servicio. En la actualidad, las instituciones ofrecen sus beneficios comunitarios por iniciativa propia. Si bien estos servicios tienen valor para la ciudad y sus residentes, quizás no estén entre las prioridades actuales de servicios de la ciudad. Aun en casos en que las solicitudes específicas de servicios surgieron de un funcionario municipal para satisfacer una necesidad de corto plazo, tales solicitudes ad hoc carecen del proceso de priorización y revisión propio de un presupuesto disciplinado.
Se deberían planificar y priorizar las solicitudes de servicios para el programa PILOT para maximizar su valor para la ciudad. Bajo una estructura de servicios de este tipo, la ciudad podría quizá reducir o reemplazar el costo de ofrecer un servicio, o quizá podría brindar un servicio nuevo para cumplir con una necesidad que no había podido satisfacer previamente. Por medio de una planificación cuidadosa, el direccionamiento de recursos institucionales hacia áreas de prioridad reduce el compromiso financiero de la ciudad y permite que la ciudad obvie los pagos en efectivo a cambio de servicios institucionales, que dichas entidades prefieren. Este proceso de planificación también beneficia a las instituciones, ya que pueden planificar mejor sus compromisos de servicio al programa PILOT. Mientras el programa continúa en su fase de introducción, será fundamental que la ciudad y las instituciones puedan trabajar en forma cooperativa en una estrategia estructurada de servicios comunitarios para que continúe con éxito.
Conclusiones
El proceso seguido por Boston para construir su nueva estrategia para el programa PILOT ha sido tanto cuidadoso como inclusivo. Los conocimientos y las perspectivas de los miembros del comité de trabajo, junto con las décadas de experiencia de la ciudad sobre el tema de propiedades exentas del pago de impuestos, han podido generar pautas reconocidamente equitativas y razonables. El proceso también demostró que para que un programa PILOT sea exitoso, la ciudad y las instituciones tienen que ser socios, no combatientes.
Esta filosofía ha sido la base de la implementación del nuevo programa PILOT en Boston. Sin embargo, a pesar de su éxito inicial, queda mucho por realizar. La ciudad tiene que equilibrar su necesidad de ingresos con la preferencia de las instituciones por brindar servicios. Si los funcionarios municipales y las instituciones locales pueden seguir colaborando en el programa PILOT, se podrá alcanzar un equilibrio que beneficiará tanto a las instituciones como a sus clientes y los residentes de Boston.
Sobre el autor
Ronald W. Rakow ha sido comisionador del Departamento de Valuación de la Ciudad de Boston desde 1992, y en 2011 asumió también el cargo de Subgerente de Finanzas. Fue nombrado en 2010 miembro de la Junta Directiva de la Autoridad del Centro de Convenciones de Massachusetts y en la actualidad es presidente del Comité de Investigación de la Asociación Internacional de Tasadores (International Association of Assessing Officers, o IAAO).
Referencias
Ciudad de Boston. 2010. Informe final y recomendaciones del comité de trabajo del alcalde sobre el programa PILOT, diciembre.
Departamento de Valuación de la Ciudad de Boston. 2009. Análisis de propiedades exentas del pago de impuestos. Instituciones educativas y médicas. Año fiscal 2009.
Departamento de Valuación de la Ciudad de Boston. 2012. Reseña del programa PILOT, año fiscal 2012. http://www.cityofboston.gov/Images_Documents/FY12_Second_Half_PILOT_Status_Report_for_Web_tcm3-33007.pdf
Oficina de Gestión de Presupuesto de la Ciudad de Boston. 2012. Presupuesto adoptado para el año fiscal 2013. http://www.cityofboston.gov/budget/default.asp
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Correction: Under the heading “Experience from the First Year,” the percent increase in FY2012 over what was collected in FY2011 under the previous PILOT program was incorrectly reported. The correct percentage is 28.4. Both the PDF and text version below list the correct amount.
Historically communities with high concentrations of nonprofit institutions such as hospitals, colleges, and museums have struggled with the reduced tax base associated with these tax-exempt properties. For Boston, Massachusetts, the preponderance of tax-exempt property, combined with a high reliance on the property tax for local revenue, has made this impact particularly acute. Beginning in the early 1970s, Boston began seeking payments from its nonprofit organizations as a way of offsetting the loss of revenue and the increase in public service demands associated with the institutions it hosts.
Although these payments in lieu of taxes (PILOTs) expanded over time, the City of Boston remained dissatisfied with its PILOT program. The revenue from PILOTs represented a small fraction of the city’s overall budget, and the size of contributions from nonprofit institutions varied widely. Since 2008 Boston has developed and implemented a new approach to PILOTs that has received considerable national attention. This article examines the conditions that led to the development of Boston’s new PILOT program, describes its approach, and reports on the city’s experience in its first full year.
Constraints on Boston’s Tax Base
Boston traditionally has been at the center of any discussion regarding PILOTs. The confluence of several political, fiscal, and demographic forces has created a volatile mix for the city and its nonprofit institutions. Boston is the economic and cultural center of New England and is home to some of the world’s most renowned hospitals and universities. As the state capital of Massachusetts, Boston also hosts a large number of government office buildings and facilities. Among its more unusual challenges is the city’s small geographic size in relation to its metropolitan area. Boston is the 22nd largest city by population, but it represents the 10th largest metropolitan area. As a result, exempt institutions that service the entire metropolitan area are concentrated within the city’s relatively small boundaries. In fact, over 50 percent of Boston’s land area is exempt from taxation (figure 1).
Boston also has a revenue structure that is unique among its large-city peers, primarily because it has no income, payroll, sales, or other significant source of tax revenue. Instead, Boston relies heavily on the property tax, which represents two-thirds of all city revenue (figure 2). While New York or Chicago also have large amounts of institutional property exempt from the property tax, those cities are able to tax the incomes, sales, and other economic activity which the universities, hospitals, and other large nonprofit institutions generate. In contrast, Boston receives no direct compensating revenue associated with the economic activity that is generated by its vibrant nonprofit sector.
Further, the growth of the property tax in Boston is constrained by Proposition 2½, a statutory limit on the level of property taxes. The most significant limitation is that the property tax levy for existing properties can increase by only 2.5 percent per year. Proposition 2½’s other primary limitation is a cap on the overall effective tax rate of 2.5 percent. As Boston is well below this limit at 1.8 percent, the impact of exempt property is not a factor for this provision as it is in other Massachusetts communities. The combined impact of the concentration of exempt property, the high reliance on the property tax, and the limits placed on property tax growth by Proposition 2½ result in a more profound fiscal impact of exempt property in Boston than in most major cities.
Reconciling the Benefits and Costs of Nonprofit Institutions
Despite these fiscal impacts, Boston is fortunate to have a vibrant nonprofit sector. The city hosts some of the world’s most prestigious hospitals and universities that provide exceptional health care, research, and education to their clients. In addition to fulfilling their charitable missions, these large institutions are significant economic generators that form the backbone of Boston’s knowledge-based economy. The health care industry alone accounts for 125,000 jobs in Boston.
There is an economic disconnect, however, between the benefits of nonprofit institutions and the costs of providing their properties with tax exemptions. The benefits of Boston’s nonprofits do not stop at the city’s borders; the educational, scientific, and cultural benefits of Boston’s institutions accrue to the region, state, country and, in many cases, the entire world. Yet the cost of providing public services to these institutions and the loss in revenue from removing their properties from the tax base fall squarely on Boston’s taxpayers.
This point is critical to understanding the importance of PILOTs to a city like Boston. Many observers believe that the current interest in PILOTs is driven by the short-term fiscal stress associated with the recent recession. According to this school of thought, once the economy recovers and the municipal outlook brightens, the pressure for PILOTs will ebb. Boston’s experience contradicts this assertion. The city has struggled with the fiscal impact caused by its nonprofit sector over a long period, through good fiscal times and bad. It is this fundamental disconnect between institutional benefits and fiscal costs that is the ultimate source of this debate. Until these benefits and costs are better reconciled, financial tension between the city and its nonprofits will continue.
Measuring the Fiscal Impact of Tax-Exempt Property
The impact of tax-exempt property on the city as a whole has long been the focus of spirited public discussion in Boston. One question that has often been asked is how much nonprofit institutions would pay if their properties were fully taxable. For a long time this question could not be answered. Since tax-exempt property paid no property taxes, the city had little incentive to maintain accurate data and up-to-date assessments for institutional property. However, the continuing focus on the fiscal impact of exempt property clearly required an answer to this question.
Given the scarce resources available for a project to value exempt property, Boston needed to be creative in coming up with a method to generate reliable assessments while minimizing the costs of collecting data. At the city’s disposal was a particular type of tax return that nonprofit institutions are required to file annually, as well as broad statutory authority to request from property owners the information necessary to value their properties. Boston was able to leverage these tools to collect detailed information on the property owned by nonprofit institutions—specifically, the physical characteristics (size, age, condition) and uses. Most major institutions maintain accurate data on their property holdings. Once the assessors had access to these data, they were able to plug the information into the city’s computer-assisted mass appraisal system (CAMA) to generate assessments for the properties. Site inspections were performed to verify the information provided by the institutions and to ensure the accuracy and reliability of the CAMA-generated assessments.
The resulting assessments were then shared with the institutions. Each was given the details on the valuation estimates for their real estate holdings and provided with an opportunity to meet with assessors to review the results and raise any concerns. The city incorporated this feedback to complete the final value for the properties. Given that this was the city’s first effort to generate assessments for nonprofit property, this review step provided a valuable check of valuation data quality as well as an opportunity to share the preliminary results of the revenue impact of their property tax-exemptions with each institution.
The analysis, which was completed in 2009, revealed that educational and medical tax-exempt property would have generated $347.9 million in revenue if it were taxable (City of Boston 2010). To put this amount in perspective, it would equate to approximately one-quarter of the city’s total tax levy of $1.4 billion in Fiscal Year 2009, and would be equivalent to roughly half the revenue generated by the office, retail, and hotel properties that make up the commercial tax levy (figure 3).
PILOT Task Force
Once the assessment information was used to determine the amount of tax each institution would pay in a nonexempt scenario, a number of shortcomings of the current PILOT program became apparent. While the former program was considered one of the more successful PILOT programs in the country, the amount of realized revenue appeared small when compared with the revenue that exempt properties would generate if they were taxable. PILOT payments from educational and medical institutions in 2009 totaled $14.5 million, or 4.2 percent of what institutions would pay if their properties were taxed, and equivalent to just 1 percent of the city’s property tax levy. In addition, the level of participation varied widely among institutions. Some institutions made substantial contributions under the program, while others made limited payments or chose not to participate at all.
To address these concerns, Boston Mayor Thomas M. Menino appointed a task force to review the PILOT program and asked it to:
The PILOT Task Force membership drew from a wide spectrum of participants: two leaders each from local colleges, nonprofit hospitals, and Boston’s business community; and one each from the city council, public sector unions, and community-based organizations. The Task Force met over a two-year period to explore both the benefits and costs to Boston of hosting its nonprofit institutions and how these factors should be considered in the PILOT process. Also key was the discussion on how to ensure that institutions contribute to the program on a consistent basis. In December 2010, the Task Force recommended the following PILOT guidelines to Mayor Menino.
PILOT Program Should Remain Voluntary
The Task Force members believed a legal or statutory requirement for PILOTs runs counter to the spirit of partnership between the city and its nonprofit institutions. That partnership is critical to encouraging broad and uniform participation.
All Nonprofits Should Participate
Much of the PILOT discussion previously focused on hospitals and universities. The Task Force, however, felt all nonprofits that own tax-exempt real estate within the city should contribute to the PILOT program. To protect smaller institutions with fewer resources, the PILOT program was limited to those nonprofits with property valued at more than $15 million.
Determining PILOT Payments
Many alternatives were considered for the basis of PILOT contributions, including a per-student or per-hospital-bed fee, or a charge based on the amount of land or building area. The Task Force determined that a charge driven by the assessed value of the institutions—reflecting size and quality of real estate holdings—would result in the most equity. There was a general consensus that nonprofits should contribute some amount toward their consumption of essential services such as police and fire protection, as well as public works such as street cleaning and snow removal. These services consume approximately 25 percent of Boston’s budget, and the Task Force found that a PILOT equal to 25 percent of an institution’s fully taxable amount was reasonable.
Credit for Community Benefits
The public benefit provided by nonprofit institutions was a major focus of the Task Force, which recommended that institutions receive up to a 50 percent credit on their PILOT in exchange for community benefits. This credit recognized the significant inkind contributions made by nonprofit institutions that directly benefit Boston residents. The credit was limited to 50 percent of the PILOT amount to ensure significant cash contributions from each institution. However, the Task Force felt that if an exceptional opportunity for a program or service were available, the 50 percent cap could be exceeded at the city’s discretion.
While the Task Force did not offer detailed specifics on the services that were eligible for PILOT credit, it did provide general guidance on the types of services that should qualify. To be eligible, community services must directly benefit City of Boston residents, support the city’s mission and priorities, offer ways for the city and nonprofit to collaborate to meet shared goals, and be quantifiable.
Phase-in Period
Finally, the Task Force recommended that the new PILOT formula be phased in over a period of not less than five years. Given the change in scope of the city’s PILOT program, the Task Force understood that institutions would require time to make the necessary adjustments in their budget and financial plans to accommodate increased PILOT amounts.
Implementing the New PILOT Program
When Mayor Menino accepted the Task Force recommendations in December 2010, the city needed a plan to implement the new PILOT program. First, letters were sent to all institutions that fell within the criteria of the program. Each letter included a copy of the new PILOT guidelines and an analysis detailing the calculation of the PILOT that the city would request under the new formula. Each letter also indicated that the city would seek a meeting with each institution in the coming months to discuss the new program.
The subsequent meetings were a critical step in the implementation, providing a forum for each institution to ask questions about the program and to voice concerns. While these sessions were designed originally to provide information to the institutions on the new program, they also provided significant, valuable feedback for the city that in turn offered further guidance on the rollout.
The city’s previous PILOT program included contracts that laid out the terms of each institution’s PILOT commitment. While the contracts were useful as a reference, their value as a legal instrument was questionable since PILOT payments remained voluntary. For example, the city had never sought to enforce payment under a PILOT contract. As the city faced the question of whether contracts would be employed in the new program, the notion of negotiating, drafting, and executing over 40 contracts with institutions was daunting. Given that the guidelines already provided the details of each institution’s requested participation, the city felt those documents should form the basis of the relationship with the institutions and decided to forgo the use of PILOT contracts.
Experience from the First Year
In October 2011, requests for payment of the first installments for FY2012 were sent to all participating institutions, and the results were impressive. The city collected a total of $19.5 million in cash payments, a 28.4 percent increase over what was collected in FY2011 under the previous PILOT program. This represented over 90 percent of what the city requested—an extraordinary level of participation given the first year of a new, voluntary program (figure 4). Boston also received an equivalent level of contributions in the form of community services provided by the nonprofit institutions, consistent with the PILOT guidelines.
A key component of the program’s initial success was the emphasis on promoting a sense of partnership between the city and its institutions. Based on its prior experience, the city understood that a more confrontational approach would not be effective in the short or long term. At the same time, the institutions needed to recognize that as charities they have a level of accountability to their host communities. This accountability was encouraged in part by providing a high degree of transparency in the process. Task Force meetings were open to the public, and materials used during the deliberations were posted on the city’s website.
This theme of transparency continued in the implementation phase of the program. Information detailing each institution’s participation in the program, from cash payments to the community services provided, was also posted on the city’s website. Institutions that had less than full participation in the program were given the opportunity to communicate their reasons. Specific details on the community services delivered by the institutions were also disclosed, providing an opportunity for institutions to highlight and promote their valuable service contributions.
The Importance of Community Services
In its discussions with nonprofit leaders during the implementation of the new program, the city discovered that institutions have a decided preference for providing community services over making cash payments. Given that service delivery is at the core of most nonprofits’ charitable missions, this was not surprising. Conversely the city generally places a higher value on cash payments, which provide flexibility in applying resources to meet the highest-priority service needs of the community.
To reconcile these two divergent preferences, the city has recognized that it must further develop its ability to harness the community-service portion of the PILOT program to meet its service demands. Currently community benefits often are offered by the institutions based on their own initiative. While these services have value to the city and its residents, they may not be among the city’s current service priorities. Even in cases where specific requests for services came directly from a city official to fill a near-term service gap, such ad hoc requests lack the prioritization and review that is associated with a more disciplined budgeting process.
Requests for PILOT services should be planned and prioritized to maximize their value to the city. Under such a structure services are more likely to either reduce or replace the cost to the city of providing a service, or to provide a new service to meet a priority that the city had been unable to deliver previously. Through careful planning, directing institutional resources to priority areas reduces the city’s financial commitment and makes it is easier for the city to forgo cash in favor of institutionally preferred services. This planning process is also beneficial to the institutions, as they are better able to budget for their PILOT service commitments. As the program continues through its phase-in period, the ability of the city and institutions to work cooperatively on a structured approach to community services will be critical to the continued success of the PILOT program.
Closing Thoughts
The process Boston has followed to construct its new approach to PILOTs was both thoughtful and inclusive. The expertise and perspectives of the Task Force members, combined with the city’s decades of experience on the issue of exempt property, led to program guidelines that were recognized as fair and reasonable. The process also demonstrated that for a PILOT program to be successful the city and its institutions must be partners, not combatants.
This philosophy has formed the basis of Boston’s approach to the implementation of its new PILOT program. And, despite its early success, there is still much work to be done. The city needs to balance its need for revenue with the institutions’ preference for services. If city officials and local institutions can continue to work cooperatively on the PILOT program, a balance can be struck that will work to the mutual benefit of the institutions, their constituents, and the residents of Boston.
About the Author
Ronald W. Rakow has been commissioner of the City of Boston Assessing Department since 1992, and he took on the additional role of deputy chief financial officer in 2011. He was appointed in 2010 to the Board of the Massachusetts Convention Center Authority, and is currently serving as the chair of the Research Committee of the International Association of Assessing Officers (IAAO).
References
City of Boston. 2010. Mayor’s PILOT task force final report and recommendations, December.
City of Boston Assessing Department. 2009. Exempt property analysis: Educational and medical institutions, Fiscal Year 2009.
City of Boston Assessing Department. 2012. FY 2012 PILOT recap. http://www.cityofboston.gov/Images_Documents/FY12_Second_Half_PILOT_Status_Report_for_Web_tcm3-33007.pdf
City of Boston Office of Budget Management. 2012. Fiscal year 2013 adopted budget. http://www.cityofboston.gov/budget/default.asp
The Great Recession of 2007–2009 and the sluggish recovery since then have produced extraordinarily large state budget gaps. Even as the fiscal condition of most state governments is slowly improving, many central cities have only recently begun to feel the full impacts of the economic slowdown and the disruptions to the housing market.
A number of indicators have been flashing signs of local government fiscal distress. From its peak in 2008 through May 2012, local government employment has fallen by 528,000, or 3.6 percent (U.S. Bureau of Labor Statistics 2012). The media has also been reporting large cuts in public services in some cities. Newark, New Jersey, has been forced to make substantial cuts in municipal employment, as well as imposing significant increases in taxes and fees. Stockton, California, is reportedly on the verge of bankruptcy. A number of counties in New York State are either in or close to fiscal receivership, and the school district of Providence, Rhode Island, which comprises half the city’s total budget, is facing a nearly $40 million shortfall for the coming academic year.
The most recent comprehensive data on central city finances are from the U.S. Census Bureau for the year 2009. In the absence of more recent data, we have developed a forecasting model of the revenues of the nation’s largest central cities, based on a specially constructed multiyear database. We focus on large cities not only for their sheer size, but also because they are crucial to the economic success of their surrounding regions.
The prosperity of cities depends on effective public services, provided at competitive tax rates. The deep recession, reinforced by the decline in housing prices and extensive housing foreclosures, has put pressure on local tax revenues and local public services. Deep cuts in state aid to many local governments have only added to the fiscal pain. Given the ongoing sluggishness of the U.S. economy, the prospects for a robust recovery in revenues over the next few years are highly uncertain.
The Difficulty of Comparing City Revenues
The U.S. Census Bureau provides the only comprehensive source of fiscal data for cities. Information is collected separately for each type of governmental unit–general-purpose municipal governments, which include cities and towns; independent school districts; county governments; and special districts. Because the delivery of public services is organized in very different ways in different cities, direct comparisons of revenues across cities by source can be highly misleading.
While some municipal governments are responsible for financing a full array of public services for their residents, others share this responsibility with a variety of overlying governments. For example, Boston, Baltimore, and Nashville have neither independent school districts nor county governments serving local residents. Each of those municipal governments is responsible for providing core municipal services, plus education, public health, and other social services. By contrast, municipal governments in El Paso, Las Vegas, Miami, and Wichita collect only about one-quarter of the revenues that finance the delivery of public services within their boundaries. The remaining three-quarters are the responsibility of one or more independent governments serving city residents, and in some cases people who live beyond the city boundaries as well.
To illustrate the difficulty in making revenue comparisons, census data indicate that in 2009, the City of Tucson, Arizona, which relies heavily on a local sales tax, collected only 14 percent of its total tax revenue from the property tax, while Buffalo, New York, collected 88 percent of its tax revenue from the property tax. However, when we take account of the revenues paid by city residents to their overlying school districts and county governments, the situation is reversed. Property taxes accounted for 68 percent of the total local tax revenue paid by Tucson residents, but only 50 percent of tax revenue paid by the residents of Buffalo. In the latter case, the county government relies heavily on sales tax revenue.
Our approach to dealing with the variation in the organizational structure of local governments across the country is to account for all local government revenues received by governmental entities that provide services to city residents and businesses. The basic idea is to include all revenues collected by a central city municipal government and by that portion of independent school districts and county governments that overlay municipal boundaries. We refer to the result of this calculation as a “constructed city” government.
To create constructed cities we take the following steps. For cities with independent school districts that are coterminous to city boundaries, we combine the school district and municipal values of all revenue variables. For school districts that cover a geographical area larger than the city, and for cities served by multiple school districts, we use data on the spatial distribution of enrollments to allocate a pro-rata share of total school revenues to the constructed city. For each school district serving a portion of the central city, we draw on geographical information system (GIS) analysis of census block group level data from the 1980-2000 decennial censuses to determine the number of students in each school district that live in the central city.
For counties, we allocate the portion of revenues associated with city residents on the basis of the city’s share of county population. Because geographic boundaries are not readily available, and fiscal data is intermittent, our calculations do not take account of special districts. For the country as a whole, special districts are relatively unimportant, and failing to include them should do little to distort fiscal comparisons among central cities.
Constructed city revenues are calculated for the nation’s largest central cities for the years 1988 through 2009. The source for the data is the quinquennial Census of Governments, and, for noncensus years, the Annual Survey of State and Local Government Finances. The sample includes all cities with 2007 populations over 200,000, except those with 1980 populations below 100,000, and all cities with 1980 populations over 150,000 even if their 2007 population was below 200,000. In 2009, the population of the 109 central cities in our sample was 58.9 million, equaling 60.3 percent of the population of all principal cities within U.S. metropolitan statistical areas.
While prior studies have recognized the importance of overlying jurisdictions, they have been less systematic in taking account of the variations in governmental structure. Carroll (2009) ignores overlying jurisdictions, while Inman (1979) and Sjoquist, Walker, and Wallace (2005) use dummy variables as a partial adjustment. Ladd and Yinger (1989) focus on the revenue capacity of municipal governments by adjusting for the capacity “used up” by overlying governments.
Constructed City Revenues
Figure 1 displays the average share of total general revenues that came from each revenue source in the 109 constructed cities in 2009. The most important sources are state aid (34 percent) and property taxes (27 percent). User fees and charges contributed 16 percent, while taxes other than the property tax contributed 13 percent.
Sources of revenue vary enormously among constructed cities. For example, 60 percent or more of general revenue came from state and federal aid in Springfield (Massachusetts), Fresno, and Rochester, while aid contributed less than 20 percent of revenues in Atlanta, Dallas, and Seattle. The reliance on the property tax also varies across cities, with over 90 percent of tax revenue coming from the property tax in Providence, Boston, and Milwaukee, but less than 30 percent in Philadelphia, Birmingham, and Mobile.
Because the importance of counties and independent school districts varies enormously, revenue comparisons that rely only on data from municipal governments are highly misleading. For example, in 2009 per capita general revenue of the city government of Pittsburgh was $1,958, while the per capita revenue for Baltimore was $5,306. However, per capita revenues in the two constructed cities were nearly identical. This pattern is not atypical among cities.
Comparing per capita revenues across central city municipal governments overstates the differences across cities because it forces us to compare city governments that have very different sets of public service responsibilities. Utilizing the concept of constructed cities provides the basis for more accurate intercity comparisons, and allows us to generate comprehensive revenue forecasts for the cities in our sample.
Forecasting Revenues for Constructed Cities
To forecast general revenues for 109 constructed cities for the four years from 2010 to 2013, we sum projections for five separate revenue streams: property taxes; nonproperty tax revenues; nontax own-source revenues; state aid; and federal aid (Chernick, Langley, and Reschovsky 2012). We use econometric models fitted with actual and projected metropolitan area–level data to forecast the three sources of own-raised revenue. We then make a range of projections about intergovernmental revenues based on information from surveys and published revenue estimates.
Property Tax Revenues
Predicting the exact relationship between changes in tax revenues and changes in the size of the tax base is particularly difficult in the case of the property tax. Property tax rates are adjusted much more frequently than sales or income tax rates to reflect changes in assessed values and revenue needs. Predicting the revenue impact is further complicated by the existence in some states of legislatively or constitutionally imposed limits on tax rates, changes in tax levies, or changes in assessed values. Major changes in the fiscal relationships between state and local governments, such as school funding reforms, are often motivated by the goal of reducing reliance on the property tax.
Although property taxes are generally levied on all real property, comprehensive data on property values over time and across states do not exist. Thus, researchers have had to focus on changes in housing prices. Data collected on the Lincoln Institute’s website, Significant Features of the Property Tax (2012), indicate that in the large majority of states where data are available residential property accounts for well over half of total property value.
Figure 2 demonstrates the relationship since 1988 between housing prices in the United States and per capita local government property tax revenues. Inflation-adjusted housing prices rose steadily from 1998 until 2006, but by 2011 they had fallen by 25 percent. Per capita property tax revenues followed a similar pattern, with sharp growth beginning in 2001 and continuing until 2009, three years after housing prices peaked.
The lag between changes in housing prices and changes in property tax revenues occurs because changes in assessed values, on which property taxes are levied, typically lag behind changes in market values. The lag may be as little as a year, in cities with annual reassessments, or longer in cities that reassess less frequently or have explicit policies to phase in changes in market value.
The housing price indices for our 109 constructed cities indicate very different patterns of boom and bust in different parts of the country. Willingness of city residents to support increases in property taxes may reflect both changes in the value of their homes and changes in their income. Furthermore, as property tax rates are often adjusted in response to changes in other revenue sources, changes in state aid are likely to affect changes in property tax rates and revenues. To capture these various factors, we estimated a statistical relationship between annual changes in per capita property tax revenues and lagged changes in housing prices, metropolitan area personal incomes, and per capita state aid. Data on property tax revenues are for the years 1988 through 2009. Our statistical model also accounts for city-specific factors that remain constant over time.
The results of our analysis indicate a statistically significant relationship between changes in property tax revenues and changes in housing prices, lagged three years. Our results also indicate that changes in personal income two years ago lead to current year changes in property taxes revenues. This suggests that the impact of the decline in housing prices from 2006 to 2012 and reductions in personal income during the recession will exert negative pressure on property tax revenues from 2009 until at least 2015. Changes in state aid were found to be statistically insignificant.
We estimate that, on average, a 10 percent change in housing prices in our constructed cities results in a 2.5 percent change in tax revenues. This implies that the average city will offset about three-quarters of the revenue effect of falling market values by raising effective tax rates.
To forecast changes in per capita property tax revenues, our coefficient estimates are combined with actual and projected values of metropolitan housing prices, personal income, and state aid, which are then added to actual 2009 property tax revenues to calculate annual per capita revenue for each year between 2010 and 2013. Adjusting for inflation we find that per capita property tax revenue in the average constructed city will decline by $40 or 3.1 percent over the period from 2009 through 2013. Predicted changes range from increases of about 14 percent in the Texas cities of Lubbock and San Antonio to declines of 20 percent in some cities in California, Arizona, and Michigan, where the bursting of the housing bubble was most severe.
Other Locally Raised Revenues
As demonstrated in figure 1, revenue raised from local sources other than the property tax in the average constructed city accounts for a little over one-third of total revenues. These revenues come from local government sales taxes, income taxes, user charges, fees, licenses, and other miscellaneous sources. The importance of these revenue sources varies tremendously across cities, ranging from 6 percent of general revenues in Springfield (Massachusetts) to 60 percent in Colorado Springs.
As we did in forecasting property tax revenues, we started by estimating the statistical relationship between annual changes in revenues and changes in metropolitan area personal income, lagged one year. We estimate separate equations for tax revenue from taxes other than the property tax and for local-source revenue from nontax sources. Using the coefficients from our estimated equations and actual and forecast data on metropolitan area per capita personal income, we forecast a $20 per capita (2.1 percent) increase in tax revenue from sources other than the property tax and a $29 (1.2 percent) increase in nontax locally raised revenues over the four-year period between 2009 and 2013.
State Aid to Cities
Over the past few years, most state governments have faced large budget shortfalls. Budget adjustments have occurred mainly on the spending side, and in many states there have been large reductions in state aid to local governments. To forecast reductions in state aid through 2013, we draw on a survey of changes in state education aid between 2008 and 2012 by the Center on Budget and Policy Priorities (Oliff and Leachman 2011). We assume that the reported percentage change in each state’s education aid applies to the school districts in every constructed city in that state, and that the same percentage change in aid applies to noneducation aid as well.
Given the uncertainty over future legislative actions, we make three alternative predictions. The base case assumes that state aid stays constant in real terms from 2012 to 2013. Our best case assumption is that state aid increases in each city by 3 percent in that period, while our worst case is that state aid changes by the same amount in real terms as in 2011–2012, i.e., an average reduction of about 6 percent. Under our base case, per capita state aid is forecast to decline by $153 (9.5 percent) between 2009 and 2013.
Federal Aid to Cities
Cites receive federal grants through a myriad of different programs. In the past few years, fiscal pressure at the federal level has led to a number of proposals to sharply reduce such spending. President Obama’s FY2013 budget calls for large cuts in a wide range of programs that provide revenue to cities. Based on alternative assumptions about Congressional actions, we take as a base case assumption a 15 percent reduction in federal aid between 2009 and 2013, a worst case of a 37.7 percent reduction in federal grants between 2009 and 2013 (the current budget proposal), and a best case of a 9.5 percent cut.
Total General Revenues
General revenues are defined as the sum of the five sources of revenues discussed above. Adding up the forecasts, we predict that on average inflation-adjusted per capita general revenues will decline between 2009 and 2013 by 3.5 percent ($169). Though the variation in revenue forecasts across the nation is substantial, nearly three-quarters of central cities face some level of reductions (figure 3). The largest projected revenue declines are in California and Arizona, where 11 cities have declines of greater than 10 percent. There is no particular regional pattern to the cities where we forecast growth in revenues. For example, per capita revenue growth in excess of 3 percent is predicted for such diverse cities as Atlanta, Cincinnati, and Lubbock.
Figure 4 groups constructed cities by their census division. Above-average revenue declines are forecast in the Pacific, Mountain, and South Atlantic divisions. Revenues are declining in the central cities in these regions because they are facing a combination of reduced property tax revenues and sharp reductions in state aid. By contrast, in the East and West South Central divisions, real general revenues remain largely unchanged because declines in state aid are offset by increases in property taxes. The opposite is true in New England, where property tax reductions are offset by state aid increases.
Forecasting future levels of state and federal aid to central cities is extraordinarily difficult. Our approach is to choose a range of estimates for 2012–2013 changes in intergovernmental aid. From the cities’ perspective, our worst case calls for steep cuts in both state and federal aid, while our best case calls for smaller cuts in federal aid and modest increases in state aid. When combined with cities’ own sources of revenue, under the worst case scenario, real general revenues will decline by $295 per capita (6.1 percent) between 2009 and 2013. This decline is $126 per capita more than our base case forecast. Even under our best case, we forecast that on average general revenues will decline by $116 per capita or 2.4 percent over the four-year period.
Conclusions
These predicted reductions in revenue place many of the nation’s largest central cities in uncharted territory. While these revenue declines may appear modest, they contrast quite sharply with the resiliency of city revenues following the previous three recessions. For example, real per capita revenues grew by a robust 17 percent in our 109 constructed cities during the four years following the recession of 1981–1982. Given the severity of that recession, the current revenue declines highlight the unprecedented magnitude and duration of fiscal pressure on cities that has resulted from the housing market collapse and the Great Recession in 2007–2009.
Demographic and economic trends, such as the aging of the population and the persistence of high poverty rates, contribute to the rising costs of providing government services in central cities. In many cities legally binding pension and health care benefits for retirees constitute a large and growing component of total compensation. Facing both rising costs and reduced revenues, many central cities have no choice but to implement substantial cuts in locally provided public services. There is little question that these reductions, when combined with projected cuts in federal and state government programs that provide direct assistance to city residents, such as Food Stamps, Medicaid, and unemployment insurance, will cause substantial harm to central city economies.
While the governments serving central city residents must continue to search for ways to reduce costs without harming service quality and to explore potential new sources of revenue, it is also critically important that the federal government and state governments take an active partnership role in mitigating the adverse impact of the recession on the nation’s central cities.
About the Authors
Howard Chernick is professor of economics at Hunter College and the Graduate Center of the City University of New York. He specializes in the public finances of state and local governments, both in the U.S. and abroad.
Adam H. Langley is a research analyst in the Department of Valuation and Taxation at the Lincoln Institute of Land Policy, where he has coauthored papers on property tax incentives and relief programs, nonprofit payments in lieu of taxes, and state-local government fiscal relationships.
Andrew Reschovsky is a professor of public affairs and applied economics in the Robert M. La Follette School of Public Affairs of the University of Wisconsin-Madison and a visiting fellow at the Lincoln Institute of Land Policy. He conducts research on property taxation and other aspects of state and local public finance.
Note: This article is a condensed and updated version of the article published in Publius in 2012.
References
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Chernick, Howard, Adam Langley, and Andrew Reschovsky. 2012. Predicting the impact of the U.S. housing crisis and “Great Recession” on central city revenues. Publius: The Journal of Federalism 42(3).
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