The effect of property tax limitation measures on local government fiscal behavior

Journal of Public Economics 66 (1997) 469–487

The effect of property tax limitation measures on local government fiscal behavior a b, Richard F. Dye , Therese J. McGuire * a

Department of Economics, Lake Forest College, 555 N Sheridan Road, Lake Forest, IL 60045 USA b Institute of Government and Public Affairs, University of Illinois, 815 West Van Buren Street, Suite 525, Chicago, IL 60607 USA Accepted 8 April 1997

Abstract Previous evidence on the effects of tax and expenditure limitation measures has not been conclusive. Difficulties arise in characterizing differences in fiscal institutions across states, and estimating behavior in the absence of limitation measures. A recently enacted tax limitation measure limits the growth in local property taxes in some Illinois jurisdictions, but not in others. Such differential treatment of otherwise similar jurisdictions provides a natural experiment for estimating the impact of the tax cap on local government fiscal behavior. We find that the cap has been effective in that the fiscal behavior of capped jurisdictions differs from that of never-capped jurisdictions.  1997 Elsevier Science S.A. Keywords: Property tax limitation measures JEL classification: H7

Beginning with Proposition 13 in California in 1978, there has been a wave of tax and expenditure limitation measures across the United States. The rationale for such limitation measures is not clear. Are they to reduce the size of governments biased by budget-maximizing public managers or by wage-maximizing public employees? 1 Are they to reduce the property tax or rather to force a reallocation *Corresponding author. Tel.: 312 996-1643; fax: 312 996-1404; e-mail [email protected] 1 Courant and Rubinfeld (1981) demonstrate that the welfare effects of using limitations differ between these alternative objectives. 0047-2727 / 97 / $17.00  1997 Elsevier Science S.A. All rights reserved. PII S0047-2727( 97 )00047-9

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between the property tax and other revenue sources? In her study of the election of home-rule status among Illinois municipalities, Temple (1996) reviews the theory of tax and expenditure limitation measures. She notes that a primary justification for property tax limitation measures is a desire to cut the size of unresponsive (budget-maximizing) governments. In their analysis of California’s Proposition 13 measure, O’Sullivan et al. (1995) argue that it is more accurate to view the tax revolt of the late 1970s as a desire to reduce and reform the property tax rather than as evidence of general voter dissatisfaction with the size of local government. In July 1991 the Illinois General Assembly passed a measure to limit the growth rate of property taxes for jurisdictions in the five metropolitan counties surrounding Cook County, the county containing the City of Chicago. Since then the growth rate of property taxes has declined in the counties affected by the tax cap, and many observers have taken this as evidence that the cap has effectively limited property taxes. But the growth rate of property taxes has also declined for jurisdictions in the metropolitan area not subject to the cap, suggesting that the slowdown in property taxes may be caused by some metro-wide factor, such as the recession that occurred in Illinois in 1991. In this paper we seek evidence on whether the tax cap has been effective at lowering the growth rate of property tax revenues and the expenditures they finance. It may seem obvious that limitations on taxes or expenditures should be effective at limiting the behavior they are intended to address. However, such limitations are common across the country and the evidence is decidedly mixed as to how effective they have been. It appears that the actual design of the limitation measure matters as do the details of the local fiscal institutions. There have been several recent studies of limitation measures in other states. Merriman (1987) studies tax and expenditure limitations in general and an expenditure limitation in New Jersey in particular. He finds limited evidence of restraint and notes instances of jurisdictions increasing current spending in order to preserve future flexibility. Fisher and Gade (1991) find that the property tax limitation in Arizona, which is somewhat similar to the Illinois measure, did not restrain the growth of property taxes in the first 8 years following its implementation. On the other side, Preston and Ichniowski (1991) examine property tax limitation measures across the country from 1976 to 1986 and find that the growth of municipal property tax revenues in states with such limits is lower than the growth observed in municipalities in states without such measures. In a recent study, Poterba and Rueben (1995) find evidence of substantially lower growth rates in public sector wages in states with stringent limitation measures, and evidence of lower growth rates in public sector employment in states with both stringent limitation measures and generous public-sector labor laws. Joyce and Mullins (1991) find evidence that local tax limitations have resulted in a shift in the revenue mix away from local taxes towards state aid and local non-tax revenues, and a shift of expenditure responsibility away from local governments towards state government.

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Empirical examinations of the effectiveness of property tax limitation measures can be viewed as tests of two competing theories of government behavior. If the median voter model is operative, and a binding constraint is imposed on local governments, we would expect to see local residents voting to override the constraint in order to maintain their desired levels of spending. In this situation, passage of a limitation measure would not necessarily result in a change in fiscal behavior (spending or tax levels). However, if the relevant model is the Leviathan, budget-maximizing model of government, and the limitation imposed is binding on the bureaucrats’ choices, we would expect to see changes in the fiscal outcomes. For an empirical examination of the effectiveness of limitation measures to be a clean test of these competing theories, the limitation must be a binding constraint, otherwise under either model we would expect to see no effect of the measure. There are two difficulties with the existing evidence on the effectiveness of tax and expenditure limitations. The within-state studies suffer from the difficulty of knowing or estimating what would have happened in the absence of the limitation measure. The cross-state studies suffer from the need to capture in a limited number of variables potentially intricate differences in both the limitation measures and the fiscal structures employed by the various states. Because the Illinois property tax cap measure applies to only a subset of local governments within the same metropolitan area, we are able to address these two difficulties in our study, and we are able to provide a better test of the competing theories of local government behavior.

1. The tax cap measure and local government finance in Illinois During the latter half of the 1980s, property taxes grew at double-digit annual rates for much of metropolitan Chicago. In the suburbs, the growth in property taxes was driven by rapid development and population growth, and was reflected in rapidly growing assessed valuations of property. In the early 1990s taxpayers, tax watch-dog organizations, and state politicians from the suburbs as well as the then newly-elected anti-tax governor decided that this situation needed to be addressed. Various types of property tax limitation measures were debated for various parts of the state. What passed in July 1991 was a limit on the growth rate of aggregate property taxes (aggregated at the jurisdiction level) for non-home-rule jurisdictions in the five metropolitan counties surrounding Cook County (these counties are known as the collar counties). The cap was set at the lesser of the rate of inflation (as measured by changes in the Consumer Price Index) or 5 percent. There are various exemptions or exceptions to the measure, the most important being general obligation bonds issued prior to October 1991, new property in the year it appears, and special referenda in which voters may approve increases over and above the cap.

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The measure applies to approximately 700 of the 1,250 local jurisdictions in the six-county metropolitan area. Because the measure applies only to non-home-rule jurisdictions, and because only certain municipalities (generally those over 25,000 in population) are home-rule, the measure applies to all school districts, most small municipalities, and all special districts in the five-county collar region.2 These same jurisdictions, like non-home-rule jurisdictions throughout Illinois, are also subject to a much older limit on the nominal rate of property taxation. The interaction of the two property tax limitation measures is of interest. One rationale offered for the recent tax cap measure limiting the growth of property taxes was that the older measure limiting property tax rates had proved not to be effective, especially in the rapidly developing collar counties where assessments were increasing rapidly. Even if the jurisdictions are at their rate limits, if assessments rise rapidly property taxes will also rise rapidly unless tax rates are adjusted downward. The measure does not apply to any jurisdictions in Cook County nor to any home-rule municipalities in the collar counties.3 We thus have the opportunity to conduct a natural experiment. All the jurisdictions in the six-county metropolitan area have experienced similar, if not identical, economic conditions. The state laws and grants-in-aid formulas are virtually identical for all units of a given type of jurisdiction.4 Thus, the approximately 1,250 local governments in the metropolitan area provide both the control group and the experimental group for an examination of the effectiveness of the tax cap legislation. Our analysis improves upon previous within-state studies because we can obtain a better estimate of what would have happened in the absence of the cap by examining the behavior of the control group of jurisdictions. Our analysis also has advantages over cross-state studies in that we do not have to proxy for the stringency of the limitation measure, and we can take into account institutional details of local government finances. There are two caveats to our study. First, the control group of jurisdictions is not ideal in that it largely consists of jurisdictions located in Cook County, which has a property tax system that differs from the system operating in the other 101 counties in Illinois including the five collar counties. In particular, property is classified in Cook County, and the timing from assessment to levy differs from the other counties. Still, for our purposes the differences in the property tax systems between Cook County and the collar counties are not of major concern because we examine growth rates of aggregate property taxes rather than the distribution of property tax burdens across classes of 2

The non-home-rule versus home-rule distinction is important fiscally since home-rule jurisdictions have much more latitude to impose and set the rates of property and other taxes (see Temple, 1996). 3 Subsequent to our analysis a law was passed to impose a similar cap on jurisdictions in Cook County. 4 The exceptional jurisdictions are the City of Chicago, the Chicago School District, the Chicago Park District, and Cook County, where state law is tailored to special circumstances.

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property.5 Second, because the tax cap legislation passed recently, the period of experimentation with the cap is short, so we are unable to observe the long run effects of the limitation measure.

2. Data, methodology and results Suburban Cook County, from which our control group of jurisdictions is drawn, is compared to the collar counties, the source for our experimental group of jurisdictions, in the descriptive statistics presented in Table 1. The collar counties, with population just slightly less than the population for suburban Cook County in 1990, but an area nearly four times the size, are much less densely populated than suburban Cook. The growth in population over the decade was much higher in the collar counties than in suburban Cook. Property values rose in both areas from 1987 through 1993, and while they rose more rapidly in the collar counties, this Table 1 Descriptive statistics for collar counties versus suburban Cook County Suburban Cook (excludes Chicago) Area (square miles)

730

Collar counties 2765

Population 1980 1990 Annual growth 1980–90 (%)

2 248 583 2 321 341 0.32

1 849 969 2 156 109 1.54

Equalized assessed valuation (tax base in $ million) 1987 tax year 1990 tax year 1993 tax year Annual growth 1987–90 (%) Annual growth 1990–93 (%)

23 899 32 065 38 172 10.29 5.98

22 154 32 651 41 590 13.80 8.40

Personal income per capita ($) 1979 1989 Annual growth 1979–89 (%)

15 384 27 169 5.85

11 450 22 814 7.14

Number of local jurisdictions

536

715

Sources: 1991 Illinois Statistical Abstract and Illinois Department of Revenue. 5 In Downes et al., forthcoming, where we examine the effects of the tax cap on measures of school output, we use different control groups (Cook County, the outer-collar counties, the remainder of the state, etc.) and find that the results are invariant to the choice of control group.

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was true before and after the imposition of the cap in 1991. Per capita income was lower in the collar counties in 1989, but the relative gap between suburban Cook and the collar counties narrowed over the decade of the 1980s. The number of local jurisdictions in suburban Cook was 536 in 1993 compared to 715 in the collar counties. We study five different major types of jurisdictions: school districts, municipalities, park districts, fire districts and library districts.6 Together they account for a large fraction of the property taxes collected in Illinois – roughly 60 percent from school districts, 15 percent from municipalities, 5 percent from park districts, 2 percent from fire districts, and 1 percent from library districts (Illinois Department of Revenue, 1993). This separation of jurisdictions by type enables us to control for additional factors common to type of jurisdiction. For example, school districts are all subject to the same state aid formula, municipalities have access to state-imposed local sales taxes, and each type of special district has similar access to charges and fees. We choose three years of growth prior to the cap consisting of growth between tax years 1987 and 1990, and are limited by data to a three-year period during the cap consisting of growth between tax years 1990 and 1993.7 During this time period the metropolitan area experienced fairly steady economic growth except for a mild recession in 1991. Our sample consists of annual observations from 1987 to 1993 on 282 school districts, 238 municipalities, 154 park districts, 124 fire districts, and 88 library districts.8 The data on property taxes and assessed valuations for tax years 1987 through 1993 were obtained from the Illinois Department of Revenue. The data on numbers of pupils for school districts for fiscal years 1986–87 through 1993–94 were obtained from the Illinois State Board of Education, and the data on population for municipalities for years 1986, 1988, 1990 and 1992 were obtained from the Northeastern Illinois Planning Commission. We begin the natural experiment analysis with a comparison of the property tax growth rates before and after the imposition of the cap for both the control group (jurisdictions never subject to the cap) and the experimental group (jurisdictions subject to the cap beginning in 1991). For each group for each period we calculate an average annual growth rate of total property taxes. Our measure of the

6 The unexamined types of jurisdictions are counties, townships, and special jurisdictions that are small in number (such as water districts). Also, a small number of jurisdictions with missing data in one or more years or, in the case of municipalities, with changed home-rule status were removed from the sample. 7 The first year of experience with the cap was ‘‘tax year’’ 1991 – the taxes based on 1991 assessments, but billed and collected in 1992. The references to property taxes in this paper are by tax year. 8 Because the City of Chicago, the Chicago Park District, and the Chicago School District are unusual jurisdictions in many respects, these three units have been omitted from the analysis.

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effectiveness of the cap is to test whether the change in growth rates over time for the control group differs from the change in growth rates over time for the experimental group. If the changes in property tax growth rates are the same for both the control group and the experimental group, we conclude that the tax cap measure has not been effective. If the changes in growth rates differ, in particular if the property tax growth rate falls much more significantly for the experimental group than for the control group, then we conclude that there is evidence that the tax cap has been effective. One problem with this methodology is that we control only for factors common to jurisdictions of the same type in the metropolitan area, such as common economic conditions and common state grants-in-aid formulas. There are certainly other factors specific to the individual jurisdictions that are likely to affect the growth rate of property taxes. For two types of jurisdictions, school districts and municipalities, we can take population growth, clearly one important jurisdictionspecific factor, into account. To do so, for school districts, we compare the growth rates of property taxes per pupil across time and groups, and for municipalities, we compare the growth rates of property taxes per capita across time and groups. For each of the five types of local government, Table 2 presents average annual property tax growth rates for the capped and never-capped groups and for the before-the-cap and during-the-cap periods. The first panel of Table 2 examines park districts. For the capped group average annual property tax growth rates declined sharply from 14.78% per year for the three-year period before the cap to 4.21% per year for the 3-year period during the cap. Since growth rates also declined for the uncapped group (from 9.47 to 7.18% per year), this evidence alone cannot be interpreted as an impact of the new cap law. The decline for park districts subject to the cap is, however, much larger than the decline for park districts never subject to the cap. The difference in trends of 2 8.23 percentage points is statistically significant (t-statistic of 3.61) suggesting that the cap may have had an impact on park districts. The second panel of Table 2 displays property tax growth rates for fire districts. Fire districts in both groups experienced large declines in property tax growth rates between the two periods. While the decline for the capped fire districts (from 14.09 to 7.59 percentage points) is larger than the decline (from 12.61 to 4.54) for the fire districts not subject to the cap, the difference in the changes in growth rates (1.56) is not statistically significant (t-statistic of 0.26). The results in the next three panels of Table 2, for library districts, municipalities and school districts, are similar to those for park districts. Coincident with the imposition of the cap the growth of property taxes declines for both groups, but the decline for the capped group is significantly larger (at only the 10% confidence level for municipalities). Because we have multiple years of population data for municipalities and we have annual observations on the number of pupils for each school district, we can

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Table 2 Average annual growth rates of property taxes Number of jurisdictions

Growth rate before the cap

Growth rate during the cap

Park districts Capped group Never capped group

72 82

14.78 9.47

4.21 7.18

Fire districts Capped group Never capped group

97 27

14.09 12.61

7.59 4.54

Library districts Capped group Never capped group

46 42

17.90 9.49

8.01 6.58

Municipalities Capped group Never capped group

104 134

14.57 9.03

7.14 7.55

School Districts Capped group Never capped group

140 142

14.76 10.69

7.58 7.34

Differences between groups in trends before and after the cap

2 8.23 (3.61)

1.56 (0.26)

2 6.99 (3.08)

2 5.95 (1.89)

2 3.83 (5.19)

Average annual growth rates of property taxes per capita or per pupil Municipalities ( per capita) Capped group 104 Never capped group 134

11.77 9.30

3.37 6.40

School districts ( per pupil) Capped group 140 Never capped group 142

11.79 9.53

4.20 4.76

2 5.48 (1.87)

2 2.81 (3.47)

Notes: The capped group consists of jurisdictions subject to the tax cap starting in tax year 1991. The never capped group consists of jurisdictions never subject to the cap during the period analyzed. The period before the cap consists of tax years 1987 through 1990. The period during the cap consists of tax years 1991 through 1993, with the growth rate calculated from 1990, the last year before the cap. The growth rates are average annual percentage growth rates of total property taxes. The ‘‘Differences between groups in trends before and after the cap’’ is the change in growth rates between the two periods for the capped groups minus the change in growth rates between the two periods for the never capped groups. The figures in parentheses are absolute values of t-statistics (calculated using variances of the sample mean).

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examine the growth of property taxes per pupil and per capita.9 The last two panels of Table 2 present the average annual growth rates of municipal property taxes per capita and school district property taxes per pupil. These adjustments narrow the differences in the downward trends between the capped and uncapped groups, but for both municipalities and schools the decline for the capped group is still significantly larger (again, at only the 10% level of significance for municipalities). There are at least two problems with the evidence presented in Table 2. First, except for the per capita and per pupil adjustments in the last two panels, the method only controls for factors common to all jurisdictions. Second, the comparison of average annual growth rates across periods does not allow for cleanly separate annual effects, which may be important for distinguishing withinperiod trends from the effects of the cap, especially since the cap took effect during the 1991 recession. With regression analysis we can partially address these shortcomings. For each type of jurisdiction we estimate two OLS regressions (three for municipalities) with the annual growth rate of property taxes (or property taxes per capita or per pupil) as the dependent variable. In results not reported here, each regression is estimated with fixed jurisdiction effects. Because the results are very similar to the results without fixed effects, we only report the results for regressions without fixed effects. Each regression is estimated on a panel data set with six annual growth rate periods and with the number of jurisdictions ranging from 88 libraries to 282 school districts. In the regression analysis we have omitted outlier observations, which we define to be any year of observation in which property taxes more than doubled or declined by more than a half. Our rationale for omitting these observations is that property tax increases or decreases of this magnitude are attributable to unusual circumstances – such as a large bond issue (or bond retirement), a major annexation, a major change in service responsibility, or reporting changes in the timing of receipts – rather than normal operations. This is not behavior we hope to explain with our models. In the simplest form of the regression, we include seven dummy variables (eight for municipalities). The variable Located in Collar Counties takes the value one for jurisdictions located in the collar counties and zero for jurisdictions located in Cook County. We expect the growth rate of property taxes to be higher for jurisdictions located in the collar counties. The variable Home Rule applies only to municipalities and takes the value one if the municipality has home-rule status and zero otherwise. We do not have a strong prior on this variable. Home-rule municipalities have greater access to non-property tax revenues and greater 9

The population data for municipalities are problematic. The Northeastern Illinois Planning Commission (NIPC) relied on census data for 1980 and 1990 and some method of extrapolation for 1986, 1988, and 1992. We interpolated annual population estimates for 1987, 1989, and 1991 and extrapolated for 1993 using the NIPC data.

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authority to set property tax rates. However, property tax revenues are driven both by tax rates and assessed valuations, and we have no reason to expect differences in the growth rates of assessed valuations between home-rule and non-home-rule municipalities. To control for annual time effects five dummy variables for annual growth rate periods are included. Except for the mild recession of 1991, the metropolitan economy experienced fairly steady growth throughout the period of analysis. The Capped in 1991 variable takes the value one only in the 1990-to-1991, 1991-to1992, and 1992-to-1993 periods and only for the jurisdictions subject to the cap; it is zero otherwise. The Capped in 1991 variable is our hypothesis variable. If the cap has had a restraining effect, we would expect to find a negative coefficient for this variable. The second type of regression retains the dummy variables and includes variables for relevant economic and demographic factors. For all types of jurisdictions we include annual observations on the residential share of total assessed property valuation. This variable may affect property tax growth rates if the demands placed on local government differ by class of property or if nonresidential property tax burdens can be exported (see Ladd, 1975). For all jurisdictions except school districts we include one cross section of observations for 1990 Population (measured in thousands). The 1990 population data for the special districts are drawn from information reported to the Illinois Comptroller’s Office and the data are not complete. The level of population may affect property tax growth rates if large (or small) jurisdictions have faster (or slower) growth in population or business development. A convergence argument could be made that smaller jurisdictions might experience faster population growth and thus faster growth in property taxes. For municipalities we have data for three additional variables. One cross section of data on Income Per Capita in 1989 was obtained from the Northeastern Illinois Planning Commission. This variable may affect property tax growth rates if higher income municipalities exhibit a systematically stronger taste for increasing or decreasing property taxes. A variable for Population Growth over the period is defined as the average annual percentage growth in population from 1986 to 1990 for the first three growth periods, and the average annual percentage growth in population from 1990 to 1992 for the final three growth periods. Population and property taxes are expected to move together. Building permit data were obtained from the Bell Federal Savings and Loan Association (1994) and were used to construct a variable that measures the amount of new property added in a year relative to already existing property at the beginning of the period. This variable is meant to capture the effect of rapid real estate development on property tax growth rates and also to account for the specific feature of the law that exempts new property from the tax cap in the year it is added to the rolls. Finally, for school districts we define two additional variables: Growth in Average Daily Attendance and Percentage Students Low Income. Annual data for

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these variables were obtained from the Illinois State Board of Education. We measure percentage of students from low income families as percentage of students on the federally-subsidized school lunch program. The growth in average daily attendance should capture population pressures on the schools, while the percentage low income students might have an effect on property tax growth rates if poor districts systematically have lower or higher need or desire for increasing expenditures (and thus property taxes). In Table 3 we present a sample regression for each of three types of jurisdictions: park districts, fire districts, and library districts. The regressions include the seven dummy variables for location in the collar counties and for different time periods, as well as a variable for residential share of assessed property and for 1990 population level. The Located in Collar Counties variable suggests that over the entire period collar-county park districts experienced 5.51 percent per year higher growth in property taxes, collar-county fire districts experienced 5.70 percent per year higher growth in property taxes, and collarcounty library districts experienced 8.22 percent per year higher growth in property taxes relative to their suburban Cook County counterparts. Focussing on the hypothesis variable, Capped in 1991, the cap appears to have reduced annual Table 3 Selected regressions with annual growth in property taxes as dependent variable (absolute values of t-statistics in parentheses)

Constant Located in collar counties Residential share of assessed property 1990 population 1988 to 1989 1989 to 1990 1990 to 1991 1991 to 1992 1992 to 1993 Capped in 1991 Number of observations R2

Park districts

Fire districts

Library districts

6.00 (3.12) 5.51 (3.78) 0.05 (2.10) 2 0.04 (1.64) 0.14 (0.08) 3.45 (2.01) 4.61 (2.35) 2 2.85 (1.45) 2 2.30 (1.17) 2 8.60 (4.34) 803 0.10

7.45 (2.56) 5.70 (2.89) 2 0.00 (0.01) 0.08 (2.38) 0.49 (0.24) 2 1.35 (0.67) 2 2.07 (0.70) 2 4.68 (1.59) 2 1.64 (0.56) 2 4.97 (1.80) 644 0.07

5.46 (2.11) 8.22 (4.21) 2 0.01 (0.22) 0.04 (1.33) 5.28 (2.40) 4.78 (2.19) 3.22 (1.26) 2 0.76 (0.30) 0.77 (0.30) 2 6.71 (2.67) 516 0.10

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property tax growth rates for park districts by 8.60 percentage points, for fire districts by 4.97 percentage points, and for library districts by 6.71 percentage points. Based on these regressions, the cap appears to have had a restraining effect on the growth rate of property taxes. In Table 4 we present two regressions each for municipalities and school districts. The difference in the two regression is the definition of the dependent Table 4 Annual growth in property taxes, property taxes per capita, or property taxes per pupil as dependent variable (absolute values of t-statistics in parentheses) Municipalities Property taxes Constant Located in collars Counties Home rule Residential share of assessed property Growth in average daily attendance Percentage students 1990 population Population growth over Income per capita 1989 1988 to 1989 1989 to 1990 1990 to 1991 1991 to 1992 1992 to 1993 Capped in 1991 Number of observations R2

School districts Property taxes taxes per capita

9.99 (8.11) 2.19 (2.82) 2 0.83 (0.99) 2 0.00 (0.26)

10.73 (7.36) 2.31 (2.49) 2 0.29 (0.31) 2 0.02 (1.06)

2 0.03 (1.40) 0.21 (3.59) 0.00 (0.03) 2 2.94 (2.88) 2 0.30 (0.29) 2 0.95 (0.84) 2 3.18 (2.83) 2 2.12 (1.89) 2 4.63 (4.23) 1412 0.05

2 0.06 (2.68) 2 0.49 (2.35) 0.00 (0.06) 2 1.99 (1.62) 1.27 (0.96) 2 0.96 (0.81) 2 3.06 (2.74) 2 2.05 (1.81) 2 5.16 (4.85) 1412 0.11

Property taxes

Property taxes per pupil

8.37 (9.64) 2.52 (4.25)

8.66 (10.04) 2.42 (4.12)

0.04 (3.47) 0.33 (8.75) 2 2.52 (1.70)

0.04 (3.31) 2 0.63 (16.98) 2 1.72 (1.17)

2 1.10 (1.62) 2.37 (3.47) 2 2.20 (2.78) 2 5.70 (7.22) 2 2.39 (3.03) 2 3.61 (4.58) 1692 0.20

2 1.40 (2.07) 1.87 (2.76) 2 2.60 (3.31) 2 5.98 (7.62) 2 2.76 (3.51) 2 3.53 (4.52) 1692 0.27

Note: For the municipal property taxes per capita specification only, standard errors are corrected for heteroskedasticity following White (1980).

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variable. The results for the Capped in 1991 variable indicate that the cap has had an effect on property tax growth rates for municipalities and school districts. The estimated coefficients on the cap variable are very similar across the two specifications for each type of district, and the size of the effect is larger for municipalities than for school districts. It is noteworthy, given that home-rule municipalities have a wider array of revenue sources available to them than non-home-rule municipalities, that the home-rule variable in the regression for municipalities has little effect. For municipalities only we can use the home-rule versus non-home-rule status to explore further the differential effect of the tax cap from the effect of being located in the collar counties, and we can separate more cleanly the effect of the tax cap from the effect of home-rule status. The group subject to the tax cap includes 104 non-home-rule municipalities in the collar counties. The group not subject to the tax cap includes 22 home-rule municipalities in the collar counties, and 52 home-rule and 61 non-home-rule municipalities in Cook County. In regressions not reported here we estimate equations comparable to the ones in Table 4 on a sample restricted to non-home-rule municipalities only (104 subject to the cap in the collar counties and 61 not subject to the cap in Cook County). The coefficients on the Capped in 1991 variable are very similar to the coefficient displayed in Table 4 in that they are large, negative, and significant. Thus the tax cap appears to have a separate effect from the effect, if any, of home-rule status. In another set of regressions not reported here we estimate equations comparable to the one displayed in Table 4 on a sample restricted to home-rule municipalities only (22 in the collar counties and 52 in Cook County). None of the home-rule municipalities is subject to the cap so we would expect the estimated coefficients on the Capped in 1991 variable (which takes a value of one in the post-1991 years for the municipalities in the collar counties) to be zero. In fact the estimated coefficients on the Capped in 1991 variable are negative, but either insignificantly different from zero or only marginally significant (absolute values of t-statistics ranging from 1.09 to 1.62). This suggests that there may be something about location in the collar counties in the latter years of the sample that affected property tax growth rates in addition to the imposition of the cap. Still, the results using the full sample yield much stronger negative impacts of the cap, thus indicating that the cap has had an effect on property tax growth rates of municipalities. The results for the effect of the tax cap are quite robust to changes in specification. In Table 5 we display the estimated coefficient for the Capped in 1991 variable derived from several different specifications of the property tax growth rate equation for all five types of jurisdictions. We estimate two specifications for each of the three types of special districts (parks, fire districts, and libraries) and get very similar results for the Capped in 1991 variable. The results seem to indicate that the cap has been effective for park and library districts, but the effect has not been as strong for fire districts. For municipalities and school districts we estimate one set of regressions with growth rate in property taxes as

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Table 5 Estimated coefficients for capped in 1991 variable (absolute values of t-statistics in parentheses)

Park districts Fire districts Library districts Municipalities Municipalities (per capita) School districts School districts (per pupil)

Specification (1)

Specification (2)

2 8.48 (4.51) 2 3.59 (1.32) 2 6.73 (2.71) 2 4.51 (4.13) 2 5.00 (4.62) 2 3.80 (4.69) 2 2.83 (3.35)

2 8.60 (4.34) 2 4.97 (1.80) 2 6.71 (2.67) 2 4.63 (4.23) 2 5.16 (4.85) 2 3.61 (4.58) 2 3.53 (4.52)

Specification (3)

4.06 (3.23) 2 4.10 (3.47)

Notes: The Capped in 1991 variable takes the value one only for jurisdictions subject to the cap and only for the three time periods after the imposition of the cap. Specification (1) includes a constant plus seven dummy variables: a variable that takes the value one for location in the collar counties, five variables for annual growth periods with 1987 to 1988 omitted, and the Capped in 1991 variable. For municipalities this specification includes a variable that takes on the value of one for home-rule governments. Specification (2), the specification shown in Tables 3 and 4, includes the variables in specification (1) plus variables that take jurisdiction-specific values. For park, fire and library districts, these variables include 1990 population and the residential share of assessed property valuation. For municipalities, these variables include 1990 population, the residential share of assessed property valuation, a variable measuring population growth over the period, and income per capita in 1989. For school districts these variables include the residential share of assessed property valuation, growth in average daily attendance, and the percentage of students with low income. Specification (3) for municipalities adds a variable with building permit value as a share of existing assessed property value. Missing values for this variable result in the loss of a number of observations. For the municipal per capita specifications only, standard errors are corrected for heteroskedasticity following White (1980).

the dependent variable and another set of regressions with growth rate in property taxes per capita or per pupil as the dependent variable. The cap appears to have been effective for both municipalities and school districts. The range in estimated coefficients on the Capped in 1991 variable for municipalities is from 2 4.10 to 2 5.16 and for school districts from 2 2.83 to 2 3.80. The result that school districts have been affected by the property tax cap is not surprising. School districts in Illinois have virtually no other local source of revenue; a large majority of them are at the maximum of the allowable property tax rates, which would seem to indicate that additional constraints would be binding; and the anecdotes in the media have described school districts forced to cut programs or staff in order to comply with the tax cap. In the next section we examine school district expenditures to see if the systematic evidence supports the anecdotal evidence.

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3. School district expenditures Although the tax cap is imposed on the growth rate in property taxes, its impact is felt on the budgets of local governments and therefore on expenditures. Here we examine the expenditures of school districts, fiscally the most important form of local government. The data on school district expenditures were obtained from the Illinois State Board of Education. These data are by school or fiscal year beginning with FY 1986–87 and ending with FY 1993–94. In Fig. 1 we display total expenditures per pupil for school districts. The numbers are the averages for the two groups of districts (the control or nevercapped group and the experimental or ever-capped group), with the first five years occurring during the period before the imposition of the cap.10 Throughout the period, spending per pupil was higher among the never-capped group of districts (school districts in Cook County) than among the group capped in 1991 (school districts in the collar counties), and spending per pupil increased for both groups each year. It is also apparent that the rate of increase in total spending slowed for both groups in the last two years. Spending increased about $500 per pupil each year for all districts until between 1991–92 and 1992–93 when the average annual increase slowed to about $100 per pupil. If the cap had caused a disruption in

Fig. 1. 10

Illinois property tax collections for a given tax year are paid to individual governments in June and September of the following calendar year. Since school districts have a July 1 to June 30 fiscal year, collections from tax year 1991 – the first year of the cap – were received half in the 1991–92 fiscal year and half in the 1992–93 fiscal year.

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spending for the affected jurisdictions, we would expect to see a break – a change in pattern – between FY 1990–91 (uncapped), FY 1991–92 (half capped), and FY 1992–93 (fully capped) for the affected districts only. At this gross level, it is difficult to discern any such effect. Two important subcategories of spending for schools are operating expenditures, which exclude capital spending, and instructional expenditures, which exclude not only capital spending but also spending on administration and support staff. Operating and instructional spending increased over this time period in concert for the two groups of school districts, and spending was higher on average for both categories for the districts in Cook county relative to the collar county. As with total expenditures it is not easy to discern a break in the trend for the capped districts that differs from the never-capped districts around the time of the imposition of the cap. In Table 6 we present regressions where the dependent variable is the fiscalyear-to-fiscal-year growth rate in school district expenditures – total, operating, or instructional – and the independent variables are the usual set of time and location

Table 6 School district expenditures regressions with annual growth in expenditures as dependent variable (absolute values of t-statistics in parentheses)

Constant Located in collar counties Residential share of assessed property Growth in average daily attendance Percentage students low income FY 1988–89 to 1989–90 FY 1989–90 to 1990–91 FY 1990–91 to 1991–92 FY 1991–92 to 1992–93 FY 1992–93 to 1993–94 Capped in 1991 Number of observations R2

Total

Operating

Instructional

6.79 (3.76) 2.98 (2.42) 0.02 (0.76) 0.42 (5.34) 2 2.12 (0.69) 1.03 (0.73) 0.65 (0.45) 1.97 (1.20) 2 3.26 (1.99) 2 3.37 (2.05) 2 2.74 (1.68) 1692 0.05

6.09 (9.76) 1.82 (4.27) 0.02 (1.99) 0.57 (21.20) 2 2.12 (1.99) 0.04 (0.08) 2 0.41 (0.83) 2 0.49 (0.86) 2 2.15 (3.78) 2 3.90 (6.86) 2 1.75 (3.09) 1692 0.29

7.05 (10.98) 1.28 (0.44) 0.02 (1.76) 0.53 (18.92) 2 2.09 (1.90) 2 0.73 (1.45) 2 0.31 (0.61) 2 1.69 (2.88) 2 2.86 (4.89) 2 3.73 (6.36) 2 0.28 (0.48) 1692 0.24

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dummy variables plus the available economic and demographic variables. The capped in 1991 variable here takes a value of one for school districts located in the collar counties during the change periods FY 1990–91 to 1991–92, FY 1991–92 to 1992–93, and FY 1992–93 to 1993–94. The omitted time dummy variable is change period FY 1987–88 to 1988–89. The coefficient on the Capped in 1991 variable is negative in all three regressions, but only marginally significant for total expenditures and insignificantly different from zero for instructional expenditures. The capped in 1991 variable is significant for operating expenditures, which includes all forms of non-capital expenditures including instructional spending as well as spending on administration and support services. The fact that school districts subject to the cap do appear to limit overall operating expenditures but not instructional spending indicates that the short run response of school districts to the cap may be to protect or maintain instructional spending at the expense of non-instructional spending.11

4. Conclusion In the past 25 years the nature of state government involvement in local government finances has become more constraining rather than facilitating. Beginning with Proposition 13 in California in 1978 the overriding presumption seems to be that local governments are fiscally imprudent or Leviathan-like and that state-imposed constraints on their revenue or spending authority are desirable. This prevailing view contrasts rather sharply with the median voter theory of local governments being close to and accountable to local voters. Limits on the use of the local property tax are of particular interest and concern, given that for many local governments, particularly school districts, which are fiscally the most important local governments, the property tax is the only local source of revenue and the only means of providing a link between spending authority and revenueraising responsibility. Empirical studies of the effects of tax and expenditure limitation measures on local government fiscal behavior provide a partial test of the validity of competing models of local governments. We employ a sample of Illinois local governments to examine the effect of a 1991 property tax cap that was imposed on only a subsample of the local jurisdictions. We find that the magnitude of the impact of the cap differs across types of jurisdictions, but, with the possible exception of fire districts, that the cap has had a restraining effect on the growth of property taxes. The cap also appears to have had a restraining effect on school district operating expenditures, but no effect on school district instructional spending. While 11

These results are robust to specifications with different sets of independent variables and with a per-pupil definition of the dependent variable.

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preliminary and short run in nature, these results are consistent with the Leviathan, budget-maximizing theory of government behavior.12 The long run effects of the cap may be larger, if the cumulative nature of the tax cap is important, or they may be smaller, if the jurisdictions subject to the cap devise methods of getting around the cap or if changes in the characteristics of the underlying economy make the cap less binding. Further work is needed to understand fully the implications of the tax cap for local government behavior and for state and local intergovernmental relations. We need a better understanding of how the behavior of jurisdictions subject to the cap has changed under the cap. In the complex, second-best world of state-local fiscal relations, the intended and actual effects of policy changes often differ.

Acknowledgements The authors thank Tom Downes, Dave Merriman, two anonymous referees, and seminar participants at Northern Illinois University, Lake Forest College, the University of Michigan, the Federal Reserve Bank of San Francisco, the Harvard / MIT Public Economics Workshop, and Hunter College for useful comments and suggestions.

References Bell Federal Savings and Loan Association, 1994. Survey of Building: Chicago Metropolitan Area, Author, Chicago, IL. Courant, P.N., Rubinfeld, D.L., 1981. On the welfare effects of tax limitation. Journal of Public Economics 16, 289–316. Downes, T.A., R.F. Dye, T.J. McGuire, forthcoming. Do limits matter? Evidence on the effects of tax limitations on student performance. Journal of Urban Economics. Fisher, R.C., Gade, M.N., 1991. Local property tax and expenditure limits. In: McGuire, T.J., Naimark, D.W. (Eds.), State and Local Finance for the 1990s: A Case Study of Arizona. Arizona State University, Tempe, AZ, pp. 449–464. Illinois Department of Revenue, 1993. Illinois Property Tax Statistics 1991. State of Illinois, Springfield, IL. Joyce, P.G., Mullins, D.R., 1991. The changing fiscal structure of the state and local public sector: the impact of tax and expenditure limitation. Public Administration Review 51, 240–253. Ladd, H.F., 1975. Local education expenditures, fiscal capacity and the composition of the property tax base. National Tax Journal 28, 1–18.

12

This conclusion must be tempered by the fact that the number and passage rates of referenda to override the tax cap have been small (see McGuire and Rueben, forthcoming). This mechanism for voter preference revelation, needed for a clean test of the two theories of government behavior, may not be operating well in Illinois.

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McGuire, T.J., Rueben, K.S., forthcoming. Tax and bond referenda in California and Illinois: Observations on Local Governments Operating Under State-imposed Constraints. Proceedings Eighty-Ninth Annual Conference of the National Tax Association, 1996, Boston, MA. Merriman, D., 1987. The Control of Municipal Budgets: Toward the Effective Design of Tax and Expenditure Limitations. Greenwood Press, Westport, CT. O’Sullivan, A., Sexton, T.A., Sheffrin, S.M., 1995. Property Taxes and Tax Revolts: the Legacy of Proposition 13. Cambridge University Press, Cambridge. Poterba, J.M., Rueben, K.S., 1995. The effect of property tax limits on wages and employment in the local public sector. American Economic Review 85, 384–389. Preston, A.E., Ichniowski, C., 1991. A national perspective on the nature and effects of the local property tax revolt, 1976-1986. National Tax Journal 44, 123–145. Temple, J., 1996. Community composition and voter support for tax limitations: evidence from home-rule elections. Southern Economic Journal 62, 1002–1016. White, H., 1980. A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica 48, 817–838.