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Civic Report
No. 1  March 1996


New Jersey Income Tax Cut Led To Savings,
Not Rise In Local Taxes

Timothy J. Goodspeed
Professor of Economics, Hunter College
Peter D. Salins
Professor of Urban Affairs and Planning, Hunter College and Senior Fellow, Manhattan Institute

Introduction

Governor Christine Todd Whitman instituted cuts in the state income tax beginning in fiscal year l995.  This has direct implications for local financing decisions because revenue from the New Jersey income tax is, by law, dedicated solely to relief of local property taxes, to which New Jerseyans are also subject and which are levied by both municipalities and local school districts.  No revenue from the state income tax is allocated to general funds. This connection has led to some fear that the state income tax cuts would simply lead to dollar-for-dollar increases in local property taxes. The evidence suggests that this has not been the case so far, and is not likely to be the case in the future.

First, historically, there has been little or no relationship between changes in the state income tax and local property taxes. They simply do not seem to be connected. For instance, during the period from 1985-1990, property taxes increased steadily in real terms (at about 7 percent per year) while income tax revenue was extremely variable (real income tax revenue increased by over 20 percent in 1987 and decreased by over 5 percent in 1988).

Second, an examination of data for 1995, the first year of the Whitman tax cuts, shows virtually no change in real property taxes relative to 1994, further bearing out the fact that the two taxes are not related.

Third, an empirical phenomenon observed in previous studies indicates that lump sum grants from higher levels of government lead to higher levels of spending than if the funds are collected locally. This study finds that this phenomenon holds for New Jersey as well.  In other words, localities are found to spend more money when funds come from the state than if taxes are collected and spent directly by the school district.

Since 83 percent of local property taxes go to school districts, the study examined school district taxation and expenditure policy in detail. (In New Jersey, both school districts and municipalities have the power to levy taxes.)  An econometric model was developed to look at the relationship between school district property taxes and changes in the state income tax. According to the model, New Jersey taxpayers have saved 78 cents for each dollar decrease in state income tax.  The model, which takes into account how school districts have historically reacted, predicts that relationship will continue to hold.  Based on that prediction, New Jerseyans will save approximately $895 million over the five-year period from 1994 to 1998.

History

An overview of New Jersey income and property tax collections is given in Figures 1, 2, and 3 for the years 1985 to 1994.  The income tax data are taken from various issues of the Annual Report of the New Jersey Division of Taxation.  The property tax data was compiled by the New Jersey Department of Community Affairs from the County Abstract of Ratables and includes the three levels of government that levy property taxes:  school districts, municipal governments, and county governments.  Figure 1 gives tax collections in nominal terms and Figure 2 gives these figures in real terms. (That is to say, Figure 2 numbers are adjusted for inflation, using a standard methodology involving the Consumer Price Index baseline of 1982-1984 dollars.) Figure 3 plots the growth rate of real property and income taxes during this period.

The growth of property taxes can be thought of in two segments.  The first segment shows a fairly steady rise from 1985 to 1990 in real terms; the real growth rate of property taxes for these years ranges from 6 to 7 percent except for 1988 when the real growth rate was 8 percent.  After a fall in real terms in 1991, property taxes continued steady but lower growth in real terms from l992 to 1994; the growth rate for these years ranges from 1 to 2 percent.

Figure 1--New Jersey Property and Income Tax Collections--1985-1994

Figure 2--Real Revenue of New Jersey Property and Income Tax--1985-1994

Figure 3--Real Growth of New Jersey Property and Income Tax--1985-1994

The growth of income tax revenues shows an upward trend, but also shows high variability. The real growth rate rose to over 20 percent in 1987, fell to -5.5 percent in 1989, rose again to 8 percent in 1989 and fell to -3.4 percent in 1990. The tax increases passed under former Governor Jim Florio are reflected in the increase in the real growth rate (to 10 percent and 17 percent in 1991 and 1992, respectively).  The real growth rate then fell to 1 percent in 1993 and to 2 percent in 1994.

Taken together, these figures demonstrate very little historical relationship between New Jersey income and property taxes.  It is true that both have tended to rise in real terms over time.  But the period from 1985 to l990 saw a fairly steady increase in real property tax revenue (about 6 percent to 7 percent per year) but large swings in the growth rate of the income tax.  (In 1987, income tax revenues rose by over 20 percent and in 1988 income tax revenues fell by over 5 percent). In 1991 there was an initial fall in the rate of real growth.  But there followed a period of steady growth (1 percent to 2 percent per year) from 1992 to 1994.

Table 1

Real Per Capita New Jersey Figures for Sample of 509 School Districts
(1982-1984 Dollars)

 

1991

1992

1993

1994

1995

Overall

State Aid

236

271

255

209

200

234

Property Tax

425

422

428

479

480

447

School Expenditures

649

718

648

715

750

696

Income

9,482

9,405

9,386

9,389

9,372

9,407

School District Survey

Most of the revenue from the New Jersey income tax is given as aid to local school districts. Let’s take fiscal 1994 as an example to illustrate how this process works. Total revenue collected from the New Jersey individual income tax amounted to $4.5 billion. This amount was transferred to the property tax relief fund which, along with a small surplus from previous years, amounted to $4.6 billion. Of this amount, $3.8 billion, or about 83 percent of the property tax relief fund, was given to local school districts for educational spending.  Of the remaining amount, $330 million was refunded to individuals in the form of homestead rebates, and $440 million was given to municipalities.

Since the revenues from the state income tax go primarily to local school districts, the remainder of the study concentrates on how changes in state income tax have affected property taxes levied by local school districts.  For this analysis we used data on a sample of 509 individual New Jersey school districts for the fiscal years 1991-1995, supplied by the New Jersey Department of Education. A school district was included in the sample if data were available for that district for all  five years.

The first piece of information that can be gleaned from the data is that real property tax revenue was virtually unchanged from 1994 to 1995, despite the Whitman state tax cuts.  (Real property tax revenue was $3.674 billion in 1994 and $3.691 billion in 1995.)

The second part of our examination involves an effort to reveal the historic relationship between school district tax and expenditure policy and then to use that information to predict how school districts are likely to behave in the next several years. This involves the creation of an econometric equation which takes into account both numerical data and behavioral modeling techniques.  The methodology is discussed in detail in the Appendix.

The results of the analysis show that school districts have not, in the past, raised their levels of taxation commensurate with cuts in the state income tax. In fact, the historical trends suggest that overall, New Jersey taxpayers will save 78 cents for each dollar the state income tax is lowered. It is worth reiterating at this point, regardless of the historical trends, that the Whitman tax cuts have not resulted in any local property tax hikes.  Taxpayers have saved a full dollar for every dollar cut in the income tax.

The New Jersey Treasury Department estimates a cumulative decrease of $1.358 billion in revenues as a result of the state income tax cut (compared to the revenue expected if taxes had remained at 1993 levels).  School districts would have received about 83 percent of this, or $1.147 billion.  Using our estimate of a 78-cent decrease in taxes for every dollar cut in the income tax, New Jersey taxpayers can expect to save about $895 million on school district taxes over the five-year period from 1994 to 1998. (The econometric study did not consider the relationship between fluctuations in state income tax and other municipal tax rates or homestead rebate provisions, nor did it consider other state aid to localities which could further offset the impact of the income    tax cut.)

The contention of Governor Whitman, that reduced reliance on state income taxes will lead to less than a dollar-for-dollar increase in local taxes, is therefore borne out by this study. The phenomenon has also been recorded in the economics literature. Lower level governments tend to spend more out of grants that come from higher levels of government than out of locally raised revenue. This phenomenon has been dubbed the “flypaper effect” because “money sticks where it hits” (i.e., localities spend most of the aid).

Understanding the flypaper effect

The flypaper effect normally refers to the effect of an increase in grants on spending decisions, and has been most often tested empirically by examining the impact of federal grants on state and local governmental behavior. The conclusions of this paper suggest that the flypaper effect also works in reverse.

To explain the phenomenon further, it is useful to work through a simple example.  Suppose that the residents of a local school district rely on locally raised revenue and have a median income of $20,000. Suppose that the residents have decided to spend $1,000 per person (5 percent of their income) on local schools.  Now suppose that the state gives the local school district a $50 per person grant to be spent on education.  In effect each individual will experience a $50 increase in income.  Based on their commitment to spend 5 percent of their income on education, the residents of the district would theoretically want to spend about 5 percent of the grant ($2.50) on education. Since they must spend the entire grant on education, they would probably want to lower local taxes by $47.50, leaving $952.50 in local taxes.  With the $50 grant, total educational spending then rises to $1,002.50.

However, the economics literature notes that such a scenario is unlikely to unfold in real life. Instead, we observe the results of the flypaper effect.  Typically, the local school district would actually spend 40 - 50 percent of the grant, or roughly $25. Local taxes would then be lowered by $25 rather than by $47.50.

To see the effect of a spending decrease, we can simply work through the example in reverse. Suppose we begin by assuming that the $50 grant is currently given to the locality.  Since 50 percent of the grant is spent on schools, total spending on education in the district is $1,025. Now consider taking the grant away from the local school district. According to our understanding of the flypaper effect we would assume that the local district would not raise taxes commensurate with the decrease in state aid.  It is more likely that the district would want to continue funding education at the 5 percent level, or $1,000. That is, while state taxes would decrease by $50, local property taxes are likely to increase by only $25.  This is, indeed, the phenomenon we appear to be observing in New Jersey.

Explanations for the flypaper effect

While the empirical phenomenon of the flypaper effect is well documented, economists are divided on the causes and several explanations have been suggested. One possibility is that local officials are prone to try to conceal the level of grants from the electorate. If they are successful, the electorate may see a fall in local taxes and be unaware that it results from grants.  Local officials can then take credit for both lowering taxes and increasing spending on education.

Another theory emphasizes the ability of local bureaucrats to control the spending options available to the voter, thereby increasing the budget. For example, it is possible to hold a referendum in which the alternative to a defeated budget increase is a significant decrease. A voter may, therefore, choose to support the higher spending level because the alternative is even worse.

This may be applicable to the New Jersey case since many school districts vote directly on a proposed school budget.  In some districts, if the budget is defeated, the city council decides on a spending level, which is typically close to the previous year’s budget. Voters may prefer a bloated school budget as the lesser of two evils.

Another possibility is that it is easier to spend money when someone else is paying. This is probably most applicable to relatively poor school districts, which tend to pay less in state tax than they receive in grants. These districts pay a lower price for education when the state income tax is high. Consequently they favor higher state income taxes and higher grants.

Finally, there is an argument based on the idea that property values are related positively to education spending and negatively to local taxes.  If spending on education goes up in a district (assuming local taxes remain constant), there will then be increased demand for homes in that district, leading to increased property values.  In this sense, spending on education has a spillover effect into the private sector. On the other hand, if increased spending must be accompanied by increased local taxes, the property is no longer as attractive.

If, however, increased spending on education is instead funded by state taxes, there would be increased demand for housing in districts that spend relatively more on education, since taxes paid would remain the same no matter where an individual resides in the state.  Thus, the argument goes that homeowners can increase their property values by relying more on state taxes than local taxes and increasing spending on education relatively more than other districts.

Conclusion

We began this study to examine the relationship between New Jersey’s state income tax and the state’s local property taxes.  Specifically, we wanted to determine whether New Jersey residents are paying less tax overall following Governor Whitman’s cuts in the state’s income tax.

The study determined that historically there has been little or no relationship between income tax rates, which have varied significantly, and property tax rates, which have increased consistently but moderately. Moreover, an examination of data from 1995, the first year of the cuts, showed virtually no change in real property taxes relative to 1994.  And an econometric analysis showed that, overall, New Jersey taxpayers will receive 78 cents of every dollar cut from the state income tax. It is estimated that taxpayers will save about $895 million on school district taxes over the five-year period from 1994 to 1998.

This phenomenon was attributed to what economists have termed the flypaper effect; that is, localities are more likely to spend lump sum grants from the state than they are to spend money raised locally.

A final point: both local and state tax bases in New Jersey are projected to grow in the years ahead. As a result, the sharp reduction in state tax rates, and the modest increase in local tax rates, may still fund higher absolute spending levels in local schools. So it is conceivable that New Jerseyans may be able to look forward to what many would consider “the best of both worlds” — lower combined state and local taxes and continued — albeit slower — growth in local school spending.

About the Authors

Timothy J. Goodspeed, Professor of Economics, Hunter College; and Peter D. Salins, Professor of Urban Affairs and Planning, Hunter College and Senior Fellow, Manhattan Institute. The survey was commissioned by the Manhattan Institute’s Center for Civic Innovation.

The Center for Civic Innovation gratefully acknowledges the assistance of the New Jersey Policy Research Organization in the preparation of this report.

Appendix:  An Econometric Study

To better understand the relationship between New Jersey income and property taxes, we turn to more disaggregated data. As mentioned earlier, the revenue from the New Jersey income tax is earmarked for property tax relief.  Most of the income tax revenue (83 percent in 1994) goes to aid local school districts, and we therefore concentrate on an analysis of local school districts.  We use data on individual New Jersey school districts for the fiscal years 1991-1995, supplied by the New Jersey Department of Education. Property taxes and state aid are taken from individual audit statements for each local school district.1  Enrollment and income figures were also provided by the Department of Education.  The data were combined by school district, and a panel data set was created.  A school district is in the sample if data were available for that district for all five years. This resulted in 509 districts represented in the sample over five years; the pooled data set therefore has 2,545 observations.

Table 1 gives a summary of the data. As income tax revenue and hence state aid to local school districts change, local school districts may respond by altering both expenditures and property taxes. Once we recognize that local governments can change expenditures as well as local property taxes, we can immediately see that any increase in property taxes resulting from a fall in state aid need not be dollar for dollar.  Suppose, for instance, that a $1 decrease in state aid would have led to a $1 increase in property taxes if expenditures had remained unchanged. Further suppose, however, that local governments are not as eager to spend out of own-source revenues as out of state aid, and that the $1 decrease in state aid results in a $.50 fall in expenditures and hence a $.50 increase in property taxes.  The behavioral response of local governments has reduced a $1 increase in property taxes to $.50.

In order to investigate the relationship between state aid and property taxes that takes into account other reasons for changes in property taxes, including the behavioral response of local school districts, we turn to regression analysis. A naive attempt to estimate the relationship between property taxes and state aid might start from the budget constraint of the local school district and postulate the linear relationship

Property Tax = b0 + b1 Expenditures + b2 StateAid + e

where epsilon is an error term.  The results from such an estimation are presented in the first column of Table 2, and we see a coefficient of -1 for state aid. The problem with this procedure is that it takes no account of the relationship between expenditures and state aid; consequently, we are left with the erroneous impression that lower state aid leads to a dollar-for-dollar increase in property taxes.

To estimate the true effect of a change in state aid on property taxes, we must take account of how changes in income affect expenditures and consequently property taxes and the behavioral response of school districts. To do this, we need to augment equation (1) by recognizing that expenditures are being endogenously determined by several factors, including state aid, income, and enrollment in a school district.  Hence, our model must include not only equation (1), but also a second equation:

Expenditures = µ0 + µ1 Income + µ2 StateAid + µ3 Enrollment + u

Substituting for expenditures in the first equation yields

Property Tax = (b0 + µ0b1 ) + b1µ1 Income + (b1µ2 + b2 )StateAid + b1µ3 Enrollment + n

The results of estimating this model are given in the second column of Table 2.  The coefficient of state aid in this equation is -.22, indicating that a fall of one real dollar in state aid leads to a real property tax increase of 22 cents. To understand this, notice that the coefficient of state aid in this equation depends not only on the direct effect of a change in state aid on property taxes (b2), but also on the behavioral response of a change in state aid on expenditures (a2) multiplied by the impact of the change in expenditures on property taxes (b1). Hence, any fall in real state aid is estimated to reduce expenditures by enough that property taxes only increase by 22 cents. This result is consistent with the claims of the Whitman administration that the state income tax cuts result in a net saving to New Jersey taxpayers.

Since the sample of school districts spans five years, it is useful to see whether the coefficient on state aid has changed over time.  This can be tested by including dummy variables for years and interacting the year dummy variables with state aid. The results from this regression are shown in the third column of Table 2. Of interest here is the significant coefficients on the interaction terms of 1994 and 1995.  This indicates that the response of property taxes to a change in state aid was significantly different in 1994 and 1995 relative to 1991

Of further interest is whether the change in property taxes induced by a change in per capita state aid differs depending on the average income of a school district. To test this, school districts were grouped into one of five income categories based on nominal per capita income: $0 to $7,500, $7,500 to $10,000, $10,000 to $12,500, $12,500 to $15,000, and greater than $15,000.  Dummy variables were constructed based on these categories. The income dummies and interactions of the income dummies with per capita state aid were included in a fourth regression, the results of which are shown in the fourth column of Table 2.

The final column of Table 2 includes both the year and income effects. Again, significant differences are seen for 1994 and 1995, and across income groups.

Table 2

Least Squares Regression Results
(t-statistics in parentheses)
Dependent Variable:  Per Capita Property Tax

Constant

71 (9.6)

189 (18.9)

135  (8.2)

288 (13.5)

182  (7.0)

Per Capita State Aid

.998 (-61.4)

-.22 (-10.4)

 -.095 (-1.82)

 .626 (8.5)

 1.00 (11.2)

Per Capita Expenditures

 .876 (77.4)

 

 

 

 

Per Capita Income

 

  .032 (43.2)

 .032 (43.6)

 .02 (17.5)

 .021 (18.7)

Enrollment

 

 .004 (3.59)

 .0036 (3.22)

 .001 (1.45)5

 .001 (1.13)

1992 Dummy

 

 

14 (.67)

 

1.94 (.104)

1993 Dummy

 

 

25 (1.28)

 

7.49 (.409)

1994 Dummy

 

 

95 (5.07)

 

117.4 (6.7)

1995 Dummy

 

 

96 (5.19)

 

119.2 (6.8)

Per Capita State Aid*1992 Dummy

 

 

 -.04  (-.59)

 

-.029 (-.461)

Per Capita State Aid*1993 Dummy

 

 

   -.068 (-1.01)

 

  -.057 (-.92)

Per Capita State Aid*1994 Dummy

 

 

-.192  (-2.88)

 

-.268  (-4.31)

Per Capita State Aid*1995 Dummy

 

 

 -.213 (-3.16)

 

-.305  (-4.86)

Income1 Dummy

 

 

 

 -93 (-3.72)

-44  (-1.75)

Income2 Dummy

 

 

 

-52 (-2.4)

 .57 (.026)

Income3 Dummy

 

 

 

15 (.77)

58 (2.93)

Income4 Dummy

 

 

 

55 (2.79)

92 (4.61)

Per Capita State Aid*Income1 Dummy

 

 

 

-.939 (-8.9)

-1.16 (-11.0)

Per Capita State Aid*Income2 Dummy

 

 

 

-.826 (-10.1)

-1.07  (-12.9)

Per Capita State Aid*Income3 Dummy

 

 

 

-.895 (-11.0)

-1.11 (-13.6)

Per Capita State Aid*Income4 Dummy

 

 

 

-.88 (-9.9)

-1.08 (-12.2)

R2

 .73

.48

 .49

.55

 .57

 


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SUMMARY:
Governor Christine Todd Whitman instituted cuts in the state income tax beginning in fiscal year l995. This has direct implications for local financing decisions because revenue from the New Jersey income tax is, by law, dedicated solely to relief of local property taxes, to which New Jerseyans are also subject and which are levied by both municipalities and local school districts.

TABLE OF CONTENTS:

Introduction

History

Figure 1--New Jersey Property and Income Tax Collections--1985-1994

Figure 2--Real Revenue of New Jersey Property and Income Tax--1985-1994

Figure 3--Real Growth of New Jersey Property and Income Tax--1985-1994

Table 1 : Real Per Capita New Jersey Figures for Sample of 509 School Districts

School District Survey

Understanding the flypaper effect

Explanations for the flypaper effect

Conclusion

About the Authors

Appendix: An Econometric Study

Table 2: Least Squares Regression Results

 


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