Abstract

The Great Recession led to marked declines in state revenue. In this paper we investigate whether (and how) local school districts modified their funding and taxing decisions in response to state aid declines in the post-recession period. Our results reveal school districts responded to state aid cuts in the post-recession period by countering these cuts. Relative to the pre-recession period, a unit decrease in state aid was associated with a relative increase in local funding. To further probe the school district role, we explore whether the property tax rate, which reflects decisions of districts facing budgetary needs, responded to state aid cuts. We find, relative to the pre-recession period, the post-recession period was characterized by a strong negative relationship between property tax rate and state aid per pupil. We also find important heterogeneities in these responses by region, property wealth, and importance of School Tax Relief Program revenue in district budgets.

1.  Introduction

The effects of the Great Recession on the U.S. economy were both widespread and dramatic. State and local governments were hit hard by the loss of income tax, property tax, and sales tax revenues that resulted from the recession. State and local governments generally provide the vast majority of public school funding, so the recession left schools especially vulnerable to funding losses. Chakrabarti and Livingston (2013a) find that there were multiyear declines in state aid to education following the Great Recession. The objective of this paper is to study the interactions of state funding and local revenue and determine whether the relationship between the two changed in the post-recession period. More specifically, we examine whether the declines in state aid after the recession affected local districts’ fundraising behavior. Did local governments respond to cuts in state funding for education, and if so, how? Did they use local revenue and property taxes to counter the decline of state aid?

It is not necessarily clear a priori how the Great Recession and the resulting cuts in state aid would have affected local property taxes and revenues. On the one hand, school districts faced a shortfall in revenue from the state relative to what they normally received and they may have wanted to replace some of the lost state funds with local funds to avoid having to cut services. On the other hand, the decline in state aid came precisely when property values were plummeting, diminishing the tax base and making it harder to increase property tax revenues. Moreover, many people had lost their jobs, likely making them more averse to increased property taxes. Ultimately, how the recession affected the relationship between state aid and property taxes is an empirical one, and we aim to leverage our data set to provide some insight in this paper.

More specifically, using a detailed district-level panel data set of New York school districts, we investigate whether (and how) the Great Recession affected the relationship between state aid and property taxes. New York State is of interest for a variety of reasons. New York is the third largest state school system, serving 5.5 percent of the country's students.1 Additionally, New York districts vary widely in terms of wealth, demographics, and urbanization.2

This paper builds on the literature studying school district funding (see, for example, Stiefel and Schwartz 2011; Rubenstein et al. 2007; Baker 2009; and Duncombe and Yinger 1998 and 2011, among others) but is more related to the literature that studies the impact of recessions on school district finances.3 Chakrabarti and Livingston (2013a, b) analyze the impact of the Great Recession on school finances in New York and New Jersey and find that there were significant downward shifts from pre-recession trends in funding and expenditure. In addition, they find that, relative to corresponding pre-recession trends, both noninstructional and instructional expenditures declined sharply after the recession. New York was one of many states to cut education funding after the recession. A national analysis by the Center on Budget and Policy Priorities (Leachman and Mai 2013) finds that even as of the 2013–14 school year, six years after the recession hit, thirty-four states provide less per pupil funding than they did before the Great Recession. Even among states that increased funding in more recent years, the increases in state aid have not been enough to offset the funding losses experienced during the recession. There are many states (such as Wisconsin, California, and Texas) that experienced even more drastic declines in total funding per pupil than New York.

The paper most directly related to ours is Dye and Reschovsky (2008). That paper analyzes the effect of cuts in state aid resulting from the 2001 recession on property tax revenues raised by districts and local governments. They find that, on average, school districts increased property taxes by 23 cents for every dollar lost in state aid. Dye and Reschovsky also find that the relationship between state aid and local property taxes varies a great deal across states, however—twenty-six states had a positive correlation between yearly changes in state aid and property taxes from 1978 to 2000, including New York.

Although this paper has been greatly informed by Dye and Reschovsky (2008) and builds on it, it differs in some key ways. One is the granularity of the data—whereas Dye and Reschovsky used state-level data, we exploit district-level data. We also have a longer panel spanning eight years (2005–12), whereas the main analysis in Dye and Reschovsky contrasted school finance indicators between 2002 and 2004. The availability of a longer panel enables us to control for any pre-existing trends, as well as investigate whether the relationship changed with time after the post-recession period. Second, because we focus on one state in particular, we avoid the problem of having differential patterns across states masking the overall effect. Another fundamental difference is the period of analysis—the 2001 recession that Dye and Reschovsky analyze was far less severe than the Great Recession. Yet another important difference is that, in addition to overall impacts, we leverage our district-level data to investigate whether there were heterogeneities in patterns by poverty and region—a line of inquiry that was not possible with state-level data in Dye and Reschovsky (2008). Finally, we use a more rigorous estimation strategy. We start by utilizing district fixed effects estimation to control for time-invariant unobserved district characteristics that might affect the relationship. Next, to further eliminate any endogeneity problems, we pursue an instrumental variables estimation strategy (IV).

We find robust evidence that local revenue and property taxes responded to the decline in state aid following the recession. In the post-recession period, a unit decrease in state aid per pupil led to a relative increase in both local revenue per pupil and property tax revenue per pupil in comparison to the pre-recession period. More specifically, we find that in comparison to the pre-recession period, a dollar decrease in per-pupil state aid led to a relative increase of 19 cents in local funding per pupil, and a relative increase of 14 cents in property tax revenue per pupil.4

To further investigate the role of local control, we explore whether changes in local revenue were associated with changes in the actual property tax rate. We find that, relative to the pre-recession period, a decline in state aid per pupil led to a relative increase in property tax rates. We believe that by separately considering the tax rate we are able to determine whether the change in property tax revenue was a result of local tax policy decisions or simply changes in property values. As outlined here, we do find that districts changed their tax rates in response to state aid shifts.

In addition to analyzing overall local responses to changes in state funding, we also investigate whether there were heterogeneities in responses across regions, and by property wealth. We find interesting variations in the extent of local responses between wealthy and less property-wealthy districts, and between regions. In particular, the general pattern—that districts countered state aid cuts following the Great Recession with local and property tax revenue increases (relative to the pre-recession period)—seems to stem mostly from the responses of the high-wealth districts. This is largely due to the interaction of state aid cuts with the existing School Tax Relief (STAR) program. The STAR program operates like a matching grant, lowering voters’ tax prices and thereby increasing their demand for education. High-wealth districts benefited the most from STAR because of the matching grant nature of the program (Eom et al. 2014). In the aftermath of the Great Recession, high-wealth districts have been able to leverage the matching grant nature of STAR to replace traditional state aid with a combination of additional property tax revenues and state aid they receive as a result of STAR.

To further explore and understand the effects of the STAR program, we conduct a heterogeneity analysis based on the relative importance of STAR revenue in district budgets, and indeed find that the districts with the lowest share of STAR revenue have weaker responses to state aid changes after the recession. This indicates there is some subsidizing effect of STAR that has encouraged districts, particularly more wealthy districts, to increase local and property tax revenue in an effort to take advantage of the “matching grant” nature of STAR.

2.  Background

Economic Background

The bursting of the housing bubble in 2007 and subsequent financial crisis led to a surge in unemployment and a decline in house prices. The rise in unemployment and fall of consumption meant less income and sales tax revenue for state governments, and the collapse of housing prices led to property tax revenue declines. New York's unemployment rate increased from 4.6 percent in 2006 to a peak of 8.5 percent in 2010. Since the peak in 2010, unemployment has fallen to 7.4 percent nationally and 7.5 percent in New York (as of July 2013).5 To counteract declines in state and local revenues, the federal government enacted the American Recovery and Reinvestment Act (also known as the Stimulus Package), much of which was targeted at bolstering state and local government finances. Most of the stimulus funds, however, were used in the first two years after the recession. As the economic recovery stalled, many local governments faced fiscal tightening.

School Funding Overview

Funding for public schools comes from three main sources: federal aid, state aid, and local revenue. Out of these three sources, New York districts received approximately 3 percent of their funding from federal aid, 40 percent from state aid, and 57 percent from local revenue, on average, in the immediate pre-recession year (2008; see figure 1).6 State aid and local revenue constitute the vast majority of school district funding, which makes schools vulnerable to fluctuations in state and local budgets. State aid is determined based on a variety of characteristics of the school districts, including enrollment, varying regional labor market costs, low-income students, limited English proficient students, and income wealth of the district.

Figure 1.

Primary District Funding Sources (2008).

Figure 1.

Primary District Funding Sources (2008).

Local revenue is composed primarily of residential and commercial property tax revenues.7,8 The largest school districts (Buffalo, New York City, Rochester, Syracuse, and Yonkers) do not fund schools directly from property tax revenue; instead, the schools are funded as part of the city's budget (of which property taxes are one component). Because of their different budgetary guidelines and processes, we exclude these five school districts from our analysis.

The school districts’ fiscal years end on 30 June. In the spring (early April), before the next school fiscal year starts, the state passes its annual budget, which allocates, through a wide variety of programs and formulae, state aid for school districts. The school districts then draw up budgets and set their property tax rates to generate the amount of revenue needed to fund their operations. These are voted on9 and the tax rates go into effect in September.10 For a visual representation of the timing see figure 2. This timing sequence (local budgets being set after state budgets are finalized) allows us to study the response of local revenue to changes in state aid.

Figure 2.

Chronology of State and Local Funding in a Representative Year (2011–12 School Year).

Figure 2.

Chronology of State and Local Funding in a Representative Year (2011–12 School Year).

The School Tax Relief Program (STAR)

Instituted in 1997, STAR is a homestead tax exemption program aimed at reducing homeowners’ property taxes. STAR provides a state subsidy that pays for a portion of homeowners’ school district property taxes. STAR is divided into two types: basic STAR, which is available to all homeowners whose primary residence is in New York regardless of income or age, and enhanced STAR, which is available to homeowners age 65 or over with incomes below $79,050 (originally $60,000). Enhanced STAR took effect in the 1998–99 school year. When it was implemented, enhanced STAR exempted $50,000 of property value; that exemption has since risen. Basic STAR was phased in over the course of three years starting in the 1999–2000 school year, with an exemption of $10,000, and reaching its final amount of $30,000 in 2002. In areas with relatively high property values (such as Westchester County) that exemption is multiplied by a sales price differential factor, so homeowners in those high-value counties receive much larger exemptions. Eom et al. (2014) examine New York's STAR program and find the state subsidy to property taxes resulted in increased property tax rates and spending. STAR is different from other state education spending in that its benefits go primarily to wealthier districts—those with more homeowners and higher property values (Duncombe and Yinger 2000). STAR is an important program in New York education finance because of its size—it applies to approximately three million taxpayers and provides several billion dollars in direct tax benefits.

Although the importance of STAR in New York's school finance system is undeniable, it is important to note here the program was completely phased in well before the start of our period of analysis (2005–12). It is possible, however, that the responses from school districts differed depending on the importance of STAR revenue in their budget. To further investigate what effect STAR may have had, we calculate the ratio of STAR revenue to state aid (which does not include STAR revenue), classify districts into quartiles based on their 2005 ratio, and conduct our analysis separately for these quartiles to see if the responses of districts varied across the four quartiles.

3.  Data

We construct our school district panel by combining district financial report data with local property tax levy data, both from the New York Office of the State Comptroller. We obtain student racial demographic data and the percent of students eligible for free or reduced price lunch from the New York State Education Department. We include K–12 districts in our analysis, and exclude the “big five” districts (Buffalo, New York City, Rochester, Syracuse, and Yonkers) because their funding systems are different (see section 2). The resulting data set covers 632 school districts spanning the 2004–05 to 2011–12 school years.11

Our data set includes data on state aid, federal funding, local revenue, property tax revenue, and the property tax rate (taxes per $1,000 of property value12). For our analysis, we express all financial variables in real 2012 dollars and per pupil terms.

In addition to analyzing these variables across all districts in the state, we delve deeper and look at heterogeneities by average property values, heterogeneities across different regions, and by the importance of STAR revenue in district budgets. To study variation by property value, we construct quartiles based on districts’ 2005 per pupil property values and study any differences in responses across the four quartiles. To study spatial variations, we consider the “geographic regions” defined by the New York State Department of Labor. Figure 3 shows a map of the geographic regions. The NY Department of Labor defines ten regions but because of space constraints we study three that provide a good representation of different parts of New York—the Finger Lakes region captures much of the western part of New York, the Central region captures the central part, and the Hudson Valley region captures much of the southern part of New York.13 These regions are also of interest because they include some of the key metropolitan areas of New York (Syracuse, Rochester, and Westchester). The results for the other regions are qualitatively similar (and available on request). To study variation by the importance of STAR revenue in district budgets, for each district we calculate the ratio of STAR payments to state aid in 2005, and divide them into quartiles based on that ratio. We then investigate whether there were differences in local responses across these quartiles.

Figure 3.

Regions of New York State.

Figure 3.

Regions of New York State.

4.  Empirical Analysis

Using school district data from 2005 through 2012, we investigate whether the post-recession period was characterized by a different local revenue response to changes in state aid relative to the pre-recession period. Specifically, did the state aid cuts prompted by the Great Recession lead districts to counter those cuts by increasing local revenue and/or property tax responses (relative to the pre-recession period)? It is worth noting here that our period of analysis, especially the start of our period of analysis, has a distinct advantage. Recall that the STAR program was enacted in 1997 and took full effect in 2002, so it was completely phased in before our period of analysis. Thus, in our analysis, STAR is part of the status quo rather than a confounding factor. Moreover, controlling for pre-recession patterns (using pre-recession data for 2005–08) allows us to control for effects of STAR. We further allay concerns about potential STAR effects by analyzing responses separately by STAR revenue quartiles.

Examining the Relationship between State and Local Sources of Funding

Table 1 presents summary characteristics of the various school finance and socioeconomic indicators used in this study in the immediate pre-recession year (2008). The average district received approximately $8,600 per pupil in state aid in 2008, and raised approximately $12,000 per-pupil in local revenue, with $9,000 coming from property taxes. The average property tax rate was approximately 1.6 percent ($16 per $1,000 of property value).

Table 1.
Summary Statistics in the Immediate Pre-Recession Year (2008)
MeanMedian25th Percentile75th Percentile
Federal Aid Per Pupil 708.13 541.27 376.04 765.69 
 (1569)    
State Aid Per Pupil 8,597.27 8,683.90 5,798.19 11,476.62 
 (3884.8)    
Local Funding Per Pupil 12,226.38 9,580.52 7,018.56 15,130.79 
 (7946.68)    
Property Tax Revenue Per Pupil 9,230.18 6,798.52 4,571.52 12,147.69 
 (6762.48)    
Tax Rate (per $000) 16.45 16.41 13.40 19.60 
 (4.85)    
% Black 5.29 2.00 1.00 4.00 
 (10.16)    
% Hispanic 5.68 2.00 1.00 6.00 
 (9.63)    
% Asian 2.31 1.00 1.00 2.00 
 (3.81)    
% American Indian 0.55 0.00 0.00 0.00 
 (3.5)    
% Free/Reduced Lunch 29.18 30.00 14.00 41.00 
 (17.1)    
% State Aid 42.09 44.88 28.15 58.15 
 (19.15)    
Property Value Per Pupil ($000) 938.42 500.42 310.55 993.45 
 (2188.8)    
Observations 628    
MeanMedian25th Percentile75th Percentile
Federal Aid Per Pupil 708.13 541.27 376.04 765.69 
 (1569)    
State Aid Per Pupil 8,597.27 8,683.90 5,798.19 11,476.62 
 (3884.8)    
Local Funding Per Pupil 12,226.38 9,580.52 7,018.56 15,130.79 
 (7946.68)    
Property Tax Revenue Per Pupil 9,230.18 6,798.52 4,571.52 12,147.69 
 (6762.48)    
Tax Rate (per $000) 16.45 16.41 13.40 19.60 
 (4.85)    
% Black 5.29 2.00 1.00 4.00 
 (10.16)    
% Hispanic 5.68 2.00 1.00 6.00 
 (9.63)    
% Asian 2.31 1.00 1.00 2.00 
 (3.81)    
% American Indian 0.55 0.00 0.00 0.00 
 (3.5)    
% Free/Reduced Lunch 29.18 30.00 14.00 41.00 
 (17.1)    
% State Aid 42.09 44.88 28.15 58.15 
 (19.15)    
Property Value Per Pupil ($000) 938.42 500.42 310.55 993.45 
 (2188.8)    
Observations 628    

Note: All financial variables are inflation-adjusted to 2012 dollars.

We begin our analysis by examining the overall trends of our variables of interest. Figure 4 presents trend plots of the average state aid, property tax revenue, and local funding received by districts from 2005 to 2012, in per pupil amounts. In the years leading up to the recession state aid, property tax revenue, and local funding were all on an upward trend. After 2009, state aid declined sharply as a result of the Great Recession. Coincidentally, and interestingly, trends in both property taxes and local revenue showed a notably steeper increasing trend since 2009, just as state aid started to fall, and this pattern continued until the end of our period (2012). From these trend plots, it appears that local funding, through property taxes, may have increased in response to the decline in state aid. We explore this relationship more formally subsequently.

Figure 4.

Trends in State and Local Funding.

Figure 4.

Trends in State and Local Funding.

Like most analyses of local public good provision, our analyses (and specifications herein) are based on intuition derived from the median voter literature.14 Under an assumption of single peakedness of preferences, the median voter model predicts that a majority rule voting system will select the outcome most preferred by the median voter, that is, the median voter will be pivotal in election outcomes. Our specification in equation 1 captures the preference of the median voter; specifically, we seek to understand the choice of the median voter facing a cut in state aid.
formula
1
where is a school finance indicator (local revenue per pupil, property tax revenue per pupil) for each school district i in year t; StateAid_ppit is the per pupil state aid, StateAid_ppit * Recessiont is the interaction of per pupil state aid and a dummy indicating the recession, the latter equal to 0 before 2009 and 1 in 2009 and onward. Consistent with the median voter literature,15 we control for other intergovernmental grants;16FedAid_ppit represents the amount of per pupil funding coming from federal aid. Given intergovernmental grants (state aid per pupil and federal aid per pupil), the median voter chooses . represents the vector of school district demographic characteristics (racial composition and the percentage of students eligible for free or reduced price lunch), and the percent of district funding coming from state aid. As in Dye and Reschovsky (2008), we include the share of revenue from state aid because the responses of districts that are more dependent on state aid will likely be different from districts that are less dependent. is a vector of year dummies, and denotes district fixed effects. All financial variables are inflation-adjusted to constant 2012 dollars. All regressions use robust standard errors that are adjusted for clustering by school districts.

Our data set includes STAR payments as part of local revenue, and, importantly, not as part of state aid.17 Thus, changes in state aid are determined solely by the state, not by local districts changing their property tax rates.

The results from estimation of specification 1 are presented in table 2. Looking at column 1, although state aid per pupil had a positive relationship with local funding prior to the recession, this relationship weakened after the recession. We find similar results for property tax revenue (column 2). This indicates that local governments responded by countering changes in state funding with changes in local funding after the recession hit.

Table 2.
Did Property Tax Revenue and Local Revenue Respond to State Aid Cuts During the Great Recession? (Using School District Fixed Effects)
Property TaxProperty Tax
Local FundingRevenueLocal FundingRevenue
Per PupilPer PupilPer PupilPer Pupil
FEFEFEFE
(1)(2)(3)(4)
State Aid Per Pupil 1.04*** 0.45*** 1.05*** 0.45*** 
 (0.31) (0.11) (0.31) (0.11) 
State Aid PP × Recession -0.19*** -0.14***   
 (0.04) (0.02)   
State Aid PP × 2009   -0.15*** -0.12*** 
   (0.05) (0.02) 
State Aid PP × 2010   -0.23*** -0.16*** 
   (0.05) (0.02) 
State Aid PP × 2011   -0.19*** -0.14*** 
   (0.04) (0.02) 
State Aid PP × 2012   -0.20*** -0.15*** 
   (0.04) (0.02) 
Observations 5,072 5,072 5,072 5,072 
R 0.98 0.99 0.98 0.99 
Property TaxProperty Tax
Local FundingRevenueLocal FundingRevenue
Per PupilPer PupilPer PupilPer Pupil
FEFEFEFE
(1)(2)(3)(4)
State Aid Per Pupil 1.04*** 0.45*** 1.05*** 0.45*** 
 (0.31) (0.11) (0.31) (0.11) 
State Aid PP × Recession -0.19*** -0.14***   
 (0.04) (0.02)   
State Aid PP × 2009   -0.15*** -0.12*** 
   (0.05) (0.02) 
State Aid PP × 2010   -0.23*** -0.16*** 
   (0.05) (0.02) 
State Aid PP × 2011   -0.19*** -0.14*** 
   (0.04) (0.02) 
State Aid PP × 2012   -0.20*** -0.15*** 
   (0.04) (0.02) 
Observations 5,072 5,072 5,072 5,072 
R 0.98 0.99 0.98 0.99 

Notes:***Statistically significant at the 1% level. Robust standard errors adjusted for clustering by school district are in parentheses. All regressions include year fixed effects, racial composition, the percent of students eligible for free or reduced price lunch, per pupil federal aid, and the percent of district funding from state aid. All financial variables are expressed in real terms. See equations 1 and 2 in the text.

To further understand the relationship, we split the recession interaction into individual year interactions to study the effects separately in each post-recession year. If the negative relationship we found in the first specification occurs in only some of the post-recession years, then that will be revealed in a more flexible specification such as specification 2, which allows the effect to vary across the different post-recession years. Distinguishing between individual year effects also allows us to investigate whether the relationship changed over years in the post-recession period. The specification is as follows:
formula
2

In this model, the coefficient on state aid per pupil captures the relationship between state aid per pupil and local revenue per pupil during the pre-recession period. The coefficients β2 to β5 capture the changes (if any) in this relationship in each of the post-recession years.

The results are presented in columns 3 and 4 of table 2. Each post-recession interaction year has a negative coefficient, and each of them is statistically different from zero. The magnitudes are smaller than the pre-recession coefficient on state aid per pupil, which indicates that in the post-recession years local revenue per pupil would still decline as state aid per pupil declined, but it would do so less strongly than it would have before the recession.

These results imply that although during the post-recession period a unit decline in state aid per pupil would still be associated with a decline in local revenue per pupil (and property tax revenue per pupil), the extent of the latter declines were markedly smaller. In other words, it seems that the local government responded to cuts in state aid by increasing the local funding effort, compared to the pre-recession period.

Investigating the Relationship between State Aid and the Property Tax Rate

To explore whether the changes in property tax revenue we observed earlier were related to changes in the property tax rates, we next investigate the impacts of change in state aid. In particular, we want to see whether the patterns seen earlier were associated with relative increases in property tax rates in the post-recession period.

The trend graph in figure 5 plots the property tax rate, which shows a sharp decline leading up to the recession, and then an equally sharp increase after 2010, which points to a potential response to the downward movement of state aid. Next, we investigate the relationship between state aid per pupil and property tax rate more formally, using the following specifications 3 and 4:
formula
3
and
formula
4

This analysis also draws on the median voter literature—given intergovernmental revenues (state aid and federal aid), the property tax rate choice of the median voter depends on the assessed value of property. Therefore, in specifications 3 and 4, we include (assessed) property value per pupil as an additional regressor. Specification 3 constrains the post-recession tax rate response (to a decline in state aid per pupil) to vary linearly with time. In contrast, specification 4 estimates a more flexible specification where the property tax rate impacts are allowed to vary nonlinearly over the various post-recession years.

Figure 5.

Trends in Property Tax Rates.

Figure 5.

Trends in Property Tax Rates.

The results of this analysis are presented in table 3. They reveal that prior to the recession state aid had a positive relationship with the tax rate; after the recession that relationship diminished sharply. Decomposing the recession interaction into separate year interactions (column 2), we see that the pattern holds for each post-recession year, and in fact the substitution grew stronger over each year. In other words, the results reveal that facing state aid cuts following the Great Recession, the districts responded with relative increases in the property tax rate (in comparison with the pre-recession period), in an effort to counter the declines in state aid.18,19 The table also shows that (as might be expected), an increase in property value per pupil is associated with a decrease in tax rates, and vice versa. This negative relationship continues to hold in the rest of the paper, and in most cases (unlike in table 3) the relationship is statistically significant.

Table 3.
Did Property Tax Rates Respond to State Aid Cuts During the Great Recession?
FE
Tax RateTax Rate
(1)(2)
State Aid Per Pupil 0.00035*** 0.00035*** 
 (0.000) (0.000) 
State Aid PP × Recession -0.00025***  
 (0.000)  
State Aid PP × 2009  -0.00014*** 
  (0.000) 
State Aid PP × 2010  -0.00023*** 
  (0.000) 
State Aid PP × 2011  -0.00030*** 
  (0.000) 
State Aid PP × 2012  -0.00035*** 
  (0.000) 
Property Value PP ($000) -0.00076 -0.00071 
 (0.001) (0.000) 
Observations 5,057 5,057 
R 0.93 0.93 
FE
Tax RateTax Rate
(1)(2)
State Aid Per Pupil 0.00035*** 0.00035*** 
 (0.000) (0.000) 
State Aid PP × Recession -0.00025***  
 (0.000)  
State Aid PP × 2009  -0.00014*** 
  (0.000) 
State Aid PP × 2010  -0.00023*** 
  (0.000) 
State Aid PP × 2011  -0.00030*** 
  (0.000) 
State Aid PP × 2012  -0.00035*** 
  (0.000) 
Property Value PP ($000) -0.00076 -0.00071 
 (0.001) (0.000) 
Observations 5,057 5,057 
R 0.93 0.93 

Notes:***Statistically significant at the 1% level. Robust standard errors adjusted for clustering by school district are in parentheses. All regressions include year fixed effects, racial composition, the percent of students eligible for free or reduced price lunch, per pupil federal aid, and the percent of district funding from state aid. All financial variables are expressed in real terms. See equations 3 and 4 in the text.

To sum, the results in tables 2 and 3 show that in the aftermath of the Great Recession, districts facing state aid cuts responded with relative increases in local revenues, and in the property tax rate. Recall that this is the aggregate picture—different groups of districts may have responded differently. We next investigate if, among other factors, differences in property wealth and importance of STAR mattered in the extent of offsets the districts were able to make.

Were There Heterogeneities in Local Response to Declines in State Aid?

In addition to looking at how changes in state aid affected changes in local funding across all districts in the state, we dive deeper and examine whether there were variations in local responses by district property value (or wealth) and across districts in different regions of the state. Moreover, to understand how STAR interacted with property tax and local revenue responses of districts, we conduct a heterogeneity analysis based on the relative importance of STAR revenue in district budgets.

Heterogeneities by Property Values

Based on the median voter theorem, one would expect the responses of higher income or property wealthy districts to differ from lower income or property poor districts. High property wealth districts contain more wealthy families and a wealthier median voter who would have a higher demand for education, and hence a higher propensity to counter any state aid cuts. Moreover, property wealthy districts also have the means to provide for more revenues at a lower cost to them, by virtue of having a higher property tax base.

One would expect STAR to play a role here too. As Eom et al. (2014) point out, STAR acts as a matching grant lowering voters’ tax prices. Because of this, one would expect a higher tax rate response in districts with higher property value wealth because the same tax rate increase yields a larger dollar increase in property tax revenue, some of which is reimbursed by the state through STAR. Additionally, STAR is adjusted up by the sales price differential factor in counties where the median home sale prices exceed the statewide median sales price (i.e., the higher property value districts).

In table 4 we present results for our local revenue and property tax regressions where we allow the impacts to vary by the property wealth of the district. We divide districts into quartiles based on their per pupil property values in 2005 (the first year of our panel). We find the wealthiest districts have the largest negative post-recession relationship (relative to the pre-recession period), indicating that they offset cuts in state aid more than poorer districts. This pattern is consistent with our earlier discussion. The more wealthy districts have a higher demand for education, have the means to tax themselves more, and receive more money from STAR. These factors have likely led to larger offsets of state aid cuts (by local and property tax funding) in these districts. Meanwhile, the responses of the less-wealthy districts are smaller, both economically and statistically. These districts may not have had the resources to counter state aid cuts as much. There is still some evidence of offsets, but these offsets are smaller than those in the wealthier districts.

Table 4.
Studying Heterogeneity by Property Value: Did Property Tax Revenue and Local Revenue Responses Vary by District Property Values?
Property TaxProperty Tax
Local FundingRevenueLocal FundingRevenue
Per PupilPer PupilPer PupilPer Pupil
FEFEFEFE
(1)(2)(3)(4)
 First Quartile 
State Aid Per Pupil 0.44*** 0.15*** 0.45*** 0.15*** 
 (0.06) (0.06) (0.05) (0.05) 
State Aid PP × Recession -0.07*** -0.02   
 (0.01) (0.02)   
State Aid PP × 2009   -0.09*** -0.02 
   (0.01) (0.02) 
State Aid PP × 2010   -0.10*** -0.03 
   (0.03) (0.02) 
State Aid PP × 2011   -0.05*** -0.01 
   (0.02) (0.02) 
State Aid PP × 2012   -0.06** -0.01 
   (0.02) (0.02) 
Observations 1,263 1,263 1,263 1,263 
R 0.98 0.95 0.98 0.95 
 Second Quartile 
State Aid Per Pupil 1.34** 0.23*** 1.32** 0.23*** 
 (0.64) (0.09) (0.62) (0.08) 
State Aid PP × Recession -0.07 -0.00   
 (0.09) (0.02)   
State Aid PP × 2009   -0.22 -0.03 
   (0.14) (0.02) 
State Aid PP × 2010   -0.07 -0.00 
   (0.09) (0.02) 
State Aid PP × 2011   0.01 0.00 
   (0.10) (0.02) 
State Aid PP × 2012   0.01 0.02 
   (0.11) (0.03) 
Observations 1,264 1,264 1,264 1,264 
R 0.74 0.95 0.75 0.95 
 Third Quartile 
State Aid Per Pupil 1.11*** 0.81*** 1.14*** 0.84*** 
 (0.07) (0.07) (0.07) (0.07) 
State Aid PP × Recession -0.09*** -0.06***   
 (0.01) (0.01)   
State Aid PP × 2009   -0.14*** -0.11*** 
   (0.01) (0.02) 
State Aid PP × 2010   -0.10*** -0.06*** 
   (0.01) (0.01) 
State Aid PP × 2011   -0.06*** -0.03* 
   (0.02) (0.02) 
State Aid PP × 2012   -0.05** -0.02 
   (0.02) (0.02) 
Observations 1,264 1,264 1,264 1,264 
R 0.98 0.98 0.98 0.98 
 Fourth Quartile 
State Aid Per Pupil 2.24*** 1.79*** 2.23*** 1.78*** 
 (0.32) (0.37) (0.33) (0.37) 
State Aid PP × Recession -0.33*** -0.28***   
 (0.07) (0.07)   
State Aid PP × 2009   -0.26*** -0.24*** 
   (0.06) (0.07) 
State Aid PP × 2010   -0.29*** -0.25*** 
   (0.05) (0.06) 
State Aid PP × 2011   -0.37*** -0.30*** 
   (0.10) (0.09) 
State Aid PP × 2012   -0.41*** -0.38*** 
   (0.12) (0.12) 
Observations 1,265 1,265 1,265 1,265 
R 0.97 0.97 0.97 0.97 
Property TaxProperty Tax
Local FundingRevenueLocal FundingRevenue
Per PupilPer PupilPer PupilPer Pupil
FEFEFEFE
(1)(2)(3)(4)
 First Quartile 
State Aid Per Pupil 0.44*** 0.15*** 0.45*** 0.15*** 
 (0.06) (0.06) (0.05) (0.05) 
State Aid PP × Recession -0.07*** -0.02   
 (0.01) (0.02)   
State Aid PP × 2009   -0.09*** -0.02 
   (0.01) (0.02) 
State Aid PP × 2010   -0.10*** -0.03 
   (0.03) (0.02) 
State Aid PP × 2011   -0.05*** -0.01 
   (0.02) (0.02) 
State Aid PP × 2012   -0.06** -0.01 
   (0.02) (0.02) 
Observations 1,263 1,263 1,263 1,263 
R 0.98 0.95 0.98 0.95 
 Second Quartile 
State Aid Per Pupil 1.34** 0.23*** 1.32** 0.23*** 
 (0.64) (0.09) (0.62) (0.08) 
State Aid PP × Recession -0.07 -0.00   
 (0.09) (0.02)   
State Aid PP × 2009   -0.22 -0.03 
   (0.14) (0.02) 
State Aid PP × 2010   -0.07 -0.00 
   (0.09) (0.02) 
State Aid PP × 2011   0.01 0.00 
   (0.10) (0.02) 
State Aid PP × 2012   0.01 0.02 
   (0.11) (0.03) 
Observations 1,264 1,264 1,264 1,264 
R 0.74 0.95 0.75 0.95 
 Third Quartile 
State Aid Per Pupil 1.11*** 0.81*** 1.14*** 0.84*** 
 (0.07) (0.07) (0.07) (0.07) 
State Aid PP × Recession -0.09*** -0.06***   
 (0.01) (0.01)   
State Aid PP × 2009   -0.14*** -0.11*** 
   (0.01) (0.02) 
State Aid PP × 2010   -0.10*** -0.06*** 
   (0.01) (0.01) 
State Aid PP × 2011   -0.06*** -0.03* 
   (0.02) (0.02) 
State Aid PP × 2012   -0.05** -0.02 
   (0.02) (0.02) 
Observations 1,264 1,264 1,264 1,264 
R 0.98 0.98 0.98 0.98 
 Fourth Quartile 
State Aid Per Pupil 2.24*** 1.79*** 2.23*** 1.78*** 
 (0.32) (0.37) (0.33) (0.37) 
State Aid PP × Recession -0.33*** -0.28***   
 (0.07) (0.07)   
State Aid PP × 2009   -0.26*** -0.24*** 
   (0.06) (0.07) 
State Aid PP × 2010   -0.29*** -0.25*** 
   (0.05) (0.06) 
State Aid PP × 2011   -0.37*** -0.30*** 
   (0.10) (0.09) 
State Aid PP × 2012   -0.41*** -0.38*** 
   (0.12) (0.12) 
Observations 1,265 1,265 1,265 1,265 
R 0.97 0.97 0.97 0.97 

Notes:***Statistically significant at the 1% level; **statistically significant at the 5% level; *statistically significant at the 10% level. Robust standard errors adjusted for clustering by school district are in parentheses. All regressions include year fixed effects, racial composition, the percent of students eligible for free or reduced price lunch, per pupil federal aid, and the percent of district funding from state aid. All financial variables are expressed in real terms. The first quartile represents the districts with the lowest per pupil property values. See equations 1 and 2 in the text.

A similar pattern is borne out in the tax rate results in table 5. Relative to the pre-recession period, the wealthier districts increased their tax rates considerably more after the recession to compensate for state aid declines.

Table 5.
Studying Heterogeneity by Property Value: Did Property Tax Rate Response Vary by District Property Values?
FE
Tax RateTax Rate
(1)(2)
 First Quartile 
State Aid Per Pupil 0.00032* 0.00032* 
 (0.00017) (0.00017) 
State Aid PP × Recession 0.00003  
 (0.00006)  
State Aid PP × 2009  0.00001 
  (0.00006) 
State Aid PP × 2010  0.00004 
  (0.00007) 
State Aid PP × 2011  0.00007 
  (0.00006) 
State Aid PP × 2012  -0.00001 
  (0.00008) 
Property Value PP ($000) -0.02772*** -0.02779*** 
 (0.00515) (0.00505) 
Observations 1,262 1,262 
R 0.95 0.95 
 Second Quartile 
State Aid Per Pupil 0.00044** 0.00043** 
 (0.00021) (0.00021) 
State Aid PP × Recession 0.00000  
 (0.00005)  
State Aid PP × 2009  -0.00006 
  (0.00005) 
State Aid PP × 2010  0.00001 
  (0.00005) 
State Aid PP × 2011  0.00003 
  (0.00005) 
State Aid PP × 2012  0.00005 
  (0.00006) 
Property Value PP ($000) -0.02748*** -0.02759*** 
 (0.00229) (0.00229) 
Observations 1,264 1,264 
R 0.96 0.96 
 Third Quartile 
State Aid Per Pupil 0.00143*** 0.00148*** 
 (0.00018) (0.00017) 
State Aid PP × Recession -0.00012***  
 (0.00004)  
State Aid PP × 2009  -0.00020*** 
  (0.00003) 
State Aid PP × 2010  -0.00011*** 
  (0.00003) 
State Aid PP × 2011  -0.00008 
  (0.00005) 
State Aid PP × 2012  -0.00008 
  (0.00007) 
Property Value PP ($000) -0.01830*** -0.01845*** 
 (0.00179) (0.00182) 
Observations 1,264 1,264 
R 0.96 0.96 
 Fourth Quartile 
State Aid Per Pupil 0.00014 0.00012 
 (0.00016) (0.00015) 
State Aid PP × Recession -0.00031***  
 (0.00005)  
State Aid PP × 2009  -0.00021*** 
  (0.00004) 
State Aid PP × 2010  -0.00032*** 
  (0.00005) 
State Aid PP × 2011  -0.00036*** 
  (0.00007) 
State Aid PP × 2012  -0.00039*** 
  (0.00008) 
Property Value PP ($000) -0.00038 -0.00036 
 (0.00031) (0.00030) 
Observations 1,265 1,265 
R 0.94 0.94 
FE
Tax RateTax Rate
(1)(2)
 First Quartile 
State Aid Per Pupil 0.00032* 0.00032* 
 (0.00017) (0.00017) 
State Aid PP × Recession 0.00003  
 (0.00006)  
State Aid PP × 2009  0.00001 
  (0.00006) 
State Aid PP × 2010  0.00004 
  (0.00007) 
State Aid PP × 2011  0.00007 
  (0.00006) 
State Aid PP × 2012  -0.00001 
  (0.00008) 
Property Value PP ($000) -0.02772*** -0.02779*** 
 (0.00515) (0.00505) 
Observations 1,262 1,262 
R 0.95 0.95 
 Second Quartile 
State Aid Per Pupil 0.00044** 0.00043** 
 (0.00021) (0.00021) 
State Aid PP × Recession 0.00000  
 (0.00005)  
State Aid PP × 2009  -0.00006 
  (0.00005) 
State Aid PP × 2010  0.00001 
  (0.00005) 
State Aid PP × 2011  0.00003 
  (0.00005) 
State Aid PP × 2012  0.00005 
  (0.00006) 
Property Value PP ($000) -0.02748*** -0.02759*** 
 (0.00229) (0.00229) 
Observations 1,264 1,264 
R 0.96 0.96 
 Third Quartile 
State Aid Per Pupil 0.00143*** 0.00148*** 
 (0.00018) (0.00017) 
State Aid PP × Recession -0.00012***  
 (0.00004)  
State Aid PP × 2009  -0.00020*** 
  (0.00003) 
State Aid PP × 2010  -0.00011*** 
  (0.00003) 
State Aid PP × 2011  -0.00008 
  (0.00005) 
State Aid PP × 2012  -0.00008 
  (0.00007) 
Property Value PP ($000) -0.01830*** -0.01845*** 
 (0.00179) (0.00182) 
Observations 1,264 1,264 
R 0.96 0.96 
 Fourth Quartile 
State Aid Per Pupil 0.00014 0.00012 
 (0.00016) (0.00015) 
State Aid PP × Recession -0.00031***  
 (0.00005)  
State Aid PP × 2009  -0.00021*** 
  (0.00004) 
State Aid PP × 2010  -0.00032*** 
  (0.00005) 
State Aid PP × 2011  -0.00036*** 
  (0.00007) 
State Aid PP × 2012  -0.00039*** 
  (0.00008) 
Property Value PP ($000) -0.00038 -0.00036 
 (0.00031) (0.00030) 
Observations 1,265 1,265 
R 0.94 0.94 

Notes:***Statistically significant at the 1% level; **statistically significant at the 5% level; *statistically significant at the 10% level. Robust standard errors adjusted for clustering by school district are in parentheses. All regressions include year fixed effects, racial composition, the percent of students eligible for free or reduced price lunch, per pupil federal aid, and the percent of district funding from state aid. All financial variables are expressed in real terms. The first quartile represents the districts with the lowest per pupil property values. See equations 3 and 4 in the text.

To summarize the results so far, the overall patterns in tables 2 and 3 show that in the post-recession period districts facing state aid cuts responded with relative increases in local funding and in the property tax rate. The findings in tables 4 and 5 reveal that these patterns were driven primarily by the high wealth districts. It appears that the high wealth districts were able to take advantage of the matching grant nature of STAR to replace traditional state aid with a combination of additional property tax revenues and state aid they received as a result of STAR. In other words, the residents of wealthy districts were able to leverage a unique aspect of New York's school finance system to replace, at least partially, one form of state aid with a second, indirect form of state aid. Residents of poorer districts, where the matching rate is lower, did not respond in the same way.

Heterogeneities by Regions

New York is a large and very diverse state, and districts in different areas may have faced different situations following the recession. We examine heterogeneities in our results across a few key regions of the state— the Finger Lakes region, the Central region, and the Hudson Valley region (see section 3 for more details). These results are presented in tables 6 and 7. We see that the Hudson Valley school districts had a stronger negative post-recession relationship between state aid and property tax revenue than the other two regions did. In other words, a unit fall in state aid per pupil after the recession led to a larger increase in property tax revenue in the Hudson Valley region than the other two regions. This may be because the Hudson Valley, which includes Westchester County, is in general wealthier than the more rural Central and Finger Lakes regions. However, none of the differences in coefficients across the regions are statistically significant. Results in table 7 reveal the decline in state aid was countered by increases in local tax rates in all three regions. Of note is the tax rate changes were not statistically significantly different between these regions.

Table 6.
Studying Heterogeneity by Region: Did Property Tax Revenue and Local Revenue Responses Vary by Region?
Property TaxProperty Tax
Local FundingRevenueLocal FundingRevenue
Per PupilPer PupilPer PupilPer Pupil
FEFEFEFE
(1)(2)(3)(4)
 Central Region 
State Aid Per Pupil 0.80*** 0.50*** 0.80*** 0.49*** 
 (0.11) (0.13) (0.11) (0.13) 
State Aid PP × Recession -0.13*** -0.09***   
 (0.02) (0.02)   
State Aid PP × 2009   -0.15*** -0.10*** 
   (0.02) (0.03) 
State Aid PP × 2010   -0.14*** -0.09*** 
   (0.02) (0.03) 
State Aid PP × 2011   -0.12*** -0.09*** 
   (0.03) (0.02) 
State Aid PP × 2012   -0.12*** -0.07** 
   (0.03) (0.03) 
Observations 376 376 376 376 
R 0.99 0.98 0.99 0.98 
 Finger Lakes Region 
State Aid Per Pupil 0.83*** 0.55*** 0.84*** 0.55*** 
 (0.12) (0.12) (0.11) (0.12) 
State Aid PP × Recession -0.11*** -0.07***   
 (0.02) (0.02)   
State Aid PP × 2009   -0.11*** -0.07*** 
   (0.02) (0.02) 
State Aid PP × 2010   -0.11*** -0.08*** 
   (0.03) (0.02) 
State Aid PP × 2011   -0.13*** -0.09*** 
   (0.03) (0.02) 
State Aid PP × 2012   -0.09*** -0.06** 
   (0.03) (0.02) 
Observations 544 544 544 544 
R 0.99 0.99 0.99 0.99 
 Hudson Valley Region 
State Aid Per Pupil 1.50*** 0.87*** 1.51*** 0.87*** 
 (0.32) (0.13) (0.29) (0.13) 
State Aid PP × Recession -0.14 -0.15***   
 (0.08) (0.03)   
State Aid PP × 2009   -0.02 -0.14*** 
   (0.17) (0.02) 
State Aid PP × 2010   -0.25*** -0.18*** 
   (0.05) (0.03) 
State Aid PP × 2011   -0.15** -0.17*** 
   (0.06) (0.04) 
State Aid PP × 2012   -0.17* -0.13*** 
   (0.09) (0.04) 
Observations 780 780 780 780 
R 0.97 0.99 0.97 0.99 
Property TaxProperty Tax
Local FundingRevenueLocal FundingRevenue
Per PupilPer PupilPer PupilPer Pupil
FEFEFEFE
(1)(2)(3)(4)
 Central Region 
State Aid Per Pupil 0.80*** 0.50*** 0.80*** 0.49*** 
 (0.11) (0.13) (0.11) (0.13) 
State Aid PP × Recession -0.13*** -0.09***   
 (0.02) (0.02)   
State Aid PP × 2009   -0.15*** -0.10*** 
   (0.02) (0.03) 
State Aid PP × 2010   -0.14*** -0.09*** 
   (0.02) (0.03) 
State Aid PP × 2011   -0.12*** -0.09*** 
   (0.03) (0.02) 
State Aid PP × 2012   -0.12*** -0.07** 
   (0.03) (0.03) 
Observations 376 376 376 376 
R 0.99 0.98 0.99 0.98 
 Finger Lakes Region 
State Aid Per Pupil 0.83*** 0.55*** 0.84*** 0.55*** 
 (0.12) (0.12) (0.11) (0.12) 
State Aid PP × Recession -0.11*** -0.07***   
 (0.02) (0.02)   
State Aid PP × 2009   -0.11*** -0.07*** 
   (0.02) (0.02) 
State Aid PP × 2010   -0.11*** -0.08*** 
   (0.03) (0.02) 
State Aid PP × 2011   -0.13*** -0.09*** 
   (0.03) (0.02) 
State Aid PP × 2012   -0.09*** -0.06** 
   (0.03) (0.02) 
Observations 544 544 544 544 
R 0.99 0.99 0.99 0.99 
 Hudson Valley Region 
State Aid Per Pupil 1.50*** 0.87*** 1.51*** 0.87*** 
 (0.32) (0.13) (0.29) (0.13) 
State Aid PP × Recession -0.14 -0.15***   
 (0.08) (0.03)   
State Aid PP × 2009   -0.02 -0.14*** 
   (0.17) (0.02) 
State Aid PP × 2010   -0.25*** -0.18*** 
   (0.05) (0.03) 
State Aid PP × 2011   -0.15** -0.17*** 
   (0.06) (0.04) 
State Aid PP × 2012   -0.17* -0.13*** 
   (0.09) (0.04) 
Observations 780 780 780 780 
R 0.97 0.99 0.97 0.99 

Notes:***Statistically significant at the 1% level; **statistically significant at the 5% level. Robust standard errors adjusted for clustering by school district are in parentheses. All regressions include year fixed effects, racial composition, the percent of students eligible for free or reduced price lunch, per pupil federal aid, and the percent of district funding from state aid. All financial variables are expressed in real terms. See equations 1 and 2 in the text.

Table 7.
Studying Heterogeneity by Region: Did Property Tax Rate Response Vary by Region?
FE
Tax RateTax Rate
(1)(2)
 Central Region 
State Aid Per Pupil 0.00063*** 0.00064*** 
 (0.00020) (0.00020) 
State Aid PP × Recession -0.00022***  
 (0.00005)  
State Aid PP × 2009  -0.00018*** 
  (0.00006) 
State Aid PP × 2010  -0.00022*** 
  (0.00005) 
State Aid PP × 2011  -0.00022*** 
  (0.00006) 
State Aid PP × 2012  -0.00027*** 
  (0.00006) 
Property Value PP ($000) -0.01677*** -0.01677*** 
 (0.00333) (0.00318) 
Observations 376 376 
R 0.96 0.96 
 Finger Lakes Region 
State Aid Per Pupil 0.00079*** 0.00079*** 
 (0.00020) (0.00020) 
State Aid PP × Recession -0.00020***  
 (0.00006)  
State Aid PP × 2009  -0.00019*** 
  (0.00005) 
State Aid PP × 2010  -0.00022*** 
  (0.00005) 
State Aid PP × 2011  -0.00019*** 
  (0.00006) 
State Aid PP × 2012  -0.00020*** 
  (0.00007) 
Property Value PP ($000) -0.01240*** -0.01239*** 
 (0.00223) (0.00225) 
Observations 544 544 
R 0.97 0.97 
 Hudson Valley Region 
State Aid Per Pupil 0.00032 0.00037 
 (0.00034) (0.00033) 
State Aid PP × Recession -0.00020***  
 (0.00005)  
State Aid PP × 2009  -0.00024*** 
  (0.00004) 
State Aid PP × 2010  -0.00026*** 
  (0.00004) 
State Aid PP × 2011  -0.00017*** 
  (0.00006) 
State Aid PP × 2012  -0.00006 
  (0.00007) 
Property Value PP ($000) -0.00630*** -0.00680*** 
 (0.00091) (0.00099) 
Observations 766 766 
R 0.94 0.95 
FE
Tax RateTax Rate
(1)(2)
 Central Region 
State Aid Per Pupil 0.00063*** 0.00064*** 
 (0.00020) (0.00020) 
State Aid PP × Recession -0.00022***  
 (0.00005)  
State Aid PP × 2009  -0.00018*** 
  (0.00006) 
State Aid PP × 2010  -0.00022*** 
  (0.00005) 
State Aid PP × 2011  -0.00022*** 
  (0.00006) 
State Aid PP × 2012  -0.00027*** 
  (0.00006) 
Property Value PP ($000) -0.01677*** -0.01677*** 
 (0.00333) (0.00318) 
Observations 376 376 
R 0.96 0.96 
 Finger Lakes Region 
State Aid Per Pupil 0.00079*** 0.00079*** 
 (0.00020) (0.00020) 
State Aid PP × Recession -0.00020***  
 (0.00006)  
State Aid PP × 2009  -0.00019*** 
  (0.00005) 
State Aid PP × 2010  -0.00022*** 
  (0.00005) 
State Aid PP × 2011  -0.00019*** 
  (0.00006) 
State Aid PP × 2012  -0.00020*** 
  (0.00007) 
Property Value PP ($000) -0.01240*** -0.01239*** 
 (0.00223) (0.00225) 
Observations 544 544 
R 0.97 0.97 
 Hudson Valley Region 
State Aid Per Pupil 0.00032 0.00037 
 (0.00034) (0.00033) 
State Aid PP × Recession -0.00020***  
 (0.00005)  
State Aid PP × 2009  -0.00024*** 
  (0.00004) 
State Aid PP × 2010  -0.00026*** 
  (0.00004) 
State Aid PP × 2011  -0.00017*** 
  (0.00006) 
State Aid PP × 2012  -0.00006 
  (0.00007) 
Property Value PP ($000) -0.00630*** -0.00680*** 
 (0.00091) (0.00099) 
Observations 766 766 
R 0.94 0.95 

Notes:***Statistically significant at the 1% level. Robust standard errors adjusted for clustering by school district are in parentheses. All regressions include year fixed effects, racial composition, the percent of students eligible for free or reduced price lunch, per pupil federal aid, and the percent of district funding from state aid. All financial variables are expressed in real terms. See equations 3 and 4 in the text.

Thus, all of these regions follow the same general pattern that the overall sample follows. This indicates that the effects of the recession and responses were not concentrated just in one part of the state, but were widespread.

Heterogeneities by STAR Revenue Shares

Because the STAR program explicitly subsidizes districts that increase property taxes and property tax revenue, we might expect to see different responses in districts where STAR revenue plays a larger role in their budget. To test this, we calculate the ratio of STAR revenue to state aid in each district and classify districts into quartiles based on their ratio in 2005 (the highest quartile representing the districts with the largest STAR to state aid ratio). We then estimate our model of district response separately for each quartile.

These results are presented in tables 8 and 9. Looking at table 8, the bottom quartile (those with the least STAR revenue relative to state aid) had a weaker pre-recession relationship between state aid and local revenue (or property tax revenue) than the other quartiles, indicating less willingness or ability to increase local revenue or property taxes as state aid was increasing. Furthermore, their post-recession response (relative to the pre-recession period) is statistically insignificant, whereas the other three quartiles have both economically and statistically significant compensatory local and property tax revenue responses to post-recession cuts in state aid. We see the strongest post-recession response in the highest quartile. This is possibly due to a combination of factors—they enjoy greater STAR subsidies, they likely have higher assessed values so a given tax rate yields higher property tax revenue, they have a higher demand for education, and they have the means to tax themselves more.

Table 8.
Studying Heterogeneity by STAR Revenue Shares: Did the Importance of STAR Revenue Matter in Local and Property Tax Revenue Responses?
Property TaxProperty Tax
Local FundingRevenueLocal FundingRevenue
Per PupilPer PupilPer PupilPer Pupil
FEFEFEFE
(1)(2)(3)(4)
 First Quartile 
State Aid Per Pupil 0.48*** 0.28** 0.52*** 0.28** 
 (0.17) (0.11) (0.16) (0.11) 
State Aid PP × Recession 0.05 -0.03   
 (0.12) (0.03)   
State Aid PP × 2009   0.31 -0.03 
   (0.36) (0.02) 
State Aid PP × 2010   -0.10 -0.07 
   (0.07) (0.05) 
State Aid PP × 2011   -0.04 0.00 
   (0.04) (0.03) 
State Aid PP × 2012   0.03 -0.01 
   (0.06) (0.04) 
Observations 1,260 1,260 1,260 1,260 
R 0.97 0.98 0.97 0.98 
 Second Quartile 
State Aid Per Pupil 2.04*** 0.48*** 2.02*** 0.48*** 
 (0.69) (0.13) (0.67) (0.13) 
State Aid PP × Recession -0.25*** -0.20***   
 (0.09) (0.04)   
State Aid PP × 2009   -0.34*** -0.19*** 
   (0.10) (0.04) 
State Aid PP × 2010   -0.28*** -0.22*** 
   (0.11) (0.06) 
State Aid PP × 2011   -0.19* -0.18*** 
   (0.11) (0.03) 
State Aid PP × 2012   -0.20* -0.21*** 
   (0.11) (0.06) 
Observations 1,264 1,264 1,264 1,264 
R 0.94 0.98 0.95 0.98 
 Third Quartile 
State Aid Per Pupil 1.83*** 1.50*** 1.85*** 1.51*** 
 (0.15) (0.16) (0.15) (0.17) 
State Aid PP × Recession -0.24*** -0.17***   
 (0.06) (0.07)   
State Aid PP × 2009   -0.26*** -0.20*** 
   (0.04) (0.05) 
State Aid PP × 2010   -0.28*** -0.21*** 
   (0.06) (0.07) 
State Aid PP × 2011   -0.19*** -0.13 
   (0.07) (0.08) 
State Aid PP × 2012   -0.22*** -0.16* 
   (0.08) (0.09) 
Observations 1,262 1,262 1,262 1,262 
R 0.99 0.98 0.99 0.98 
 Fourth Quartile 
State Aid Per Pupil 2.00*** 1.47*** 2.05*** 1.52*** 
 (0.71) (0.50) (0.76) (0.54) 
State Aid PP × Recession -0.34*** -0.31***   
 (0.06) (0.06)   
State Aid PP × 2009   -0.25*** -0.24*** 
   (0.04) (0.05) 
State Aid PP × 2010   -0.36*** -0.32*** 
   (0.10) (0.09) 
State Aid PP × 2011   -0.41*** -0.36*** 
   (0.07) (0.07) 
State Aid PP × 2012   -0.39*** -0.37*** 
   (0.08) (0.08) 
Observations 1,271 1,271 1,271 1,271 
R 0.98 0.99 0.98 0.99 
Property TaxProperty Tax
Local FundingRevenueLocal FundingRevenue
Per PupilPer PupilPer PupilPer Pupil
FEFEFEFE
(1)(2)(3)(4)
 First Quartile 
State Aid Per Pupil 0.48*** 0.28** 0.52*** 0.28** 
 (0.17) (0.11) (0.16) (0.11) 
State Aid PP × Recession 0.05 -0.03   
 (0.12) (0.03)   
State Aid PP × 2009   0.31 -0.03 
   (0.36) (0.02) 
State Aid PP × 2010   -0.10 -0.07 
   (0.07) (0.05) 
State Aid PP × 2011   -0.04 0.00 
   (0.04) (0.03) 
State Aid PP × 2012   0.03 -0.01 
   (0.06) (0.04) 
Observations 1,260 1,260 1,260 1,260 
R 0.97 0.98 0.97 0.98 
 Second Quartile 
State Aid Per Pupil 2.04*** 0.48*** 2.02*** 0.48*** 
 (0.69) (0.13) (0.67) (0.13) 
State Aid PP × Recession -0.25*** -0.20***   
 (0.09) (0.04)   
State Aid PP × 2009   -0.34*** -0.19*** 
   (0.10) (0.04) 
State Aid PP × 2010   -0.28*** -0.22*** 
   (0.11) (0.06) 
State Aid PP × 2011   -0.19* -0.18*** 
   (0.11) (0.03) 
State Aid PP × 2012   -0.20* -0.21*** 
   (0.11) (0.06) 
Observations 1,264 1,264 1,264 1,264 
R 0.94 0.98 0.95 0.98 
 Third Quartile 
State Aid Per Pupil 1.83*** 1.50*** 1.85*** 1.51*** 
 (0.15) (0.16) (0.15) (0.17) 
State Aid PP × Recession -0.24*** -0.17***   
 (0.06) (0.07)   
State Aid PP × 2009   -0.26*** -0.20*** 
   (0.04) (0.05) 
State Aid PP × 2010   -0.28*** -0.21*** 
   (0.06) (0.07) 
State Aid PP × 2011   -0.19*** -0.13 
   (0.07) (0.08) 
State Aid PP × 2012   -0.22*** -0.16* 
   (0.08) (0.09) 
Observations 1,262 1,262 1,262 1,262 
R 0.99 0.98 0.99 0.98 
 Fourth Quartile 
State Aid Per Pupil 2.00*** 1.47*** 2.05*** 1.52*** 
 (0.71) (0.50) (0.76) (0.54) 
State Aid PP × Recession -0.34*** -0.31***   
 (0.06) (0.06)   
State Aid PP × 2009   -0.25*** -0.24*** 
   (0.04) (0.05) 
State Aid PP × 2010   -0.36*** -0.32*** 
   (0.10) (0.09) 
State Aid PP × 2011   -0.41*** -0.36*** 
   (0.07) (0.07) 
State Aid PP × 2012   -0.39*** -0.37*** 
   (0.08) (0.08) 
Observations 1,271 1,271 1,271 1,271 
R 0.98 0.99 0.98 0.99 

Notes:***Statistically significant at the 1% level; **statistically significant at the 5% level; *statistically significant at the 10% level. Robust standard errors adjusted for clustering by school district are in parentheses. All regressions include year fixed effects, racial composition, the percent of students eligible for free or reduced price lunch, per pupil federal aid, and the percent of district funding from state aid. All financial variables are expressed in real terms. The first quartile represents the districts with the lowest ratio of STAR revenue to state aid. See equations 1 and 2 in the text.

Table 9.
Studying Heterogeneity by STAR Revenue Shares: Did the Importance of STAR Revenue Matter in Property Tax Rate Responses?
FE
Tax RateTax Rate
(1)(2)
 First Quartile 
State Aid Per Pupil 0.00022** 0.00022** 
 (0.00011) (0.00011) 
State Aid PP × Recession -0.00003  
 (0.00006)  
State Aid PP × 2009  -0.00006 
  (0.00005) 
State Aid PP × 2010  -0.00003 
  (0.00006) 
State Aid PP × 2011  0.00001 
  (0.00006) 
State Aid PP × 2012  -0.00003 
  (0.00007) 
Property Value PP ($000) -0.00467* -0.00467* 
 (0.00268) (0.00267) 
Observations 1,251 1,251 
R 0.92 0.92 
 Second Quartile 
State Aid Per Pupil 0.00015 0.00017 
 (0.00019) (0.00019) 
State Aid PP × Recession -0.00017***  
 (0.00006)  
State Aid PP × 2009  -0.00010* 
  (0.00006) 
State Aid PP × 2010  -0.00018*** 
  (0.00007) 
State Aid PP × 2011  -0.00020*** 
  (0.00007) 
State Aid PP × 2012  -0.00019** 
  (0.00008) 
Property Value PP ($000) -0.00006 -0.00005 
 (0.00014) (0.00014) 
Observations 1,264 1,264 
R 0.94 0.94 
 Third Quartile 
State Aid Per Pupil 0.00046** 0.00044** 
 (0.00021) (0.00021) 
State Aid PP × Recession -0.00032***  
 (0.00007)  
State Aid PP × 2009  -0.00026*** 
  (0.00006) 
State Aid PP × 2010  -0.00033*** 
  (0.00007) 
State Aid PP × 2011  -0.00033*** 
  (0.00009) 
State Aid PP × 2012  -0.00037*** 
  (0.00010) 
Property Value PP ($000) -0.00174*** -0.00174*** 
 (0.00064) (0.00063) 
Observations 1,262 1,262 
R 0.95 0.95 
 Fourth Quartile 
State Aid Per Pupil 0.00193*** 0.00191*** 
 (0.00038) (0.00036) 
State Aid PP × Recession -0.00020**  
 (0.00008)  
State Aid PP × 2009  -0.00027*** 
  (0.00007) 
State Aid PP × 2010  -0.00027*** 
  (0.00009) 
State Aid PP × 2011  -0.00014 
  (0.00012) 
State Aid PP × 2012  -0.00010 
  (0.00012) 
Property Value PP ($000) -0.00209*** -0.00213*** 
 (0.00045) (0.00046) 
Observations 1,271 1,271 
R 0.95 0.95 
FE
Tax RateTax Rate
(1)(2)
 First Quartile 
State Aid Per Pupil 0.00022** 0.00022** 
 (0.00011) (0.00011) 
State Aid PP × Recession -0.00003  
 (0.00006)  
State Aid PP × 2009  -0.00006 
  (0.00005) 
State Aid PP × 2010  -0.00003 
  (0.00006) 
State Aid PP × 2011  0.00001 
  (0.00006) 
State Aid PP × 2012  -0.00003 
  (0.00007) 
Property Value PP ($000) -0.00467* -0.00467* 
 (0.00268) (0.00267) 
Observations 1,251 1,251 
R 0.92 0.92 
 Second Quartile 
State Aid Per Pupil 0.00015 0.00017 
 (0.00019) (0.00019) 
State Aid PP × Recession -0.00017***  
 (0.00006)  
State Aid PP × 2009  -0.00010* 
  (0.00006) 
State Aid PP × 2010  -0.00018*** 
  (0.00007) 
State Aid PP × 2011  -0.00020*** 
  (0.00007) 
State Aid PP × 2012  -0.00019** 
  (0.00008) 
Property Value PP ($000) -0.00006 -0.00005 
 (0.00014) (0.00014) 
Observations 1,264 1,264 
R 0.94 0.94 
 Third Quartile 
State Aid Per Pupil 0.00046** 0.00044** 
 (0.00021) (0.00021) 
State Aid PP × Recession -0.00032***  
 (0.00007)  
State Aid PP × 2009  -0.00026*** 
  (0.00006) 
State Aid PP × 2010  -0.00033*** 
  (0.00007) 
State Aid PP × 2011  -0.00033*** 
  (0.00009) 
State Aid PP × 2012  -0.00037*** 
  (0.00010) 
Property Value PP ($000) -0.00174*** -0.00174*** 
 (0.00064) (0.00063) 
Observations 1,262 1,262 
R 0.95 0.95 
 Fourth Quartile 
State Aid Per Pupil 0.00193*** 0.00191*** 
 (0.00038) (0.00036) 
State Aid PP × Recession -0.00020**  
 (0.00008)  
State Aid PP × 2009  -0.00027*** 
  (0.00007) 
State Aid PP × 2010  -0.00027*** 
  (0.00009) 
State Aid PP × 2011  -0.00014 
  (0.00012) 
State Aid PP × 2012  -0.00010 
  (0.00012) 
Property Value PP ($000) -0.00209*** -0.00213*** 
 (0.00045) (0.00046) 
Observations 1,271 1,271 
R 0.95 0.95 

Notes:***Statistically significant at the 1% level; **statistically significant at the 5% level; *statistically significant at the 10% level. Robust standard errors adjusted for clustering by school district are in parentheses. All regressions include year fixed effects, racial composition, the percent of students eligible for free or reduced price lunch, per pupil federal aid, and the percent of district funding from state aid. All financial variables are expressed in real terms. The first quartile represents the districts with the lowest ratio of STAR revenue to state aid. See equations 3 and 4 in the text.

A similar pattern plays out in the tax rate response (table 9), where the bottom quartile does not show any statistically significant tax rate response in the post-recession period, although the coefficients are still negative. The top three quartiles have economically much stronger post-recession responses that are statistically significant in most cases.

5.  Conclusion

In this paper, we analyzed how the Great Recession changed the relationship between state aid and local revenues in New York, specifically looking at how changes in state aid before and after the recession had varying impacts on local revenue and property taxes. This analysis furthers our understanding of how districts make spending decisions given changes in their funding sources.

Our analysis uncovered some interesting patterns. We find that the relationship between state aid per pupil and local revenue (or property tax revenue) changed markedly with the Great Recession. The post-recession era was characterized by local governments proactively increasing taxes (relative to that in the pre-recession period) for a decrease in state aid per pupil. More specifically, relative to the pre-recession period, a dollar decline in state aid resulted in a 14-cent increase in property tax revenue and a 19-cent increase in local revenue. By allowing the effects of state aid to vary across years, we find that this pattern is not driven by a single year effect but is a consistent pattern reflected in each year after the recession.

By separately analyzing the driver of property tax revenue—the property tax rate—we find that changes in state aid per-pupil consistently affected the tax rate, suggesting districts did respond to changes in state aid. In addition, the compensatory relationship became stronger over the years.

Our analysis reveals an important role of property taxes in school finance. We find that property taxes acted as a stabilizing force—school districts facing cuts in state funding responded by countering these state aid cuts through increased property taxes. But there were important variations in the responses of school districts. Investigating whether the response to state aid cuts varied with property value, we find wealthier districts raised property tax rates more following the recession, and raised greater funds through local and property tax revenue. We argue that this pattern relates to the STAR program being essentially a matching grant. STAR allowed high-wealth districts to increase their spending at a relatively lower cost to themselves. Residents of poorer districts, where the matching rate was lower, do not seem to have responded in the same way. The importance of STAR is also brought out when, to investigate whether the local responses varied by the importance of STAR revenue in districts’ budgets, we classify districts into four quartiles based on the ratio of their STAR revenue to their state aid. Our results show that districts in the highest quartile had the strongest compensatory local and property tax revenue responses facing state aid cuts in the post-recession period, and the districts in the lowest quartile had the weakest responses. This underscores the fact that all of the elements of a state's school finance system matter and that, particularly in downturns, elements of the system that have disequalizing effects can serve to accentuate existing inequalities. Finally, analyzing variations by region, we find that the effect was qualitatively similar across regions, with a somewhat stronger relationship between state aid and property tax revenue in Hudson Valley.

Thus, we find robust evidence that state aid does affect local government decision making. The findings of this study have the potential to inform policy decisions at the state and local levels. The state's decisions about how much to spend on education during fiscal crises clearly have an effect on not just state funding for education, but also on local revenue decisions. Policy makers need to keep this response in mind when planning education financing. New York was not alone in its substantial declines in education spending following the Great Recession. State aid has not returned to pre-recession levels in the majority of states (including other northeastern states such as Pennsylvania and Maine). Consequently, school funding depended to a much greater extent on property taxes. Our results for New York show that some local governments responded by countering the state aid cuts and replenishing some of the lost funds. However, the local revenue offsets were substantially smaller than the actual state funding declines. This phenomenon of incomplete offsets is likely to put pressure on funding and spending in schools. In addition, because property taxes are unpopular politically, several recent laws, such as New York's property tax rate cap (that went into effect in the 2012–13 school year), have limited the ability of districts to raise local funds through increasing property tax rates. These laws would further intensify pressure on districts trying to adequately fund K–12 education.

Notes

1. 

Authors’ calculations using data from National Center for Education Statistics (NCES) Common Core of Data (CCD) available at http://nces.ed.gov/pubs2012/2012327.pdf.

2. 

Because we focus on New York schools, it is important to note that these results apply specifically to New York, and may not necessarily be generalizable to other states. Many of the issues New York districts face are common across states, however, therefore the results are still informative in the context of other states.

3. 

Duncombe and Yinger (2000) provide an extensive documentation of property tax trends and policies. They find that over time there was a nationwide increase in property taxes as well as a significant increase in the cost of state and local government services that in turn caused an increase in education expenditures. They find that overall the real property tax burden per capita increased by approximately one third from 1965 to 1996.

4. 

These estimates are obtained from specifications that include school district fixed effects. Instrumental variables estimates, which are qualitatively similar, reveal that a dollar decrease in per-pupil state aid led to a relative increase of 24 cents in local funding per pupil, and a relative increase of 20 cents in property tax revenue per pupil.

5. 

Source: Bureau of Labor Statistics/Haver Analytics.

6. 

In contrast, the national average in 2008 was 8 percent federal, 51 percent state, and 41 percent local.

7. 

On average, in 2008 (the immediate pre-recession year) 72 percent of local revenue came from property taxes, with a standard deviation of 11.6 percent.

8. 

The bulk of local revenue is constituted by real property taxes and assessments (76 percent in 2008) and STAR payments (12 percent in 2008). Other components include other real property tax items (such as payments in lieu of taxes, interest payments), sales and use tax revenue, charges for services (such as education, public safety, health, and culture and recreation fees), charges to other governments, earnings related to use and sale of property, and other local revenue (such as fines, gifts, etc.).

9. 

School district budgets are voted on by annual referenda. Voters are mailed the relevant information, including the proposed budget and the estimated property taxes they would pay if the budget is approved (Rockoff 2010).

10. 

In 2011, the New York State Legislature enacted a law limiting the annual rate of change in the property tax rate, but this was not implemented until after our period of analysis. New York City and Nassau County both have existing limits on the rate of increase of assessed property values. As discussed earlier, New York City is excluded from our analysis. To investigate whether the limit on assessed values in Nassau is contributing to our results, we re-estimate our specifications after excluding Nassau school districts. The results remain qualitatively very similar and are available on request.

11. 

For the remainder of the paper school years will be referred to using the year of the spring semester.

12. 

Property value refers to the equalized assessed value.

13. 

Given space constraints, we chose to present results for regions in the east, south, and central over the northern region (North County) as the latter region is considerably more sparsely populated compared with the other nine regions.

14. 

See, for example, Ross and Yinger (1999), Fletcher and Kenny (2008), Brunner and Ross (2010), Corcoran and Evans (2010), Wang, Duncombe, and Yinger (2011), and Boustan et al. (2013).

15. 

See, for example, Corcoran and Evans (2010).

16. 

For impacts of intergovernmental grants on educational expenditure, see Tsang and Levin (1983).

17. 

This is in keeping with the accounting method used in our data source (the New York State Comptroller's Office).

18. 

Note that whereas fixed effects control for district specific time-invariant attributes, there may be endogeneity problems caused by unobserved time-varying characteristics that are correlated with local revenue and state aid. To address this endogeneity, we implement an IV strategy, using the four-year lag of state aid per pupil as the instrument for state aid per pupil. The IV results remain qualitatively similar to each of the corresponding fixed effects results reported in the paper; to save space we only report IV results corresponding to tables 2 and 3 in appendix tables A.1 and A.2. The other IV results are available on request.

19. 

There may be cause for concern in estimations of specifications 3 and 4 if the property value is endogenous. To address this potential issue, we carry out two alternative estimations using pre-recession data on property values. In the first strategy (following Chakrabarti and Roy 2014), we use 2005 property value (the first year available in our data) and interact it with year dummies to get variation over time—the purpose is to obtain a measure of property value that is exogenous. The second strategy is based on the same intuition but uses 2008 property value and its interactions with year dummies (note that 2008 is the immediate pre-recession year). The results from these two strategies (not presented here, but available on request) mirror closely those obtained here, giving us further confidence in these results.

Acknowledgments

We thank Peter Bergman, Carrie Conaway, Tom Downes, Hank Levin, Andrew Reschovsky, Jonah Rockoff, Judith Scott-Clayton, Amy Ellen Schwartz, John Yinger, and participants at the Lincoln Institute of Land Policy Conference on Property Tax and Financing of K 12 Education funding for valuable insight and feedback. We are grateful to Theresa Hunt and Craig Kinns of the New York State Comptroller's Office for their generous help with the data and for patiently answering numerous questions. We are also grateful to Darlene Tegza of the New York State Education Department for her valuable explanations of New York education finances. All errors are our own. The views expressed in this paper are those of the authors and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System.

Color versions of the figures in this article are available at http://www.mitpressjournals.org/doi/suppl/10.1162/EDFP_a_00141.

REFERENCES

Baker
,
Bruce D.
2009
.
Within district resource allocation and the marginal costs of providing equal educational opportunity: Evidence from Texas and Ohio
.
Education Policy Analysis Archives
17
(
3
):
1
31
.
Boustan
,
Leah
,
Fernando
Ferreira
,
Hernan
Winkler
, and
Eric M.
Zolt
.
2013
.
The effect of rising income inequality on taxation and public expenditures: Evidence from U.S. municipalities and school districts, 1970–2000
.
Review of Economics and Statistics
95
(
4
):
1291
1302
. doi:10.1162/REST_a_00332
Brunner
,
Eric J.
, and
Stephen L.
Ross
.
2010
.
Is the median voter decisive? Evidence from referenda voting patterns
.
Journal of Public Economics
94
(
11–12
):
898
910
. doi:10.1016/j.jpubeco.2010.09.009
Chakrabarti
,
Rajashri
, and
Max
Livingston
.
2013a
.
The long road to recovery: New York schools in the aftermath of the Great Recession
.
New York
:
Federal Reserve Bank of New York Staff Report No. 631
.
Chakrabarti
,
Rajashri
, and
Max
Livingston
.
2013b
.
Still not out of the woods? New Jersey schools during the recession and beyond
.
New York
:
Federal Reserve Bank of New York Staff Report No. 632
.
Chakrabarti
,
Rajashri
, and
Joydeep
Roy
.
2014
.
Do charter schools crowd out private school enrollment? Evidence from Michigan.
Federal Reserve Bank of New York Working Paper
.
Corcoran
,
Sean
, and
William N.
Evans
.
2010
.
Income inequality, the median voter, and the support for public education
.
NBER Working Paper No. 16097
.
Duncombe
,
William
, and
Yinger
John
.
1998
.
School finance reform: Aid formulas and equity objectives
.
National Tax Journal
51
(
2
):
239
262
.
Duncombe
,
William
, and
Yinger
John
.
2000
.
Alternative paths to property tax relief. Unpublished paper
,
Syracuse University
.
Duncombe
,
William
, and
Yinger
John
.
2011
.
Making do: State constraints and local responses in California's education finance system
.
International Tax and Public Finance
18
(
3
):
337
368
. doi:10.1007/s10797-010-9159-3
Dye
,
Richard
, and
Andrew
Reschovsky
.
2008
.
Property tax responses to state aid cuts in the recent fiscal crisis
.
Public Budgeting & Finance
28
(
2
):
87
111
. doi:10.1111/j.1540-5850.2008.00906.x
Eom
,
Tae Ho
,
William
Duncombe
, Phuong Nguyen-Hoang, and
John
Yinger
.
2014
.
The unintended consequences of property tax relief: New York's STAR program
.
Education Finance and Policy
9
(
4
):
446
480
.
Fletcher
,
Deborah
, and
Lawrence W.
Kenny
.
2008
.
The influence of the elderly on school spending in a median voter framework
.
Education Finance and Policy
3
(
3
):
283
315
. doi:10.1162/edfp.2008.3.3.283
Leachman
,
Michael
, and
Chris
Mai
.
2013
.
Most states funding schools less than before the recession
.
Washington, DC
:
Center on Budget and Policy Priorities
.
Rockoff
,
Jonah E
.
2010
.
Local response to fiscal incentives in heterogeneous communities
.
Journal of Urban Economics
68
(
2
):
138
147
. doi:10.1016/j.jue.2010.03.010
Ross
,
Stephen
, and
Yinger
John
.
1999
.
Sorting and voting: A review of the literature on urban public finance
. In
Handbook of regional and urban economics
, vol.
3
, edited by
Paul
Ceshire
and
Edwin S.
Mills
, pp.
2001
2060
.
Amsterdam
:
Elsevier
.
Rubenstein
,
Ross
,
Amy Ellen
Schwartz
,
Leanna
Stiefel
, and
Bel Hadj Amor
Hella
.
2007
.
From districts to schools: The distribution of resources across schools in big city school districts
.
Economics of Education Review
26
(
5
):
532
545
. doi:10.1016/j.econedurev.2006.08.002
Stiefel
,
Leanna
, and
Schwartz
Amy Ellen
.
2011
.
Financing K–12 education in the Bloomberg years, 2002–2008: Ambitious change in the nation's most complex school system
. In
Education Reform in New York City
, edited by
Jennifer A.
O’Day
,
Catherine S.
Bitter
, and
Louis M.
Gozmez
, pp.
55
86
.
New York
:
Institute for Education and Social Policy
.
Tsang
,
Mun
, and
Henry
Levin
.
1983
.
The impact of intergovernmental grants on educational expenditure
.
Review of Educational Research
53
(
3
):
329
367
. doi:10.3102/00346543053003329
Wang
,
Wen
,
William D.
Duncombe
, and
John M.
Yinger
.
2011
.
School district responses to matching aid programs for capital facilities: A case study of New York's building aid program
.
National Tax Journal
64
(
3
):
759
794
.

Appendix

Table A.1.
Did Property Tax Revenue and Local Revenue Respond to State Aid Cuts During the Great Recession? (Using Instrumental Variables)
Property TaxProperty Tax
Local FundingRevenueLocal FundingRevenue
Per PupilPer PupilPer PupilPer Pupil
IVIVIVIV
(1)(2)(3)(4)
State Aid Per Pupil 1.19*** 1.12*** 1.18*** 1.12*** 
 (0.18) (0.18) (0.18) (0.17) 
State Aid PP × Recession -0.24*** -0.20***   
 (0.03) (0.03)   
State Aid PP × 2009   -0.19*** -0.18*** 
   (0.03) (0.03) 
State Aid PP × 2010   -0.31*** -0.22*** 
   (0.04) (0.04) 
State Aid PP × 2011   -0.26*** -0.20*** 
   (0.04) (0.03) 
State Aid PP × 2012   -0.22*** -0.18*** 
   (0.03) (0.03) 
Observations 5,052 5,052 5,052 5,052 
Property TaxProperty Tax
Local FundingRevenueLocal FundingRevenue
Per PupilPer PupilPer PupilPer Pupil
IVIVIVIV
(1)(2)(3)(4)
State Aid Per Pupil 1.19*** 1.12*** 1.18*** 1.12*** 
 (0.18) (0.18) (0.18) (0.17) 
State Aid PP × Recession -0.24*** -0.20***   
 (0.03) (0.03)   
State Aid PP × 2009   -0.19*** -0.18*** 
   (0.03) (0.03) 
State Aid PP × 2010   -0.31*** -0.22*** 
   (0.04) (0.04) 
State Aid PP × 2011   -0.26*** -0.20*** 
   (0.04) (0.03) 
State Aid PP × 2012   -0.22*** -0.18*** 
   (0.03) (0.03) 
Observations 5,052 5,052 5,052 5,052 
Table A.2.
Did Property Tax Rates Respond to State Aid Cuts During the Great Recession? (Using Instrumental Variables)
IV
Tax RateTax Rate
(1)(2)
State Aid Per Pupil 0.00042** 0.00044** 
 (0.000) (0.000) 
State Aid PP × Recession -0.00028***  
 (0.000)  
State Aid PP × 2009  -0.00015*** 
  (0.000) 
State Aid PP × 2010  -0.00024*** 
  (0.000) 
State Aid PP × 2011  -0.00033*** 
  (0.000) 
State Aid PP × 2012  -0.00038*** 
  (0.000) 
Property Value PP ($000) -0.00080** -0.00080** 
 (0.000) (0.000) 
Observations 5,046 5,046 
IV
Tax RateTax Rate
(1)(2)
State Aid Per Pupil 0.00042** 0.00044** 
 (0.000) (0.000) 
State Aid PP × Recession -0.00028***  
 (0.000)  
State Aid PP × 2009  -0.00015*** 
  (0.000) 
State Aid PP × 2010  -0.00024*** 
  (0.000) 
State Aid PP × 2011  -0.00033*** 
  (0.000) 
State Aid PP × 2012  -0.00038*** 
  (0.000) 
Property Value PP ($000) -0.00080** -0.00080** 
 (0.000) (0.000) 
Observations 5,046 5,046 

Notes:***Statistically significant at the 1% level; **statistically significant at the 5% level; *statistically significant at the 10% level. Robust standard errors adjusted for clustering by school district are in parentheses. All regressions include year fixed effects, racial composition, the percent of students eligible for free or reduced price lunch, per pupil federal aid, and the percent of district funding from state aid. All financial variables are expressed in real terms. See equations 14 in the text.