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Economics of Education Review 19 (2000) 417–429

www.elsevier.com/locate/econedurev

Does fiscal dependency matter? Aid elasticities for

dependent and independent school districts

Thomas A. Downes

*

Department of Economics, Tufts University, Medford, MA 02155, USA

Received 30 January 1998; accepted 26 February 1999

Abstract

In New York state, there is a perception that the fiscally dependent status of the five large city school districts creates an impediment to the attainment of standards. I attempt to assess the impact of fiscal dependence on educational spending. The results suggest that levels of spending may be systematically lower in the fiscally dependent districts. There is, however, little evidence that the general purpose governments to which these districts are fiscally dependent “steal” a disproportionate share of state aid for education. I conclude by evaluating policies that could mitigate any detrimental impact that fiscal dependence might have. This evaluation leads me to the conclusion that, even if spending levels are inadequate, elimination of fiscal dependency may not be the best policy for addressing this problem. Instead, policy makers may want to consider governance changes that would better align responsibilities for allocating revenues to the schools and for governing the schools.2000 Elsevier Science Ltd. All rights reserved.

JEL classification:I22; H77; H72

Keywords:Fiscal dependency; Aid elasticities; Flypaper effect

1. Introduction

Providing students with the skills to meet or exceed stringent academic standards requires both sufficient resources and effective use of those resources. In New York state, there is a lingering perception that the fiscally dependent status of the five large city school districts1

creates an impediment to the attainment of standards in these districts. For example, when the Board of Regents proposed in 1994 that the “category of fiscally dependent districts be eliminated”, the proposal noted that “[t]he present Maintenance of Effort requirements are ... insuf-ficient” to ensure that adequate resources will be allo-cated to the schools. Further, the impetuses for the

pro-* Tel.:+1-617-627-3560; fax:+1-617-627-3917. E-mail address:[email protected] (T.A. Downes).

1 _{The fiscally dependent districts are Buffalo, New York}

City, Rochester, Syracuse, and Yonkers.

posal to eliminate fiscal dependency were the desires to ensure “theefficient use of adequate financial resources to areas which demonstrate the most needand... to move the accountability closer to the public” (Office of Fin-ance, Management and Information Services, 1997).

The facts that have led to these concerns about the fiscal dependency of the five large city districts are numerous and easily related. In the 5 academic years from 1987–88 to 1991–92, each of the five large city districts experienced a maintenance of effort shortfall2_at

2 _{A maintenance of effort shortfall occurs when current}

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least once, with an average of two shortfalls in the 5-year period.3 _{Since shortfalls occur only if per pupil}

spending in a year has declined relative to spending in previous years, the existence of shortfalls signals poten-tial instability in spending in the five large city districts. In addition, instability in spending frequently occurs at the same time that state aid is increasing. For example, between 1990–91 and 1991–92, per pupil state aid to the Buffalo City schools increased by over $100 (in 1991 dollars).4 _{In the same period, total per pupil spending}

and current expenditures per pupil each declined by about $600, in real terms.

The existence of shortfalls and the apparent absence of a positive relationship between state aid and spending are all the more troubling in light of relatively low levels of achievement in the five large city districts. It would seem that the natural conclusion is that either adequate resources have not been provided in these districts or, if adequate resources have been provided, these resources have not been used efficiently. Once this conclusion is drawn, arguing for fiscal independence of the five large city districts seems natural.

Unfortunately, neither the conclusion that fiscal dependence is associated with inadequate or inefficient spending nor the conclusion that fiscal independence will improve the situation in the five large city districts follow from the evidence cited above. Take, for example, the above noted case of Buffalo. Claiming that this case sup-ports the conclusion that state aid increases to five large city districts are not necessarily translated into spending increases is fallacious for one simple reason: we possess no knowledge of what would have happened to spending in the absence of increases in state aid. Similarly, by themselves, shortfalls tell us nothing about the adequacy of spending or the accountability of the schools. In determining if the fiscally dependent status of these dis-tricts adversely affects the quality of education, it is insufficient to consider these districts in isolation, since it is impossible to separate the effects of urbanicity from the effects of fiscal dependency. For similar reasons, it is not enough to compare spending and student ance in these districts to spending and student perform-ance in the fiscally independent districts in New York state.

The foregoing discussion hints at the approach that will be taken in this paper to assess the impact of fiscal

3 _{While only New York City is currently subject to the}

main-tenance of effort requirement, the New York State Education Department calculates shortfalls for the other five large city dis-tricts under the assumption that they are subject to the same requirement.

4 _{These figures, and all revenue and expenditure figures that}

follow, are drawn from the National Center for Education Stat-istics’ Common Core of Data (CCD). Thus, the figures will not correspond to those drawn from administrative data.

dependence. Specifically, I assemble a data set that includes school districts from the New England and Mid-Atlantic states. Because this data set includes a mix of fiscally dependent and fiscally independent districts and a mix of urban, suburban, and rural districts, it can be used to isolate the effect of fiscal dependency on the level, the growth, and the mix of spending. Before I pur-sue that strategy, in the next section of the paper, I ask whether there is any reason to believe that fiscal depen-dency would affect the quality of education provided in the five large city districts.

2. Should fiscal dependency matter?

Are the problems of the five large city districts explained in part or in toto by their fiscally dependent status? Standard economic analysis would suggest that the most likely answer to this question is no. In fact, in their discussion of the possible impact of the fiscally dependent status of the five large city districts, Dick Netzer and Robert Berne (1995, p. 53) give just such an answer:

In fact, there is little reason to believe that fiscal independence would address the problems commonly cited as the reasons for change.

The essence of the argument that lies behind this statement from Netzer and Berne is that there is nothing inherent in any particular fiscal structure that would pre-vent the voters from getting the level of education pro-vision that they desire. In the abstract, government sim-ply serves as an agent for the voters, selecting the spending levels for each public service (and the accompanying levels of taxation) that are desired. If the voters so desire, they can design political institutions such that, whether each service is provided by a different governmental unit or by a single governmental unit mat-ters not at all since individual vomat-ters will balance off their needs for these services, and for private consump-tion, in making their electoral decisions. Thus, the exist-ence of a fiscally independent governmental unit that is responsible for primary and secondary education will not provide education with favored status. Further, fiscal independence will not translate into greater account-ability. The combination of political competition and intergovernmental competition will provide the disci-pline needed to ensure that the educational services pro-vided are of the quality desired by the voters.

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imperfections in the political process or in the process by which information about the provision of government services is disseminated, or the structure of political institutions must be such that outcomes are likely to dif-fer between settings even if no imperfection exists. In reality, it is likely that such imperfections exist and that the institutional setting will matter. For example, in his summary of the literature on general fund financing, Mueller (1979) makes clear that the chosen level of ser-vices under general fund financing can differ from the chosen level of services when each service is, in effect, financed by an independent governmental unit. Spending on any given service could be higher or lower under gen-eral fund financing depending on the “nature and distri-bution of preference functions” (Mueller, 1979, p. 94). The presence of groups of voters that are particularly interested in certain services will only serve to accentu-ate this conclusion (Ingberman & Inman, 1988).

Even if political institutions were structured so that voters, in effect, voted on provision levels for each ser-vice, the analysis of Netzer and Berne (1995) suggests that imperfections in the political process or information imperfections could result in spending differences between the two settings. For instance, the level of edu-cation spending that is selected could be different under a system of fiscal independence of all school districts if different sets of voters participate in municipal elections and in school board elections. If this is the only source of differences between the two settings, however, it can-not be presumed that education spending would increase under fiscal independence (Netzer & Berne, 1995) or that the chosen level of education spending would even be socially more desirable. In fact, since participation in school board elections tends to be lower than partici-pation in municipal elections, fiscal independence could result in a chosen level of educational spending that dif-fers more from what the typical voter desires than does the chosen level of spending under the current system.

Differences in the sets of voters who effectively par-ticipate in the determination of education spending are not the only possible causes of differences in the pro-vision of educational services under fiscal independence and fiscal dependence. Further, these other imperfections could plausibly create the type of problems that pro-ponents of fiscal independence for the five large city dis-tricts apparently want to address. One such imperfection could arise because those who allocate resources to the schools are not those who are ultimately responsible for the quality of the education that is provided. This mis-match can create a situation in which it is difficult for the voters to assign blame if provision of schooling is inadequate. In essence, the opaqueness that is created by the current system permits policy makers to pursue objectives that differ from the objectives of the voters (Filimon, Romer & Rosenthal, 1982).5 _{For those who}

allocate the resources, these objectives could include

increasing non-education spending relative to education spending, a plausible strategy since the ultimate responsibility for the quality of non-education services lies with those who allocate resources. For those who run the schools, this opaqueness may permit use of resources that is technically inefficient, since they may be able to argue plausibly that the problems are attribu-table not to technical inefficiency but to inadequacy of the resources allocated. The ultimate implication of this logic is that the mismatch between those who make spending decisions and those who run the schools means that an increase in aid can translate into an increase in technical inefficiency (Duncombe & Yinger, 1997).

A less cynical explanation for why fiscal dependency might matter is suggested by the voluminous literature that has attempted to explain the phenomenon that has come to be known as the flypaper effect. The reasoning used above to justify the conclusion that fiscal depen-dency should not matter would also lead to the con-clusion that state or federal aid to a local government is equivalent to a grant of income directly to the constitu-ents of that government. Thus, an increase in aid and an equal increase in the income of voters should have the same stimulatory effects on public spending. The bulk of empirical evidence, however, supports the conclusion that aid increases stimulate larger increases in spending than do equivalent income increases. In other words, money tends to stick where it hits—the flypaper effect. In the case of fiscally dependent school districts, a type of flypaper effect could arise if a smaller share of school aid makes it to the schools than in fiscally independent districts. In essence, the aid has “stuck” to the general purpose government responsible for making resource allocation decisions.

The flypaper effect is inconsistent with the notion that individuals can see through the veil of government. The accumulated evidence in a variety of contexts, however, supports the view that, in practice, “the location of a pool of funds can easily alter perceptions of what is fair” (Hines & Thaler, 1995, p. 223). Thus, spending on edu-cation out of aid that goes to a fiscally independent school district could be very different from spending on education out of aid that goes to a general purpose government responsible for allocating resources to a fis-cally dependent school district.

In summary, as the preceding discussion reveals, fiscal dependency could well matter. This discussion also

5 _{In the literature, policy makers in such situations are said}

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reveals, however, that, relative to fiscally independent districts, spending levels and aid elasticities could be higher or lower in fiscally dependent districts. Thus, before venturing into a discussion of solutions to the fis-cal dependency “problem”, the existence of such a prob-lem must be established. This can only be done empiri-cally, and this cannot be done by examining only the experience of the fiscally dependent school districts in New York. The commonly cited problems in these dis-tricts may be attributable to inadequacies and technical inefficiencies in spending arising from fiscal depen-dency, but these problems could also be a result of the fact that the fiscally dependent districts are also urban districts. The work of Duncombe and Yinger (1997) sug-gests that, in New York, cost disparities contribute sig-nificantly to variation in student achievement and that deficiencies in student performance in the five large city districts cannot be explained fully by technical inef-ficiencies. Thus, the observed differences between dependent and independent districts in spending levels and patterns could simply reflect rational responses to differences in circumstances.

The challenge is to isolate the effect of dependency. The next sections of this paper review some initial efforts to estimate this effect.

3. Data

As has already been noted, examination of only the experience in New York state cannot permit us to deter-mine if, for example, a one dollar increase in state aid for education translates into a smaller increase in education expenditures in the five large city districts than in the other school districts in the state. For that reason, I have assembled data on the revenues, expenditures, and characteristics of school districts in the 12 East Coast states from Maine in the north to Virginia in the south. What is ideal about this data set is that it includes fiscally dependent districts in rural, suburban, and urban settings, as well as urban, fiscally independent school districts. Thus, the separate effects of urbanicity and fiscal depen-dency can be parcelled out.

These data are drawn from the Common Core of Data (CCD).6 _{Using the CCD assures comparability of}

rev-enue and expenditure measures. Further, the CCD pro-vides multiple years of data; information for school years 1989–90 to 1994–95 was used in this analysis.

For both the fiscally dependent and fiscally

inde-6 _{Financial data for the 1992–93, 1993–94, and 1994–95}

school years were acquired from the US Census Bureau’s web site (http://www.census.gov/govs/www/schools.html). These data will eventually be incorporated into the CCD.

pendent school districts in New York, Table 1 provides basic summary information on revenues, expenditures,7

and demographics. To observers of New York’s schools, there are no surprises in these numbers. Per pupil expen-ditures are lower in the dependent districts, while per pupil federal aid and per pupil state aid are higher. The differences in the means of per pupil state aid are prim-arily attributable to differences in the categorical compo-nents of state aid; the difference in the means of per pupil operating aid is less than $200. A hint of the higher costs in the fiscally dependent districts is also provided in Table 1; the means of the percent of children living in poverty, the percent of schoolchildren at-risk, and the percent of children who do not speak English well are all substantially higher in the fiscally dependent districts. What the numbers do not reveal is the adequacy or the efficiency of spending. In dependent districts, spend-ing is lower while aid is higher, but such an observation does not allow us to conclude that five large city govern-ments are “stealing” school aid or failing to give proper weight to the needs of schoolchildren. In fact, given the demographics of these dependent districts, these num-bers could as easily support the conclusion that aid has effectively promoted spending in localities with extra-ordinary demands for public services.

4. Fiscal dependency and aid elasticities: preliminary estimates

In the CCD, the location of each school district is assigned to one of seven categories.8 _{Four of the five}

fiscally dependent districts in New York fall into the large central city category.9_{Thus, one avenue for}

explor-ing the role of fiscal dependency is to compare fiscally dependent and independent districts in the large central city category. This comparison can be made using the summary statistics presented in Table 2. From this table, we can see that total and current spending are slightly lower in the fiscally dependent districts, but so too is state aid, both total and operating, to these districts. Thus, the table neither supports nor refutes the claim that fiscal dependency matters. What is apparent from the table is the demographic similarity of the fiscally depen-dent and fiscally independepen-dent districts in this category. There are differences in the means of median income and in the determinants of school district costs, but these

7 _{All dollar figures have been transformed into 1994 dollars}

using the Consumer Price Index for all services.

8 _{These are large central city, mid-sized central city, suburb}

of large central city, suburb of mid-sized central city, large town, small town, and rural.

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Table 1

Spending and demographic characteristics of fiscally dependent and independent school districts in New York State, 1989–90 to 1994–95

Fiscally dependent districts Fiscally independent districts Comparison of means— T-valuesa

Variable Mean Standard Number of Mean Standard Number of

deviation observations deviation observations

Total expenditures 9852.54 1207.02 30 10,950.13 5974.77 4254 4.60

per pupil

Current 8681.21 1007.43 30 9577.63 4256.63 4254 4.59

expenditures per pupil

Equipment 133.12 58.06 30 171.87 181.95 4254 3.53

Total state aid per 4739.14 1011.74 30 3913.87 1859.96 4254 24.42

pupil

Total federal aid 773.55 206.17 30 288.83 271.84 4254 212.80

per pupil

Operating aid per 3278.97 1260.84 20 3021.21 1594.59 2834 20.91

pupil

Median incomeb _30,160.83 _8518.99 ₅ _42,416.62 _16,844.23 ₆₉₉ _3.17

Median house 138,668.91 96,308.53 5 132,266.55 97,754.88 699 20.15

valueb

Children in poverty 31.76 6.83 5 10.86 7.21 699 26.81

(%)b

Schoolchildren at- 9.76 2.00 5 1.47 1.70 699 29.27

risk (%)b

Children—limited 3.16 1.78 5 0.86 1.17 699 22.89

English prof. (%)b

a _{Variances are not assumed to be equal when}_{t-statistics are calculated.} b _{Variable is drawn from the 1990 Census of Population and Housing.}

differences are small in comparison to the differences observed in Table 1.

The barrier to drawing conclusions using a compari-son of means is that in such a comparicompari-son it is not poss-ible to control for cross-state differences in fiscal struc-tures. Such conclusions can be drawn on the basis of estimates of reduced-form expenditure functions. Expen-diture functions are advantageous in this setting also because they are consistent, as first-order approxi-mations, with the outcomes of a variety of different pub-lic choice processes.10_{In other words, since ultimately}

the goal of this research is determining the impact of dependency on expenditures and is not estimating demand parameters, assuming that the estimating equa-tions are based on the median voter model is not neces-sary.

Operationally, the log of expenditures per pupil (Ej)

10 _{Downes (1992) provides a more detailed discussion of}

this point.

for locality j,j=1,...,n, in period t,t=1,...,T, is assumed to be given by

lnEjt5Xita1blnMjt1yln(Vjt)1dlnAjt1flnpjt (1) 1Cjtq1gDj1tDjlnAjt1Fj1Tt1uit

wherepjtis the price of inputs for communityj,Cjtis a

vector of attributes of the community that influence its cost of providing schooling outcomes,Vjtis a proxy for

(measure of) the tax base of that community, Mjt is a

proxy for (measure of) the income of the community’s residents,Ajtis intergovernmental aid to the community,

Xjtis a vector of attributes of the residents of that

com-munity that individually influence their demand for pub-licly provided education, and Dj is a dummy variable

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Table 2

Spending and demographic characteristics of fiscally dependent and independent urban school districts, 1989–90 to 1994–95 Fiscally dependent districts Fiscally independent districts Comparison

of means— T-valuesa

Variable Mean Standard Number of Mean Standard Number of

deviation observations deviation observations

Total expenditures 9006.98 9843.21 271 9717.19 1995.30 66 1.01

per pupil

Current 7653.58 8919.25 271 8729.06 1901.07 66 1.74

Equipment 95.49 305.82 271 106.21 62.45 66 0.58

Total state aid per 3045.82 3774.79 271 3181.59 1843.98 66 0.46

pupil

Total federal aid 429.41 587.20 271 360.04 353.19 66 21.27

per pupil

Operating aid per 1681.51 1966.18 177 2315.74 1418.57 44 2.52

pupil

Median incomeb _45,256.27 _14,275.10 ₄₄ _41,228.97 _16,098.23 ₁₁ _21.01

Median house 180,600.12 55,041.84 44 116,650.76 70,696.81 11 22.76

valueb

Children in poverty 13.75 13.32 44 11.71 13.94 11 20.13

(%)b

Schoolchildren at- 3.78 5.04 44 3.26 5.03 11 0.07

risk (%)b

Children—limited 1.62 2.42 44 1.41 1.31 11 0.47

English prof. (%)b

a _{Variances are not assumed to be equal when}_{t-statistics are calculated.} b _{Variable is drawn from the 1990 Census of Population and Housing.}

The error term in Eq. (1) has three components: a locality-specific effectFj; a time-specific effect Yt; and

a purely random effectujt. When estimating the

expendi-ture function, both the locality-specific effect,F, and the time-specific effect T can be treated as either fixed or random. In the estimates presented below, the time-spe-cific effects T are always assumed to be fixed. The approach taken with F is more agnostic since, if F is treated as a fixed effect, it is not possible to determine how spending levels differ between fiscally dependent and fiscally independent districts, all else being equal. For this reason, estimates of Eq. (1) in whichFis not treated as a fixed effect are presented below. TreatingF

as a fixed effect does, however, eliminate bias due to correlation ofincluded explanatory variables with omit-ted variables whose influence on expenditures varies across localities but is stable across time within each locality. The random-effects specification is preferable to the fixed-effects specification not just because the full impact of dependency can be estimated but also because the random effects estimates are more efficient if the locality-specific effect is uncorrelated with the

regressors. The locality-specific effectFmay, however, include omitted determinants of provision costs or demand that are correlated with included cost or demand determinants.11 _{To avoid pre-judging the question of}

whether the locality-specific effect is correlated with included regressors, a Hausman test for the appropriate-ness of the random-effects model (i.e. a test of the hypothesis that F is statistically independent of the regressors) was implemented. The relevant test statistics are reported below.

Implicit in the specification of the expenditure func-tion given in Eq. (1) are several assumpfunc-tions that warrant comment. The first of these assumptions is that the deter-minants of the cost of provision can be cleanly divided from the determinants of demand for the publicly-pro-vided outputs. In practice, such a clean division is neither

11 _{When estimating expenditure functions like those}

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necessary nor possible.12_{Since the goal of this work is}

to estimate aid elasticities, it matters not at all whether the remaining independent variables are interpreted as cost or demand determinants. The second assumption implicit in the specification given in Eq. (1) is that the structure of the expenditure function is time-invariant. In reality, this assumption is testable. For the data used in the analysis that follows, the null hypothesis that the structure is time-invariant can be rejected at the 1% level.13_{None of the fundamental conclusions changed,}

however, when the parameters in Eq. (1) were allowed to change from year to year. Thus, so as to avoid over-whelming the reader with numbers, the results presented below are based on the restricted specification presented in Eq. (1). Finally, as the specification is written, all of the observable determinants of expenditures save for the dependency dummy are assumed to be time-varying. In reality, many of the determinants are temporally stable.14

As a result, the impact of these determinants on expendi-tures cannot be estimated if the locality-specific effectF

is such that a fixed-effects variant of Eq. (1) must be esti-mated.

Since the CCD provides information on operating aid only after 1990–91, two sets of regressions were esti-mated for both the random effects and fixed effects vari-ants of Eq. (1). First, all components of state aid were combined into a single measure. Second, the later years of data were used to see if operating aid has an effect on spending that differs from the effect of the various categorical aid programs.

Estimates of Eq. (1) which treat the locality-specific effect as uncorrelated with the included regressors are given in Table 3.15 _{Since the null hypothesis that the}

locality-specific effect is uncorrelated with the included regressors can be rejected for each variant of Eq. (1) presented in Table 3,16_{these estimates are presented}

sim-ply to provide the best available evidence of how, all else being equal, total spending and its components differ between dependent and independent districts. With that cautionary note in mind, what is evident from Table 3 is that these estimates provide a relatively consistent pic-ture of the effect of fiscal dependency on the level and the mix of spending. At best, total per pupil spending

12 _{That such a clean division is not possible has long been}

realized; see Hamilton (1983) for an example that draws out this difficulty.

13 _{The relevant}_{F-statistic equals 27.2058 with 34 numerator}

and 16,161 denominator degrees of freedom.

14 _{Specifically, a single value is observed for any variable}

that is drawn from the 1990 Census.

15 _{The standard errors reported in Table 3 are robust to}

het-eroscedasticity and second-order autocorrelation. Those reported in Tables 4 and 5 are robust to heteroscedasticity.

16 _{The Hausman test statistics ranged in value from 127.38}

to 6239.1.

and each component of spending are essentially the same in fiscally dependent and fiscally independent districts. At worst, total spending and each component of spending are lower in fiscally dependent districts. For example, the estimates imply that current spending per pupil could be as much as 5% lower in the fiscally dependent dis-tricts, all else being equal.17_{Thus, these estimates imply}

that fiscal dependency could plausibly be a barrier to adequate provision of education.

For the reasons noted above, conclusions drawn on the basis of the estimates in Table 3 must be interpreted with caution. Less caution is needed in drawing conclusions using the fixed-effect estimates in Table 4. Since the underlying specification is in log–log form, the estimates in Table 4 give the relevant aid elasticities. Thus, for example, the second column of Table 4 implies that a 1% increase in per pupil operating aid will translate into a 0.034% increase in per pupil expenditures.

While this elasticity and the other elasticities given in Table 4 seem low, they are actually reasonably consistent with other estimates of the responsiveness of spending to aid. Most of the discussion of estimates of the relation-ship between aid and spending focuses on the implied change in spending that results when aid increases by one dollar. Fisher (1996) indicates that most estimates of the relationship between aid and spending imply that a $1 increase in lump sum aid will translate into an increase in spending of between $0.25 and 0.50. Bartle’s (1995) summary of the literature provides some indi-cation of the relationship between aid and spending for large central cities. For fiscally dependent school districts like those in New York, the responsiveness of total city spending to aid provides the best available comparisons currently available in the literature, even though, for all of the reasons noted above, there is no reason to expect that the aid elasticities for total city spending and for education spending are equal. The estimates that Bartle reports indicate that a $1 increase in lump sum federal aid could result in an increase in spending of anywhere between $0 and $1, with the sole estimate of the relation-ship between lump sum state aid and spending equa-ling 0.32.

The case that the aid elasticities given in Table 4 fall inside the range can be made by calculating, for a typical district,18 _{the spending increases that result from a $1}

increase in aid. For example, the results in Table 4 imply that, for a fiscally dependent urban school district with the mean levels of total spending per pupil and operating

17 _{Using as the base the mean characteristics for fiscally}

inde-pendent urban districts given in Table 2, these estimates trans-late into a spending difference of the order of $412 per pupil.

18 _{Since the expenditure function is in log–log form, the}

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Table 3

Estimates of aid elasticities—expenditures in levels model method of estimation: ordinary least squares (asymptotic standard errors in parentheses)a

Independent variables Dependent variable

Log of total Log of total Log of Log of Log of Log of expenditures expenditures current current equipment equipment per pupil per pupil expenditures expenditures expenditures expenditures

per pupil per pupil per pupil per pupil

Log of median income 20.0096 0.1901 20.0133 0.0922 20.2912 20.2707

(0.0271) (0.0308) (0.0229) (0.0289) (0.0792) (0.1071)

Log of median house value 0.2677 0.1576 0.2247 0.1634 20.0896 20.1394

(0.0150) (0.0158) (0.0136) (0.0150) (0.0429) (0.0549)

Children in poverty (%) 0.0022 0.0047 0.0027 0.0038 0.0002 0.0007

(0.0007) (0.0007) (0.0006) (0.0007) (0.0022) (0.0029) Schoolchildren at-risk (%) 20.0019 20.0047 20.0020 20.0047 0.0029 20.0042 (0.0017) (0.0019) (0.0016) (0.0016) (0.0058) (0.0076) Children with limited English profic. (%) 20.0052 20.0029 20.0042 20.0037 20.0054 0.0109

(0.0025) (0.0031) (0.0023) (0.0029) (0.0102) (0.0123) African–American children (%) 0.0032 0.0025 0.0026 0.0018 20.0010 20.0001 (0.0003) (0.0003) (0.0003) (0.0002) (0.0009) (0.0011)

Hispanic children (%) 0.0035 0.0042 0.0017 0.0025 20.0049 20.0016

(0.0006) (0.0007) (0.0006) (0.0008) (0.0022) (0.0027)

Asian–American children (%) 0.0032 0.0027 0.0029 0.0036 20.0054 0.0005

(0.0011) (0.0014) (0.0009) (0.0012) (0.0039) (0.0055)

Adults with hs degree (%) 20.0001 20.0010 20.0004 20.0009 0.0047 0.0044

(0.0006) (0.0007) (0.0005) (0.0006) (0.0019) (0.0024)

Adults with college degree (%) 0.0037 0.0022 0.0032 0.0025 0.0164 0.0157

(0.0005) (0.0005) (0.0004) (0.0005) (0.0016) (0.0020)

Pop. age 5–17 (%) 20.0014 20.0106 20.0013 20.0062 20.0025 0.0028

(0.0014) (0.0009) (0.0011) (0.0008) (0.0013) (0.0034) Log of total number of students 20.1123 20.0940 20.0491 20.0404 20.0438 20.0577 (0.0036) (0.0039) (0.0032) (0.0036) (0.0104) (0.0137)

Log of total federal aid 0.0419 0.0440 0.0594 0.0658 0.0684 0.0657

(0.0060) (0.0073) (0.0055) (0.0060) (0.0180) (0.0244) Interaction of fed. aid with dep. dummy 20.0251 20.0031 0.0053 0.0171 0.1176 0.1455

(0.0090) (0.0117) (0.0079) (0.0111) (0.0302) (0.0413)

Log of total state aid 0.0662 20.0101 20.0883

(0.0069) (0.0063) (0.0183)

Interaction of st. aid with dep. dummy 0.0087 0.0210 20.0099

(0.0105) (0.0092) (0.0328)

Log of operating aid 0.0194 20.0118 20.0647

(0.0038) (0.0036) (0.0154)

Interaction of op. aid with dep. dummy 0.0006 0.0049 20.0130

(0.0060) (0.0056) (0.0237)

Log of categorical aid 0.0486 0.0273 0.0216

(0.0046) (0.0039) (0.0173)

Interaction of cat. aid with dep. dummy 0.0186 0.0250 20.0585

(0.0105) (0.0099) (0.0306)

Dependent district dummy 0.0459 20.1186 20.2572 20.3434 20.8725 20.6380 (0.0904) (0.1110) (0.0846) (0.1109) (0.2633) (0.2872)

Number of observations 16,371 9712 16,371 9712 15,899 9473

a _{In addition to the variables given above, each regression includes a constant, year dummies, state dummies, and dummy variables}

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Table 4

Estimates of aid elasticities—fixed effects model method of estimation: ordinary least squares (asymptotic standard errors in parentheses)a

per pupil per pupil per pupil per pupil Log of total number of students 20.7925 20.8769 20.7943 20.8764 20.6601 20.9942 (0.0252) (0.0275) (0.0234) (0.0261) (0.0797) (0.1660)

(0.0045) (0.0061) (0.0024) (0.0038) (0.0209) (0.0440) Interaction of fed. aid with dep. dummy 0.0047 0.0233 0.0010 0.0084 0.0889 20.1597 (0.0071) (0.0107) (0.0044) (0.0074) (0.0471) (0.0862)

(0.0083) (0.0051) (0.0293)

(0.0124) (0.0087) (0.0727)

(0.0080) (0.0037) (0.0442)

(0.0103) (0.0074) (0.0690)

(0.0037) (0.0013) (0.0210)

(0.0107) (0.0056) (0.0909)

Number of observations 16,801 9903 16,801 9903 16,310 9655

R2 _0.9065 _0.9266 _0.9710 _0.9796 _0.5494 _0.6119

a _{In addition to the variables given above, each regression includes year dummies.}

aid per pupil given in Table 2, a $1 increase in operating aid per pupil would result in a $0.1685 increase in total spending. A $1 increase in operating aid per pupil would translate into a $0.1271 increase in total spending. Though these aid responses are low, they are within the range given by Bartle and are only slightly outside the range given by Fisher.

A quick perusal of the estimates in Table 4 reveals that there is little evidence to support the claim that smaller percentages of the aid increases in fiscally dependent dis-tricts show up in increased spending. In fact, while the estimates imply that the elasticity of total spending with respect to total state aid is smaller in dependent districts, the estimates also indicate that the elasticity of current spending with respect to operating aid is larger in the fiscally dependent districts. In addition, the elasticity of both total and current spending with respect to total fed-eral aid appears to be slightly larger in these districts, further support for the claim that aid elasticities in depen-dent districts are not lower.

In conclusion, these estimates suggest that while fiscal dependency may matter, it does not appear to matter in quite the manner that might have been expected. The results imply that levels of spending may be

systemati-cally lower in the fissystemati-cally dependent districts, though this conclusion must be viewed with caution. What does seem clear is that there is little, if any, evidence that the general purpose governments to which these districts are fiscally dependent “steal” a disproportionate share of state aid for education.

5. Policy options

The results discussed in the previous section suggest that the fiscally dependent status of the five large city school districts has, at most, a limited effect on the level and mix of spending in these districts. Nevertheless, if fiscal dependency has any impact at all, as some of the results suggest, policies that mitigate this impact must be considered. In this section, five policy options will be considered: fiscal independence; alignment of resource allocation and governance; increased use of categorical grants; extension of the minimum effort requirement beyond New York City; and use of matching grants that provide a financial incentive to spend.

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dependent status of the five large city districts. The fact that this option has been considered since at least 1964 but never adopted suggests that the political barriers are large. As importantly, fiscal independence could aggra-vate some of the problems that exist in the fiscally dependent districts. The City of Chicago Public School District offers an example of a case in which a move away from fiscal independence has translated into appar-ent improvemappar-ent in the fiscal position of the school dis-trict and in the performance of students residing in the district. Historically, the City of Chicago Public School District has been fiscally independent; that status has not prevented the district from effectively slipping into receivership in the late 1980s. Nor has that status resulted in student performance that is, by any measure, acceptable. While recent reform attempts have been mar-ginally successful, they have not resulted in the dramatic turn-around that the political leaders of the city and their constituents sought.19_{As a result, in 1995 the Mayor of}

Chicago, Richard M. Daley, made a deal with state polit-ical leaders that gave him effective control over the finances and governance of the public schools. While this shift in control has been in place for too short a time to determine its ultimate success, early evaluations suggest that more effective use is being made of existing resources and that student performance may be improv-ing.20

This example suggests that a second policy option, aligning responsibility for the finances and the govern-ance of the public schools in the fiscally dependent dis-tricts, could alleviate many of the problems that fiscal dependence is perceived to create. As Netzer and Berne (1995) note, this policy option is not new to anyone who has observed the battles over control of the public schools in New York City. Thus, like the fiscal indepen-dence option, this option could come up against signifi-cant opposition, though experiences like that in Chicago may help to weaken this opposition.

What aligning responsibility cannot do is automati-cally induce spending increases, even if the voters desire such increases. Elected officials could still possess mon-opoly power and thus could still thwart the desires of the voters. Since alignment makes it simpler for voters to observe how dollars are allocated and spent, however, it is likely that exercising this option will lessen the extent of monopoly power, if any exists. Further, if the

19 _{See Downes and Horowitz (1995) for further discussion of}

the recent history of finances and reform in the City of Chicago Public School District.

20 _{For further discussion of the improvements in the financial}

status of and the student performance in the Chicago public schools, see “Chicago Schools Bring Home a Better Grade”, Chicago Tribune, 8 April 1997, and “City’s High Schools Take Big Step up on Test Scores”,Chicago Tribune, 1 May 1997.

mayor and other elected leaders can be held directly responsible for the quality of the local public schools, they are likely to pay more attention to the adequacy of education spending and to the uses of those education dollars. In other words, increases in the level of spending and improvements in technical efficiency are likely under this policy option.

In an effort to further explore the potential effective-ness of this second policy option, a variant of the expen-diture function was estimated in which separate aid elas-ticities were estimated for districts with elected school boards and for districts with appointed school boards.21

The results are given in Table 5. In general, the estimates support the view that aligning responsibilities can increase education spending. Specifically, for both total and current spending, aid elasticities in districts with appointed school boards are never significantly lower than aid elasticities in districts with elected boards.22

Further, aid elasticities in districts with appointed boards are sometimes significantly higher. While the rarity of within state variation in the alignment of responsibilities means the results in Table 5 are, at best, suggestive, these results strongly suggest that further exploration of the implications of this second policy option is warranted.

The results above suggest that the third policy option, increasing the share of state dollars that reach localities in the form of categorical grants, may do little to allevi-ate the problems in the fiscally dependent public school districts. The elasticities given in Table 4 indicate that shifting aid from operating aid to categorical aid would reduce per pupil spending, though these reductions would be small since the elasticities of spending with respect to operating and categorical aid are typically not substantially different. Spending could be increased by increasing categorical aid, though the estimates above suggest increasing operating aid may be a more effective strategy for increasing spending.

Recent work by Staples and Rubin (1997) suggests another potential problem with increasing the reliance on categorical aid. In their examination of the budgeting process in Virginia school districts, all of which are fis-cally dependent, Staples and Rubin found that increased dependence on categorical spending requirements increased the likelihood that actual school district expen-ditures would exceed budgeted school district expendi-tures. By limiting the fungibility of dollars within the school district’s budget, categorical spending

require-21 _{Thanks to Don Boyd for suggesting this potential}

specifi-cation.

22 _{For each type of aid, the relevant aid elasticity for}

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Table 5

Estimates of aid elasticities—fixed effects model method of estimation: ordinary least squares (asymptotic standard errors in parentheses)a

per pupil per pupil per pupil per pupil Log of total no. of students 20.7351 20.8039 20.7335 20.7895 20.5863 20.8356 (0.0315) (0.0547) (0.0311) (0.0576) (0.0861) (0.2138)

(0.0046) (0.0061) (0.0025) (0.0039) (0.0210) (0.0441) Interaction of fed. aid with dep. dummy 20.0070 0.0168 20.0108 0.0027 0.0784 20.1596 (0.0077) (0.0111) (0.0050) (0.0078) (0.0487) (0.0881) Interaction of fed. aid with app. dummy 0.0640 0.0482 0.0892 0.0221 20.0157 20.3067 (0.0278) (0.0376) (0.0303) (0.0401) (0.1742) (0.2861)

(0.0085) (0.0053) (0.0294)

(0.0136) (0.0095) (0.0797)

Interaction of st. aid with app. dummy 0.1424 0.1293 0.2849

(0.0220) (0.0246) (0.1754)

(0.0082) (0.0039) (0.0445)

(0.0108) (0.0077) (0.0725)

(0.0173) (0.0276) (0.1716)

(0.0037) (0.0013) (0.0210)

(0.0114) (0.0065) (0.0966)

Interaction of cat. aid with app. dummy 0.1041 0.1276 0.9486

(0.0442) (0.0388) (0.3287)

Observations 16,801 9903 16,801 9903 16,310 9655

R2 _0.9074 _0.9270 _0.9720 _0.9802 _0.5496 _0.6127

a _{In addition to the variables given above, each regression includes year dummies.}

ments limit the district’s ability to respond to changing circumstances. Thus, even though these results suggest that categorical spending requirements can stimulate increased total spending on education, the results also imply that the increased spending would be unplanned and potentially short-lived.

Extending the minimum effort requirement to all of the five large city districts could only translate into increased spending if these requirements have teeth. Dis-cussion of the efficacy of the minimum effort require-ment for New York City suggests that, since the budg-eted amounts, not actual spending are used to determine satisfaction of the requirement, the requirement fails to place a floor under actual spending. A requirement that was based on actual spending would limit the ability of localities to respond to changing circumstances. In addition, it is not obvious how localities would be

pun-ished if they failed to meet the requirement. Many poten-tial punishments, such as reductions in state aid, would have the effect of hurting those children the minimum effort requirement was designed to help. In short, expan-sion of the minimum effort requirement is an imperfect method, at best, for achieving the goal of increased spending.

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edu-cation.23 _{In general, compelling justifications must be}

offered for spending requirements since there is no rea-son to believe that, in practice, state policy makers have better knowledge of the needs and desires of a locality’s residents than do those residents and their elected lead-ers. That is not to say that there are not circumstances under which state intervention in the form of minimum spending requirements is justified. The discussion above suggests such circumstances. Even under such circum-stances, however, an alternative to dictating spending levels may be to change the locality’s incentives to spend on education.

This argument brings us to the final policy option, use of matching grants to encourage increased spending. Currently, each dollar of spending in excess of combined state and federal aid costs the locality a dollar. For each dollar of spending above some pre-established level, the matching grant would have the effect of reducing below one dollar the local cost of additional spending.

Such a matching grant program could easily be designed to supplement the existing operating aid pro-gram. In fact, any matching grant program should be considered only if it supplements, rather than replaces, the existing operating aid program. This hybrid system of state aid would ensure a minimum level of provision in all districts, even if there is no minimum effort requirement. No such insurance exists under an operating aid system involving only matching grants. Reschovsky and Wiseman (1994) provide evidence that the matching grant (District Power Equalization) system in Wisconsin has neither eliminated spending inequality nor resulted in spending in excess of some minimum level.

One advantage of supplementing the existing operating aid grants with matching grants is that localities continue to be given discretion over spending. A second advantage is that localities would still be responsible for financing a sizeable portion of the basic level of spending.24_{There are, however, two obvious}

dis-advantages associated with this policy option. First, most of the extant evidence on matching grants in education indicates that, while such grants stimulate larger spend-ing increases than do equal-value lump sum grants, the matching grants are not substantially more stimulative

23 _{To some extent, these problems can be avoided by}

mandat-ing a minimum tax rate as opposed to establishmandat-ing a minimum spending level. Such a policy is advocated by Duncombe and Yinger (1997). If a minimum tax rate is mandated, then, if there is a relative decline in a district’s property values, the district would not be required to increase the nominal property tax rate, as would be necessary if there was a minimum spending requirement. Still, if the minimum tax rate is sufficiently high, it too can lead to some of the problems discussed here.

24 _{Maintaining a substantive local role in financing helps to}

maintain the incentive for local residents to monitor the effec-tiveness with which dollars are used.

since demand for education is price-inelastic (Fisher, 1996).25_{Thus, a relatively high matching rate would be}

needed to stimulate tangible spending increases. This conclusion brings us to the second disadvantage of a matching grant program: the cost. If the incentives work well, the amount of aid that needs to be given may be large. The magnitude of the state commitment would depend both on the matching rate and on the level of spending beyond which the matching grant becomes operative. State budgetary liability could be limited by setting a low matching rate, by setting a high operative spending level, or by explicitly capping this liability. All of these methods of limiting liability reduce the spending incentives for local governments, however. Some exper-imentation may be needed to set the parameters of the policy so that localities are given the right incentives and the state government expense is manageable.

In conclusion, even if spending levels are inadequate, elimination of fiscal dependency may not be the best pol-icy for addressing this problem. Better aligning responsi-bilities for allocating revenues to the schools and for governing the schools is one policy option that warrants serious consideration. Consideration should also be given to using matching grants to change the incentives that urban districts have to increase spending. Neither of these policies represents a quick fix, but experience suggests that each of these options will address the per-ceived causes of the current problems.

Acknowledgements

Thanks to Helen Connolly for assistance with data assembly and to Don Boyd, Larry Kenny, Jim Wyckoff, and an anonymous referee for helpful comments and suggestions. All remaining errors are those of the author.

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