The E ect of School District Financial Health Information ...haider/LaborDay/thompson.pdf · e ects...

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The Effect of School District Financial Health Information on Housing Prices: Evidence from Fiscal Stress Labels in Ohio * Paul N. Thompson Michigan State University Preliminary Draft: Please Do Not Cite May 10, 2013 Abstract Fiscal stress labels identify fiscally troubled school districts, aid in financial recovery, and alert residents of the overall fiscal health of these districts. This paper is one of the first to examine how school districts and residents are responding to receipt of these labels. Examining the use of these labels in Ohio from 2000-2012, I find that districts decrease expenditures following label receipt, with the largest cuts occurring immediately after the label is received or after district finances are taken over by the state. In addition to expenditure cuts, local property tax revenue for operating expenditure increases following label receipt. In response to these changes, I find that housing prices fall following the receipt of these labels. Following label receipt, prospective homebuyers are willing to pay nearly four percent less for homes in labeled districts, with the largest effects occurring after district finances are taken over by the state. Keywords: Fiscal Stress; House Prices; School Districts. JEL Classification Numbers: H75, I2, R31. * The author is grateful to Mike Conlin for his guidance and suggestions. Thanks also goes to Leslie Papke, Steven Haider, and the participants of the 2012 Meeting of the Annual Conference on Taxation and 2013 Annual Meeting of the Midwest Economics Association for their helpful comments and discussion. A special thanks to the various county Auditor’s offices and members of the Ohio Department of Education who helped me during the collection of the data. This work was supported in part by a Pre-Doctoral Training Grant from the Institute of Education Sciences, U.S. Department of Education (Award #R305B090011) to Michigan State University. Department of Economics, Michigan State University, 110 Marshall Adams Hall, East Lansing, MI 48824, email: [email protected] 1

Transcript of The E ect of School District Financial Health Information ...haider/LaborDay/thompson.pdf · e ects...

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The Effect of School District Financial Health Information on

Housing Prices: Evidence from Fiscal Stress Labels in Ohio∗

Paul N. Thompson†

Michigan State University

Preliminary Draft: Please Do Not Cite

May 10, 2013

Abstract Fiscal stress labels identify fiscally troubled school districts, aid in financial recovery,

and alert residents of the overall fiscal health of these districts. This paper is one of the first to

examine how school districts and residents are responding to receipt of these labels. Examining

the use of these labels in Ohio from 2000-2012, I find that districts decrease expenditures following

label receipt, with the largest cuts occurring immediately after the label is received or after district

finances are taken over by the state. In addition to expenditure cuts, local property tax revenue

for operating expenditure increases following label receipt. In response to these changes, I find

that housing prices fall following the receipt of these labels. Following label receipt, prospective

homebuyers are willing to pay nearly four percent less for homes in labeled districts, with the

largest effects occurring after district finances are taken over by the state.

Keywords: Fiscal Stress; House Prices; School Districts.

JEL Classification Numbers: H75, I2, R31.

∗The author is grateful to Mike Conlin for his guidance and suggestions. Thanks also goes to Leslie Papke, StevenHaider, and the participants of the 2012 Meeting of the Annual Conference on Taxation and 2013 Annual Meetingof the Midwest Economics Association for their helpful comments and discussion. A special thanks to the variouscounty Auditor’s offices and members of the Ohio Department of Education who helped me during the collectionof the data. This work was supported in part by a Pre-Doctoral Training Grant from the Institute of EducationSciences, U.S. Department of Education (Award #R305B090011) to Michigan State University.†Department of Economics, Michigan State University, 110 Marshall Adams Hall, East Lansing, MI 48824, email:

[email protected]

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1 Introduction

In the current financial climate, school districts have not been immune to financial hardships.

It is not uncommon to observe school districts operating under large budget deficits due to expen-

ditures outpacing revenues. In order to help districts address these growing deficits, some states

have developed fiscal stress indicators that provide early warning signs of deficits and other finan-

cial problems. The goal of these indicators is to identify financially troubled districts and help

to alleviate these problems before the financial situation becomes too dire.1 These fiscal stress

indicators often take the form of labels indicating varying levels of fiscal distress. As noted in

Kloha, et al. (2005) these fiscal health indicators serve multiple purposes. In addition to providing

early warning signs of problems, they identify which school districts require state intervention. In

these most severe cases, a state-appointed committee develops a financial recovery plan and ensures

its implementation. Lastly, these indicators serve to alert current and potential residents of the

overall financial health of the district. Given that the overall financial health may be difficult for

individuals to determine, the indicators may serve as a signal of financial trouble. Therefore, these

labels may alert residents to fiscal problems that are beyond what they can ascertain in the absence

of these indicators.

Despite the growing use of these labels, little is known about how districts are responding to the

sanctions (i.e. mandated financial recovery plans) associated with these labels. Districts placed in

fiscal stress are required to create a financial recovery plan that will lead to balanced budgets in the

future. In the most severe case of fiscal stress, a state commission is given the authority to develop

and implement a recovery plan for the district. So, how are these recovery plans achieving the goal

of future balanced budgets? In particular, are there differences between recovery plans undertaken

by the district and those undertaken by the state? Given that the state has more authority to

make budget cuts, state-led recoveries may exhibit greater reductions in operating expenditures

than recovery plans implemented by school districts.

In addition to examining school district responses to these labels, I analyze how the housing

1Honadle (2003) and Kloha, et al. (2005) found that 15 states had some fiscal health evaluation system in placeand nearly a third more states are considering using these indicators.

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market reacts to label receipt and the subsequent recovery plans. Unlike previous studies, which

primarily examine the effects of transitory changes to school inputs and outputs on housing prices,

I examine the effect of sudden, long-lasting changes in revenues and expenditures on housing prices

in these labeled districts. If the recovery plans are working as intended, the changes undertaken

in these districts are likely to be relatively long-lasting in order to maintain balanced budgets in

the future. Therefore, the housing market is likely to react differently to less transitory changes

in school district finances. Potential homebuyers may either positively or negatively value these

recovery plans, depending on the type and amount of expenditure eliminated and the amount of

additional taxes these homebuyers will face in the future. Reducing expenditure and increasing

taxes is likely to reduce the attractiveness of the tax-services bundle offered by the district, which

may lead potential homebuyers to lower their valuations for housing in the district. Given that these

sudden, long-term cuts or tax increases may be larger than ordinary year-to-year fluctuations, these

changes may have a greater impact on housing prices than what is found in the previous literature.

On the other hand, if the recovery plans primarily eliminate unnecessary or inefficient spending

then potential homebuyers may positively value these recovery plans, as the cuts are unlikely to

impact the academic quality of the educational services the district provides. In addition, if these

recovery plans work as intended, districts will be more financially viable in the future and this

future financial stability may also be positively valued by homebuyers.

This paper provides the first analysis of the effect of these labels on school district financial

behavior and the housing market. I focus on the state of Ohio, which categorizes school districts into

three levels of fiscal stress. I examine the impact of label receipt on school district expenditures

and revenues from 2000-2010. I also analyze the impact of these labels on housing prices using

residential home sales data from 2000-2012. I find that districts reduce expenditures, primarily

new construction and salaries, and increase local property tax revenue for operating expenditure

following label receipt. These changes are immediate and long-lasting, with significant effects

persisting many years after initial label receipt. I also find that home prices fall by around four

percent following a district’s receipt of a fiscal stress label. These effects are largest under the most

severe rating, a situation where district finances are overtaken by a state financial commission.

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The paper begins with a brief literature review that summarizes the existing literature on the

capitalization of school quality. Section 3 provides background on the fiscal health indicators used

in Ohio and explains what situations necessitate the use of these indicators. The relevant data

sources used in this analysis are described in Section 4. The empirical models used are described

in Section 5 to help better understand how these labels might influence school district finances and

the housing market. The empirical results are presented in Section 6. Section 7 discusses the main

conclusions regarding the the effects of these labels on housing prices.

2 Literature Review

A large literature has examined the capitalization of academic school quality measures into

housing valuations.2 A majority of this literature has focused on the capitalization of student test

scores. Black (1999) examines the effect of test scores on housing prices in the Boston metropolitan

area. Comparing homes on either side of school attendance zone boundaries, she finds that a one

standard deviation increase in test scores increases housing prices by around 2.1 percent. Other

studies of United States school districts (Bayer et al., 2007; Clapp et al., 2008; Dougherty et al.,

2009) find similar sized effects of yearly test score levels on home prices. In addition to literature on

the capitalization of test scores in the United States, there work in international settings (Gibbons

and Machin, 2003, 2006; Gibbons, Machin, and Silva, 2009; Fack and Grenet, 2010; Davidoff

and Leigh, 2008) also finds similar sized effects of test score levels on home prices. Based on

this expansive literature, the current benchmark magnitude of the average causal effect of a one

standard deviation increase in test scores is around three percent (Black and Machin, 2010). In

addition to test score levels, a few studies (Brasingtion and Haurin, 2006; Downes and Zabel, 2002;

Kane et al., 2006) have analyzed the impact of student test scores gains, year-to-year changes in

test score levels, on housing prices, but largely find no effect of these student gains on housing

prices.

Some of this literature has also focused on the capitalization of school inputs, primarily per-

2For a more expansive review of the literature and the econometric issues surrounding estimating these effects,see the Black and Machin chapter of the “Handbook of the Economics of Education” or Nguyen-Hoang and Yinger(2011).

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pupil expenditures. Most notably, Black (1999) finds that a $500 increase in per-pupil expenditures

increases house prices by 2.2 percent. Cellini, et al. (2010) examine the effect of passing property

tax referenda for capital expenditure on housing prices. They find that marginal homebuyers are

willing to pay $1.50 for an additional dollar of capital spending. They find some positive effects of

bond passage on student achievement, but they attribute much of the increase in home values to

the increased safety and aesthetics of new and renovated buildings.

A smaller literature has focused on the effect of overall academic quality indicators on housing

prices. Figlio and Lucas (2004) examine the capitalization effects of school district report card

grades in Florida. Similar to the fiscal health labels examined here, the school district report card

grades represent an “information shock” to residents. They find that even when controlling for

student test scores, the measure most often used as a proxy for overall school quality, homebuyers

are still responsive to the report card grades. Their results suggest that report card grades do

provide information about school quality beyond the information signaled by student test scores,

information that may be hard for residents to ascertain in the absence of these grades. They find

that receipt of an ”A” grade is associated with a 19.5 percent increase in home values relative

to schools receiving a ”B” grade. Kane, Staiger, and Samms (2003) examine the effects of these

categorical ratings on house prices in Mecklenburg County, North Carolina. They find that housing

prices are more sensitive to long term trends in school quality than to year-to-year fluctuations in

school quality. They do not find any impact of receipt of a ”low-performing” rating, largely due

to these districts being low-performing for a long time prior to receiving the ratings. Fiva and

Kirkebøen (2009) analyze the release of school quality information in Norway and find short-term

effects on housing prices, but the effect of this information only lasts for two or three months.

Zahirovic-Herbert and Turnbull (2009) examine how housing prices react to changes in these school

quality ratings in the East Baton Rouge Parish school district. They find that improvement in the

school ranking increases house prices between 3.8 percent and 6.1 percent.

The main contribution of this paper is to examine how school districts and housing prices

respond to mandated reductions in expenditures and/or increases in local taxation. The above

literature has primarily examined year-to-year fluctuations in school inputs and outputs, which

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are largely transitory changes based on yearly need. If these mandated recovery plans work as

intended, school districts experience a permanent, or relatively long-term shock, to revenues and/or

expenditures in order to maintain balanced budgets over many years. Therefore, housing prices

may react differently to a permanent, or less transitory, shock to a district’s finances than they

do to yearly fluctuations in these variables. As discussed previously, whether homebuyers react

positively or negatively to these changes largely will depend on the nature and size of the cuts

and/or increases in tax burden.

3 Fiscal Stress Labels in Ohio

3.1 Overview of Fiscal Stress Labels

Ohio school districts with financial difficulties may be placed into one of three fiscal stress

categories indicating various levels of severity: fiscal caution (least severe), fiscal watch, or fiscal

emergency (most severe). Their use dates back to the 1970s when the City of Cleveland was

declared in fiscal emergency, but has since grown to include the early warning indicators of fiscal

watch and fiscal caution. The fiscal watch label was introduced in 1996 for both local governments

and school districts to identify jurisdictions potentially in danger of falling into fiscal emergency.

To provide even earlier detection of financial problems, the fiscal caution label was established for

school districts in 2001 and local governments in 2011.3

Data on the school districts currently, or previously, labeled in one of the three fiscal stress

categories were obtained from the Ohio Auditor’s office and the Ohio Department of Education.

This data includes the date the school district was declared fiscally stressed and, if no longer labeled,

the date the fiscal stress label was removed. The data set also contains indicators for whether a

jurisdiction receives a fiscal emergency, fiscal watch, or fiscal caution label. Dates of transition from

one label to another are also collected and include an indicator for whether a downgrade to a more

severe label resulted from the school district’s failure to adopt a suitable financial recovery plan.

3For more detailed information regarding the history of these labels, the various criteria used to selectthese districts, and the requirements associated with these labels see the Ohio Auditor of the State website(http://www.auditor.state.oh.us/services/lgs/fiscalwatch/schools.htm) or the Ohio Department of Education Website(http://www.ode.state.oh.us/gd/gd.aspx?page=2TopicRelationID=1012).

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As shown in Table 1, 111 school districts have received at least one of these labels since the year

2000. The average length of time districts remain labeled is about three and a half years. Ninety

of these districts have received a fiscal caution label, while 40 and 35 have received fiscal watch and

fiscal emergency, respectively. As shown in Figure 1, these labeled districts are largely clustered

around the state’s urban centers, suggesting that regional economic changes may play a role in the

deteriorating finances in these districts. Figure 2 depicts the yearly number of labels received over

the time span of interest. The number of school districts in fiscal stress sharply increased starting

in 2002, coinciding with the introduction of the fiscal caution label for school districts. The number

of fiscal emergency labels has remained relatively constant since 2005, but there has been a sharp

reduction in the number of fiscal watch labels since 2007. Largely due to this decline in the number

of fiscal watch labels, the total number of labels has fallen from 54 to 40 in 2011.

After a district is notified of the label receipt, a press release is issued on the Auditor’s website4

that details why the district received the fiscal stress label. The press release also provides a link

to the full financial analysis report conducted by the Auditor. Current and prospective residents

are able to view this press release on the website, but it is often reprinted or reported in local

newspapers in the days following the issuance of the press release. The initial label receipt is likely

unanticipated given the lack of local media coverage prior to the publication of the press release.5

Similarly, a press release is posted to inform residents when a label is changed or removed. This

unanticipated change in the fiscal stress rating of the district serves as an exogenous shock of

information regarding the fiscal health of the district and is the main source of identification in a

difference-in-differences analysis of the effect of these labels.

The main goal of these labels is to identify districts that are in the midst of financial problems

and provide assistance and guidance to these districts. Under fiscal stress, districts are required to

develop and implement financial recovery plans that outline the changes that will be made to ensure

4http://www.auditor.state.oh.us/newscenter/press/releases/category/Fiscal Caution, Watch, and Emergency5Examining newspaper reports gives no indication that residents are aware that the Auditor is examining school

district financial records or that a fiscal stress determination was made prior to the publication of the press release.News reports covering districts that have been further downgraded to fiscal watch due to the failure to create arecovery plan speculate about whether the district will fall into fiscal emergency, but no official word is given untilthe press release is posted. The speculation is also likely due to the information these downgrades provide regardingthe ability of school officials to handle these financial problems. Given that the five-year forecast is publicly available,however, there is the potential that some individuals may be able to anticipate the receipt of these labels.

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balanced budgets in the future. These proposed changes include reductions in expenditures and/or

increases in revenue to offset the budget deficit. In Ohio, districts fund much of their operating

and capital expenditure through local property and income taxation. Renewal of existing taxation

and any new taxes the district wishes to levy are subject to voter approval. Of primary interest to

districts in fiscal stress are emergency operating levies, which generate a specific amount of property

tax revenue over a five-year period, regardless of how property values change over the life of the

tax. Current expense levies, also for general operating expenditure, specify a specific millage rate,

which is subject to rollbacks if property values increase over the life of the tax (i.e. a five percent

increase in property values decreases the tax rate by five percent). One caveat, however, is that

the tax rate cannot rise above the voted upon rate, meaning that if property values decrease the

district may not raise enough revenue from a current expense tax to offset the deficit. Therefore,

passage of emergency operating levies is likely most effective in eliminaing the fund deficit and help

districts avoid these fiscal stress labels and/or hasten the their removal.

3.2 Fiscal Caution

The process of receiving a fiscal caution label starts with the development of the yearly five-year

forecast. Each October, school districts must submit a five-year forecast to the Ohio Department of

Education. This forecast projects the expenditures and revenues of the district for the current fiscal

year and the next four years based on predicted changes in taxable property values, tax rates, state

aid, teacher and healthcare contracts, and other operating costs. After receiving these forecasts,

one of the fiscal consultants employed by the Ohio Department of Education reviews the forecasts

and flags districts that have potential deficits in one of the first three forecasted years.

If a forecast predicts a deficit (i.e. negative balance in the general fund) for the current fiscal

year or projects positive general fund balances that are less than 2% of projected revenue for that

year the fiscal consultant contacts the district treasurer to determine whether or not the projection

is accurate. If a deficit is verified during a financial analysis conducted by the Ohio Department

of Education, the district is placed into fiscal caution. Districts may avoid fiscal caution if they

immediately eliminate the deficit by reducing expenditures or through a tax advance from the

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county auditor to cover the amount of the deficit, but otherwise do not have sufficient time to levy

new taxation to cover the amount of the deficit. If the district accurately predicts a low positive

fund balance, no immediate action is taken, but the district can make use of the fiscal consultant

if it requires further assistance with maintaining its budget.

In addition to current year deficits or low fund balances, district forecasts are flagged if deficits

that exceed 2% of projected revenue are present in the second or third projected years. If a

district has a deficit in the second projected year, even after assuming passage of any renewal or

replacement levies, the district must submit a written proposal that addresses how the district

plans to eliminate the potential deficit or be placed into fiscal caution.6 One key restriction on

these recovery plans is that districts must adopt plans that would solve the deficit without the use

of additional operating property tax levies. In the third projected year, however, districts may

assume passage of new operating referenda when computing the projected fund balance. If deficits

still remain, after accounting for new millage, the district must develop ways to alleviate this deficit

before the next fiscal year.

After receiving the fiscal caution label, the district is given 60 days to submit an acceptable

recovery plan to the Department of Education. The Department of Education may also visit and

inspect the district. As part of its inspection, the Department of Education may choose to monitor

the district’s monthly financial situation. During the fiscal caution period, the Auditor of State

may also conduct a performance audit of the district.7 If the district fails to develop a suitable

recovery plan or if the district is not adhering to its recovery plan, the State Superintendent may

recommend to the Auditor of State that the district be placed into fiscal watch or fiscal emergency.

Once a district shows projected positive fund balances for the current fiscal year and the following

6Failure to submit this written proposal within 60 days of the financial consultant’s request for the proposal willresult in fiscal caution. After receiving the district’s proposed plan, the fiscal consultant accepts or rejects that plan.If the plan is accepted, the district undergoes the proposed changes and avoids the fiscal caution label. If the plan isrejected, the fiscal consultant explains to the district what would be required of an acceptable proposed plan. Thedistrict is then given 30 days to change the plan to include these recommendations, but if an acceptable plan is notdeveloped the district will fall into fiscal caution.

7This performance audit examines a districts financial practices and identifies ways in which the district could cutcosts and raise additional revenue. The recommendations from this performance audit can help guide the district’srecovery. The performance audit often identifies areas in which the district is spending above their peers andrecommends cuts or wage freezes in these areas. Recommendations include freezing step increases for teacher salaries,reducing staff, increasing employee health insurance contributions, implement fee-based extracurricular activities orreduce extracurricular expenditures, and eliminating unnecessary busing, among others.

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fiscal year, the Department of Education will remove the fiscal caution label. A district cannot

be removed from fiscal caution in the same fiscal year in which the fiscal caution declaration was

made. On average, it takes about three years for districts to successfully implement these recovery

plans under fiscal caution.

3.3 Fiscal Watch

Unlike fiscal caution which is declared and monitored by the Ohio Department of Education,

only the Auditor of State can declare fiscal watch. The Auditor may place a school district in

fiscal watch if the operating deficit exceeds 8% of the general fund revenue and the school district

has been unable to pass a levy providing sufficient revenue to eliminate the deficit. In addition to

selection based on the deficit in the general fund, districts lying outside the cutoff range may also

receive fiscal watch if it is determined that they fail to meet payroll, default on debt payments,

or have poor financial record-keeping. A district may also receive a fiscal watch label if a suitable

recovery plan is not developed while the district is under fiscal caution. After receiving fiscal watch,

the district has an additional 60 days to submit a recovery plan to the State Superintendent, who

decides whether the plan is adequate to achieve balanced budgets. While under fiscal watch some

districts may also restructure loans provided certain criteria are met.8 Just as in fiscal caution, the

Auditor of State may conduct a performance audit while the district is under fiscal watch. Districts

are removed from fiscal watch if they successfully achieve balanced budgets in projections for the

next two fiscal years. On average, successful recovery under fiscal watch takes about five years

to complete, which for some downgraded districts includes time spent in fiscal caution (around

two-thirds of a year).

3.4 Fiscal Emergency

A school district may receive fiscal emergency if the operating deficit exceeds 16% of the general

fund revenue and the school district has been unable to gain voter approval on a levy that would

8Districts may restructure loans if the deficit to revenue ratio exceeds 15%, voters have approved a levy thatprovides new operating revenue, the district has adopted a recovery plan that takes into account the restructuredloans and provides steps towards achieving a balanced budget.

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provide sufficient revenue to eliminate the deficit. As is the case with fiscal watch, districts lying

outside the cutoff range may also receive fiscal emergency if it is determined that they fail to

meet payroll, default on debt payments, or have poor financial record-keeping. A district may

also receive a fiscal emergency label if a suitable recovery plan is not developed while the district

is under fiscal caution and/or fiscal watch. On average, districts that are downgraded to fiscal

emergency spend just under a combined two years in fiscal caution and fiscal watch. Once in fiscal

emergency, successful recovery takes an average of three and half years to complete, but in some

cases has taken more than nine years to complete.

School districts in fiscal emergency are placed under the control of a financial planning and

supervision commission, which adopts a financial recovery plan for the school district.9 The com-

mission reviews and assumes responsibility for all projected revenues and expenditures and has

final approval on any property tax levies and debt issuances the school district wishes to propose

to voters. The commission also has the authority to make reductions in force in order to ensure

a balanced budget. This means that the commission has the power to reduce the number of em-

ployees irrespective of current employment contracts and collective bargaining agreements. These

reductions first eliminate administrative and non-teaching employees, giving preference to employ-

ees with continuing contracts and those with greater seniority. If the budget is still not balanced

following this first round of layoffs, the commission may layoff teachers in order to achieve a bal-

anced budget. The commission also may remove the district superintendent and/or treasurer if

they fail to comply with the commission’s recovery plan.

In addition to the takeover of its finances, the Auditor is required to conduct a performance

audit while a district is in fiscal emergency. Districts in fiscal emergency are also eligible to receive

two-year loans from the state. These loans, which are up to the amount of a two year advance on

9This commission consists of five voting members including the Director of the Office of Budget and Managementand the State Superintendent. The other three members of the commission include a business person appointed bythe Governor, a business person appointed by the mayor or county auditor, and a parent with child in the districtappointed by the State Superintendent. The business people must have at least five years experience in the publicor private sector in business management, public accounting, or another related field. The commission must includeat least one female member and one minority member if the minorities constitute at least twenty percent of districtenrollment. If the commission fails to come to a consensus on a financial recovery plan within 120 days, the commissionis dissolved and a fiscal arbitrator is put in charge of recovery. The fiscal arbitrator assumes all powers and duties ofthe commission, including creation and implementation of a financial recovery plan.

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the district’s state foundation aid, are intended to keep the district solvent during its recovery.10

Once the district meets the objectives of the recovery plan and eliminates the deficits that led to

fiscal emergency, the district is removed from the label. In rare cases where the district still has

outstanding debt at the time of release from fiscal emergency, the district will be placed into fiscal

watch until the debt is paid off.

3.5 Trends in Label Receipt

As observed in Table 2, a majority of the fiscal caution labels are received as a result of current

or potential deficits in the general fund. Nearly all of the fiscal watch and fiscal caution labels are

received because of the Auditor’s discretion or the failure of school officials to adopt a financial

recovery plan. Table 3 depicts the number of label transitions based on the initial label received.

A large majority of initial labels are fiscal caution labels, with only fifteen and thirteen districts

placed directly into fiscal watch and fiscal emergency, respectively11. Of the ninety districts to

initially receive a fiscal caution label, twenty-five were lowered to fiscal watch and six were lowered

to fiscal emergency. Of the twenty-five lowered to fiscal watch, fifteen were further downgraded to

fiscal emergency. Only one of the fifteen districts initially labeled in fiscal watch was downgraded

to fiscal emergency, while two districts initially labeled in fiscal emergency were upgraded to fiscal

watch after completing the recovery requirements but still holding outstanding debt.

Figure 3 shows a majority of these labels result from current and potential deficits in the

general fund, while label downgrades make up nearly a third of all labels received. The number of

downgrades, along with the number of fiscal watch and fiscal emergency labels, have been reduced

since 2007, suggesting that districts are beginning to take the responsibility of recovery seriously

and adopting recovery plans in a timely manner. As shown in Figure 4, not all districts falling

10These loans are paid out of the School District Solvency Assistance Fund. The Ohio General Assembly ap-propriates money to this fund, which consists of two accounts, the Shared Resource Account and the CatastrophicExpenditure Account. The Shared Resource Account provides districts with a two year, interest free advance on thedistrict’s state foundation payment in order to help the district to remain solvent while it implements its recoveryplan. Loans received through the Shared Resource Account must be repaid by the end of the second fiscal yearfollowing the receipt of the cash advance. The Catastrophic Expenditures Account is used to issue grants to districtsthat suffer a catastrophic event that depletes the district’s finances, but can also be used for solvency assistance if allof the Shared Resource Account funds have been allocated.

11Of these twenty-eight districts to receive an initial fiscal watch or fiscal emergency label, twenty-two were receivedprior to the introduction of the fiscal caution label in 2001

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below these cutoff points are chosen to receive a label and some districts above these cutoffs may

receive a label for a number of other poor financial practices. Looking at 2006, districts with ratios

below -0.16 received a label nearly 70 percent of the time, while districts with ratios between -0.02

and -0.16 received a label around 20 percent of the time. Surprisingly, districts with ratios just

above the -0.02 cutoff point received a label nearly 40 percent of the time, but this is likely due

to previously labeled districts improving the ratio while implementing the recovery plan. Districts

with positive general fund balances received labels less than 10 percent of the time.

4 Data

4.1 Data Sources

The fiscal stress data described in section 3 are augmented with data on school district finances,

tax rates, and local property sales. Data on school district general fund revenues and expenditures

were also obtained from the Ohio Auditor’s office. This data, from 2000-2010, provides a measure of

the deficit in the general fund, the primary measure used in the determination of these fiscal stress

declarations. Detailed expenditure and revenue information is also collected from the Common

Core of Data from 2000-2009. This information contains not only total revenues and expenditures

per year, but also disaggregated data of the specific components that make up these totals. This

allows me to analyze exactly which types of revenue and expenditure districts are targeting in their

recovery plans. Data on student test score proficiency levels, school report card grades, and district

accountability status are collected from the Ohio Department of Education.

Data on all tax rates levied by school districts is collected from the Ohio Department of Taxation

from 1997-2011. This data includes the specific purpose of each tax and the tax rate for the

given year. This tax data is supplemented with taxable values for class I (residential) and class II

(commercial, industrial) real property for each school district. Combining these two data sets allows

me to separately calculate the tax revenue collected for operating expenses and those calculated

for capital expenditure. I also collect data on school tax election outcomes was collected from

2003-2012 from the Ohio Secretary of State’s Office. These data include election outcomes for all

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property taxes for operating and capital expenditure, income taxes for operating expenditure, and

debt issuance for capital expenditure. The information collected includes the proposed tax rate,

the proposed dollar amount of the debt issuance, the number of yes and no votes, the duration of

the proposed tax, and the purpose of the tax.

Residential property sales data from 2000-2012 was obtained for 63 of the 88 counties in Ohio12.

The residential sales data were obtained from individual Ohio county auditors offices and include

the location of the property, the date of sale, the sale price, numerous characteristics of the home,

and the tax district13 in which the property resides. The data from these various sources is linked

to the sales data using the the tax district associated with each parcel. To ease the constraints in

collecting the housing transaction data, the sample is restricted to include only single-family homes

with sale prices that exceed $10,000. The analytic sample contains 1,108,557 parcel sales with all

the relevant parcel characteristics. For a full description of the data sets used in this analysis and

an explanation of the relevant variables see Appendix A.

4.2 Descriptive Statistics

Tables A.3 and A.4 in Appendix A provide means and standard deviations for the relevant

variables used in this study. The means are broken down by the various stages of fiscal stress.

Table A.3 provides means and standard deviation for the school district financial and demographic

characteristics. Districts that never receive a label are smaller, less likely to reside in urban areas,

have better school report card grades, and better financial situations than districts that are labeled.

In the pre-fiscal stress period, 38 percent of labeled districts have general fund deficits that are below

the fiscal caution cutoff (two percent of general fund revenue) compared with only five percent for

districts that never receive a label. Labeled districts also have average expenditures above average

revenues, leading to the large deficits in these districts. Also in Panel A, means for the period prior

to receiving the label and the fiscal stress period are compared for the 81 labeled districts that are

12As shown in Table A.2 in the Appendix, the 63 counties included in the analytic sample are quite representativeof the entire state. The districts in the analytic sample have slightly larger enrollments and spend slightly more perstudent, but are nearly identical on all the other covariates of interest.

13A tax district corresponds to a unique county-township-city-school combination. Within a school district theremay be a number of different tax districts. This means that the taxes faced by residents within a given school districtmay vary depending on which tax district the resident resides.

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observed in both time periods. The financial health of labeled districts appears to improve following

receipt of the label, evidence that the recovery plans associated with these labels are positively

impacting the financial health in these districts. Following label receipt district expenditures per

pupil fall by just over $1,000 on average. Nearly all of this reduction in costs can be attributed to

the reduction in capital outlay per pupil, which decrease by nearly $1,250 on average. Instructional

costs do not change substantially following label receipt. In addition, there is some evidence that

local tax revenue is increasing following label receipt. Local property tax revenue increases by

nearly $235 per pupil and income tax revenue increases by about $120 per pupil following label

receipt.

Panel B compares the means across the 71 labeled districts during the fiscal stress period and

the period following the removal of the label. Following the removal of the label, labeled districts

exhibit financial characteristics that resemble that of districts that never received a label. Post-

fiscal stress fund balances, total expenditures, and total revenues are nearly identical to those of

districts that never receive a label. This is further evidence that these labels are achieving the

intended goal of creating more financially viable districts. Interestingly, however, capital outlay for

labeled districts continues to decrease following the removal of the label. Labeled districts spend

nearly $900 less per pupil on capital outlay during the post-fiscal stress time period than districts

that never receive a label.

Examining Panel A of Table A.4, homes sold in districts that never receive a label sell for

around $7,000 more than homes sold in the pre-fiscal stress period in labeled districts. The homes

sold in districts that never receive a label also tend to be slightly larger. Also in Panel A, among

the 79 labeled districts observed in both the period prior to receiving the label and during the

labeled period, the sale price falls by nearly $11,000 following the receipt of the label. Given that

the average characteristics of the homes sold are nearly identical between the pre-fiscal stress and

fiscal stress periods, much of this reduction in sale prices is likely not attributable to changes in

the composition of homes being sold.14 Panel B compares the means across the 67 labeled districts

14The average age of the homes sold during the fiscal stress period is nearly 6 years older than the average age ofhomes sold during the pre-fiscal stress period. This is largely attributable to the fiscal stress period occurring laterin time than the pre-fiscal stress period. it is not all that surprising to see the average age of sold homes rise. Giventhat the housing stock is relatively fixed in the short-run, housing within a district is likely aging at very similar

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during the fiscal stress period and the period following the removal of the label. Following the

removal of the label, the sale price falls by nearly $17,000, suggesting that the changes being made

in these districts or the stigma attached to these labels has long-lasting negative effects on housing

prices. In many districts, however, a majority of the post-fiscal stress period occurs during the

Great Recession, so some aspects of the post-housing bubble may be causing these much lower sale

prices during the post-fiscal stress period.

5 Methodology

5.1 Effect of Label Receipt on School District Finances

As discussed earlier, school districts in fiscal stress are required to develop and implement

financial recovery plans that lead to balanced budgets in the future. In order to achieve this, districts

must either reduce expenditures and/or increase local tax revenue. To analyze the impact of these

recovery plans on school district expenditures and revenues, I use the following two approaches.

First, I analyze whether there are differential effects of the these recovery plans across the different

severity levels using the following equation:

ln(y)sy = α+ β1FCsy + β2FW sy + β3FEsy + γXsy + λs+ θy + εsy (1)

where ln(y)sy is the natural log of one of a set of per-pupil expenditure and revenue variables for

school district s in year y; FCsy, FW sy, and FEsy are indicators for whether school district s is

under fiscal caution, fiscal watch, or fiscal emergency in year y, respectively; Xsy is a vector of

time-varying district characteristics; λs is a school district fixed effect; θy is a year fixed effect; and

εsy is an idiosyncratic error.

The most substantial recovery efforts are expected to occur during fiscal caution and fiscal

emergency, since a majority of fiscal watch districts fail to develop recovery plans. Although some

changes in district finances are expected to occur during fiscal caution, with proactive districts

trying to get these labels removed as quickly as possible, the most noticeable changes are likely

rates. Thus, this increase in age is not likely attributable as a composition effect in the types of housing sold.

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to occur under fiscal emergency. This is largely due to recovery under fiscal emergency being

undertaken by the state commission, which has greater authority than school districts to make

reductions in staff and salary schedules.

I also use a flexible event study framework to examine how soon after label receipt these re-

covery plans take effect and for how long the effects of these recovery plans persist. This flexible

specification also allows for the realistic possibility that these recovery plans may be implemented

in stages and the effect of these recovery plans may grow over time. To perform this analysis, I

estimate the following equation:

ln(y)sy = α+−2∑

k=−6

βkFSsyk +9∑

k=0

βkFSsyk + γXsy + λs+ θy + εsy (2)

where FSsyk is an indicator for k years before or after label receipt, with k = 0 signifying the

year of label receipt. Each of the βk coefficients are relative to the omitted year, one year prior to

label receipt. There is some potential that β−2 may be non-zero, reflecting the changes districts

are making in the year before label receipt in order to avoid the label after being flagged in the

five-year forecast by the ODE. Much of the effect, however, is not likely to occur until after the

label is implemented (k ≥ 0). It is expected that these effects may grow over the first few years

after label receipt, as districts implement the recovery plans. These effects may somewhat fade

out later, as districts transition out of fiscal stress and can spend more freely again. Although, if

these recovery plans are meeting the goal of future balanced budgets, these changes are expected

to persist over many years.

5.2 Effect of Label Receipt on Single-Family Home Sales

To better understand how these changes in revenue and/or expenditure may be impacting the

housing market, consider a stylized hedonic model of the effect of these labels on house prices:

ln(P )isjt = α+ βFSst + γZisjt + ωXsy + λjy + θt + εisjt (3)

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where ln(P )isjt represents the natural log of the sale price of parcel i in school district s and

municipality/township15 j at time t; FSst is an indicator for whether school district s is in fiscal

stress at time t; Zisjt is a vector of observable housing and parcel characteristics16; Xsy is a

vector of observable district-level financial and demographic characteristics17; λjt is a vector of

municipality/township-by-year fixed effects influences; θt is a set of time (month-by-year) fixed

effects; and εijt is an idiosyncratic error.

If these recovery plans decrease expenditure and/or increase taxation, the attractiveness of the

tax-services bundle these districts provide is reduced and individuals may capitalize these future

reductions into lower current housing valuations. If districts are spending inefficiently, however,

these recovery plans may reduce expenditure without increasing taxation or negatively impacting

the academic quality of the district. In these cases, it is likely that residents would respond positively

to these recovery requirements, especially if the reduction in inefficient spending frees up additional

funds for districts to spend or to reduce taxes.

Given that implementation of these recovery plans is likely to vary across label severity, I also

analyze whether there are differential impacts on housing prices across the severity levels:

ln(P )isjt = α+ β1FCst + β2FW st + β3FEst + γZisjt + ωXst + λjy + θm + εisjt (4)

where FCst, FW st, and FEst are indicators for whether school district s is under fiscal caution,

fiscal watch, or fiscal emergency in year y, respectively. Housing prices are most likely to change

under fiscal caution and fiscal emergency, given that districts are expected to be making a majority

of the financial changes during these periods. Given that changes made to eliminate deficits may

15Parcels that lie within incorporated areas are linked to a given city or village j. Parcels in unincorporated areasare linked to a given township j

16In the empirical model, this vector contains variables for the number of rooms, number of bedrooms, numberof bathrooms, indicators for the amount of acreage, and the square footage of the home’s living area. Intervals ofacreage are used instead of total acreage due to the fact that actual acreage is missing for a large percentage of thesample. In sensitivity checks, total acreage was used in place of these intervals and the general results remained thesame, although the power was reduced greatly due to the reduction in the sample size.

17In the empirical model, this vector contains district financial characteristics including the general fund balanceto revenue ratio, which is one of the primary selection variables used by the Auditor when deciding to apply a fiscalstress label, and the various eligibility cutoff points discussed earlier. District demographics, such as, percent ofstudents eligible for free/reduced lunch, indicator for whether the district is in an urban area, and median housingincome are also included.

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be different than changes made as a result of debt defaults or missed payroll, some specifications

of equation (4) include an indicator, ADst, for whether a label was received due to the Auditor’s

discretion. If the changes differ between labels received due to deficits and those due to the Auditor’s

discretion, potential homebuyers may react differentially to these Auditor’s discretion labels.

Finally, I also use the flexible event study framework to see how quickly housing prices are

responding to these changes and to allow for changes in the effect over time following label receipt:

ln(P )isjt = α+−2∑

k=−6

βkFSstk +9∑

k=0

βkFSstk + γZisjt + ωXst + λjy + θm + εisjt (5)

where FSsyk is an indicator for k years before or after label receipt, with k = 0 signifying the year

of label receipt. Each of the βk coefficients are relative to the omitted year, one year prior to label

receipt. For k ≥ 1, I also include interactions with an indicator for whether the district is no longer

labeled, to account for a differential response to districts no longer undergoing recovery. With these

interactions, the βk’s capture the effect of a district remaining fiscally stressed k years after initial

label receipt.

6 Results

6.1 Effect of Labels on School District Behavior

Districts are reducing expenditures and increasing local operating revenue as a result of these

fiscal stress labels. As observed in Table 4, reductions in expenditure occur during both fiscal

caution and fiscal emergency, with no significant changes occurring during fiscal watch. Total ex-

penditure per-pupil is reduced by 7.4 percent in fiscal caution and by 5.8 percent in fiscal emergency.

Districts appear to be reducing both capital and operating expenditure, with the capital exhibiting

the greatest reductions. Total capital outlay per pupil is reduced by 52 percent and per pupil

expenditure on new construction is reduced by 54 percent under fiscal caution. New construction

is even more constrained under fiscal emergency, with a reduction in per-pupil expenditure of 80

percent. Districts may be eliminating capital construction projects at higher rates in order to avoid

large operating cuts that would negatively impact students. Although new or renovated schools

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may provide some positive benefits to students, eliminating them is likely to have less impact on

student achievement than reductions in the number or quality of teachers. Despite the large re-

ductions in capital expenditure, total elementary-secondary operating expenditure per-pupil falls

by 4.1 percent in fiscal caution and 4.2 percent in fiscal emergency. Per-pupil expenditures on

student instruction fall by 3.5 percent in fiscal caution and 4.3 percent in fiscal emergency. These

operating expenditure cuts appear to be driven by districts heeding the advice of the Auditor in

regards to reductions in salaries and benefits.18 Total salaries per pupil fall by between four and

six percent and employee benefits per pupil fall by 2.5 percent. Salaries for instructional staff fall

by 3.7 percent under fiscal caution and 4.4 percent under fiscal emergency.

As observed in Table 6, these reductions in per-pupil expenditures are sudden and long-lasting.

Some of these reductions occur in the year prior to label receipt, as districts flagged by the ODE for

deficits in the five-year forecast attempt to avoid label receipt by cutting costs. Total expenditures

per-pupil fall by five percent in the year before label receipt. Total capital outlay per-pupil is

reduced by 28.4 percent and new construction is reduced by nearly sixty percent in the year before

the label is received. These results, along with the smaller, one and two percent, reductions in

salaries and operating expenditure, suggest that districts are attempting to avoid these labels

primarily through cuts to capital expenditure.

Even after the reductions made in the year prior, labeled districts continue to reduce expendi-

tures in the years following label receipt. Total expenditures per-pupil fall by eight to ten percent

in the years following label receipt. There is a significant reduction in total expenditures per-pupil

continues to persist seven years after receiving the label, suggesting that these reductions last many

years after the implementation of these recovery plans. New construction expenditure per-pupil

falls by 60 percent in the year prior to label receipt and by an additional 88 percent in the year of

label receipt, but this effect fades out a year or two after receipt. This large reduction in capital

expenditure in the first few years of fiscal stress suggests that capital expenditure is relatively easier

to eliminate quickly and/or districts are eliminating large capital projects in an attempt to spare

operating expenditure. As cuts in capital fade out, districts further reduce salaries and other in-

18Performance audits conducted by the auditor often find that salaries and benefits in fiscal stress districts areabove their peer districts and suggest that districts freeze wages and/or reduce health benefits.

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structional expenditures. These reductions in salaries and instructional expenditures persist much

longer than reductions in capital, with reductions of four and five percent lasting between three

and six years after the initial label receipt.

In addition to reductions in expenditures as a result of these recovery plans, districts also make

some adjustments to local revenue. Table 5 shows that all of the increases in revenue occur during

fiscal emergency, although there is some reduction in property tax revenue for capital expenditure

during fiscal emergency. Total local revenue falls by 2.5 percent during fiscal caution, primarily due

to a nice percent reduction in property tax revenue for capital expenditure. Total local revenue

increases by 6.6 percent during fiscal emergency, with an 8.6 percent increase in property tax

revenue for operating expenses. Given that fiscal emergency districts are eligible for a two-year

advance on their state aid, districts in fiscal emergency may need to raise additional revenue to pay

back these advances at the end of the two years. Additionally, given the pressure for districts in

fiscal caution or fiscal watch to recovery quickly in order to avoid downgrades into fiscal emergency,

there may not be enough time to wait for voters to a new tax levy, choosing instead to reduce

expenditures for immediate cost-saving. Districts in fiscal emergency also have larger deficits on

average and may need additional revenue in order to avoid making expenditure cuts that impact

the districts ability to meet the state’s adequacy standards.

As evidenced in Table 7, districts are increasing local property tax revenue and changing their

operating and capital tax mix immediately following label receipt. Unlike expenditures, there

are no significant changes to revenue in the year prior to label receipt. This is expected, given

that districts do not have adequate time to raise new taxes after being flagged by the ODE for

deficits in the five-year forecast. Local property tax revenue per pupil steadily increases following

label receipt, from a 2.8 percent increase in the year of receipt to a 9.6 percent increase two years

after receipt. This increase is driven completely by the increase in property taxes for operating

expenses, as revenue for capital expenses substantially falls after label receipt. Operating property

tax revenue rises by 3.6 percent in the year of label receipt and continues to grow to between a

ten and eleven percent increase. This increase begins to fade out after six years, but I still observe

around a six percent increase as far out as seven years after the district received the label. Property

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tax revenue for capital expenditure falls by between seven and twenty percent after label receipt,

with about a sixteen percent reduction persisting more than nine years after receipt of the label.

This large, persistent drop in revenue for capital expenditure is consistent with the reductions in

capital outlay as a result of these recovery plans.

6.2 Effect of Labels on Housing Sale Prices

The expenditure and revenue results find that the recovery plans associated with these labels are

leading districts to reduce expenditures, primarily through reductions in capital outlay and salaries.

In addition, to these reductions in expenditures, local tax revenues are increasing. So, how is the

housing market responding to these changes? The reductions in expenditure and increases in taxes

would suggest that the attractiveness of the tax-services bundle these districts offer is reduced. In

this case, residents may capitalize this reduction in the bundle’s attractiveness into lower current

housing valuations. If districts are reducing inefficiently high salaries and eliminating unnecessary

construction and renovation projects, then residents may positively value these cuts as they may

free up additional funds to spend on educational inputs that will improve the academic quality of

the district.

As shown in column 1 of Table 8, I find a 3.8 percent drop in sale prices following label receipt,

suggesting potential residents are capitalizing these cuts and increases in revenue into lower housing

valuations. This effect differs across the severity levels, with the largest effects occurring during

fiscal emergency. Following the receipt of the fiscal caution label, the sale price falls by between four

and 4.5 percent. The sale price falls by between ten and twelve percent following the receipt of fiscal

emergency. There are no significant changes in sale prices during fiscal watch, an unsurprising result

given the lack of revenue or expenditure changes that occur under fiscal watch. This large negative

effect for fiscal emergency is likely attributable to the increase in taxation that is observed during

this period, in addition to continued expenditure cuts. The state takeover of the school district

during fiscal emergency may also be a negative stigma to potential homebuyers, as individuals may

not be fully aware of what this state intervention entails.

Given that these labels are applied at the district level, a parcel level analysis may not be the

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most appropriate to identify these effects. Therefore, I calculate the district-by-day means for all

of the variables in the model and estimate the model using this aggregated data. Performing the

analysis at the district level finds even stronger results than the parcel level analysis, suggesting

that some districts with large numbers of parcel sales were influencing the results towards finding

smaller effects. From Table 9, this aggregate analysis finds a 6.4 percent decrease in housing prices

following fiscal stress receipt. I again find the strongest effects for the fiscal emergency label with

around an 18 percent reduction in sale prices following label receipt. I find around a five percent

decrease in sale prices following receipt of fiscal caution, and a similar sized effect for fiscal watch

when a control for the Auditor’s discretion is included.

Table 10 presents results of the year-by-year effect of label receipt on house prices at both the

parcel level and district level. This flexible specification also allows for a separate effect to be

estimated if the label has been removed after a given number of years. The parcel level analysis

finds little effect of these labels on housing prices, but finds strong positive effects on housing

prices for districts that have been removed from these labels. Housing prices in districts that are

removed rise by between seven and twelve percent, suggesting that homebuyers are responding

positively to successful recoveries. Homebuyers may be reacting to the likelihood that further cuts

in expenditure and increases in revenue will taper off as recovery has been completed or may be

positively valuing the better financial health and stability in the district. The district level analysis

finds that housing prices fall by between five and fifteen percent in districts that remain fiscally

stressed k years after label receipt, with the magnitude of the effect increasing as k increases. This

suggests that homebuyers are severely lowering their valuations for housing in districts that fail to

take recovery seriously, those most likely to end up in fiscal emergency. After the removal of the

label, I again find that housing prices recovery to near pre-fiscal stress levels.

7 Conclusion

This paper provides the first major analysis of the effects of fiscal stress labels on school district

finances and housing prices. I examine fiscal stress labels received by school districts in Ohio

from 2000-2012. I find that home prices fall by around four percent following the receipt of these

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labels, an effect size that is comparable to a one standard deviation reduction in test scores. These

effects are largest for fiscal emergency, during which state-developed recovery plans cut spending

and increase tax revenue. Housing prices are less responsive to district-led recoveries, which focus

more on expenditure reduction, suggesting that housing prices respond more to tax increases than

expenditure reductions. It also suggests that some of the expenditure cuts are targeting unnecessary

or inefficient spending and are therefore not greatly reducing the services these districts provide.

The recovery plans associated with these labels are effective in changing district financial be-

havior, suggesting that state intervention is a credible threat for these districts. The changes to

revenues and expenditures are long-lasting, suggesting that these districts are continuing to balance

budgets even after the recovery has concluded. This increased financial viability is also evidenced

by the reduction in the number of districts in fiscal stress over the past few years, further suggesting

that districts are taking these recoveries seriously. This increased financial viability is highly valued

by residents, leading to housing prices following successful recovery that are nearly unchanged from

their pre-fiscal stress levels.

The Ohio fiscal stress model has been quite successful at eliminating these deficits, with little

long-term impact on housing prices. Future work should examine labels in other states and/or labels

received by local governments. Given different institutional structures, are labels in other states

or settings as effective at eliminating deficits as the Ohio school district model? School district

responses may be different in states where revenue for operating expenditure is not collected at

the local level. In these instances, we may see more severe reductions to expenditures, including

instructional expenditures. In addition to school districts, an analysis of the effects of labels on

local governments would be particularly interesting and extremely policy relevant, given the rise

in the number of cities declaring bankruptcy. Analyzing these labels in a variety of settings, will

allow policymakers to determine which systems work best given certain institutional settings and

help states adopt systems that best fit with their goals.

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Table 1: Number Jurisdictions in Fiscal Stress since 2000, by Jurisdiction Type

Total School Districts Municipalities Townships

Total Number 167 111 53 3Number in Fiscal Caution 94 90 3 1Number in Fiscal Watch 59 40 19 0Number in Fiscal Emergency 75 35 38 2

Note: Scioto County is the only county that has been classified in fiscal stress

Table 2: Number of Fiscal Stress Labels from 2000-2010, by Reason Label Received

Current Potential Auditor’s DowngradedDeficits Deficits Discretion w/o Plan

Total 39 59 22 40Fiscal Caution 32 59 5 -Fiscal Watch 2 - 11 17Fiscal Emergency 5 - 6 23

Table 3: Number of Label Transitions, by Initial and Secondary Label Type

Second Label Third Label

Total Fiscal Watch Fiscal Emergency Fiscal Emergency

Initial LabelFiscal Caution 90 25 6 15Fiscal Watch 15 - 1 -Fiscal Emergency 13 2 - -

27

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Figure 1: Geographic Distribution of Labeled School Districts Across Ohio

Figure 2: Yearly Number of Labels, by Label Severity

28

Page 29: The E ect of School District Financial Health Information ...haider/LaborDay/thompson.pdf · e ects on housing prices, but the e ect of this information only lasts for two or three

Figure 3: Yearly Number of Labels, by Reason Label Received

Figure 4: Probability of Receiving a Label in 2006, by Gen Fund Balance to Revenue Ratio

29

Page 30: The E ect of School District Financial Health Information ...haider/LaborDay/thompson.pdf · e ects on housing prices, but the e ect of this information only lasts for two or three

Table 4: Effect of Fiscal Stress Receipt on Expenditures per pupil, by severity level

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Total El-Sec Instruct Capital New Total Instruct Employee InstructExpend Expend Expend Outlay Construct Salaries Salaries Benefits Benefits

Fiscal Caution -0.074*** -0.041*** -0.035*** -0.524*** -0.544** -0.040*** -0.037*** -0.025** -0.023*(0.026) (0.009) (0.010) (0.160) (0.264) (0.009) (0.009) (0.012) (0.013)

Fiscal Watch -0.023 0.004 -0.005 -0.179 -0.600 -0.002 -0.005 0.003 -0.005(0.029) (0.015) (0.016) (0.252) (0.442) (0.015) (0.015) (0.021) (0.020)

Fiscal Emergency -0.058* -0.042*** -0.043*** -0.258 -0.804* -0.057*** -0.044*** 0.002 0.008(0.035) (0.012) (0.015) (0.270) (0.455) (0.013) (0.013) (0.022) (0.023)

Constant 8.97*** 8.79*** 8.27*** 6.33*** 5.35*** 8.34*** 7.91*** 7.10*** 6.63***(0.009) (0.002) (0.002) (0.046) (0.080) (0.002) (0.002) (0.004) (0.004)

Observations 5397 5397 5397 5397 4988 5397 5397 5397 5397R-squared 0.50 0.92 0.90 0.31 0.35 0.92 0.91 0.90 0.84

Dependent variables are natural logs of the listed per-pupil variables. Each specification contains controls for schooldistrict time varying demographics, school district fixed effects, and year fixed effects. Robust standard errors,clustered at the school district level given in parentheses.*** p<0.01, ** p<0.05, * p<0.1

Table 5: Effect of Fiscal Stress Receipt on Revenues per pupil, by severity level

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Total Federal State General Local Local Prop Oper Prop Cap Prop Local IncRevenue Revenue Revenue State Aid Revenue Tax Rev Tax Rev Tax Rev Tax Rev

Fiscal Caution -0.015 -0.047** -0.013 -0.017 -0.025* 0.016 0.023 -0.091** -0.264(0.020) (0.023) (0.031) (0.012) (0.015) (0.017) (0.017) (0.043) (0.234)

Fiscal Watch 0.013 -0.035 0.008 0.025 0.011 0.017 0.011 0.070 0.056(0.025) (0.036) (0.040) (0.024) (0.017) (0.020) (0.027) (0.104) (0.269)

Fiscal Emergency 0.036 0.037 -0.008 0.004 0.066*** 0.073** 0.086*** -0.001 0.212(0.037) (0.032) (0.051) (0.038) (0.023) (0.029) (0.029) (0.054) (0.874)

Constant 8.99*** 5.67*** 8.14*** 7.95*** 8.23*** 7.75*** 7.62*** 5.55*** 6.26***(0.008) (0.011) (0.012) (0.005) (0.005) (0.005) (0.005) (0.023) (0.078)

Observations 5397 5396 5397 5397 5397 5941 5941 5432 1376R-squared 0.62 0.90 0.75 0.91 0.93 0.97 0.97 0.80 0.83

Dependent variables are natural logs of the listed per-pupil variables. Each specification contains controls for schooldistrict time varying demographics, school district fixed effects, and year fixed effects. Robust standard errors,clustered at the school district level given in parentheses.*** p<0.01, ** p<0.05, * p<0.1

30

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Tab

le6:

Even

tS

tud

yR

esu

lts

-S

chool

Dis

tric

tE

xp

end

itu

res

per

Pu

pil

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

Tota

lE

l-Sec

Inst

ruct

Capit

al

New

Tota

lIn

stru

ctE

mplo

yee

Inst

ruct

Exp

end

Exp

end

Exp

end

Outl

ayC

onst

ruct

Sala

ries

Sala

ries

Ben

efits

Ben

efits

Six

+Y

ears

Bef

ore

0.0

43

0.0

06

0.0

11

0.2

00

0.2

50

0.0

08

0.0

14

-0.0

16

-0.0

14

(0.0

44)

(0.0

16)

(0.0

15)

(0.2

61)

(0.4

50)

(0.0

16)

(0.0

16)

(0.0

21)

(0.0

19)

Fiv

eY

ears

Bef

ore

-0.0

12

-0.0

02

0.0

05

-0.0

92

-0.2

05

-0.0

03

0.0

01

-0.0

13

-0.0

11

(0.0

27)

(0.0

08)

(0.0

09)

(0.1

71)

(0.3

11)

(0.0

07)

(0.0

07)

(0.0

12)

(0.0

14)

Four

Yea

rsB

efore

0.0

11

0.0

02

-0.0

05

0.1

10

0.1

19

-0.0

04

-0.0

06

-0.0

21**

-0.0

30**

(0.0

242)

(0.0

06)

(0.0

07)

(0.1

33)

(0.2

29)

(0.0

07)

(0.0

07)

(0.0

10)

(0.0

12)

Thre

eY

ears

Bef

ore

0.0

48**

0.0

24***

0.0

21***

0.2

08

0.2

97

0.0

16***

0.0

13**

0.0

16*

0.0

10

(0.0

23)

(0.0

06)

(0.0

06)

(0.1

26)

(0.2

17)

(0.0

06)

(0.0

06)

(0.0

09)

(0.0

11)

Tw

oY

ears

Bef

ore

0.0

56***

0.0

24***

0.0

21***

0.2

84**

0.5

97***

0.0

15***

0.0

13**

0.0

13

0.0

11

(0.0

19)

(0.0

06)

(0.0

07)

(0.1

15)

(0.1

98)

(0.0

05)

(0.0

05)

(0.0

09)

(0.0

11)

Yea

rof

Lab

elR

ecei

pt

-0.0

80***

-0.0

21**

-0.0

17**

-0.6

57***

-0.8

76***

-0.0

30***

-0.0

24***

0.0

08

0.0

12

(0.0

21)

(0.0

08)

(0.0

09)

(0.1

44)

(0.2

63)

(0.0

08)

(0.0

08)

(0.0

13)

(0.0

15)

Yea

rA

fter

-0.0

83***

-0.0

46***

-0.0

50***

-0.4

64**

-0.6

62*

-0.0

58***

-0.0

56***

-0.0

40***

-0.0

50***

(0.0

30)

(0.0

09)

(0.0

12)

(0.2

02)

(0.3

57)

(0.0

10)

(0.0

10)

(0.0

14)

(0.0

16)

Tw

oY

ears

Aft

er-0

.061*

-0.0

27

-0.0

34*

-0.3

04

-0.3

52

-0.0

45**

-0.0

47**

-0.0

28

-0.0

33

(0.0

33)

(0.0

19)

(0.0

20)

(0.2

17)

(0.3

74)

(0.0

19)

(0.0

19)

(0.0

23)

(0.0

24)

Thre

eY

ears

Aft

er-0

.054*

-0.0

41***

-0.0

49***

-0.1

16

-0.1

17

-0.0

54***

-0.0

57***

-0.0

37**

-0.0

44***

(0.0

33)

(0.0

10)

(0.0

11)

(0.2

27)

(0.4

14)

(0.0

11)

(0.0

11)

(0.0

16)

(0.0

17)

Four

Yea

rsA

fter

-0.0

61*

-0.0

22

-0.0

32*

-0.3

72

-0.6

20

-0.0

41**

-0.0

43**

-0.0

32

-0.0

39

(0.0

34)

(0.0

18)

(0.0

19)

(0.2

31)

(0.4

28)

(0.0

19)

(0.0

19)

(0.0

24)

(0.0

24)

Fiv

eY

ears

Aft

er-0

.088**

-0.0

33*

-0.0

40**

-0.3

59

-0.5

23

-0.0

50***

-0.0

48***

-0.0

37

-0.0

33

(0.0

39)

(0.0

18)

(0.0

20)

(0.2

45)

(0.4

83)

(0.0

18)

(0.0

18)

(0.0

24)

(0.0

26)

Six

Yea

rsA

fter

-0.1

09***

-0.0

30

-0.0

41*

-0.6

06**

-0.2

96

-0.0

45**

-0.0

49**

-0.0

27

-0.0

33

(0.0

41)

(0.0

19)

(0.0

22)

(0.2

35)

(0.4

19)

(0.0

21)

(0.0

23)

(0.0

27)

(0.0

28)

Sev

enY

ears

Aft

er-0

.104**

-0.0

32

-0.0

38*

-0.6

87**

-0.8

04

-0.0

34

-0.0

37

-0.0

34

-0.0

27

(0.0

43)

(0.0

20)

(0.0

22)

(0.2

87)

(0.5

02)

(0.0

22)

(0.0

24)

(0.0

29)

(0.0

31)

Eig

ht

Yea

rsA

fter

-0.0

65

-0.0

17

-0.0

34

-0.3

48

-0.1

24

-0.0

34

-0.0

46

-0.0

48

-0.0

52

(0.0

47)

(0.0

24)

(0.0

29)

(0.3

09)

(0.5

93)

(0.0

25)

(0.0

29)

(0.0

37)

(0.0

39)

Nin

eY

ears

Aft

er-0

.009

-0.0

14

-0.0

11

-0.1

82

0.0

94

-0.0

36

-0.0

39

-0.0

07

-0.0

09

(0.0

61)

(0.0

24)

(0.0

28)

(0.4

01)

(0.7

09)

(0.0

27)

(0.0

29)

(0.0

33)

(0.0

35)

Const

ant

9.1

5***

8.9

7***

8.4

4***

6.2

5***

5.2

7***

8.4

7***

8.0

6***

7.3

6***

6.8

8***

(0.0

09)

(0.0

02)

(0.0

03)

(0.0

51)

(0.0

87)

(0.0

03)

(0.0

03)

(0.0

04)

(0.0

06)

Obse

rvati

ons

5425

5425

5425

5425

5014

5425

5425

5425

5425

R-s

quare

d0.5

10.9

30.9

10.3

30.3

70.9

30.9

20.9

10.8

5

Each

spec

ifica

tion

conta

ins

contr

ols

for

school

dis

tric

tti

me

vary

ing

dem

ogra

phic

s,sc

hool

dis

tric

tfixed

effec

ts,

and

yea

rfixed

effec

ts.

Robust

standard

erro

rs,

clust

ered

at

the

school

dis

tric

tle

vel

giv

enin

pare

nth

eses

.***

p<

0.0

1,

**

p<

0.0

5,

*p<

0.1

31

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Tab

le7:

Even

tS

tud

yR

esu

lts

-S

chool

Dis

tric

tR

even

ues

per

Pup

il

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

Tota

lF

eder

al

Sta

teG

ener

al

Loca

lL

oca

lP

rop

Op

erP

rop

Cap

Pro

pL

oca

lIn

cR

even

ue

Rev

enue

Rev

enue

Sta

teA

idR

even

ue

Tax

Rev

Tax

Rev

Tax

Rev

Tax

Rev

Six

+Y

ears

Bef

ore

0.0

31

0.0

29

0.0

74*

0.0

58**

0.0

07

0.0

11

0.0

16

-0.0

44

-0.4

27

(0.0

30)

(0.0

32)

(0.0

40)

(0.0

23)

(0.0

22)

(0.0

27)

(0.0

27)

(0.0

90)

(0.4

54)

Fiv

eY

ears

Bef

ore

0.0

03

0.0

21

-0.0

01

-0.0

03

0.0

10

-0.0

02

0.0

01

-0.0

31

0.1

26

(0.0

22)

(0.0

26)

(0.0

28)

(0.0

16)

(0.0

20)

(0.0

16)

(0.0

17)

(0.0

66)

(0.6

11)

Four

Yea

rsB

efore

0.0

09

0.0

06

0.0

22

-0.0

02

0.0

00

0.0

04

0.0

04

0.0

26

0.2

79*

(0.0

17)

(0.0

24)

(0.0

24)

(0.0

10)

(0.0

12)

(0.0

13)

(0.0

12)

(0.0

45)

(0.1

65)

Thre

eY

ears

Bef

ore

0.0

43**

0.0

29*

0.0

54**

0.0

17*

0.0

26**

0.0

25*

0.0

12

0.0

67*

0.0

22

(0.0

19)

(0.0

17)

(0.0

26)

(0.0

09)

(0.0

13)

(0.0

13)

(0.0

13)

(0.0

35)

(0.3

60)

Tw

oY

ears

Bef

ore

0.0

18

0.0

18

0.0

13

0.0

02

0.0

173

0.0

02

-0.0

07

-0.0

17

0.2

89

(0.0

18)

(0.0

18)

(0.0

24)

(0.0

09)

(0.0

12)

(0.0

12)

(0.0

13)

(0.0

35)

(0.3

15)

Yea

rof

Lab

elR

ecei

pt

0.0

02

-0.0

21

0.0

03

0.0

01

-0.0

04

0.0

28*

0.0

36**

-0.0

75**

-0.1

55

(0.0

17)

(0.0

24)

(0.0

24)

(0.0

09)

(0.0

14)

(0.0

16)

(0.0

16)

(0.0

31)

(0.3

35)

Yea

rA

fter

0.0

30

-0.0

08

0.0

07

0.0

03

0.0

36**

0.0

49**

0.0

59***

-0.0

99**

0.3

25

(0.0

21)

(0.0

30)

(0.0

29)

(0.0

14)

(0.0

17)

(0.0

20)

(0.0

19)

(0.0

41)

(0.2

90)

Tw

oY

ears

Aft

er0.0

60**

-0.0

02

0.0

19

0.0

02

0.0

75***

0.0

96***

0.1

10***

-0.0

54

0.3

42

(0.0

27)

(0.0

35)

(0.0

41)

(0.0

32)

(0.0

23)

(0.0

28)

(0.0

28)

(0.0

59)

(0.2

55)

Thre

eY

ears

Aft

er0.0

63**

-0.0

30

0.0

27

-0.0

11

0.0

74***

0.0

80***

0.1

01***

-0.1

09*

0.1

90

(0.0

29)

(0.0

39)

(0.0

46)

(0.0

22)

(0.0

19)

(0.0

23)

(0.0

23)

(0.0

63)

(0.3

05)

Four

Yea

rsA

fter

0.0

43

0.0

09

-0.0

22

-0.0

04

0.0

90***

0.0

83***

0.1

05***

-0.1

34**

0.3

25

(0.0

31)

(0.0

39)

(0.0

44)

(0.0

29)

(0.0

25)

(0.0

25)

(0.0

26)

(0.0

64)

(0.2

94)

Fiv

eY

ears

Aft

er0.0

08

-0.0

29

-0.0

46

-0.0

22

0.0

57**

0.0

57**

0.0

90***

-0.2

02***

0.4

05

(0.0

34)

(0.0

44)

(0.0

49)

(0.0

30)

(0.0

26)

(0.0

26)

(0.0

26)

(0.0

68)

(0.3

19)

Six

Yea

rsA

fter

0.0

07

-0.0

85*

-0.0

40

-0.0

30

0.0

38

0.0

37

0.0

63**

-0.1

74**

-0.1

96

(0.0

32)

(0.0

47)

(0.0

48)

(0.0

43)

(0.0

29)

(0.0

26)

(0.0

26)

(0.0

71)

(0.5

34)

Sev

enY

ears

Aft

er-0

.003

-0.0

87

-0.0

57

-0.0

48

0.0

24

0.0

33

0.0

66**

-0.1

67**

-0.1

25

(0.0

33)

(0.0

59)

(0.0

46)

(0.0

34)

(0.0

30)

(0.0

25)

(0.0

26)

(0.0

78)

(0.5

26)

Eig

ht

Yea

rsA

fter

-0.0

03

-0.0

44

-0.0

15

0.0

03

-0.0

00

0.0

11

0.0

42

-0.1

46*

-0.0

82

(0.0

33)

(0.0

61)

(0.0

57)

(0.0

57)

(0.0

35)

(0.0

31)

(0.0

33)

(0.0

86)

(0.4

34)

Nin

eY

ears

Aft

er0.0

55

-0.0

05

0.0

55

0.0

17

-0.0

08

0.0

31

0.0

52

-0.1

65*

-0.2

15

(0.0

51)

(0.0

60)

(0.0

81)

(0.0

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32

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Table 8: Effect of School District Fiscal Stress Label Receipt on Housing Prices

(1) (2) (3) (4) (5)

Dependent Variable: ln(Sale Price)

Fiscal Stress -0.038*(0.0216)

Fiscal Emergency -0.108** -0.117** -0.107** -0.116**(0.050) (0.047) (0.051) (0.049)

Fiscal Watch -0.007 -0.036 -0.007 -0.036(0.027) (0.033) (0.027) (0.032)

Fiscal Caution -0.039 -0.044* -0.040* -0.045*(0.025) (0.025) (0.024) (0.025)

Auditor’s Discretion 0.056 0.056(0.039) (0.037)

Poor School Report Card Grade -0.042*** -0.042***(0.014) (0.014)

Gen Fund Balance/Revenue Ratio -0.006 -0.006 -0.006 -0.007 -0.007(0.011) (0.011) (0.011) (0.011) (0.011)

Below FC Cutoff -0.028* -0.029* -0.029* -0.026* -0.026*(0.015) (0.015) (0.015) (0.014) (0.014)

Below FW Cutoff 0.005 0.005 0.005 0.005 0.005(0.017) (0.017) (0.017) (0.017) (0.017)

Below FE Cutoff -0.012 -0.006 -0.005 -0.006 -0.006(0.013) (0.015) (0.015) (0.014) (0.014)

Constant 8.033*** 8.038*** 8.028*** 8.240*** 8.230***(1.341) (1.346) (1.345) (1.328) (1.327)

Observations 1108557 1108557 1108557 1108557 1108557R-squared 0.58 0.58 0.58 0.58 0.58

Each specification contains controls for school district financial statistics and demograph-ics, parcel characteristics, and time (month-by-year) and municipality-by-year fixed effects.Robust standard errors, clustered at the school district level given in parentheses.*** p<0.01, ** p<0.05, * p<0.1

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Table 9: Effect of School District FS Label Receipt on District Mean Housing Prices

(1) (2) (3) (4) (5)

Dependent Variable: ln(District Mean Sale Price)

Fiscal Stress -0.064**(0.0275)

Fiscal Emergency -0.179*** -0.185*** -0.182*** -0.184***(0.067) (0.065) (0.066) (0.066)

Fiscal Watch -0.034 -0.053* -0.041 -0.052*(0.033) (0.030) (0.033) (0.030)

Fiscal Caution -0.046* -0.049* -0.050* -0.049*(0.027) (0.028) (0.026) (0.028)

Auditor’s Discretion 0.038 0.038(0.047) (0.047)

Poor School Report Card Grade -0.011 -0.019**(0.009) (0.008)

Gen Fund Balance/Revenue Ratio -0.010 -0.010 -0.010 -0.010 -0.010(0.008) (0.009) (0.008) (0.010) (0.009)

Below FC Cutoff -0.013* -0.014** -0.014** -0.009 -0.014*(0.007) (0.007) (0.007) (0.007) (0.007)

Below FW Cutoff -0.006 -0.005 -0.005 -0.003 -0.004(0.010) (0.010) (0.010) (0.010) (0.010)

Below FE Cutoff -0.018 0.001 0.001 0.010 0.002(0.018) (0.017) (0.017) (0.016) (0.016)

Constant 8.37*** 8.40*** 8.39*** 8.45*** 8.47***(0.740) (0.734) (0.733) (0.731) (0.731)

Observations 635318 635318 635318 635318 635318R-squared 0.64 0.64 0.64 0.64 0.64

Each specification contains controls for school district financial statistics and demograph-ics, parcel characteristics, and time (month-by-year) and municipality-by-year fixed effects.Robust standard errors, clustered at the school district level given in parentheses.*** p<0.01, ** p<0.05, * p<0.1

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Table 10: Event Study Results - Housing Prices

(1) (2) (3) (4)

ln(Sale Price) ln(Mean Sale Price)

Three+ Years Before -0.023 -0.026 -0.024 -0.028*(0.025) (0.024) (0.016) (0.016)

Two Years Before 0.016 0.013 0.012 0.007(0.021) (0.021) (0.017) (0.017)

Year of Label Receipt 0.014 0.010 -0.018 -0.025(0.023) (0.023) (0.019) (0.019)

Year After 0.013 -0.013 -0.022 -0.054*(0.033) (0.038) (0.026) (0.030)

Two Years After 0.012 -0.030 -0.032 -0.081**(0.033) (0.041) (0.026) (0.034)

Three Years After -0.007 -0.054 -0.050* -0.099**(0.032) (0.045) (0.027) (0.041)

Four Years After 0.005 -0.081* -0.045* -0.129***(0.032) (0.042) (0.026) (0.038)

Five Years After 0.031 -0.065 -0.037 -0.152***(0.033) (0.047) (0.028) (0.054)

Six+ Years After 0.070 -0.012 0.001 -0.114(0.044) (0.065) (0.035) (0.088)

Removed Year After 0.052 0.064**(0.033) (0.031)

Removed Two Years After 0.074* 0.085**(0.041) (0.033)

Removed Three Years After 0.079** 0.080**(0.040) (0.036)

Removed Four Years After 0.124*** 0.119***(0.029) (0.031)

Removed Five Years After 0.121*** 0.144***(0.040) (0.050)

Removed Six+ Years After 0.088 0.129(0.067) (0.085)

Constant 7.93*** 7.98*** 8.34*** 8.40***(1.310) (1.315) (0.756) (0.748)

Observations 1108557 1108557 635318 635318R-squared 0.58 0.58 0.64 0.64

Each specification contains controls for school district financial statis-tics and demographics, parcel or district-by-day mean parcel character-istics, and time (month-by-year) and municipality-by-year fixed effects.Robust standard errors, clustered at the school district level given inparentheses.*** p<0.01, ** p<0.05, * p<0.1

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A Appendix

Table A.1: Variable Names and DefinitionsVariable Name Description

Fiscal Stress Indicators†Fiscal Stress = 1 if school district is labeled at time tFiscal Caution = 1 if school district is labeled in fiscal caution at time tFiscal Watch = 1 if school district is labeled in fiscal watch at time tFiscal Emergency = 1 if school district is labeled in fiscal emergency at time tAuditor’s Discretion = 1 if school district is labeled due to Auditor’s discretionDistrict Financials†Gen Fund Balance/Revenue Ratio The balance in the general fund divided by the previous year’s general fund revenueBelow FC Cutoff Range =1 if the deficit in the GF exceeds 2% of GF revenueBelow FW Cutoff Range =1 if the deficit in the GF exceeds 8% of GF revenueBelow FE Cutoff Range =1 if the deficit in the GF exceeds 16% of GF revenueTotal Expenditure PP Total expenditure divide by total enrollmentEl-Sec Expenditure PP Total operating expenditure for elementary and secondary educationInstruct Expenditure PP Total instructional expenditure divided by total enrollmentCapital Outlay PP Total capital outlay divided by total enrollmentNew Construct PP Total expenditure on new construction projects divided by total enrollmentTotal Salaries PP Total expenditure on employee salaries divided by total enrollmentInstruct Salaries PP Total expenditure on salaries for instructional staff divided by total enrollmentEmployee Benefits PP Total expenditure on employee benefits divided by total enrollmentInstruct Benefits PP Total expenditure on benefits for instructional staff divided by total enrollmentTotal Revenue PP Total revenue divided by total enrollmentFederal Revenue PP Total federal revenue divided by total enrollmentState Revenue PP Total state revenue divided by total enrollmentGeneral State Aid PP Total state foundation aid divided by total enrollmentLocal Revenue PP Total local revenue divided by total enrollmentLocal Prop Tax Revenue PP Total local property tax revenue divided by total enrollmentOper Prop Tax Revenue PP Total local property tax revenue for operating expenditure divided by total enrollmentCap Prop Tax Revenue PP Total local property tax revenue for capital expenditure divided by total enrollmentLocal Inc Tax Revenue PP Total local income tax revenue divided by total enrollmentDistrict Demographics•Total Enrollment Total district enrollmentPercent Free and Reduced Lunch Percentage of students that are eligible for free and reduced price lunchPercent Black Percentage of students that are blackNumber of Schools in District Total number of schools in the districtPupil-Teacher Ratio Total district enrollment divided by total full-time equivalent teachersPoor School Report Card Grade School Report Card Grade is below averageUrban = 1 if school district is in an urban areaParcel Characteristics?ln(Sale Price) The natural log of the sale priceTotal Rooms The total number of rooms in the houseTotal Bedrooms The total number of bedrooms in the houseTotal Bathrooms The total number of bathrooms in the house (half bath = 0.5)Total Square Footage of Living Area The total square footage of the living area in the house

† Sources: Data from Ohio Auditor website and Ohio Department of Education website’s list of fiscal caution,fiscal watch, and fiscal emergency districts.‡ Sources: Data from Ohio Auditor, Ohio Department of Taxation, and Common Core of Data• Sources: Common Core of Data and Ohio Department of Education? Sources: Data from 62 of 88 counties in Ohio. Data was downloaded from individual county auditor websitesusing parcel search tools or data set downloads.

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Table A.2: Comparison of Full and Analytic Samples

Full Sample Analytic Sample

Fiscal Stress 0.06 0.06(0.24) (0.24)

Poor School Report Card Grade 0.18 0.18(0.39) (0.39)

Urban District 0.19 0.19(0.39) (0.39)

Gen Fund Balance/Revenue Ratio 0.18 0.18(0.28) (0.26)

Below FC Cutoff 0.08 0.08(0.28) (0.27)

Below FW Cutoff 0.03 0.03(0.17) (0.17)

Below FE Cutoff 0.00 0.00(0.06) (0.06)

Revenue per Pupil (2012 $) 11839 11987(3146) (3171)

Expenditure per Pupil (2012 $) 11730 11871(3668) (3644)

Total Class I Millage Rate 29.83 30.32(6.85) (7.26)

% Free/Reduced Lunch Students 0.24 0.24(0.18) (0.18)

% Black Students 0.06 0.06(0.14) (0.15)

Total Enrollment 2922 3106(4653) (5143)

Number of Schools in District 5.91 6.27(9.10) (10.19)

Pupil Teacher Ratio 17.25 17.23(2.24) (2.32)

% Above Math Proficiency 76.97 77.05(10.89) (11.02)

% Above Reading Proficiency 0.83 0.83(0.08) (0.08)

Observations 7351 5662

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Table A.3: Table of Means - School District Characteristics*Panel A† Panel B‡

Never in Pre-Fiscal Fiscal Fiscal Post-FiscalFiscal Stress Stress Stress Stress Stress

School District Financial CharacteristicsGen Fund Balance/Revenue Ratio 0.19 0.02 0.09 0.11 0.20

(0.15) (0.09) (0.32) (0.34) (0.26)Below FC Cutoff 0.05 0.38 0.23 0.22 0.05

(0.13) (0.37) (0.29) (0.29) (0.13)Below FW Cutoff 0.01 0.18 0.10 0.10 0.02

(0.06) (0.27) (0.20) (0.20) (0.06)Below FE Cutoff 0.00 0.03 0.03 0.03 0.00

(0.01) (0.09) (0.13) (0.13) 0.00Total Expenditure PP (2012 $) 11723 12149 11012 11184 11215

(2222) (2621) (2454) (2559) (1968)El-Sec Expenditure PP (2012 $) 9603 9595 9631 9589 9990

(1632) (1255) (1455) (1237) (1440)Total Capital Outlay PP (2012 $) 1594 2051 796 1055 681

(1271) (2100) (1643) (2067) (762)Total Salaries PP (2012 $) 5818 5896 5723 5716 5873

(1099) (831) (897) (767) (805)Total Revenue PP (2012 $) 11841 11394 11991 12071 11961

(2127) (2161) (2450) (2540) (2025)Total Federal Rev PP (2012 $) 590 749 912 780 746

(321) (467) (520) (487) (541)Total State Rev PP (2012 $) 5452 5877 5944 5603 5139

(1960) (2572) (2349) (2949) (1987)Total Local Rev PP (2012 $) 5799 4768 5135 5687 6076

(2658) (1584) (1659) (2044) (2145)Local Prop Tax Rev PP (2012 $) 4160 3352 3947 4246 4387

(2695) (1605) (1814) (2017) (1878)Oper Prop Tax Rev PP (2012 $) 3637 2916 3443 3780 3922

(2486) (1443) (1640) (1936) (1805)Capital Prop Tax Rev PP (2012 $) 519 425 497 459 465

(366) (323) (389) (377) (375)Local Income Tax Rev PP (2012 $) 265 93 211 270 339

(484) (249) (408) (488) (601)School District Demographic Characteristics

Total Enrollment 2789 3034 2884 3739 3427(4201) (2574) (2190) (7445) (6305)

% Free/Reduce Lunch Students 0.23 0.29 0.32 0.29 0.34(0.13) (0.17) (0.16) (0.15) (0.16)

Number of Schools in District 5.64 6.41 5.72 7.29 7.30(8.40) (4.73) (3.98) (13.58) (14.21)

Pupil/Teacher Ratio 17.26 16.91 17.88 17.48 16.98(1.80) (1.78) (1.94) (1.99) (1.84)

% Proficient in Math 0.78 0.67 0.74 0.73 0.78(0.08) (0.11) (0.11) (0.11) (0.10)

% Advanced in Math 0.19 0.08 0.18 0.15 0.22(0.07) (0.05) (0.09) (0.09) (0.09)

% Proficient in Reading 0.84 0.77 0.81 0.80 0.84(0.06) (0.08) (0.08) (0.08) (0.07)

% Advanced in Reading 0.16 0.10 0.15 0.14 0.15(0.05) (0.04) (0.05) (0.06) (0.05)

Poor School Report Card Grade 0.16 0.30 0.30 0.29 0.17(0.20) (0.25) (0.37) (0.35) (0.27)

Urban District 0.16 0.36 0.36 0.34 0.34(0.36) (0.48) (0.48) (0.48) (0.48)

Observations 509 81 81 71 71

Note: Pre-Fiscal Stress corresponds to the time period prior to the declaration of fiscal stressfor labeled districts. Fiscal Stress corresponds to the time period a fiscal stress label isattached to the district. Non-Fiscal Stress corresponds to all non-labeled jurisdictions.†Panel A includes districts that appear in both the pre-FS period and the FS period.‡Panel B includes districts that appear in both the FS period and the post-FS period.*Standard Deviations are given in parentheses.

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Table A.4: Table of Means - Housing and Parcel Characteristics*

Panel A† Panel B‡Never in Pre-Fiscal Fiscal Fiscal Post-Fiscal

Fiscal Stress Stress Stress Stress Stress

Sale Price (2012 $) 140912 133457 122809 134777 117720(62379) (50589) (49204) (56164) (52163)

Rooms 6.01 5.84 5.85 5.99 5.99(1.27) (1.34) (1.16) (0.85) (0.86)

Bedrooms 2.95 2.89 2.90 2.87 2.88(0.48) (0.60) (0.57) (0.61) (0.60)

Bathrooms 1.59 1.55 1.50 1.51 1.54(0.39) (0.48) (0.42) (0.41) (0.39)

Living Area (Sq. Ft.) 1679 1564 1538 1563 1593(315) (294) (254) (270) (277)

Age of Home (Years) 46.08 42.69 48.64 46.05 50.08(16.02) (19.01) (17.61) (17.26) (17.36)

Observations 409 79 79 67 67

Note: Pre-Fiscal Stress corresponds to the time period prior to the declarationof fiscal stress for labeled districts. Fiscal Stress corresponds to the time perioda fiscal stress label is attached to the district. Non-Fiscal Stress correspondsto all non-labeled jurisdictions.†Panel A includes districts that appear in both the pre-FS and FS periods.‡Panel B includes districts that appear in both the FS and post-FS periods.*Standard Deviations are given in parentheses.

39