Behind the Opinions: Why People Oppose School Choice

David M. Brasington Kautz Professor of Political Economy

Associate Professor University of Cincinnati Economics Department

david.brasington@uc.edu

Diane Hite Professor

Auburn University Department of Agricultural Economics

and Rural Sociology hitedia@auburn.edu

October 18, 2012 JEL Codes: H44, H75, I22 Keywords: school choice, school vouchers, open enrollment, charter schools, tuition tax credits

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Abstract Several studies look at the characteristics of who supports and opposes various types of school choice (charter schools, school vouchers, open enrollment, and tuition tax credits). We go a step farther by taking the people who oppose school choice and seeing which types of people oppose school choice for any of four different reasons: (1) that choice will decrease house value, (2) that choice will bring worse students into the public school, (3) that choice takes tax money away from public schools, and (4) that choice helps support religious schools. Our simultaneous system of censored probits, corrected for sample selection, reveals over 40 findings. Among these, we find people who live in open enrollment school districts are more likely to oppose school choice because it takes tax money away from the home district, but they are less likely to oppose it for its potential to bring worse students into the district.

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School choice proposals often make headlines but rarely become enacted. K-12 schooling is

generally funded by tax dollars, and students may attend an assigned public school district using these

tax-supported funds. If students attend a private school or a public school other than the one they are

assigned to, they must continue to pay taxes for their assigned public school, and they pay full tuition at

their chosen alternative school. A variety of measures lumped under the term school choice attempt to

reduce the cost of students attending alternative schools. These measures include school vouchers,

tuition tax credit, charter schools, and open enrollment.

Only 8 states have tax credits or deductions for parents who send children to alternative

schools. Only 15 states require inter-district open enrollment, where students may attend alternative

school districts without additional cost. In 2007 the governor of South Carolina vetoed open enrollment

legislation, and the state legislature failed to override the veto. While there are 45 states with charter

school laws on the books, many of these laws are so restrictive that charter schools rarely arise, or

stringent regulations cap the number of charter schools or make the ones that arise nearly

indistinguishable from traditional public schools. School vouchers are found in a limited number of

countries like Chile, Bangladesh, Lesotho and Sweden, and in certain locations in the United States like

Cleveland, Milwaukee, and Florida. Still, the failures of voucher proposals outnumber the successes,

including recent objections by the judicial system, state and national legislatures, and voter referenda.

Witness the U.S. Congress closing the D.C. voucher program to new students (Birnbaum, 2010), courts in

Arizona and Oklahoma declaring state voucher programs unconstitutional (Kossan and Gersema, 2009;

Archer, 2012), the Illinois legislature killing a proposed school voucher for Chicago (Long and Manchir,

2010), a voucher bill being withdrawn from consideration in the Georgia legislature for lack of support

(Cheplick, 2009), and the defeat of a state-wide voucher referendum in Utah, even with a Republican

legislature and governor (Associated Press, 2007).

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The current study fills in a gap in the school choice literature. Instead of just asking, Who

opposes school choice?, we go a step deeper by asking people why people oppose choice. For example,

do they oppose it because school choice will help support religious schools? We then ask, What are the

characteristics of the people who oppose school choice because it will help support religious schools? In

addition, unlike previous studies, we allow people to express their opinion on the principle of school

choice rather than limiting them to a single school choice delivery system, such as vouchers. More

specifically, we first calculate an inverse Mills ratio to address survey sample selection bias. We use this

inverse Mills ratio in a simultaneous system of censored probits. One probit asks whether a respondent

opposes school choice or not; the other focuses on people who oppose school choice and asks whether

the person opposes school choice for reason x. Estimating these probits simultaneously allows for

correlation between the error terms, improving efficiency.

Ohio is a good choice for our study as it has a variety of schooling options. Ohio residents are

already familiar with certain forms of school choice and have had a chance to form something of an

informed opinion of them. There are 614 public school districts, many of which participate in a

voluntary open enrollment program. A majority of school districts (371) allow students to enroll from

anywhere in the state; an additional 118, or about 28%, allow only students living in adjacent school

districts to enroll; and the remaining 173 school districts do not allow any form of open enrollment.

Since 1995, the Cleveland City School District has operated the Cleveland Scholarship and Tutoring

Program, a school voucher experiment open to residents of Cleveland in grades K-8. Students chosen by

lottery to receive the voucher may attend any non-public school within the city of Cleveland or any

public school district adjacent to Cleveland. The voucher covers 75% or 90% of tuition up to the

legislated maximum, depending on family income. The voucher also includes transportation. The Ohio

Educational Directory lists 852 non-public schools for all grades K-12. There are many types of private

schools in Ohio, including schools for girls, Baptist, Orthodox, Lutheran, Catholic, Montessori, Adventist,

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secular academies, Jewish, Islamic, and a school for autistic students. In addition, there are 292 public

charter schools specializing in areas such as college prep, technology, leadership, fitness, culture,

entrepreneurship, science, arts, manufacturing, health care, and maritime training.

For our analysis, we select four reasons why people might oppose school choice, based in part

on issues explored in previous literature. We ask 1,186 Ohio homeowners whether they support or

oppose choice and why. We then investigate the characteristics of the people who oppose it for each of

four reasons. Many results conform to expectations, some do not, and other findings are surprising but

seem to be empirical facts. For example, we find people living in school districts that allow open

enrollment don’t think school choice draws worse students into their school district, but they do oppose

choice because they believe it funnels tax money away from their public school districts. There are

many types of respondents who oppose choice on the grounds that it will attract worse students: those

who have graduate degrees, coach youth sports teams, are involved in homeowner associations, and

whose children attend public schools. People who purchased their current house for the good schools

are more likely to oppose choice on the grounds that it will decrease their house value. We identified

five characteristics of people who oppose choice on grounds that it will help religious schools, the

largest number of significant characteristics in any regression.

Literature Review

Several studies examine whether people support or oppose school choice. These studies help motivate

our choice of reasons to oppose choice. For example, Catholics and evangelical Christians are more

likely to apply for and use the Children’s Scholarship Fund national partial voucher program, a private

charity, which helps send as many as 40,000 children1 to private school (Campbell, West and Peterson,

126,384 students are currently funded; see http://www.scholarshipfund.org/drupal1/.

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2005). Although some people might support school choice because it helps support religious schools,

other people might oppose school choice for the same reason.

Several studies investigate the relationship between the quality of a person’s assigned public

school and their attitudes toward school choice (e.g., Brunner, Imazeki and Ross, 2010; Brasington and

Hite, 2012a,b). While school choice provides an escape for children assigned to low-performing public

schools, from the perspective of people living in high-performing schools, school choice also allows

students from low-performing schools to infiltrate high-performing schools. Whether the incoming

students are worse or not is debatable, but the fact that they may come from a low-performing school

may make some people think the school choice program will attract worse students to their

neighborhood schools, decreasing quality.

Hoyt (1996) and Reback (2005) study Minnesota’s open enrollment program. They find house

prices fall in school districts that accept students from lower-performing school districts, and house

prices rise in areas where students transfer to better-performing school districts. The capitalization of

school quality into property values may underlie some people’s opinions about school choice (Brunner,

Sonstelie and Thayer, 2001; Brunner and Sonstelie, 2003).

A report by Strate and Wilson (1991) helps identify the final reason to oppose school choice in

our study: that school choice will take tax money away from the public schools.1 Strate and Wilson do a

limited investigation of the characteristics of people who oppose choice. Specifically, they show the

percent of respondents who oppose each form of school choice, and break down this opposition by the

respondent’s race and his or her subjective rating of their assigned school district. For example, they

report the percentage of respondents who oppose cross-district public school choice, and then show the

percentage of black respondents who oppose it and the percentage of respondents from self-described

“poor” quality public school districts who oppose it. In contrast, the current study uses regression

analysis to control for a respondent’s race, school quality, and dozens of other factors when analyzing

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opposition to school choice. Also unlike Strate and Wilson (1991), the current study explicitly asks

respondents why they oppose choice, and it uses regression analysis to identify the set of characteristics

of the people who oppose for each reason.

Data

Our data set is based on a survey of 1,186 Ohio homeowners, 322 of whom oppose school choice. The

data set is based on that used in Brasington and Hite (2012a,b); readers are referred to these papers for

detailed information about the survey design and sampling technique.

[insert Table 1 about here]

Most of the variables used in the study come from the phone survey, which provides detailed

demographic data about the respondents, but data from other sources is required to test additional

hypotheses. We use the percentage of students who are proficient or above proficient on the 12th grade

Ohio math proficiency test as a measure of public school district performance (Ohio Department of

Education, 2002a). The number of disciplinary actions and expulsions in a school district is taken from

the Ohio Department of Education (2002b). The percent of Catholics comes from Bradley, et al. (1992).

Data on private school tuition comes from a phone survey conducted in 2005 by Brasington’s graduate

assistants. The Ohio Department of Taxation provides data on the percent of taxable property coming

from agricultural land and from new construction (ODOT 2003). We identify the school districts that

participate in Ohio’s voluntary open enrollment program from the Ohio Department of Education

(2007), the number of school levies that pass (2002a), and expenditures by school district (2002a).

Variable means, definitions, and sources are found in Table 1. Other variables are drawn from the 2000

U.S. Census.

Although regression analysis is the focus of the paper, it is instructive to pay attention to some

of the simple means. For instance, 44% of respondents favor school choice while 27% oppose it and

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30% have not made up their minds. By far the most popular reason given to oppose school choice was

that it would take tax money away from public schools, with 76% of opponents voicing this concern.

The next most popular reason (37%) is that choice helps support religious schools. It would be

interesting to see if this reflects anti-religious attitudes of certain Ohioans, or whether such respondents

simply have concerns with the separation of church and state. Only 16% of opponents felt that school

choice would draw worse students to their public school district, and only 9% felt school choice would

decrease the value of their houses.

Empirical Model

Investigation of the reasons why a respondent supports school choice with our dataset requires

estimation of censored probit models with sample selection. The sample selection problem arises

because of selection bias from survey nonresponse. The censored probit is necessary because we focus

only on opponents of school choice, while supporters are censored from the analysis.

We begin by performing a Heckman two-stage sample selection correction. A probit is

estimated for survey response, and the resulting inverse Mills ratio (IMR) from this regression is used to

correct for sample selection bias in a series of censored probit models of reasons to oppose school

choice.

Formally, we estimate a series of models consisting of three equations, two of which are

estimated simultaneously. Equation (1) is a probit for whether each of the 10,499 people we contact

responds to the survey. It takes the following form:

Pr(Yi1)=f(Hi,DCi, Si)+ εi1 (1)

where Yi1=1 for respondents and Yi1=0 for non-respondents. The remaining variables are determinants

of whether a person responds to the survey, with Hi representing house characteristics, DCi representing

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Census block group demographic variables and Si representing school characteristics of respondents and

non-respondents.

The second equation in our model takes the set of people who respond to our survey and runs a

probit for whether the respondent opposes school choice or not. It takes the following form:

Pr(Yi2)=f(Di,Hi ,Si,Ai, IMRj)+ εi2 (2)

where Yi2=1 for opponents of choice, Di is a vector of demographic characteristics of individual

respondents, Hi are house characteristics of respondents, Si represents school district characteristics of

respondents, Ai represents political attitudes of respondents, and IMRj is the inverse Mills ratio

calculated in Equation (1).

The third equation in our model represents a probit on the censored sample. A LIML model

regresses opposition or non-opposition for choice for reason x as a function of different characteristics.

It takes the following form:

Pr(Yi3)=f(Di,Hi ,Si,Ai)+ εi3 (3)

where Yi3=1 for a reason chosen in the survey and 0 otherwise, and the explanatory variables have the

same definitions as above. Equations (2) and (3) are estimated simultaneously.

For all j equations, (εij)~Bernoulli, and E(εij, εik)≠0. In addition, exclusion restrictions apply to all

three equations. For the sake of brevity, only the results of Equations (2) and (3) are reported in this

paper.2 Figure 1 illustrates our estimation approach.

Insert Figure 1 about here

As an example of the model, consider the support of school choice for its potential to lower

property values. Equation (1) estimates the probability that one of the 10,499 individuals contacted

responds to the survey. Then, for this reason to support choice, Equations (2) and (3) are

simultaneously estimated. Equation (2) is a probit for whether each of the 1,186 respondents opposes

school choice or not, corrected for sample selection. The second equation in the system, Equation (3), is

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a probit that uses the sample of the 322 people who oppose school choice, and censors the 864 people

who do not support school choice. The dependent variable of Equation (3) is a dummy variable that

takes the value 1 for a respondent who opposes choice specifically because it will lower the value of his

house; it takes the value zero otherwise. The two probits are estimated simultaneously to capture

correlation between opponents and the reasons for their opposition; the correlation parameter

estimate is statistically significant in two out of four cases.

We considered running a series of bivariate probits for our reasons to oppose choice. One

probit would be whether a person opposes choice or not, and the other probit would be whether a

person opposes it for reason x. However, this approach would not work because a person must oppose

choice to be part of the “oppose for reason x” regression, and in this case, the dependent variable in the

“oppose choice or not” regression would have no variation.

We also considered using a conditional logit of the pooled data. But conditional logits require

that a respondent be faced with multiple, mutually exclusive choices, with each choice explained not

just by personal characteristics, but also by a choice-specific variable, which is usually the cost of the

choice. In our case, we have only personal characteristics. We considered a nested logit, where in the

first stage a person decides how he feels about choice, and in the second stage he chooses the reasons

why he opposes choice. However, we face a problem of non-mutually exclusive choices, similar to the

conditional logit. That is, in a nested logit a person only ends up on a single branch of the decision tree,

while in our data a person can choose as many as four reasons to oppose choice.

Heteroskedasticity is inherent in probability models, but a series of LR tests cannot reject the

null of homoskedasticity.3 Nevertheless, we use robust standard errors to alleviate any potential bias in

the standard errors. We also suspect VOTED might be endogenous in the OPPOSE CHOICE regression.

We perform a Rivers and Vuong (1988) test for endogeneity, using renter status, participants in the arts,

and volunteers for youth groups as instruments.4 The Rivers and Vuong test cannot reject the null

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hypothesis that VOTED is exogenous in the SUPPORT CHOICE regression.5 A Moran’s I test and an LR

test could not reject the null hypothesis of no spatial dependence in Brasington and Hite’s (2012b)

SUPPORT CHOICE regression, so spatial dependence is not likely an issue either; this is likely because of

the geographic dispersion of respondents across the state.6

Choice of Relevant Regressors

Prior research provides some guidance for the choice of explanatory variables used in our study,

especially for the selection regression that explains the characteristics of people who oppose school

choice.

Relevant Regressors: Selection Model

Recall that we run two probits simultaneously. The first probit is for whether a respondent opposes

school choice or not. Prior research suggests that support for school choice depends on the quality of

public schooling a respondent enjoys (Strate and Wilson, 1991; Campbell, West and Peterson 2005;

Brasington and Hite, 2012a,b). We thus include the math proficiency passage rate of the respondent’s

public school district in the oppose choice probit.

Most research finds less support for school choice the higher a person’s age (e.g. Brunner,

Imazeki and Ross, 2010). Although Brasington and Hite (2012a) find no such role for age, we include it

as a demographic control for its theoretical importance.

Campbell, West and Peterson (2005) find higher income makes a person less likely to apply for

and use the Children’s Scholarship Fund partial voucher. Brunner, Sonstelie and Thayer (2001) find

precincts with higher incomes less likely to vote for California’s 1993 voucher program. Brasington and

Hite (2012a,b) find no role for income, but the preponderance of the evidence suggests income should

be a regressor.

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Racial composition is usually significantly related to a person’s support for school choice

(Brasington and Hite, 2012a,b; Sandy, 1992; Howell, et al., 2002), so we include a dummy variable for

whether a person is non-white. We include a respondent’s sex, as there is some evidence that men

oppose school choice more than women (Brasington and Hite, 2012b).

The literature shows conflicting evidence for whether higher education levels are positively or

negatively related to school choice support, but in all studies it is an important factor (Brasington and

Hite, 2012a,b). We therefore include a respondent’s education level in the choice regression.

Having school-aged children makes a person more likely to support school choice (Brunner,

Sonstelie and Thayer, 2001; Brasington and Hite, 2012a), so we include this variable in our choice

regression.

We also include a set of political variables as controls: ideology variables (Brunner, Imazeki and

Ross, 2010; Brunner, Sonstelie and Thayer, 2001), whether a respondent voted in the last election, and

per-capita political contributions in a respondent’s zip code to the Republican and Democratic parties.

We also include the inverse Mills ratio that mitigates survey nonparticipation bias.

Relevant Regressors: Reasons to Oppose Choice Models

1. Oppose Because Lowers House Values

Some literature suggests people base their opinions on school choice with the capitalization of school

quality into house values in mind (Brunner, Sonstelie and Thayer, 2001); other studies find no

capitalization motive (Brasington and Hite, 2012b). We suspect people who say they oppose choice

because it will decrease the value of their house live in areas with a high degree of home ownership,

have high incomes (correlated with high property values), and live in high-performing public school

districts where the capitalization of school quality is high.

2. Oppose Because Brings Worse Kids into Schools

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Tiebout sorting assumes people sort to a place that offers the mix of local public services that a

household likes best. Prime among these public services is schooling. But public school choice programs

allow children from outside the attendance zone to attend a public school. We ask opponents whether

they oppose school choice because it would draw worse students into their school district. We suspect

that respondents with children who attend public school would be more likely to select this reason, as it

would directly affect their children’s peer group at school. People with high levels of education might

also be more concerned than most about a change in peer group in their public school, so we include a

dummy variable for whether the respondent has a graduate degree. We also include variables

representing a respondent’s opinions about the quality of the typical public school in Ohio (Brasington

and Hite, 2012a), as these people might most be concerned about worse students from neighboring

districts entering the school and lowering its quality. The number of school districts in the area also

should play a role: if there are more public school districts in the respondent’s urban area, there is more

opportunity for Tiebout sorting, and therefore more dramatic differences between children in each

school district. Also, having a large number of small school districts in the area lowers the

transportation cost of new students attending a respondent’s school district.7 Parents in a rural area are

less likely to engage in school choice because the distances between schools are greater, and children

are more likely to be similar across districts in rural areas.

3. Oppose Because Takes Tax Money Away from Public Schools

Many respondents are concerned that school choice would take tax money away from their

public school district. Some are probably concerned because they support the idea of public education

for a community’s children, like people with graduate degrees, high incomes, and minorities. Financial

concerns may be important for other people, like males, people living in school districts that have

difficulty passing school tax levies or that have slow-growing property tax bases, and people who

specifically moved to an area for its low taxes. In a similar vein, people in areas with heavily-used

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private schools may be less concerned about the public school district’s finances, as would people

whose nearest private school charges high tuition. Respondents living in a public school district that

participates in Ohio’s open enrollment program are probably more aware of the issue, and therefore

more concerned about a loss of tax revenue. And people living in urban areas with a lot of smaller

public school districts may realize that transportation time between school districts is low, so that a

school choice program might attract heavy participation and concomitant exodus of money from their

public school.

4. Oppose Because Supports Religion

People may also oppose school choice because it supports religious schools. We suspect that

people with the highest levels of education may oppose organized religion, as might very liberal people.

Minorities may be more involved with religion than whites, so we suspect minorities are less likely to

oppose school choice on these grounds. Supporters of religious schools are less likely to oppose choice

for religious reasons, so we include as explanatory variables the prevalence of Catholics in an area and a

dummy variable for whether a person thinks his nearest private school is excellent.

Results: Oppose Choice

[insert Table 2 about here]

1. Oppose Because Lowers House Values

Respondents chose up to four reasons why they oppose school choice. The first of these we discuss is a

possible loss in property values, a reason chosen by 9% of school choice opponents. Theory suggests

that higher-income people would choose this reason, and the results in Table 2 bear out this hypothesis.

At the mean, given a 10% increase in income a person is 6.4% more likely to oppose choice to protect

property values. We also suspected that respondents living in areas of high home ownership rates

would be more concerned about property value losses from school choice, but this variable does not

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reach statistical significance at conventional levels. Our final theoretical variable, school quality,

conforms to theory. People who bought their house for the good schools are more likely to oppose

choice with house prices in mind.

Because this is a new line of investigation, there is a limit to the influences that theory suggests. But

just as theory often guides empirical work, sometimes empirical work stimulates theory. For each

reason to oppose choice, after we have examined the variables with a theoretical foundation, we search

for more factors that might prove important. Such experimentation uncovers additional types of people

who oppose choice because it might lower property values, including the strongest effect in the

regression. Respondents who are single oppose school choice for property value reasons (elasticity

0.18). Respondents living in agricultural school districts feel the same way. The marginal effect of

increased agricultural property value in a school district is 0.007 (elasticity 0.16). The final statistically

significant influence we uncover is for respondents whose households work long hours each week. Such

respondents are less likely to oppose school choice with property values in mind, and they have the

strongest economic effect in the regression (elasticity -0.98).

2. Oppose Because Brings Worse Kids into Schools

[insert Table 3 about here]

16% of respondents oppose school choice because it will draw bad students to their public

school district. Who are these people? We thought they would be people who use the public schools,

and in fact Table 3 shows having kids in public school makes a person more likely to oppose choice

because of concern about a change in peer groups (marginal effect 0.027, elasticity 0.26). Theory also

suggested including variables for what a respondent thinks of the quality of the typical public school.

We find no significant relationship for these variables. The coefficient for the number of school districts

in the area is not significant, either. Having a graduate degree is significant, making a respondent 2

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percentage points more likely to oppose choice because it brings bad students to the school district.

Experimentation with additional variables provided more significant results. People who live in school

districts with a high expulsion rate are more likely to oppose choice with negative peer effects in mind

(marginal effect 0.017, elasticity 0.21), as are respondents who volunteer as youth coaches (marginal

effect 0.027). Finally, respondents whose school districts already engage in Ohio’s voluntary open

enrollment program apparently have had their fears allayed: such people are less likely to oppose

school choice for its potential to draw bad students to their schools (-0.028 marginal effect, -0.31

elasticity).

3. Oppose Because Takes Tax Money Away from Public Schools

[insert Table 4 about here]

We next see which types of people object to school choice because it will take tax money from

the public schools. This was the most common reason given to oppose choice, selected by 76% of

respondents opposing choice. As we theorized, Table 4 shows people with graduate degrees selected

this reason (marginal effect 0.09). We theorized that people with high incomes would oppose choice for

public school budget reasons, but this variable was not significant. Minorities were less likely to be

concerned about public school funding, the strongest marginal effect in the regression (-0.12). Men

expressed this concern at the same rate as women. As we expected, school districts with a proven

ability to pass tax levies were less concerned about school choice’s effect on public schools’ budgets (-

0.06 elasticity), as were school districts with fast-growing industrial and commercial tax bases. We

expected respondents in areas with many school districts to be less concerned, but in fact they are no

more or less concerned about public school budgets. We expected people in areas with a high market

share for private schools to be less concerned about public school budgets, but this variable was

insignificant, as was the tuition charged by the nearest private school. Finally, we expected people in

school districts that allow open enrollment to have thought more about school choice, and therefore to

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be more concerned about its potential to take money from public schools. We find respondents in

open-enrollment school districts are 9 percentage points more likely to oppose choice for school budget

reasons than other respondents.

4. Oppose Because Supports Religion

[insert Table 5 about here]

The second-most popular reason to oppose choice is that school choice helps support religious

schools. The 37% of opponents who choose this concern are either against religion altogether or are

especially conscious about separation of church and state issues. We expected people with graduate

degrees and self-identified very liberal people to express this concern. While being very liberal and

minority are insignificant in Table 5, having a graduate degree does make a respondent oppose choice

on religious grounds (marginal effect 0.12). As we theorized, being in a heavily Catholic area makes a

person less likely to oppose choice for religious reasons (-0.11 elasticity). Experimentation brought

several other significant factors to light. People in blue-collar neighborhoods are more concerned about

supporting religion (0.18 elasticity), as are people in high-spending public school districts (0.67

elasticity), the strongest effect in the regression. Living in a school district with more school discipline

problems is associated with a greater concern for school choice’s effect on promoting religion (0.0011

marginal effect, 0.08 elasticity). And people who volunteer in schools are also concerned about the

religion-supporting effects of school choice.

Conclusion

Some previous research studies who supports and opposes school choice without asking why. We

identify four reasons why people might oppose choice and see which types of people oppose choice for

these reasons.

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Overall, people’s opinions about the quality of the public and private schools in their area, and

whether their children attend public or private schools, do not matter: they are not independently

related to a person opposing choice for reasons of religion, house prices, peer effects or protection of

public school spending. We do find that people who purchased their house because of the good schools

oppose choice for fear that it will lower their house price; and we do find that people who use the public

schools oppose choice because it will bring in worse students. But the other seven variables related to

school performance or attendance are insignificant. Given that people in high-performing public school

districts oppose school choice overall, it may be concerns about peer effects and house prices that

underlie their opposition.

We find that respondents with special interests have stronger opposition to school choice than

the typical respondent. School volunteers oppose choice on religious grounds, and youth coaches and

members of homeowners associations oppose choice for its potential to bring worse students to the

school.

Respondents whose school districts participate in open enrollment programs have had an extra

opportunity to gauge the effects of school choice. Such respondents are more likely to oppose school

choice because it takes tax money away from the home district, but they are less likely to oppose it for

its potential to bring worse students into the district.

We also note that people with high levels of education have particularly strong views on school

choice. People with master’s degrees and above oppose school choice, and the source of their

opposition is widespread: they chose three of our four reasons to oppose school choice, the sole

exception being the concern that school choice lowers house prices.

Appendix: Sample Selection Correction

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Each probit we perform is jointly estimated with a sample selection correction probit. For example, our

results for Table 2, Oppose Choice: Will Decrease Value of My House, are estimated jointly with a probit

for whether a person opposes choice in the first place, let alone whether he opposes it for house price

reasons. Results are shown in Table A1: Oppose Choice or Not Regression.

We find that, relative to moderates, Very Conservative people support school choice and Very

Liberal people oppose it. Minorities and older people support choice, all else constant, while

respondents who live in a school district with high proficiency test passage oppose choice, perhaps

because they paid a premium to live in high-performing school districts, while choice would make it

easier for people who didn’t pay a premium to attend their schools. Respondents with some college

attendance but no bachelor’s degree support choice, as do respondents with high school education or

less. Respondents with children age 0 to 5 support choice. People who voted in the most recent

election are more likely to oppose school choice, while respondents living in areas with more

contributions to Republicans are more likely to support school choice. Other influences—income, being

male, having school-aged children, and living in an area with high political contributions to Democrats—

are statistically insignificant. We also include an inverse Mills ratio reflecting whether a person

responded to our survey or not. The construction of this variable is described in Brasington and Hite

(2012b).

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Figure 1: Estimation Approach

Note: Equation (1) yields an inverse Mills ratio used in Equation (2), and Equations (2) and (3) are estimated simultaneously with correlation allowed between them.

Respond to survey?

no

yes Support choice?

no

yes

Oppose choice because…

Decrease House Value?

Bring Bad Kids to My School?

Take Tax Money Away from Public School?

Support Religion?

yes

no

yes

no

yes

no

no

yes

Equation (2) Equation (1) Equation (3)

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Table 1 Variable Names, Definition, and Means

Variable Definition (Source) Mean (Std. Dev.)

Choice No Dummy variable indicating whether the survey respondent opposes school choice (=1) or not (=0) (1)

0.27 (0.44)

Decrease House Value Dummy variable indicating whether the survey respondent opposes school choice because it will decrease the value of their house (=1) or not (=0) (1)

0.09 (0.29)

Bring Bad Students Dummy variable indicating whether the survey respondent opposes school choice because it will bring bad students into their public school (=1) or not (=0) (1)

0.16 (0.36)

Take Tax Money Dummy variable indicating whether the survey respondent opposes school choice because it will take tax money away from their public school (=1) or not (=0) (1)

0.76 (0.43)

Oppose Religion Dummy variable indicating whether the survey respondent opposes school choice because it will support religious schools (=1) or not (=0) (1)

0.37 (0.48)

Minority Dummy variable = 1 if respondent’s race is black, Asian, American Indian/Pacific Islander, other non-white race, or Hispanic any race (1)

0.09 (0.29)

Age Age of respondent; midpoint of age categories asked in survey with 85 used for “85 and above” (1)

44.4 (12.4)

Male Dummy variable = 1 if respondent is male (1) 0.40 (0.49)

#Districts Number of school districts in the respondent’s urban area

22.7 (12.7)

Coach Dummy variable = 1 if respondent is currently active in youth league coaching (1)

0.12 (0.33)

Inverse Mills Ratio Inverse Mills ratio from sample selection regression for whether a household responded to the survey or not (2)

1.64 (0.13)

School Volunteer Dummy variable = 1 if respondent volunteers in public or private schools (1)

0.30 (0.46)

Homeowners Association Dummy variable = 1 if respondent is currently active in a condo or homeowner’s association (1)

0.09 (0.28)

Proficiency Test Public school proficiency test score; percentage of students in school district at or above proficient in year 2000 math section of Ohio 12th grade proficiency test (3)

64.5 (19.9)

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Public Excellent Dummy variable = 1 if respondent believes his own public school district is excellent (1)

0.39 (0.49)

Private Excellent Dummy variable = 1 if respondent believes his nearest private school district is excellent (1)

0.31 (0.46)

Typical Public Poor Dummy variable = 1 if respondent believes the typical public school district in the state is poor quality, one notch above “poor” in our survey (1)

0.05 (0.21)

Typical Public Not Good Dummy variable = 1 if respondent believes the typical public school district in the state is not good quality (1)

0.06 (0.24)

Hours Worked Number of hours per week people in respondent’s household work for pay (1)

55.1 (20.3)

Graduate Degree Dummy variable = 1 if respondent has a master’s, Ph.D, or professional degree (1)

0.33 (0.47)

High School or Less Dummy variable = 1 if respondent has a high school diploma or less as highest degree (1)

0.17 (0.38)

Less than Bachelor’s Dummy variable = 1 if respondent has attended college but earned an associate’s degree or less (1)

0.29 (0.46)

Income Respondent’s family income; midpoint of income categories in tens of thousands of U.S. dollars, assuming $300,000 as highest income (1)

8.54 (5.85)

Kids 0-5 Number of children ages 0 to 5 living in respondent’s house at least half of the time (1)

0.47 (0.79)

Kids 6-17 Number of children ages 6 to 17 living in respondent’s house at least half of the time (1)

0.70 (0.98)

Public Expenditures Per-pupil expenditures in respondent’s public school district in 2000-01 school year in dollars (3)

8368.3 (1328.9)

Discipline Problems Number of disciplinary actions per 100 students at school district level for 2000-1 school year (4)

44.5 (33.3)

Expulsions Number of expulsions per 100 students at school district level for 2000-1 school year (4)

0.36 (0.48)

Private Market Share Percentage of students in Census block group enrolled in grades 1-12 who attend private schools (6)

19.6 (17.4)

Single Dummy variable = 1 if respondent’s marital status is single (1)

0.12 (0.33)

Blue Collar Percentage of employed civilian population age 16+ in Census block group with blue collar jobs; blue collar defined as the following occupations: farming, protective services, food preparation, fishing and forestry, construction, extraction and maintenance, production, transportation, and material moving (6)

24.0 (12.4)

Tuition Tuition in dollars for private school nearest to the respondent (5)

8257 (5075)

Attend Public Dummy variable = 1 if respondent has children who attend public school (1)

0.38 (0.49)

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Attend Private Dummy variable = 1 if respondent has children who attend private school (1)

0.08 (0.27)

Very Conservative Dummy variable = 1 if respondent reports being politically very conservative (1)

0.07 (0.25)

Conservative Dummy variable = 1 if respondent reports being politically conservative (1)

0.25 (0.43)

Liberal Dummy variable = 1 if respondent reports being politically liberal (1)

0.19 (0.39)

Very Liberal Dummy variable = 1 if respondent reports being politically very liberal (1)

0.14 (0.35)

Buy Because School Good Dummy variable = 1 if one of the two most important reasons respondent bought house was because local public school is good (1)

0.46 (0.50)

Buy Because Low Taxes Dummy variable = 1 if one of the two most important reasons respondent bought house was because local taxes are low (1)

0.09 (0.29)

Tax Levy Passage Percent of school tax levies that appeared on local ballots during 2001 that passed by simple majority vote in respondent’s school district (11)

0.32 (0.47)

Catholic Percentage of respondent’s county that identified with Catholicism as religious affiliation in 1990 (8)

19.5 (10.3)

Welfare Recipients Percentage of residents in respondent’s Census block group who are receiving public assistance (6)

1.7 (2.7)

Agricultural Percent of property value in respondent’s school district that is agricultural in 2000 (9)

0.63 (1.36)

Owner Occupied Percent of occupied housing units in respondent’s Census block group that are occupied by owners rather than renters (6)

73.5 (20.3)

Open Enrollment Dummy variable = 1 if respondent’s school district allows any form of open enrollment (students from other school districts to attend) (7)

0.33 (0.47)

New Construction Change in per pupil value of new mineral, industrial, commercial, and railroad real (class 2) property in the public school district (10)

1077 (1050)

Voted Dummy variable = 1 if respondent says they voted in the last election (1)

0.87 (0.34)

Contributions to Democrats

Per capita Federal Elections Commission contributions to a single Democratic presidential campaign or National Committee for the 2004 or 2008 election cycles in respondent’s zip code (12)

0.47 (0.78)

Contributions to Republicans

Per capita Federal Elections Commission contributions to a single Republican presidential campaign or National Committee for the 2004 or 2008 election cycles in respondent’s zip code (12)

0.91 (1.80)

Means based on all 1186 survey respondents for variables that only appear in Choice No regression; means based on 322 school choice opponents for variables that appear in Reasons to Oppose regression. Sources: (1) = survey instrument, (2) = sample selection probit from

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Brasington and Hite (2012b), (3) = Ohio Department of Education (2002a), (4) = Ohio Department of Education (2002b), (5) = phone survey by Brasington’s graduate student assistants, (6) = GeoLytics (2002), (7) = Ohio Department of Education (2007), (8) = Bradley, et. al (1992), (9) = Ohio Department of Taxation (2003), (10) = Ohio Department of Taxation (2000), (11) = Ohio Department of Education (2002a), (12) = Huffington Post (2007).

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Table 2 Reasons to Oppose Choice:

Will Decrease Value of My House

Explanatory Variable Name

Parameter Estimate t-ratio

Explanatory Variable Name

Parameter Estimate t-ratio

Income 0.035* 2.31 Buy Because School Good

0.45* 1.94

Proficiency Test

-0.00031 -0.05 Single 0.48* 1.72

Agricultural 0.12* 2.19 Hours Worked -0.0079* -1.87

Owner Occupied

0.0050 0.98 Constant -2.44** -4.21

Dependent variable = Decrease House Value. ** = statistically significant at 1%, * = statistically significant at 10% level. Robust standard errors used. Log-likelihood = -721.5. Number of observations = 322, with 864 censored. Estimated jointly with sample selection probit shown in appendix, rho = 0.53, p-value 0.17.

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Table 3 Reasons to Oppose Choice:

Will Attract Worse Students to My Public School District

Explanatory Variable Name

Parameter Estimate t-ratio

Explanatory Variable Name

Parameter Estimate t-ratio

Attend Public 0.34* 2.43 Welfare Recipients 0.0056 0.20

Typical Public Poor -0.46 -1.22

Homeowners Association 0.31 1.51

Typical Public Not Good 0.052 0.17 Coach 0.36* 2.09

#Districts -0.0073 -1.35 Open Enrollment -0.36* -2.07

Graduate Degree 0.24* 1.65 Constant -1.82** -8.37

Expulsions 0.21* 1.69

Dependent variable = Bring Bad Students. ** = statistically significant at 1%, * = statistically significant at 10% level. Robust standard errors used. Log-likelihood = -755.7. Number of observations = 322, with 864 censored. Estimated jointly with sample selection probit shown in appendix, rho = 0.88, p-value 0.002.

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Table 4 Reasons to Oppose Choice:

Will Take Tax Money Away from Public Schools

Explanatory Variable Name

Parameter Estimate t-ratio

Explanatory Variable Name

Parameter Estimate t-ratio

Open Enrollment 0.50** 2.68 #Districts 0.0083 1.30

New Construction -0.00012* -1.73 Tuition 0.000022 1.26

Buy Because Low Taxes -0.072 -0.28

Private Market Share -0.0038 -0.79

Very Conservative -0.46 -1.29

Tax Levy Passage -0.34* -2.10

Graduate Degree 0.50* 2.41 Male 0.12 0.78

Income -0.0027 -0.19 Constant 1.04** 2.91

Minority -0.63* -2.21

Dependent variable = Take Tax Money. ** = statistically significant at 1%, * = statistically significant at 10% level. Robust standard errors used. Log-likelihood = -785.4. Number of observations = 322, with 864 censored. Estimated jointly with sample selection probit shown in appendix, rho = -0.56, p-value 0.11.

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Table 5 Reasons to Oppose Choice:

Will Help Support Religious Schools

Explanatory Variable Name

Parameter Estimate t-ratio

Explanatory Variable Name

Parameter Estimate t-ratio

Very Liberal 0.27 1.33 Age -0.0014 -0.26

Minority -0.18 -0.75 Income -0.0074 -0.65

Public Expenditures

0.00016** 2.79 Catholic

-0.011* -1.73

Attend Private -0.011 -0.05 Blue Collar 0.013* 2.32

Public Excellent

-0.13 -1.02 Discipline Problems

0.0033* 1.75

Private Excellent

-0.16 -1.28 School Volunteer

0.35* 2.48

Graduate Degree

0.34* 2.26 Constant

-1.07 -1.38

Dependent variable = Oppose Religion. ** = statistically significant at 1%, * = statistically significant at 10% level. Robust standard errors used. Log-likelihood -815.5. Number of observations = 322, with 864 censored. Estimated jointly with sample selection probit shown in appendix, rho = -0.77, p-value 0.002.

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Table A1 Oppose Choice or Not Regression

Dependent Variable = Oppose Choice

Explanatory Variable Name

Parameter Estimate t-ratio

Explanatory Variable Name

Parameter Estimate t-ratio

Voted 0.56** 3.86 Proficiency Test 0.0078** 3.62

Very Conservative -0.51** -3.40

High School or Less -0.51** -4.02

Conservative -0.090 -0.83 Less than Bachelor’s -0.43** -4.46

Liberal 0.061 0.56 Kids 0-5 -0.099* -1.77

Very Liberal 0.30* 2.12 Kids 6-17 -0.0062 -0.15

Income 0.00040 0.06 Inverse Mills Ratio -0.18 -0.55

Minority -0.28* -2.22 Contributions to Democrats 0.088 1.52

Age 0.0071* -1.96 Contributions to Republicans -0.045* -1.80

Male 0.11 1.24 Constant -1.33* -2.17

Results are shown for the probit that is jointly estimated with Decrease House Value probit. Results change slightly depending on the reason to oppose probit that accompanies the sample selection probit. ** = statistically significant at 1%, * = statistically significant at 10% level. Robust standard errors used. Number of observations = 1186.

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Acknowledgements: Thanks to Olivier Parent for constructive comments at the 2011 NARSC meetings. References Archer, Kim. School voucher law ruled unconstitutional by Tulsa district judge. www.tulsaworld.com,

3/28/12, accessed 9/24/12. Associated Press. Nation’s First Statewide Voucher Program Defeated at Utah Polls.

www.firstamendmentcenter.org, 11/7/07, accessed 9/29/10. Birnbaum, Michael. Senate Votes Against Reopening D.C. Voucher Program.

www.washingtonpost.com, 3/17/10, accessed 9/29/10. Bradley, Martin B., Norman M. Green, Jr., Dale E. Jones, Mac Lynn, and Lou McNeil. 1992. “Churches

and Church Membership in the United States 1990: An Enumeration by Region, State and County Based on Data Reported for 133 Church Groupings.” Glenmary Research Center, Atlanta, GA.

Brasington, David M.and Diane Hite, “School Choice and Perceived School Quality,” Economics Letters

116(3), September 2012a, p. 451-453. Brasington, David M. and Diane Hite. 2012b. School Choice: Supporters and Opponents. Contemporary

Economic Policy (forthcoming). Brasington, David M. and Diane Hite. 2010. Behind the Opinions: Why People Support School Choice.

University of Cincinnati Department of Economics working paper, September 2010. Brunner, Eric J., Jennifer Imazeki, and Stephen L. Ross. 2010. “Universal Vouchers and Racial and

Economic Segregation.” Review of Economics and Statistics 92(4), p. 912-927. Brunner, Eric J. and Jon Sonstelie. 2003. “Homeowners, Property Values, and the Political Economy of

the School Voucher.” Journal of Urban Economics 54(2), p. 239-257. Brunner, Eric J., Jon Sonstelie, and Mark Thayer. 2001. “Capitalization and the Voucher: An Analysis of

Precinct Returns from California's Proposition 174.” Journal of Urban Economics 50(3), p. 517-536.

Campbell, David, Martin R. West and Paul E. Paterson. 2005. Participation in a National, Means-Tested

School Voucher Program. Journal of Policy Analysis and Management 24(3):523-541. Cheplick, Thomas. Ambitious Voucher Bill Defeated in Georgia. www.heartland.org, 4/1/09, accessed

9/29/10. GeoLytics. 2002. CensusCD 2000 Long Form Release 2.0. East Brunswick, NJ. Howell, W. G., P.J. Wolf, D.E. Campbell, and P.E. Peterson. 2002. “School Vouchers and Academic

Performance: Results from Three Randomized Field Trials.” Journal of Policy Analysis and Management 21, p. 191-217.

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Hoyt, William H. 1996. Public School Choice, Property Values, and Investment in Public Education. Working paper, University of Kentucky.

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1 A companion study by Brasington and Hite (2010) investigates reasons why people support school choice.

2 See Brasington and Hite (2012b) for the exact regressions that create the inverse Mills ratio used in this study.

3 The largest associated Chi-square statistic is 0.88, well below the critical level.

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4 These three variables were relatively highly correlated with VOTED and not highly correlated with included

explanatory variables in the OPPOSE CHOICE probit, and thus seemed like promising instruments. All three variables are statistically significant explanatory variables in the VOTED probit stage of the Rivers and Vuong test. 5 The t-ratio of the residual from the VOTED regression is -0.59 in the OPPOSE CHOICE probit, with a p-value of

0.55. 6 The LR test statistic is 0.0013, with a marginal probability of 0.97 and a chi-square value of 6.64. The Moran’s I

test statistic is 0.056 with a marginal probability of 0.40. 7 Increased numbers of schools in the same geographic area could also provide enhanced opportunities for choice

in an open-enrollment district.