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Parental Valuation of Charter Schools and Student Performance

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Author: James VanderHoff

Cato Journal

Parental Valuation Model
Charter schools are not allowed to charge tuition or make admission decisions based on entrance exam scores. Consequently, charter schools that have more applications than openings conduct a random admission drawing. Students who are not chosen in the lottery are put on the wait list and are contacted if space becomes available. Because parents incur costs to apply, which may or may not lead to enrolment in the charter school, the number of unsuccessful applications provides a better gauge of parental valuation than responses to survey questions or school changes, some of which are due to employment changes, personal reasons, and other factors unrelated to school quality. Also, by examining wait list data, parents can determine the value of charter schools—a long list means a higher-valued school.
The average wait list for the 42 New Jersey charter schools analyzed in this article is 184 students, and the average number of openings for new students is 40. Thus, on average, the preferences of over 80 percent of parents who desire a particular charter school would not be represented in any survey limited solely to the charter school students. Moreover, one would not expect charter
schools with waiting lists of several hundred students to be similar
to charter schools with no waiting lists. Studies of charter school
students give equal weight to oversubscribed and undersubscribed
charter schools with equal enrolments.
The model used in this article relates school value to factors that affect parental choice: academic effectiveness, school resources, and the characteristics of students and schools—both for charter schools and traditional public schools. The model can be stated as follows:
(1) WAITc,t = f(SCOREc,t, SCOREd,t, STUDENTSc,t, STUDENTSd,t, SCHOOLSc,t),

where

WAITc,t ,the dependent variable, is a proxy for parental valuation of the charter schools, as measured by the number of students wait listed for charter school c at time t;
SCOREc,trepresents the test scores of students at charter school c at time t;
SCOREd,t indicates the grade equivalent test scores of students at the regular public school in the home district;

STUDENTS indicates student characteristics, including race and economic situation;
SCHOOL reflects school characteristics, including resources (measured by per student expenditures), class size, teacher salaries, student-teacher ratios, instructional time, suspensions, number of grades in the school, and two binary variables—one indicating schools that emphasize academic excellence, the other indicating a school located in a low income urban area.
Because the distribution of WAIT, a nonnegative integer, does not conform to requirements for efficient estimation with a standard regression model, a negative binomial regression provides efficient estimates of the model parameters. The statistical model assumes that the distribution of WAIT values depends on the number of openings for new students; OPENINGS is the exposure variable.

Conclusion
This article finds that parents choose charter schools based on academic effectiveness and endorsement of academic goals. It thus supports a basic tenet for the belief that school choice will improve public school academic effectiveness. The New Jersey data illustrate that charter schools are not equally effective (as measured by student test scores), equally preferred (as measured by waiting lists), or equally funded. The analysis indicates that a 10 percent increase in a charter school’s test scores will increase the number of students on its wait list by at least 63 percent. The characteristics of students and schools, both regular and charters, do not generally affect the size of the wait list.

 

To read more: http://object.cato.org/sites/cato.org/files/serials/files/cato-journal/2008/11/cj28n3-6.pdf

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