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September/October 2010

Is your elementary school on a track for closure?
by Joe Pacha, Sherrilyn Billger, Frank Beck and Norm Durflinger

Joe Pacha and Norm Durflinger are both with the Educational Administration and Foundations Department at Illinois State University. Sherrilyn Billger is with ISU’s Department of Economics and Frank Beck is with ISU’s Department of Sociology.

Closure project

When researchers from Illinois State University approached The Illinois School Board Journal last spring regarding a series on the factors that influence school closure, we realized that the material being presented was going to demand special treatment in the magazine.

This is the first installment in a series that will be presented over the next three issues. Subsequent articles will deal with the factors that affect school closure in junior highs and then high schools.

At the conclusion of the series, the Association will package the three articles together and post it as a single document to download from

If you have information to add from your district’s experience with school closure, please contact Linda Dawson at Your comments can be included with subsequent articles and included in the final package.

I n the 1940’s, Illinois had more than 11,000 school districts, most of which were one-room schools. Since then, district consolidations and school closures have whittled the number to 866, as of July 1, 2010.

Little research exists about the predictors and outcomes of school closure. Research attempting to do so used only part of the measures for a limited time. If in-depth analyses of the causes and consequences of school closure have been studied, it has been on a case-by-case basis.

As Illinois State University researchers, we worked together three years gathering data from 1972 to 2005 for a study of Illinois school closure to answer the following questions:

• What are the demographic, economic and educational causes of school closure?

• What trends lead up to a closure decision and which are most important?

• What are the demographic, economic and educational impacts resulting from school closure? Are these effects immediate or do they manifest over time?

• Under what circumstances does the closure of a school bring about demographic, economic and educational benefits for a county, district or community?

We wanted to understand the relative size and importance of these forces, expecting that multiple factors are important and at work in these cases. We also wanted to understand the issues in order to help school boards and administrators better understand what is involved as they make difficult decisions concerning their schools.

We believe that our analysis confirms that school closure is not tied to the two most often cited issues — money and enrollment. Other issues and factors come into play in the decision making process and are important for both legislators and school leaders to understand.

Predictors over time

Graphs 1-4 represent the significant predictors of school closure over time: the education fund; per pupil operating expenditures; enrollment; and equalized assessed valuation. These graphs represent a 10-year history of each of these four variables just prior to the closure of schools. It is important to remember that this is an aggregate of all the closed schools. The bottom line of the graph represents “time” and starts at 10 years and ends with closure at zero.

So what do these charts tell us about closing or not closing schools?

Graph 1, the education fund, shows a steady increase over the 10 years prior to school closure. An interesting phenomenon happens about two years before closure: the education fund falls. This should be predictable since there is a similar leveling in the EAV (shown in Graph 4), which would also cause stagnation in the ability of the school to raise funds. Couple this graph with Graph 3, enrollment, and it becomes apparent that with declining enrollment that the gap between the needs (students) and the resources (per pupil operating expenses) widens to a point where the community is unable to provide the support needed.

Graph 2, per-pupil operating expenditures, shows a steady increase throughout the 10-year period. What is striking is that as the enrollment falls, the cost to operate the school continues to increase at a steady rate, demonstrating a major factor in school closure. Additionally, the education fund and the operating cost per pupil of closed schools were still lower than that of the schools that remained open.

Graph 3, school enrollment, is very telling and demonstrates why this is one of the main predictors of school closure. When declining enrollment is combined with increased operating expenditures per pupil and increased education fund expenditures, the formula for school closure is high. Conversely, when enrollment increases, operating expenditures per pupil decrease and the education fund stabilizes, so the health of the elementary school is solid.

Graph 4, equalized assessed valuation (EAV), demonstrates an average increase of about $12,000 per student over the 10-year period before school closure. When compared to schools that remained open, this amount is significantly lower and is highly connected to the inability of the school to raise funds in the same manner as the open schools.

Additional predictors

Not all the predictors can be shown over time, so to what degree do they affect the closure overall? The analysis of the data suggests 25 variable predictors as shown in Table 1 and Table 2. These tables provide a quick look at the predictors and their values to help understand their relationship to school closure.

Table 1 addresses “education/ school” predictors; Table 2 addresses “community” predictors.

To read the tables, use the following formula: “Increasing (insert the variable name) (insert the column designation) the likelihood of closure.” The first variable would read: “Increasing enrollment significantly decreases the likelihood of closure.”

Individually, what do these variables mean and how can we better understand them in the context of the whole?

First, several variables do not influence school closure whether they increase or decrease. These variables have been designated on the tables as “neutral.”

Three variables increase the likelihood of school closure: EAV per pupil; teacher experience; and percent of students not meeting math goals.

• An increase in EAV per pupil will significantly increase the likelihood of school closure. For every increase of $100,000 of EAV per pupil, the probability of school closure increased by 1.8 percent.

• An increase in teacher experience increases the likelihood of school closure. Having teachers with less experience is a double edged sword: it is good for the budget but not necessarily good for student learning.  

• An increase in students not meeting math goals increases the likelihood of school closure. Every parent and taxpayer wants their school to perform well and to have students attain the goals established for them. Not meeting academic goals increases the likelihood of closure in elementary schools.  

What will help?

But what variables actually help decrease the likelihood of an elementary school closing? If known, school districts could potentially do something about these variables in order to decrease the likelihood of closure.

Those nine variables are: enrollment; expenditures per pupil; elementary-only district; pupil/teacher ratio; percent exceeding in reading goals; poverty rate; being in an urban area; percent of immigrants; and percent of workers in agriculture. Looking at each individually:

• Increasing enrollment will significantly decrease the likelihood of closure. When enrollment is increased by 1 percent, there is a 10 percent lowering of the likelihood that the school will close. That is significant and makes common sense, but what is most important is the power of this variable.

• Another significant predictor was the type of district. If a school is in an elementary-only district, it is 5 percent less likely that it will close than if it is in a unit district.

• Increasing expenditures per pupil will significantly decrease the likelihood of closure. Higher expenditures per pupil are not usually desired by taxpayers. However, even while the closed schools’ graph exhibited higher expenditures per pupil, the closed schools were still lower than their open school counterparts.  

• Increasing poverty rate significantly decreases the likelihood of closure. Increased poverty rates are not usually welcomed by schools; however, more poverty students mean funds from both the state and the federal levels.

• Increasing the pupil/teacher ratio decreases the likelihood of closure. A higher pupil/teacher ratio would mean fewer staff needed for more students; however, this may be hard to achieve in small schools with small numbers at each grade level.

• Increasing the percent of students who exceed in reading goals decreases the likelihood of closure. Increasing the percent exceeding in reading goals would be a worthy goal for all schools. If a school can increase its test scores, it’s more likely to remain open!

• The more urban the area the likelihood of closure decreases. Being rural increases the likelihood of closure and the more rural a school is, the more likely it will close.

• Increasing the percent of immigrants in the community decreases the likelihood of closure and is a way to keep the school open. More research will need to be done to determine the factor of this variable.

• Increasing the percent of agricultural workers decreases the likelihood of closure and is also a way to keep the school open. Perhaps the stability factor of farmers and those attached to agriculture may be at play here.

What does it mean?

What conclusions can be drawn from this? Breaking them into three parts will make it easier to better understand the overall ramifications.

First, when comparing closed and open elementary schools without taking into account other similarities or differences, the following are important:

• Schools that remained open tended to have a higher percentage of students exceeding in math and reading than those that closed.

• Schools that closed were in more rural places and in unit districts.

• Schools that remained open had higher EAV, enrollment, expenditures per pupil and pupil/teacher ratios.

Second, when looking at closed elementary schools alone, the following findings are important:

• A downward trend in enrollment precedes closure by four to eight years.

• A downward trend in the education fund seems to precede closure by two to five years.

• A pronounced upward trend in per-pupil operating expenditures precedes closure decisions.

• EAV continues to increase before closure, but this relationship is less clear and needs more research.

Third, when comparing open and closed elementary schools that are similar on all other characteristics, the findings are:

• Larger enrollments have a significant negative effect on the likelihood of school closure.

• Larger expenditures per pupil decrease the probability of closure.

• Test scores, especially in reading, are important in the decision making to close.

• The economic health of communities (e.g., household income, median home values, vacancies and unemployment) are not strongly related to the probability of closure.

• Larger immigrant populations in communities are linked to lower closure probabilities.

• The greatest school level predictors of closure are fiscal characteristics of the district and enrollment.

• When all school and community level effects are compared within levels of “ruralness,” consistently, schools in the smallest and most isolated of rural counties (i.e., counties with no single community larger than 2,500 residents) have the highest probability of closure. This is compared to schools in other rural counties with larger communities all the way up to and including schools in metropolitan counties.  

When school board members and administrators compare the above findings to their own school(s), they may find one or two of the characteristics of a school that closed. Does that mean their school is doomed to close as well?

Probably not. Careful analysis of all of the predictors must be made, not just one or two. However, one or two factors can be a warning sign of things to come. Taking a careful look at all of the factors together can help give school leaders the answers they need and show them where to concentrate their efforts.

Part II: Junior Highs (November/December)

Part III: High Schools (January/February)

For more information

If individual schools would like a quick determination of the probability of closure, please contact the authors.   By providing some basic data this can be done in a short amount of time. In-depth analysis of the probability of school closure will take additional time and research but can be accomplished for a nominal fee to cover expenses.

For additional information concerning individual school closure predicted probabilities contact:

• Frank Beck — or 309-438-7770

• Sherrilyn Billger — or 309-438-8720

• Norm Durflinger — or 309-438-8989

• Joseph Pacha — or 309-438-8575


Alan J. DeYoung, The Life and Death of a Rural American High School: Farewell Little Kanawha, New York: Garland, 1995  

David R. Reynonds, There Goes the Neighborhood: Rural School Consolidation at the Grass Roots in Early Twentieth-Century Iowa, Iowa City, Iowa: University of Iowa Press, 1999

Methodology for the study

Robust sources of information and data were used to find predictors of school closure in order to get as clear a picture as possible of all the components that could be involved. Data was acquired from 1986–2005. The trends and predictors in the accompanying graphic were part of the analysis in order to determine the factors that could impact school closure.

Standard statistical techniques were used to determine which predictors had the strongest relative effect on school closure, with 25 predictors giving understanding to the closure of elementary schools. Furthermore, because of the power of this research methodology, models of what happens prior to school closure can be made. An individual variable can be modeled to show what is happening years before school closure.

This research was funded by a grant from the Cooperative State Research, Education and Extension Service (CSREES) of the United States Department of Agriculture (USDA).

Examining three recent closures
by Linda Dawson

 Linda Dawson is an IASB director/editorial services and editor of The Illinois School Board Journal.

Closing a school is never easy … not for the teachers, the students, the parents and especially not for the board of education that has to make the final decision.

The three-part series that begins in this issue of The Illinois School Board Journal outlines a number of factors that researchers at Illinois State University have found are precursors to school closure. The factors vary depending on whether the school is for elementary, junior high or high school students. But the authors were adamant about one thing: the most often cited reasons of money and enrollment are not enough in and of themselves to doom a building to close.

The following three districts are among those that have recently needed to close one or more schools for varying reasons:

Aurora West USD 129

Mike Chapin, community relations director for Aurora West USD 129, said his board’s decision to close an elementary school for the 2009-10 school year did come down to a question of enrollment and budget, but another deciding factor was the age of the building.

The Lincoln Elementary building was more than 100 years old, Chapin said, and had the district’s smallest enrollment. Plus, room for students was available in other nearby schools.

“During a public hearing at the school,” he said, “it came down to the fact that we had a significant budget hole to fill and the school was so old.”

Closing Lincoln saved the district more than $900,000 in operating costs for fiscal year 2009-10.

Cairo SD 1

Cairo SD 1 at the southern tip of Illinois voted in March to close Bennett Elementary for the coming year to balance the district budget. According to the district’s website, the building had been built in 1949 and was “a symbol of education in Cairo.” The 145 affected students will be moved to Emerson Elementary, where class size will be about 20, compared to a 14-student average at Bennett. The district expects to save $600,000 in 2010-11 and $300,000 the next two years by closing the school, according to a story posted at

Monmouth-Roseville CUSD 238

When districts consolidate, the hope of the affected communities is often that everyone will be able to keep their buildings open. While that can be true in the short term, financial realities may intervene resulting in school closures.

In 2005, Monmouth USD 38 and Roseville CUSD 200 consolidated to form Monmouth-Roseville CUSD 238. On March 9, 2010, the school board voted to close two schools (Willits Primary School in Monmouth and Roseville Elementary) and drew the ire of citizens.

According to the Monmouth Review-Atlas, Superintendent Paul Wohlke told the board at a March 5 meeting that “the only acceptable option — based on education needs and transportation — was to close and sell Willits and Roseville, move Roseville Pre-K to the junior high school, and all second and third grades to Harding and fourth through sixth grades to Central.”

Wohlke had based his options on class sizes, keeping the youngest students on the ground floor in buildings, transportation needs and long-term maintenance costs, in addition to which scenario would cause the least disruption.

“It is not an easy decision to wrestle with,” Wolke said. “First and foremost, I’m responsible for the education of our children, that’s that paramount issue that needs to be kept in forefront as we look at what’s before us.”

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