LPA Report on School Finance: A Critique

The legislature commissioned the division of post-audit (LPA) to study the cost of providing a “suitable” education. You can find the executive summary (PDF) of the study here, and the study itself (PDF) here.

Kenneth Daniel, small business owner and publisher of Kssmallbiz.com, is one severe critic of the study.

Start with FULL ANALYSIS: NEW KANSAS SCHOOL COST STUDY. It didn’t take long for the reader to know just what Daniel thought of the work: “the report is built on tainted data, false assumptions, breathtakingly improper methods, and absolutely no science.” Worse, he accused the consultants and the LPA of fraud: “both LPA and Duncomb and Yinger, the consultants hired by LPA, knew the data was tainted, but used it anyway.”

Such a charge may cause the average reader to roll his eyes. But since the validity of a claim is not necessarily linked to the politeness of its presentation, let’s continue reading. Daniel’s case is based on the assertion that districts systematically inflate the number of three groups of students, low-income, special-education, and English-language learners, which bring more state money into their treasuries.

Low Income

The LPA report says1:”Since 1999-00…the number of students from low-income families has increased by 26%.”

This statement is completely false. The U.S. Census Bureau reports fewer, not more, Kansas students from low-income families.

Both the LPA and Daniel may be right, actually. Participation in the free lunch program does depend on income–but there are several reasons why participation may increase even if the “true” number of poor decreased. It may be, for example, that some low-income families were not actually signed up before. Which brings us to:

Again, districts are paid bounties for poor kids, and they keep “finding” more and more of them.

Instead of using Census data, the most reliable data available on how many “children in poverty” each district has, LPA furnished D&Y with heavily-falsified “free lunch” figures provided by school districts.

If a district is paid more for the number of free-lunch children it enrolls, why would it NOT conduct an aggressive campaign to identify students who qualify?

Daniel presents a chart that compares Census bureau numbers of children in families with incomes that are 130 percent of the poverty level with the number of children in the free lunch program. The number of free-lunch students is, for the year 2003, 60 percent higher. Given that 130 percent is the cutoff for free lunches, there may indeed be some sloppiness in the number of free-lunch students. Given that districts get extra money for low-income students, it’s entirely possible that the state is overpaying on its own formula.

Special Education
The LPA report says5:”Since 1999-00, the number of students enrolled in Special Education has increased by 16%…

While the statement is true, it is extremely misleading. It is true that “the number of students enrolled in Special Education” has increased, but it is not true that there has been any significant change in the kids. Because districts are paid huge bounties for Special Education, districts keep hiring more and more special ed staff and “finding” more and more special ed kids.

The possibility of institutional bias in identifying students are “special ed” cannot be discounted. But it is speculative.

English Language Learners
Daniel argues also that the number of ELL students is systematically inflated by the LPA report.

D&Y did not like the data that LPA furnished them in this category. So they threw that data out and substituted Census statistics. This greatly increased D&Y’s “found” costs for ELL kids.

So how does this report, fueld by “blatant dishonesty,” play out?

The larger districts that will be hurt the most are the Johnson County districts and suburban districts around Topeka and Wichita. Low-enrollment districts statewide will be devastated.

Sounds like the making of a classic struggle based in geography-based interests.

Other Criticisms
Daniel offers more criticisms of the LPA report.
– Duncomb and Yinger, authors of the report, systematically produce higher cost estimates than other consultants.

– The “Successful School Method” of estimating school costs (define success, identify who does it, and find out how much they spend) is better than the “Professional Judgement Method” (how much do you think you need?) Yet only the 2002 Kansas Augenblick and Myers Study used the Successful School Method–and then discarded it in favor of the Professional Judgement Method, which produced a much higher figure.

– Other, less desirable methods include the “Resource Cost Model Method,” which imaginary “resources … costs … and … relationships,” and the “Evidence-Based Method,” which is “a shortcut” for the Professional Judgment method.

– The LPA report used a “Cost Function Method,” which, Daniel says, is mere alchemy.

– The LPA report confused correlation with causation. (The cock crows when the sun rises–but does not cause the sun to rise.) This may be a valid criticism as far as it goes, but Daniel confuses the extent of a correlation with its statistical significance. He suggests that correlations of .4 and below as not being statistically significant. It’s been a while since we’ve reviewed statistics but we’re pretty sure that even a correlation of .25 can be statistically significant. (The correlation number refers to the strength of the relationship. Significance, by contrast, refers to the likelihood that the relationship occured by chance. These are two different concepts.)

– On the other hand, Daniel is on firmer ground when he discusses the meta-analyses conducted by Greenwald, Hedges, and Laine (who find a positive relationship between spending and achievement) and Eric Hanushek (who finds no such relationship).

Useful Message, Flawed Presentation
In short, Daniel does a service by bringing some attention to possible flaws in the LPA report. On the other hand, the strident presentation mars the package, and could cause some people to dismiss the analysis entirely.

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