I’ve noticed a pattern in a few recent school funding proposals, mostly emanating from shoddy, haphazard proposals developed on behalf of the CANs (ConnCAN & its close relatives) and often with “technical support” of Bryan Hassel of Public Impact. Let’s call it school finance reform in a CAN.

These new simplified school funding formula proposals, framed under the “money follows the child” ideology are intended to make state school funding formulas more “transparent” and to allow for more equitable and predictable flow of funding to charter schools or other non-district schools.

In each proposal (ConnCAN’s Spend Smart & The Tab, or Rhode Island’s new formula [albeit laced with other problems unique to RI-see post]), among a variety of other major overlooked factors, arbitrary and unfounded recommendations, exists a seemingly innocuous proposal regarding how to target aid for variations in student needs across districts.

As the authors of ConnCan’s recent Spend Smart brief explain deeply embedded in a footnote… you really only need to use a single factor to get state aid targeted to the right schools and that factor is the share of children qualifying for FREE OR REDUCED PRICED LUNCH. There’s no need for a special factor for limited English proficient/English language learner populations, or anything else. It’s all pretty much correlated to free and reduced lunch. (Hassel’s previous report for ConnCan, The Tab, included a trivially small LEP/ELL weight instead of none at all).

First, this assumption is patently wrong to begin with and is never actually validated by the authors of these proposals. But let’s set that aside for the moment. I’ll have a future post where I use actual data to show just how freakin’ wrong the assumption is.

But why would they propose this anyway? Well, it turns out to be really simple. If a state has a fixed sum of money to distribute (generally how it works), the CAN game is to figure out on what basis might charter schools get the maximum share of that money – regardless of who really needs it most. That is, what measures CAN they choose for weightings which will drive money to charters. Charter schools do tend to operate in poorer communities (relative to state averages), but a) serve the less poor among the poor, b) serve few or no LEP/ELL children, and c) incidentally, also serve few or no children with disabilities (as has been addressed on my blog regarding NY and NJ charter schools, and will be addressed soon regarding CT charters – numbers already run, charts forthcoming).  I’ll set aside c) for now.

So, the way to maximize charter funding, is to give a single weight for children qualified for free OR REDUCED PRICE LUNCH, and to negate any weight for LEP/ELL children (or make it as small as possible). That way, charters will get the same weight for kids whose family income falls between the 130% poverty level and 185% poverty level as neighborhood schools get for children below the 130% poverty level (This distinction is NOT TRIVIAL), where neighborhood schools have far more of the lower-income children. Any money that would have gone to LEP/ELL children can be rolled into a bigger weight for free/reduced lunch children, channeling a larger share of the total funding available to charter schools.

While not specifically addressed in these proposals, one would imagine that the same pundits would also favor flat, lump sum, or census based funding for special education, not differentiated by disability type, such that every school or district gets a specific dollar amount for special education based on a fixed share of their enrollment – a) whether they serve any special education students at all, or b) whether they only serve mild specific learning disability students, and none more severe. Watch out for this one as well!

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Note: I’m sure that many will respond to this post by arguing that charters get severely shortchanged on state aid anyway, and that even if they make out okay on these adjustments, the lack of funding for such things as capital outlay and facilities more than offsets the difference. That’s a topic for another day. But, suffice it to say, existing comparisons like those made in the recent Ball State/Public Impact (imagine that) study are grossly oversimplified (as I explain regarding NYC schools, here: http://nepc.colorado.edu/publication/NYC-charter-disparities (page 23)). For example, typical crude comparisons never address whether having few or no special education children (relative to averages for district schools) result in cost reductions (per pupil) that might actually be greater than facilities average annual expenses per pupil.

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Follow up figure for those who asked:

Note that using only a weight on free or reduced lunch would drive the same amount of supplemental funding to Torrington as to Norwalk or Danbury, despite large differences in LEP/ELL populations. So too would any charter school that has comparable low income population to Danbury, Stamford or Norwalk, even if that school had no LEP/ELL children. There may be other valid differences that require additional attention. Even this graph is too crude to give us the full story. The bottom line is that one must at least evaluate the distributions of children by need categories across districts and settings before making such bold, but oversimplified policy recommendations.

Here’s Rhode Island:

The issue here is similar in that Central Falls in particular (imagine that) gets shafted by failure to independently address differences in ELL/LEP concentration. While RI has few districts, and has a specific cluster of high poverty districts, the rates of LEP/ELL children across those districts vary from 5% to 20%. But, as I’ve explained previously, the RI formula and logic behind it have numerous other empirical and logical gaps. see: https://schoolfinance101.wordpress.com/2010/07/01/the-gist-twists-rhode-island-school-finance/

This is another one of those mundane school finance formula posts. This one is focused on media and political spin in New York State around the recently adopted state budget and proposed school aid cuts.

Yesterday, I had the displeasure of reading a New York Post piece in which New York Governor Cuomo and the Post were validating how and why the proposed budget cuts would not and should not compromise the quality of New York State public schools. But this article – both the Post explanations and especially the Governor’s spokespersons explanations present a massive distortion of how the proposed cuts actually affect different types of districts across New York State.

Let’s break it down:

Political Spin

Here’s the public appeal, political spin on why cutting state aid to schools in New York really causes no harm:

The state’s student population dropped to 2.7 million from 2.8 million — or 4.6 percent — during that period.

And during that same span, the number of rank-and-file teachers grew to 214,000 from 194,957 — a 9.8 percent increase.

As a result, overall public-school expenditures more than doubled, from $26 billion to $58 billion statewide.

And:

“The huge growth in school bureaucracy and overhead is disturbing, especially since many schools are threatening to fire teachers,” Cuomo spokesman Josh Vlasto said. “School districts clearly have more than enough to do more with less.”

Read more: http://www.nypost.com/p/news/local/supervisor_bloat_hikes_overhead_gnbt3xbRu6hnqPRqrCTZvO#ixzz1IkEkATFa

Very simple: New York State school districts have added a whole bunch of administrators they don’t need – administrators who are obscenely high paid, and really just a massive waste. That is, if we accept the numbers reported above. But I won’t go after those in this post, because the argument is flawed on so many other levels. I will say that it is a foolish stretch to argue that administrative bloat has caused a doubling of per pupil spending across New York school districts.

Essentially, the argument here is that since there is so much bloat and waste – REGARDLESS OF WHERE THAT BLOAT AND WASTE EXISTS, if we cut aid to districts, they can simply cut that bloat. Of course that logic doesn’t work so well if the proposal is to cut aid from districts which are not the ones with the reported bloat.

Academic Analysis on Relative Efficiency and State Aid in New York

It is indeed interesting that the NY Post and Governor’s office have chosen to focus on spending increases since 1997.  Spending in many New York school districts, teacher salaries and administrative salaries in many New York school districts did escalate over this period. But why? What’s going on there? In what districts and what parts of the state is spending increasing, and does state aid play any role in those increases? Perhaps most directly on the question above, are some of those increases in spending actually leading to inefficiency, and is there any component of state aid that might be encouraging inefficient spending in school districts? If that was the case, we’d probably want to look first at those state aid programs as a place to cut.

Here are some summaries of findings from studies on New York State’s STAR tax relief program, which provides a sizeable chunk of financial support in systematically larger amounts to affluent communities:

Eom:

We test this hypothesis by examining the introduction of New York State’s large state-subsidized property tax exemption program, which began in 1999. We find evidence that, all else constant, the exemptions have reduced efficiency in districts with larger exemptions, but the effects appear to diminish as taxpayers become accustomed to the exemptions.

http://bk21gspa.snu.ac.kr/datafile/downfile/%EC%97%84%ED%83%9C%ED%98%B8%28GSPA-SD%2907_1.6.8.pdf

Public Budgeting & Finance / Spring 2006

Eom & Killeen:

Similar to many property tax relief programs, New York State’s School Tax Relief (STAR) program has been shown to exacerbate school resource inequities across urban, suburban, and rural schools. STAR’s inherent conflict with the wealth equalization policies of New York State’s school finance system are highlighted in a manner that effectively penalizes large, urban school districts by not adjusting for factors likely to contribute to high property taxation. As a policy solution, this article presents results of a simulation that distributes property tax relief using an econometrically based cost index. The results substantially favor high-need urban and rural school districts.

http://eus.sagepub.com/content/40/1/36.full.pdf+html

Education and Urban Society November 2007

Rockoff:

I examine how a property tax relief program in New York State affected local educational spending. This program, which lowered the marginal cost of school expenditure to homeowners, had statistically and economically significant effects on local government behavior. A typical school district, which received 20% of its revenue through the program in the school year 2001- 2002, raised expenditure by 4.1% and local property taxes by 6.8% in response. I then examine how the preferences of various groups of local taxpayers affect educational spending by identifying systematic variation across districts in the response to fiscal incentives. These results support the hypothesis that homeowners are more influential on local expenditure decisions than renters, owners of second homes, or owners of non-residential property.

http://www0.gsb.columbia.edu/faculty/jrockoff/papers/local_response_draft_january_10.pdf

Recap of the Research

So, let’s recap. What do we know about NY state aid and the potential link to the supposed inefficiencies to which the NY Post article and governor’s spokesman refer:

1. That STAR aid in particular is allocated disproportionately to more affluent downstate school districts;
2. That STAR aid, by reducing the price to local homeowners of raising an additional dollar in taxes to their schools, encouraged increased local spending on schools;
3. That when the relative efficiency of school districts is measured in terms of increases in measured test scores, given additional dollars spent, STAR aid appears to have encouraged less efficient spending. STAR aid enabled affluent suburban districts to spend on other things not directly associated with measured outcomes, but things those communities still desired for their schools.
4. That STAR aid contributes to inequities across districts in a system that is already highly inequitable.

What’s happening now?

As I have shown here, in recent years, STAR aid continues to be allocated inequitably, benefitting systematically wealthier districts.

https://schoolfinance101.wordpress.com/2011/02/04/where%E2%80%99s-the-pork-mitigating-the-damage-of-state-aid-cuts/

https://schoolfinance101.com/wp-content/uploads/2011/02/figure3.jpg

Funding inequities persist across New York state districts, with affluent suburban districts far outspending their poorer urban neighbors.

See www.schoolfundingfairness.org

But, the proposed funding cuts are not targeted at the districts which are most likely contributing to “inefficient” spending growth (if it is really inefficient).

The state aid cuts are not targeted to the state aid which seems to be stimulating less efficient spending and exacerbating inequity.

Rather, the proposed state aid cuts fall disproportionately on general foundation formula aid for those districts which have already been left in the dust by their more affluent neighbors. https://schoolfinance101.wordpress.com/2011/02/04/where%E2%80%99s-the-pork-mitigating-the-damage-of-state-aid-cuts/

https://schoolfinance101.com/wp-content/uploads/2011/02/figure5.jpg

How does that make sense?

Quite honestly, the argument made in the Post, and by the governor’s spokesperson is really obnoxious and misguided, given the distribution of the planned cuts.

Analogy for the day

Let’s say we have a state aid program for personal transportation and we have some really rich communities and some really poor communities.

Let’s assume no mass transportation exists.

Let’s say we (the state) decide to give individuals in the poor communities $200 per month to help them purchase, insure and maintain a personal vehicle –  a freakin’ car… and pretty damn cheap car that is minimally functional and questionably reliable. The $200 per month is pretty much all they’ve got. They’ve got few or no personal resources to contribute to an upgrade, and pretty much live month to month on maintenance and insurance.

We use another pot of aid to give $100 per month to residents of the rich community, who’ve already gone out and purchased Bentleys and Ferraris, and mostly use that money for occasional detailing of their vehicles which they might otherwise forgo (perhaps not) or perhaps an enhanced satellite radio subscription they might not have otherwise chosen and one that includes channels the never really expect to use (typically, they would have gotten the most expensive subscription anyway. As the truly rich like to point out, no-one who’s truly rich would ever dare ask how much it costs to maintain a yacht).

All of the sudden, the state budget is tight and a new report from some think tank comes out showing that in the past 10 years, more and more NY residents are driving Ferraris and Bentleys and more and more of them get their cars detailed on a monthly basis and have the most expensive satellite radio subscription. It’s an abomination. Therefore, cutting aid certainly causes no harm.

So policymakers pass their first on-time budget in years, cutting 10% of that $200 per month that currently supports basic car purchases in the poor communities! They ignore entirely that the $100 per month to the rich communities even exists.

Of course, once we’ve cut that money and ignored the other, what we now have is a set of poor communities that is less able to insure and maintain their economy vehicles. And about those Ferraris and Bentleys? We haven’t even touched their detailing subsidy.

Alternative title: Why Hassel with research, data and facts?

I was called up on this past week to review a new policy brief on reforming Connecticut’s education funding system – or Education Cost Sharing formula. The brief, titled Spend Smart: Fix Connecticut’s Broken School Funding System seemed simple enough on its face, but as I looked deeper, ended up being among the most offensively shallow and poorly documented reports I have ever seen.

Further, some of elements of the report which were stated as fact, but entirely unsubstantiated would actually lead to funding policies that significantly disadvantage some of the state’s highest need children. Even worse, this brief was accompanied by submitted legislation that included these ill-conceived policies.

But this post is only partly about this new brief produced by ConnCan, with an eclectic mix of authors put forth in reformy manifesto style. Nearly every attempt to ground “facts” in the brief was tied to previous ConnCan briefs, which themselves included little or no substantiation.

The common denominator in this brief and those on which it relies, as well as the accompanying legislation, appears to be Bryan Hassel of Public Impact. Hassel has also played a role on previous haphazard manifesto-like school funding reports including Fund the Child. Bryan Hassel has also been mentioned as the outside expert to advocate on behalf of ConnCan for school funding reform in Connectictut, including testifying in favor of the proposed legislation. See: http://blog.ctnews.com/kantrowitz/2009/12/03/1208/, or the ConnCan tweet:

Brian Hassel, co-dir. Public Impact: SB 1195 would “catapult Connecticut into a national model for schools” #edreform #getsmartct

http://twitter.com/#!/conncan/status/51061576467361792

Tangentially, Bryan Hassel and Public Impact were also involved in the production of the deeply problematic analysis of charter school funding disparities released last year, which I critique in part, in my recent work on New York City charter schools.

There comes a point where I encounter enough different reports linked to single organization and author, where those reports are so shockingly bad that I simply can’t hold back anymore.

The following three examples, all connected back to Public Impact and Bryan Hassel, provide evidence of the utter methodological incompetence of this organization and their/his complete disregard for a) existing rigorous research, b) legitimate analytical methods and data, and perhaps most disturbingly, c) significant adverse consequences of performing shoddy analysis and making bold but haphazard policy recommendations.

Below are three of my related critiques of policy “research” (used as loosely as I can imagine) with ties to Public Impact and Bryan Hassel. I offer these critiques in particular to any policy makers who might believe it reasonable to rely on this junk, or the organization that produces it.

Example 1: Public Impact and ConnCan’s Funding Reform Proposals

http://nepc.colorado.edu/files/TTR-ConnCan-Baker-FINAL.pdf

Here are just a few examples from my review of Spend Smart. The Spend Smart brief essentially argues that the Connecticut finance system is broken (it may well be, and I think it is), and that it should be fixed with a simple school funding formula with a single weight on children qualified for free or reduced price lunch.

This particular brief stated a number of supposed “facts” about the status of the current system, few or none of which could be substantiated with information provided, and some which were clearly unchecked and simply wrong, with significant consequences.

Here are some quoted claims from the brief and a tracing of the factual basis for those claims:

Claim 2: “Moreover, our current system was designed to direct 33 percent more dollars to students in towns with high poverty, but actually provides only 11.5 percent more funding for these students.” (Page 2)

Claim 2 posits that the current ECS formula leads to an average of 11.5% additional funding per low-income child across Connecticut school districts. That claim is cited to a previous ConnCan report, The Tab, authored by Bryan Hassel of Public Impact (specifically Page 18 of The Tab). Page 18 of The Tab cites this claim in Footnote 18 as “Authors’ analysis using 2007-08 data from the State Department of Education.  See Appendix for Details.” However, the appendix of the report provides no such justification and no further reference to the 11.5 figure. Rather the appendix provides only listings of data sources supposedly used and no explanation of how those sources might have been used.[i]

Claim 5: “For example, students at Connecticut’s charter schools are funded at only 75 cents on the dollar compared with traditional public schools.” (page 3)

Claim 5 is perhaps most perplexing, and like Claim 1, an example of the evidentiary black hole. The claim that Connecticut charter schools receive, on average, about 75% of state average funding is cited to a previous ConnCan report [not a Hassel/Public Impact product] titled Connecticut’s Charter School Law and Race to the Top. [ii] This ConnCan report was previously reviewed by Robert Bifulco for NEPC, who explained:[iii]

“The brief provides no indication of how it was determined that charter schools end up with only 75% of per-pupil funding that districts receive, or how, if at all, this comparison accounts for in-kind services or differences in service responsibilities.” [p. 3, Bifulco Critique]

And finally, for now:

Claim 6:“The formula could also hypothetically provide weights for other student needs, such as English Language Learner status. However, data shared by Connecticut State Department of Education with the State’s Ad Hoc Committee to Study Education Cost Sharing and School Choice show that the measure for free/reduced price lunch also captures most English language learners. In other words, there is a very strong correlation between English language learner concentration and poverty concentration in Connecticut. In addition, keeping the formula simple allows a more generous weight for students in poverty.” (p. 7, FN 12)

Claim 6 is particularly disconcerting, both because it includes a statistical finding which is never validated and because it is used to inform a policy solution which would produce substantial inequities harmful to a specific student population – children with limited English language skills. The authors claim outright that there is no need for additional adjustment for districts serving large shares of limited English proficient children because:

“there is a very strong correlation between English language learner concentration and poverty concentration in Connecticut.” (p. 7, FN 12)

This finding is cited only ambiguously in a footnote to data shared by CTDOE.  In some states, a strong relationship between the two measures might warrant collapsing supplemental aid for LEP and low-income children into one student need factor – with sufficient additional support to meet the combination and concentration of needs. However, a quick check of the data in Connecticut shown in Figure 1 (below) reveals that several districts have disproportionately high LEP concentrations relative to their low-income concentrations – specifically Norwalk, Danbury, New London, Windham and New Britain. These districts would be substantially disadvantaged by a formula with no additional weighting for LEP children, coupled with an arbitrary, small weighting for low-income status. In fact, the proposal to include only a relatively small weight for free or reduced price lunch and ignore the concentrated needs of these districts is most likely a back-door way to reduce the overall cost of the formula, and limit the extent that the formula truly redistributes funding where it is needed.

Figure 1

Relationship between Subsidized Lunch Rates and ELL Concentrations 2009

Data source: CTDOE 2009, Student need (free or reduced lunch: http://sdeportal.ct.gov/Cedar/WEB/ct_report/StudentNeedDT.aspx) and LEP data files (http://sdeportal.ct.gov/Cedar/WEB/ct_report/EllDT.aspx)

Note: From 2005 to 2009, the r-squared for this relationship ranges from .25 to .62, and is generally around .5.

The bottom line – The authors clearly never checked. The authors clearly don’t know what they are talking about, even at the most basic level. Yet they are willing – all who signed on to this brief, including Hassel, Hawley-Miles and Paul Hill – to go out on a limb and make these proclamations – proclamations and policy proposals which are simply bad, wrong, misguided – and irresponsible.

Example #2: Public Impact ConnCan’s The Tab

Much of the content of the Spend Smart brief seems to be grounded in, and some of it directly cited to, the previous ConnCan finance report titled The Tab, on which Bryan Hassel was listed as lead author.

I have written previously about The Tab, which is of equal quality to Spend Smart. Here’s a copy and paste of my previous post on The Tab.

https://schoolfinance101.wordpress.com/2009/11/23/why-is-it-ok-for-think-tanks-to-just-make-stuff-up/

==========Original Blog Post

This topic comes to mind today because ConnCan has just released a report (http://www.conncan.org/matriarch/documents/TheTab.pdf)    on how to fix Connecticut school funding which provides classic examples of just makin’ stuff up (page 25). The report begins with a few random charts and graphs showing the differences in funding between wealthy and poor Connecticut school districts and their state and local shares of funding. These analyses, while reasonably descriptive are relatively meaningless because they are not anchored to any well conceived or articulated explanation of “what should be.” Such a conception might be located here or even here (Chapters 13, 14 & 15 are particularly on target)!

The height of making stuff up in the report is the recommended policy solution to the problem which is never clearly articulated. There are problems in CT, but The Tab, certainly doesn’t identify them!

The supposed ideal policy solution involves a pupil-based funding formula where each pupil should receive at least $11,000 per pupil (made up), and each child in poverty (no definition provided – just a few random ideas in a footnote) should receive an additional $3,000 per pupil (also made up) and each child with limited English language proficiency should receive an additional $400 per pupil (yep… totally made up). There is minimal attempt in the report (http://www.conncan.org/matriarch/documents/TheTab.pdf) to explain why these figures are reasonable. They’re simply made up.

The authors do provide some back-of-the-napkin explanations for the numbers they made up – based on those numbers being larger than the amounts typically allocated (not necessarily true). They write off the possibility that better numbers might be derived by way of a general footnote reference to a chapter in the Handbook of Research on Education Finance and Policy by Bill Duncombe and John Yinger which actually explains methods for deriving such estimates.

The authors of The Tab conclude: “Combined with federal funding that flows on the basis of poverty and (in some cases) the English Language Learner weight of an additional $400, the $3,000 poverty weight would enable districts and schools to devote considerable resources to meeting the needs of disadvantaged students.” I’m glad they are so confident in their “made up” numbers! I, however, am less so!

It would be one thing if there was no conceptual or methodological basis for figuring out which children require more resources or how much more they might actually need. Then, I guess, you might have to make stuff up. Even then, it might be reasonable to make at least some thoughtful attempt to explain why you made up the numbers you… well… made up. But alas, such thinking seems beyond the grasp of at least some “think tanks.” Guess what? There actually are some pretty good articles out there which attempt to distill additional costs associated with specific poverty measures… like this one, by Bill Duncombe and John Yinger: How much more does a disadvantaged student cost?

It’s not like the title of this article somehow conceals its contents, does it? Nor is the journal in which it was published (Economics of Education Review) somehow tangential to the point at hand. This paper, prepared for the National Research Council provides some additional insights into additional costs associated with poverty and methods for estimating those costs.

Rather than even attempt to argue that these figures are somehow founded in something, the authors of The Tab seem to push the point that it really doesn’t matter what these numbers are as long as the state allocates pupil-based funding.  That’s the fix! That’s what matters… not how much funding or whether the right kids get the right amounts. In fact, the reverse is true. The potential effectiveness, equity and adequacy of any decentralized weighted funding system is highly contingent upon driving appropriate levels of funding and funding differentials across schools and districts!

Example #3: Public Impact Charter Disparity Analysis

Finally, there’s the report done by Public Impact with Ball State University on charter school funding disparities, which remains fresh in my mind because it keeps coming back up again and again. And it is because of the connection between the shoddy methods of that report, and the absurdly shoddy analysis in The Tab and Spend Smart, that this post is focuses on Bryan Hassel and Public Impact.

When digging deeper on financial differences among charter and non-charter schools in New York City, and looking at what the Public Impact/Ball State study had said about New York charter schools, my coauthor and I were shocked at how poorly the Public Impact/Ball State study had been conducted. Here’s a short section of our critique:

From: Baker, B.D. & Ferris, R. (2011). Adding Up the Spending: Fiscal Disparities and Philanthropy among New York City Charter Schools. Boulder, CO: National Education Policy Center. Retrieved [date] from http://nepc.colorado.edu/publication/NYC-charter-disparities.

This section returns to the issue of disparities in funding between non-charter and charter schools. As already noted, the Ball State/Public Impact study identified New York State as having large financial disparities between traditional public schools and charter schools. In contrast, the NYC independent budget office concluded that charters with department of education facilities had only negligibly fewer resources than non-charter public schools. One of these accounts is incorrect.

Ball State/Public Impact study claims that NYC traditional public school per-pupil expenditures were $20,021 in 2006-07, and that charter school expenditures were $13,468, for a 32.7% difference.[iv] However, the first figure appears to be inflated; the only figure that closely resembles $20,021 is the total expenditure, including capital outlay expense. This amounts to 19,198,[v] according to the 2006-07 NCES fiscal survey.[vi] This amount includes spending that is clearly not for traditional public schools—it includes not only transportation and textbooks allocated to charter schools, but also the city expenditures on buildings used by some charter schools.[vii] In essence, this approach attributes spending on charters to the publics they are being compared with—clearly a problematic measurement.

After offering these figures and the crude comparisons, the Ball State/Public Impact study argues that the purportedly severe funding differential is not explained by differences in need, because on average 43.5% of the students in public schools in New York State qualify for free or reduced-price lunch, while on average 73.3% of those in charter schools in New York State do. But, as was demonstrated earlier, there are three problems: (a) the focus on state rates, rather than NYC rates; (b) the inclusion of reduced-price lunch rates rather than just free-lunch rates as a measure of poverty (when focused on comparisons within NYC); and (c) the failure to compare only schools serving the same grade-levels. When these details are addressed, a different picture emerges. At the elementary level in NYC, for example, charter school free lunch rates were 57% and non-charter public school rates were 68%.

The NYC IBO report offers figures that are more in line with the data. For 2008-09, traditional public schools are found to have expenditures of $16,678, while charters that are provided with facilities are at nearly the same level ($16,373). Public expenditures on charters not provided facilities are found to be about $2,700 per pupil lower ($13,661). But even this comparison is not necessarily the most precise or accurate that might be made, because it does not attempt to compare schools that are (a) similar in grade level and grade range and (b) similar in student needs. The IBO analysis provides a useful, albeit limited, comparison of charter schools in their aggregate to district schools in their aggregate. Importantly, the IBO charter school funding figures do not include funds raised through private giving to schools or monies provided by their management organizations.

Once the cost differences associated with student populations are factored in, the IBO analysis changes significantly. In fact, the cost associated with student population differences is the same as the per-pupil cost associated with lack of a facility: $2,500. After adding the $2,500 low-need-population adjustment to charters, those not in BOE facilities can be seen to have funding nearly equal to that of non-charters ($16,171 vs $16,678) while those in BOE facilities have significantly more funding than non-charters (see Table 3).[viii]

One might try to argue that these problems we identify with the NY estimates, which render them entirely meaningless, are specific to New York, but that the rest of the states are reasonably estimated. The reality is that when it comes to estimating these types of funding differentials, each state and each local district, depending on the charter funding formula has its own peculiarities. If the crude method used by Hassel and colleagues completely missed the boat on New York, it is highly likely that comparable problems exist across many other settings. Without further, more detailed an appropriate analysis it would be unwise to base any conclusions on the existing Ball State/Public Impact study.

I’ve been writing quite a bit lately about rather complex state school finance formula issues. That is much the point of this blog.  But it may be hard for some to see how my recent posts on school finance relate back to the broader reform agenda, and to understand the implications of these posts for state policies. Let me try to summarize these posts – posts on spending bubbles, the “New Normal” and school finance PORK.  My overarching goal in these posts is to explain that much of the reformy rhetoric about budget cuts and the “New Normal” is based on myth about how school funding works and what we should be doing in these catastrophic economic times.

Here are the myths and some of the realities.

Reformy myth #1: That every state has done its part and more, to pour money into high need, especially poor urban districts. It hasn’t worked, mainly because teachers are lazy and overpaid and not judged on effectiveness, measured by value-added scores. So, now is the time to slash the budgets of those high need districts, where all of the state aid is flowing, and fire the worst teachers. And, it will only help, not hurt.

Reality: Only a handful of states have actually targeted substantial additional resources to high need districts. See www.schoolfundingfairness.org. And the effort of states to finance their elementary and secondary education systems varies widely. Some states have in fact systematically reduced their effort to finance local public schools for decades. That is, the tax burden to finance public schools in some states is much lower now than it was decades ago. Very few states apply much higher effort than in the past.  See: https://schoolfinance101.wordpress.com/2010/12/23/is-it-the-new-normal-or-the-new-stupid/

Reformy myth #2: The only aid to be cut, the aid that should be cut, and the aid that must be cut in the name of the public good, is aid to high need, large urban districts in particular. The argument appears to be that handing down state aid cuts as a flat percent of state aid is the definition of “shared sacrifice.” And the garbage analysis of district Return on Investment by the Center for American Progress, of course, validates that high need urban districts tend to be least efficient anyway. Therefore, levying the largest cuts on those districts is entirely appropriate.

Reality: As I have discussed in my series of recent posts, if there are going to be cuts – if states really believe that cuts to state aid are absolutely necessary, many state aid formulas include aid that is more appropriate to cut. That is, aid to districts who really don’t need that aid. Aid to districts that can already spend well above all others with less local effort. Aid to districts that will readily replace their losses in state aid with additional local revenues (or even private contributions). That’s the pork, and that’s where cuts, if necessary, should occur.

Reformy myth #3: The general public is fed up and don’t want to waste any more of their hard earned tax dollars on public schools. They are fed up with greedy teachers with gold plated benefits and fed up with high paid administrators. They don’t care about small class sizes and…well… are just fed up with all of this taxing and spending on public schools that stink. As a result, the only answer is to cut that spending and simultaneously make schools better.

Reality: The reality is that local voters in a multitude of surveys rate their own local public schools quite highly and that local voters when given the opportunity, even during the recent economic downturn, show very high rates of support for school budgets – including budgets with significant increased property taxes (the most hated tax). As I noted in a previous post, when New Jersey handed down state aid cuts to 2010-2011 school budgets and when- for the first time in a long time- the majority of local district budgets statewide failed to achieve approval from local voters, it was still the case that the vast majority (72%) of local budgets passed in affluent communities – in most cases raising sufficient local property tax resources to cover the state aid cuts. In another case, local residents in an affluent suburban community raised privately $420,000 to save full day kindergarten programs. Meghan Murphy’s analysis of Hudson Valley school districts shows that New York State districts also have attempted to counterbalance state aid cuts with property tax increases, but that the districts have widely varied capacity to pull this off.  Parents in a Kansas district are suing in federal court requesting injunctive relief to allow them to raise their taxes for their schools (they use faulty logic and legal arguments, but their desire for better schools should be acknowledged!).

Reformy myth #4: None of this school funding stuff matters anyway. It doesn’t matter what the overall level of funding is and it doesn’t matter how that funding is distributed. As evidence of this truthiness, reformers point to 30+ years of huge spending growth coupled with massive class size reduction and they argue… flat NAEP scores, low international performance and flat SAT scores. Therefore, if we simply cut funding back to 1980 levels (adjusted only for the CPI) and fire bad teachers, we can achieve the same level of outcomes for one heck of a lot less money.

Reality: First of all, these comparisons of spending now to spending then are bogus. I address the various factors that influence the changing costs of achieving desired educational outcomes in this post: https://schoolfinance101.wordpress.com/2011/01/12/understanding-education-costs-versus-inflation/. Second, rigorous peer reviewed studies do show that state school finance reforms matter. Shifting the level of funding can improve the quality of teacher workforce and ultimately the level of student outcomes and shifting the distribution of resources can shift the distribution of outcomes. http://www.tcrecord.org/content.asp?contentid=16106 Similarly, constraining education spending growth over the long term can significantly harm the quality of public schools. See: https://schoolfinance101.wordpress.com/2010/04/22/a-few-quick-notes-on-tax-and-expenditure-limits-tels/

An opportunity for states?

I would argue that now… right now… represents a real opportunity for those states who actually want to step up, and really invest in the quality of their education systems and use the quality of their education systems to drive their economic futures.

I stumbled across this article http://www.foxnews.com/us/2011/02/13/states-offer-tax-breaks-guarantee-jobs/ on the Fox News website the other day, and it presents some useful insights for state policy makers regarding tax policy decisions and economic growth. I’ve written about the same point very early in my blogging (that the Small Business Survival Index in particular, misses some big points about location selection). Here’s a short section of the Fox News piece:

But there’s a catch to the anti-tax, pro-business rhetoric: Businesses consider a range of factors when deciding where to locate, including the quality of schools, roads and programs that rely on a certain level of public spending and regulation. And evidence suggests there is little correlation between a state’s tax rate and its overall economic health.

“Concerns about taxes are overstated,” said Matt Murray, a professor of economics at the University of Tennessee who studies state finance. “Labor costs, K-12 education and infrastructure availability are all part of a good business climate. And you can’t have those without some degree of taxation.”

States’ tax rates also do not predict their resilience during an economic downturn.

Arguably, no time is better than now. Other states are jumping on board with the “New Normal” reformy logic that slashing education budgets, increasing class sizes and narrowing curriculum around tested content areas is the only way to go. Yet, educated parents invariably want small class sizes (often topping the list of preferences for private or public schools) and want their children to have intellectually stimulating and broad, enriched curriculum. The current environment presents a great opportunity for some states to step outside the “New Normal” and truly race to the top with real investment in their public schooling systems.