I was pleased to read this morning that the Texas Legislature is now finally reconsidering the error of adopting into law the 65% requirement pitched by pundits a few years back as a revenue neutral “solution” for increasing education spending.
Of course, it was in Texas that the actual agenda of those pundits was revealed in a memo exposed in the Austin American Statesman.
Doug Elmer of the University of Kansas and I wrote about the 65 cent solution in the January 2009 issue of Educational Policy (The Politics of Off-the-Shelf School Finance Reform).
What makes the 65 cent solution so interesting, in retrospect, is that it was a “reform” that in some states become legislation, but was never based on any evidence whatsoever that allocating 65 cents of every “education dollar” improves outcomes. In fact, Doug Elmer and I discuss the best empirical research on this topic which suggests otherwise.
Further, setting aside those good empirical studies of the relationship between instructional budget shares and student outcomes, the basic argument for the 65 cent solution was utterly absurd. The 65 cent solution was based on the argument that public school systems are inefficient and wasteful and should be told how to use their money. So… the 65 cent target was selected as roughly (slightly higher than) the average percent of current expenditures allocated to instruction (based on NCES expenditure data). So… the idea is that school districts are inneficient and wasteful in general, therefore we should ask them all to spend roughly like the average public school district? Good thinkin’… eh?
Here are some quick summary points regarding education funding and student outcomes in Louisiana and Mississippi, two states getting some national attention these days…
1. In Louisiana, according to data on 5 to 17 year olds from the American Community Surveys of 2005 to 2007, approximately 17% of children avoid the public schooling system to attend private schools. That’s second highest in the nation. Mississippi is closer to, but still above the middle among states.
2. In addition to ranking second highest in non-public school attendance, Louisiana also ranks second lowest in “effort” in financing public schools, where effort is measured as total state and local spending on public education as a percentage of gross state product. Mississipi, because it is a generally poorer state with lower GSP, is nearer the average on effort.
3. Both states rank near the bottom annually on the reading and math portions of the National Assessment of Educational Progress.
4. Both states rank near the bottom annually on state and local per pupil spending on public schools even after adjusting for regional variation in competitive wages and for various other characteristics of public schools (size, poverty rate, etc.).
The two figures below are illustrative of the position of Louisiana and Mississippi on questions of education funding, effort and outcomes.
Regional Wage and Cost Adjusted State and Local Revenues and NAEP Reading
This first chart shows that there exists a modest relationship between state and local spending on education across states and NAEP reading scores. And two states that spend little and achieve little are Louisiana and Mississippi.
Effort and NAEP Reading
This second graph shows the relationship between Effort (% of GDP spent on public schools including state and local resources) and NAEP reading scores. As noted above, Mississippi puts up relatively average effort but in spite of this effort simply cannot muster the resources to achieve desirable outcomes with it’s very high poverty student population.
Lousiana has much less excuse than Mississippi. It’s effort is low. It’s spending is low, and indeed it’s outcomes are low, for those who remain left behind in public schools in Lousiana.
Once again, efforts to reform Philadelphia public schools are in the news, and one item that remains at least a significant part of that reform package is a proposal to use a Weighted Student Funding formula to improve equity in resource allocation across schools within the Philadelphia public school system. Here’s the link to a recent story:
Let me be absolutely clear that I am not opposed to Weighted Student Funding per se. What I am opposed to, and have been very vocal about, is the overselling of Weighted Student Funding as a panacea for both within district equity concerns and for decentralized management of schools and school systems.
Let me start here by clarifying that Weighted Student Funding and decentralized management are two separate issues that are often purposefully entangled when presented by pundits. Indeed, having a well defined school based allocation formula can enable decentralization of decision making to building principals. I offer (reiterate) three potential concerns here regarding weighted student funding coupled with decentralized management, specifically regarding Philadelphia.
1. It remains very difficult if not entirely infeasible for large urban school districts to successfully tilt their internal playing field (across schools within district) when those large urban districts remain at a competitive disadvantage regarding financial resources compared to surrounding districts competing for teachers on the same labor market.
In no major city in the nation is this concern more true than in Philadelphia (with Chicago running second). In relative terms (urban core per pupil spending relative to surrounding districts), Philadelphia has consistently been the least well funded urban core district in the nation for quite some time… falling in some years as low as 76% of surrounding district spending (using the NCES labor market definition).
In my recent work on Texas and Ohio cities, none of which are as poorly positioned as Philadelphia, I found that the relative funding of the urban core compared to surrounding districts poses a significant constraint on the urban core district’s ability to reshuffle funding. For example, the lowest poverty, lowest minority concentration schools in the urban core typically are higher poverty, higher minority concentration than suburban schools only streets away. Even before tilting the playing field to move funding out of the lower poverty urban district schools and to the higher poverty ones, the lower poverty schools within the urban districts are already at a competitive disadvantage relative to even lower poverty neighboring schools in adjacent suburbs. This is not to suggest, by any means, that the urban core districts should make no attempt at leveling their playing field, but that the urban district may be unable to significantly tilt their playing field to assist the higher poverty schools. Here is a schematic diagram I often use to describe this problem:
Difficulties in Tilting the Within District Playing Field
Here is an example of school level budgets per pupil (elementary schools) in a section of Dallas, immediately adjacent to marginally lower poverty but higher spending schools in Mesquite ISD.
Spending per Pupil in Dallas Schools and Neighboring District
Now, credit should be given to ye ol’ Commonwealth of PA for recently adopting their first, statewide, reasonably organized basic education funding formula (special education remains substantially screwed up), albeit slowly phased in and already under the gun due to state budget concerns. However, the figure below shows that even after first year state support shifts, Philadelphia city school district remains at a significant financial disadvantage compared to districts in Montgomery, Bucks, Chester and Delaware counties (neighbors in the same labor market).
Philadelphia is much higher poverty than neighbors, and still has fewer financial resources!
2. There is little compelling evidence that large urban districts using Weighted Student Funding are achieving any greater equity in resource allocation across schools when compared with other large urban districts in the same state which do not use WSF.
This was a major finding of my recent and ongoing work. Look, the reality is that any resource allocation formula from state to school districts or from school districts to schools, is subject to political tug-of-war.Whether we’re talking about allocating staffing positions from one school to another, or dollars generated by weights, constituents involved in the process will attempt to figure out which levers on the system can be used to benefit them and then the games will begin. This is how, for example, Cincinnati ends up adopting within its weighted funding formula a larger adjustment for gifted children than for children in poverty. This is how, for example, the state of Kansas had adopted a larger weight for children in “new facilities” (in affluent suburban districts) than for children in poverty or children with limited English language proficiency (prior to recent court rulings). These are the politics of weighted funding systems – and these politics differ little from any other politics which involving shifting finite resources toward some and away from others.
One should not be fooled into believing that Weighted Funding eliminates such games. It merely creates new ones. (see my Art of Inequitable School Funding post)
3. After presenting one critical review of weighted student funding and decentralized governance I was challenged by a skeptic of my work to provide any reasonable argument against the decentralized governance component – on the basis that it is somehow a well understood and broadly accepted fact among scholars that decentralized governance of large urban school districts is necessarily good – always and forever.
In light of the first two points above, consider the following. First, decentralized decision making is and can only be as good as the decentralized decision makers – in this case, the principals of schools to be granted greater control. Now, this issue is largely about equity right? Well, as it turns out, in many urban settings, the principals with the weakest academic qualifications (those who’ve repeatedly failed certification exams, attended academically weaker undergraduate and graduate preparation programs) are leading the schools with the highest poverty and minority concentrations. Some of my earlier work (in Educational Administration Quarterly with Bruce Cooper) indicates a propensity among principals to hire teachers with academic backgrounds similar to their own – a propensity which can work for the positive, or negative.
With leadership quality distributed in this manner across schools within large urban districts, would decentralizing control lead to greater equity? I suspect not. Further, if district resources are relatively constrained as in Philadelphia it remains unlikely that leadership quality may be effectively redistributed (by paying high enough salaries to principals of the toughest schools) and even less likely that those principals can be provided sufficient resources to recruit and retain the teachers they need.
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So… all of that heavy stuff in mind, I urge caution in making too much of this next round of Philadelphia school reforms and other similar attempts elsewhere. Without sufficient targetted resources to Philadelphia public schools, the district may continue to spin its wheels for some time. I hope not.
One area of school finance about which I’ve written quite a bit is what I refer to as the “tricks of the trade” in state aid allocation formulas. Most people who study or observe state school funding policies, including popular media outlets like Education Week tend to make the automatic assumption that increased state effort toward financing local schools necessarily leads to more equitable distribution of resources. After all, the initial goals of state intervention and aid allocation were to (a) encourage towns to create public schooling systems for their children and (b) to equalize towns’ ability to pay for schools, because substantial disparities in taxable property wealth across towns made it more difficult for some than others to pay for quality schools.
However, as state aid formulas have become increasingly complex over time, so too have the various ways in which state legislatures may craft allocations of aid in ways that actually send fewer dollars to those who need them more. Here is my short list of some of the more common Tricks of the Trade that shift state aid away from poorer, higher minority concentration school districts and quite often toward neighboring affluent suburban districts. Many of these policies lead to sharp racial differences in funding across school districts. And at least some of these policies are built on historical racial disparities within public education systems and in housing and residential segregation.
1. Aid allocated based on Average Daily Attendance rather than based on enrollment or membership. This one is relatively straight forward. Higher poverty and higher minority concentration school districts tend to have lower average daily attendance rates. As such, providing per pupil financing on the basis of average daily attendance systematically reduces aid to high poverty, high minority districts. Preston Green and I show this effect in an article titled “Urban Legends, Desegregation and School Finance: Did Kansas City Really Prove that Money Doesn’t Matter.”
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Missouri is among a handful of states that continues to provide aid to local public school districts on the basis of their average daily attendance (ADA) rather than by enrolled pupil count or membership. From 2000 to 2004, poverty rates and black student population share alone explain 59% of variations in attendance rates across Missouri school districts enrolling over 2,000 students. Both black population share and poverty rate are strongly associated with lower attendance rates, leading to systematically lower funding per eligible or enrolled pupil in districts with higher shares of either population. Table 9 shows that, in 1999, while districts on average (excluding KCMSD) lost 5.6% of state aid due to differences between enrollment and ADA, KCMSD lost nearly 13%. That margin has decreased after KCMSD had improved its attendance rates. Nonetheless, KCMSD continues to receive a lower share of state aid due to ADA based funding, than other districts with lower poverty rates and smaller black populations.
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2. Incorrectly estimated or wrongly conceived geographic cost (wage variation) adjustments. Geographic cost adjustments seem to be the new, hip and cool way to manipulate state aid formulas in order to drive more funding to affluent suburban districts, or in the case of Wyoming, very affluent tourist locations (Jackson Hole). Because estimating a well conceived and appropriate factor to compensate for variations in employment costs can be a complicated endeavor, Legislatures in some states have latched on to “plain common sense” solutions to twist state aid in their favor. I write about the worst of these in a recent article in the journal of education finance titled Doing more harm than good. The two most offensive examples of which I am presently aware are the Wyoming legislature’s choice to retain an index that provides 40% additional resources to Jackson Wyoming simply because the average housing value in Jackson (for tourist properties of the rich) is much higher than the rest of the state. Equally offensive is the Kansas policy that allows additional revenues to be raised in the 17 districts with housing values over 25% above state average. Most problematic about this Kansas policy is that those receiving the adjustment are districts in the Kansas City metropolitan area where the majority of residential housing was developed with racial restrictions in deeds – restrictions that were introduced as late as 1962 (years after prohibited by the U.S. Supreme Court) and were only symbolically stricken from deeds in 2006 (after some Kansas legislators resisted when the issue was raised the previous year). For a fun article on this topic, see: http://www.pitch.com/2005-04-14/news/funny-math/
More on this topic at a later point.
3. Allocating or adjusting aid based on existing patterns of teacher degree levels or teacher experience. An alternative to creating a complex wage index for adjusting aid is simply to include a factor that reinforces directly the existing patterns of disparities in teacher qualifications across wealthier and poorer school districts. Preston Green and I, in an article in the American Journal of Education titled “Tricks of the Trade” explain how Alabama, which at one time funded its highly segregated public schooling system on teacher units, assigning white teacher units twice the dollar value of black teachers, managed to accomplish roughly the same pattern of disparity across black and white schools by retaining their teacher unit funding model but allocating more money to schools having teachers with advanced degrees (the whiter, less poor schools). The Arizona alternative is to provide more funding to districts where the average teacher experience level is above the state average (whiter, less poor schools) – the Teacher Experience Index.
Like funding on attendance (why should we pay for kids who aren’t there?), funding on teacher experience and degree level can be argued to pass that “plain common sense” test, at least in some states. “Let’s fund ’em for the teachers they dun-did-got… not them ones they wish they dun-did-got or for cryin’ out loud, the ones they actually need.”
4. Allocating substantially higher levels of aid per high school student than per elementary school student in a district (student grade level weighting within K-12 unified school districts).
This one is a little trickier and more subtle, and thankfully the average effect of this “trick” seems to be somewhat smaller than the others on this list. But, I have found in some recent work that when a state puts a big enough differential in place on the cost of high school students relative to elementary school students, poorer, higher minority unified K-12 school districts end up receiving systematically less funding than more affluent districts. There appears to be a relationship between the percentage of children who are in elementary versus high school grades and district poverty rates. Higher poverty districts have more children in elementary grades and fewer in upper grades, and there may be any number of logical explanations for this pattern. First, dropouts may affect the pattern. Second, as children grow up beyond elementary grades, their parents may become more professionaly stable and have the opportunity to move up and out. Also, those same parents may have had the option while the child was in the elementary grades, but when faced with the prospect of poor urban middle or secondary schools they finally exercised that option. Or, they perhaps exercised the private schooling option (urban Catholic high school).
5. Census-based financing of special education programs. I used to strongly favor the “flat” or census based special education funding approach because of the increased flexibility and reduced incentive to identify children with marginal disabilities. For those not familiar, census based funding for special education involves setting a statewide average (or some other arbitrary) rate of assumed children with disabilities that exist in all school districts and then funding on that arbitrarily set assumed rate. Okay… those of you working in the field of special education can see the problem with this already… but that hasn’t slowed the policy momentum in this direction, has it?
After evaluating a handful of state special education finance programs, I’ve changed my mind… quite strongly. Hey… we don’t provide the same amout of poverty based funding across districts – because the concentration of children in poverty varies by neighborhood and town. We don’t provide the same level of funding for bilingual education programs – because the concentrations of children with limited English speaking skills varies by neighborhood and town. And, as I’ve come to learn, the concentrations of children with various forms of disabilities vary by neighborhood and town… and in some cases in logical and explanable ways. Large town and small city hubs that are otherwise distant from major urban centers and surrounded by rural areas often have much higher rates of children with disabilities than their surrounding rural districts. These patterns show up in both school enrollment data and in U.S. Census data based on resident responses (not school identification practices). It seems logical that parents having children identified with a disability might choose to relocate to the nearest population hub where a wider array of social and medical services are available. Whatever the reasons, disability population concentrations, like poverty, vary widely from one location to the next across states. And quite often, disability concentrations vary in relation to poverty and even minority student concentrations. In two states where I have conducted recent analyses, higher poverty school districts are systematically disadvantaged by this flat approach to special education funding.
Okay… so the media is on it. Do a Google News Search on “Education Week” and “Quality Counts” and you’ll get over 100 headlines from major and small local news outlets across the country, like:
Unfortunately, as I discussed yesterday, at least the finance portion of these ratings is relatively meaningless – failing to capture critically important features of state school finance systems. (See my previous post)
This failure is particularly evident in the paragraph below from the Education Week summary of their newest findings. Yes, there are huge disparities in funding across Alaska schools – because tiny remote school districts are incredibly expensive to operate, relative to scale efficient districts in the state’s larger cities and towns. And yes, there are relatively large differences in spending across New Jersey districts. But New Jersey, more than any other state in the country (along with others like Minnesota), systematically allocates greater resources to poor urban districts. Much of the difference in resources across New Jersey school districts can be predicted as a function of student need variation across districts. And so it should be.
Broadly speaking, equity indicators still show wide disparities across districts in many states. For example, our Restricted Range indicator measures the difference in per-pupil expenditures between school districts at the 95th and 5th percentiles of spending within individual states, adjusted for regional cost differences and student needs. Smaller gaps denote more equitable spending across the districts in a state. Our analysis found a $12,307 gap between those high- and low-spending districts in Alaska in the 2005-06 school year, the largest difference in the nation. New Jersey had the second-largest gap—$10,838—and West Virginia displayed the smallest gap at $1,895.
This particular article in the Lawrence Journal World includes a quote by a legislative leader that perpetuates one of the standard myths of education funding – that somehow, any funding that is not “going to the classroom” is necessarily wasteful funding.
This argument relates back to a “movement” of a few years ago in which pundits bankrolled by Overstock.com CEO Patrick Byrne were wining and dining conservative state legislators to get them to introduce legislation that would mandate that 65% of each education dollar be spent in the classroom! Thankfully, this movement came to a grinding halt when the motives of this movement came out in a memo (exposed by the Austin Statesman) by the movement’s main pundit – Tim Mooney.
Anyway, a colleague – Douglas Elmer – and I have a new article out on this topic, and Off the Shelf school finance reforms (in Educational Policy, vol 23, #1, Jan. 2009).
From our recent article, here’s a quick run-down on what research studies say on this particular topic:
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The core assumption of the 65% solution is that increasing the share of spending to areas labeled as “instruction” will improve student outcomes without increasing overall levels of education spending. Implicit in this argument, and highlighted by some anecdotal examples provided on the FCE web site, is the notion that schools are presently wasting too much money in areas such as administration. FCE argues the districts can reallocate that money to instruction. In the 1990s, while schools endured the aftermath of A Nation at Risk and the subsequent criticisms of rising education spending and stagnant outcomes, many policy analysts conducted studies on education spending. These studies made the forgone conclusion that central administrative expenses were necessarily inefficient and therefore harmful for students, and that higher percentages of dollars allocated “to the classroom” were efficient, and therefore beneficial to students. Programmers developed software for school districts to track dollars to the classroom[1]and studies reported instructional expenditures in New York City schools at only 21.9% in an attempt to validate the inefficiency of large urban school districts (Speakman et al., 1996). However, few methodologically strong studies were able to directly link student outcomes to the ratio of resources districts allocated to administrative and other non-instructional expenses and classroom instructional expenses.[2]
A significant point of confusion in the literature on instructional spending relates to the difference between instructional spending levels and instructional spending as a share of total spending. For example, proponents of the 65% Solution point to a policy brief prepared for Texas legislators (Patterson, 2005) citing the research of Wenglinsky (1997) as finding a positive relationship between instructional spending and student outcomes. Wenglinsky, however, does not evaluate tradeoffs between instructional and other spending an outcomes, but rather finds that either instructional or administrative spending increases, both of which appear related to increased overall staffing and class size reduction, lead to improved educational outcomes.
Like Wenglinsky (1997), Ferguson and Ladd (1996) find in Alabama that instructional spending has a positive effect on test scores. Using data from Oklahoma school districts, Jacques and Borsen (2002) evaluate the effects of spending levels on student outcomes across a variety of categories, finding “Test scores were positively related to expenditures on instruction and instructional support, and are negatively related to expenditures on student support, such as counseling and school administration.” (p. 997) The authors raise concerns however with deriving causal implications from their findings, noting: “It could be that schools with problems hire more administrators and counselors.” (p.997) Taken together, these findings suggest that when policy makers add new money to education systems, adding that money to instruction areas while holding other areas constant may improve outcomes. In each case, however, researchers evaluated the level of resources allocated to schools, but not tradeoffs or potential reallocation of existing levels of resources. A core tenet of both the 65 and 100% solutions is not that states raise the level of funding for schools, but rather that lawmakers’ require districts to reallocate existing funds.
Bedard and Brown (2000), in an unpublished working paper, attempt the leap from evaluating levels of spending across categories to evaluating relative proportions, and find that reallocation from administration specifically toward classroom instruction might lead to increased outcomes. “Either the reallocation of $100 from administrative to classroom spending, with no change in overall expenditures, or an $100 increase aimed directly at the classroom moves the average California high school approximately 5 percentage points higher in the state test score rankings.” (p. 1) But, Taylor, Grosskopf and Hayes (2007) also in an unpublished working paper, using data on Texas schools to test directly the 65% solution, find that “the analysis suggests that schools that spend a larger share of their budgets on instruction are significantly less efficient than other public schools.” (p. 1)
Two other published, peer reviewed studies specifically examine the relationship between administrative expenses and student outcomes also yielded conflicting findings.In one, Brewer (1996) found little relationship between non-instructional expenses and student outcomes.Marlow (2001), contrasting with Brewer’s findings to an extent, found that: “While numbers of teachers do not influence performance measures, numbers of administrators are shown to positively affect performance — results that suggest that too many teachers, but too few administrators, are employed.”[3]
Finally, Huang and Yu (2002) combine NAEP data with NCES Common Core expenditure data to evaluate whether current expenditures per pupil and/or the difference between an individual district’s instructional spending rate and the state average instructional spending rate (called DDR in their study) relate to student outcomes in 1990, 1992 and 1996. The authors found overall positive effects of current spending on outcomes but “Net of relevant district factors, DDR was found unrelated to districts’ average 8th grade math performance.” This test is similar to testing whether districts over or under a 65% instructional spending threshold perform better or worse. The difference is that each district’s instructional share is benchmarked against its own state mean.
Probably the best, and most direct recent test of the 65% solution can be found here:
Taylor, L., Grosskopf, S., Hayes, K. (2007) Is a low instructional share an indicator of school inefficiency? Exploring the 65 percent solution. Bush School of Government and Public Service. Texas A&M University. Working Paper # 590
[1] Entire states such as Rhode Island adopted these resource tracking systems (IN$ITE)
[2] However, several methodologically weak production function studies did find cross-school correlations between percentage of expenditures on instruction and school aggregate test scores.
[3] Marlow’s finding seems counterintuitive and may be explained by factors overlooked in Marlow’s analysis. Among other things, studies that are more recent have shown that districts with higher overall spending or higher fiscal capacity to spend tend to spend proportionately more on administration. Many of those same higher spending, higher fiscal capacity school districts also serve more advantaged student populations and/or benefit from stronger community support.
It’s that time of year again. Time for Education Week Quality Counts to grade the states on a number of education policy issues – ranging from accountability systems to school finance systems. But, once again, Education Week’s Quality Counts ratings of state school finance policies simply lack understanding of the goals of today’s state school finance policies and methods for better understanding and evaluating state school finance policies. We have been working diligently to develop an alternative set of indicators to be released sometime in the near future. I will attempt to provide my critique of the Ed Week indicators herein without divulging to much detail about our alternatives – yet.
Here is a blurb I wrote a short while ago in which I lay out the initial critique of two popular state school finance rating systems:
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Two existing reports are disseminated annually and highly publicized. The first is the Education Trust Funding Gap Report which has as its focus, characterizing the differences in average per pupil state and local revenues between high and low minority concentration districts and between high and low poverty concentration school districts within states. The report appears to have significant traction in policy circles but is methodologically problematic and deceptive in a number of ways. First, the report calculates its funding gaps with respect to “need adjusted” estimates of state and local revenues per pupil. In order to generate these need adjusted estimates, the authors must adopt a set of weights that prescribe how much more a child from impoverished background is expected to need and how much more a child with disabilities is expected to need. That is, the method requires an a priori assumption of the magnitude of differential need for certain populations.
Second, the Funding Gap report overlooks entirely other major factors that affect the costs of providing equal educational opportunity, leading to misinformed conclusions. For example, the report fails to account for differences in costs associated with economies of scale and the interplay between district size and poverty distributions within states across small rural and larger urban and suburban districts. For example, in Kansas, many very small rural districts show elevated poverty rates even when compared to poor urban districts in the state. Small districts in Kansas have much higher revenues per pupil as a function of the state aid formula which favors small districts (but not necessarily high poverty districts). The higher revenues of small districts in Kansas has, in many years of the Education Trust report led to a favorable gap in poverty related funding in contrast to the state’s large unfavorable gap in minority related funding. Education Trust has acknowledged this apparent discrepancy and its cause but has not attempted to reconcile it in subsequent reports.
Education Week also publishes equity analyses of state school finance data in their annual report Quality Counts. Education Week also adopts a set of a priori “cost/need” adjustment factors (for student characteristics and for regional wage variation), and then from their cost adjusted revenue measure, calculates a series of standard school finance equity indices including coefficients of variation and McLoone Indices to characterize each states’ school finance data. These analyses also can lead to misinformed conclusions. For example, a McLoone Index measures the extent to which the average resources of the lower half of the students in a system are approaching the median level of resources. Education Week uses this index as an Adequacy measure. States like New York and Kansas which have very large minority funding gaps in the Education Trust Report often have among the best McLoone Indices in the Education Week report – precisely because all of the states’ poorest minority students are clustered in one or a handful of districts whose revenues are the lower half of the distribution and include or approach the median.
To illustrate the potential negative impact of these two reports, in 2003 in the context of state school finance litigation in Kansas, attorneys for the State submitted in defense of the school funding formula, both the Education Trust finding that higher poverty districts had higher revenue per pupil and the Education Week finding that Kansas showed a good McLoone index. The state’s attorneys and local news outlets did not understand why Kansas received good ratings on these indices nor did they care as long as those indices were from highly publicized, publicly recognized sources. Plaintiffs pointed out that Education Trust finding was not a function of systematic poverty related support, but rather a function of small rural school support which left out the poorer urban and large town districts and that the “good” McLoone index was a function of having nearly half of the state’s children and nearly all of the state’s poor minority children attending six districts with below average revenues. These points were difficult to make in the face of media accolades for state’s supposed achievements regarding school funding equity and adequacy. The district court and eventually Supreme Court of Kansas declared the state school finance system unconstitutional, but not without at least a few vocal critics chastising the judges who would give the legislature a failing grade for a school finance system that had received a grade of “B” from a leading national media outlet.
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Education Week’s 2009 version uses pretty much the same indicators they used in reports that I previously critiqued including the McLoone Index and Coefficient of Variation. And again, states like New York, where large shares of poor and minority children are clustered in a single, relatively underfunded school district, do quite well on the McLoone Index. Also, states that have aggressively differentiated funding to meet varied needs and costs across districts, like New Jersey, fair poorly on the Coefficient of Variation – a measure of raw variation in spending levels across districts without sufficient accounting for need and cost variation across districts. The bottom line is that there are two types of variations in resources across public school districts – good variations (cost and need related variations) and bad variations (variations related to wealth and/or fiscal capacity variations among school districts). A good school finance system might/should have a great deal of variation in resources across schools and districts, assuming that needs and costs vary across schools and districts.
Education Week also attempts to compare spending of districts in each state to national average spending – using the percent of children in districts at or above national average as an “adequacy benchmark.” But, just as districts within states vary, so too do states. The average poverty level in some states is much higher than in others – and the concentrations of limited English proficient children also higher. Further some states have far more children served in concentrated urban poverty settings and some states have far greater shares of children served in remote rural settings and necessarily small schools. All of these factors affect the costs of equitable and adequate education.
Our general strategy to rating state school finance systems is (a) to evaluate whether those state school finance systems do, in fact, attempt to target greater resources to school districts having greater costs associated with educational needs such as poverty (and controlling for all of the other costs noted above) and (b) to estimate the expected per pupil state and local revenue levels for a district with X, Y and Z characteristics in each state – that is, what is the predicted level of resources for a school district of 2,000 students in an average wage labor market, at a specific poverty level, and other student needs.
Without giving you the technical details, here’s how our factors line up with Ed Week’s 2009 grades.
This first figure shows the average “poverty sensitivity” or progressiveness scores for states by their Ed Week grades. That is, did the state provide, on average, more or less resources to higher poverty districts after controlling for other factors. A progressiveness index below 1.0 indicates “regressive” funding – higher in lower poverty districts and an index above 1.0 indicates “progressive” funding. Interestingly, Ed Week’s highest grades went to states that were, on average “regressive.”
This second figure provides the average “predicted spending” for a district with 20% poverty (census poverty) holding other cost factors constant. It’s a sort of – relative adequacy – measure – focused on relatively high poverty (but constant across states) districts. In this case, we also see that the “relative adequacy” of funding in those states receiving the highest grades from Ed Week is lower than the relative adequacy of funding in those states receiving some lower grades.
So, if Ed Week’s grading system (a) doesn’t capture the extent to which state school finance systems target resources to those districts where they are needed most, and (b) doesn’t capture the true “relative adequacy” of resources across states (accounting for wage, scale and need differences), then what does it capture? I’m just not sure.
On a daily basis, in print media and on talk radio, I read and hear a lot of bombastic rhetoric about state rankings of small business competitiveness – the most frequent references of late to the Small Business Survival Index (SBSI).
Nearly every component of this index deals with the tax and regulatory environment imposed by states. That is, it is assumed that the major reason one would want to start a business in one location versus another – New Jersey versus North Dakota – is the favorable state tax policy and regulation (minimum wage, etc.).
It would seem to me that this is a relatively limited if not utterly useless perspective. Indeed, among bordering states and within commutable regions at state boundaries such comparisons might be relevant. An individual who wishes to live in a particular region and/or recruit employees with specific skills that may be obtained within that region, might choose to open shop a few streets or miles away in the more favorable state.
However, from a broader, national perspective, issues such as access to human capital, intellectual and cultural environment are critical to at least some if not many small business and entrepreneurial endeavors.
Let’s consider, for the moment, the relationship between 3 different measures –
1. Small Business Survival Index
2. Gross State Product per Capita
3. The Percent of High Schools Achieving a Silver or Gold Rating from U.S. News
Across states, the correlations between these figures look like:
GSP and SBSI (higher is bad) = .1662
A weak correlation, but a positive one, suggesting that on average, states more “hostile” to small business have higher gross state product per capita. Hmm… how can that be?
GSP and % of High Schools Gold or Silver = .4406
A reasonable positive correlation and statistically significant. Indeed states with more resources may be able to allocate more resources to providing high quality schools. That means taxes. Alternatively, and related, states with highly educated and productive adult populations may emphasize the importance of high level education to their children leading to not only higher participation but higher success rates on AP and IB tests (the underlying elements of the U.S. News HS Rankings).
SBSI and % of High Schools Gold or Silver = .3554
This is also a reasonably positive and statistically significant correlation, indicating that states with more high-end high schools have, on average, less favorable tax policy for small business.
Now… If I’m thinking of starting a small business that relies on intellectual capital and/or creative energy, and if I’m unlike most people and can choose to locate that start-up business anywhere in the country, then I get to make the trade-off decision as to whether I prefer favorable tax climate or intellectual capital and creative energy.
I may be wrong, but it strikes me that the latter is far more important to building a successful business. One might argue that the heavier tax burden is, in part, a premium one pays in order to be in a region with the creative, intellectual work force I need.
Further, if I want to recruit and retain an adult workforce that is going to stick with the business, I need to be recruiting them to work in an area where they feel comfortable raising their children and sending them to school.
In other words, I’m picking Massachusetts, New Jersey or California before South Dakota or Nevada, in spite of the wisdom presented by the authors of the Small Business Survival Index. Quite simply, small business survival is far more contingent on the quality (relevant qualities) of one’s workforce than on the marginal differences in tax policy.
I almost hate to waste so much time dealing with such utterly absurd and ignorant rhetoric as appears daily in “news” outlet Kansas Liberty. But, they’re at it again: https://www.kansasliberty.com/liberty-update-archive/22dec2008/salina-comes-back-for-more-money#1229435964
Again, they raise the point that it has now been proven that the massive infusion of cash over the past 10 years has led to no improvement in results. See my post below where I explain that there was no massive infusion of cash.
In their latest story, the raise two new points:
Regarding the lawsuit filed by Salina and Dodge City in 1999, eventually found in their favor, they note in the most recent article:
“The suit gave the Kansas Supreme Court the opportunity to order the Legislature to provide substantial funding increases for schools.”
This phrasing suggests that the court was simply waiting to be fed such an opportunity. In fact, the initial response of the trial court was to dismiss the case on the grounds that the same formula had been found constitutional in 1994 (USD 229 v. State). The Supreme Court did accept plaintiffs argument that enough things had changed since that time that a trial was warranted. Neither the trial court nor supreme court seemed enthusiastic to address the issue at the time, since it was still relatively soon after all of the 1990s reforms and court rulings.
They also note that the huge increases in funding are now responsible for the state budget situation:
“The increases are widely blamed for being the primary culprit in creating the state’s growing financial crisis.”
… or could it just be the economy… stupid. States are facing large budget deficits. That’s just how it is right now.
Now, the states facing the biggest deficits are those most dependent on income tax revenues to fill their general fund budgets and support public services. Those facing the biggest problems in education funding are those most reliant on state general funds to support education. This is because income tax returns drop off more quickly than sales tax returns, and property tax revenues are the most stable of the mix.
So, why is this relevant? Well, Kansas’ difficulties with education funding and the impact of education funding on the state budget are largely a function of the reductions in the statewide general fund mill levy from 35 mills to 20 mills in the late 1990s. The legislature created an imbalanced revenue portfolio for itself at that time, leading to the difficult school funding circumstances from 2001 to 2003, and again now. Had the legislature not cut this more stable revenue source from the system, they’d be much better off right now. Yes, unlike the 2001-2003 downturn where only income tax revenues declined, this downturn is hitting other revenues, even potentially property tax revenues. That said, property tax revenues are still more resilient (less elastic).
I’m simply mind-blown by the level of ignorant rhetoric I see in this supposed news outlet.
School Finance 101 