Resource Deprivation in High Need Districts? (& CAP’s goofy ROI)

This post provides a follow-up on two seemingly unrelated topics, both of which can be traced back to the Center for American Progress.

First, there was that wonderful little Return on Investment indicator series that CAP did a while back.

Second, there’s the frequent, anecdotal argument that creeps into CAP/Ed Trust and AEI conversations that high need districts all have enough resources anyway and just have to stop wasting them on things like Cheerleading and Ceramics.

In this post, I provide an abbreviated version of some of the findings one of my recent conference papers.

The goal of the research study was to first identify those districts which fell into various regions or quadrants, applying a framework similar to that used by CAP in their ROI and second, explore the differences in personnel allocation in each group of districts looking for insights into what makes them tick (or not). It’s not a very good framework to begin with, but at least provides a common starting point:

The idea is that districts may fall into four groups. Some are high spending high performers and some are low spending low performers. Others are high spending low performers and still others are low spending high performers. What would be interesting from a policy perspective is whether we really could identify those in Q1 above and those in Q3 above and determine what makes them tick (Q1), or not tick (Q3).

As I discussed in a previous post, CAP took a particularly egregiously flawed approach to correcting/adjusting for various factors and laying out districts across these four quadrants. Here’s a snapshot of their Illinois findings:

The CAP IL snapshot shows plenty of districts in those green and red quadrants. Of course, the CAP snapshot a) fails to full correct for poverty related costs or ELL related costs and b) doesn’t correct at all for economies of scale or population density. If one were to believe the CAP findings, one would assume that there are similar proportions of districts that are in each group – both the expected groups (upper right and lower left) and the less likely groups (upper left and lower right). Of course, CAP also blew it in their interpretation of what’s going on in the lower left. They seemed to chastise these low spending low performing districts for their low performance, rather than acknowledge that these are actually the districts that have been screwed on funding, and are producing exactly what is expected of them in terms of outcomes.

Of course, if one more fully corrects for differences in costs across IL school districts, the actual distribution by quadrant comes out more like this (see conference paper for details on cost adjustment model):

The reality is that there aren’t a whole lot of districts – at least in the Chicago metro area that fall in the upper left and lower right quadrants. In fact, districts are largely where they are expected to be – Some have plenty of resources and do quite well, and others have limited resources and are doing poorly. Now, there is plenty of variance in the lower left and upper right which could be explored for interesting patterns.

Note that Illinois (along with PA and NY) is among the most regressively funded and racially disparately funded systems in the country!

How do resource constraints relate to curricular offerings?

Much of the  conversation of the past few days/weeks by pundits on twitter and in blogs has been on the question of what’s good for the “rich” and what’s good for the “poor.” Let me reframe that issue in this post in terms of what kids have access to in districts in the upper right quadrant of the above figure versus what kids have access to in the lower left quadrant.  Of course, the anecdotal assumption laid out above is that there are actually a whole bunch of districts in the lower right that have elaborate cheerleading and ceramics programs. Say it ain’t so! Okay… it ain’t!

What is so is that students attending districts in the lower left hand quadrant tend to have much less access to advanced curricular opportunities and boutique electives courses than children attending districts in the upper right hand quadrant. Here are a few figures, based on individual staffing assignment data:


Children attending districts in the upper right hand quadrant are nearly 3 times as likely to have access to a teacher assigned primarily to advanced math courses, nearly twice as likely to have access to a teacher primarily assigned to advanced literature or advanced science, and significant more likely to have access to a teacher assigned primarily to advanced social sciences or even seemingly more basic offerings like Algebra and Geometry. Moving deeper into the extremes of the upper right and lower left quadrants magnifies these disparities.  Further, while these distributions are expressed as a percent of total staffing, high spending high outcome districts tend to have significantly more staff per pupil.

Students in the lower left hand quadrant do have more of some stuff. They have a greater density (as a share of total staffing, but NOT on a per pupil basis) of elementary classroom teachers, and teachers in bilingual, alternative and at risk education. They also seem to have marginally more school site administrators. They have only comparable shares of staff allocated to basic level courses.

Implications?

Analyses in the full paper provided little evidence in Illinois or Missouri that high need and low performing districts were squandering their resources on things like cheerleading or ceramics, or, for that matter that there were large numbers of high need low performing districts that really had enough resources to begin with but weren’t using them productively. The classic emergent profile of a high need low performing district in Missouri and Illinois was of a district with highly constrained resources after adjustment for costs, and a district that had largely forgone assigning teachers to advanced content areas and elective courses for which they perhaps expected few students to enroll. Lack of a rich curriculum in high need settings is a significant policy concern and is a concern that cannot likely be remedied by reshuffling deck chairs.  These districts in fact need more total resources than high spending high outcome districts because they must be able to offer both the basic course work to prepare students to gain access to higher level courses, and to offer the higher level courses. Under present circumstances in many states, those resources just aren’t there, and it is very counterproductive to pretend either that they are or that it’s the districts’ fault they aren’t!

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School Funding Equity Smokescreens: A note to the Equity Commission

In this blog post, I summarize a number of issues I’ve addressed in the past. In my previous post, I discussed general reformy myths about school spending. In this post, I address smokescreens commonly occurring in DC beltway rhetoric about school funding equity and adequacy. School funding is largely a state and local issue, where even that “local” component is governed under state policies. So I guess that makes it a state issue, really. Occasionally, the federal government will dabble in the debate over how or whether to intervene more extensively in state and local public school finance.  Now is one of those times where the federal government is again at least paying lip services to the question of equity – with some implication that they may even be talking about school funding equity. The federal government has created an equity commission!

One of my fears is that this current discussion of funding equity will be typical of recent beltway discussions of school funding, and be trapped in the constant fog of School Funding Smokescreens and insulated entirely from more legitimate representations and analyses of the critical issues that should be addressed.

So, for you – the equity commission – here’s a quick run down on School Funding Smokescreens:

1. On average, nationally, we now put more funding into higher poverty school districts than lower poverty ones (to no avail)

This argument seems to be popping up more and more of late, and often with the table below attached. This table is from the National Center for Education Statistics and shows the average current operating expenditure per pupil of school districts nationally over time. The table would appear to show that in 1994-95, low poverty school districts had between $300 and $400 less in per pupil spending than higher poverty ones. By 2006-07, the highest poverty quintile of school districts had about $100 per pupil more than the lowest poverty quintile. That’s it. We’re done. Equity problems fixed. No more savage inequalities. And after all of this fixing of school finance equity, we really got nothing for it. Achievement gaps are still unacceptably large and NAEP scores stagnant? Right? All of this after dumping a whole extra $100 per pupil into high poverty districts. I guess we should be rethinking this crazy strategy of systematically pouring so much into high poverty districts.

Table 1

NCES Oversimplification of Funding Differences by Poverty


Well, to begin with, a $100 difference really wouldn’t be that much anyway, given that the costs of actually meeting the needs of children from economically disadvantaged backgrounds are much greater than this. Setting that (really important) question aside, this table provides a less than compelling argument that we as a nation have accomplished improved funding equity for kids in high poverty districts.

Here’s the underlying scatter of school districts that lead to the neatly packed aggregations above. In the graph below, districts are plotted by current expenditures per pupil with respect to census poverty rates, using 2007-08 data. Clearly there is substantial variation in current spending. In fact, the underlying relationship isn’t even a relationship at all. It’s all over the place. And yes, if you fit a trend line – if you take out a huge magnifying glass – you can see that the trendline is ever so slightly higher in the higher poverty schools than in the lower poverty ones (perhaps about $100?). It’s not systematic. It’s not statistically significant. It’s pretty darn meaningless.

Figure 1

Pattern of school districts underlying Table 1


In our recent report Is school funding fair? we conducted a far more rigorous analysis of state and local revenue per pupil with respect to poverty, for each state. What we showed was that there exists huge variation across states both in the overall level of resources available to local public school districts and in the differences in state and local revenue in higher and lower poverty districts.  In that report, we showed that 9 states have statistically significantly lower state and local revenue per pupil in higher poverty districts (after controlling for economies of scale and competitive wage variation). Overall, half of states had lower funding per pupil in higher poverty districts (with many of those approximately the same).

Among the worst states were New York, Illinois and Pennsylvania. Let’s pull Illinois forward in Figure 1 – and also look at state and local revenues (excluding federal support, to focus on state policies) in place of current expenditures.

Figure 2

State and local revenues with respect to poverty, with Illinois highlighted


Now, when we exclude federal revenues the overall line tips slightly downward. The federal effect is slight, but there. More strikingly, when we pull Illinois forward in the picture, we see that funding by poverty across Illinois districts is highly regressive, and is systematic and statistically significant. Funding inequities across Illinois districts are far from being resolved. AND ILLINOIS IS NOT ALONE. I could go on and on with this.

2. The remaining (Because of #1), most egregious disparities in funding and teacher quality occur across schools within districts (because of politically motivated and corrupt local administrators) and these disparities are what cause the persistent racial achievement gaps (the reason those gaps haven’t improved since we’ve fixed between district inequity)

To many, this argument seems absurd (and is) on its face. Who really says that? Does anyone? Am I just makin’ this stuff up? No. And in fact, because this argument has become so pervasive of late, I even had to take the time to write a fairly extensive research article on the topic. See: http://epaa.asu.edu/ojs/article/view/718

I have written about this topic on my blog on several occasions and much of my writing on this topic can be found by reading my critiques of reports from the Center for American Progress and from the Education Trust. Here are some choice quotes where CAP and Ed Trust frame this argument – or blow this smoke!

Center for American Progress

State funding formulas tend to exert an equalizing effect on per pupil revenues between districts, on average, and not by accident. These formulas were sculpted by two generations of litigation and legislation seeking equitable or adequate funding for property-poor school districts.

Scandalous inequity in the distribution of resources within school districts has plagued U.S. education for more than a hundred years.

empirical literature documenting the extent of within-district inequity is astonishingly thin. [my reply: well, not if you actually read the research on the topic]

Center for American Progress

The outcome of such practices is predictable: A further widening of the dangerous achievement gap that has become endemic in American schools today.

Education Trust

Many states have made progress in closing the funding gaps between affluent school districts and those serving the highest concentrations of low-income children. But a hidden funding gap between high-poverty and low-poverty schools persists between schools within the same district.

These gaps occur partly because teachers in wealthier schools tend to earn more than their peers in high-poverty schools and because of pressure to “equalize” other resources across schools.

All of these claims that within district inequities are the major source of persistent inequity and that our failure to close within district funding and teacher quality gaps (having already fixed between district ones) are the reason for persistent black-white and poor-non-poor achievement gaps might be reasonable if poor children and non-poor children and black children and white children actually lived in the same school districts. BUT, IN GENERAL,* THEY DO NOT! As a result this argument is patently absurd, ridiculous, irresponsible and ignorant. It’s one massive distraction. A smokescreen of monumental proportion!

Here’s a quick visual of the reality that any informed analyst (or anyone who simply lives in the real world) understands. Below are two maps of the Chicago metropolitan area. On the left is a map which shows school districts and the level of state and local revenue per pupil in each of those districts. We know from above that Illinois maintains a very regressive state school finance formula. That is, higher poverty districts have less funding than lower poverty ones. Note that the diagonal shading indicates the location of districts that have majority minority (black and Hispanic) enrollment. As it turns out, most of those districts are in the orange – lower funding levels.

Now, CAP and Ed Trust would have you believe otherwise to begin with (that poor minority districts already have enough money), but would then go further to say that the real problem is that these Illinois districts are putting money into their white, rich schools at the expense of their poor black and Hispanic ones. How is that even possible?

Okay, so let’s look at the right hand panel, in which I have indicated the locations of individual schools, with majority black schools in red and majority Hispanic schools in purple. Majority white schools are in white. NOTE THAT THE WHITE DOTS TEND TO BE DISTRICTS ENTIRELY SEPARATE FROM THE PURPLE OR RED ONES. AND ONLY CHICAGO PUBLIC SCHOOLS HAS MUCH OF A MIX OF PURPLE AND RED. Only a handful of districts have both white and majority minority schools. Also, only a handful of districts have both low(er) poverty and high poverty schools. Districts are highly segregated.

Figure 3

State and Local Revenue and the Location of Majority Minority Schools in Illinois


FEW IF ANY SCHOOL DISTRICTS IN THIS MAP HAVE THE OPPORTUNITY TO REDISTRIBUTE RESOURCES ACROSS THEIR “RICH” AND “POOR” OR “BLACK” AND “WHITE” SCHOOLS – BECAUSE THEY DON’T HAVE BOTH!!!!!  Yes, Chicago Public Schools and a few other districts can re-allocate between poor black and poor Hispanic schools. But such re-allocation accomplishes little toward improving educational equity in the Chicago metro area or State of Illinois.

Now… to those at Ed Trust and CAP – if you really don’t mean this, I dare you to actually say it. Say that between district differences in demographics and funding are THE BIG ISSUE. At least as big if not much bigger than within district differences. Say it. Acknowledge it. I challenge you. Release another hastily crafted report and press release – but this time – having conclusions that are at least reasonably grounded in reality.  The data are unambiguous in this regard. Yes, within district disparities exist and it is important to address them. I will certainly admit that, and I’ve never said otherwise.  But solving within district resource variation alone will accomplish very little.

*Clarification – In states with county-wide districts, and large diverse populations, like Florida, one is more likely to see between school  within district segregation to be a greater problem.

3. High need, poor urban districts (in addition to misallocating all of their resources to the schools serving rich white kids in their district???) are simply wasting massive sums of money on things like cheer leading and ceramics.

This is another absurd and empirically unfounded argument. Again, you ask, is anyone really saying that high need, low performing school districts are actually wasting money on cheerleading and ceramics that could easily be translated into sufficient resources for improving reading and math performance (can we really fire the cheer leading coach and hire 6 more math specialists)? Surely no-one is advancing an argument – SMOKESCREEN – that utterly absurd. But again, these quotes can be found all over the Beltway talk-circuit regarding the best fixes for school funding inequities and inefficiencies (and nifty was to stretch that school dollar).

Here’s the advertisement headline from a recent beltway discussion at the Urban Institute:

Urban Institute Event Headline (based on content from Marguerite Roza)

Imagine a high school that spends $328 per student for math courses and $1,348 per cheerleader for cheerleading activities. Or a school where the average per-student cost of offering ceramics was $1,608; cosmetology, $1,997; and such core subjects as science, $739.

I’ve only recently begun exploring more deeply the resource differences across school districts that fall into different performance and efficiency categories. I’ve been specifically looking at Illinois and Missouri school districts, and estimating statistical models to determine which districts are:

a) resource constrained and low performing (low-low)

b) resource constrained and high performing (low-high)

c) resource rich and high performing (high-high)

d) resource rich and low performing (high-low)

These categories are based on thoroughly cost adjusted analysis. As such, a district identified as having low or constrained “resources” may actually spend more per pupil in nominal dollars than a district identified as having high resource levels. The resource levels are adjusted for various cost pressures including differences in student needs. I should be posting the forthcoming paper on my research page some time in the next month. But here’s a preview.

In both states, most districts fall into categories a) and c), where you would expect. There’s somewhat more “scatter” in Missouri, either because Missouri has some better funded high need districts (less regressive than Illinois) or because my statistical model just isn’t working quite right. I picked these neighboring states because Missouri is less regressive than Illinois and because I had similar data on both. So, the big question here is – if I compare the dominant categories of resource constrained low performing schools to resource rich high performing ones what do we actually see in the organization of their staffing and course delivery?

In Missouri, I tabulate each individual course to which teachers are assigned. In Illinois my tabulation is by the main assignment of each teacher. To begin with, in both states, the high spending high performing schools have more course offerings per pupil and more teachers per pupil (and smaller class sizes). These differences are far greater under the more regressive Illinois policies.

Here are a few fun visuals of what I’m finding so far, expressed in “shares of staff” allocation and relating staffing allocations in low-low districts to those of high-high districts.

The first two graphs compare the main assignments of teachers in high resource high performing Illinois schools (high school assignments only) to those in low resource low performing ones. The diagonal line represents “comparable” allocation to high resource high performing schools. Assignments falling below the line represent “deficits” (relative) in low resource low performing schools.

Across all assignment areas, Figure 4 shows that kids in low resource low performing schools tend to have reduced access to physical education, biology, chemistry and foreign language. Sadly, no indicator for ceramics in these data.

Figure 4

Allocation of Main Teaching Assignments in Illinois Districts


Focusing on less frequent assignment areas – lower budget share & staff allocation areas – Figure 5 shows that in Illinois, kids in low resource low performing schools tend to have reduced access to advanced math and science courses and drivers education, but have greater access to basic courses. That is, these districts are already channeling their resources to the basic, at the detriment of potentially important advanced coursework in math and science, and even basic coursework in biology and chemistry.

Figure 5

Allocation of Main Teaching Assignments in Illinois Districts (less frequent assignments)


Missouri – despite having somewhat higher relative resource levels in higher poverty settings (than Illinois, but still regressive), shows very similar patterns. Figure 6 shows reduced access to physical education for kids in low resource low outcome schools and elevated access to “general” math and language arts courses.

Figure 6

Allocation of Assigned Courses in Missouri Districts


Kids in low resource low outcome schools have reduced access to advanced math courses including calculus and trigonometry, and reduced access to chemistry. They have higher shares of teachers in special education, basic life skills, earth and physical (basic/introductory) science and in JROTC. Again, significant reallocation to “basics” is already occurring and within significant resource constraints.

Figure 7

Allocation of Assigned Courses in Missouri Districts (less frequent courses)


Also, LET IT BE KNOWN THAT HIGH SPENDING HIGH PERFORMING SCHOOLS IN MISSOURI HAVE TWICE AS MANY CERAMICS COURSE OFFERINGS PER PUPIL AS LOW SPENDIGN LOW PERFORMING MISSOURI SCHOOLS!!!!!

4. None of this school funding equity – between district stuff – matters anyway!

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.

We conclude that there is arbitrariness in how research in this area appears to have shaped the perceptions and discourse of policymakers and the public. Methodological complexities and design problems plague finance impact studies. Advocacy research that has received considerable attention in the press and elsewhere has taken shortcuts toward desired conclusions, and this is troubling. As demonstrated by our own second look at the states discussed in Hanushek and Lindseth’s book, the methods used for such relatively superficial analyses are easily manipulable and do not necessarily lead to the book’s conclusions. Higher quality research, in contrast, shows that states that implemented significant reforms to the level and/or distribution of funding tend to have significant gains in student outcomes. Moreover, we stress the importance of the specific nature of any given reform: positive outcomes are likely to arise only if the reform is both significant and sustained. Court orders alone do not ensure improved outcomes, nor do short-term responses.

Thinking through cost-benefit analysis and layoff policies


If you’re running a school district or a private school and you are deciding on what to keep in your budget and what to discard, you are making trade-offs. You are making trade-offs as to whether you want to spend money on X or on Y, or perhaps a more complicated mix of many options. How you come to your decision depends on a number of factors:

  1. The cost – the total costs of the various ingredients that go into providing X and providing Y. That is, how many people, at what salary and benefits, how much space at what overhead cost (per time used) and how much stuff (materials, supplies and equipment) and at what market prices?
  2. The benefits – the potential dollar return to doing X versus doing Y. For example, how much dollar savings might be generated in operating cost savings from reorganizing our staffing and use of space, if we spend up front (capital expenses) to reorganize and consolidate our elementary schools where they have become significantly imbalanced over time?
  3. The effects – the relative effectiveness of doing X versus doing Y. For example, in the simplest case, if we are choosing between two reading programs, what are the reading achievement gains, or effects, from each program? Or, more pertinent to the current conversation (but far more complex to estimates), what are the relative effects of reducing class size by 2 students when compared to keeping a “high quality” teacher.
  4. The utility – The utility of each option refers to the extent that the option in question addresses a preferred outcome goal. Utility is about preferences, or tastes. For example, in the current accountability context, one might be pressured to place greater “utility” on improving math or reading outcomes in grades 3 through 8. If the costs of a preferred program are comparable to the costs of a less preferred program… well… the preferred program wins. There are many ways to determine what’s “preferred,” and more often than not, public input plays a key role especially in smaller, more affluent suburban school districts. As noted above, federal and state policy have played a significant role in defining utility in the past decade (and arguably, distorting resource allocation to a point of significant imbalance in resource-constrained districts)

This basic cost analysis framework laid out by Henry Levin back in 1983 and revisited by Levin and McEwan since should provide the basis for important trade-off decisions in school budgeting and should provide the conceptual basis for arguments like those made by Petrilli and Roza in their recent policy brief. But such a framework is noticeably absent and likely so because most of the proposals made by Petrilli and Roza:

  1. are not sufficiently precise to apply such a framework  largely because little is known about the likely outcomes (which may in fact be quite harmful); and
  2. because they have failed entirely to consider in detail the related costs of proposed options, especially up-front costs of many of the options (like school reorganization or developing teacher evaluation systems). Note that the full length book (from which the brief comes) is no more thoughtful or rigorous.

Back of the Napkin Application to Layoff Options

Allow me to provide a back-of-the-napkin example of some of the pieces that might go into determining the savings and/or benefits from the BIG suggestion made by Pettrilli and Roza – which is to use quality based layoffs in place of seniority based layoffs when cutting budgets. This one would seem to be a no-brainer. Clearly, if we layoff based on quality, we’ll have better teachers left (greater effectiveness) and we’ll have saved a ton money or a ton of teachers. That is, if we are determined to layoff X teachers, it will save more money to lay off more senior, more expensive teachers than to lay off novice teachers. However, that’s not the likely what-if scenario. More likely is that we are faced with cutting X% of our staffing budget, so the difference will be in the number of teachers we need to lay off in order to achieve that X%, and the benefit difference might be measured in terms of the change in average class size resulting from laying off teachers by “quality” measures and laying off teachers by seniority.

Let’s lay out some of the pieces of this cost benefit analysis to show its complexity.

First of all, let’s consider how to evaluate the distribution of the different layoff policies.

Option 1 – Layoffs based on seniority

This one is relatively easy and involves starting from the bottom in terms of experience and laying off as many junior teachers as necessary to achieve 5% savings to our staffing budget.

Option 2 – Layoffs based on quality

Here’s the tricky part. Budget cuts and layoffs are here and now. Most districts do not have in place rigorous teacher evaluation systems that would allow them to make high stakes decisions based on teacher quality metrics. AND, existing teacher quality metrics where they do exist (NY, DC, LA) are very problematic. So, on the one hand, if districts rush to immediately implement “quality” based layoffs, districts will likely revert to relying heavily on some form of student test score driven teacher effectiveness rating, modeled crudely (like the LA Times model).  Recall that even in better models of this type, we are looking at a 35% chance of identifying an average teacher as “bad” and 20% chance of identifying a good teacher as “bad.”

In general, the good and bad value-added ratings fall somewhat randomly across the experience distribution. So, for simplicity in this example, I will assume that quality based firings are essentially random. That is, they would result in dismissals randomly distributed across the experience range. Arguably, value-added based layoffs are little more than random, given that a) there is huge year to year error even when comparing on the same test and b) there are huge differences when rating teachers using one test, versus using another.

Testing this out with Newark Public Schools – Elementary Classroom Teachers 2009-10

At the very least, one would think that randomly firing our way to a 5% personnel budget cut would create a huge difference when compared to firing our way to a 5% personnel budget cut by eliminating the newest and cheapest teachers. I’m going to run these numbers using salaries only, for illustrative purposes (one can make many fun arguments about how to parse out fixed vs. variable benefits costs, or deferred benefits vs. short run cost differences for pensions and deferred sick pay, etc.).

We start with just over 1,000 elementary classroom teachers in Newark Public Schools, and assume an average class size of 25 for simplicity. The number of teachers is real (at least according to state data) but the class sizes are artificially simplified. We are also assuming all students and classroom space to be interchangeable.  A 5% cut is about $3.7 million. Let’s assume we’ve already done our best to cut elsewhere in the district budget, perhaps more than 5% across other areas, but we are left with the painful reality of cutting 5% from core classroom teachers in grades K-8. In any case, we’re hoping for some dramatic saving here – or at least benefits revealed in terms of keeping class sizes in check.

Figure 1: Staffing Cut Scenarios for Newark Public Schools using 2009-10 Data

If we layoff only the least experienced teachers to achieve the 5% cut, we layoff only teachers with 3 or fewer years of experience when using the Newark data.  The average experience of those laid off is 1.8 years. And we end up laying off 72 teachers (a sucky reality no matter how you cut it).

If we use a random number generator to determine layoffs (really, a small difference from using Value-added modeling), we end up laying off only 54 teachers instead of 72. We save 18 teachers, or 1.7% of our elementary classroom teacher workforce.

What’s the class size effect of saving these 18 teachers? Well, under the seniority based layoff policy, class size rises from 25 to 26.86. Under the random layoff policy, class size rises from 25 to 26.37. That is, class size is affected by about half a student per class. This may be important, but it still seems like a relatively small effect for a BIG policy change. This option necessarily assumes no downside to the random loss of experienced teachers. Of course, the argument is that more of those classes now have a good teacher in front of them. But again, doing this here and now with the type of information available means relying not even on the “best” of teacher effectiveness models, but relying on expedited, particularly sloppy, not thoroughly vetted models. I would have continued concerns even with richer models, like those explored in the recent Gates/Kane report, which still prove insufficient.

Perhaps most importantly, how does this new policy affect the future teacher workforce in Newark – the desirability for up-and-coming teachers to pursue a teaching career in Newark, where their career might be cut off at any point, by random statistical error? And how does that tradeoff balance with a net difference of about half a student per classroom?

What about other costs?

Petrilli and Roza, among others, ignore entirely any potential downside to the teacher workforce – those who might choose to enter that workforce if school districts or states al-of-the-sudden decide to rely heavily on error prone and biased measures of teacher effectiveness to implement layoff policies.  This downside might be counterbalanced by increased salaries, on average and especially on the front end. That is, to achieve equal incoming teacher quality over time, given the new uncertainty, might require higher front end salaries. This cost is ignored entirely (or simply assumed to come from somewhere else, like cutting benefits… simply negating step increments, or supplements for master’s degrees, each of which have other unmeasured consequences).

I have assumed above that districts would rely heavily on available student testing data, creating error-prone, largely random layoffs, while ignoring the cost of applying the evaluation system to achieve the layoffs. Arguably, even contracting an outside statistician to run the models and identifying the teachers to be laid off would cost another $50,000 to $75,000, leading to reduction of at least one more teacher position under the “quality based” layoff model.

And then there are the legal costs of fighting the due process claims that the dismissals were arbitrary and the potential legal claims over racially disparate firings. Forthcoming law review article to be posted soon.

Alternatively, developing a more rigorous teacher evaluation system that might more legitimately guide layoff policies requires significant up-front costs, ignored entirely in the current overly simplistic, misguided rhetoric.

How can we implement quality based layoffs when we’re supposed to be laying off teachers NOT teaching math and reading in elementary grades?

Here’s another issue that Petrilli, Roza and others seem to totally ignore. They argue that we must a) dismiss teachers based on quality and b) must make sure we don’t compromise class sizes in core instructional areas, like reading and math in the elementary grades.

Let’s ponder this for a moment. The only teachers to whom we can readily assign (albeit deeply flawed) effectiveness ratings are those teaching math and reading between grades 3 and 8. So, the only teachers who we could conceivably layoff based on preferred “reformy” quality metrics are teachers who are directly responsible for teaching math and reading between grades 3 and 8.

That is, in order to implement quality based layoffs, as reformers suggest, we must be laying off math and reading teachers between grades 3 and 8, except that we are supposed to be laying off other teachers, not those teachers. WOW… didn’t think that one through very well… did they?

Am I saying seniority layoffs are great?

No. Clearly seniority layoffs are imperfect and arguably there is no perfect answer to layoff policies. Layoffs suck and sometimes that sucky option has to be implemented. Sometimes that that sucky option has to be implemented with a blunt and convenient instrument and one that is easily defined, such as years of service. It is foolish to argue that teaching is the only profession where those who’ve been around for a while – those who’ve done their time – have greater protection when the axe comes down. Might I suggest that paying one’s dues even plays a significant role in many private sector jobs? Really? And it is equally foolish to argue that every other profession EXCEPT TEACHING necessarily makes precise quality decisions regarding employees when that axe comes down.

The tradeoff being made in this case is a tradeoff  NOT between “keeping quality teachers” versus “keeping old, dead wood” as Petrilli, Roza and others would argue, but rather the tradeoff between laying off teachers on the unfortunately crude basis of seniority only, versus laying off teachers on a marginally-better-than-random, roll-of-the-dice basis. I would argue the latter may actually be more problematic for the future quality of the teaching workforce!  Yes, pundits seem to think that destabilizing the teaching workforce can only make it better. How could it possibly get worse, they argue? Substantially increasing the uncertainty of career earnings for teachers can certainly make it worse.

Bad Teachers Hurt Kids, but Salary Cuts Have no Down Side?

The assumption constantly thrown around in these policy briefs is that putting a bad teacher in front of the kids is the worst possible thing you could do. We have to fire those teachers. They are bad for kids. They hurt kids.

But, the same pundits argue that we should cut pay for the teachers in any number of ways (including paying for benefits) and subject teachers to layoff policies that are little more than random. Since so many teachers are bad teachers – and simply bad people – these policies are, of course, not offensive. Right? Kids good. Teachers bad. Treat kids well. Take it out on teachers. No harm to kids. Easy!

I’m having a hard time swallowing that. That’s just not a reasonable way to treat a workforce (if you want a good workforce), no less a reasonable way to treat a workforce charged with educating children. In fact, it’s bad for the kids, and just plain ignorant to assert that one can treat the teachers badly, lower their pay, morale and ultimately the quality of the teacher workforce and expect there to be no downside for the kids.

Petrilli and Roza make the assumption that there is big savings to be found from cutting teacher salaries directly and also indirectly by passing along benefits costs to teachers.  That’s a salary cut! Or at least a cut to the total compensation package and it’s a package deal! This argument seems to be coupled with an assumption that there is absolutely no loss of benefit or effectiveness from pursuing this cost-cutting approach (because we’ll be firing all of the sucky teachers anyway). That is, teacher quality will remain constant even if teacher salaries are cut substantially.  A substantial body of research questions that assumption:

  • Murnane and Olson (1989) find that salaries affect the decision to enter teaching and the duration of the teaching career;
  • Figlio (1997, 2002) and Ferguson (1991) find that higher salaries are associated with better qualified teachers;
  • Figlio and Reuben (2001) “find that tax limits systematically reduce the average quality of education majors, as well as new public school teachers in states that have passed these limits;”
  • Ondrich, Pas and Yinger (2008) “find that teachers in districts with higher salaries relative to non-teaching salaries in the same county are less likely to leave teaching and that a teacher is less likely to change districts when he or she teaches in a district near the top of the teacher salary distribution in that county.”

To mention a few.

That is, in the aggregate, higher salaries (and better working conditions) can attract a stronger teacher workforce, and at a local level, having more competitive teaching salaries compared either to non-teaching jobs in the same labor market or compared to teaching jobs in other districts in the same labor market can help attract and especially retain teachers.

Allegretto, Corcoran and Mishel, among others, have shown that teacher wages have lagged over time – fallen behind non-teaching professions. AND, they have shown that the benefits differences are smaller than many others argue and certainly do not make up the difference in the wage deficit over time. I have shown previously on my blog that teacher wages in New Jersey have similarly lagged behind!

So, let’s assume we believe that teacher quality necessarily trumps reduced class size, for the same dollar spent. Sadly, this has been a really difficult trade-off to untangle in empirical research and while reformers boldly assume this, the evidence is not clear. But let’s accept that assumption. But let’s also accept the evidence that overall wages and local wage advantages lead to a stronger teacher workforce.

If that’s the case, then the appropriate decision to make at the district level would be to lay off teachers and marginally increase class sizes, while making sure to keep salaries competitive. After all, the aggregate data seem to suggest that over the past few decades we’ve increased the number of personnel more than we’ve increased the salaries of those personnel. That is, cut numbers of staff before cutting or freezing salaries. In fact, one might even choose to cut more staff and pay even higher salaries to gain competitive advantage in tough economic times. Some have suggested as much.  I’m not sold on that either, especially when we start talking about increasing class sizes to 30, 35 or even 50.  Note that class size may also affect the competitive wage that must be paid to a teacher in order to recruit and retain teachers of constant quality. Nonetheless, it is important to understand the role of teacher compensation in ensuring the overall quality of the teacher workforce and it is absurd to assume no negative consequences of slashing teacher pay across-the-board.

Take home point!

In summary, we should be providing thoughtful decision frameworks for local public school administrators to make cost-effective decisions regarding resource allocation rather than spewing laundry lists of reformy strategies for which no thoughtful cost-effectiveness analysis has ever been conducted.

Further, now is not the time to act in panic and haste to adopt these unfounded strategies without appropriate consideration of the up-front costs of making truly effective reforms.

A few references

Richard J. Murnane and Randall Olsen (1989) The effects of salaries and opportunity costs on length of state in teaching. Evidence from Michigan. Review of Economics and Statistics 71 (2) 347-352

David N. Figlio (1997) Teacher Salaries and Teacher Quality. Economics Letters 55 267-271.

David N. Figlio (2002) Can Public Schools Buy Better-Qualified Teachers?” Industrial and Labor Relations Review 55, 686-699.

Figlio (1997, 2002) and Ferguson (1991) find that higher salaries are associated with better qualified teachers

Ronald Ferguson (1991) Paying for Public Education: New Evidence on How and Why Money Matters. Harvard Journal on Legislation. 28 (2) 465-498.

Figlio, D.N., Reuben, K. (2001) Tax limits and the qualifications of new teachers Journal of Public Economics 80 (1) 49-71

Ondrich, J., Pas, E., Yinger, J. (2008) The Determinants of Teacher Attrition in Upstate New York.  Public Finance Review 36 (1) 112-144

Stretching Truth, Not Dollars?

This week, Mike Petrilli (TB Fordham Institute) and Marguerite Roza (Gates Foundation) released a “policy brief” identifying 15 ways to “stretch” the school dollar. Presumably, what Petrilli and Roza mean by stretching the school dollar is to find ways to cut spending while either not harming educational outcomes or actually improving them. That goal in mind, it’s pretty darn hard to see how any of the 15 proposals would lead to progress toward that goal.

The new policy brief reads like School Finance Reform in a Can. I’ve written previously about what I called Off-the-Shelf school finance reforms, which are quick and easy – generally ineffective and meaningless, or potentially damaging – revenue-neutral school finance fixes. In this new brief, Petrilli and Roza have pulled out all the stops. They’ve generated a list, which could easily have been generated by a random search engine scouring “reformy” think tank websites, excluding any ideas actually supported by research literature.

The policy brief includes some introductory ramblings about district level practices for “stretching” the school dollar, but the policy brief focuses on state policies that can assist in stretching the school dollar at the state level and provide local districts greater options to stretch the school dollar. I will focus my efforts on the state policy list.

Here’s the state policy recommendation list:

1. End “last hired, first fired” practices.

2. Remove class-size mandates.

3. Eliminate mandatory salary schedules.

4. Eliminate state mandates regarding work rules and terms of employment.

5. Remove “seat time” requirements.

6. Merge categorical programs and ease onerous reporting requirements.

7. Create a rigorous teacher evaluation system.

8. Pool health-care benefits.

9. Tackle the fiscal viability of teacher pensions.

10. Move toward weighted student funding.

11. Eliminate excess spending on small schools and small districts.

12. Allocate spending for learning-disabled students as a percent of population.

13. Limit the length of time that students can be identified as English Language Learners.

14. Offer waivers of non-productive state requirements.

15. Create bankruptcy-like loan provisions.

This list can be lumped into four basic categories:

A) Regurgitation of “reformy” ideology for which there exists absolutely no evidence that the “reforms” in question lead to any improvement in schooling efficiency. That is, no evidence that these reforms either “cut costs” (meaning reduce spending without reducing outcomes) or improve benefits (or outcome effects).

  1. Creating a rigorous evaluation system
  2. Ending “last hired, first fired” practices
  3. Move toward weighted student funding

B) Relatively common “money saving” ideas, backed by little or no actual cost-benefit analysis – the kind of stuff you’d be likely to read in a personal finance column in magazine in a dentist’s office.

  1. Pool health-care benefits.
  2. Create bankruptcy-like loan provisions. (???)
  3. Tackle pensions
  4. Cut spending on small districts and schools (consolidate?)

C) Reducing expenditures on children with special needs by pretending they don’t exist.

  1. Allocate spending for learning-disabled students as a percent of population.
  2. Limit the length of time that students can be identified as English Language Learners.

D) Un-regulation

  1. eliminate class-size limits
  2. provide waivers for ineffective mandates
  3. eliminate seat time requirements
  4. merge categorical programs
  5. eliminate work rules
  6. eliminate mandatory salary schedules

So, let’s walk through a few of these in greater detail. Let’s address whether there is any evidence whatsoever that these policies a) would actually lead to reduced short run costs while not harming, or even improving outcomes, or b) are for any other reason a good idea.

Creating an Evaluation System

This likely requires significant up front spending- heavy front end investment to design the system and put the system into place. Yes, increased, not decreased spending. And in the short-term, while money is tight. AND, there is little or no evidence that what is being recommended – a Tennessee or Colorado-style teacher evaluation model (50% on value-added scores), would actually reduce spending and /or improve outcomes. Rather, I could make a strong case that such a model will lead to exorbitant legal fees for the foreseeable future (I have a forthcoming law review article on this topic).  The likelihood of achieving long run benefits from these short run expenses is questionable at best. In fact, the likelihood of significant harm seems equal if not greater (see my previous post on this topic: value-added teacher evaluation).

Ending “Last Hired, First Fired” layoff policies

In very crude terms, this approach might simply allow a district – or entire state – to layoff senior, higher salary teachers. Yeah… that could reduce the payroll. Good policy? Really questionable! Of course, Petrilli and Roza also argue that we simply shouldn’t be paying teachers for experience or degrees anyway. So I guess if we did that, we wouldn’t generate savings from this recommendation. Silly me. One or the other, I guess.

Now, we could generate performance increases (at lower spending, if we keep seniority pay, or at constant spending if we don’t) if, and only if, the future actually plays out as simulated in the various performance-based layoff simulations which I, and others have recently discussed. The assumptions in these simulations are bold (unrealistic), and much of the logic circular.

And then there are those short-term legal costs of defending the racially disparate firings, and random error firings.

Eliminating Class Size Limits

Yes, larger classes require less spending – on a per pupil basis. Smaller classes have greater benefit (greater “bang for the buck” shall we so boldly say) in higher poverty settings. A labor market dynamic problem realized in the late 1990s, when CA implemented statewide class size reduction, was that the policy stretched the pool of highly qualified teachers and ultimately made it even harder for high poverty schools to get high quality teachers (a dreadfully oversimplified and disputable version of the story).

Removing class size limits might be reasonable if only affluent districts agreed to increase their class sizes, putting more “high quality” teachers into the available labor pool… who might then be recruited into high poverty districts (another dreadfully oversimplified, if not absurd scenario).  But who really thinks it will play out this way? We already know that affluent school districts a) have strong preferences for very small class sizes and b) have the resources to retain those small class sizes or reduce them further. See Money and the Market for High Quality Schooling.

Eliminating mandatory salary schedules

It seems that in this recommendation, Petrilli and Roza are arguing against state policies that mandate the adoption by local public school districts of specific step and lane salary schedules. They really only provide one brief paragraph with little or no explanation regarding what the heck they are talking about.

I’ve personally never been much of a fan of state rigidity regarding local negotiated agreements – at least in terms of steps and lanes. Many problems can occur where states enact policies as rigid as those of Washington State, were teachers statewide are on a single salary schedule.

The best work on this topic (and I’ve worked on the same topic with Washington data) is by Lori Taylor of Texas A&M who shows that the Washington single salary schedule leads to non-competitive wages for teachers in metro areas, and also leads to non-competitive wages for teachers in math and science relative to other career opportunities in metro areas. The statewide salary schedule in Washington is arguably too rigid. Here’s a link to Taylor’s study:

Taylor, L. (2008) Washington Wages: An Analysis of Educator and Comparable Non-educator Wages in the State of Washington. Washington State Institute for Public Policy.

But this does not mean, by any stretch of the imagination, that removing this requirement would save money, or “stretch” the education dollar. It might allow bargaining units in metro areas in Washington to scale up salaries over time as the economy improves. And it might lead to some creative differentiation across negotiated agreements, with districts trying to leverage different competitive advantages over one another for teacher recruitment.

But, these competitive behaviors among districts may also lead to ratcheting of teacher salaries across neighboring bargaining units, and may lead to increased salary expense with small marginal returns (as clusters of districts compete to pay more for an unchanging labor pool). For an analysis of this effect, see Mike Slagle’s work on spatial relationships in teacher salaries in Missouri. In short, Slagle finds that changes to neighboring district salary schedules are among the strongest predictors of an individual district’s salary schedule. Ratcheting upward of salaries in neighboring districts is likely to lead to adjustment by each neighboring district (to the extent resources are available). Ratcheting downward does not tend to occur (not reported in this article).

Slagle, M. (2010) A Comparison of Spatial Statistical Methods in a School Finance Policy Context. Journal of Education Finance 35 (3)

[note: this article is a shortened version of Mike’s dissertation. The article addresses only the ratcheting of per pupil spending, but the full dissertation also addresses teacher salaries]

In any case, we certainly have no evidence that removing state level requirements for mandatory salary schedules would save money while holding outcomes harmless – hence improving efficiency. Like I said, I’m not a big fan of such restrictions either, but I have no delusion that removing them will save any district a ton of money – or any for that matter.

This recommendation seems to also be tied up in the notion that we shouldn’t be paying teachers for experience or degree levels anyway. Therefore, mandating as much would clearly be foolish. I’ve addressed this idea previously in The Research Question that Wasn’t Asked.

In addition, this recommendation seems to adopt the absurd assumption that we could immediately just pay every teacher in the current system the bachelor’s degree base salary (Okay, the salary of a teacher with 3 years and a bachelor’s degree, where marginal test-score returns to experience fade). We could immediately recapture all of that salary money dumped into differentiation by experience or differentiation by degree, and that we could have massive savings with absolutely no harm to the quality of schooling – or quality of teacher labor force in the short-run or in the long-term. Again, that’s the research question that was never asked. Previous estimates of all of the money wasted on the master’s degree salary “bump” are actually this crude.

For similarly absurd analysis by Marguerite Roza regarding teacher pay, see my previous post on “inventing research findings.”

Move toward Weighted Student Funding

Petrilli and Roza also advocate moving to Weighted Student Funding. They seem to argue that the “big” savings here will come from the ability of states and school districts to immediately take back funding as student enrollments decline. That is, a district in a state, or school in a district gets a certain amount per kid. If they lose the kid, they lose the money. This keeps us from wasting a whole lot of money on kids who aren’t there anymore.

Okay… Now… most state aid is allocated on a per pupil basis to begin with. And, in general, as enrollments fluctuate, state aid fluctuates. Lose a kid. Lose the state aid that is driven by that kid. Some states have recognized that the costs of providing education don’t actually decline linearly (or increase linearly) with changes in enrollment and have included safety valves to slow the rate of aid loss as enrollments decline. Such policies are reasonable.

Petrilli and Roza seem to be belligerently and ignorantly declaring that there is simply never a legitimate reason for a funding formula to include small school district or declining enrollment provisions. I have testified in court as an expert against such provisions when those provisions are completely “out of whack”, but would never say they are entirely unwarranted. That’s just foolish, and ignorant.

Local revenues in many states (and in many districts within states) still make up a large share of public school funding, and local revenues are typically derived from property taxes applied to the total taxable property wealth of the school district. As kids come and go, local revenues do not come and go. If a tax levy of X% on the district’s assessed property values raises $8,000 per pupil – and if enrollment declines, but the total assessed value stays constant, the same tax raises more per pupil, perhaps $8,100. The district would lose state funding because it has fewer pupils (and perhaps also because it can generate larger local share per pupil).  But that’s really nothing new.

There’s really no new “huge” savings to be had here.

UNLESS:

a) we are talking about kids moving to charter schools from the traditional public schools, and for each kid who moves to a charter school, we either require the district to pass along the local property tax share of funding associated with that child (Many states), or reduce state aid by the equivalent amount (Missouri).

b) there exists a property tax revenue limit tied specifically to the number of pupils served in the district (as in Wisconsin and other states) which then means that the district would have to reduce its local property taxes to generate only the per pupil revenue allowed. That’s not savings. It’s a state enforced local tax cut.

So then, why do Petrilli and Roza care about Weighted Student Funding as an option? The above two “Unless” scenarios are possible suspects. Blind reformy punditry regardless of logic is equally possible (WSF is cool… reformy… who cares what it does?).

It’s not really about “saving” money at all. Rather, it’s about creating mechanisms to enable local property tax revenues to be diverted in support of charter schools (even if the local taxpayers did not approve the charter), or to have local budgets forcibly reduced/capped when students opt-in to voucher programs (Milwaukee).

And this isn’t really a “weighted student funding” issue at all. In many states, it already works this way (WSF or not). Big savings? Perhaps an opportunity to reduce the state subsidy to charter schools by requiring greater local pass through – in those states where this doesn’t already occur. But these provisions face significant legal battles in some states. If a state is not already doing this, this policy change would also likely lead to significant up front legal expenses.

In fact, I can’t imagine a circumstance where adopting weighted student funding can be expected to either save money or improve outcomes for the same money. There’s simply no proof to this effect. Sadly, while it would seem at the very least, that adopting weighted funding might improve transparency and equity of funding across schools or districts, that’s not necessarily the case either.

My own research finds that districts adopting weighted funding formulas have not necessarily done any better than districts using other budgeting methods when it comes to targeting financial resources on the basis of student needs. See: http://epaa.asu.edu/ojs/index.php/epaa/article/view/5

Petrilli and Roza’s Weighted Funding recommendation for “stretching” the dollar is strange at best. As a recommendation to state policymakers, adoption of weighted funding provides few options for “stretching” the dollar, but may provide a mechanism for diverting districts’ local revenues to support choice programs (potentially reducing state support for those programs).

As a recommendation to local school district officials, adoption of weighted funding really provides no options for “stretching” the dollar, and may, in fact, increase centralized bureaucracy required to develop and manage the complex system of decentralized budgeting that accompanies WSF (see: http://epx.sagepub.com/content/23/1/66.short)

So,

No savings?

No improvements to equity?

No evidence of improved efficiency?

What then, does WSF have to do with “stretching” the school dollar?

Baker, B.D., Elmer, D.R. (2009) The Politics of Off‐the‐Shelf School Finance Reform. Educational Policy 23 (1) 66‐105

Baker, B.D. (2009) Evaluating Marginal Costs with School Level Data: Implications for the Design of Weighted Student Allocation Formulas. Education Policy Analysis Archives 17 (3)

Savings from Small Districts and Schools

I am one who believes in creating savings through consolidation of unnecessarily small schools and school districts. And, at the school or district level, some sizeable savings can be achieved by reorganizing schools into more optimal size configurations (elementary schools of 300 to 500 students and high schools of 600 to 900 for example, See Andrews, Duncombe and Yinger)

For other research on the extent to which consolidation can help cut costs, see Does School District Consolidation Cut Costs, also by Bill Duncombe and John Yinger (the leading experts on this stuff).

Now, Petrilli and Roza, however, seem to imply that the savings from these consolidations or simply from starving the small schools and districts can perhaps help states to sustain the big districts – STRETCHING that small school dollar. Note that Petrilli and Roza ignore entirely the possibility that some of these small schools and districts (in states like Wyoming, western Kansas, Nebraska) might actually have no legitimate consolidation options. Kill them all! Get rid of those useless small schools and districts, I say!

Here’s the thing about de-funding small schools and districts to save big ones. The total amount of money often is not much… BECAUSE THEY ARE SMALL SCHOOLS!!!!!  I learned this while working in Kansas, a state which arguably substantially oversubsidizes small rural school districts, creating significant inequities between those districts and some of the states large towns and cities with high concentrations of needy students. While the inequity can (and should) be reduced, the savings don’t go very far.

So, let’s say we have 6 school districts serving 100 kids each, and spending $16,000 per pupil to do so. Let’s say we can lump them all together and make them produce equal outcomes for only $10,000 per pupil. A bold, bold assumption. We just saved $6,000 per pupil (really unlikely), across 600 pupils. That’s not chump change… it’s $3,600,000 (okay… in most state budgets that is chump change).

So, now let’s take this savings, and give it to the rest of the kids in the state – oh – about 400,000. Well, we just got ourselves about $9 per pupil. Even if we try to save the mid-sized city district of 50,000 students down the road, it’s about $72 per pupil. That is something. And if we can achieve that, then fine. But slashing small districts and schools to save big, or even average ones, usually doesn’t get us very far. BECAUSE THEY ARE SMALL! GET IT! SMALL DISTRICTS WITH SMALL BUDGETS!

Similar issues apply to elimination of very small schools in large urban districts. It’s appropriate strategy – balancing and optimizing enrollment (reorganizing those too-small high schools created as a previous Gates-funded reform?). It should be done. But unless a district is a complete mess of tiny, poorly organized schools, the savings aren’t likely to go that far.

Let’s also remember that major reconfiguration of school level enrollments will require significant up front capital expense! Yep, here we are again with a significant increased expense in the short-term. Duncombe and Yinger discuss this in their work. Strangely, this slips right past Petrilli and Roza.

Use Census Based Funding for Special Education

So, what Petrilli and Roza are arguing here is that states could somehow save money by allocating their special education funding to school districts on an assumption that every school district has a constant share of its enrollment that qualifies for special education programs. Those districts that presently have more? Well, they’ve just been classifying every kid they can find so they can get that special education money. This flat-funding policy will bring them into line… and somehow “stretch” that dollar.

Let’s say we assume that every district has 16% (Pennsylvania) or 14.69% (New Jersey) children qualifying for special education. Let’s say we pick some number, like these, that is about the current average special education population.  Our goal is really to reduce the money flowing to those districts that have higher than average rates. Of course, if we pick the average, we’ll be reducing money to the districts with higher rates and increasing money to the districts with lower rates and you know what – WE’LL SPEND ABOUT THE SAME IN SPECIAL EDUCATION AID? “Stretching?” how?

And will we have accomplished anything close to logical? Let’s see, we will have slammed those districts that have been supposedly over-identifying kids for decades just to get more special ed aid. That, of course, must be good.

BUT, we will also be providing aid for 14.69% of kids to districts that have only 7% or 8% children with disabilities. Funding on a census basis or flat basis requires that we provide excess special education aid to many districts – unless we fund all districts as if they have the same proportion of special education kids as the district with the fewest special education kids. That is, simply cut special education aid to all districts except the one that currently receives the least.

How is that smart “stretching?”

The only way to “save” money with this recommendation is simply to “cut funding” and “cut services.” And, unless cut to the bare minimum, the “flat allocation” strategy requires choosing to “overfund” some districts while “underfunding” others. One might try to argue that this policy change would at least reduce further growth in special ed populations. But the article below suggests that this is not likely the case either. The resulting inequities significantly offset any potential benefits.

There exist a multitude of problems with flat, or census-based special education funding, which have led to declining numbers of states moving in this direction in recent years, New Jersey being an exception. I discuss this with co-authors Matt Ramsey and Preston Green in our forthcoming chapter on special education finance in the Handbook on Special Education Policy Research.

Of course, there also exists the demographic reality that children with disabilities are simply not distributed evenly across cities, towns and rural areas within states, leading to significant inequities when using Census Based funding. CB Funding is, in fact, the antithesis of Weighted Student Funding. How does one reconcile that?

For a recent article on the problems with the underlying assumptions of Census Based special education funding, see:

Baker, B.D., Ramsey, M.J. (2010) What we don’t know can’t hurt us? Evaluating the equity consequences of the assumption of uniform distribution of needs in Census Based special education funding. Journal of Education Finance 35 (3) 245‐275

Here’s a draft copy of our forthcoming book chapter on special education finance: SEF.Baker.Green.Ramsey.Final

Limit Time for ELL/LEP

This one is both absurd and obnoxious. Essentially, Petrilli and Roza argue that kids should be given a time limit to become English proficient and should not be provided supplemental programs or services – or at least the money for them – beyond that time frame. For example, a child might be funded for supplemental services for 2 years, and 2 years only. Some states have done this. Again, there is no clear basis for such cutoffs, nor is it clear how one would even establish the “right” time limit, or whether that time limit would somehow vary based on the level of language proficiency at the starting time.

Yes, this approach, like cutting special education funding can be used to cut spending and cut and reduce the quality of services. But that’s all it is. It’s not “stretching” any dollar.

Other Stuff

Now, the brief does list other state policy options as well as other district practices. Some of these are rather mundane, typical ideas for “cost saving.” But, of course, no evidence or citation of actual cost effectiveness, cost benefit or cut utility analysis is presented. Petrilli and Roza toss around ideas like a) pooling health care costs, b) redesigning sick leave policies or c) shifting health care costs to employees. These are the kind of things that are often on the table anyway.

I fail to see how this new policy brief provides any useful insights in this regard. Some actual cost-benefit analysis would be the way to go. As a guide for such analyses, I recommend Henry Levin and Patrick McEwan’s book on Cost Effectiveness Analysis in Education.

There are a handful of articles available on the topic of incentives associated with varied sick leave policies, including THIS ONE, School District Leave Policies, Teacher Absenteeism, and Student Achievement, by Ron Ehrenberg of Cornell (back in 1991).

One category I might have included above is that at least two of the recommendations embedded in the report argue for stretching the school dollar, so-to-speak, by effectively taxing school employees. That is, setting up a pension system that requires greater contribution from teacher salaries, and doing the same for health care costs. This is a tax – revenue generating (or at least a give back). This is not stretching an existing dollar. This is requiring the public employees, rather than the broader pool of taxpayers (state and/or local), to pay the additional share. One could also classify it as a salary cut. But Petrilli and Roza have already proposed salary cuts in half of the other recommendations. Just say it. Hey… why not just take the “master’s bump” money and use that to pay for pensions and health care? No-one will notice it’s even gone? We all know it was wasted and un-noticed to begin with.

I was particularly intrigued by the entirely reasonable point that school districts should NOT make the harmful cuts by narrowing their curriculum. I was intrigued by this point because this is precisely what Marguerite Roza has been arguing that poor districts MUST do in order to achieve minimum standards within their existing budgets. I wrote about this issue previously HERE. It is an interesting, but welcome about-face to see Roza no-longer arguing that poor, resource constrained school districts should dump all but the basics (while other districts, with more advantaged student populations and more adequate resources need not do the same).

Utter lack of sources/evidence for any/all of this junk

Finally, I encourage you to explore the utter lack of support (or analysis) that the policy brief provides for any/all of its recommendations. It won’t take much time or effort. Read the footnotes. They are downright embarrassing, and in some cases infuriating. At the very least, they border on THINK TANKY MALPRACTICE.

There is a reference to the paper by Dan Goldhaber simulating seniority based layoffs, but that paper provides no analysis of cost/benefit, the central premise of the dollar stretching brief. The Petrilli/Roza (not Goldhaber) assumption is simply that the results will be good, and because we are firing more expensive teachers, it will cost less to get those good results.

The policy brief makes a reference to “typical teacher contracts” (FN2) regarding sick leave, with no citation… no supporting evidence, and phrased rather offensively (18 weeks a year off? For all teachers? Everywhere! OMG???)

FN2: Typical U.S. teacher contracts are for 36.5 weeks per year and include 2.5 weeks sick and personal days for a total work year of 34 weeks, or 18 weeks time off.

The brief refers to work by NCTQ (not the strongest “research” organization) for how to restructure teacher pay.

The report self-cites The Promise of Cafeteria Style Pay (by Roza, non-peer reviewed… schlock), and makes a bizarre generalized attack in footnote 5 that school districts uniformly defend the use of non-teaching staff as substitutes (no evidence/source provided).

FN5: Districts requiring non-teaching staff to serve as substitutes argue that it is good practice to have all staff in classrooms at least a few days a year.

The brief cites policy reports (and punditry) on pension gaps (including the Pew Center report), and those reports refer to alternative plans for closing gaps over time. These are important issues, but the question of how this “stretches” the school dollar is noticeably absent.

And that’s it. That’s the entire extent of “research” and “evidence” used to support this policy brief.

The problem? Cheerleading and Ceramics, of course!

David Reber with the Topeka Examiner had a great post a while back (April, 2010) addressing the deceptive logic that we should be outraged by supposed exorbitant spending on things like cheerleading and ceramics, and not worry so much about the little things, like disparities between wealthy and poor school districts. I finally saw this post today, from a tweet, and realized I had not yet blogged on this topic.

This logic/argument comes from the “research” of Marguerite Roza, who, well, has a track record of making such absurd arguments in an effort to place blame on poor urban districts and take attention away from disparities between poor urban districts and their more affluent suburban neighbors.

This new argument is really just more of the same ol’ flimsy logic from this crew. For the past several years, Roza and colleagues have attempted to argue that states have largely done their part to fix inequities in funding between school districts, and that now, the burden falls on local public school districts to clean up their act. Here’s an excerpt from one of my recent articles on this topic:

On other occasions, Roza and Hill have argued that persistent between-district disparities may exist but are relatively unimportant. Following a state high court decision in New York mandating increased funding to New York City schools, Roza and Hill (2005) opined: “So, the real problem is not that New York City spends some $4,000 less per pupil than Westchester County, but that some schools in New York [City] spend $10,000 more per pupil than others in the same city.” That is, the state has fixed its end of the system enough.

This statement by Roza and Hill is even more problematic when one dissects it more carefully. What they are saying is that the average of per pupil spending in suburban districts is only $4,000 greater than spending per pupil in New York City but that the difference between maximum and minimum spending across schools in New York City is about $10,000 per pupil. Note the rather misleading apples-and-oranges issue. They are comparing the average in one case to the extremes in another.

In fact, among downstate suburban[1] New York State districts, the range of between-district differences in 2005 was an astounding $50,000 per pupil (between the small, wealthy Bridgehampton district at $69,772 and Franklin Square at $13,979). In that same year, New York City as a district spent $16,616 per pupil, while nine downstate suburban districts spent more than $26,616 (that is, more than $10,000 beyond the average for New York City). Pocantico Hills and Greenburgh, both in Westchester County (the comparison County used by Roza and Hill), spent over $30,000 per pupil in 2005.[2] These numbers dwarf even the purported $10,000 range within New York City (a range that we agree is presumptively problematic); our conclusion based on this cursory analysis is that the bigger problem likely remains the between-district disparity in funding.

http://epaa.asu.edu/ojs/article/viewFile/718/831

My article (with Kevin Welner) goes on to show how states have far from resolved between district disparities and that New York State in particular has among the most substantial persistent disparities between wealthy and poor school districts.For more information on persistent between district disparities that really do exist, see: Is School Funding Fair?.

I have a forthcoming paper this spring where I begin to untangle the new argument about poor urban districts really having plenty of money but simply wasting it on cheerleading and ceramics. Here’s a draft of a section of the introduction to that paper:

A handful of authors, primarily in non-peer reviewed and think tank reports posit that poor urban school districts have more than enough money to achieve adequate student outcomes and simply need to reallocate what they have toward improving achievement on tested subject areas. These authors, including Marguerite Roza and colleagues of the Center for Reinventing Public Education encourage public outrage that any school district not presently meeting state outcome standards would dare to allocate resources to courses like ceramics or activities like cheerleading. To support their argument, the authors provide anecdotes of per pupil expense on cheerleading being far greater than per pupil expense on core academic subjects like math or English.

Imagine a high school that spends $328 per student for math courses and $1,348 per cheerleader for cheerleading activities. Or a school where the average per-student cost of offering ceramics was $1,608; cosmetology, $1,997; and such core subjects as science, $739.[1]

These shocking anecdotes, however, are unhelpful for truly understanding resource allocation differences and reallocation options. For example, the major reason why cheerleading or ceramics expenses per pupil are highest is the relatively small class sizes, compared to those in English or Math. In total, the funds allocated to either cheerleading of ceramics are unlikely to have much if any effect if redistributed to reading or math.

Further, the requirement that poor urban (or other) districts currently falling below state outcome standards must re-allocate any and all resources from co-curricular and extracurricular activities toward improving achievement on tested outcomes may increase inequities in the depth and breadth of curricular offerings between higher and lower poverty schools – inequities that may be already quite substantial. That is, it may already be the case that higher poverty districts and those facing greater resource constraints are reallocating resources toward core, tested areas of curriculum and away from more advanced course offerings which extend beyond the tested curriculum and enriched opportunities including both elective courses and extracurricular activities.  Some evidence on this point already exists.

The perspective that low performing districts merely need to reallocate what they already have is particularly appealing in the current fiscal context, where state budgets and aid allocations to local public school districts are being slashed. Accepting Roza’s logic, states under court mandates or in the shadows of recent rulings regarding educational adequacy, but facing tight budgets may simply argue that high poverty and/or low performing districts should shift all available resources into the teaching of core, tested subjects. Lower poverty districts with ample resources that exceed minimum outcome standards face no such reallocation obligations, leading to substantial differences in depth and breadth of curriculum. Arguably a system that is both adequate and fair would protect the availability of deep and broad curriculum while simultaneously attempting to improve narrowly measured outcomes.

More later as this research progresses.


[1] “Downstate Suburban” refers to areas such as Westchester County and Long Island and is an official regional classification in the New York State Education Department Fiscal Analysis and Research Unit Annual Financial Reports data, which can be found here: http://www.oms.nysed.gov/faru/PDFDocuments/2008_Analysis.pdf and http://www.oms.nysed.gov/faru/Profiles/profiles_cover.html

[2] Interestingly, however, Bridgehampton and New York City have relatively similar “costs” due to Bridgehampton’s small size and New York City’s high student needs (see Duncombe and Yinger, 2009). The figures offered in this paragraph are based on Total Expenditures per Pupil from State Fiscal Profiles 2005. http://www.oms.nysed.gov/faru/Profiles/profiles_cover.html. Results are similar when comparing current operating expenditures per pupil.

New from the Center on Inventing Research Findings

The other day, the Center on Reinventing Public Education (CRPE) at University of Washington released a bold new study claiming that Washington school districts underpay Math and Science teachers relative to other teachers – which is clearly an abomination in a state that is home to high-tech industries like Boeing and Microsoft.

The study consisted of looking at the average salaries of math and science teachers and other teachers in several large Washington State school districts and showing that in most, the average for math and science teachers is lower than for other teachers. As it turns out, the average experience of math and science teachers is lower and far more of them are in their first five years. So, it’s mainly about the experience differential. The authors infer from this that turnover of math and science teachers must be higher, but never actually test this assumption. They next infer that this turnover must be a function of having less competitive salaries – relative to what they could earn outside of teaching.

The study never calculates relative turnover of math and science versus other teachers. Rather, the study implies that lower average experience levels must be indicative of higher turnover. The only follow-up analysis on this point is to show that math and science teachers, in addition to being less experienced, are also younger. Wow! That doesn’t validate the turnover claim though, which may be true… but no validation here.

This is a silly study to begin with, but check out the not-so-subtle difference between the press release and the study itself.

The Press Release
http://www.crpe.org/cs/crpe/view/news/111

The analysis finds that in twenty-five of the thirty largest districts, math and science teachers had fewer years of teaching experience due to higher turnover—an indication that labor market forces do indeed vary with subject matter expertise. The subject-neutral salary schedule works to ignore these differences.

The Study
http://www.crpe.org/cs/crpe/download/csr_files/rr_crpe_STEM_Aug10.pdf

That said, the lower teacher experience levels are indicative of greater turnover among the math and science teaching ranks, lending support to the hypothesis that math and science teachers may have access to more compelling non-teaching opportunities than do their peers. (p. 5)

Both are a stretch, given the thin analysis, but the press release declares outright that turnover is the issue, while the study merely infers without ever testing or validating.

The study goes on to be an indictment of paying teachers more for years of experience – (because we all know that experience doesn’t matter?) – and argues that differential pay by teaching field is the answer. This is an absurd false dichotomy. Even if it is reasonable to differentiate pay by teaching field that does not mean that it is unreasonable to differentiate by experience, or that taking dollars away from experience-based pay is the only way to differentiate by field.

I happen to agree that there exist significant problems with Washington’s statewide teacher salary schedule, and that among other things, math and science teachers in Washington State are disadvantaged on the broader labor market. But the CRPE study does nothing to advance this argument.

Previous work by Lori Taylor, of Texas A&M does:

Report on Taylor Study:

http://www.wsipp.wa.gov/rptfiles/08-12-2201.pdf

Taylor Study:

http://www.leg.wa.gov/JointCommittees/BEF/Documents/Mtg11-10_11-08/WAWagesDraftRpt.pdf

The CRPE study goes further to say that the findings indicate that school districts haven’t taken seriously a state policy initiative to increase investment in math and science teaching. So let’s say that the bill to which the CRPE press release refers – House Bill 2621 – really did stimulate districts to step up their efforts to hire more math and science teachers. What would likely happen to math and science teacher average salaries? Well, many new math and science teachers would enter the system. That would alter the experience distribution of math and science teachers – they would likely become less experienced on average – and hence their average salaries would decline and be lower than average salaries in other fields not stimulated by similar initiatives.

When I get a chance, I’ll try to play around with my Washington teacher data set and post some follow-up analyses.

Kevin Welner and I point to similar misrepresentations of findings from several reports from this same center in this article on within and between-district financial disparities:

Baker, B. D., & Welner, K. G. (2010). “Premature celebrations: The persistence of interdistrict funding disparities” Educational Policy Analysis Archives, 18(9). Retrieved [date] from http://epaa.asu.edu/ojs/article/view/718

And now, for some fun follow-up figures:

These figures use individual teacher level data from the State of Washington. I include all teachers holding “secondary” assignments and identify teachers certified to teach biology, chemistry, physics, general science and math (and all subcategories) using the certification record files on the same teachers. Note that some teachers in the data set hold multiple assignments, so the total numbers of cases in these graphs is not an exact match for the total number of individual teachers. I haven’t asked for Washington Teacher data for a few years, so these only go up to 2006-07. Unlike the CRPE report, which cherry picks 30 districts, I use the whole state. If I get a chance, I’ll play with some other cuts at the data. These data don’t coincide at all with the CRPE “findings.”

Here are the experience differences:

Here are the salary differences, on average, which coincide with the experience differences:

Now, here are the total numbers of teachers, and apparent decline in share that are math/science certified over this time period. Math/science teachers were relatively flat, while others grew.

Finally, here’s a portion of the regression model of certified base salaries, where I control for degree level, experience, year, hours per day and days per year, all of which influence salaries. Interestingly, this regression shows that math and science teachers, holding all that other stuff constant, made about $380 more than non-math/science teachers, even under the fixed salary schedule.