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Thoughts on Improving the School Funding Reform Act (SFRA) in NJ

I’ve seen a number of tweets and vague media references of late about the fact that NJ Education Commissioner Cerf will at some point in the near future be providing recommendations for how to change the School Funding Reform Act of 2008.

I also have it on good authority that NJDOE has convened a working group to discuss how to alter SFRA and are bringing in outside consultants for ideas. To no surprise, I’ve been left out of these conversations, despite my narrowly focused expertise on these very topics.

SFRA is subject to review by the department. Most of SFRA is laid out in statute, or laws passed by the legislature. But, as I understand it, the department of education does have some latitude to “tweak” parameters within SFRA. For example, adjusting/changing various weights and other factors which drive more money to some districts and less to others.

Now, I hate to stick my nose in on this process with my own preemptive recommendations, but you see, this happens to be a topic I know something about. After all, if within my broad areas of expertise on education policy/finance there is one area in which I really specialize it’s the design of state school finance formulas to meet student needs. And, I happen to have a little background on NJ’s SFRA. So, here’s my free advice. A little pro-bono technical advisement.

First, keep in mind that I have in the past testified on problems with SFRA, specifically focusing on what I consider to be technical errors made in the original design of the formula which fall under the umbrella of “tweakable” stuff.  I also happen to have done research  conference presentations and have published peer reviewed research related to some of the problematic features of SFRA – specifically the way the state chose to adjust for competitive wage variation across settings and the way the state chose to fund special education.

My apologies to all the non-Jersey and non-finance geeks out there for whom this analysis is going to quickly go technical. Can’t avoid it. Would take far too much space to provide full background on each issue. But I do have complete related documentation linked throughout. My reason for this post is simply to get this stuff out there. To make it known what the actual, technical issues are and what should be addressed when talking about “tweaking” SFRA. Some background is in order though, if for no other reason to explain how I’ve narrowed my scope here.

First, state school funding formulas like SFRA start out by calculating an “adequacy budget” target for each school district:

Adequacy Budget = (Base Funding + Student Need Funding) x Geographic Cost Variation

Typically, the student need category includes additional funding for a) low income children, b) children with limited English language proficiency, and c) children with disabilities. Under geographic cost variation, states generally adjust for geographic variation in competitive wages (how much more does it cost to pay teachers competitively in one labor market versus another) and for small, remote and sparsely populated districts (economies of scale & sparsity). The latter issue is less relevant in NJ.

Typically the second step in a state school finance formula is the parsing of state versus local responsibility to pay for the adequacy budget:

Foundation Formula State Aid = Adequacy Budget – Local Fair Share

This part is important too, especially for balancing tax equity concerns. But, in this post and in most of my analyses of SFRA, I’m focused on getting those adequacy targets correct.  And with SFRA, there is plenty to talk about.

SFRA emerged in part from an analysis prepared for the department of education on the costs of providing an adequate education. That report, by John Augenblick and Associates was produced to the department around 2003, but was not released by the department until 2006. Elements of that report were used to guide a new school funding formula adopted in 2008 – SFRA.

It’s really important to understand that the adoption of state school funding formulas is necessarily a political process. That’s just reality. One can ponder a world in which we substitute technical expertise for political deliberation as somehow being the perfect substitute, but even I understand that’s not realistic.

And quite honestly the quality of technical advisement varies widely. I would go so far as to say that some technical advisement is clearly better than other technical advisement, and some is not worth a damn. For examples of the latter, see:   and:

So, the reality is that legislatures adopt something, perhaps with technical advisement and state courts are available to hear any legally relevant grievances (and consider technical advisement) to evaluate whether those concerns rise to the level of constitutional violation.

I often assist in identifying what those grievances are. Here, I’m pointing mainly to technical quibbles over what came out of the legislative process in New Jersey. These are technical quibbles for which I would argue the research suggests there is a “right way” to do things and the New Jersey legislature and department of education chose the “wrong way.” These are technical quibbles which result in relatively modest, though important corrections to the setting of district “adequacy budgets.” And these are technical quibbles which the court appointed special master decided did not rise to a level of constitutional violation. That is, SFRA was “good enough” to meet constitutional muster.

So then, I suggest that the departmental (regulatory) review process is the right time to address these technical problems.

Table 1 provides my short list of relatively easy fixes.

First, when adopting SFRA someone, somewhere along the line suggested that the formula provide substantially greater money for each high school student than for each elementary student and marginally more money for each middle school student than for each elementary student. But, there is no clear evidence – no firm research basis for such differentiation. No evidence, for example, that it costs more to provide equal educational opportunity in districts that have a larger share of secondary than elementary students. Rather, differences that do exist in spending on high school versus elementary students are merely artifacts of the ways in which districts have typically spent regardless of which children would benefit more from additional expenditure. The most problematic feature of this adjustment is that higher poverty districts tend to have smaller shares of their total enrollment in high school, meaning that this adjustment drives more money to lower poverty and less to higher poverty districts. And it does so without any real justification. This pattern occurs for a variety of reasons, including dropout rates but also family migration patterns and family economic status shifts with maturation.

Second, when determining how to include an adjustment for differences in competitive wages across areas of New Jersey, department officials decided to rely conceptually on a new approach proposed by the National Center for Education Statistics – the Comparable Wage Index (see link below). But then they abandoned the actual index and the actual methods behind it to come up with their own. In their own method, NJDOE looked not at labor market level wages but at county level wages of non-teachers (controlling for age, occupation, industry and education level). By using county level data, NJDOE officials came up with a “geographic cost adjustment” that gives the biggest adjustments to the highest income counties (Bergen, Morris, Essex) rather than broadly applying the adjustment to regions of the state. Most problematically, this GCA gives a bigger funding boost to affluent Ridgewood (Bergen) than to nearby Paterson (Passaic) and to Franklin Township than to New Brunswick. That’s just wrong!

Third, and this is a big one, when adopting SFRA the choice was made to fund special education by a method called Census Based funding. That is, assuming that every district really has or should have the same share of population in need of services. They set the rate to 14.69% of students. The argument is that districts with more than that have simply been identifying more to chase additional funding and not that they actually have greater need. I address the flaws of this logic extensively in the linked research article below. Of course, the most absurd aspect of financing every district as if they have 14.69% children with disabilities is the assumption that it is somehow appropriate to fund many districts at that level who actually have far fewer children in need. Fiscal prudence this is not! But again, it does tend to reduce funding in higher poverty urban districts as well as larger, poor remote southern NJ towns (see my research article).

Fourth, in another seemingly back of the napkin exercise, someone decided that a child who is both from a low income background and with limited English language proficiency clearly doesn’t need the additional funding tied to both characteristics, and instead should be provided something in between. So, they instituted a “combination weight” which was a marginal increase over the low income weight, instead of the sum of the low income weight and LEP/ELL weight. I could probably make a stronger case that increased concentrations of both needs in districts serving very high concentrations of children who are both low income and non-English speaking leads to escalating not diminishing costs. Clearly, use of this weight instead of using the sum of the two reduces funding to the districts with the highest concentrations of students who are both poor and non-English speaking. Further, if a district is majority low income, each marginal child who is non-English speaking is more likely to be both and receive the lower combination weight.

Table 1. Summary of Current Errors and Proposed Fixes

Errors in Original SFRA 2008-09 How it Works  Why it’s Wrong Alternative
Grade Level Weight 1.0 Elementary Based on back of the napkin analysis. No real basis in true cost differential. Disadvantages higher poverty districts with lower share of children in upper grades. Eliminate (Revenue neutral, set to average)
1.04 Middle
1.17 Secondary
Geographic Cost Adjustment Based on non-teacher wages in county County is the wrong unit for this analysis. Should be labor market (clusters of counties). Current approach rewards affluent counties (Bergen, Morris, Somerset). Labor Market Based Comparable Wage Index
Census Based Funding of Special Education Special education funding is allocated in flat amount assuming each district has 14.69% children qualified for special education. This assumption is wrong and it leads to significant inequities in special education funding per child with actual needs.  Allocate on need basis
Combination Weight Children who are both ELL and Low Income do not receive weighted funding for both, but rather receive an adjustment between the two. Reduction was based on back of the napkin estimate, and signifcanlty draws funding away from most needy districts. Reinstate full weighting for both

Here is a link to my full report in which I first identify these issues:

Baker.PJP-SFRA.Report.WEB (My complete report explaining the above problems)

Figure 1 shows what happens if we run a formula simulation based on the original 2008 SFRA parameters, and if we incrementally fix each one of these errors.

First, I remove the Combination weight and replace it with an option where each child can receive the sum of the at risk weight and the LEP/ELL weight if they qualify for both.  Table 2 below shows that taking this approach raises the combo weight cost for TYPE 3 districts from $212 million to $330 million. And, looking at the second set of bars in Figure 1, it increases funding in lower income, higher need districts. Note that these are shifts in the total adequacy targets, for which costs will be shared between the state and local districts (albeit increasing targets more in districts heavily reliant on state aid).

Second, I allocate special education funding according to actual concentrations of children with disabilities. This does come at an increased total cost as well, raising total target funding for special education from $991 million to just over $1 billion. Again, total, to be funded by state and local, but again with stronger effect on districts more dependent on state aid.

Third, I get rid of that pesky grade level adjustment and replace it with the revenue neutral average foundation funding level. This does drive some more money into lower income districts.

Fourth, I replace the county level geographic cost adjustment with the National Center for Education Statistics adjustment, set to a statewide average of 1.0 (to make it more revenue neutral). This ain’t perfect. The NCES index has some “rough edges” (see my linked paper). But it’s still more justifiable in general, even if it does hurt some districts which actually need more help. This issue really requires a complete redo!

Figure 1. Simulation based on Operating Type 3 Districts

Table 2 provides some fiscal implications, as noted above, but it’s important to understand that these fiscal implications are based on a simulation of only Type 3 districts (which does include most of the kids). Table 2 is intended to show the patterns of reshuffling that would occur with these corrections.

Table 2. Simulation based on Operating Type 3 Districts

Formula Component Status Quo Remove Combo Fix Special Ed Remove Grade Level Fix GCA Fix All
Total Base Cost $9,547 $9,547 $9,547 $9,547 $9,547 $9,547
Total Cost of At Risk $1,610 $1,610 $1,610 $1,611 $1,610 $1,610
Total Cost of LEP/ELL $70 $70 $70 $70 $70 $70
Total Cost of Combo $212 $330 $212 $212 $212 $330
Total Cost of Special Ed Base $991 $991 $1,018 $991 $991 $1,018
Full State Funding            
Total Cost of Special Ed Categorical $496 $496 $509 $496 $496 $509
Bottom Line Before Regional Wage Index $12,926 $13,044 $12,966 $12,927 $12,926 $13,084
Bottom Line After Regional Wage Index $13,007 $13,126 $13,043 $13,008 $13,041 $13,198

Figure 2. Distribution of Need-based Adjustments before Adjustment

(excludes special education)

Figure 3. Distribution of Need-based Adjustments after Adjustment (Fix All)

(excludes special education)

The bottom line here is that the reason each and every one of these corrections is important is that each of the original errors of logic and analysis that found their way into the SFRA formula shifts funding away from higher need and toward lower need districts. These aren’t huge shifts, but they’re not trivial either.

For those who wish to play around, here’s the simulation:

Aid Simulation (MS Excel File with Macros)

And for those wishing some additional technical reading to explain my arguments above, here are links to some of my related writing.

AERA.WageIndexPaper.March2008 (Conference Paper on Problems with NJ Wage Index)

Link to Published Article on Problems with Census Based Special Education Funding


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Bruce D. Baker

Bruce Baker is Professor and Chair of the Department of Teaching and Learning at the University of Miami. Professor Baker is widely recognized as the nation’s lea...