Private Public Schools – OK Idea – Bad Calculations

I read with curiosity today, the Fordham Institute’s new report on “Private Public” schools, or elementary schools where fewer than 5% of children qualify for free or reduced lunch and middle or secondary schools where fewer than 3% qualify. Not a bad idea on their part, but some of the numbers just didn’t match up with my reasonably sound knowledge of the NCES common core Public School Universe data.

For example, on Page 6, State Findings, the report indicates 70 private public schools in Illinois, and on page 7, the report indicates 402 such schools in New Jersey. These are two states where I have used the most recent available 3 years of NCES CCD data quite often. While the New Jersey numbers seem close to reasonable, the Illinois numbers are undoubtedly low – and quite honestly, wrong.

First, here’s my tally of total schools by grade level in Illinois and New Jersey:

|                 schlevel08
state_name | 1-Primary   2-Middle     3-High    4-Other |     Total
———–+——————————————–+———-
Illinois |     2,562        777        788        203 |     4,330
New Jersey |     1,547        453        425        158 |     2,583
———–+——————————————–+———-
Total |     4,109      1,230      1,213        361 |     6,913

(sorry for the messy layout)

Next, here’s my tally for total schools by grade level with less than 5% free or reduced lunch in 2007-08:

. tab state schlevel08 if pct_freereduced08<.05

|                 schlevel08
state_name | 1-Primary   2-Middle     3-High    4-Other |     Total
———–+——————————————–+———-
Illinois |       281         89         65          4 |       439
New Jersey |       273         98         94          7 |       472
———–+——————————————–+———-
Total |       554        187        159         11 |       911

And again in 2006-07:

. tab state schlevel08 if pct_freereduced07<.05

|                 schlevel08
state_name | 1-Primary   2-Middle     3-High    4-Other |     Total
———–+——————————————–+———-
Illinois |       302         90         60          3 |       455
New Jersey |       194         74         73          6 |       347
———–+——————————————–+———-
Total |       496        164        133          9 |       802

In either year, and many other years, Illinois has far more than 70 elementary schools alone (280 to 300) under 5% free or reduced price lunch. The New Jersey numbers, while close, can’t be reconciled that easily either.

Fordham includes a footnote which suggests that schools reporting no children qualifying for free or reduced lunch were dropped on an assumption of non-reporting/non-participation. This is likely an incorrect assumption and one that should be checked across multiple years.

For example, here is a map of district level low income rates (background shading, based on state data source) and schools reporting “0” Free Lunch children (to NCES CCD) in North Shore areas near Chicago. Note that most of the “0” flags by schools are in very low poverty districts. These likely are “Private Public” schools by the Fordham definition, but were inappropriately excluded by their count method:

Here are some New Jersey “0” values for free or reduced lunch, against a backdrop of median family income. The “0” value schools here are in Franklin Lakes and Saddle River. I suspect that those “0” values for kids in poverty are real – not errors in the data. There were likely better ways to handle these values than to simply exclude all “0” values. For example, checking across multiple years, or identifying “0” value schools in districts that show higher versus lower U.S. Census poverty rates (not subject to district level reporting). “0” values in low poverty districts are more likely to be correct where as “0” values for schools in high poverty districts are more likely reporting error.

Note: I just ran a quick test of this latter approach using Census Small Area Income and Poverty Estimates. About 198 of 341 Illinois “0” value schools are in districts with less than 5% poverty. About 303 of those 341 are in districts with less than 10% poverty – using Census poverty tabulations. These schools likely should have been included as “Private Publics” rather than excluded outright.

===== On a related note:

I should also point out that Fordham is among those organizations that has frequently pointed the finger at school districts as being the primary causes of persistent inequities, and not state education systems. Fordham does not point out in their report that almost invariably, these private public schools are clustered in private public school districts. The low poverty schools are in low poverty districts often immediately adjacent to high poverty schools in high poverty districts. That is, the inequity the authors reveal in this report is largely a between not within district inequity and one that cannot be resolved by reshuffling resources within districts, as many of their previous reports have argued (most notably Fund the Child).

Here’s a fun map of New Jersey Private Public Schools in the Newark metro area:

Data for NJ and IL available on request.

NJ Surplus Drill-down Redux

This is a quick reply to NJ Left Behind’s highly suspect if not outright bogus NJ Surplus Drill-down. The crux of my response to NJ Left Behind’s summary of NJ school district surpluses, is that his/her analysis completely distorts the distribution of school district surpluses by not taking into account district size (enrollment). Of course the larger districts on average have larger surpluses. And Abbott districts on average are larger. Now, this is not uniformly the case, but for the most part, the largest surpluses are in larger districts (indeed there are some large districts with no surplus and some smaller districts with large surpluses).

The more appropriate way to look at these numbers is in per pupil terms. First, here are the per pupil Total Surpluses by district factor group and by Abbott status:

Interestingly, relative to districts in the same factor group (wealth-income category), Abbott districts seem to be carrying somewhat smaller per pupil surpluses. Further, total surpluses per pupil in Abbott districts on average are lower than surpluses in DFG J districts.

Here is the proposed state aid withholding (in other words, proposed CUTS) by district factor group and Abbott status:

Note in this case that state aid withholding is systematically higher in poorer district factor groups, though lower in Abbott districts relative to others in their factor group.

Finally, here is the withholding as a share of total surpluses:

So, the bottom line here is that the poorest Abbott districts are in fact taking the biggest hit in terms of the share of total surpluses that will be withheld from state aid. A somewhat different story from the deceptively oversimplified NJ Left Behind post.

Today’s fun maps: NYC charter school free lunch rates

Just for fun, here are a few maps of New York City traditional public, special public and public charter schools. Charter schools are indicated with an asterisk. School level rates of children qualifying for free lunch are indicated by circle color. Deep red circles have free lunch shares over 83.6%. Blue circles have very low free lunch shares. Free lunch shares and school locations (lat / lon) are from the National Center for Education Statistics Common Core – Public School Universe 2007-08. Note that as with my previous NJ charter slides, NYC charter schools tend to serve somewhat lower shares of children qualifying for free lunch than are served by many of the surrounding traditional public schools.

A closer look at New Jersey taxes

I often hear talk radio pundits ranting about New Jersey’s supposed highest in the nation taxes – that New Jersey’s taxes are driving people out of the state. I’ll tackle the migration issues in a later post, but any attempted link to tax policy as a single driver is a stretch, to say the least. I have previously addressed the absurdity of the “Small Business Survival Index,” as a standard for measuring whether or not a business should or would locate in a particular state.

I have also pointed out that within New Jersey, property taxes as a share of income remain lower in higher wealth suburban communities, despite claims that those communities are suffering at the hands of decades of state funding being driven disproportionately to poor urban communities. Indeed, property taxes in the wealthier communities might be lower if they received more state aid – but they are already inequitably low compared to middle and lower wealth communities. I have pointed out before that these same communities – high wealth suburbs – remain in control of the teacher salary game.

Those issues aside, here are a few graphs I made yesterday just out of curiosity using the data tool from taxpolicycenter.org.

So, what do we learn from these graphs?

1) When it comes to total taxes, New Jersey is not at the top. While higher than average, New Jersey is relatively close to the rest of the pack, and lower than some states. Overall, as in most other states, total taxes as a share of income have increased gradually over time.

2) When it comes to either sales or income taxes, New Jersey is not as high as other states in the region. Income taxes as a percent of income are, in fact, relatively low. Sales taxes as a percent of income are relatively low and have declined over time.

3) Property taxes as a percent of income in New Jersey are highest in the figures above. Vermont and New Hampshire, not shown on property tax as percent of income, are both higher than New Jersey on that measure. New Jersey does not, by this measure, have the highest property taxes in the nation!

It is particularly important to understand that these three major sources of tax revenue should be considered collectively. It’s a package deal – a portfolio. Different states rely on different mixes of state level sales and income tax and local property tax (to oversimplify a bit). Local property tax revenues are responsive to different levels of aid received from the state to municipalities or local school districts (intergovernmental aid). Where local homeowner voters desire or expect a certain level of public service, but state aid comes up short, property taxes are typically used to make up the difference (though state imposed limits may restrict this option). Similarly, if increased aid is received but local spending preferences remain constant, local property taxes may be reduced in response to the aid.

Yeah… yeah… that’s the professor in me talking. The point here, as we know in New Jersey, is that property tax increases are used to make up for state aid shortfalls (whether municipal aid or school aid), and state aid increases can be used to slow growth in property taxes.

As the graphs above show, New Jersey is relatively high in its reliance on local property taxes. The reality is that this reliance on high property taxes reflects the demand for high quality public schools in those communities where local public schools are most reliant on property taxes (least reliant on state aid). In other words, the relatively high property tax burden in NJ is self-inflicted, and at a local level, across a multitude of relatively small municipalities – not large bureaucracies, but small communities.

Meanwhile, our state level taxes are far from out of line with neighboring states or the nation. And even when we add the property taxes to the state level taxes to evaluate our cumulative effort, New Jersey is not out of line, and certainly is not the most taxed state in the nation.

Note:

There is actually an upside to high reliance on property taxes to fund public schools. What we saw in the last, smaller, economic downturn (2001 to 2002) was that in states where education systems were most reliant on property taxes, public schools took a smaller budget hit than in states where education systems were most reliant on state general funds – especially where those general funds were heavily dependent on income tax revenues. Over time, state income tax receipts have become much more sensitive to economic downturn because a smaller share of income is wage income and a larger share is investment income & other non-wage income which tends to fluctuate more than wage income. These days, state income tax receipts tend to drop most sharply in economic downturn, sales tax receipts much less, and local property tax revenues not much if at all. As such, it is a good idea for states to maintain a balanced portfolio of revenues. One might argue that New Jersey’s portfolio is a bit imbalanced. Heavy on property taxes and relatively light on sales taxes in particular.

Another interesting twist is that there exists little or no relationship between the percent of funding generated through local property taxes and the overall equity of a state’s school funding system. It all depends on how the state aid allocations are distributed with respect to local revenues.

CAP’s Title I Myth

I just read a copy of “Spoonful of Sugar” from Center for American Progress in which they again propose fixes to Title I funding, which I have pointed out in the past are based on misguided assumptions and analyses (or lack thereof).

Please see my previous analysis here:

https://schoolfinance101.wordpress.com/2009/11/27/title-i-does-not-make-rich-states-richer/

The authors of this “spoonful” note:

Still other districts would see their allocations drop because the proposed formula
removes the current bias toward high-spending states that exert relatively low fiscal
effort in education funding.

(page 2)

The inclusion of an effort factor in this particular version of the CAP analysis appears to improve their proposal somewhat (perhaps… maybe?). But the proposal – or spoonful – still fails to address the poverty measurement problem which is substantial. For example, the spoonful recommends much larger increases for Mississippi, Arkansas and Alabama than for New York, California or New Jersey (Figure 1). But, this figure shows that after correcting for poverty measurement and regional costs, the latter three states are much less well funded under Title I presently than the former three states.

My post above explains clearly and with data and with links to prior presentations and Census bureau analyses on this topic that this assumption by CAP that Title I funding favors rich states is simply wrong and based on bad analyses (rooted in mis-measurement of poverty differences across states). Yes, it is illogical to drive money to states simply on their ability to spend more on their own. That portion of the current Title I formula is problematic (okay… just plain silly) on its face. But, the resulting distribution pattern is far less problematic and – once again – does not, on average favor Rich States over Poor States.

Apparently, I need to reinforce this point even more (from previous post):

Let me clarify that the same issue of mis-measurement of poverty plagues urban-rural comparisons within states. Rural poverty is, in relative terms, overstated compared to urban poverty. So too are rural costs (competitive wages) lower than urban costs. So, just as it is true that Title I does not necessarily overfund “rich” states, Title I also does not necessarily overfund urban districts at the expense of rural ones. Unfortunately, I do not yet have available a finer grained adjusted poverty measure which will allow me to easily display the urban/rural issue.

CAP’s spoonful brief is backed by their analyses here: http://www.americanprogress.org/issues/2010/02/pdf/bitter_pill.pdf

These analyses include faulty assumptions about rural-urban poverty distribution in an ill-conceived example applied to Missouri – a state on which I have conducted extensive research on school funding in the past.

Another “You Cannot Be Serious!”

Saw this today:

http://www.washingtonpost.com/wp-dyn/content/article/2010/01/29/AR2010012903405.html

Huffman opines:

I’m picking on New Jersey not because it has the worst plan (it doesn’t) but because it so perfectly embodies the old way of applying for federal education funding — lots of promises and ideas; little chance of change on the ground.

By contrast, Louisiana submitted a clear, concise, actionable plan to reform a large swath of its public schools.

The beauty of Louisiana’s reform model lies in its simplicity. The state has taken critical baseline steps, it proposes expanding projects that have shown promising results, and it has ensured that participating school districts will actually do the things that are in the application.

Louisiana already built and uses a data system that ties students’ test scores to the teachers who taught them and to the universities and programs that trained the teachers. In its application, Louisiana proposes expanding the use of data and using test-score results to count for 50 percent of teacher evaluations and to help drive decisions of hiring, retaining, and promoting teachers and principals.

Thankfully, because I have little time this morning, I’ve already addressed this issue in at least two posts.

I discuss Louisiana specifically here:

https://schoolfinance101.wordpress.com/2009/12/18/disg-race-to-the-top/

And the issue of whether state data systems alone can save a state that has generally abandoned its public education system here:

https://schoolfinance101.wordpress.com/2009/12/15/why-do-states-with-best-data-systems/

One might make the simple argument that New Jersey’s old way of doing things, including sufficient financial support for schools and wider participation in the public education system – actually works – at least when compared to many other states – and certainly when compared to Louisiana. That said, Louisiana is in far greater need of stimulating improvement- but until Louisiana actually makes a substantial state commitment to its public K-12 and higher education system that’s not likely to happen.

You cannot be serious bonus clip on link above!

NCTQ Teacher Policy Ratings: Where’s the quality?

First, to the media – the National Council on Teacher Quality Ratings are NOT ratings of actual differences in Teacher Quality across states. They are ratings of supposed steps which can be taken in state policy in order to improve teacher quality. Here, the blame goes on the media spin, not on NCTQ.

NCTQ does make some reasonable attempts to explain the research basis for their policy elements. However, NCTQ fails miserably at understanding the importance of context within which policies are applied. For example, under AREA 2, NCTQ cites the importance of increasing numbers of teachers from more competitive colleges, and cites expanding the teacher pool as a way to accomplish this, through policies such as alternative certification. My own work a few years back on charter school hiring in states with more and less relaxed teacher certification requirements provides some support for this notion. But, my research also shows that in some cases, expanding the pool weakens, on average, the academic credentials of teachers. Some states and some regions of the country simply don’t have more competitive colleges and universities.

As many of these rating/grading systems which strongly favor deregulatory policies (and the power of state data systems) do, the NCTQ policy ratings favor those states that in fact have the weakest overall public education systems including the academically weakest teachers – of all things. NCTQ only handed out Cs and Ds for grades (and a few Fs). A quick tally based on my prior analyses of Schools and Staffing Survey Data finds that 6 of the 8 states that got a C (the high grade) fall in the bottom half of states in the percentage of teachers who attended highly or most competitive colleges (a factor acknowledged by NCTQ as important, and as a factor that would supposedly improve as a function of expanding the teacher pool). Louisiana, Alabama and Arkansas are all in the bottom 10. Most of these states also fall in the bottom half of states, and 3 in the bottom 10 states for the change in percent of teachers (03-04 to 07-08) who attended highly or most competitive colleges. None of the states that received the high grade were even in the top 20 in change in % of teachers from highly or most competitive colleges.

You know – it’s possible that teacher salaries might also be a factor here (there’s some pretty good research on this-see link), and a limiting condition might actually be the available funding for schools which is sadly lacking in many of these states. So too might the supply of high quality public colleges and universities for preparing teachers. States like Louisiana have been taking the axe to their public higher education systems of late. Deregulatory strategies cannot trump these conditions, and in fact, may worsen teacher quality and ultimately school quality under these conditions.

Increased regulatory strategies like improved data for teacher evaluation systems (also advocated by NCTQ, and quite reasonably so) are simply window dressing for states that are choosing to avoid the more difficult and more expensive problems facing their public education systems.

On numerous occasions on this blog, I’ve discussed the systemic failures of the public education systems in states like Louisiana – their failure to serve even 80% of school-aged children – or their failure to provide reasonable overall funding or target any funding to higher need districts (across most of these states).

So, if the Teacher Quality Policy ratings have little to do with actual teacher academic preparation in a state, or overall quality of the state’s education system, then what do they tell us? Apparently not much!

New Jersey Teacher Salaries: Spiraling out of Control?

Not long ago, the transition teams for our new governor released their reports including an extensive report on K-12 education reform strategies. In the area of school finance, the report recommended:

(great synopsis at: http://njleftbehind.blogspot.com/2010/01/cheat-sheet-for-christies-educational.html)

Identify “immediate opportunities to eliminate waste and expenditures from practices…that are making no or only limited contribution to the quality of education for children.”

Review the efficacy of Corzine’s School Funding Reform Act where, famously, “the money follows the child.” Establish an “expert task force” to assess N.J.’s “overall funding system.”

Freeze salaries for all public employees, including pre K-12 teachers, for FY 2011.

Support and adopt A-15/S-1861, which eliminates public votes on school budgets that come in below cap.

Reduce costs in the “difficult area” of special education by limiting tuition increases at private out-of-district placements (currently 8-10% per year), shifting the burden of proof from local districts to parents when disputes arise regarding placements, and providing adequate state funding under IDEA to lift the financial burden off of local districts.

When school districts and local bargaining units reach an impasse, allow districts the ability to invoke a “last best offer,” a practice in effect until the McGreevey administration.

“Create regional salary guides to control escalating salary increases.”

Figure out how to fund recurring expenditures now underwritten by ARRA money. Closely track the 327 million dollars due Jersey of Phase II ARRA money in FY 2010 budgets.

I’ll probably have something to say on each of these topics at some point in time, but for now, what caught my eye was the emphasis throughout these recommendations on the notion that New Jersey teacher salaries are “escalating” out of control: http://www.northjersey.com/news/state/012210_Teacher_staff_salaries_may_be_frozen_Christie_says.html

There seems to be much finger pointing that the budget crunch faced by local public school districts in New Jersey is driven by our supposed tops-in-the-nation teacher salaries and inappropriate increases to teacher wages in tough economic times (where these increases have occurred as a function of an imbalanced mediation process).

Let’s take a reasoned, data-driven (since that’s what we’re supposed to do) look at the question of whether New Jersey teacher salaries have, in fact, escalated out of control, and if so, where – what school districts/locations – are New Jersey teacher salaries most out of line, or in line?

I offer the following comparison bases:

1) How do New Jersey teacher salaries compare presently and over time with salaries of comparably qualified teachers in other states sharing the same labor market? That is, how do Northern New Jersey salaries compare not with all of New York State, but with teachers in the New York metropolitan area within New York State? Similarly, how do teacher salaries compare in the Camden area with those in the Philadelphia metropolitan area?

Unfortunately most available reports only compare state averages, and it’s much harder to easily access comparable teacher data across states which share a labor market. One data set that makes this possible is the National Center for Education Statistics, Schools and Staffing Survey, which has been administered in 1987-88, 1990-91, 1993-94, 1999-00, 2003-04, 2007-08. This is a data set I use frequently, but one which requires a special license and involves disclosure approvals (so I can’t just go posting fun, detailed findings here. Darn!). I urge the current NJDOE to get a license for these data and explore the question of how NJ teacher salaries compare to those of comparable teachers in the same labor market. I’ve not looked yet at the Philadelphia labor market, but I have looked at NY, NJ, CT in the past and have generally found that NEW JERSEY TEACHER SALARIES AT COMPARABLE QUALIFICATIONS, LAG BEHIND NEW YORK SUBURBAN SALARIES, AND HAVE FALLEN FURTHER BEHIND OVER TIME. Recently, NJ salaries seem to have slipped behind Southern CT salaries. This is also true of administrator salaries. Ford Fessenden has written on this topic in the past:

http://www.nytimes.com/2007/06/10/nyregion/nyregionspecial2/10mainwe.html

As I noted to Ford Fessenden in this article, between 1998 and 2005 in particular, “The data suggest that New York is outbidding its neighbors for the best teachers and administrators.” (this was also based on analysis of statewide teacher database data, but my current NY data file only goes through 2003).

UPDATE: I finally got the chance to run some appropriate comparisons of NY and NJ teacher salaries which validate Ford Fessenden’s and my own previous findings. see: https://schoolfinance101.wordpress.com/2010/04/12/teacher-salaries-in-nj-and-ny-counties/

2) How do New Jersey teacher salaries compare with salaries of non-teachers a) in the same labor market, b) at the same age, c) at the same degree level and d) for the same amount of hours worked per day and days worked per year?

I’ve blogged on this topic in the past, pointing out that in New Jersey, based on U.S. Census and American Community Survey data on income from wages, teachers in New Jersey actually used to be – at one time – compensated quite similarly to their non-teacher peers on an hourly basis. That is, back around 1990. But, over time, New Jersey teacher salaries have slid further behind their non-teacher peers (though they have somewhat stronger average benefits packages. See my previous posts on teacher wages).

Here are my latest graphs on the topic – first, hourly wages over time by degree level and second, a modeled projection of teacher and non-teacher wages controlling for age, degree level, labormarket, hours worked and weeks worked. The first graph clearly shows that teacher salaries have slid from near 100% (near even) with non-teacher salaries back in 1990 for those with a BA only, to around 80% of the hourly wage of non-teachers with a BA. At other degree levels, teachers have fallen below 80%.

The second graph shows the projected annual wage for a 40 year old working 40 hours per week and 40 weeks per year, at the BA and MA level. This graph actually shows non-teachers with a BA surpassing teachers with an MA at the end of the period.

Note regarding benefits & bias: Corcoran and Mishel point out here: http://epi.3cdn.net/05447667bb274f359e_zam6br3st.pdf that

…overall K-12 teacher compensation was 27.5% greater than teacher wages alone, while overall professional compensation was 23.5% greater than professional wages. These differences in benefit shares translate into a benefits “bias”of 2.8 percentage points in 2006.

That is, benefits would close little of the overall gap in wages. Costrell and Podgursky show about a 5% (slightly less) differential (10% non-teachers, 15% teachers) in the value of pensions, a portion of benefits. This too would close only part of the teacher to non-teacher wage gap in New Jersey, even if we assume New Jersey benefits for teachers to be much greater than other employee benefits.

3) Where are those teacher salaries getting most out of line and what are the implications for property taxes? Is it really because the state has dumped so much funding into those Abbott districts? Or might it be because districts with high income families have chosen to adopt school district budgets which support higher salaries (essentially, canceling out the intended teacher recruitment edge produced by Abbott funding, if there ever was such a competitive edge)?

Because I love maps (see charter post), here are some maps of the school level relative competitiveness of teacher salaries – blue circles, overlaid on the median family income of school districts. The blue circles indicate the “relative competitiveness” of teacher salaries in a given school with a larger circle indicating that the actual salaries in that school are greater than the average predicted salaries for teachers with the degree and experience level of teachers in those schools. Schools are compared against others in their own labor market. So, a school identified as a large blue circle, or 1.05 value is a school where teacher salaries are 5% above the average expected salaries for those teachers in that labor market. Note that very low income, high minority urban schools would generally require higher salaries simply in order to recruit and retain comparable teachers. These maps, and competitiveness ratios include only New Jersey districts compared against other New Jersey districts. They do not include, for example, New York state districts which have much higher salaries for comparable teachers.

The first map shows the Newark area, and indeed Newark public schools do have relatively strong salaries, running at about 5% above expected. However, this margin is unlikely to yield teacher equity between Newark and its surroundings. Note that the many of the largest circles and highest competitiveness ratios – 1.12 to 1.14 – are in far more affluent suburbs like Millburn and Livingston. These self-inflicted higher salaries in districts that already provide more favorable working conditions create a competitive disadvantage for all other neighboring districts. The second map below shows the Camden area, where Camden teacher salaries are relatively non-competitive (as the district has increased quantities of staff rather than salaries over time) and where surrounding higher income suburbs have outpaced Camden city and other middle class suburbs.

This does all raise some fun questions regarding the property tax debate. One might argue that these high spenders are doing so on property taxes – high property taxes in fact. Actually, my previous analyses show that these wealthy communities with high teacher salaries actually have lower property taxes as a percent of income. If there is a squeeze going on here, that squeeze is at the juncture of the relatively lower teacher salaries and relatively higher local property tax burden (as a share of income) in middle to lower middle wealth communities who are trying to keep up with their affluent neighbors, but are less reliant on state aid than poor urban districts.

So, to conclude this rant – I’m having some trouble accepting the basic assumption that New Jersey teacher salaries are spiraling out of control, on either of the first two bases I discuss above. And further, I’m having some trouble accepting the notion that the spiraling salaries are a function of a statewide teachers’ union and strongly imbalanced mediation process. Rather, it would appear to me that very high income districts are simply choosing to spend what they can, and that it may be reasonable for these very districts to cut back, if their communities wish to do so. Actually, from a state policy perspective and especially from an equity perspective, if the current administration wishes to maintain the critical leverage provided by poverty-based funding to poor urban districts, the administration might wish to take a look at holding back the salary growth in the most affluent neighbors of the poorest urban districts. But, the notion that interventions are required to hold back all teacher salaries (with emphasis on those runaway urban districts) seems misguided.

for a discussion of technical problem’s with Jay Greene’s teacher salary analysis which is often used to argue that teachers are very well paid on an hourly basis. This is not directly relevant herein, because the analysis above deals with NJ teachers specifically, and uses more appropriate data for such analysis (the same data used by the National Center for Education Statistics for estimation of regional wage variation and for estimating teacher wages relative to other professional wages here: https://bush.tamu.edu/research/workingpapers/ltaylor/Comparing_Teacher_Salaries.pdf )

More Fun with New Jersey Charter Schools

LINK TO UPDATED SPREADSHEET OF FREE LUNCH AND SPECIAL ED DATA

I love maps. I love GIS software. This is a particularly interesting one related to the shares of children who qualify for free (not free or reduced, but free only, a poorer population) lunch in traditional public schools and in charter schools in Newark. One reason why mapping is useful here is that it is important to compare school demographics with other nearby schools, rather than district average. This map of a portion of Newark pretty much speaks for itself. Click to enlarge the map (to read the free lunch ranges on the key). Clearly, two of the “high performers” among charters – North Star and Robert Treat, have noticeably lower free lunch rates than other schools around them (except for other special schools).(CS indicates Charter School)

Data for this map were acquired from the National Center for Education Statistics Common Core of Data – Public School Universe Survey for 2007-08. These data include latitude and longitude for schools, which may not be perfectly precise. But, they are pretty good overall.

While I’m at it – here are the Jersey City Charters – even more striking differences:

Stepping back a bit to see more charters and taking off the names for clarity, here’s what all of Newark looks like, including some other neighboring towns. Charters have a pink asterisk. Again, smaller circles in lighter shades are lower free lunch schools. There are a few charters that are moderate to higher poverty – similar to many Newark schools (bright green, medium size bubble). However, many charters are the lowest poverty schools to be found. The same is true in the second map below for Jersey City.

Recall from previous posts that Charters are even more different from their neighbors in terms of the numbers of special education and limited English proficient students they serve. Their one saving grace was that they did seem to have relatively high shares of students qualifying for free or reduced price lunch. But, as I have noted in previous posts, they seem, on average to be taking in the less poor among the poor – at least the “model charters” do. That’s simply not scalable reform. Claims by NJ Charter advocates that these schools are serving the same, high poverty, needy student populations as other schools in their neighborhood are simply wrong – and not supported by any legitimate, fine-grained analysis (and it doesn’t even have to be that fine grained).

Note: One error in other analyses that compare charter school free or reduced lunch rates to district average rates is that those analyses fail to compare by grade level. Few charters in New Jersey are High Schools. High schools on average have lower rates of children qualifying for free/reduced lunch for a variety of reasons – primarily reporting issues. So, if you compare a bunch of elementary schools to a district average which includes high schools, you are likely to show that the elementary schools have higher average free/reduced lunch rate. But it’s not a correct comparison. Charter schools should be compared by grade level to their nearest neighboring and/or sending schools. I’ve not yet run the relevant spatial statistics above.

So, here are a few basic guidelines for future comparisons:

1) compare by relevant grade level because of the way in which subsidized lunch rates shift from elementary to secondary school;

2) while it’s okay to evaluate free and reduced shares, it is also important to slice those shares because children in these categories differ by family background. Looking only at the sum of free and reduced conceals substantial differences in student populations across charters and traditional public schools;

3) compare by location.

========

Here’s some follow-up data on New Jersey Charter School demographics. Here are the comparisons of disability rates and free lunch shares for Newark and Jersey City Public (Traditional Public) schools by grade level and the disability rates and free lunch shares for Charter schools often cited as outperforming the host district. Note that most claims that these schools outperform the host district use all kids’ test scores, not just general student test scores. So, differences in shares of children with disabilities make a huge difference in proficiency rates. I show this in previous posts on this thread (New Jersey Charter Schools).

Special Education

Note: A knowledgeable reader has informed me that the “0” value for Greater Newark Charter is actually “missing data,” for that year and has assured me that Greater Newark Charter does indeed enroll children with disabilities. At some point, I may get around to updating these analyses.

% Free Lunch

Note that the highest flyin’ charters (Treat and North Star) have substantially lower free lunch shares than the host district in addition to having very low special education rates. Only Marion P. Thomas has a relative high free lunch share, but has very few special education students.

Racial Achievement Gaps and Within-District Funding Inequity

I’ve written on this blog on a number of occasions, comments regarding the relative significance of within versus between district funding inequities. For example, I’ve explained (in response to an absurd claim by pundits from Education Trust) that southern states have not, in fact, substantively resolved between district funding disparities – leaving only district allocation policies to blame for persistent inequities.

A Center for American Progress report claims:

One of the most harmful manifestations of this is that local school district funding is allocated in a way that hurts poor and minority students. A study by the Thomas B. Fordham Institute found that educational funding is being allocated on the basis of “staff allocations, program-specific formulae, squeaky-wheel politics, property wealth, and any number of other factors that have little to do with the needs of students.”1

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

http://www.americanprogress.org/issues/2008/06/pdf/comparability.pdf

Notably, some of the above concerns raised in the Fordham report are between, not within-district concerns (property wealth related disparities), but the CAP report focuses on within district disparities as the central issue.

I have a forthcoming article (which I will forward by request) which explains that the existing literature which claims that within-district disparities far outweigh between-district disparities is problematic at best, drawing premature if not entirely unfounded and overextended conclusions. This is not to deny the problem of within district disparities but rather to point out that between district disparities persist and must be addressed either simultaneously with or as a precursor to resolving within district disparities.

Many pundits who wish to shift focus entirely onto within district disparities, blaming districts instead of state funding policies, seem to base their arguments on the idea that within-district funding disparities are the reason for persistent racial achievement gaps. Their story goes… that over the decades through the 1990s, states fixed between district funding disparities and achievement gaps improved. Since that time however, improvement to achievement gaps has stagnated if not backslid (true), with pundits arguing that the persistent within district disparities are the cause (unlikely). That is, that individual school districts are now funding their non-poor, white schools well and depriving their poor minority schools. That districts are allowing their better teachers to transfer from the high poverty, black schools to their low poverty white schools. There are certainly cases where this is true (Cincinnati accomplishes this through its weighted student funding formula by weighting gifted children more than poor children).

As a broader policy concern, the above argument might make sense if, in fact, student populations across schools within districts varied widely but that student populations vary less between districts. That is, it might make sense to argue that between-school within-district funding disparities are causing racial achievement gaps if racial minorities and whites attended the same districts but not the same schools. But that’s not always, or often the case, especially in densely populated states and metropolitan areas which included many small school districts.

Allow me to use Connecticut – a state with among the largest racial achievement gaps – as an example. Here’s the racial composition (black enrollment share in red bars, Hispanic share in yellow bars) for Hartford area school districts (click to enlarge). Those flat bars in other districts are schools with few or no black or Hispanic children.

In Connecticut, like New Jersey or like the Chicago metro area, school districts tend to be either minority or white – not a balanced mix sorted across schools. Hartford, in this case, can only re-allocate resources across schools that are all approximately 99% poor, and either majority black (north end) or majority Hispanic (south end) schools (except for the magnet schools which serve relatively smaller portions of the district population).

New Britain, to the southwest of Hartford can allocate resources across predominantly Hispanic schools or other predominantly Hispanic schools.

Meanwhile, West Hartford, Simsbury, Avon, Newington, Wethersfield and others can allocate resources across white schools and other white schools (some in West Hartford having modest minority populations)

Here’s the New Haven area:

And the Bridgeport area:

So, at least in Connecticut, it would appear highly unlikely that within- district resource allocation across schools could be fueling their large achievement gaps. That’s because – for the most part – the minorities attend some districts and the whites attend other districts. That’s not to say there aren’t likely some pretty big within district funding disparities in these districts, but in some districts those disparities exist between blacks and Hispanics, or Hispanics and other Hispanics, blacks and other blacks and in the other districts the disparities are between whites and other whites. For the most part, minority students attend minority districts and white students attend white districts in Connecticut. Patterns are similar in the Chicago metro area and in New Jersey.

Yes there are exceptions – racially integrated middle class inner-urban-fringe and suburban districts. But these exceptions do not account for the majority of minority or white students by any stretch of the imagination. And yes, in these exception districts, there are often very large achievement gaps even within schools. That is a separate and equally important (though smaller in magnitude) story.

It is an absurd stretch, however, to blame between-school within-district allocation policies for large achievement gaps in states like Connecticut, where minority students and white students attend different districts, much more so than different schools within the same districts.

See my previous post on between-district disparities in Connecticut here:

https://schoolfinance101.wordpress.com/2009/08/19/random-thoughts-on-ct/

Here are the scatterplots of the school level free/reduced lunch rates and black and Hispanic concentrations for the above urban CT districts – elementary schools. Dots in red are schools within the district in question. Blue dots are schools in all other districts, including the other urban districts. Note that in Hartford and Bridgeport in particular, all elementary schools are high poverty and high minority concentration. New Haven is more diverse, but still less diverse than the statewide (between district) distribution.

CT School Demographics-Elementary

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