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Racial Bias in Governor Wolf’s Proposed Funding of Public Schools

By April 27, 2015January 11th, 2016No Comments

Click here for a PDF version of the report.

by David Mosenkis, April 2015

On March 3, Governor Wolf announced his proposed budget for the next fiscal year. The governor’s budget includes an overall 7% increase in Basic Education Funding (BEF), the main line item for classroom spending for K-12 public education.  But the governor’s proposed breakdown of funding to school districts perpetuates an existing pattern of racial disparity in school funding.

A study published last October demonstrated systematic racial disparity in the distribution of Basic Education Funding to Pennsylvania’s 500 school districts.  Based on data available on the Department of Education’s web site, the study revealed dramatically higher per-student funding in districts with predominantly white populations compared to economically similar districts with more racial diversity.

Even though the incremental increases that Wolf’s budget proposes are distributed in a racially more neutral way, they do little to reduce the racial bias in overall BEF funding.

Figure 1 shows Governor Wolf’s proposed per-student funding in each district versus its poverty rate, with the dots shaded according to the percentage of white students.  There is a clear and expected trend that poorer districts generally receive higher state funding rates than richer ones, reflecting both the higher cost of educating poorer students, and the lower capacity to generate local school funding in poorer districts.  The diagonal black line represents the statistically expected funding of a district based solely on poverty. Districts above the line are receiving more than expected per-student for their level of poverty, and districts below the line are receiving less than expected. There are numerous other considerations besides poverty rates that influence funding levels, and these factors explain why any point in the graph lies above or below the line.

Yet the coloring of the dots in the graph reveals a distinct racial pattern.  The dots are colored continuous shades of gray according to the percentage of white students in each district.  We see that dots tend to be darker the further they are toward the lower right corner, reflecting the fact that the fewer white students a district has, the less funding the district tends to get compared to the norm for its poverty level.

Figure 1.  Per student BEF funding as a function of poverty (measured as the percentage of students eligible for free or reduced cost lunch).  Each district is colored according to its percentage of white students from 0% (black dots) to 100% (white dots).  The diagonal line is a best-fit linear regression line, R = 0.65, p < .0001.

Perpetuating Racial Bias

This trend in Wolf’s proposed funding is nearly indistinguishable from the trend observed in current funding for the 2014-2015 school year.  Figure 2 compares the two budgets.  To make the racial patterns easier to see and compare, Figure 2 colors the state’s 250 whitest districts yellow, and the 250 less white districts brown.

Figure 2.  Top graph:  2014-2015 funding.  Bottom graph:  Wolf proposed 2015-16 funding.  Per student BEF funding as a function of poverty.  Districts are colored yellow if their percentage of white students is above the state district median of 92%, and brown if their percentage of white students is below 92%.  The black, yellow, and brown lines are best-fit linear regression lines for all points, yellow points, and brown points respectively. 

 

As with current funding, Governor Wolf’s proposed funding provides significantly higher per-student funding for whiter districts at every level of district poverty.  Figure 3 shows the average of Wolf’s proposed funding levels for whiter and less white districts at each poverty decile (i.e. intervals of 10%).

Figure 3.  Average per-student BEF funding for districts with different poverty levels.  Yellow bars show the averages for each poverty decile for the 250 districts with >92% white students.  Brown bars show the averages for the 250 districts with <92% white students.  Poverty is defined here as the percentage of students eligible for free or reduced cost lunch.

The same trend is apparent when funding is compared based on district wealth (as measured by the MV/PI aid ratio) rather than student poverty, as illustrated in Figure 4:

Figure 4.  Average per-student BEF funding for districts with different wealth levels.  Yellow bars show the averages for each wealth decile for the 250 districts with >92% white students.  Brown bars show the averages for the 250 districts with <92% white students.  The faded bars represent deciles that had only a single district comprising the yellow bar.   Wealth is defined here by the MV/PI Aid Ratio, a state-computed value that represents the relative wealth (market value and income), in relation to the state average.  Lower values indicate wealthier districts.

How Can Existing Disparities be Changed?

The above analysis demonstrates that Governor Wolf’s proposed budget perpetuates the current systematic racial disparity in district funding.  The data do not suggest that Governor Wolf or his predecessors had any intention to bias funding levels based on race, but rather simply that a racial bias does in fact exist.  Since the Governor’s budget starts with current funding and then gives an incremental increase to each district, it is inevitable that an overall increase of 7% cannot dramatically change overall patterns.  So it is revealing to examine just the increases that the Wolf budget proposes for each district for patterns of racial disparity.

Figures 5 and 6 depict the proposed dollar increases as a function of poverty and race.  Like the overall funding levels depicted in the previous figures, the Wolf increases are progressive, in that they tend to be larger for poorer districts.  However, the pattern of racial distribution of the increases does not reveal a clear pattern.  Although whiter districts get somewhat greater increases at lower poverty levels, that trend reverses slightly at higher poverty levels, as reflected by the yellow best-fit line in Figure 5 crossing and falling below the brown line, and by the taller brown bar in the 60-70% poverty bracket in Figure 6.  This indicates that the Wolf budget distributes increased dollars to districts in a fairly racially neutral way.  If an equitable approach were applied to the entire BEF budget, rather than just the increases, it would eliminate the racial disparity in how Pennsylvania funds its districts.

Figure 5.  Per student increases in BEF in the Wolf budget as a function of poverty


Figure 6.  Average proposed per-student increases in BEF funding for districts with different poverty levels.  

The difference in the racial pattern observed when looking at Governor Wolf’s entire BEF budget versus just the increases demonstrates the inability of equitably allocated incremental increases to undo large disparities in a large budget.  Implementing a fair, unbiased funding system would require applying a fair distribution to the entire BEF budget, not just to incremental increases.