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Inadequate State Support of Oklahoma’s Common
Schools’ Funding FormulaKen Hancock, PhD
Northeastern State University
Problem
Oklahoma has become the national leader in decreasing funding to common education since 2008.
Impact: Decreased equity that adversely affects the poorer school districts.
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 20130
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ACTUALRatio of State to District Support
Ratio
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 20130
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ACTUALRatio of State to District Support
Compared to the Restricted Range
Ratio Actual RR
Research Question
Has the 2014 level of state support of the Oklahoma Funding Formula continued downhill?
Has the fiscal neutrality of the funding formula continued to drop?
Hypotheses
For all scenarios: There is no significant difference in the Pearson r
correlation coefficient of district wealth to state support in 2013 compared to 2014.
The Restricted Range increased in 2014. The number of districts breaking the formula
increased in 2014. The ratio of state funding to district funding
became smaller.
Methodology There were three scenarios that were viewed
ActualPearson r was calculated between district wealth and state
appropriations
A Restricted Range (RR) was calculated
Ratio of RR to total dollars was calculated
Ratio between local support and state support was calculated
Simulation 1All the above
Number of districts that broke the formula
Simulation 2All the above, excluding the districts that broke the formula.
Methodology for comparing correlations:
Pearson rFisher’s z’Standard ErrorZ scoreAccept or reject hypothesis based on a Z score of
2.56 or greater.
Results2013 r RR Ratio N RatioActual -0.827 $1597 340.79 516 $0.91Simulation 1 -0.879 $ 144.84 44.19 516 $1.12Simulation 2 -1.000 $ 20.01 6.43 455 $1.22
(61 districts broke the formula in whole or part.)
2014 r RR Ratio N Ratio
Actual -0.738 $ 517 155.78 517 $1.30
Simulation 1 -0.863 $ 283.21 85.31 517 $1.02
Simulation 2 -1.000 $ 20.70 6.63 440 $1.15(77 districts broke the formula in whole or part.)
Results: Comparing Correlations
Actual Simulation 1 Simulation 2
2013 2014 2013 2014 2013 2014r = -0.827 -0.738 -0.879 -0.863 -0.999904 -.999888
N = 516 517 516 517 455 440Fisher’s z’ = -1.179 -0.946 -1.371 -1.305 -4.971 -4.897Std Error = 0.0624 0.0624 0.0671
Z score = -3.725* -1.063 -1.102
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Restricted Range: ActualMiddle 80% of Districts
Broke Actual
r = 0.438
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 20140
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Restricted Range: ActualMiddle 80% of DistrictsWithout 2012 & 2013
Broke Actual
r = 0.737
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
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Restricted Range: Simulation 1Middle 80% of Districts
Broke Sim-1
r = 0.913
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 20140
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Restricted Range: Simulation 2Middle 80% of Districts
Broke Sim-2
r = 0.870
Conclusions
2014 overall was worse than 2013.Significant difference in correlations Increase in number of districts breaking the formula.Decrease in RR*Ratio of state funding increased.*
*Due to local revenue going down
Recommended