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Efficiency and Equity in School Funding: A case Study for Kansas.

Article Excerpt
Abstract This study measures cost inefficiency of Kansas public school districts and applied both mathematical programming and stochastic frontier approach. The empirical study uses two-stage data envelopment analysis model and the cost inefficiency effects model proposed by Battese and Coelli (Empirical Economics 24:325-332, 1995) and applied to a panel data. The results found mean inefficiencies from these two models are very close. The results indicate that Kansas school districts, on average, exhibit cost inefficiency in their operations, however, there is a tendency for inefficiencies to decline over time. The study does not find any strong evidence for lower efficiency due to lower expenditure per-pupil. Instead, we found inconclusive evidences where lower efficiency for certain school districts could be assigned to unfavorable environmental cost conditions.

Keywords Cost inefficiency. Stochastic cost frontier. Function. Public education

JEL Code D2.I2.R0

Introduction

In recent years, several states have faced challenges to their K-12 school funding systems on the basis of equity and inadequacy. Kansas has a long history of litigation related to school funding. Since 1972, state courts have declared the state school funding system unconstitutional five times (Green 2005). Equity in school funding became one of the most important issues before the Kansas legislature since the summer of 2005 when Kansas Supreme Court declared in Montoy vs Kansas that the current system of school financing violated the Education Article [Article 6] of the Kansas Constitution. The current ruling is the outcome of a lawsuit filed in 1999 where the plaintiffs in the Dodge City and Salina school districts alleged that the state school finance system was flawed and that districts with the largest number of at-risk students were receiving inadequate funds to address the special needs of those students. In the summer of 2005, the Kansas Supreme Court ordered the Kansas legislature to provide and a total of $285 million by July 1, 2005 for public school financing.

The recent court ruling has necessitated a critical examination about how school districts are managing their resources for educational services. Except the studies by Chakraborty (2003, 2005), no study has made an effort to uncover the causes of low performance for some school districts in Kansas by applying sound economic theory and advanced tools of econometric analysis. Our interest in measuring cost efficiency is motivated by the question that has been raised recently in the public policy arena: "Are the school districts in Kansas minimizing cost while trying to achieve state mandated educational standards?" We addressed this issue by measuring cost efficiency for school districts using 5-year panel data applied to parametric and non-parametric methods. The major objectives of the current study are: (1) to identify the districts that are inefficiently managing their resources while delivering the state mandated educational outcome; and (2) to identify the factors which account for efficiency differential among school districts. We have also made an effort to identify the sources of low performance for plaintiffs' districts vis-a-vis all other districts in the sample.

To achieve our first objective, we defined and estimated an educational cost function and constructed a cost inefficiency index for all school districts in Kansas. In order to achieve our second objective, we conducted a regression analysis capturing the relationship between the inefficiency index and the environmental cost factors affecting inefficiency. We have applied an econometric model that captures the impact of environmental factors on school district inefficiency more rigorously than the models used in past public education literature. We consider this approach as novel and unique, and it will add to the existing body of knowledge.

In the next section, we have provided the background for this study including a brief survey of the studies done in the literature. Both educational cost function and the model are defined in the third section, which is followed by a section on the dataset. The fifth section discusses the results. The summary and conclusions are in the concluding section.

Background

Efficiency and equity in school finance has remained the major issue over the past 25 years. Most states are experiencing growth in per-pupil expenditure while student achievement score remains stagnant (Hanushek and Rivkin 2004). In June 2005 before the Supreme Court ruling, the state independently conducted two separate studies and investigated the relationship between school funding and student achievement for all Kansas school districts (Poggio 2001; Glasnapp and Poggio2003). Both of these studies used simple statistical analysis and concluded that expenditure per-pupil is not a "powerful" determining factor for student achievement. In general, research in public school finance mostly initiated in response to lawsuits or court rulings in the U.S. (McCarty and Yaisawarang 1993; Downes and Pouge 1994; Noulas and Ketkar 1998; Duncombe and Yinger 2000; and Ruggiero 2001).

A recent study by Duncombe and Yinger (2005) estimated the base cost per student for Kansas school districts and developed a cost index for inclusion into the school finance formula. Similar studies were found in the literature using data from other states (Ruggeiro 2001; Duncombe and Yinger 1998; Downs and Pouge 1994). Although revising the state funding formula based on base cost and/or cost index makes funding more transparent and equitable, it does not guarantee improved cost efficiency for districts. Researchers found that budgetary reforms to equalize expenditure could actually increase the inequality of student achievement (Grosskopf et al. 1997; Husted and Kenny 2000).

Most past studies estimated an educational production function using stochastic and/or non-stochastic methods and measured technical efficiency index (McCarty and Yaisawarang 1993; Grosskopf et al. 1997; Chakraborty 2001, 2003, 2005). Some studies that used two-stage data envelopment analysis (TSDEA) and stochastic frontier approach (SFA) to measure two sets of efficiency scores found the rank correlation between this two sets of efficiency scores is close to one (i.e., they are highly correlated) (Ruggerio and Vitaliano 1999; Chakraborty et al....