Nonparametric estimation of education productivity incorporating nondiscretionary inputs with an application to Dutch schools

In this paper we develop a Malmquist productivity index for public sector production characterized by the influence of environmental variables. We extend Johnson and Ruggiero (2011) to the more general case of variable returns to scale to further decompose the Malmquist productivity index into technical, efficiency, scale and environmental change. We apply our model to analyze productivity of Dutch schools using 2002–2007 data. The results indicate that the environment influences the productivity index as well as the technical, efficiency, scale and environmental change components. We see that schools with a moderate classification of environment have the highest productivity numbers. In line with expectations, schools with the worst environment also perform worse and would perform better with an improved environment.

[1]  J. N. Boles.  The 1130 Farrell efficiency system-multiple products, multiple factors. , 1971 .

[2]  A. Charnes,et al.  Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis , 1984 .

[3]  C. O'Donnell.  THE SOURCES OF PRODUCTIVITY CHANGE IN THE MANUFACTURING SECTORS OF THE U.S. ECONOMY , 2011 .

[4]  Mike Smet,et al.  Economies of scale and scope in Flemish secondary schools , 1998 .

[5]  J. Ruggiero.  Measuring the Cost of Meeting Minimum Educational Standards: An Application of Data Envelopment Analysis , 2007 .

[6]  John Ruggiero,et al.  On the measurement of technical efficiency in the public sector , 1996 .

[7]  C. Hoxby.  Productivity in Education: The Quintessential Upstream Industry , 2004 .

[8]  William F. McComas,et al.  Trends in International Mathematics and Science Study (TIMSS) , 2014 .

[9]  H. Gaziel,et al.  Impact of School Culture on Effectiveness of Secondary Schools With Disadvantaged Students , 1997 .

[10]  Peter J. Fensham,et al.  Programme for International Student Assessment (PISA) , 2014 .

[11]  Carlos Santos,et al.  Assessing school efficiency in Portugal using FDH and bootstrapping , 2005 .

[12]  Álvaro Choi,et al.  The efficiency of public and publicly subsidized high schools in Spain: Evidence from PISA-2006 , 2012, J. Oper. Res. Soc..

[13]  P. Ouellette,et al.  An evaluation of the efficiency of Québec's school boards using the Data Envelopment Analysis method , 2005 .

[14]  T. Kirjavainen,et al.  Efficiency differences of finnish senior secondary schools: An application of DEA and Tobit analysis , 1998 .

[15]  John Ruggiero,et al.  Non-discretionary inputs in data envelopment analysis , 1998, Eur. J. Oper. Res..

[16]  Robert Crouchley,et al.  Stochastic frontier estimation of a CES cost function: the case of higher education in Britain , 2002 .

[17]  L. R. Christensen,et al.  THE ECONOMIC THEORY OF INDEX NUMBERS AND THE MEASUREMENT OF INPUT, OUTPUT, AND PRODUCTIVITY , 1982 .

[18]  C. Haelermans.  On the productivity and efficiency of education : the role of innovations in Dutch secondary education , 2012 .

[19]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[20]  S. Grosskopf,et al.  The Relative Efficiency of Charter Schools , 2009 .

[21]  C. O'Donnell,et al.  Nonparametric Estimates of the Components of Productivity and Profitability Change in U.S. Agriculture , 2012 .

[22]  S. Ray,et al.  PRODUCTIVITY GROWTH, TECHNICAL PROGRESS AND EFFICIENCY CHANGE IN INDUSTRIALIZED COUNTRIES: COMMENT , 1997 .

[23]  John Ruggiero,et al.  Estimating technical and allocative efficiency in the public sector: A nonparametric analysis of Dutch schools , 2013, Eur. J. Oper. Res..

[24]  Jill Johnes,et al.  Efficiency in the further education sector in England , 2012 .

[25]  K. Chakraborty,et al.  Economies of Scale in Public Education: An Econometric Analysis , 2000 .

[26]  Carla Haelermans,et al.  The role of innovations in secondary school performance - Evidence from a conditional efficiency model , 2012, Eur. J. Oper. Res..

[27]  R. Färe,et al.  Nonparametric Cost Approach to Scale Efficiency , 1985 .

[28]  C. Haelermans,et al.  The role of innovations in secondary school efficiency : Evidence from a conditional efficiency model , 2012 .

[29]  António Afonso.  CROSS-COUNTRY EFFICIENCY OF SECONDARY EDUCATION PROVISION A SEMI-PARAMETRIC ANALYSIS WITH INPUTS , 2006 .

[30]  R. Färe,et al.  Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries , 1994 .

[31]  E. Hanushek.  Conceptual and Empirical Issues in the Estimation of Educational Production Functions , 1979 .

[32]  Nestor M. Arguea,et al.  An estimation of technical efficiency for Florida public elementary schools , 2008 .

[33]  John Ruggiero,et al.  Nonparametric estimation of returns to scale in the public sector with an application to the provision of educational services , 2000, J. Oper. Res. Soc..

[34]  W. Oates,et al.  THE RISING COST OF LOCAL PUBLIC SERVICES: SOME EVIDENCE AND REFLECTIONS , 1969, National Tax Journal.

[35]  Pierre Ouellette,et al.  Malmquist indexes with quasi-fixed inputs: an application to school districts in Québec , 2010, Ann. Oper. Res..

[36]  Gerhard Kempkes,et al.  Do Institutions Matter for University Cost Efficiency? Evidence from Germany , 2008 .

[37]  R. RajivD.BANKE.  Estimating most productive scale size using data envelopment analysis , 2003 .

[38]  M. Farrell,et al.  Estimating Efficient Production Functions Under Increasing Returns to Scale , 1962 .

[39]  Daniel L. Millimet,et al.  Efficiency in public schools: Does competition matter? , 2008 .

[40]  Jos L. T. Blank,et al.  Is a schools' performance related to technical change? - A study on the relationship between innovations and secondary school productivity , 2012, Comput. Educ..

[41]  Wendy Van de Kerckhove,et al.  Trends in International Mathematics and Science Study (TIMSS) 2003. Nonresponse Bias Analysis. Technical Report. NCES 2007-044. , 2006 .

[42]  H. Essid,et al.  Productivity, efficiency, and technical change of Tunisian schools: a bootstrapped Malmquist approach with quasi-fixed inputs , 2014 .

[43]  Rolf Färe,et al.  Measuring the technical efficiency of production , 1978 .

[44]  C. Haelermans,et al.  On the allocation of resources for secondary schools , 2012 .

[45]  Rajiv D. Banker,et al.  The Use of Categorical Variables in Data Envelopment Analysis , 1986 .

[46]  Suniya S. Luthar,et al.  Social-Emotional Factors Affecting Achievement Outcomes Among Disadvantaged Students: Closing the Achievement Gap , 2002, Educational psychologist.

[47]  Laurens Cherchye,et al.  Economies of scope in research and teaching: A non-parametric investigation , 2013 .

[48]  John Ruggiero,et al.  Efficiency of Educational Production: An Analysis of New York School Districts , 1996 .

[49]  John Ruggiero,et al.  Nonparametric measurement of productivity and efficiency in education , 2014, Ann. Oper. Res..

[50]  Rajiv D. Banker,et al.  Efficiency Analysis for Exogenously Fixed Inputs and Outputs , 1986, Oper. Res..

[51]  Othman Joumady,et al.  Performance in European higher education: A non‐parametric production frontier approach , 2005 .

[52]  Shawna Grosskopf,et al.  Budget-Constrained Frontier Measures of Fiscal Equality and Efficiency in Schooling , 1997, Review of Economics and Statistics.

[53]  H. Essid,et al.  Small is not that beautiful after all: measuring the scale efficiency of Tunisian high schools using a DEA-bootstrap method , 2013 .

[54]  Eric A. Hanushek,et al.  The Economics of Schooling: Production and Efficiency in Public Schools , 1986 .

[55]  Joanna Wolszczak-Derlacz,et al.  Dynamics of productivity in higher education: cross-european evidence based on bootstrapped Malmquist indices , 2013 .

[56]  M. Farrell.  The Measurement of Productive Efficiency , 1957 .

[57]  R. Färe,et al.  Productivity changes in Swedish pharamacies 1980–1989: A non-parametric Malmquist approach , 1992 .