The overall Malmquist index: a new approach for measuring productivity changes over time

This paper deals with a special case of the non-homogeneity problem related to the determination of the global benchmark technology when measuring productivity changes over time. The authors propose a new way of constructing the global framework of the Malmquist index which applies the minimum extrapolation principle on the aggregation of the experienced contemporaneous technologies. The proposed index, called overall Malmquist index, preserves the role of each contemporaneous technology in the determination of the newly-proposed best practice technology, whereby an acceptable level of discrimination between non-homogeneous observations is provided. With respect to both computational and test properties, the proposed index possesses the circularity property, generates a single measure of productivity change and is immune to infeasibility under variable returns to scale. Furthermore, unlike in the global form, previously computed results by the overall Malmquist index are more stable and less sensitive to changes in the shape of the best practice technology when a new time period is incorporated. Similar to traditional indices, it can be decomposed into various components such as efficiency change, scale efficiency change, and best practice change. The suggested index will be illustrated by means of a real-world example from banking. In particular, it will be compared to the contemporaneous and global forms of the Malmquist index introduced into the literature by Färe et al. (J Product Anal 3:85–101, 1992) and Pastor and Lovell (Econ Lett 88:266–271, 2005) , respectively.

[1]  M. R. Alirezaee,et al.  Improving the discrimination of data envelopment analysis models in multiple time periods , 2010, Int. Trans. Oper. Res..

[2]  Emmanuel Thanassoulis,et al.  Malmquist-type indices in the presence of negative data: An application to bank branches , 2010 .

[3]  C. Lovell,et al.  A generalized Malmquist productivity index , 1999 .

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

[5]  Ali Emrouznejad,et al.  A Performance Assessment Method for Hospitals: The Case of Municipal Hospitals in Angola , 2008, Journal of Medical Systems.

[6]  R. Shepherd Theory of cost and production functions , 1970 .

[7]  Lan Xu,et al.  Theoretical and Empirical Studies of Productivity Growth in the Agricultural Economics –– Cases of China and the United States , 2012 .

[8]  Shawna Grosskopf,et al.  Some Remarks on Productivity and its Decompositions , 2003 .

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

[10]  Fotios Pasiouras,et al.  Assessing Bank Efficiency and Performance with Operational Research and Artificial Intelligence Techniques: A Survey , 2009, Eur. J. Oper. Res..

[11]  Rolf Färe,et al.  Productivity growth, technical progress, and efficiency , 1997 .

[12]  Yujiro Hayami,et al.  Sources of Agricultural Productivity Gap Among Selected Countries , 1969 .

[13]  Jun-Yen Lee,et al.  Measuring productivity in the biotechnology industry using the global Malmquist index , 2012 .

[14]  David C. Wheelock,et al.  PUBLISHED: Journal of Money, Credit and Banking, , 1996 .

[15]  Chiang Kao,et al.  Malmquist productivity index based on common-weights DEA: The case of Taiwan forests after reorganization , 2010 .

[16]  Jeong-Dong Lee,et al.  A metafrontier approach for measuring Malmquist productivity index , 2010 .

[17]  Yao Chen A non-radial Malmquist productivity index with an illustrative application to Chinese major industries , 2003 .

[18]  Mette Asmild,et al.  Combining DEA Window Analysis with the Malmquist Index Approach in a Study of the Canadian Banking Industry , 2004 .

[19]  Robert G. Dyson,et al.  Data envelopment analysis and Malmquist indices for measuring group performance , 2006 .

[20]  V. V. Podinovski,et al.  Selective convexity in DEA models , 2005, Eur. J. Oper. Res..

[21]  Harold O. Fried,et al.  The Measurement of Productive Efficiency and Productivity Growth , 2008 .

[22]  V. V. Podinovski,et al.  Production trade-offs and weight restrictions in data envelopment analysis , 2004, J. Oper. Res. Soc..

[23]  R. F. Aghdam,et al.  Dynamics of productivity change in the Australian electricity industry: Assessing the impacts of electricity reform , 2011 .

[24]  Emmanuel Thanassoulis,et al.  Productivity change in the water industry in England and Wales: application of the meta-Malmquist index , 2011, J. Oper. Res. Soc..

[25]  Finn R. Førsund,et al.  Malmquist Indices of Productivity Growth during the Deregulation of Norwegian Banking, 1980-89 , 1992 .

[26]  Henry Tulkens,et al.  Nonparametric Approaches to the Assessment of the Relative Efficiency of Bank Branches , 1996 .

[27]  Mieko Nishimizu Total factor productivity growth, technological progress and technical efficiency change : dimensions of productivity change in Yugoslavia, 1965-1978 , 1982 .

[28]  M. Farrell,et al.  THE MEASUREMENT OF PRODUCTIVITY EFFICIENCY , 1957 .

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

[30]  R. Färe,et al.  Profit, Directional Distance Functions, and Nerlovian Efficiency , 1998 .

[31]  Alice Shiu,et al.  Economic growth, telecommunications development and productivity growth of the telecommunications sector: Evidence around the world , 2010 .

[32]  Dong-hyun Oh,et al.  A global Malmquist-Luenberger productivity index , 2010 .

[33]  S. Malmquist Index numbers and indifference surfaces , 1953 .

[34]  J. T. Pastor,et al.  A Quasi-Malmquist Productivity Index , 1998 .

[35]  Rolf Färe,et al.  Productivity and Undesirable Outputs: A Directional Distance Function Approach , 1995 .

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

[37]  Emmanuel Thanassoulis,et al.  A circular Malmquist-type index for measuring productivity , 2008 .

[38]  Juan Aparicio,et al.  On the inconsistency of the Malmquist-Luenberger index , 2013, Eur. J. Oper. Res..

[39]  Mieko Nishimizu,et al.  TOTAL FACTOR PRODUCTIVITY GROWTH, TECHNOLOGICAL PROGRESS AND TECHNICAL EFFICIENCY CHANGE: DIMENSIONS OF PRODUCTIVITY CHANGE , 2016 .

[40]  P. W. Wilson,et al.  Productivity Growth in Industrialized Countries , 1998 .

[41]  Victoria Shestalova,et al.  Sequential Malmquist Indices of Productivity Growth: An Application to OECD Industrial Activities , 2003 .

[42]  Joseph C. Paradi,et al.  A survey on bank branch efficiency and performance research with data envelopment analysis , 2013 .

[43]  J. Pastor,et al.  A global Malmquist productivity index , 2005 .

[44]  Francisco Javier Ramos-Real,et al.  Firm size and productivity. Evidence from the electricity distribution industry in Brazil , 2011 .

[45]  E. Fernandes,et al.  Malmquist financial efficiency analysis for airlines , 2012 .

[46]  Rikard Althin,et al.  A new, transitive productivity index , 1996 .

[47]  Timo Kuosmanen,et al.  FDH Directional Distance Functions with an Application to European Commercial Banks , 2001 .

[48]  Vernon W. Ruttan,et al.  Agricultural productivity differences among countries. , 1970 .

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

[50]  S. Berg,et al.  Benchmarking Central American Water Utilities , 2009 .

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

[52]  C. Lovell,et al.  The Decomposition of Malmquist Productivity Indexes , 2003 .

[53]  J. Zofío,et al.  Graph efficiency and productivity measures: an application to US agriculture , 2001 .

[54]  Ku-Hsieh Chen,et al.  A cross-country comparison of productivity growth using the generalised metafrontier Malmquist productivity index: with application to banking industries in Taiwan and China , 2011 .

[55]  Walter P. Wodchis,et al.  Efficiency and technological change in health care services in Ontario , 2011 .

[56]  Abraham Charnes,et al.  A developmental study of data envelopment analysis in measuring the efficiency of maintenance units in the U.S. air forces , 1984, Ann. Oper. Res..

[57]  Emmanuel Thanassoulis,et al.  Negative data in DEA: a directional distance approach applied to bank branches , 2004, J. Oper. Res. Soc..

[58]  G. Battese,et al.  A Metafrontier Production Function for Estimation of Technical Efficiencies and Technology Gaps for Firms Operating Under Different Technologies , 2004 .

[59]  Rolf Färe,et al.  Hicks′ Neutrality and Trade Biased Growth: A Taxonomy , 1994 .

[60]  Per Joakim Agrell,et al.  A Dual Approach to Nonconvex Frontier Models , 2001 .

[61]  Paul W. Wilson,et al.  Effects of Deregulation on the Productivity of Korean Banks , 1998 .

[62]  José Luis Zofío,et al.  Malmquist productivity index decompositions: a unifying framework , 2007 .

[63]  Rikard Althin,et al.  Measurement of Productivity Changes: Two Malmquist Index Approaches , 2001 .

[64]  Simone Gitto,et al.  Bootstrapping the Malmquist indexes for Italian airports , 2012 .

[65]  Jesus T. Pastor,et al.  Circularity of the Malmquist productivity index , 2007 .

[66]  Mette Asmild,et al.  The biennial Malmquist productivity change index , 2011 .

[67]  B. Yawe,et al.  Total factor productivity growth in Uganda's telecommunications industry , 2011 .