Metafrontier productivity indices: Questioning the common convexification strategy

Abstract While the construction of metafrontiers based on the union of underlying group frontiers normally yields a non-convex metaset, a large majority in the literature seems to assume that a convexification strategy leads to a reasonable convex approximation of this non-convex metafrontier. However, Kerstens, O’Donnell, and Van de Woestyne (2019) recently deliver new results on the union operator on technologies under a variety of assumptions and empirically illustrate that such a convexification strategy is doubtful. The purpose of this contribution is to verify to which extent such a convexification strategy is tenable when computing the Malmquist and Hicks–Moorsteen productivity indices with respect to a metafrontier. Furthermore, the differences between the Malmquist and Hicks–Moorsteen productivity indices are investigated at the metafrontier level. This existing methodology is empirically applied on a secondary data under a wide variety of assumptions: we explore balanced and unbalanced data as well as constant and variable returns to scale. Anticipating our key results, we provide statistical evidence on the potential bias arising from applying the convexification strategy for the metafrontier productivity indices.

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

[2]  Mohsen Afsharian,et al.  A non-convex meta-frontier Malmquist index for measuring productivity over time , 2018 .

[3]  Léopold Simar,et al.  Testing Hypotheses in Nonparametric Models of Production , 2016 .

[4]  Scott E. Atkinson,et al.  Economic Efficiency and Productivity Growth in the Post-Privatization Chilean Hydroelectric Industry , 2005 .

[5]  R. Färe,et al.  Productivity Developments in Swedish Hospitals: A Malmquist Output Index Approach , 1994 .

[6]  Qi Li,et al.  Nonparametric testing of closeness between two unknown distribution functions , 2009 .

[7]  Kristiaan Kerstens,et al.  Infeasibility and Directional Distance Functions with Application to the Determinateness of the Luenberger Productivity Indicator , 2009 .

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

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

[10]  Tsu-Tan Fu,et al.  Metafrontier cost Malmquist productivity index: an application to Taiwanese and Chinese commercial banks , 2015 .

[11]  Barnabé Walheer,et al.  Aggregation of metafrontier technology gap ratios: the case of European sectors in 1995-2015 , 2018, Eur. J. Oper. Res..

[12]  Kristiaan Kerstens,et al.  Comparing Malmquist and Hicks-Moorsteen productivity indices: Exploring the impact of unbalanced vs. balanced panel data , 2014, Eur. J. Oper. Res..

[13]  Qi Li,et al.  A nonparametric test for equality of distributions with mixed categorical and continuous data , 2009 .

[14]  Lawrence J. Lau,et al.  The meta-production function approach to technological change in world agriculture☆ , 1989 .

[15]  R. Färe,et al.  The Structure of Technical Efficiency , 1983 .

[16]  B. Balk,et al.  Various Approaches to the Aggregation of Economic Productivity Indices , 2016 .

[17]  Ning Zhang,et al.  A deterministic parametric metafrontier Luenberger indicator for measuring environmentally-sensitive productivity growth: A Korean fossil-fuel power case , 2015 .

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

[19]  Scott E. Atkinson,et al.  Feasible Estimation of Firm-Specific Allocative Inefficiency through Bayesian Numerical Methods , 2009 .

[20]  C. O'Donnell Productivity and Efficiency Analysis: An Economic Approach to Measuring and Explaining Managerial Performance , 2018 .

[21]  Kostas Tsekouras,et al.  Productive performance, technology heterogeneity and hierarchies: Who to compare with whom , 2017 .

[22]  María Molinos-Senante,et al.  Comparing the efficiency of wastewater treatment technologies through a DEA metafrontier model , 2011 .

[23]  Tsu-Tan Fu,et al.  An examination of the cost efficiency of banks in Taiwan and China using the metafrontier cost function , 2013 .

[24]  Kristiaan Kerstens,et al.  Metatechnology frontier and convexity: A restatement , 2019, Eur. J. Oper. Res..

[25]  Saeideh Fallah-Fini,et al.  Measuring and analysing productivity change in a metafrontier framework , 2017 .

[26]  Mohsen Afsharian,et al.  A linear programming approach to efficiency evaluation in nonconvex metatechnologies , 2018, Eur. J. Oper. Res..

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

[28]  Hans Bjurek The Malmquist Total Factor Productivity Index , 1996 .

[29]  Christopher J. O'Donnell,et al.  Using information about technologies, markets and firm behaviour to decompose a proper productivity index , 2016 .

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

[31]  Subhash C. Ray,et al.  Data Envelopment Analysis: Theory and Techniques for Economics and Operations Research , 2004 .

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

[33]  Tammo Francksen,et al.  Assessing the performance of German Bundesliga football players: a non-parametric metafrontier approach , 2011, Central Eur. J. Oper. Res..

[34]  Rolf Färe,et al.  On two definitions of productivity , 1996 .

[35]  S. Kumbhakar,et al.  Efficiency measurement using a latent class stochastic frontier model , 2004 .

[36]  Christopher J. O'Donnell,et al.  An aggregate quantity-price framework for measuring and Decomposing productivity and profitability change , 2008 .

[37]  R. G. D. Allen,et al.  The Economic Theory of Index Numbers , 1949 .

[38]  Mohsen Afsharian,et al.  The overall Malmquist index: a new approach for measuring productivity changes over time , 2015, Ann. Oper. Res..

[39]  Konstantinos Kounetas,et al.  Efficiency decompositions for heterogeneous technologies , 2009, Eur. J. Oper. Res..

[40]  Michael A. Trueblood Agricultural Production Function Estimates from Aggregate Intercountry Observations: A Selected Survey , 1991 .

[41]  R. Russell,et al.  Theoretical Productivity Indices , 2018, The Oxford Handbook of Productivity Analysis.

[42]  Marijn Verschelde,et al.  Semiparametric stochastic metafrontier efficiency of European manufacturing firms , 2016 .

[43]  G. Battese,et al.  Metafrontier frameworks for the study of firm-level efficiencies and technology ratios , 2008 .

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

[45]  George E. Battese,et al.  Technology Gap, Efficiency, and a Stochastic Metafrontier Function , 2002 .

[46]  József Fogarasi,et al.  Efficiency, productivity and technology comparison for farms in Central and Western Europe: The case of field crop and dairy farming in Hungary and France , 2012 .

[47]  Steven T. Hackman,et al.  Production Economics: Integrating the Microeconomic and Engineering Perspectives , 2007 .

[48]  W. Briec,et al.  The Hicks–Moorsteen Productivity Index Satisfies the Determinateness Axiom , 2011 .

[49]  Kevin J. Fox,et al.  Decomposing productivity indexes into explanatory factors , 2017, Eur. J. Oper. Res..

[50]  Wilbur John Coleman,et al.  The World Technology Frontier , 2000 .

[51]  B. Casu,et al.  Regulatory Reform and Productivity Change in Indian Banking , 2009, Review of Economics and Statistics.

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

[53]  Rolf Färe,et al.  Malmquist Productivity Indexes: A Survey of Theory and Practice , 1998 .

[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]  Claudio Thieme,et al.  A mutilevel decomposition of school performance using robust nonparametric frontier techniques ∗ , 2011 .

[56]  C.-H. Lin,et al.  Measuring non-convex metafrontier efficiency in international tourist hotels , 2013, J. Oper. Res. Soc..

[57]  F. Førsund,et al.  Malmquist Productivity Indexes: An Empirical Comparison , 1998 .

[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]  Léopold Simar,et al.  On Testing Equality of Distributions of Technical Efficiency Scores , 2006 .

[60]  Léopold Simar,et al.  Estimating and bootstrapping Malmquist indices , 1999, Eur. J. Oper. Res..

[61]  K. Kerstens,et al.  Comparing Luenberger and Luenberger-Hicks-Moorsteen productivity indicators: How well is total factor productivity approximated? , 2018 .

[62]  K. Dakpo,et al.  Productivity, technical efficiency and technological change in French agriculture during 2002-2015: a Färe-Primont index decomposition using group frontiers and meta-frontier , 2018, Applied Economics.

[63]  Valentin Zelenyuk,et al.  Aggregation of Malmquist productivity indexes allowing for reallocation of resources , 2014, Eur. J. Oper. Res..

[64]  Yanqin Fan,et al.  On goodness-of-fit tests for weakly dependent processes using kernel method , 1999 .

[65]  Sang-Go Lee,et al.  Comparison of efficiency levels using meta-frontier analysis of global fisheries for the period 1960–2010 , 2014, Fisheries Science.

[66]  D. Primont,et al.  Multi-Output Production and Duality: Theory and Applications , 1994 .

[67]  P. W. Wilson,et al.  INFERENCE IN DYNAMIC, NONPARAMETRIC MODELS OF PRODUCTION: CENTRAL LIMIT THEOREMS FOR MALMQUIST INDICES , 2020, Econometric Theory.