Parametric Decomposition of a Generalized Malmquist Productivity Index

By Luis Orea. 2002

324 citations recorded by the source corpus.

This paper provides a parametric decomposition of a generalized Malmquist productivity index which takes into account scale economies. Unlike Balk (2001), the contribution of scale economies to productivity change is evaluated without recourse to scale efficiency measures, which are neither bounded for globally increasing, decreasing, or constant returns to scale technologies nor for ray-homogeneous technologies. An empirical application using panel data from Spanish savings banks is included. This application shows the advantages of the suggested method compared to Balk's approach. The results show an increase of total factor productivity which can be mainly attributed to technical progress and the positive effect of returns to scale.

Subfields: Economics and Econometrics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/8c1cb7e6e1a6aa1849dfd3b98e831bfdec11b734

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Citations in the corpus

Integrating spatial dependence into stochastic frontier analysis (2012, methodology): “…AJARE 2012 Australian Agricultural and Resource Economics Society Inc. and Blackwell Publishing Asia Pty Ltd estimable regression model by normalising the function by one of the outputs (Lovell et al. 1994; Coelli and Perelman 1999; Brümmer et al. 2002, 2006; Orea 2002; O¢Donnell and Coelli 2005).”
A cross-country comparison of productivity growth using the generalised metafrontier Malmquist productivity index: with application to banking industries in Taiwan and China (2011, background): “attributed to the fact that TFP can be measured using dis tance functions without the requirement for information on prices or cost shares of factors (Orea 2002; Coelli et al. 2005).”
Efficiency, technical change, and returns to scale in large US banks: Panel data evidence from an output distance function satisfying theoretical regularity (2010, background): “However, none of the previous studies in the banking productivity literature have checked or imposed those theoretical regularity conditions when violated see, for example, Orea (2002), Lovell (2003) and Cha¤ai et al. (2001).”
Reforms and infrastructure efficiency in Spain's container ports (2005, methodology): “We applied the methodology developed by Battese and Coelli (1988) for panel data and apply an additive term as suggested by Cuesta and Orea (2002), to account for the fact that we are estimating an output oriented distance function.”
A Bayesian Approach to Imposing Curvature on Distance Functions (2005, methodology): “They have also been used to measure and decompose productivity growth through time – see the analysis of Spanish insurance companies by Fuentes, Grifell-Tatje and Perelman (2001), the analysis of Spanish savings banks by Orea (2002) , and the study by Brummer, Glauben and Thijssen (2002) which meas”
Multinationals Productivity Advantage: Scale or Technology? (2007, background): “See, Färe et al. (1994) and Grifell and Lovell (1997) for examples of nonparametric; and Koop, Osiewalski, and Steel (1999), Balk (2001), and Orea (2002) for examples of fully parametric approaches.”
Determining the contribution of technical change, efficiency change and scale change to productivity growth in the privatized English and Welsh water and sewerage industry: 1985–2000 (2007, methodology): “nies (WaSCs) in England and Wales using a methodology proposed in Orea (2002) , and Coelli et al. (2003).”
A Primer on Efficiency Measurement for Utilities and Transport Regulators (2003, methodology): “Here we follow the general approach outlined in Orea (2002); however, we have adjusted the output distance function mefhod in Orea (2002) to suit the input distance function used here”
Farm size and productivity growth in the United States Corn Belt (2019, methodology): “If stochastic production function or data envelope analyses were performed, it would be possible to disaggregate TFP change for each size category into technical change, and technical and scale efficiency change (Färe et al., 1994; Orea, 2002).”
Tourism productivity and economic growth (2019, methodology): “Stochastic frontier analysis (SFA) is often used to estimate the parameters because unlike the deterministic methods, it can accommodate random errors when solving frontier production functions (Orea, 2002).”