In this chapter, we wish to explore models that differentiate between short-run transitory and long-run persistent inefficiency, possibly due to market pressures, or the lack thereof. With the introduction of the technical efficiency measurement techniques we have discussed in previous chapters, empirical studies of the sources of productive inefficiency using both DEA (Leibenstein and Maital, 1992), and SFA (Caves and Barton, 1992) were taken up relatively quickly by leading scholars in the field of economics and management as software platforms became publically available. In their exhaustive study of 285 US industries, Caves and Barton (1992) found that the degree of competition in the various industries had a measurable effect on the level of efficiency. During this time period in the early 1990s studies of the links between efficiency and market structure were also carried out by public utilities (Reifschneider and Stevenson, 1991), since the dependency between efficiency and competitive pressure has significant regulatory relevance. Button and Weyman-Jones (1992), in their summary of the X-efficiency literature, found similar results that point to a strong link between the level of regulatory oversight in an industry and the efficiency levels. Market structure is a driver of performance and this has long been recognized by economists (Hicks, 1935). Leibenstein (1966) pointed out that, given “proper motivations,” firm performance can be enhanced. The empirical studies that have followed to date continue to provide a strong consensus for the existence of such a link.

NONPARAMETRIC PANEL DATA MODELS OF PRODUCTIVITY DYNAMICS

The foundation for the theory of dynamic adjustment can be broadened by considering the axiomatic approach by Silva and Stefanou (2003), who laid out the set theoretic approach that was then extended in Silva and Stefanou (2007). Elaboration on the foundation for an adjustment cost framework by switching to the dynamic directional distance function approach allowed Silva et al. (2015) to deal with an even broader characterization of efficiency and productivity notions. Building on the Luenberger-based approach (using the dynamic directional distance function), Stefanou and his colleagues develop the relationship between the primal and dual forms of productivity (Lansink et al., 2015). Econometrically implementable frameworks for the dynamic adjustment model that address asymmetric dynamic adjustment appear in the review by Hamermesh and Pfann (1996).