European Competitiveness: A Semi-Parametric Stochastic Metafrontier Analysis at the Firm Level

In this paper a semiparametric stochastic metafrontier approach is used to obtain insight into firm-level competitiveness in Europe. We divert from standard TFP studies at the firm level as we simultaneously allow for inefficiency, noise and do not impose a functional form on the input-output relation. Using AMADEUS firm-level data covering 10 manufacturing sectors from seven EU15 countries, (i) we document substantial, persistent divergences in competitiveness (with Belgium and Germany as benchmark countries and Spain lagging behind) and a wide technology gap, (ii) we confirm the absence of convergence in TFP between the seven selected countries, (iii) we confirm that the technology gap is more pronounced for smaller firms, (iv) we highlight the role of post-entry growth for competitiveness

Exact relationships between fisher indexes and theoretical indexes

We develop exact relationships between empirical Fisher indexes and their theoretical Malmquist and Konus counterparts. We begin by using implicit Malmquist price and price recovery indexes to establish exact relationships between empirical Fisher quantity and productivity indexes and theoretical Malmquist quantity and productivity indexes. We then show that Malmquist quantity and productivity indexes and Fisher price and price recovery indexes "almost" satisfy the product test with the relevant value change, and we derive a quantity mix function that ensures satisfaction of the product test. We next use implicit Konus quantity and productivity indexes to establish exact relationships between empirical Fisher price and price recovery indexes and theoretical Konus price and price recovery indexes. We then show that Konus price and price recovery indexes and Fisher quantity and productivity indexes "almost" satisfy the product test with the relevant value change, we derive a price mix function that ensures satisfaction of the product test, and we show that this price mix function differs fundamentally from the quantity mix function relating Malmquist and Fisher indexes

Measuring Efficiency in Local Government: An Analysis of New South Wales Domestic Waste Management Function

Data envelopment analysis (DEA) is used to measure the technical and scale efficiency of the domestic waste management function in 103 New South Wales’ local governments. After allowance is made for nondiscretionary environmental factors which may affect the provision of these local public services, such as congestion and the inability to operate machinery in densely-populated urban areas, comparison of efficiency across geographic/demographic criteria is made. The results suggests that, on average, waste management inputs could be reduced to just over 65 percent of the current level based upon observable best-practice whilst productivity losses due to scale effects account for slightly over 15 percent of total inputs. The results also indicate that inefficiency in urban developed councils is largely the result of congestion and other collection difficulties encountered in densely-populated areas, whilst inefficiency in regional and rural councils stems from an inability to attain an optimal scale of operations

Econometric estimation of distance functions and associated measures of productivity and efficiency change

Multi-input multi-output production technologies can be represented using distance functions. Econometric estimation of these functions typically involves factoring out one of the outputs or inputs and estimating the resulting equation using maximum likelihood methods. A problem with this approach is that the outputs or inputs that are not factored out may be correlated with the composite error term. Fernandez et al. (J Econ 98:47-79, 2000) show how to solve this so-called 'endogeneity problem' using Bayesian methods. In this paper I use the approach to estimate an output distance function and an associated index of total factor productivity (TFP) change. The TFP index is a new index that satisfies most, if not all, economically-relevant axioms from index number theory. It can also be exhaustively decomposed into a measure of technical change and various measures of efficiency change. I illustrate the methodology using state-level data on U.S. agricultural input and output quantities (no prices are needed). Results are summarized in terms of the characteristics (e.g., means) of estimated probability density functions for measures of TFP change, technical change and efficiency change