Two nonparametric methods for measuring eco-productivity change

The efficiency analysis of any entity (say, a country or a firm) without taking economics of ecological issues into account often yields wrong conclusion concerning the real health of the entity. This is precisely because there is no trade off between economy and ecology and an economy’s performance is not sustainable without efficient ecological system. Therefore, there is a need to have a measure of performance that aims at achieving more goods and services not only with fewer resources but also with less waste and emissions. Eco-efficiency is such a concept to capture this ideal measure of performance whose measurement has been operationalized in non-parametric data envelopment analysis (DEA) setting by Korhonnen and Luptacik (2004).

The European Union (EU) recognizes eco-efficiency as a key to reaching the Lisbon competitiveness targets and highlights the need to strengthen eco-innovations and resources’ efficiency in order to make the EU the most competitive knowledge economy in the world (European Commission 2005). This paper therefore aims at measuring inter-temporal eco-performance behaviors that can provide the European countries the valuable important policy information concerning whether the productive performance is driven by reduction in waste and emissions or primary resources like labor and capital or both. The concept of inter-temporal eco-efficiency is more relevant in terms of analyzing management behavior of government officials concerning whether their policy action undertaken over an accounting period to improve the overall economic performance is effective or not.

There can be two alternative ways to measure inter-temporal eco-performance in a DEA setting. One is to modify the decomposition method of Malmquist productivity index by Fare et al. (1994) and then apply it to ‘absolute’ input and output data of a balanced panel, and the other one is to directly apply the CCR/BCC model to growth in input and output data over an accounting period, to compute inter-temporal (growth) performance. Each method has its own strength and weakness. The former is superior in terms of decomposing total factor productivity (TFP) into innovation and catch-up components, but reveals unstable estimates when the panel data suffers from the problem of heteroscedasticity. The latter scores over the former in revealing stable estimates in the presence of heteroscedasticity when the first difference data becomes stationary, but is unable to decompose TFP into innovation and catch-up components.

Our proposed methodology is illustrated using macroeconomic data of 15 members of the European Union to examine the impacts of environmental regulations on the productive performance of these countries. Our study is unique in two ways: it first deals with three different ways of measuring environment-based total factor productivity change (TFPCH) and growth efficiency (GE), and the concept of environment-based GE is argued in this paper to be a proxy for TFPCH for measuring inter-temporal performance behavior.

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