An Extended-Directional Mix-Efficiency Measure: Performance Evaluation of OECD Countries Considering NetZero

Conventional data envelopment analysis (DEA) models make the assumption of controllable inputs and desirable outputs. However, in many real-world applications, there are two major issues facing the management of decision-making units. The first one is how to deal with uncontrollable inputs whose levels are determined by exogenous fixed factors. The second is how to deal with undesirable outputs that are accompanied by desirable outputs. The effect of the operating environment is frequently captured by uncontrollable inputs and undesirable outputs. The modulation of these two factors into a directional DEA model is still in its infancy in the DEA literature. This paper proposes new directional mix-efficiency measure and slacks-based measure models. These two efficiency models are proposed in the context of uncontrollable inputs and undesirable outputs. The new metric looks at how well the input and/or output mix should change to achieve a fully efficient status by decreasing controllable inputs and undesirable outputs and/or increasing desirable outputs while keeping uncontrollable inputs constant. The new mix-efficiency measure is based on the directional distance function and the slacks-based measure. The usefulness and applicability of the proposed models are assessed by measuring the eco-efficiency of the Organization for Economic Co-Operation and Development (OECD) countries. The aim of the application is to measure efficiency in the context of NetZero, with a specific focus on reducing CO2 emissions. The findings reveal that six countries—France, Luxembourg, Germany, Norway, Sweden, and the UK—have achieved eco-efficiency; therefore, these countries function in the constant returns-to-scale (CRS) regio

Data envelopment analysis: uncertainty, undesirable outputs and an application to world cement industry

Starting from the pioneering papers by Charnes, Cooper and Rhodes (CCR model) and Banker, Charnes and Cooper (BCC model), a large number of papers concerning Data Envelopment Analysis (DEA) with outputs uncertainty appeared in the literature. In particular, chance-constrained programming is the most used technique to include noise variations in data and to solve data envelopment analysis problems with uncertainty in data. Chance-constrained programming admits random data variations and permits constraint violations up to specified probability limits, allowing linear deterministic equivalent formulations in case a normal distribution of the data uncertainty is assumed. The standard DEA models rely on the assumption that inputs are minimized and outputs are maximized. However, both desirable and undesirable (e.g., pollutants or wastes) output factors may be present. The undesirable and desirable outputs should be treated differently when we evaluate the production performance: if inefficiency exists in the production, the undesirable pollutants should be reduced to improve efficiency. In order to include undesirable factors in DEA models, according to the literature, two different approaches can be used to model undesirable factors: one group of DEA models treats them as inputs, whereas a second group considers them as undesirable outputs. DEA models with undesirable factors are particularly suitable for models where several production inputs and desirable and undesirable outputs are taken into account, in order to provide an eco-efficiency measure. In this Ph.D thesis alternative DEA models, which consider both uncertain and undesirable outputs, are proposed and studied. In particular, in the first part of this thesis two different models with uncertain outputs and deterministic inputs are proposed with the aim to move away the classical chance-constrained method and to obtain a more accurate DMU ranking whatever situation occurs. Specifically speaking, the proposed models remove the hypothesis of normal data distribution and use a scenario generation approach to include data perturbations. For the sake of completeness, these models are compared with two further ones based on an expected value approach, where uncertainty is managed by means of the expected values of random factors both in the objective function and in the constraints. Deeply speaking, the main difference between the two proposed models and the expected value approaches lies in their mathematical formulation. In the new models, based on the scenario generation approach, the constraints concerning efficiency level are expressed for each scenario. On the other hand, in the expected value models the constraints are satisfied in expected value. As a consequence, the models proposed in the thesis result to be more selective in finding a ranking of efficiency, thus becoming useful strategic management tools aimed to determine a restrictive efficiency score ranking. In the second part of this study, we focus on environmental policy and eco-efficiency. Nowadays, one of the most intensively discussed concepts in the international political debate is, in fact, the concept of sustainability and the need for eco-efficient solutions that enable the production of goods and services with less energy and resources and with less waste and emissions (eco-efficiency). In particular, we consider the environmental impact of CO2 in cement and clinker production processes. Cement industry is, in fact, responsible for approximately 5% of the current worldwide CO2 emissions. DEA models can provide an appropriate methodological approach for developing eco-efficiency indicators. A cross-country comparison of the eco-efficiency level of the worldwide cement industry is presented by applying both a data envelopment analysis and a directional distance function approach. These tools result to be particularly suitable for models where several production inputs and desirable and undesirable outputs are taken into account. Strong and weak disposability assumptions are analyzed in order to evaluate the impact of environmental regulations interpreted as the cost of regulation. The few papers appeared in the literature of eco-efficiency in cement production analyze the emission performance trends only from an interstate point of view. In this thesis a worldwide study has been carried on, covering 90% of the world's cement production by means of 21 countries, European (EU) and non-European (non-EU) ones. The obtained results show that the efficiency level mainly depends on decisions to invest in alternative raw materials and alternative fuels, both in the case of regulated countries and in the case of voluntary emission-trading schemes. This study highlights, both at national and international levels, the possibility of reducing CO2 emissions and expanding cement production. The use of alternative raw materials, alternative fuels and the possibility of producing blended cements, which require less energy consumption and reduce pollutant emissions, seem to be appropriate means. Environmental regulations can provide incentives in terms of tax exemption benefits or more restrictive pollutant limits. Finally, we try to answer to the following questions: do undesirable factors modify the efficiency levels of cement industry? Is it reasonable to omit CO2 emissions in evaluating the performances of the cement sector in different countries? In order to answer to these questions, alternative formulations of standard data envelopment analysis model and directional distance function are compared both in presence and in absence of undesirable factors. This analysis shows that the presence of undesirable factors greatly affects efficiency levels. Efficiency levels are influenced by investments in best available technologies and by the utilization of alternative fuels and raw materials in cement and clinker production processes. The original results of this Ph.D. thesis have been collected in the following research papers: • Riccardi R. and R. Toninelli. Data Envelopment Analysis with outputs uncertainty. Journal of Information & Optimization Sciences, to appear. • Riccardi R., Oggioni G. and R. Toninelli. The cement industry: eco-efficiency country comparison using Data Envelopment Analysis. Journal of Statistics & Management Systems, accepted for publication. • Riccardi R., Oggioni G. and R. Toninelli. Eco-efficiency of the world cement industry: A Data Envelopment Analysis. Energy Policy, Vol. 39, Issue 5, p. 2842-2854, 2011, available online at: http://dx.doi.org/10.1016/j.enpol.2011.02.057 • Riccardi R., Oggioni G. and R. Toninelli. Evaluating the efficiency of the cement sector in presence of undesirable output: a world based Data Envelopment Analysis. Technical Report n. 344, Department of Statistics and Applied Mathematics, University of Pisa, 2011, submitted to Resource and Energy Economics. The research topic considered in this thesis shows many different lines for future developments. In particular, from a theoretical point of view, starting from the models proposed in Riccardi and Toninelli (2011), we are studying for a bi-objective like DEA formulation where both uncertainty desirable and undesirable factor are taken into account. As regards the applicative aspects, we are also studying and applying bootstrap techniques to manage uncertainty and generate empirical distributions of efficiency scores, in order to capture and analyze the sensitivity of samples with respect to changes in the estimated frontier

Incorporating Both Undesirable Outputs and Uncontrollable Variables into DEA: the Performance of Chinese Coal-Fired Power Plants

There are two difficulties in doing an objective evaluation of the performance of decision-making units (DMUs). The first one is how to treat undesirable outputs jointly produced with the desirable outputs, and the second one is how to treat uncontrollable variables, which often capture the impact of the operating environment. Given difficulties in both model construction and data availability, very few published papers simultaneously consider the above two problems. This article attempts to do so by proposing six DEA-based performance evaluation models based on a research sample of the Chinese coal-fired power plants. The finding of this paper not only contributes for the performance measurement methodology, but also has policy implications for the Chinese coal-fired power sector

Improving energy efficiency considering reduction of CO2 emission of turnip production:A novel data envelopment analysis model with undesirable output approach

Modern Turnip production methods need significant amount of direct and indirect energy. The optimum use of agricultural input resources results in the increase of efficiency and the decrease of the carbon footprint of turnip production. Data Envelopment Analysis (DEA) approach is a well-known technique utilized to evaluate the efficiency for peer units compared with the best practice frontier, widely used by researches to analyze the performance of agricultural sector. In this regard, a new non-radial DEA-based efficiency model is designed to investigate the efficiency of turnip farms. For this purpose, five inputs and two outputs are considered. The outputs consist turnip yield as a desirable output and greenhouse gas emission as an undesirable output. The new model projects each DMU on the strong efficient frontier. Several important properties are stated and proved which show the capabilities of our proposed model. The new models are applied in evaluating 30 turnip farms in Fars, Iran. This case study demonstrates the efficiency of our proposed models. The target inputs and outputs for these farms are also calculated and the benchmark farm for each DMU is determined. Finally, the reduction of CO2 emission for each turnip farm is evaluated. Compared with other factors like human labor, diesel fuel, seed and fertilizers, one of the most important findings is that machinery has the highest contribution to the total target energy saving. Besides, the average target emission of turnip production in the region is 7% less than the current emission

Environmental efficiency : meaning and measurement and application to Australian dairy farms

Technical efficiency has been widely studied in the literature, but in its pursuit, many of the inputs used can impact on the environment. Environmental effects can be modelled as undesirable output or, as has been the case in more recent studies, as conventional inputs. This paper examines the concept of environmental efficiency and how it can be used to evaluate the performance of Australian dairy farming, using nitrogen surplus, arising from excessive applications of fertilizer, as a detrimental input. Farming promotes the image of clean and green production and if this image is to be maintained, there is a need to ensure activities are environmentally friendly.<br /

Incorporating Undesirable Outputs into Malmquist TFP Index: Environmental Performance Growth of Chinese Coal-Fired Power Plants

In this article we examine the effects of undesirable outputs on the Malmquist TFP indices. Our empirical work uses an unbalanced panel which covers 796 utility and non-utility coal-fired power plants in China during 1996-2002. In order to meet the requirement of a balanced panel for calculating the Malmquist indices, an innovative fake unit approach has been introduced. Our final results show that (1) the growth of the Chinese electricity heavily depends upon an increase of resource input; and (2) huge potential remains with regards to the efficiency improvement and emissions control in Chinese coal-fired power plants

Monitoring bank performance in the presence of risk

This paper proposes a managerial control tool that integrates risk in efficiency measures. Building on existing efficiency specifications, our proposal reflects the real banking technology and accurately models the relationship between desirable and undesirable outputs. Specifically, the undesirable output is defined as nonperforming loans to capture credit risk, and is linked only to the relevant dimension of the output set. We empirically illustrate how our efficiency measure functions for managerial control purposes. The application considers a unique dataset of Costa Rican banks during 1998–2012. Results’ implications are mostly discussed at bank-level, and their interpretations are enhanced by using accounting ratios. We also show the usefulness of our tool for corporate governance by examining performance changes around executive turnover. Our findings confirm that appointing CEOs from outside the bank is associated with significantly higher performance ex post executive turnover, thus suggesting the potential benefits of new organisational practices.Peer ReviewedPostprint (author’s final draft

Reallocating Agricultural Greenhouse Gas Emission in EU15 Countries

This research work uses an alternative approach for modeling agricultural greenhouse gas emissions as an undesirable output, based on the zero sum gains DEA model (ZSG-DEA BCC model). This approach reallocates agricultural greenhouse gas emissions among EU15 countries. The reallocation analysis of greenhouse gas emissions permits countries that increase their emissions negotiate the emissions reduction with the others. This negotiation process might create a quota trade system for agricultural activity.DEA, Zero Sum Gains, Movement along the Efficient Frontier, Smoothed Frontier, Greenhouse Gas Emissions, Environmental Economics and Policy, Q54, Q56,

Does the Kyoto Protocol Agreement matters? An environmental efficiency analysis

This paper uses both conditional and unconditional Data Envelopment Analysis (DEA) models in order to determine different environmental efficiency levels for a sample of 110 countries in 2007. In order to capture the effect of countries compliance with the Kyoto Protocol Agreement (KPA), we condition the years since a country has signed the agreement until 2007. Particularly, various DEA models have been applied alongside with bootstrap techniques in order to determine the effect of Kyoto protocol agreement on countries’ environmental efficiencies. The study illustrates how the recent developments in efficiency analysis and statistical inference can be applied when evaluating environmental performance issues. The results indicate that the first six years after countries signed the Kyoto protocol agreement have a positive effect on their environmental efficiencies. However after that period it appears that countries avoid complying with the actions imposed by the agreement which in turn has an immediate negative effect on their environmental efficiencies.Environmental efficiency; Kyoto protocol agreement; Conditional full frontiers; Statistical inference; DEA