Advances in Efficiency and Productivity II

We begin by providing contextual background of this book, the second in a series. We continue by proclaiming the importance of efficiency and productivity, for businesses, industries, and nations. We then summarize the chapters in the book, which consist of an equal number of advances in the analytical foundations of efficiency and productivity measurement and advances in empirical applications that illustrate the significance of efficiency and productivity.

Overall efficiency measures were introduced in the literature for evaluating the economic performance of firms when reference prices are available. These references are usually observed market prices. Recently, Aparicio and Zofío (Economic cross-efficiency: Theory and DEA methods. ERIM Report Series Research in Management, No. ERS-2019-001-LIS. Erasmus Research Institute of Management (ERIM). Erasmus University Rotterdam, The Netherlands. http://​hdl.​handle.​net/​1765/​115479, 2019) have shown that the result of applying cross-efficiency methods (Sexton, T. R., Silkman, R. H., & Hogan, A. J. (1986). Data envelopment analysis: Critique and extensions. In R. H. Silkman (Ed.), Measuring efficiency: An assessment of data envelopment analysis, new directions for program evaluation (Vol. 32, pp. 73–105). San Francisco/London: Jossey-Bass), yielding an aggregate multilateral index that compares the technical performance of firms using the shadow prices of competitors, can be precisely reinterpreted as a measure of economic efficiency. They termed the new approach “economic cross-efficiency.” However, these authors restrict their analysis to the basic definitions corresponding to the Farrell (Journal of the Royal Statistical Society, Series A, General 120, 253–281, 1957) and Nerlove (Estimation and identification of Cobb-Douglas production functions. Chicago: Rand McNally, 1965) approaches, i.e., based on the duality between the cost function and the input distance function and between the profit function and the directional distance function, respectively. Here we complete their proposal by introducing new economic cross-efficiency measures related to other popular approaches for measuring economic performance, specifically those based on the duality between the profitability (maximum revenue to cost) and the generalized (hyperbolic) distance function and between the profit function and either the weighted additive or the Hölder distance function. Additionally, we introduce panel data extensions related to the so-called cost-Malmquist index and the profit-Luenberger indicator. Finally, we illustrate the models resorting to data envelopment analysis techniques—from which shadow prices are obtained and considering a banking industry dataset previously used in the cross-efficiency literature.

In this chapter, we compare the existing non-parametric approaches that account for undesirable outputs in technology modelling. The approaches are grouped based on Lauwers’ (Ecological Economics 68:1605–1614, 2009) seminal three-group classification and extended to a fourth group of recent models grounded on the estimation of several sub-technologies depending on the type of the outputs. With this fourth group of models, we provide a new complete picture of pollution-technologies modelling in the non-parametric framework of data envelopment analysis (DEA). We undertake a numerical comparison of the most recent models – the approach based on materials balance principle and weak G-disposability and the multiple equation technologies, namely, the by-production model and its various extensions, as well as the unified framework of natural and managerial disposability. The results reveal that the weak G-disposability and the unified natural and managerial disposability perform poorly compared to the multiple equation models. In addition, simulation fails to explicitly discriminate between the various multiple equation models.

Average efficiency is popular in the empirical education literature for comparing the aggregate performance of regions or countries using the efficiency results of their disaggregated decision-making units (DMUs) microdata. The most common approach for calculating average efficiency is to use a set of inputs and outputs from a representative sample of DMUs, typically schools or high schools, in order to characterize the performance of the population in the analyzed education system. Regardless of the sampling method, the use of sample weights is standard in statistics and econometrics for approximating population parameters. However, weight information has been disregarded in the literature on production frontier estimation using nonparametric methodologies in education. The aim of this chapter is to propose a preliminary methodological strategy to incorporate sample weight information into the estimation of production frontiers using robust nonparametric models. Our Monte Carlo results suggest that current sample designs are not intended for estimating either population production frontiers or average technical efficiency. Consequently, the use of sample weights does not significantly improve the efficiency estimation of a population with respect to an unweighted sample. In order to enhance future efficiency and productivity estimations of a population using samples, we should define an independent sampling design procedure for the set of DMUs based on the population’s production frontier.

In this paper, we characterize local circularity for the Laspeyres, Paasche, and Fisher price indexes. In the first two cases, we begin by deriving a sufficient condition for achieving circularity that establishes that at least one of two proposed equalities must hold. We end up showing that the sufficient condition is also necessary. We continue with the Fisher price index that is the geometric mean of the two, and we find a sufficient circularity condition that is a direct consequence of the corresponding sufficient conditions for its two component indexes. However, we also show that, unlike its Laspeyres and Paasche components, this sufficient circularity condition for the Fisher price index is not necessary. We reach different conclusions when we extend our investigation to the circularity properties of the geometric Laspeyres, geometric Paasche, and Törnqvist price indexes, for which none of the proposed sufficient conditions is necessary. Throughout, we distinguish local circularity, which all six price indexes satisfy, from global circularity, which none of the price indexes satisfies.

In this paper, we present a comparison of robust efficiency scores for the scenario in which the specification of the inputs/outputs to be included in the data envelopment analysis (DEA) model is modeled with a probability distribution, through the traditional cross-efficiency evaluation procedure. We evaluate the ranking obtained from these scores and analyze the robustness of these rankings, in such a way that any changes respect the set of units selected for the analysis. The probabilistic approach allows us to obtain two different robust efficiency scores: the unconditional expected score and the expected score under the assumption of maximum entropy principle. The calculation of these efficiency scores involves the resolution of an exponential number of linear problems. We also present an algorithm to estimate the robust scores in an affordable computational time.

This chapter examines the relationship between corporate social responsibility (CSR) and firms’ productivity change. The application focuses on panel data of US firms from 2004 to 2015. The chapter uses a dynamic data envelopment analysis (DEA) model to measure productivity change and its technical, technical-inefficiency, and scale-inefficiency change components. A bootstrap regression model relates CSR and its dimensions of social, environmental, and governance CSR with dynamic performance measures. Results support a positive association between CSR and dynamic productivity change. The findings also provide evidence about the relevance of CSR dimensions, as well as the components of dynamic productivity change, adding interesting insights into the relationship between CSR and productivity change.

In recent decades, concerns have emerged regarding the fact that standard macroeconomic statistics (such as gross domestic product) do not provide a sufficiently detailed and accurate picture of societal progress and well-being and of people’s true quality of life. This has further translated into concerns regarding the design of related public policies and whether these actually have the intended impact in practice. One of the first steps in bridging the gap between well-being metrics and policy intervention is the development of improved well-being measures. The calculation of a regional Social Progress Index (SPI) has been on the policymakers’ agenda for quite some time, as it is used to assist in the proposal of strategies that would create the conditions for all individuals in a society to reach their full potential, enhancing and sustaining the quality of their lives, while reducing regional inequalities. In this manuscript, we show a novel way to calculate a regional SPI under a two-phase approach. In the first phase, we aggregate the item-level information into subfactor-level indices and the subfactor-level indices into a factor-level index using an objective general index (OGI); in the second phase, we use the factor-level indices to obtain the regional SPI through a pure data envelopment analysis (DEA) approach. We further apply the method developed to analyse a single period of social progress in Peru. The manuscript is a contribution to the practical measurement of social progress.

In this chapter, we provide evidence as to the effects of infrastructure provision on aggregate productivity using industry-level data for a set of developed and developing countries over the 1995–2010 period. A distinctive feature of our empirical strategy is that it allows the measurement of intra- and interindustry resource reallocations which are directly attributable to the infrastructure provision. To achieve this objective, we propose a two-level top-down decomposition of labor aggregate productivity that extends the decomposition introduced by Diewert (Journal of Productivity Analysis 43:367–387) using a time-continuous setting.

Although Data Envelopment Analysis models have been intensively used for measuring efficiency, the inclusion of undesirable outputs has extended their use to analyse relevant fields such as environmental efficiency. In this context, slacks-based measure (SBM) models offer a remarkable alternative, largely due to their ability to deal with undesirable outputs. Additionally, super-efficiency evaluation in DEA is a useful complementary analysis for ranking the performance of efficient DMUs and even mandatory for dynamic efficiency evaluation. An extension to this approach in the presence of undesirable outputs is here introduced and then applied in the context of the environmental efficiency in electricity and derived heat generation in the European Union, providing the necessary tool to detect influential countries.

The paper attempts to analyze whether shareholders value as intangible assets the management decisions of bank production plan, in terms of cost efficiency, and risk associated to bank portfolio composition, in terms of probability of default (PoD). To test the market response to both management decisions, we employ a regression equation for bank valuation, using the panel regression model estimation procedure with country and year fixed effects, for the listed banks of 15 European countries, during the period 1997–2016. The results show that shareholders value both the efficiency of the production plan and the default risk. In particular, shareholders positively value banks’ cost efficiency and negatively value those banks with high PoD. These findings have important policy implications and show that the market value performance allows for the provision of more insights than book value into potential drivers of banks’ system stability and potential mechanisms for regulators and supervisors to maintain and control bank stability.

Improving the efficiency and effectiveness of public services and at the same time reducing public deficit have become an important concern in the public sector. Undoubtedly, local governments could benefit from adhering to these objectives. They play an important role in providing public goods and services to citizens in many countries, since they are the closest political level to the population and their needs. Moreover, local authorities and public managers are increasingly under pressure to conform to the standards demanded by the general public in terms of both quantity and quality. Nevertheless, the resources to fulfill the demand for more and better local public services are scarce, especially after the cutbacks and debt constraints imposed by the economic and financial crisis. In this framework, the assessment of municipal efficiency has become a very important factor in providing additional guidance for policy makers worldwide.

This chapter evaluates the impact of the land consolidation (LC) processes that have taken place in Asturias during the period 2001–2017. These processes have received European funds as they help to improve the economic activity in rural areas. In particular, the LC processes involve very localized public investments in infrastructures that favour accessibility and development not only in the local but also in adjacent areas. To evaluate the effect of LC processes on milk and beef production, we treat the parishes in Asturias as production units and estimate a set of multi-output distance functions. Our results indicate that LC contributes to increase parishes’ livestock production, although those processes not always are accompanied by an increase in the number of farms. We also find that the (indirect) effect from LC processes implemented in neighbouring parishes is positive and even more relevant than the (direct) effect on the local LC processes.