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About this book

The volume examines the state-of-the-art of productivity and efficiency analysis. It brings together a selection of the best papers from the 10th North American Productivity Workshop. By analyzing world-wide perspectives on challenges that local economies and institutions may face when changes in productivity are observed, readers can quickly assess the impact of productivity measurement, productivity growth, dynamics of productivity change, measures of labor productivity, measures of technical efficiency in different sectors, frontier analysis, measures of performance, industry instability and spillover effects.
The contributions in this volume focus on the theory and application of economics, econometrics, statistics, management science and operational research related to problems in the areas of productivity and efficiency measurement. Popular techniques and methodologies including stochastic frontier analysis and data envelopment analysis are represented. Chapters also cover broader issues related to measuring, understanding, incentivizing and improving the productivity and performance of firms, public services, and industries.

Table of Contents

Frontmatter

Editors’ Introduction

Abstract
The papers in this collection of works presented at the 2018 North American Productivity Workshop X hosted at the University of Miami, represent contributed, peer reviewed chapters across all areas of efficiency and productivity analysis. They offer new insights and perspectives into the modeling, identification, and estimation of productivity and its major components, efficiency and innovation. The collection is aptly titled Advances in Efficiency and Productivity Analysis. The contributions in this volume speak to firms or agencies that are privately or state-owned, capitalist or centrally planned economies, developed, developing, or transitional countries—anywhere where the goal is to measure productivity and identify and explain possible inefficiencies and thus help a productive enterprise/entity improve and move to higher levels of efficiency and productivity and a more efficient utilization of valuable and costly resources. Productivity growth, as we know, is the main vehicle through which growth in living standards and welfare is achieved. Constraints on this growth, whether by ineffective or misguided regulatory oversight, maldistribution of productivity growth, failure to properly account for hidden costs and benefits of productive decisions and allocations, or market failures to accurately price current resources in light of how their depletion impacts future generations, all contribute to a diminution in productivity growth and thus in living standards. The papers in this volume provide new research findings these issues.
Christopher F. Parmeter, Robin C. Sickles

The Difference Approach to Productivity Measurement and Exact Indicators

Abstract
There are many decompositions of productivity growth for a production unit that rely on the ratio approach to index number theory. In this paper, three analogous decompositions for productivity growth in a difference approach to index number theory are obtained. The first approach uses the production unit’s value added function in order to obtain a suitable decomposition. It relies on various first order approximations to this function but in the end, the decomposition can be given an axiomatic interpretation. The second approach uses the cost constrained value added function and assumes that the reference technology for the production unit can be approximated by the free disposal conical hull of past observations of inputs used and outputs produced by the unit. The final approach uses a particular flexible functional form for the producer’s value added function and provides an exact decomposition of normalized value added.
W. Erwin Diewert, Kevin J. Fox

Efficiency Driven Socio-Technical System Design

Abstract
In this paper we advocate that the efficiency measurement paradigm could transition from an evaluation-to-rank towards an evaluation-to-design paradigm. We suggest that this transition can inform the design of socio-technical systems. In order to achieve this type of design would require the consideration of issues associated with organizational design, enterprise systems engineering along with system complexity. We recommend that the required research be conducted within inter- or trans-disciplinary context with all of their benefits and challenges to achieve high quality application results. We describe five illustrations conducted over the years at Virginia Tech’s System Performance Laboratory. We present these illustrations by describing the societal or socio-technical system needs that drove the research, the research constraints and considerations, the stakeholders affected by the research, the approach or approaches used, the feedback to theory and open modeling issues, and a description of societal and socio-technical system impacts. We describe the potential of a complex adaptive systems approach as an enabler of socio-technical system design and conclude with a series of open-ended questions and issues.
Konstantinos Triantis

A Framework for the Assessment and Consolidation of Productivity Stylized Facts

Abstract
This chapter tackles the little-treated subject of how productivity and efficiency stylized facts are measured and consolidated. We show that measurement requires the formulation of a model starting from a general framework. We propose a doubly conditional performance evaluation model for the measurement of productivity stylized facts and an econometric approach for consolidating stylized facts. The proposed framework can complement recent methodological works guiding the users to describe and choose the most appropriate method for their context of analysis. Our performance measurement framework may act as a leading thread for bringing together different strands of literature that are outlined in the concluding section.
Cinzia Daraio

Water’s Contribution to Agricultural Productivity over Space

Abstract
After recent projections for food and agricultural production for the next three decades, water is at the centre of the discussion. Given the increase in population growth, food demand will increase and the agricultural sector will likely have to expand the use of irrigation water to meet this rising demand. However, water scarcity leads to significant water management issues in the agricultural sector. With agriculture playing an important role in the water crisis as it is by far the largest user of water, the emphasis is finding ways to allocate this scarce resource more efficiently and to produce increasing quantities of food with decreasing quantities of water. The improved effectiveness of water conveyance, the efficiency in its use, and the associated impact on non-water input and output choices have the potential to impact the economic well-being of the farming community and promote the sustainability of agricultural production. The objective of this paper is to contribute toward productivity-enhancing policies by estimating the magnitude of gains from the more effective use of water in agriculture. The effectiveness of these policies depends on the proper measurement of water’s contribution to agricultural efficiency and productivity. This paper develops a measure of water’s contribution to total factor productivity (TFP) change that accounts for spatial water quantity and quality adjustments. This spatial model is a first attempt to estimate the contribution of water use to agricultural productivity and to capture differences in farm-level productivity due to head versus tail disparities in water allocation and water quality. Water policy strategies should aim toward internalizing the spatial externalities and encouraging productivity-enhancing techniques allowing the farmers to produce more output with the same or even less water and to improve the quality of water used in the agricultural sector by deploying sustainable management practice and promoting community engagement.
Maria Vrachioli, Spiro E. Stefanou

A Survey of the Use of Copulas in Stochastic Frontier Models

Abstract
Copulas are used to create joint distributions with specified marginal distributions. The copula models the dependence between the corresponding marginal random variables. In the normal case, the multivariate normal distribution is a natural choice of joint distribution with normal marginals and its covariance matrix parameterizes the dependence between the individual marginal normals. But how would we specify a joint distribution for a normal and a half-normal, where these two random variables are allowed to be dependent? We can do this using copulas.
Christine Amsler, Peter Schmidt

Does Xistence of Inefficiency Matter to a Neoclassical Xorcist? Some Econometric Issues in Panel Stochastic Frontier Models

Abstract
Does the presence of inefficiency affect estimation of the production function? This paper shows that one cannot ignore inefficiency in estimating the production function simply because standard neoclassical production theory does not recognize its existence. Exclusion of inefficiency can cause inconsistency in the estimates of the technology parameters due to omitted variables which are determinants of inefficiency. We show how one can avoid this inconsistency in estimating the production technology irrespective of whether one is interested in estimating inefficiency or not. Our proposed estimation methods use two state-of-the-art stochastic frontier (SF) panel models. Since distributional assumptions are often a bone of contention even among the followers of the SF approach, we focus on estimation methods that do not rely on distributional assumptions for the inefficiency and noise components.
Subal C. Kumbhakar, David H. Bernstein

The Two-Tier Stochastic Frontier Framework (2TSF): Measuring Frontiers Wherever They May Exist

Abstract
Stochastic frontier analysis (SFA) focuses mostly on measuring and analyzing matters of efficiency in production and in cost decisions, based on the conceptual and modeling device of a frontier, a boundary beyond which a firm can find itself only by chance, literally. But the existence of frontiers in human activity is a consequence of physical and of economic scarcity: the fact that resources are always less than what we would desire to have available in order to fulfill whatever needs and wants we are able to imagine (or cannot ignore no matter how hard we try). Scarcity creates restrictions, constraints, bounds, boundaries... frontiers. Therefore “frontier modeling” is not constrained to be a specialized tool for efficiency and productivity analysis but can be used as a general methodological approach to formulate and then study economic phenomena (and not only).
Alecos Papadopoulos

Individual Efficient Frontiers in Performance Analysis

Abstract
We propose a new approach for performance comparisons with a goal similar to the DEA or efficiency analysis based on stochastic frontiers. Our approach accounts for varying environmental factors and human resources among the units under consideration by assuming individual production possibility sets (PPS). In a partial equilibrium framework we assume that the observed netputs represent an equilibrium. Thus, each DMU is efficient with respect to its individual PPS. The netputs and estimated prices common for all units reveal characteristics of the individual PPSs and assess the units’ relative performance. To obtain such prices from scarce data we assume that the observed netput vectors represent a random sample of netput vectors. We use prices which render the realizations of individual profits or returns of the DMUs most likely. We compare the DEA based efficiency rankings with our performance rankings. Strong rank correlation is observed between the two. The discriminatory power of our ranking is superior to conventional DEA methods.
Markku Kallio, Merja Halme

DEA Models Without Inputs or Outputs: A Tour de Force

Abstract
In this paper we review DEA models without outputs or inputs and models with a single constant input or output and we explore their properties and relations. Then we summarize their potential usefulness in several applications, including (a) multiple criteria decision-making (MCDM) such as supplier selection and ABC inventory classification, (b) construction of composite indicators (environmental, sustainability, subjective well being, etc.), (c) ratio analysis, and (d) spatial efficiency. We further consider the cases of optimistic versus pessimistic composite indicators and of intra- and inter-group composite indicators. We also explore the usefulness of these models in other topics of performance evaluation such as cross efficiency, efficiency based on common weights, and productivity analysis. Lastly, we consider their aggregation across DMUs rules.
Giannis Karagiannis

U.S. Banking in the Post-Crisis Era: New Results from New Methods

Abstract
This paper examines the performance of U.S. bank holding companies before, during, and after the 2007–2012 financial crisis. Fully nonparametric methods are used to estimate technical, cost, and input allocative efficiencies. Recently developed statistical results are used to test for changes in efficiencies as well as productivity over time, and to test for changes in technology over time. I find evidence of non-convexity of banks’ production set is found. In addition, the data reveal that mean technical efficiency declined during the financial crisis, but recovered in the years after, ending higher in 2016 than in 2006, while both cost and input allocative efficiencies declined from 2006 to 2016. Statistical tests indicate that technology shifted downward throughout the period 2006–2016.
Paul W. Wilson

Room to Move: Why Some Industries Drive the Trade-Specialization Nexus and Others Do Not

Abstract
We investigate which industries drive the trade-specialization nexus in the European Union over the 1997–2006 period. We study the impact of the reallocation of resources within industries. We find that the true drivers of the trade-specialization nexus are productive firms, who benefit from the increase in trade openness by appropriating resources from less productive firms, coinciding with the expansion of the industry in which they operate, at the expense of other industries, in which there is no room to make such moves.
Jaap W. B. Bos, Lu Zhang

Expansionary Investment Activities: Assessing Equipment and Buildings in Productivity

Abstract
We study firm-level expansionary investment activities in both equipment and buildings—the so-called investment spikes. Our identification strategy decomposes firm investment spikes into three streams: a spike in equipment only, buildings only, or a simultaneous spike. Empirically, we find that the timing and size of investment in equipment and buildings are not independent. Firms conducting a simultaneous spike enhance firm scale more than in the case of a spike in equipment or buildings alone. Employment growth occurs when a firm builds structures. Investment in equipment affects the optimal input mix and high productivity in equipment and buildings provides investment timing signals. In low-tech sectors firm production growth depends on investment in buildings. In contrast, a necessary condition for firms in high-tech sectors to grow their production is investment in equipment.
Jasper Brinkerink, Andrea Chegut, Wilko Letterie

Applying Statistical Methods to Compare Frontiers: Are Organic Dairy Farms Better Than the Conventional?

Abstract
The Malmquist index is widely used in empirical studies of productivity change over time. The index is based on estimates of the frontier obtained from the convex envelopment of the data as in DEA. The statistical properties of the Malmquist index and its components, i.e. the frontier shift and the efficiency change, have until recently only been subject to a limited number of studies. The asymptotic properties of the geometric mean of the individual Malmquist indexes have been studied in the literature. Permutation tests for performing statistical inference in finite samples have recently been proposed and are easily performed. In the present paper we illustrate the permutation methods by an analysis of data comprising organic and conventional dairy farms in Denmark from 2011–2015. Further, differences between the frontiers of the production possibility sets for two separate samples are studied, specifically those of the organic and the conventional producers. We suggest to use jackknife methods when estimating the differences to ensure that these are not affected by the well-known bias originating from estimation of the frontier. In summary, the paper offers an illustration of how to analyse productivity data, in particular a comparison of two independent groups, and furthermore an analysis of how the separate groups evolve over time is provided.
Mette Asmild, Dorte Kronborg, Anders Rsønn-Nielsen

Nutrient Use and Precision Agriculture in Corn Production in the USA

Abstract
This is a timely study of precision agriculture as both data management (mapping) and field production technologies for agricultural production are changing rapidly. We compare the performance of producers who adopt precision agriculture tools versus those that do not. We estimate both their own frontier performance and a metafrontier that enables the research to compare the efficiency of producers across technologies. To make these comparisons we pre-processed the data with a matching procedure in order to have a sample of producers of equal size for each category who faced similar conditions. In the metafrontier results we find that GPS yield maps, guidance auto-steering precision agriculture technologies, and managerial ability save input costs and increase farm production efficiency which has environmental benefits. Maps created from soils or aerial data and input applications using VRT did not produce useable results.
Roberto Mosheim, David Schimmelpfennig

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