The format of this monograph is three essays, which we arrived at after spending a year writing over one hundred pages of what we even tually realized was a tedious reworking of old material. So we started over determined to write something new. At first we thought this approach might not work as a coherent mono graph, which is why we chose the essay format rather than chapters. As it turns out, there is a common thread—namely the directional distance function, which also gave us our title. As you shall see, the directional distance function includes traditional distance functions and efficiency measures as special cases providing a unifying framework for existing productivity and efficiency measures. It is also flexible enough to open up new areas in productivity and efficiency analysis such as environmen tal and aggregation issues. That we did not see this earlier is humbling; a student at a recent conference raised his hand and asked 'Why didn't you start with the directional distance function in the first place? In deed. This manuscript is intended to make up for our earlier oversights. This monograph contains papers coauthored with Wen-Fu Lee and Osman Zaim and one paper written by two former students, Hiroyuki Fukuyama and Bill Weber. We thank them for their contributions. An other former student, Jim Logan (Logi) read and critiqued the manu script for which we are grateful.
Written by production economics and finance specialists Rolf Färe and Shawna Grosskopf of Oregon State University and Dimitris Margaritis of the University of Auckland, Pricing Non-marketed Goods Using Distance Functions, is an inspiring new contribution highlighting the importance of duality theory for valuation purposes, especially for hard to price inputs or resources, intended or unintended goods and assets. The theoretical pricing models are supplemented by self-standing empirical applications covering real estate pricing, environmental preservation, transfer pricing, shadow prices of university knowledge outputs and spillovers, and the pricing of bank equity capital and non-performing loans.
The basic notion underlying this monograph - budget or revenue constrained models of production - we owe to Ronald W. Shephard, who recognized its fundamental importance in modeling behavior in a wide variety of settings including the service and public sector. Our endeavor here is to extend Shephard's earlier work in several directions while maintaining his axiomatic approach. Our contributions include an expanded set of duality results and a general bent toward empirical implementation: including various parameterizations, applications to efficiency and productivity measurement, and shadow pricing. We hope to provide those engaged in empirical work with some powerful and useful tools which have received relatively little attention. The nature of the material in this monograph is somewhat technical, however, the level of mathematical difficulty is standard. Although we have tried to keep the monograph fairly self-contained, we have also kept technical detail to a minimum in the body of the text. Many technical extensions appear as problems at the ends of Chapters. The reader is also referred to the notes at the end of each chapter for references to additional literature. A prepublication draft of this manuscript was used as lecture notes in a graduate course in production theory at the Department of Economics at Bilkent University. We thank our students as well as faculty members for their patience and interest. Special thanks go to Dean Togan, Zeynap Koksal and Ali Dogramaci for making our stay in Ankara not only productive, but also enjoyable.
This book extends the efficiency literature to the case of intertemporal models. First, the authors introduce static network models which serve as building blocks for the intertemporal budgeting models and the dynamic models. Next, the authors devote two chapters to productivity measurements, which are considered as comparative static models. Intertemporal budgeting models and dynamic models are taken up subsequently. Each chapter, except the first, contains empirical applications.
This book presents a mathematical programming approach to the analysis of production frontiers and efficiency measurement. The authors construct a variety of production frontiers, and by measuring distances to them are able to develop a model of efficient producer behaviour and a taxonomy of possible types of departure from efficiency in various environments. Linear programming is used as an analytical and computational technique in order to accomplish this. The approach developed is then applied to modelling producer behaviour. By focusing on the empirical relevance of production frontiers and distances to them, and applying linear programming techniques to artificial data to illustrate the type of information they can generate, this book provides a unique study in applied production analysis. It will be of interest to scholars and students of economics and operations research, and analysts in business and government.
Data Envelopment Analysis (DEA) is often overlooked in empirical work such as diagnostic tests to determine whether the data conform with technology which, in turn, is important in identifying technical change, or finding which types of DEA models allow data transformations, including dealing with ordinal data.Advances in Data Envelopment Analysis focuses on both theoretical developments and their applications into the measurement of productive efficiency and productivity growth, such as its application to the modelling of time substitution, i.e. the problem of how to allocate resources over time, and estimating the 'value' of a Decision Making Unit (DMU).
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