W. Erwin Diewert

Bio: W. Erwin Diewert is an academic researcher from University of British Columbia. The author has contributed to research in topics: Productivity & Index (economics). The author has an hindex of 39, co-authored 161 publications receiving 8098 citations. Previous affiliations of W. Erwin Diewert include National Bureau of Economic Research & University of New South Wales.

Multilateral Comparisons of Output, Input, and Productivity Using Superlative Index Numbers

Abstract: Early in this century economists began to give serious attention to making comparisons using index number techniques. There was extensive debate as to which index number formulas were the most appropriate for carrying out comparisons.1 The debate was extensive in no small part due to the lack of agreement as to criteria for preferring one formula over another. In recent decades there has been a resurgence of interest in index numbers, resulting from discoveries that the properties of index numbers can be directly related to the properties of the underlying aggregator functions that they represent. The underlying functions - production functions, utility functions, etc. - are the building blocks of economic theory, and the study of relationships between these functions and index number formulas has been referred to by Samuelson and Swamy (I974) as the economic theory of index numbers.2 A key development in the economic theory of index numbers has been the demonstration that numerous index number formulas can be explicitly derived from particular aggregator functions. This development provides a powerful new basis for selecting an index number procedure. Rather than starting the selection process with a number of plausible index number formulas, one can specify an aggregator function with desirable properties and derive the corresponding index number procedure. The resulting index is termed exact for that particular aggregator function. Diewert (I976) makes a strong case for limiting the consideration of aggregator functions to those which are flexible, i.e. those which can provide a second order approximation to an arbitrary aggregator function. He has termed index numbers that are exact for flexible aggregator functions 'superlative '. There are two superlative index numbers that are of particular interest - the Fisher Ideal index and the Tornqvist-Theil-translog index. Fisher (I 922) dubbed the following index Ideal since it best satisfied his several criteria for choosing among index numbers:

Flexible Functional Forms and Global Curvature Conditions

Abstract: Empirically estimated flexible functional forms frequently fail to satisfy the appropriate theoretical curvature conditions. Lau and Gallant and Golub have worked out methods for imposing the appropriate curvature conditions locally, but those local techniques frequently fail to yield satisfactory results. We develop two methods for imposing curvature conditions globally in the context of cost function estimation. The first method adopts Lau's technique to a generalization of a functional form first proposed by McFadden. Using this Generalized McFadden functional form, it turns out that imposing the appropriate curvature conditions at one data point imposes the conditions globally. The second method adopts a technique used by McFadden and Barnett, which is based on the fact that a non-negative sum of concave functions will be concave. Our various suggested techniques are illustrated using the U.S. Manufacturing data utilized by Berndt and Khaled

Flexible Functional Forms and Global Curvature Conditions

Abstract: Empirically estimated flexible functional forms frequently fail to satisfy the appropriate theoretical curvature conditions. Lau and Gallant and Golub have worked out methods for imposing the appropriate curvature conditions locally, but those local techniques frequently fail to yield satisfactory results. We develop two methods for imposing curvature conditions globally in the context of cost function estimation. The first method adopts Lau's technique to a generalization of a functional form first proposed by McFadden. Using this Generalized McFadden functional form, it turns out that imposing the appropriate curvature conditions at one data point imposes the conditions globally. The second method adopts a technique used by McFadden and Barnett, which is based on the fact that a non-negative sum of concave functions will be concave. Our various suggested techniques are illustrated using the U.S. Manufacturing data utilized by Berndt and Khaled

Issues in assessing the contribution of research and development to productivity growth

Abstract: The article outlines the production function approach to the estimation of the returns to R&D and then proceeds to discuss in turn two very difficult problems: the measurement of output in R&D intensive industries and the definition and measurement of the stock of R&D 'capital'. Multicollinearity and simultaneity are taken up in the next section and another section is devoted to estimation and inference problems arising more specifically in the R&D context. Several recent studies of returns to R&D are then surveyed, and the paper concludes with suggestions for ways of expanding the current data base in this field.

Productivity growth, technical progress and efficiency change in industrial countries

Abstract: This paper analyzes productivity growth in seventeen OECD countries over the period 1979-88. A nonparametric programming method (activity analysis) is used to compute Malmquist productivity indexes. These are decomposed into two component measures, namely, technical change and efficiency change. The authors find that U.S. productivity growth is slightly higher than average, all of which is due to technical change. Japan's productivity growth is the highest in the sample with almost half due to efficiency change. Copyright 1994 by American Economic Association.

Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries

Abstract: This paper analyzes productivity growth in 17 OECD countries over the period 1979-1988. A nonparametric programming method (activity analysis) is used to compute Malmquist productivity indexes. These are decomposed into two component measures, namely, technical change and efficiency change. We find that U.S. productivity growth is slightly higher than average, all of which is due to technical change. Japan's productivity growth is the highest in the sample, with almost half due to efficiency change. (JEL C43, D24) In this paper we apply recently developed