Author
Shawna Grosskopf
Other affiliations: University of North Carolina at Chapel Hill, Umeå University, Portland State University ...read more
Bio: Shawna Grosskopf is an academic researcher from Oregon State University. The author has contributed to research in topics: Productivity & Data envelopment analysis. The author has an hindex of 76, co-authored 298 publications receiving 28872 citations. Previous affiliations of Shawna Grosskopf include University of North Carolina at Chapel Hill & Umeå University.
Papers published on a yearly basis
Papers
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TL;DR: In this article, a nonparametric programming method (activity analysis) is used to compute the Malmquist productivity indexes, which are decomposed into two component measures, namely, technical change and efficiency change.
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
3,434 citations
TL;DR: In this paper, a directional distance function is used as a component in a new productivity index that readily models joint production of goods and bads, credits firms for reductions in bads and increases in goods, and does not require shadow prices of bad outputs.
2,003 citations
Book•
01 Jan 1985
TL;DR: The Structure of Production Technology as discussed by the authors, Radial Input Efficiency Measures, Hyperbolic Graph Efficiency Measures and Non-radial Efficiency Measures for Scale Efficiency and Toward Empirical Implementation.
Abstract: The Structure of Production Technology.- Radial Input Efficiency Measures.- Radial Output Efficiency Measures.- Hyperbolic Graph Efficiency Measures.- A Comparison of Input, Output, and Graph Efficiency Measures.- Nonradial Efficiency Measures.- Measures of Scale Efficiency.- Toward Empirical Implementation.
1,933 citations
TL;DR: Multilateral productivity comparisons of firms producing multiple outputs, some of which are undesirable, are obtained by making two modifications to the standard Farrell approach to efficiency measurement.
Abstract: Multilateral productivity comparisons of firms producing multiple outputs, some of which are undesirable, are obtained by making two modifications to the standard Farrell approach to efficiency measurement. The restriction that production technology satisfy strong disposability of outputs is relaxed to allow for the fact that undesirable outputs may be freely disposable, and the efficiency measures are modified to allow for an asymmetric treatment of desirable and undesirable outputs. Performance measures that satisfy these requirements are calculated as solutions to programming problems. The methodology is applied to a sample of mills producing paper and pollutants.
1,748 citations
TL;DR: In this article, a non-parametric linear programming approach for the calculation of a Malmquist productivity index was developed, which is applied to the case of Swedish pharmacies, in order to calculate the productivity index.
Abstract: In this article we develop a non-parametric (linear programming) approach for calculation of a Malmquist (input based) productivity index. The method is applied to the case of Swedish pharmacies.
878 citations
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30 Nov 1999TL;DR: In this article, the basic CCR model and DEA models with restricted multipliers are discussed. But they do not consider the effect of non-discretionary and categorical variables.
Abstract: List of Tables. List of Figures. Preface. 1. General Discussion. 2. The Basic CCR Model. 3. The CCR Model and Production Correspondence. 4. Alternative DEA Models. 5. Returns to Scale. 6. Models with Restricted Multipliers. 7. Discretionary, Non-Discretionary and Categorical Variables. 8. Allocation Models. 9. Data Variations. Appendices. Index.
4,395 citations
01 Jan 1994
TL;DR: In this article, the authors analyzed productivity growth in seventeen OECD countries over the period 1979-88 and found that U.S. productivity growth is slightly higher than average, all of which is due to technical change.
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.
3,851 citations
Posted Content•
TL;DR: In this article, a nonparametric programming method (activity analysis) is used to compute the Malmquist productivity indexes, which are decomposed into two component measures, namely, technical change and efficiency change.
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
3,434 citations
TL;DR: The authors survey 130 studies that apply frontier efficiency analysis to financial institutions in 21 countries and find that the various efficiency methods do not necessarily yield consistent results and suggest some ways that these methods might be improved to bring about findings that are more consistent, accurate, and useful.
2,983 citations
TL;DR: In this paper, a coherent data-generating process (DGP) is described for nonparametric estimates of productive efficiency on environmental variables in two-stage procedures to account for exogenous factors that might affect firms’ performance.
2,915 citations