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American Journal of Agricultural Economics
Article . 2001 . Peer-reviewed
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Data sources: Crossref
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Non‐parametric Productivity Analysis with Undesirable Outputs: An Application to the Canadian Pulp and Paper Industry

Authors: Atakelty Hailu; Terrence S. Veeman;
Abstract
AbstractThis article extends the Chavas‐Cox approach to non‐parametric analysis by incorporating undesirable outputs to provide a more complete representation of the production technology. Inner and outer non‐parametric technology bounds are constructed. The methods are illustrated with application to time series data for the Canadian pulp and paper industry. Conventional measures that ignore changes in pollutant outputs underestimate true productivity growth. Further, there is a large gap between estimates generated with reference to inner and outer bounds to the technology, suggesting that researchers need to be aware of the limitations of results derived from analyses relying only on DEA methods.
Related Organizations
- University of Alberta Canada
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).547 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 0.1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 1% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%

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citations
Citations provided by BIP!
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
popularity
Popularity provided by BIP!
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
547
Top 0.1%
Top 1%
Top 10%
Fields of Science (3) View all
Related to Research communities
Energy Research