Estimating the Characteristics of Polluting Technologies

Polluting technologies can be represented using output distance functions. A common approach to estimating such functions is to factor out one of the outputs and estimate the resulting equation using well-known stochastic frontier estimation methods, including maximum likelihood. A problem with this approach is that the outputs that are not factored out may be correlated with the error term, leading to biased and inconsistent estimates. This paper addresses the problem in a Bayesian framework. The methodology is applied to data on U.S. electric utilities. Results include estimates of technical inefficiencies and the shadow price of a pollutant.


Issue Date:
2007
Publication Type:
Conference Paper/ Presentation
DOI and Other Identifiers:
Record Identifier:
https://ageconsearch.umn.edu/record/10413
PURL Identifier:
http://purl.umn.edu/10413
Total Pages:
13
Series Statement:
Conference Paper




 Record created 2017-04-01, last modified 2019-08-26

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