Estimating the Technology Coefficients in Linear Programming Models

Linear constraints for mathematical programming models are . demonstrated to be random coefficient regression (RCR) models when estimating constraint coefficients from samples. Monte·carlo experiments show an RCR estimator preferable to least squares although least squares is also acceptable. Dependence between output levels and technical coefficients can lead to biased estimates.


Issue Date:
Jul 30 1989
Publication Type:
Conference Paper/ Presentation
DOI and Other Identifiers:
Record Identifier:
https://ageconsearch.umn.edu/record/270519
Language:
English
Total Pages:
15




 Record created 2018-04-03, last modified 2020-10-28

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