Biased and unbiased estimation: an econometric application in the tuna industry Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/3197xp73c

Descriptions

Attribute NameValues
Creator
Abstract or Summary
  • An econometric model of the canned tuna market is used to evaluate biased and unbiased estimators. Four methods for improving mean square error when multicollinearity is present in a regression equation are examined and compared with the results of ordinary least squares (OLS). Exact and inexact prior information methods are used to improve regression estimates when information is available. Ridge regression and principal components methods are used when accurate prior information is unavailable. Results of this study indicate that when the degree of multicollinearity is low, only ridge regression achieves improved mean square error estimates. In general, when the degree of multicollinearity is moderate, both principal components and ridge regressions improve mean square error estimates. However, consistent expected signs of the coefficients were achieved only by two of the three ridge estimators. When the degree of multicollinearity is high, both methods achieve significant improvement in mean square error estimation, although ridge regression produces slightly more accurate and reasonable results than does principal components. Both the ridge regression method and the principal components method are effective in producing low mean square error estimates, reduced variance, and expected signs on all coefficients. Either method appears to offer a viable alternative to the full model estimated by OLS. Exact and inexact prior information are introduced to improve regression estimates in the presence of multicollinearity. These methods reveal that if prior information is available and accurate and/or consistent, it should be incorporated directly into the estimation. If prior information is inconsistent and/or inaccurate, it is better to incorporate imprecise information approximately through other methods, such as ridge regression rather than to insist on formulating prior information with imprecise information. Price and quantity relationships are estimated for price levels of the U.S. canned tuna market. Retail level demand is found to be price inelastic. Wholesale supply price is positively correlated with import prices. Wholesale demand is price elastic for chunk light tuna, but inelastic for solid white tuna. Ex-vessel demand is most significantly influenced by world landings. Import demand is price elastic for albacore, price inelastic for yellowfin.
Resource Type
Date Available
Date Copyright
Date Issued
Degree Level
Degree Name
Degree Field
Degree Grantor
Commencement Year
Advisor
Academic Affiliation
Non-Academic Affiliation
Subject
Rights Statement
Peer Reviewed
Language
Digitization Specifications
  • File scanned at 300 ppi (Monochrome, 8-bit Grayscale) using ScandAll PRO 1.8.1 on a Fi-6670 in PDF format. CVista PdfCompressor 4.0 was used for pdf compression and textual OCR.
Replaces
Additional Information
  • description.provenance : Approved for entry into archive by Anna Opoien(anna.opoien@oregonstate.edu) on 2011-08-12T17:48:55Z (GMT) No. of bitstreams: 1 MuangkoeMarut1983.pdf: 2396982 bytes, checksum: e52e5679444e088779370a15d7b171d2 (MD5)
  • description.provenance : Approved for entry into archive by Anna Opoien(anna.opoien@oregonstate.edu) on 2011-08-12T17:00:21Z (GMT) No. of bitstreams: 1 MuangkoeMarut1983.pdf: 2396982 bytes, checksum: e52e5679444e088779370a15d7b171d2 (MD5)
  • description.provenance : Made available in DSpace on 2011-08-12T17:48:55Z (GMT). No. of bitstreams: 1 MuangkoeMarut1983.pdf: 2396982 bytes, checksum: e52e5679444e088779370a15d7b171d2 (MD5) Previous issue date: 1983-04-27
  • description.provenance : Submitted by Tamera Ontko (toscannerosu@gmail.com) on 2011-07-22T21:05:46Z No. of bitstreams: 1 MuangkoeMarut1983.pdf: 2396982 bytes, checksum: e52e5679444e088779370a15d7b171d2 (MD5)

Relationships

Parents:

This work has no parents.

Last modified

Downloadable Content

Download PDF

Items