Some Aspects of Estimating Statistical Cost Functions
Paul R. Johnson
American Journal of Agricultural Economics, 1964, vol. 46, issue 1, 179-187
Abstract:
This article analyzes the results of an empirical study for a multistore farm supply cooperative with respect to several criticisms of statistical cost functions. It shows that combining time series and cross section data in an analysis of covariance allows one to avoid the regression fallacy and provides an implicit test for the fallacy, thus avoiding one of the most damaging criticisms of cost curve fitting. Further consideration, however, validates Friedman's criticism that statistical cost curves lack identifiability. It is postulated that Hoch's development of the covariance model for production functions to avoid simultaneous equation bias in certain instances also holds for cost curves. It is argued that this is an empirical question depending on the specific circumstances, and, in general, fitting a statistical cost curve is not a test of those cost curves postulated in the theory of the firm.
Date: 1964
References: Add references at CitEc
Citations: View citations in EconPapers (7)
Downloads: (external link)
http://hdl.handle.net/10.2307/1236482 (application/pdf)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:oup:ajagec:v:46:y:1964:i:1:p:179-187.
Access Statistics for this article
American Journal of Agricultural Economics is currently edited by Madhu Khanna, Brian E. Roe, James Vercammen and JunJie Wu
More articles in American Journal of Agricultural Economics from Agricultural and Applied Economics Association Contact information at EDIRC.
Bibliographic data for series maintained by Oxford University Press ().