A Recursive Model of the Hog Industry

There are a number of estimation methods available to the econometrician. They range in complexity from least squares, which takes only a few minutes with pencil and paper for a simple problem, to full information maximum likelihood, which requires a large-capacity electronic computer for effective application. A list of the common methods, given in order of increasing complexity, includes least squares, two-stage least squares, instrumental variables, limited information, and full information. Recursive systems are fitted by least squares which makes estimation relatively simple, and they have other desirable statistical properties. Following a brief discusssion of the special characteristics of recursive systems, this paper presents an application of the recursive method to an analysis of the hog industry. The author is indebted to Anthony S. Rojko and Hyman Weingarten of the Economic Research Service for their helpful suggestions during the preparation of this paper.


Issue Date:
1962-01
Publication Type:
Journal Article
PURL Identifier:
http://purl.umn.edu/145794
Published in:
Agricultural Economics Research, Volume 14, Number 1
Page range:
1-12
Total Pages:
12




 Record created 2017-04-01, last modified 2017-08-27

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