UNDERSIZED SAMPLES AND MAXIMUM LIKELIHOOD ESTIMATION OF SUM-CONSTRAINED LINEAR MODELS

Paul de Boer and R. Harkema

No 272283, Econometric Institute Archives from Erasmus University Rotterdam

Abstract: Maximum likelihood procedures for estimating sum-constrained models like demand systems, brand choice models and so on, break down or produce very unstable estimates when the number of categories is large as compared with the number of observations available. In empirical studies this difficulty is mostly resolved by postulating the contemporaneous covariance matrix of the -1 dependent variables at time t to equal a 2 (I n n 1 1). In this paper we n n develop a maximum likelihood procedure based on a contemporaneous covariance matrix which allows that the variances per category may be different, while the number of observations required is substantially less than the number that would be required in the case of a completely unrestricted contemporaneous covariance matrix.

Keywords: Agricultural and Food Policy; Research Methods/Statistical Methods (search for similar items in EconPapers)
Pages: 39
Date: 1983-12
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://ageconsearch.umn.edu/record/272283/files/erasmus159.pdf (application/pdf)
https://ageconsearch.umn.edu/record/272283/files/erasmus159.pdf?subformat=pdfa (application/pdf)

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:ags:eureia:272283

DOI: 10.22004/ag.econ.272283

Access Statistics for this paper

More papers in Econometric Institute Archives from Erasmus University Rotterdam Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().