Prediction and sufficiency in the model factor analysis

Abul Naga, Ramses H. (1997) Prediction and sufficiency in the model factor analysis. DARP (31). Suntory and Toyota International Centres for Economics and Related Disciplines, London, UK.

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Abstract

We contrast two approaches to the prediction of latent variables in the model of factor analysis. The likelihood statistic is a sufficient statistic for the unobservables when sampling arises from the exponential family of distributions. Linear predictors, on the other hand, can be obtained as distribution-free statistics. We provide conditions under which a class of linear predictors is sufficient for the exponential family of distributions. We also examine various predictors in the light of the following criteria: (I) sufficiency, (ii) mean-square error, and (iii) unbiasedness and illustrate our results with the help of Chinese data on living standards.

Item Type:	Monograph (Discussion Paper)
Official URL:	http://sticerd.lse.ac.uk
Additional Information:	© 1997 Ramses H. Abul Naga
Divisions:	STICERD
Subjects:	H Social Sciences > HB Economic Theory H Social Sciences > HV Social pathology. Social and public welfare. Criminology
JEL classification:	C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General I - Health, Education, and Welfare > I3 - Welfare and Poverty C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics C - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology; Computer Programs
Date Deposited:	07 Jul 2008 13:00
Last Modified:	13 Sep 2024 19:38
URI:	http://eprints.lse.ac.uk/id/eprint/6597

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