Factor Analysis

Wolfgang Härdle () and Leopold Simar
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Wolfgang Härdle: Humboldt-Universität zu Berlin, CASE — Center for Applied Statistics and Economics, Institut für Statistik und Ökonometrie

Chapter 10 in Applied Multivariate Statistical Analysis, 2003, pp 275-299 from Springer

Abstract: Abstract A frequently applied paradigm in analyzing data from multivariate observations is to model the relevant information (represented in a multivariate variable X) as coming from a limited number of latent factors. In a survey on household consumption, for example, the consumption levels, X, of p different goods during one month could be observed. The variations and covariations of the p components of X throughout the survey might in fact be explained by two or three main social behavior factors of the household. For instance, a basic desire of comfort or the willingness to achieve a certain social level or other social latent concepts might explain most of the consumption behavior. These unobserved factors are much more interesting to the social scientist than the observed quantitative measures (X) themselves, because they give a better understanding of the behavior of households. As shown in the examples below, the same kind of factor analysis is of interest in many fields such as psychology, marketing, economics, politic sciences, etc.

Keywords: Factor Model; Factor Score; Specific Variance; Varimax Rotation; Spectral Decomposition (search for similar items in EconPapers)
Date: 2003
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DOI: 10.1007/978-3-662-05802-2_10

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