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Multivariate partial adjustment of financial ratios: a Bayesian hierarchical approach
Author(s) -
Gallizo Jose Luis,
Gargallo Pilar,
Salvador Manuel
Publication year - 2008
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.966
Subject(s) - multivariate statistics , econometrics , dimension (graph theory) , bayesian probability , factor analysis , dynamic factor , extension (predicate logic) , economics , financial ratio , set (abstract data type) , similarity (geometry) , computer science , finance , mathematics , statistics , artificial intelligence , pure mathematics , image (mathematics) , programming language
In this paper we propose a multivariate extension of the partial adjustment model of financial ratios. To that end, we use a dynamic factor model which assumes that financial ratios measuring, essentially, the same economic–financial dimension of the firm evolve in a similar way, reflecting the evolution of the common factor. The proposed model is hierarchical with three levels. The first describes the relationship between each ratio and its common factor; the second describes the evolution of the common factors over time by means of Lev's (1969) partial adjustment model; and the third analyzes the similarity of firms' adjustment coefficients, taking into account their characteristics. The methodology is applied to the analysis of a set of financial ratios related to the business and financial structure of the firm. Copyright © 2008 John Wiley & Sons, Ltd.