Analysing formalisation of management accounting by Bayesian variable selection in a cumulative logit model
Sprache des Vortragstitels:
2013 Applied Bayesian Statistics School: BAYESIAN METHODS FOR VARIABLE SELECTION WITH APPLICATIONS TO HIGH-DIMENSIONAL DATA
Sprache des Tagungstitel:
In many applications especially in social and business sciences it is of interest which variables out of a set of potential predictors are actually associated with an ordinal response variable. As an example we present an analysis where the response variable 'formalisation of management accounting' in firms is measured on an ordinal scale with 3 categories ranging from 'less or not recorded' to 'fully recorded'. We use a Bayesian cumulative logit model and implement variable selection by specifying spike and slab priors for the regression coefficients. Posterior inference is feasible by MCMC methods and data augmentation, expanding the auxiliary mixtures sampler of (Frühwirth-Schnatter and Frühwirth, 2010) to ordinal data. We apply the sampler to data from a survey on Austrian and German firms and consider as potential predictors in our model annual sales, number of employees, business sector, state, structure (family firm or non-family firm) and generation. Results indicate that only two of these potential regressors ('structure' and 'number of employees') are associated with the degree of formalisation of management accounting.