  The paper introduces an estimation method for flexible Bayesian quantile
regression in ordinal (FBQROR) models i.e., an ordinal quantile regression
where the error follows a generalized asymmetric Laplace (GAL) distribution.
The GAL distribution, unlike the asymmetric Laplace (AL) distribution, allows
to fix specific quantiles while simultaneously letting the mode, skewness and
tails to vary. We also introduce the cumulative distribution function
(necessary for constructing the likelihood) and the moment generating function
of the GAL distribution. The algorithm is illustrated in multiple simulation
studies and implemented to analyze public opinion on homeownership as the best
long-term investment in the United States.
