Common Trends and Common Cycles - Bayesian Approach

Abstract

In 1993 Engle and Kozicki proposed the notion of common features of which
one example is a serial correlation common feature. We say that stationary, noninnovation processes exhibit common serial correlation when there exists at least
one linear combination of them which is an innovation. Later on in 1993 Vahid
and Engle combined the notions of cointegration among I(1) processes with
common serial correlation within their first differences. It is commonly known
that cointegrated time series have vector error correction (VEC) representation.
The existence of common serial correlation leads to an additional reduced rank
restriction imposed on the VEC model’s parameters. This type of restriction
was later termed a strong form (SF) reduced rank structure, as opposed to a
weak one introduced in 2006 by Hecq, Palm and Urbain.
The main aim of the present paper is to construct the Bayesian vector error
correction model with these additional strong form restrictions.
The empirical validity of investigating both the short- and long-run comovements between macroeconomic time series will be illustrated by the analysis
of the price-wage nexus in the Polish economy.