Published online by Cambridge University Press: 21 September 2017
This paper examines the evolution of the distribution of industry-specific business cycle linkages, which are modeled through a multivariate Markov-switching model and estimated by Gibbs sampling. Using nonparametric density estimation approaches, we find that the number and location of modes in the distribution of industrial dissimilarities change over the business cycle. There is a relatively stable trimodal pattern during expansionary and recessionary phases characterized by highly, moderately, and lowly synchronized industries. However, during phase changes, the density mass spreads from moderately synchronized industries to lowly synchronized industries. This agrees with a sequential transmission of the industrial business cycle dynamics.
We are thankful to Gabriel Perez Quiros, the editor, and two anonymous referees for their comments. M. Camacho acknowledges the financial support from projects ECO2013-45698-P and ECO2016-76178-P, whose contribution also is the result of the activity carried out under the program Groups of Excellence of the region of Murcia, the Fundacion Seneca, Science and Technology Agency of the region of Murcia project 19884/GERM/15. All remaining errors are our responsibility. The views expressed in this paper are those of the authors and do not represent the views of the Banco de España or the Eurosystem.