Testing for international business cycles: A multilevel factor model with stochastic factor selection

Tino Berger, Gerdie Everaert and Lorenzo Pozzi

Journal of Economic Dynamics and Control, 2021, vol. 128, issue C

Abstract: The empirical literature on common international business cycles has largely ignored model misspecification in estimated factor models as the various cycles are typically imposed but not tested for. This paper proposes a Bayesian stochastic factor selection approach for multilevel factor models. The procedure is applied to a three-level dynamic factor model with a global factor, six regional factors and three development level factors. We estimate the factor model using real GDP growth data for a panel of 60 countries over the period 1961−2017. We find robust evidence for the presence of a global business cycle, four regional cycles (Europe, North America, Latin America and Asia) and two development level cycles (industrial countries and emerging market economies). This suggests that both geographical proximity and the development level of countries are important dimensions of international business cycle synchronization that should be considered simultaneously, a point not previously made in the existing synchronization literature.

Keywords: Global business cycle; Regional cycle; Multilevel dynamic factor model; Bayesian; Model selection (search for similar items in EconPapers)
JEL-codes: C32 C52 F44 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:dyncon:v:128:y:2021:i:c:s0165188921000695

DOI: 10.1016/j.jedc.2021.104134

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