Article published in Chaos: An Interdisciplinary Journal of Nonlinear Science – September 2017
Common dynamical properties of business cycle fluctuations are studied in a sample of more than 100 countries that represent economic regions from all around the world. We apply the methodology of multivariate singular spectrum analysis (M-SSA) to identify oscillatory modes and to detect whether these modes are shared by clusters of phase- and frequency-locked oscillators. An extension of the M-SSA approach is introduced to help analyze structural changes in the cluster configuration of synchronization. With this novel technique, we are able to identify a common mode of business cycle activity across our sample, and thus point to the existence of a world business cycle. Superimposed on this mode, we further identify several major events that have markedly influenced the landscape of world economic activity in the postwar era.
This paper analyses the drivers of French transport CO2 emissions over the period 1960-2017. A decomposition analysis is used to evaluate the relative contribution of five key drivers of passenger and freight transports emissions: transport demand, modal shift, vehicle load factor, energy efficiency and carbon intensity of the energy.
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