Working Paper: CEPR ID: DP14484
Authors: Danilo Leiva-Leon; Gabriel Perez-Quiros; Eyno Rots
Abstract: We propose an empirical framework to measure the degree of weakness of theglobal economy in real-time. It relies on nonlinear factor models designed to inferrecessionary episodes of heterogeneous deepness, and fitted to the largest advancedeconomies (U.S., Euro Area, Japan, U.K., Canada and Australia) and emerging markets (China, India, Russia, Brazil, Mexico and South Africa). Based on such inferences, we construct a Global Weakness Index that has three main features. First, itcan be updated as soon as new regional data is released, as we show by measuringthe economic effects of coronavirus. Second, it provides a consistent narrative of themain regional contributors of world economy’s weakness. Third, it allows to performrobust risk assessments based on the probability that the level of global weaknesswould exceed a certain threshold of interest in every period of time.
Keywords: international business cycles; factor model; nonlinear; coronavirus
JEL Codes: E32; C22; E27
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| global weakness index (GWI) (F01) | accurate tracking of periods of substantial weakness in the global economy (E32) |
| global weakness index (GWI) (F01) | perceptions of an upcoming global recession (F01) |
| global weakness index (GWI) (F01) | timely assessments of the global economy's state (F01) |
| global weakness index (GWI) (F01) | clear narrative of the evolving strength of the global economy (F01) |
| global weakness index (GWI) (F01) | robust risk assessments based on probability thresholds (D80) |
| Bayesian methods (C11) | estimation of model parameters (C51) |