- 9 January 2018
- OCCASIONAL PAPER SERIES - No. 205Details
- This paper studies the cyclical properties of real GDP, house prices, credit, and nominal liquid financial assets in 17 EU countries, by applying several methods to extract cycles. The estimates confirm earlier findings of large medium-term cycles in credit volumes and house prices. GDP appears to be subject to fluctuations at both business-cycle and medium-term frequencies, and GDP fluctuations at medium-term frequencies are strongly correlated with cycles in credit and house prices. Cycles in equity prices and long-term interest rates are considerably shorter than those in credit and house prices and have little in common with the latter. Credit and house price cycles are weakly synchronous across countries and their volatilities vary widely – these differences may be related to the structural properties of housing and mortgage markets. Finally, DSGE models can replicate the volatility of cycles in house and equity prices, but not the persistence of house price cycles.
- JEL Code
- C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
- 24 March 2020
- WORKING PAPER SERIES - No. 2381Details
- We propose an empirical framework to measure the degree of weakness of the global economy in real-time. It relies on nonlinear factor models designed to infer recessionary episodes of heterogeneous deepness, and fitted to the largest advanced economies (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, it can be updated as soon as new regional data is released, as we show by measuring the economic effects of coronavirus. Second, it provides a consistent narrative of the main regional contributors of world economy's weakness. Third, it allows to perform robust risk assessments based on the probability that the level of global weakness would exceed a certain threshold of interest in every period of time.
- JEL Code
- E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
C22 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models &bull Diffusion Processes
E27 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Forecasting and Simulation: Models and Applications