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Maximo Camacho
- 30 October 2020
- WORKING PAPER SERIES - No. 2484Details
- Abstract
- To analyze the international transmission of business cycle fluctuations, we propose a new multilevel dynamic factor model with a block structure that (i) does not restrict the factors to being orthogonal and (ii) mixes data sampled at quarterly and monthly frequencies. By means of Monte Carlo simulations, we show the high performance of the model in computing inferences of the unobserved factors, accounting for the spillover effects, and estimating the model's parameters. We apply our proposal to data from the G7 economies by analyzing the responses of national factors to shocks in foreign factors and by quantifying the changes in national GDP expectations in response to unexpected positive changes in foreign GDPs. Although the share of the world factor as a source of the international transmission of fluctuations is still significant, this is partially absorbed by the spillover transmissions. In addition, we document a pro-cyclical channel of international transmission of output growth expectations, with the US and UK being the countries that generate the greatest spillovers and Germany and Japan being the countries that generate the smallest spillovers. Therefore, policymakers should closely monitor the evolution of foreign business cycle expectations.
- 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
F42 : International Economics→Macroeconomic Aspects of International Trade and Finance→International Policy Coordination and Transmission
F41 : International Economics→Macroeconomic Aspects of International Trade and Finance→Open Economy Macroeconomics
- 1 August 2000
- WORKING PAPER SERIES - No. 27Details
- Abstract
- We propose an optimal filter to transform the Conference Board Composite Leading Index (CLI) into recession probabilities in the US economy. We also analyze the CLI's accuracy at anticipating US output growth. We compare the predictive performance of linear, VAR extensions of smooth transition regression and switching regimes, probit, nonparametric models and conclude that a combination of the switching regimes and nonparametric forecasts is the best strategy at predicting both the NBER business cycle schedule and GDP growth. This confirms the usefulness of CLI, even in a real-time analysis.
- 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
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods