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This chapter demonstrates the usefulness of the GVAR modelling framework as a tool for scenario-based forecasting and counterfactual analysis. Working with the GVAR model developed by Greenwood-Nimmo, Nguyen and Shin (2010, J. Appl. Econometrics), we first show how probabilistic forecasting can...
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Using a modified DCC-MIDAS specification that allows the long-term correlation component to be a function of multiple explanatory variables, we show that the stock-bond correlation in the US, the UK, Germany, France, and Italy is mainly driven by inflation and interest rate expectations as well...
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This paper puts forward a Bayesian version of the global vector autoregressive model (B-GVAR) that accommodates international linkages across countries in a system of vec-tor autoregressions. We compare the predictive performance of B-GVAR models for the one- and four-quarter ahead forecast...
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fraction of housing market volatility is local. And the local volatilities mostly are due to time-variations of idiosyncratic …
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factor are typically small, with the annualized unconditional volatility estimated at 0.06%, but highly persistent, with … estimated persistence at 0.98. Evidence of time variation in the volatility of the global factor is overwhelming as there are … times in which volatility could be several times larger than its unconditional level (about ten times in the aftermath of …
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