Macroeconomics and the Reality of Mixed Frequency Data

286 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Testing for Granger Causality in Large Mixed-Frequency VARs (2016, unknown): “Note that the parameters in Ac are related to the ones in A1 due to stacking the high-frequency observations X (m) t in Zt (Ghysels, 2015).”
Testing for Granger Causality with Mixed Frequency Data (2016, unknown): “See the technical appendix Ghysels et al. (2015) for a characterization 61 in terms of underlying parameters.”
A MIDAS Approach to Modeling First and Second Moment Dynamics (2016, unknown): “Ghysels (2012) extends the standard Bayesian VAR approach to allow for mixed frequency lags and MIDAS polynomials.”
Do High-Frequency Financial Data Help Forecast Oil Prices? The Midas Touch at Work (2015, background): “The other approach is to stack the weekly predictors in a vector depending on the timing of its release (see Ghysels 2012).”