Working Paper

Real-time forecasting with a mixed-frequency VAR

Abstract: This paper develops a vector autoregression (VAR) for macroeconomic time series which are observed at mixed frequencies ? quarterly and monthly. The mixed-frequency VAR is cast in state-space form and estimated with Bayesian methods under a Minnesota-style prior. Using a real-time data set, we generate and evaluate forecasts from the mixed-frequency VAR and compare them to forecasts from a VAR that is estimated based on data time-aggregated to quarterly frequency. We document how information that becomes available within the quarter improves the forecasts in real time.

Keywords: Bayesian statistical decision theory; Forecasting; Vector autoregression;

Bibliographic Information

Provider: Federal Reserve Bank of Minneapolis

Part of Series: Working Papers

Publication Date: 2012

Number: 701