Shock Identification of Macroeconomic Forecasts Based on Daily Panels

A new procedure for shock identification of macroeconomic forecasts based on factor analysis is proposed. The identification scheme relies on daily panels and on the recognition that macroeconomic releases exhibit a high level of clustering. A large number of data releases on a single day is of considerable practical interest not only for the estimation but also for the identification of the factor model. The clustering of cross-sectional information facilitates the interpretation of the forecast innovations as real or as nominal shocks. An empirical application is provided for Swiss inflation. We show that the monetary policy shocks generate an asymmetric response to inflation, that the pass-through for CPI inflation is weak, and that the information shocks to inflation are not synchronized.