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Title: Proxy-SVAR as a bridge for identification with mixed frequency data Authors:  Andrea Giovanni Gazzani - Bank of Italy (Italy) [presenting]
Alejandro Vicondoa - Pontificia Universidad Catolica de Chile (Chile)
Abstract: High frequency identification around key events has recently solved many puzzles in empirical macroeconomics. A novel methodology, the Bridge Proxy-SVAR, is proposed to identify structural shocks in Vector Autoregressions (VARs) by exploiting high frequency information in a more general framework. Our methodology comprises three steps: (I) identify the structural shocks of interest in high frequency systems; (II) aggregate the series of high frequency shocks at a lower frequency; (III) use the aggregated series of shocks as a proxy for the corresponding structural shock in lower frequency VARs. Both analytically and through simulations, we show that our methodology significantly improves the identification of VARs. In an empirical application on US data, a properly identified monetary policy news shock leads to a fall in output and prices.