Piergiorgio Alessandri, Andrea Gazzani, Alejandro Vicondoa
Isolating financial uncertainty shocks is difficult because financial markets rapidly price changes in several economic fundamentals. To bypass this difficulty, we identify uncertainty shocks using daily data and use their monthly averages as an instrument in a VAR. We show that this novel approach is theoretically appealing and has dramatic implications for leading empirical studies on financial uncertainty. Daily interactions between equity returns, bond spreads and expected volatility cause previous identification schemes to fail at the monthly frequency. Once these interactions are explicitly modeled, the impact of uncertainty shocks on output and inflation is significant and similar across specifications.
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