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Assessing U.S. Aggregate Fluctuations Across Time and Frequencies
We study the behavior of key macroeconomic variables in the time and frequency domain. For this purpose, we decompose U.S. time series into various frequency components. This allows us to identify a set of stylized facts: GDP growth is largely a high-frequency phenomenon whereby inflation and nominal interest rates are characterized largely by low-frequency components. In contrast, unemployment is a medium-term phenomenon. We use these decompositions jointly in a structural VAR where we identify monetary policy shocks using a sign restriction approach. We find that monetary policy shocks ...
Robust estimation of nonstationary, fractionally integrated, autoregressive, stochastic volatility
Empirical volatility studies have discovered nonstationary, long-memory dynamics in the volatility of the stock market and foreign exchange rates. This highly persistent, infinite variance?but still mean reverting?behavior is commonly found with nonparametric estimates of the fractional differencing parameter d, for financial volatility. In this paper, a fully parametric Bayesian estimator, robust to nonstationarity, is designed for the fractionally integrated, autoregressive, stochastic volatility (SV-FIAR) model. Joint estimates of the autoregressive and fractional differencing parameters ...