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Keywords:Dynamic factor model 

Working Paper
Metro Business Cycles

We construct monthly economic activity indices for the 50 largest U.S. metropolitan statistical areas (MSAs) beginning in 1990. Each index is derived from a dynamic factor model based on twelve underlying variables capturing various aspects of metro area economic activity. To accommodate mixed-frequency data and differences in data-publication lags, we estimate the dynamic factor model using a maximum- likelihood approach that allows for arbitrary patterns of missing data. Our indices highlight important similarities and differences in business cycles across MSAs. While a number of MSAs ...
Working Papers , Paper 2014-46

Working Paper
Common and Idiosyncratic Inflation

We use a dynamic factor model to disentangle changes in prices due to economy-wide (common) shocks, from changes in prices due to idiosyncratic shocks. Using 146 disaggregated individual price series from the U.S. PCE price index, we find that most of the fluctuations in core PCE prices observed since 2010 have been idiosyncratic in nature. Moreover, we find that common core inflation responds to economic slack, while the idiosyncratic component does not. That said, even after filtering out idiosyncratic factors, the estimated Phillips curve is extremely flat post-1995. Therefore, our ...
Finance and Economics Discussion Series , Paper 2020-024

Working Paper
Does Realized Volatility Help Bond Yield Density Prediction?

We suggest using "realized volatility" as a volatility proxy to aid in model-based multivariate bond yield density forecasting. To do so, we develop a general estimation approach to incorporate volatility proxy information into dynamic factor models with stochastic volatility. The resulting model parameter estimates are highly efficient, which one hopes would translate into superior predictive performance. We explore this conjecture in the context of density prediction of U.S. bond yields by incorporating realized volatility into a dynamic Nelson-Siegel (DNS) model with stochastic ...
Finance and Economics Discussion Series , Paper 2015-115

Working Paper
Oil Price Pass-Through into Core Inflation

We estimate the oil price pass-through into consumer prices both in the US and in the euro area. In particular, we disentangle the specific effect that an oil price change might have on each disaggregate price, from the effect on all prices that an oil price change might have since it affects the whole economy. To do so, we first estimate a Dynamic Factor Model on a panel of disaggregate price indicators, and then we use VAR techniques to estimate the pass-through. Our results show that the oil price passes through core inflation only via its effect on the whole economy. This pass-through is ...
Finance and Economics Discussion Series , Paper 2017-085

Working Paper
Measuring Inflation Anchoring and Uncertainty : A US and Euro Area Comparison

We use several US and euro-area surveys of professional forecasters to estimate a dynamic factor model of inflation featuring time-varying uncertainty. We obtain survey-consistent distributions of future inflation at any horizon, both in the US and the euro area. Equipped with this model, we propose a novel measure of the anchoring of inflation expectations that accounts for inflation uncertainty. Our results suggest that following the Great Recession, inflation anchoring improved in the US, while mild de-anchoring occurred in the euro-area. As of our sample end, both areas appear to be ...
Finance and Economics Discussion Series , Paper 2017-102

Working Paper
Forecasting U.S. Economic Growth in Downturns Using Cross-Country Data

To examine whether including economic data on other countries could improve the forecast of U.S. GDP growth, we construct a large data set of 77 countries representing over 90 percent of global GDP. Our benchmark model is a dynamic factor model using U.S. data only, which we extend to include data from other countries. We show that using cross-country data produces more accurate forecasts during the global financial crisis period. Based on the latest vintage data on August 6, 2020, the benchmark model forecasts U.S. real GDP growth in 2020:Q3 to be −6.9 percent (year-over-year rate) or 14.9 ...
Research Working Paper , Paper RWP 20-09

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