This paper presents insights on U.S. business cycle volatility since 1867 derived from diffusionindices. We employ a Bayesian dynamic factor model to obtain aggregate and sectoral economicactivity indices. We find a remarkable increase in volatility across World War I, which isreversed after...

This paper presents insights on U.S. business cycle volatility since 1867 de- rived from diffusion indices. We employ a Bayesian dynamic factor model to obtain aggregate and sectoral economic activity indices. We find a remarkable increase in volatility across World War I, which is reversed...

This paper presents insights on U.S. business cycle volatility since 1867 de- rived from diffusion indices. We employ a Bayesian dynamic factor model to obtain aggregate and sectoral economic activity indices. We find a remarkable increase in volatility across World War I, which is reversed...

This paper reexamines U.S. business cycle volatility since 1867. We employ dynamic factor analysis as an alternative to reconstructed national accounts. We find a remarkable volatility increase across World War I, which is reversed after World War II. While we can generate evidence of postwar...

This paper presents insights on U.S. business cycle volatility since 1867 derived from diffusion indices. We employ a Bayesian dynamic factor model to obtain aggregate and sectoral economic activity indices. We find a remarkable increase in volatility across World War I, which is reversed after...

We use a Bayesian dynamic factor model to measure Germanys pre WorldWar I economic activity. The procedure makes better use of existing time seriesdata than historical national accounting. To investigate industrializationwe propose to look at comovement between sectors. We find that...

We use a Bayesian dynamic factor model to measure Germany's pre World War I economic activity. The procedure makes better use of existing time series data than historical national accounting. To investigate industrialization we propose to look at comovement between sectors. We find that...