This article provides empirical evidence from the ‘first wave of globalization’ in the 19th century for the question as to how commodity markets integrated domestically and internationally. I apply a dynamic factor model borrowed from business cycle analysis that for the first time allows me...

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 analyses 19th century wheat market integration using comovement analysis borrowed from international business cycle research. This allows for tracking each single city's integration into its respective national market while controlling for international developments. I nd that the...

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 study analyzes annual wheat prices in 13 German cities in the years 1806 to 1855, together with wheat price series from 44 other European and American cities. The method used is a dynamic factor model, which allows for distinguishing common price uctuations on international and national...