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...

We analyze the impact of short-run economic fluctuations on age-specific mortality using Bayesian time series econometrics and contribute to the debate on the procyclicality of mortality. For the first time, we examine the differing consequences of economic changes for all individual age...

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...

This paper uses a Bayesian non-stationary dynamic factor model to extract common trends and cycles from large datasets. An important but neglected feature of Bayesian statistics allows to treat stationary and non-stationary time series equally in terms of parameter estimation. Based on this...

This paper examines the comovement of the stock market and of real activity in Germany before World War I under the efficient market hypothesis. We employ multivariate spectral analysis to compare rivaling national product estimates to stock market behavior in the frequency domain. Close...