The analysis of large panel data sets (with N variables) involves methods of dimension reduction and optimal information extraction. Dimension reduction is usually achieved by extracting the common variation in the data into few factors (k, where k N). In the present project, factors are...

We analyze quarterly occupation-level data from the US Current Population Survey for 1976-2013. Based on common cyclical employment dynamics, we identify two clusters of occupations that roughly correspond to the widely discussed notion of "routine" and "non-routine" jobs. After decomposing the...

Two Bayesian sampling schemes are outlined to estimate a K-state Markov switching model with time-varying transition probabilities. Data augmentation for the multinomial logit model of the transition probabilities is alternatively based on a random utility and a difference in random utility...