A flexible decomposition of a time series into stochastic cycles under possible non-stationarity is specified, providing both a useful data analysis tool and a very wide model class. A Bayes procedure using Markov Chain Monte Carlo (MCMC) is introduced with a model averaging approach which...

We estimate the union premium for young men over a period of declining unionization (1980-87) through a procedure which identifies the alternative sources of the endogeneity of union status. While we estimate the average increase in wages resulting from union employment to be in excess of 20% we...

If missing observations in a panel data set are not missing at random, many widely applied estimators may be inconsistent. In this paper the authors examine empirically several ways to reveal the nature and severity of the selectivity problem due to nonresponse, as well as a number of methods to...

We construct models which enable a decision maker to analyse the implications of typical time series patterns of daily exchange rates for currency risk management. Our approach is Bayesian where extensive use is made of Markov chain Monte Carlo methods. The effects of several model...