This paper sets out the theoretical foundations for continuous-time signal extraction in econometrics. Continuous-time modeling gives an effective strategy for treating stock and flow data, irregularly spaced data, and changing frequency of observation. We rigorously derive the optimal...

This paper advances the theory and methodology of signal extraction by introducing asymptotic and finite sample formulas for optimal estimators of signals in nonstationary multivariate time series. Previous literature has considered only univariate or stationary models. However, in current...

An increasing number of data sources have measured the components of reallocation of jobs across employers and workers across jobs. Whether and how job reallocation across employers and excess worker “churn” affect other measures of the health of the U.S. economy remains an open question. In...

This paper develops the theory of multi-step ahead forecasting for vector time series that exhibit temporal nonstationarity and co-integration. We treat the case of a semi-infinite past by developing the forecast filters and the forecast error filters explicitly. We also provide formulas for...

A multivariate bullwhip expression for <I>m</I> two-stage supply chains with an order-up-to inventory policy is developed. The demand models under consideration are differenced stationary vector time series with a Wold representation for which general forecasting formulas are available, resulting in a...</i>

We construct measures of individual forecasters' subjective uncertainty at horizons ranging from one to five years, incorporating a rich information set from the European Central Bank's Survey of Professional Forecasters. We find that the uncertainty curve is more linear than the disagreement...