The Lydia-Pinkham data is analysed using a recently developed system identification algorithm. For an observed time series this yields an estimate of the process impulse response which we argue is a more robust modeling device than the traditional autoregressive moving average model for...

Problem: How to help practitioners, academics, and decision makers use experimental research findings to substantially reduce forecast errors for all types of forecasting problems. Methods: Findings from our review of forecasting experiments were used to identify methods and principles that lead...

This article presents a state-space representation known as parameters as states (PASTA) for linear market response models with time-varying parameters. The PASTA representation enables (a) conversion of the problem of estimating the time-varying effectiveness of marketing interventions from a...

This paper deals with the estimation of the output gap. We use uni- and bivariate unobserved components models in order to decompose the observed German GDP-series into trend, cycle and seasonal components. The results show that using the ifo business assessment variable as an indicator for the...