In 2002 we published a paper in which we used state space time series methods to analyse the teenage employment‐federal minimum wage relationship in the US (Bazen and Marimoutou, 2002). The study used quarterly data for the 46 year period running from 1954 to 1999. We detected a small,...

This paper describes a moments estimator for a standard state-space model with coefficients generated by a random walk. A penalized least squares estimation is linked to the GLS (Aitken) estimates of the corresponding linear model with time-invariant parameters. The VC estimates are moments...

This paper examines the correlated random coefficient model. It extends the analysis of Swamy (1971, 1974), who pioneered the uncorrelated random coefficient model in economics. We develop the properties of the correlated random coefficient model and derive a new representation of the variance...

Swedish labor market programs appear large from an international perspective, yet their consequences are not fully investigated and understood. In this paper we estimate a switching regression model with training effect modeled as a random coefficient, partitioned in an observed and unobserved...

This paper develops a novel and tractable empirical approach to estimate the cycle in schooling participation decisions, which we denominate the schooling cycle. The estimation procedure is based on unobserved components time series models that decompose higher education enrollment rates into a...

The current economic crisis requires fast information to predict economic behavior early, which is difficult at times of structural changes. This paper suggests an innovative new method of using data on internet activity for that purpose. It demonstrates strong correlations between keyword...

We investigate the effect of forecast uncertainty in a cointegrating vector error correction model for Switzerland. Forecast uncertainty is evaluated in three different dimensions. First, we investigate the effect on forecasting performance of averaging over forecasts from different models....

This paper introduces a novel approach for dealing with the 'curse of dimensionality' in the case of large linear dynamic systems. Restrictions on the coefficients of an unrestricted VAR are proposed that are binding only in a limit as the number of endogenous variables tends to infinity. It is...