Many seasonal macroeconomic time series are subject to changes in their means and variances over a long time horizon. In this paper we propose a general treatment for the modelling of time-varying features in economic time series. We show that time series models with mean and variance functions...

We explore a new approach to the forecasting of macroeconomic variables based on a dynamic factor state space analysis. Key economic variables are modeled jointly with principal components from a large time series panel of macroeconomic indicators using a multivariate unobserved components time...

An attempt is made to estimate a state space model of investment and borrowing in a Bayesian framework and extract the unobservable agency cost of Japanese firms by firm size. Our estimates of the agency cost exhibited a declining trend in the late 80s and then switched to an increasing trend in...

This paper presents a new framework allowing strategic investors to generate yield curve projections contingent on expectations about future macroeconomic scenarios. By consistently linking the shape and location of yield curves to the state of the economy our method generates predictions for...

Production capital and technology, fundamental to understanding output and productivity growth, are unobserved except at disaggregated levels and must be estimated prior to being used in empirical analysis. We develop and apply a new estimation method, based on advances in economics, statistics,...

This note gives a fairly complete statistical description of the Hodrick-Prescott Filter (1997) which has been proposed in the context of my seasonal adjustment method (Schlicht 1981, 1984). A statistics estimator for the smoothing parameter is proposed that is asymptotically equivalent to the...

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...

We develop a method for directly modeling cointegrated multivariate time series that are observed in mixed frequencies. We regard lower-frequency data as regularly (or irregularly) missing and treat them with higher-frequency data by adopting a state-space model. This utilizes the structure of...

In this paper we analyze disinflation policy when a central bank has imperfect information about private sector inflation expectations but learns about them from economic outcomes, which are in part the result of the disinflation policy. The form of uncertainty is manifested as uncertainty about...