We investigate changes in the time series characteristics of postwar U.S. inflation. In a model-based analysis the conditional mean of inflation is specified by a long memory autoregressive fractionally integrated moving average process and the conditional variance is modelled by a stochastic...

The linear Gaussian state space model for which the common variance istreated as a stochastic time-varying variable is considered for themodelling of economic time series. The focus of this paper is on thesimultaneous estimation of parameters related to the stochasticprocesses of the mean part...

We consider unobserved components time series models where the components are stochastically evolving over time and are subject to stochastic volatility. It enables the disentanglement of dynamic structures in both the mean and the variance of the observed time series. We develop a simulated...

This paper models strategic interactions between a product supplier, a provider of information about product quality, and end users, in the context of road transportation. Using a game-theoretical analysis of suppliers' pricing strategies, we assess the social welfare effects of traffic...

In this paper we set out the welfare economics based case for imposing cartel penalties on the cartel overcharge rather than on the more conventional bases of revenue or profits (illegal gains). To do this we undertake a systematic comparison of a penalty based on the cartel overcharge with...

We introduce a new and general methodology for analyzing vector autoregressive models with time-varying coefficient matrices and conditionally heteroskedastic disturbances. Our proposed method is able to jointly treat a dynamic latent factor model for the autoregressive coefficient matrices and...