The recent literature on congestion pricing with large agents contains a remarkable inconsistency: though agents are large enough to recognize self-imposed congestion and exert market power over prices, they do not take into account the impact of their own actions on the magnitude of congestion...

This paper concerns estimating parameters in a high-dimensional dynamic factormodel by the method of maximum likelihood. To accommodate missing data in theanalysis, we propose a new model representation for the dynamic factor model. Itallows the Kalman filter and related smoothing methods to...

We determine the magnitude and nature of systematic default risk using 1971{2009) default data from Moody's. We disentangle systematic risk factors due to business cycle effects, common default dynamics (frailty), and industry-specific dynamics (including contagion). To quantify the contribution...

It is a common finding in empirical discrete choice studies that the estimated mean relative values of the coefficients (i.e. WTP's) from multinomial logit (MNL) estimations differ from those calculated using mixed logit estimations, where the mixed logit has the better statistical fit. However,...

In studying congestion tolling, it is important to account for heterogeneity in preferences of drivers, as ignoring it can bias the welfare gains. We analyse the effects of tolling, in the bottleneck model, with continuous heterogeneity in the value of time and schedule delay. The welfare gain...

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...

The basic structural time series model has been designed for the modelling and forecasting of seasonal economic time series. In this paper we explore a generalisation of the basic structural time series model in which the time-varying trigonometric terms associated with different seasonal...

We propose a new class of observation-driven time-varying parameter models for dynamic volatilities and correlations to handle time series from heavy-tailed distributions. The model adopts generalized autoregressive score dynamics to obtain a time-varying covariance matrix of the multivariate...

This paper analyzes the possibilities to relieve congestion using rewards instead of taxes, as well as combinations of rewards and taxes. The model considers a Vickrey-ADL model of bottleneck congestion with endogenous scheduling. With inelastic demand, a fine (time-varying) reward is equivalent...