The increasing availability of financial market data at intraday frequencies has not only led to the development of improved volatility measurements but has also inspired research into their potential value as an information source for volatility forecasting. In this paper we explore the...

Private toll roads are now seriously considered as an alternative to public (free-access) road infrastructure. Nevertheless, complete private provision without governmental control is only rarely considered. A main consideration against private roads would be that operators would be primarily...

In this paper we employ techniques developed in spatial econometrics to analyse spatial patterns of technology diffusion, to detect clusters and to estimate theoretical models that incorporate space explicitly. These techniques correct for misspecifications resulting from the omission of spatial...

This paper considers second-best congestion pricing in the monocentric city, with endogenous residential density and endogenous labour supply. A spatial general equilibrium model is developed that allows consideration of the three-way interactions between urban density, traffic congestion and...

This paper distinguishes uncertainty types that differ continuously with respect to the degree to which uncertainty affects the optimal price/price markup or optimal quantity. A monopoly example is used to show that seemingly strong assumptions on functional forms can represent a wide variety of...

"Robot cars" are cars that allow for automated driving. They can drive closer together than human driven "normal cars" and thereby raise road capacity. Obtaining a robot car instead of a normal car can also be expected to lower the userś value of time losses (VOT), because travel time can be...

This paper investigates second-best congestion pricing in a monocentric city characterized by distortionary, rigid regulatory mechanisms in the housing market (building height restrictions, zoning and property taxation). The Pigouvian toll is shown to retain its optimality under any setting with...

We introduce a Combined Density Nowcasting (CDN) approach to Dynamic Factor Models (DFM) that in a coherent way accounts for time-varying uncertainty of several model and data features in order to provide more accurate and complete density nowcasts. The combination weights are latent random...

We study the performance of alternative methods for calculating in-sample confidence and out of-sample forecast bands for time-varying parameters. The in-sample bands reflect parameter uncertainty only. The out-of-sample bands reflect both parameter uncertainty and innovation uncertainty. The...