We develop a dynamic equilibrium model of labor demand with adverse selection. Firms learn the quality of newly hired workers after a period of employment. Adverse selection makes it costly to hire new workers and to release productive workers. As a result, firms hoard labor and under-react to...

An important component of the debate surrounding climate legislation in the United States is its potential impact on labor markets. Theoretically the connection is ambiguous and depends on the sign of cross-elasticity of labor demand with respect to energy prices, which is a priori unknown. This...

Cap and trade systems are emerging as the front-running policy choice to address climate change concerns in many countries. One of the apparent attractions of this approach is the ability to achieve hard limits on emissions over a control period. The cost of achieving this certainty on emission...

In a complete financial market every contingent claim can be hedged perfectly. In an incomplete market it is possible to stay on the safe side by superhedging. But such strategies may require a large amount of initial capital. Here we study the question what an investor can do who is unwilling...

We establish a relation between stochastic volatility models and the class of generalized hyperbolic distributions. These distributions have been found to fit exceptionally well to the empirical distribution of stock returns. We review the background of hyperbolic distributions and prove...

Stochastic Volatility (SV) models are widely used in financial applications. To decide whether standard parametric restrictions are justified for a given dataset, a statistical test is required. In this paper, we develop such a test based on the linear state space representation. We provide a...

For over a decade, nonparametric modelling has been successfully applied to study nonlinear structures in financial time series. It is well known that the usual nonparametric models often have less than satisfactory performance when dealing with more than one lag. When the mean has an additive...

In this paper we motivate, specify and estimate a model in which the intra-day volatilty process affects the inter-transaction duration process and vice versa. In order to solve the estimation problems implied by this interdependent formulation, we first propose a GMM estimation procedure for...

We consider two multivariate long-memory ARCH models, which extend the univariate long-memory ARCH models, we first consider a long-memory extension of the restricted constant conditional correlations (CCC) model introduced by Bollerslev (1990), and we propose a new unrestricted conditional...

This paper offers a new approach for estimation and forecasting of the volatility of financial time series. No assumption is made about the parametric form of the processes, on the contrary we only suppose that the volatility can be approximated by a constant over some interval. In such a...