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...

The impact of shocks in dynamic environments depends on how forward-looking agents anticipate the path of future fundamentals that shape their decisions. We incorporate flexible beliefs about future fundamentals in a general class of dynamic spatial models, allowing beliefs to be evolving,...

Donald Trump's election and his nomination of Scott Pruitt, a climate skeptic, to lead the Environmental Protection Agency drastically downshifted expectations on US climate-change policy. We study firms' stock-price reactions and institutional investors' portfolio adjustments after these...

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...

This paper investigates how shocks to expected cash flows influence CEO incentive compensation. Exploiting changes in compliance with environmental regulations as shocks to expected future cash flows, we find that adverse shocks typically prompt corporate boards to recalibrate CEO compensation...

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...