We describe research on the impact of health insurance on healthcare spending ("moral hazard"), and use this context to illustrate the value of and important complementarities between different empirical approaches. One common approach is to emphasize a credible research design; we review...

The conventional wisdom in macroeconomic modeling is to attribute business cycle fluctuations to innovations in the level of the fundamentals. Though volatility shocks could be important too, their propagating mechanism is still not well understood partly because modeling the latent volatilities...

Two alternative approaches to identifying a model confidence set (MCS) are contrasted. Together with a specification of the established MCS test, we present a new version of a test that identifies a model set satisfying the MCS requirements and is characterised by an alternative model ranking...

The Value-at-Risk calculation reduces the dimensionality of the risk factor space. The main reasons for such simplifications are, e.g., technical efficiency, the logic and statistical appropriateness of the model. In Chapter 2 we present three simple mappings: the mapping on the market index,...

Die Verknüpfung der einzelnen Disziplinen des Wirtschaftsingenieurwesens wird anhand des Konfigurationsmanagements im Anlagenbau untersucht. Dafür wird vor dem Hintergrund der Modellierung von Systemen im Sinne des Systems Engineering die Methode des Konfigurationsmanagements in die Systems...

In this chapter, we discuss the use of mixed frequency models and diffusion index approximation methods in the context of prediction. In particular, select recent specification and estimation methods are outlined, and an empirical illustration is provided wherein U.S. unemployment forecasts are...

The Capital Asset Pricing Model (CAPM) has dominated finance theory for over thirty years; it suggests that the market beta alone is sufficient to explain stock returns. However evidence shows that the cross-section of stock returns cannot be described solely by the one-factor CAPM. Therefore,...

Bayesian model averaging attempts to combine parameter estimation and model uncertainty in one coherent framework. The choice of prior is then critical. Within an explicit framework of ignorance we define a ‘suitable' prior as one which leads to a continuous and suitable analog to the pretest...