Shortly before the national elections in the Netherlands, the Netherlands Bureau for Economic Policy Analysis (CPB) evaluates the economic effects of the policy proposals in election programs. This paper investigates the sensitivity of this analysis to the uncertainty of parameter estimates in...

Inflation-targeting central banks have only imperfect knowledge about the effect of policy decisions on inflation. An important source of uncertainty is the relationship between inflation and unemployment. This paper studies the optimal monetary policy in the presence of uncertainty about the...

We estimate a Markov-switching mixture of two familiar macroeconomic models: a richly parameterized dynamic stochastic general equilibrium (DSGE) model and a corresponding Bayesian vector autoregression (BVAR) model. We show that the Markov-switching mixture model dominates both individual...

We examine whether the robustifying nature of Taylor rule cross-checking under model uncertainty carries over to the case of parameter uncertainty. Adjusting monetary policy based on this kind of cross-checking can improve the outcome for the monetary authority. This, however, crucially depends...

This paper provides a complete program for the valuation of aggregate non-life insurance liability cash flows based on claims triangle data. The valuation is fully consistent with the principle of valuation by considering the costs associated with a transfer of the liability to a so-called...

We employ the robust-satisficing approach to derive robust monetary policy when parameters of a macro model are uncertain. There is a trade-off between robustness of policies and their performance. Hence, under uncertainty, the policy maker is assumed to be content with policy performance at...

We use Bayesian methods to estimate the preferences of the US Federal Reserve by assuming that monetary policy is performed optimally under commitment since the mid-sixties. For this purpose, we distinguish between three subperiods, i.e. the pre-Volcker, the Volcker-Greenspan and the Greenspan...

Paralleling regulatory developments, we devise value-at-risk and expected shortfall type risk measures for the potential losses arising from using misspecied models when pricing and hedging contingent claims. Essentially, losses from model risk correspond to losses realized on a perfectly hedged...

Mean-variance portfolio optimization is more popular than optimization procedures that employ downside risk measures such as the semivariance, despite the latter being more in line with the preferences of a rational investor. We describe strengths and weaknesses of semivariance and how to...

Polynomial chaos expansion (PCE) provides a method that enables the user to represent a quantity of interest (QoI) of a model's solution as a series expansion of uncertain model inputs, usually its parameters. Among the QoIs are the policy function, the second moments of observables, or the...