We model bank management actions in severe stress test conditions using a game-theoretical framework. Banks update their balance sheets to strategically maximize risk-adjusted returns to shareholders given three regulatory constraints and feedback effects related to fire sales, interactions of...

We model bank management actions in severe stress test conditions using a game-theoretical framework. Banks update their balance sheets to strategically maximize risk-adjusted returns to shareholders given three regulatory constraints and feedback effects related to fire sales, interactions of...

How wrong could policymakers be when using linearized solutions to their macroeconomic models instead of nonlinear global solutions? This question became of much practical interest during the Great Recession and the recent zero lower bound crisis. We assess the importance of nonlinearities in a...

This paper develops and estimates a model of firm-level fixed capital investment when firms face borrowing constraints. Dynamically optimal investment functions are derived for the firms with and without financial constraints. These policy functions are then used to construct the likelihood of...

Solving large economic models requires large amounts of computational effort, as the complexity of these models increases the computational effort required in their solution increases dramatically. To examine the nature of these solutions researchers need to repeatedly solve models using...

Our study aims to gain insight on financial stability and climate transition risk. We develop a methodological framework that captures the direct effects of a stressful climate transition shock as well as the indirect - or systemic - implications of these direct effects. We apply this framework...

The estimation of regression models subject to exact linear restrictions, is a widely applied technique, however, aside from simple examples, the reparameterization method is rarely employed except in the case of polynomial lags. We believe this is due to lack of a general transformation method...

This paper develops statistical and computational tools for modelling returns forecasts to be used by a risk neutral investor. Any forecast with the same sign as the conditional mean optimises the loss function derived from this agents' decision problem, so the class of optimal predictors is...

In this paper, I develop a population-based Markov chain Monte Carlo (MCMC) algorithm known as parallel tempering to estimate dynamic stochastic general equilibrium (DSGE) models. Parallel tempering approximates the posterior distribution of interest using a family of Markov chains with tempered...