DSGE models have recently received considerable attention in macroeconomic analysis and forecasting. They are usually estimated using Bayesian methods, which require the computation of the likelihood function under the assumption that the parameters of the model remain fixed throughout the...

Market mechanisms are increasingly being used as a tool for allocating somewhat scarce but unpriced rights and resources, such as air and water. Tradable permits have emerged as the most cost effective measure leading to the emergence of both nationwide (SO2 ) and supranational (CO2 ) emission...

Energy and climate policies are usually seen as measures to internalize externalities. However, as a side effect, these policies redistribute wealth between consumers and producers, and within these groups. While redistribution is seldom the focus of the academic literature in energy economics,...

We consider any network environment in which the "best shot game" is played. This is the case where the possible actions are only two for every node (0 and 1), and the best response for a node is 1 if and only if all her neighbors play 0. A natural application of the model is one in which the...

Climate change impacts in coastal areas (CA) have exposed coastal ecosystems to unprecedented conditions. System dynamic modelling (SD) has been used as a powerful tool to improve climate change adaptation (CCA) strategies. However, until now there are no review papers that summarize how...

This paper estimates the welfare-optimal market share of wind and solar power, explicitly taking into account their output variability. We present a theoretical valuation framework that consistently accounts for output variability over time, forecast errors, and the location of generators in the...

Non-stationary income processes are standard in quantitative life-cycle models, prompted by the observation that within-cohort income inequality increases with age. This paper generalizes Tauchen (1986) and Rouwenhorst's (1995) discretization methods to non-stationary AR(1) processes. We...

We propose a new algorithm which allows easy estimation of Vector Autoregressions (VARs) featuring asymmetric priors and time varying volatilities, even when the cross sectional dimension of the system N is particularly large. The algorithm is based on a simple triangularisation which allows to...