This chapter provides an overview of solution and estimation techniques for dynamic
stochastic general equilibrium models. We cover the foundations of numerical …

Uncertainty is critical to questions about climate change policy. Recently developed
recursive integrated assessment models have become the primary tools for studying and …

Computational methods are required to solve problems without closed-form solutions in
environmental and resource economics. Efficiency, stability, and accuracy are key elements …

We present a novel computational framework that can compute global solutions to high-
dimensional dynamic stochastic economic models on irregular state space geometries. This …

The rise of mobile communication, ample computing power, and Amazon's training of
customers has led to last-mile delivery challenges and created struggles for companies …

We study the Markov perfect equilibrium in a dynamic game where agents have non-
constant time preference, decentralized households determine aggregate savings, and a …

In this thesis, we consider three non-trivial problems of risk allocation and apply approaches
from theoretical finance and risk management to address several policy debates from a …

We introduce a flexible and scalable method for solving discrete-time dynamic incentive
problems with heterogeneous agents and persistent types. Our framework entails a generic …

This paper introduces a nonlinear certainty‐equivalent approximation method for dynamic
stochastic problems. We first introduce a novel, stable, and efficient method for computing …

Optimal control is a high-quality and challenging control approach that requires very
explorative metaheuristic optimisation techniques to find the most efficient control profile for …