Three papers on the economics of climate change

This thesis seeks to expand the tools available for policy analysis as it relates to the problem of mitigating global climate change.; Chapter 1 presents an overlapping generations mode1 of climate and economy which provides a framework for policy evaluation. The model allows for the measurement of the effects of various policies on the economy, the climate, and the welfare of specific age cohorts of agents. Specifically, this model allows the examination of the welfare implications of proposed policies on economic agents alive at the time in which these policies are proposed, which opens the question of the political feasibility of proposed regulations as a metric for evaluation. Sensitivity analysis is performed in two areas: First, the sensitivity of evaluation to the parameters of the climate model, and secondly, the sensitivity of evaluation to the persistence of the policy are examined.; Chapter 2 presents an algorithm for the solution of a class of integrated assessment models which feature uncertainty in multiple dimensions. The algorithm combines Monte Carlo methods, randomization and approximation by regression to improve upon accuracy and stability, of previously proposed solution methods. The algorithm is applied to the solution of an integrated assessment model with a persistent random component of temperature change.; Chapter 3 presents a model of learning and climate change. A social planner uses observations on climate variables to update beliefs about the sensitivity of temperatures to carbon levels and the persistence of temperature shocks. The first part of this chapter explores the dynamics of learning when two competing hypotheses can be considered by the regulator; climate sensitivity or strong persistence can both be responsible for long periods of warming temperatures. When this tension is added to a model of learning, the time to learning increases by 1--3 orders of magnitude over a case with only 1 uncertain parameter. The second part of the Chapter embeds this learning dynamic in a growth model of climate and economy, and solves and simulates the model using the methodology proposed in Chapter 2.