This paper assesses the achievement and the limitation of our path to the stabilization of anthropogenic carbon emissions with economic growth using a stochastic Kaya model. The elasticity of carbon dioxide emissions with respect to anthropogenic drivers such as population, affluence, energy...

This paper develops a stochastic Kaya model. The elasticity of carbon dioxide emissions with respect to population, per capita GDP, energy efficiency, and fossil fuel dependence is estimated using the panel data of 132 countries from 1960 to 2010. As an application of the stochastic Kaya model,...

A recursive method for solving an integrated assessment model of climate and the economy is developed in this paper. The method approximates value function with a logarithmic basis function and searches for solutions on a set satisfying optimality conditions. These features make the method...

We construct an endogenous (Bayesian) learning model with fat-tailed uncertainty on the equilibrium climate sensitivity and solve the model with stochastic dynamic programming. In our model a decision maker updates her belief on the climate sensitivity through temperature observations each time...

Uncertainty plays a significant role in evaluating climate policy, and fattailed uncertainty may dominate policy advice. Should we make our utmost effort to prevent the arbitrarily large impacts of climate change under deep uncertainty? In order to answer to this question we propose an new way...

The effect of learning on climate policy is not straightforward when climate policy is concerned. It depends not only on the ways that climate feedbacks, preferences, and economic impacts are considered, but also on the ways that uncertainty and learning are introduced. Deep (or fat-tailed)...