Continuous time is a superior representation of both the economic and climate systems that Integrated Assessment Models (IAM) aim to study. Moreover, continuous-time representations are simple to express. Continuous-time models are usually solved by discretizing time, but the quality of a...

There is great uncertainty about the impact of anthropogenic carbon on future economic wellbeing. We use DSICE, a DSGE extension of the DICE2007 model of William Nordhaus, which incorporates beliefs about the uncertain economic impact of possible climate tipping events and uses empirically...

This paper studies the conditions under which the scarcity of a factor (in particular, labor) encourages technological progress and technology adoption. In standard endogenous growth models, which feature a strong scale effect, an increase in the supply of labor encourages technological...

The study of the bias of new technologies is important both as part of the analysis of the nature of technology adoption and the direction of technological change, and to understand the distributional implications of new technologies. In this paper, I analyze the equilibrium bias of technology....

This paper introduces endogenous and directed technical change in a growth model with environmental constraints and limited resources. A unique final good is produced by combining inputs from two sectors. One of these sectors uses "dirty" machines and thus creates environmental degradation....

This paper proposes a tractable model to study the equilibrium diversity of technological progress and shows that equilibrium technological progress may exhibit too little diversity (too much conformity), in particular, foregoing socially beneficial investments in "alternative" technologies that...

We develop a microeconomic model of endogenous growth where clean and dirty technologies compete in production and innovation—in the sense that research can be directed to either clean or dirty technologies. If dirty technologies are more advanced to start with, the potential transition to...

We study the properties of generalized stochastic gradient (GSG) learning in forward-looking models. We examine how the conditions for stability of standard stochastic gradient (SG) learning both differ from and are related to E-stability, which governs stability under least squares learning. SG...

We introduce an algorithm for solving dynamic economic models that merges stochastic simulation and projection approaches: we use simulation to approximate the ergodic measure of the solution, we construct a fixed grid covering the support of the constructed ergodic measure, and we use...

First, we propose a more efficient implementation of the Smolyak method for interpolation, namely, we show how to avoid costly evaluations of repeated basis functions in the conventional Smolyak formula. Second, we extend the Smolyak method to include anisotropic constructions; this allows us to...