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This paper studies a dynamic stochastic general equilibrium model involving climate change. Our model allows for damages on economic growth resulting from global warming. In the calibration, we capture effects from climate change and feedback effects on the temperature dynamics. We solve for the optimal state-dependent abatement policy. In our simulations, the costs of this policy measured in terms of lost GDP growth are moderate. On the other hand, postponing abatement action could reduce the probability that the climate can be stabilized. For instance, waiting for 10 years reduces this probability from 60% to 30%. Waiting for another 10 years leads to a probability that is less than 10%. Finally, doing nothing opens the risk that temperatures might explode and economic growth decreases significantly.
This paper studies the relation between firm value and a firm's growth options. We find strong empirical evidence that (average) Tobin's Q increases with firm-level volatility. However, the significance mainly comes from R&D firms, which have more growth options than non-R&D firms. By decomposing firm-level volatility into its systematic and unsystematic part, we also document that only idiosyncratic volatility (ivol) has a significant effect on valuation. Second, we analyze the relation of stock returns to realized contemporaneous idiosyncratic volatility and R&D expenses. Single sorting according to the size of idiosyncratic volatility, we only find a significant ivol anomaly for non-R&D portfolios, whereas in a four-factor model the portfolio alphas of R&D portfolios are all positive. Double sorting on idiosyncratic volatility and R&D expenses also reveals these differences between R&D and non-R&D firms. To simultaneously control for several explanatory variables, we also run panel regressions of portfolio alphas which confirm the relative importance of idiosyncratic volatility that is amplified by R&D expenses.
