Created by Derek Lemoine, University of Arizona
First version: September 2020, Updated: February 2021
Suggested citation: Lemoine, Derek. 2020. DICE-2016R-Matlab. https://github.com/dlemoine1/DICE-2016R-Matlab
These files replicate DICE-2016R in Matlab. They also extend it to use carbon and climate models recommended by Dietz et al. (2020) and to use a damage specification that builds on the expert survey in Pindyck (2019), as implemented by Lemoine (2021).
See Appendix to "Incentivizing Negative Emissions Through Carbon Shares" (Lemoine, 2020) for model equations and details: https://eller.arizona.edu/sites/default/files/Econ-WP-20-08.pdf. See Nordhaus (2017) for original DICE-2016R description.
All files should be placed in the same directory. Code will create an "output" subfolder within it.
DICE_Model_Description_from_metcalf.pdf: A description of the code courtesy of Professor Gib Metcalf (Tufts). Note that the code could have changed slightly since this was written, so the line numbers may not perfectly match the current code.
main_dice2016r.m: The code should be run from here. Options to control the climate, carbon, and damage models are provided at the top. The code has not necessarily been tested on the non-default computational options. In the default approach, solver guesses trajectories for all state variables and all non-consumption controls, imposes transition equations as constraints, and uses an analytic gradient. Outputs the user may be interested in include Welfare, abaterate, emtax_pertCO2 (in 2010 dollars), T (temperature, deg C wrt 1900), Carbon_ppm (atmospheric carbon, in ppm), and emsind (industrial emissions, Gt C). Elements of each vector correspond to elements of year vector. User may also be interested in SCC_pertCO2, which calculates marginal damage from a pulse of emissions in a given period. If Params.optimizeonlysavings=1, then this gives the social cost of carbon along the business-as-usual trajectory.
sub_parameters.m: Defines equations of the model and parameterizes the model. Some users may want to change some of these parameters. When changing equations, make sure to also change their derivatives.
sub_loadguesses.m: Loads an initial guess, defines upper and lower bounds, defines normalization for computation
utilityobjective.m: Policymaker's objective, with gradient
nonlcon_utilmax.m: The constraints of the model, with gradients
trajectory.m: Simulates the model with a given trajectory of controls
OutputResults.m: Outputs results to an Excel sheet, adapted from file kindly shared by Gib Metcalf and Ben Healy
*.opt: Options files for Knitro solver. Not needed if will use Matlab's built-in fmincon instead.
DICE2016R-091916ap.gms: Source file for DICE-2016R, from http://www.econ.yale.edu/~nordhaus/homepage/homepage/DICE2016R-091916ap.gms. Provided only for reference. Not needed to run code.
Reference List:
Dietz, Simon, Frederick van der Ploeg, Armon Rezai, and Frank Venmans. 2020. “Are Economists Getting Climate Dynamics Right and Does It Matter?” Working Paper 8122. CESIfo. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3545718.
Lemoine, Derek. 2021. “The Climate Risk Premium: How Uncertainty Affects the Social Cost of Carbon.” Journal of the Association of Environmental and Resource Economists, no. forthcoming. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2560031.
Nordhaus, William D. 2017. “Revisiting the Social Cost of Carbon.” Proceedings of the National Academy of Sciences 114 (7): 1518–23. https://doi.org/10.1073/pnas.1609244114.
Pindyck, Robert S. 2019. “The Social Cost of Carbon Revisited.” Journal of Environmental Economics and Management 94 (March): 140–60. https://doi.org/10.1016/j.jeem.2019.02.003.