 DICE Experiments: Rolling the DICE

In this lab activity, we will explore a model of our global carbon cycle attached to a simple version of Nordhaus’ DICE model as a means of exploring some of the consequences of different scenarios of emissions controls from no emissions controls to complete emissions control in the next 100 years.

The DICE model is based in large part on a model outlined in Nordhaus (1992). I’ve added a couple of things here —  a converter that calculates the relative climate costs, and reservoirs that keep track of the total damages, the total abatement costs, and the total consumption. We start at year 2000, with the carbon cycle in the state that our previous model (from Module 5) arrived at under the influence of the known history of anthropogenic changes. The carbon emissions due to land use changes remain at the year 2000 level for the rest of the time. The model is initially set to run to 2200 with a time step of 0.1.

Experiment 1: Changing the Emissions Control Rate

In the DICE model, the ECR varies from 0 to 1, and it expresses the degree to which we take steps to curb emissions; a value of 0 means we do nothing, while a value of 1 means that we essentially bring emissions to a halt. According to Nordhaus, the most efficient way of implementing this control is through some kind of carbon tax, in which case a value close to 1 represents a very hefty carbon tax that would provide strong incentives for other forms of energy. In this experiment, we’ll explore 3 scenarios — in A, we’ll keep ECR constant at the initial value of 0.005, in B we'll ramp it up to 0.5 by 2100 and 1.0 by the year 2200, and in C, we’ll ramp it up to 1 by the year 2100 and then hold it constant at 1 until the end of the model in the year 2200. You can make these changes in the ECR by altering the graphical converter. The model includes a number of useful comparative graphs that will show one model parameter for a variety of different model runs.

1. Which of these 3 scenarios leads to the lowest global temperature change?

2. Which of these 3 scenarios leads to the highest global capital?

3. Which of these 3 scenarios leads to the lowest relative climate costs?

4. Which of these 3 scenarios leads to the greatest per capita consumption?

5. Which of these 3 scenarios leads to the greatest social utility?

6.  From an economic standpoint, will we be better off controlling emissions dramatically (model C), gradually (model B), or not at all (model A)? The things to focus on here would be the social utility ending value and the per capita consumption, which is probably the best measure in the model for the quality of life.

Experiment 2: Changing the Climate Damage Calculation

The model includes something called the Damage Fraction, which is the constant in Nordhaus’ equation for calculating Climate Damages, which looks like this:

Climate Damage = Gross Output x (Damage Fract x global T change^damage exponent)

Let’s explore what happens to the system if we double this Damage Fraction constant from 0.003 to 0.006. This is motivated by some critics of Nordhaus who claim that his model underestimates the costs of climate damages; increasing this parameter will increase the climate damage costs. Run the same 3 emissions control rate scenarios (models, A,B, C from above) with this new damage fraction and compare the results

7. Does this change which of the models (A,B, or C from Experiment 1) is the best from an economic standpoint? The things to focus on here would be the social utility ending value and the per capita consumption, which is probably the best measure in the model for quality of life.