DICE

State

class whynot.simulators.dice.State

State variables of the DICE simulator.

Default values are extracted from the first time step of a run of the DICE model using optimization to set the carbon price.

ABATECOST = 0.000486016

Cost of emissions reductions

C = 46.98638871

Consumption trillions US dollars

CCA = 90

Cumulative industrial carbon emissions GtC

CEMUTOTPER = 1974.226305

Period utility

CPC = 6.871364246

Per capita consumption thousands US dollars

CPRICE = 0.999999958

Carbon price (2005$ per ton of CO2)

DAMAGES = 0.108648899

Damages (trillions 2005 USD per year)

DAMFRAC = 0.0017088

Damages as fraction of gross output

E = 36.85382682

CO2-equivalent emissions GtC

FORC = 2.167363097

Radiative forcing in watts per m2

I = 16.48646319

Investment trillions US dollars

K = 135

Capital stock trillions US dollars

MAT = 830.4

Carbon concentration in atmosphere GtC

MCABATE = 0.999999958

Marginal cost of abatement (2005$ per ton CO2)

MIU = 0.038976322

Emission control rate GHGs

ML = 10010

Carbon concentration in lower oceans GtC

MU = 1527

Carbon concentration in shallow oceans GtC

PERIODU = 0.288713996

One period utility function

RI = 0.052124994

Real interest rate per annum

S = 0.259740388

Gross savings rate as fraction of gross world product

TATM = 0.8

Temperature of atmosphere in degrees C

TOCEAN = 0.0068

Temperature of lower oceans in degrees C

Y = 63.4728519

Gross world product net of abatement and damages

YGROSS = 63.58198682

Gross world product Gross of abatement and damages

YNET = 63.47333792

Output net damages equation

nonnegative_variables

Return names of all nonnegative variables.

variables

Return names of all model variables.

Config

class whynot.simulators.dice.Config

Parameter values in the DICE model.

Default values correspond to the base run of the 2013 version.

L

Level of population and labor.

a0 = 3.8

Initial level of total factor productivity

a1 = 0

Damage intercept

a2 = 0.00267

Damage quadratic term

a3 = 2

Damage exponent

al(time)

Level of total factor productivity.

b11

Carbon cycle transition matrix.

b12 = 0.088

Carbon cycle transition matrix.

b21

Carbon cycle transition matrix.

b22

Carbon cycle transition matrix.

b23 = 0.0025

Carbon cycle transition matrix.

b32

Carbon cycle transition matrix.

b33

Carbon cycle transition matrix.

c1 = 0.098

Climate equation coefficient for upper level

c3 = 0.088

Tranfer coefficient upper to lower stratum

c4 = 0.025

Transfer coefficient for lower level

cost1(time)

Cost adjusted for backstop.

cprice0 = 1

Initial base carbon price (2005$ per tCO2)

cpricebase(time)

Carbon price in base case.

dela = 0.006

Decline rate of total factor productivity (per 5 years)

deland = 0.2

Decline rate of land emissions (per period)

dk = 0.1

Depreciation rate on capital (per year)

dsig = -0.001

Decline rate of decarbonization (per period)

e0 = 33.61

Industrial emissions 2010 (GtC02 per year)

eland0 = 3.3

Carbon emissions from land 2010 (GtCO2 per year)

elasmu = 1.45

Elasticity of marginal utility of consumption.

etree(time)

Emissions from deforestation.

expcost2 = 2.8

Exponent of control cost function

fco22x = 3.8

Forcings of equilibrium CO2 doubling (Wm-2)

fex0 = 0.25

2010 forcings of non-CO2 CHG (Wm-2)

fex1 = 0.7

2100 forcings of non-CO2 CHG (Wm-2)

forcoth(time)

Exogenous forcing for other greenhouse gases.

fosslim = 6000

Maximum cumulative extraction fossil fuels (GtC)

ga(time)

Growth rate of productivity.

ga0 = 0.079

Initial growth rate for total factor productivity (per 5 years)

gama = 0.3

Capital elasticity in production function.

gback = 0.025

Initial cost decline backstop cost per period

gcprice = 0.02

Growth rate of base carbon price per year.

gsig(time)

Change in sigma (cumulative improvement of energy efficiency).

gsigma1 = -0.01

Initial growth rate of sigma (per year)

ifopt = 1

Whether or not to use optimization to set the carbon price.

k0 = 135

Initial capital value (trill 2005 USD)

lam

Climate model parameter.

limmiu = 1.2

Upper limit on control rate after 2150

mat0 = 830.4

Initial concentration in atmosphere 2010 (GtC)

mateq = 588

Equilibrium concentration atmosphere (GtC)

miu0 = 0.039

Initial emissions control rate for base case 2010

ml0 = 10010

Initial concentration in lower strata 2010 (GtC)

mleq = 10000

Equilibrium concentration in lower strata (GtC)

mu0 = 1527

Initial concentration in upper strata 2010 (GtC)

mueq = 1350

Equilibrium concentration in upper strata (GtC)

numPeriods = 60

Number of time periods to run the simulation.

optlrsav

Optimal long-run savings rate used for transversality.

partfract(time)

Fraction of emissions in control regime.

partfract2010 = 1

Fraction of emissions under control in 2010

partfractfull = 1

Fraction of emissions under control at full time

pback = 344

Cost of backstop 2005$ for tCO2 2010

pbacktime(time)

Backstop price.

periodfullpart = 21

Period at which to have full participation.

pop0 = 6838

Initial world population (millions)

popadj = 0.134

Growth rate to calibrate 2050 population projection.

popasym = 10500

Asymptotic population (millions)

prstp = 0.015

Initial rate of social time preference per year.

q0 = 63.69

Initial world gross output (trill 2005 USD)

rr(time)

Average utility social discount rate.

scale1 = 0.016408662

Multiplicative scaling coefficient

scale2 = -3855.106895

Additive scaling coefficient

sig0

Carbon intensity 2010 (kgCO2 per output 2005 USD 2010).

sigma(time)

CO2-equivalent-emissions output ratio.

t2xco2 = 2.9

Equilibrium temperature impact (oC per doubling CO2)

tatm0 = 0.8

Initial atmospheric temperature change (C from 1900)

tnopol = 45

Period before which no emissions controls base

tocean0 = 0.0068

Initial lower stratum temperature change (C from 1900)

tstep = 5

Number of year for each time period.

update(intervention)

Generate a new config object after applying the intervention.

Interventions

class whynot.simulators.dice.Intervention(**kwargs)

Encapsulate an intervention in DICE.

__init__(**kwargs)

Construct an intervention in DICE.

Currently, all interventions are performed at the first time step.

Parameters:kwargs (dict) – Only valid keyword arguments are parameters of whynot.simulators.dice.Config.

Experiments

Experiments on the DICE model.

whynot.simulators.dice.experiments.RCT = dice_rct

An RCT probing the effect of using optimal carbon prices on atmospheric temperature