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Parameter reference

Configurable parameters

time

start

Year in which the model starts

  • Type: int

  • Default: 2025

  • Min: 1900

  • Max: 2100

Example usage: 

params = load_params()
params["time"]["start"] = 2025
model = MIMOSA(params)
end

Last year of the model run

  • Type: int

  • Default: 2150

  • Min: 1901

  • Max: 2300

Example usage: 

params = load_params()
params["time"]["end"] = 2150
model = MIMOSA(params)
dt

Initial timestep length in years

  • Type: float

  • Default: 5

  • Min: 0.5

  • Max: 20

Example usage: 

params = load_params()
params["time"]["dt"] = 5
model = MIMOSA(params)
periods

Optional timestep changes, mapping each change year to the timestep length in years used after that year

  • Type: dict

  • Default: {2050: 10}

Example usage: 

params = load_params()
params["time"]["periods"] = {2050: 10}
model = MIMOSA(params)
SSP

SSP, used for population, baseline GDP and baseline emissions

  • Type: enum

  • Default: SSP2

  • Allowed values:

    • SSP1
    • SSP2
    • SSP3
    • SSP4
    • SSP5

Example usage: 

params = load_params()
params["SSP"] = "SSP2"
model = MIMOSA(params)

economics

PRTP

Pure rate of time preference

  • Type: float

  • Default: 0.015

  • Min: 0

  • Max: 0.2

Example usage: 

params = load_params()
params["economics"]["PRTP"] = 0.015
model = MIMOSA(params)
elasmu

Elasticity of marginal utility

  • Type: float

  • Default: 1.001

  • Min: 0.1

  • Max: 10

Example usage: 

params = load_params()
params["economics"]["elasmu"] = 1.001
model = MIMOSA(params)
inequal_aversion

Parameter of inequality aversion. Should be between 0 and elasmu. Only used when model structure - welfare module is inequal_aversion_general

  • Type: float

  • Default: 0.5

  • Min: 0.0

  • Max: 3

Example usage: 

params = load_params()
params["economics"]["inequal_aversion"] = 0.5
model = MIMOSA(params)

economics > GDP

alpha

Output elasticity of capital

  • Type: float

  • Default: 0.3

  • Min: 0

  • Max: 1

Example usage: 

params = load_params()
params["economics"]["GDP"]["alpha"] = 0.3
model = MIMOSA(params)
depreciation of capital

Yearly depreciation rate of capital stock

  • Type: float

  • Default: 0.05

  • Min: 0

  • Max: inf

Example usage: 

params = load_params()
params["economics"]["GDP"]["depreciation of capital"] = 0.05
model = MIMOSA(params)
savings rate

Fraction of GDP used for investments

  • Type: float

  • Default: 0.21

  • Min: 0

  • Max: 1

Example usage: 

params = load_params()
params["economics"]["GDP"]["savings rate"] = 0.21
model = MIMOSA(params)

economics > MAC

beta

Power factor of the MAC curve

  • Type: float

  • Default: 3

  • Min: 0.01

  • Max: 10

Example usage: 

params = load_params()
params["economics"]["MAC"]["beta"] = 3
model = MIMOSA(params)
gamma

Calibration level of the MAC (carbon price for 100% reduction)

  • Type: quantity

  • Default: 2887 USD2010/tCO2

  • Unit: currency_unit/emissionsrate_unit

Example usage: 

params = load_params()
params["economics"]["MAC"]["gamma"] = "2887 USD2010/tCO2"
model = MIMOSA(params)
LBD_rate

Learning by doing rate: reduction in marginal mitigation costs for doubling cumulative mitigation capacity. Empirical studies show values between 0.65 (high learning) and 0.95 (low learning)

  • Type: float

  • Default: 0.82

  • Min: 0.1

  • Max: 1

Example usage: 

params = load_params()
params["economics"]["MAC"]["LBD_rate"] = 0.82
model = MIMOSA(params)
LBD_scaling

Scaling factor for learning by doing to transform the units of cumulative mitigation in relative terms (compared to baseline emissions in t=0). Only used for calibration, and should not be used to change the amount of LBD (for this, use economics > MAC > LBD_rate)

  • Type: quantity

  • Default: 40 GtCO2

  • Unit: emissions_unit

Example usage: 

params = load_params()
params["economics"]["MAC"]["LBD_scaling"] = "40 GtCO2"
model = MIMOSA(params)
LOT_rate

Learning rate of exogenous learning (learning over time). By default, there is no exogenous learning assumed, as all the technological learning happens endogenously (learning by doing).

  • Type: float

  • Default: 0

  • Min: 0

  • Max: inf

Example usage: 

params = load_params()
params["economics"]["MAC"]["LOT_rate"] = 0
model = MIMOSA(params)
regional calibration factor

Column from mac.csv to be used for the regional MACs. The MACs are calibrated from TIMER SSP2-RCP2.6 MACs at a given year and a given carbon price / abatement level.

  • Type: enum

  • Default: kappa_rel_abatement_0.75_2050

  • Allowed values:

    • kappa_carbonprice_200_2030
    • kappa_carbonprice_200_2050
    • kappa_carbonprice_200_2070
    • kappa_carbonprice_200_2100
    • kappa_carbonprice_300_2030
    • kappa_carbonprice_300_2050
    • kappa_carbonprice_300_2070
    • kappa_carbonprice_300_2100
    • kappa_carbonprice_500_2030
    • kappa_carbonprice_500_2050
    • kappa_carbonprice_500_2070
    • kappa_carbonprice_500_2100
    • kappa_carbonprice_1000_2030
    • kappa_carbonprice_1000_2050
    • kappa_carbonprice_1000_2070
    • kappa_carbonprice_1000_2100
    • kappa_rel_abatement_0.25_2030
    • kappa_rel_abatement_0.25_2050
    • kappa_rel_abatement_0.25_2070
    • kappa_rel_abatement_0.25_2100
    • kappa_rel_abatement_0.4_2030
    • kappa_rel_abatement_0.4_2050
    • kappa_rel_abatement_0.4_2070
    • kappa_rel_abatement_0.4_2100
    • kappa_rel_abatement_0.5_2050
    • kappa_rel_abatement_0.5_2070
    • kappa_rel_abatement_0.5_2100
    • kappa_rel_abatement_0.75_2050
    • kappa_rel_abatement_0.75_2070
    • kappa_rel_abatement_0.75_2100

Example usage: 

params = load_params()
params["economics"]["MAC"]["regional calibration factor"] = "kappa_rel_abatement_0.75_2050"
model = MIMOSA(params)
economics > MAC > SSP_calibration_factor
SSP2

Dictionary of year-value pairs giving time dependent multiplication factor of the SSP2 MAC. Linear interpolation is taken in between keyframes. Used for time-dependent changes between SSPs.

  • Type: dict

  • Default: {2020: 1}

Example usage: 

params = load_params()
params["economics"]["MAC"]["SSP_calibration_factor"]["SSP2"] = {2020: 1}
model = MIMOSA(params)
SSP1

Dictionary of year-value pairs giving time dependent multiplication factor of the SSP2 MAC. Linear interpolation is taken in between keyframes. Used for time-dependent changes between SSPs.

  • Type: dict

  • Default: {2020: 1, 2100: 0.618}

Example usage: 

params = load_params()
params["economics"]["MAC"]["SSP_calibration_factor"]["SSP1"] = {2020: 1, 2100: 0.618}
model = MIMOSA(params)
SSP3

Dictionary of year-value pairs giving time dependent multiplication factor of the SSP2 MAC. Linear interpolation is taken in between keyframes. Used for time-dependent changes between SSPs.

  • Type: dict

  • Default: {2020: 1, 2050: 1.265, 2100: 1.3184}

Example usage: 

params = load_params()
params["economics"]["MAC"]["SSP_calibration_factor"]["SSP3"] = {2020: 1, 2050: 1.265, 2100: 1.3184}
model = MIMOSA(params)
SSP4

Dictionary of year-value pairs giving time dependent multiplication factor of the SSP2 MAC. Linear interpolation is taken in between keyframes. Used for time-dependent changes between SSPs.

  • Type: dict

  • Default: {2020: 1}

Example usage: 

params = load_params()
params["economics"]["MAC"]["SSP_calibration_factor"]["SSP4"] = {2020: 1}
model = MIMOSA(params)
SSP5

Dictionary of year-value pairs giving time dependent multiplication factor of the SSP2 MAC. Linear interpolation is taken in between keyframes. Used for time-dependent changes between SSPs.

  • Type: dict

  • Default: {2020: 1, 2030: 1.0724, 2040: 1.16, 2050: 1.17, 2100: 1.198}

Example usage: 

params = load_params()
params["economics"]["MAC"]["SSP_calibration_factor"]["SSP5"] = {2020: 1, 2030: 1.0724, 2040: 1.16, 2050: 1.17, 2100: 1.198}
model = MIMOSA(params)
rel_mitigation_costs_min_level

Minimum level of mitigation costs (rel to GDP). By default, this is 0: no negative attributed mitigation costs are allowed. For certain effort-sharing regimes, this value can become negative to allow certain (small) financial transfers.

  • Type: float

  • Default: 0

  • Min: -2

  • Max: 0

Example usage: 

params = load_params()
params["economics"]["MAC"]["rel_mitigation_costs_min_level"] = 0
model = MIMOSA(params)

economics > emission trade

min rel payment level

Which percentage of the area under the MAC of a region should it pay itself (minimum)? If false: no limt

  • Type: float

  • Default: False

  • Can be false: yes

  • Min: 0

  • Max: 1

Example usage: 

params = load_params()
params["economics"]["emission trade"]["min rel payment level"] = False
model = MIMOSA(params)
max rel payment level

Which percentage of the area under the MAC of a region should it pay itself (maximum)? If false: no limit

  • Type: float

  • Default: False

  • Can be false: yes

  • Min: 1

  • Max: inf

Example usage: 

params = load_params()
params["economics"]["emission trade"]["max rel payment level"] = False
model = MIMOSA(params)

economics > damages

percentage reversible

Factor of damages that are reversible

  • Type: float

  • Default: 1

  • Min: 0

  • Max: 1

Example usage: 

params = load_params()
params["economics"]["damages"]["percentage reversible"] = 1
model = MIMOSA(params)
scale factor

Manual scaling factor to increase or decrease damages

  • Type: float

  • Default: 1

  • Min: -inf

  • Max: inf

Example usage: 

params = load_params()
params["economics"]["damages"]["scale factor"] = 1
model = MIMOSA(params)
ignore damages

Flag to not take into account the damages in the GDP (but damages are calculated)

  • Type: bool

  • Default: False

Example usage: 

params = load_params()
params["economics"]["damages"]["ignore damages"] = False
model = MIMOSA(params)
quantile

Damage quantile (Only used for COACCH)

  • Type: enum

  • Default: 0.5

  • Allowed values:

    • 0.025
    • 0.05
    • 0.16
    • 0.25
    • 0.33
    • 0.5
    • 0.67
    • 0.75
    • 0.84
    • 0.95
    • 0.975

Example usage: 

params = load_params()
params["economics"]["damages"]["quantile"] = 0.5
model = MIMOSA(params)
coacch_slr_withadapt

Flag to use the SLR-with-Adapation damage functions (Only used for COACCH)

  • Type: bool

  • Default: True

Example usage: 

params = load_params()
params["economics"]["damages"]["coacch_slr_withadapt"] = True
model = MIMOSA(params)
coacch_combined_slr_nonslr_damages

If true, do not model SLR damages separately from non-SLR, but use the combined damage functions (Only used for COACCH)

  • Type: bool

  • Default: False

Example usage: 

params = load_params()
params["economics"]["damages"]["coacch_combined_slr_nonslr_damages"] = False
model = MIMOSA(params)
economics > damages > accreu
adaptation

Enable sector-specific adaptation with "sectoral", disable it with "noadaptation", or use "combined" labour productivity and riverine flooding adaptation for diagnostics and model comparisons.

  • Type: enum

  • Default: noadaptation

  • Allowed values:

    • sectoral
    • combined
    • noadaptation

Example usage: 

params = load_params()
params["economics"]["damages"]["accreu"]["adaptation"] = "noadaptation"
model = MIMOSA(params)
cba_strategy

How solve() coordinates mitigation and adaptation in an ACCREU cost-benefit analysis. The sequential strategy first optimises mitigation without adaptation and then calculates analytical optimal adaptation for that pathway. The joint strategy uses the ordinary one-model solve path, with adaptation either chosen by the solver or determined analytically.

  • Type: enum

  • Default: mitigation_then_adaptation

  • Allowed values:

    • mitigation_then_adaptation
    • joint

Example usage: 

params = load_params()
params["economics"]["damages"]["accreu"]["cba_strategy"] = "mitigation_then_adaptation"
model = MIMOSA(params)
adaptation_determination

How ACCREU adaptation expenditure is determined. With solver_control it is a free optimisation or simulation control. With analytical_optimum it is calculated from the analytical optimal-adaptation equation.

  • Type: enum

  • Default: analytical_optimum

  • Allowed values:

    • solver_control
    • analytical_optimum

Example usage: 

params = load_params()
params["economics"]["damages"]["accreu"]["adaptation_determination"] = "analytical_optimum"
model = MIMOSA(params)
adaptation_calibration

Calibration of the sectoral ACCREU adaptation curves. "accreu" uses the original source-model coefficients. The three "literature" options use realised-effectiveness caps and cost multipliers calibrated to the low, central, and high ends of literature benefit-cost ranges at a 5% discount rate. They apply to both separate and combined adaptation.

  • Type: enum

  • Default: accreu

  • Allowed values:

    • accreu
    • literature_low
    • literature
    • literature_high

Example usage: 

params = load_params()
params["economics"]["damages"]["accreu"]["adaptation_calibration"] = "accreu"
model = MIMOSA(params)
monetise_mortality

Flag for whether the mortality should be monetised using the SVL (Statistical Value of Life)

  • Type: bool

  • Default: True

Example usage: 

params = load_params()
params["economics"]["damages"]["accreu"]["monetise_mortality"] = True
model = MIMOSA(params)
mortality_vsl_rel_gdp_cap

If the monetise_mortality option is enabled, use this value for the Statistical Value of Life (SVL), expressed as multiple of GDP per capita. Note: while this assumes a global value of the SVL in relative terms, the dollar value of the SVL differs per country. This has ethical implications.

  • Type: float

  • Default: 117.59

  • Min: -inf

  • Max: inf

Example usage: 

params = load_params()
params["economics"]["damages"]["accreu"]["mortality_vsl_rel_gdp_cap"] = 117.59
model = MIMOSA(params)
adaptation_effectiveness_scale_factor

Scales the max. effectiveness factor for the sectoral adaptation. Used to analyse the effects of a less effective adaptation.

  • Type: float

  • Default: 1

  • Min: 0

  • Max: 1

Example usage: 

params = load_params()
params["economics"]["damages"]["accreu"]["adaptation_effectiveness_scale_factor"] = 1
model = MIMOSA(params)
delay_adaptation_until_year

Delays adaptation until after this given year. If false, no constraint on adaptation is set.

  • Type: int

  • Default: False

  • Can be false: yes

  • Min: 2030

  • Max: inf

Example usage: 

params = load_params()
params["economics"]["damages"]["accreu"]["delay_adaptation_until_year"] = False
model = MIMOSA(params)

emissions

emissions > pulse

year

Year in which an exogenous CO2 pulse is released

  • Type: int

  • Default: 2025

  • Min: 1900

  • Max: 2300

Example usage: 

params = load_params()
params["emissions"]["pulse"]["year"] = 2025
model = MIMOSA(params)
amount

Exogenous CO2 pulse added directly to cumulative emissions

  • Type: quantity

  • Default: 0 GtCO2

  • Unit: emissions_unit

Example usage: 

params = load_params()
params["emissions"]["pulse"]["amount"] = "0 GtCO2"
model = MIMOSA(params)
carbonbudget

Value of the carbon budget. Example: "800 GtCO2" (the unit is important). If set to False, no carbon budget is imposed: this is cost-benefit mode. Default: False.

  • Type: quantity

  • Default: False

  • Can be false: yes

  • Unit: emissions_unit

Example usage: 

params = load_params()
params["emissions"]["carbonbudget"] = False
model = MIMOSA(params)
global min level

Limit on the emission level (globally), mostly used for negative emissions. Can also be false, then no limit is imposed

  • Type: quantity

  • Default: -20 GtCO2/yr

  • Can be false: yes

  • Unit: emissionsrate_unit

Example usage: 

params = load_params()
params["emissions"]["global min level"] = "-20 GtCO2/yr"
model = MIMOSA(params)
regional min level

Limit on the emission level (per region), mostly used for negative emissions. Can also be false, then no limit is imposed

  • Type: quantity

  • Default: -10 GtCO2/yr

  • Can be false: yes

  • Unit: emissionsrate_unit

Example usage: 

params = load_params()
params["emissions"]["regional min level"] = "-10 GtCO2/yr"
model = MIMOSA(params)
not positive after budget year

If true, impose net-zero emissions after budget year (2100)

  • Type: bool

  • Default: True

Example usage: 

params = load_params()
params["emissions"]["not positive after budget year"] = True
model = MIMOSA(params)
non increasing emissions after 2100

If true, the regional emissions after 2100 are not allowed to climb.

  • Type: bool

  • Default: True

Example usage: 

params = load_params()
params["emissions"]["non increasing emissions after 2100"] = True
model = MIMOSA(params)
baseline carbon intensity

If true, use baseline carbon intensity to calculate baseline emissions. If false, the SSP baseline emissions are used, regardless of lower GDP.

  • Type: bool

  • Default: True

Example usage: 

params = load_params()
params["emissions"]["baseline carbon intensity"] = True
model = MIMOSA(params)

emissions > inertia

global

Maximum reduction speed, in % of initial emissions (should be negative) Can also be false, then no inertia limit is imposed

  • Type: float

  • Default: False

  • Can be false: yes

  • Min: -inf

  • Max: 0

Example usage: 

params = load_params()
params["emissions"]["inertia"]["global"] = False
model = MIMOSA(params)
regional

Maximum reduction speed, in % of initial emissions (should be negative) Can also be false, then no inertia limit is imposed

  • Type: float

  • Default: -0.05

  • Can be false: yes

  • Min: -inf

  • Max: 0

Example usage: 

params = load_params()
params["emissions"]["inertia"]["regional"] = -0.05
model = MIMOSA(params)
cumulative_emissions_trapz

If true, calculate cumulative emissions using trapezoidal interpolation. If false, cum. emissions are simply cum_emissions[t-1] + dt * cum_emissions[t]. This is less accurate, but better for numerical stability. For small dt the approximation is usually still acceptable.

  • Type: bool

  • Default: True

Example usage: 

params = load_params()
params["emissions"]["cumulative_emissions_trapz"] = True
model = MIMOSA(params)
delay_mitigation_until_year

Delays mitigation until after this given year. If false, mitigation is always available.

  • Type: int

  • Default: False

  • Can be false: yes

  • Min: 2030

  • Max: inf

Example usage: 

params = load_params()
params["emissions"]["delay_mitigation_until_year"] = False
model = MIMOSA(params)

effort sharing

percapconv_year

Year of convergence to per capita emission allowance (only used when model structure - effortsharing module is per_cap_convergence) Can also be false, then always use grandfathering

  • Type: float

  • Default: 2050

  • Can be false: yes

  • Min: 2020

  • Max: 2200

Example usage: 

params = load_params()
params["effort sharing"]["percapconv_year"] = 2050
model = MIMOSA(params)
ecpc_discount_rate

Discount rate for historical debt in the ECPC effort sharing regime (Equal Cumulative Per Capita regime). Only used when model structure - effortsharing module is equal_cumulative_per_cap

  • Type: float

  • Default: 0.03

  • Min: 0

  • Max: 1

Example usage: 

params = load_params()
params["effort sharing"]["ecpc_discount_rate"] = 0.03
model = MIMOSA(params)
ecpc_start_year

Start year for historical debt in the ECPC effort sharing regime (Equal Cumulative Per Capita regime). Only used when model structure - effortsharing module is equal_cumulative_per_cap

  • Type: float

  • Default: 1850

  • Min: 1800

  • Max: 2019

Example usage: 

params = load_params()
params["effort sharing"]["ecpc_start_year"] = 1850
model = MIMOSA(params)
ecpc_repayment_endyear

Year at which the repayment of the historical emission debt should be finished in the ECPC effort sharing regime. Before this year, the debt repayment is lowered linearly.

Can also be false: then the historical debt repayment is spread out equally over every time period.

- Type: float

- Default: 2050

- Can be false: yes



- Min: 2030

- Max: 2150



Example usage:


```python hl_lines="2"
params = load_params()
params["effort sharing"]["ecpc_repayment_endyear"] = 2050
model = MIMOSA(params)
```

temperature

initial

Temperature in initial year of model run (2025 by default).

  • Type: quantity

  • Default: 1.27 delta_degC

  • Unit: temperature_unit

Example usage: 

params = load_params()
params["temperature"]["initial"] = "1.27 delta_degC"
model = MIMOSA(params)
TCRE

Transient Climate Response to CO2 Emissions

  • Type: quantity

  • Default: 0.62 delta_degC/(TtCO2)

  • Unit: (temperature_unit)/(emissions_unit)

Example usage: 

params = load_params()
params["temperature"]["TCRE"] = "0.62 delta_degC/(TtCO2)"
model = MIMOSA(params)
target

Temperature target in 2100 (and beyond). Can also be false, then no temperature target is imposed

  • Type: quantity

  • Default: False

  • Can be false: yes

  • Unit: temperature_unit

Example usage: 

params = load_params()
params["temperature"]["target"] = False
model = MIMOSA(params)

sealevelrise

projection

Deterministic sea-level-rise parameter set. The central set represents an AR6-calibrated central response; low represents the lower part of the AR6 likely range, and high is a low-likelihood, high-impact sensitivity case. All sets share the same historical initial conditions.

  • Type: enum

  • Default: central

  • Allowed values:

    • low
    • central
    • high

Example usage: 

params = load_params()
params["sealevelrise"]["projection"] = "central"
model = MIMOSA(params)

model structure

damage module

Damage module to be used

  • Type: enum

  • Default: COACCH

  • Allowed values:

    • COACCH
    • ACCREU
    • ACCREU_CGE
    • nodamage

Example usage: 

params = load_params()
params["model structure"]["damage module"] = "COACCH"
model = MIMOSA(params)
emissiontrade module

Emission trade module to be used

  • Type: enum

  • Default: notrade

  • Allowed values:

    • notrade
    • emissiontrade
    • globalcostpool

Example usage: 

params = load_params()
params["model structure"]["emissiontrade module"] = "notrade"
model = MIMOSA(params)
financialtransfer module

Financial transfer module to be used

  • Type: enum

  • Default: notransfer

  • Allowed values:

    • notransfer
    • globaldamagepool

Example usage: 

params = load_params()
params["model structure"]["financialtransfer module"] = "notransfer"
model = MIMOSA(params)
effortsharing module

Type of effort sharing to be used

  • Type: enum

  • Default: noregime

  • Allowed values:

    • noregime
    • equal_mitigation_costs
    • equal_total_costs
    • per_cap_convergence
    • ability_to_pay
    • equal_cumulative_per_cap

Example usage: 

params = load_params()
params["model structure"]["effortsharing module"] = "noregime"
model = MIMOSA(params)
welfare module

Welfare and utility module to be used

  • Type: enum

  • Default: welfare_loss_minimising

  • Allowed values:

    • welfare_loss_minimising
    • cost_minimising
    • inequal_aversion_general

Example usage: 

params = load_params()
params["model structure"]["welfare module"] = "welfare_loss_minimising"
model = MIMOSA(params)
objective module

Objective module to be used

  • Type: enum

  • Default: utility

  • Allowed values:

    • utility
    • globalcosts

Example usage: 

params = load_params()
params["model structure"]["objective module"] = "utility"
model = MIMOSA(params)
regionstype

Name of the region definition. Used in the mapping of the regional parameters.

  • Type: enum

  • Default: IMAGE26

  • Allowed values:

    • IMAGE26
    • SSP5
    • World

Example usage: 

params = load_params()
params["regionstype"] = "IMAGE26"
model = MIMOSA(params)
regionsmappings

List of region types and their conversion tables. Only used for regional parameters, not for aggregating or disaggregating variables or other output.

  • Type: list

  • Default: [{'regionstype1': 'IMAGE26', 'regionstype2': 'COACCH', 'conversiontable': 'inputdata/regions/IMAGE26_COACCH.csv'}, {'regionstype1': 'IMAGE26', 'regionstype2': 'ADRICE2010', 'conversiontable': 'inputdata/regions/IMAGE26_ADRICE2010.csv'}, {'regionstype1': 'IMAGE26', 'regionstype2': 'ADRICE2012', 'conversiontable': 'inputdata/regions/IMAGE26_ADRICE2012.csv'}]

Example usage: 

params = load_params()
params["regionsmappings"] = [{'regionstype1': 'IMAGE26', 'regionstype2': 'COACCH', 'conversiontable': 'inputdata/regions/IMAGE26_COACCH.csv'}, {'regionstype1': 'IMAGE26', 'regionstype2': 'ADRICE2010', 'conversiontable': 'inputdata/regions/IMAGE26_ADRICE2010.csv'}, {'regionstype1': 'IMAGE26', 'regionstype2': 'ADRICE2012', 'conversiontable': 'inputdata/regions/IMAGE26_ADRICE2012.csv'}]
model = MIMOSA(params)
regional_parameter_files

Dictionary of regional parameter files. If the regionstype of the file is different from the regionstype of the model, the file is converted using the regionsmappings parameter.

  • Type: dict

  • Default: {'economics': {'filename': 'inputdata/regionalparams/economics.csv', 'regionstype': 'IMAGE26'}, 'MAC': {'filename': 'inputdata/regionalparams/mac.csv', 'regionstype': 'IMAGE26'}, 'COACCH': {'filename': 'inputdata/regionalparams/COACCH.csv', 'regionstype': 'COACCH'}, 'ACCREU': {'filename': 'inputdata/regionalparams/ACCREU.csv', 'regionstype': 'IMAGE26'}, 'ACCREU_CGE': {'filename': 'inputdata/regionalparams/ACCREU_CGE.csv', 'regionstype': 'IMAGE26'}}

Example usage: 

params = load_params()
params["regional_parameter_files"] = {'economics': {'filename': 'inputdata/regionalparams/economics.csv', 'regionstype': 'IMAGE26'}, 'MAC': {'filename': 'inputdata/regionalparams/mac.csv', 'regionstype': 'IMAGE26'}, 'COACCH': {'filename': 'inputdata/regionalparams/COACCH.csv', 'regionstype': 'COACCH'}, 'ACCREU': {'filename': 'inputdata/regionalparams/ACCREU.csv', 'regionstype': 'IMAGE26'}, 'ACCREU_CGE': {'filename': 'inputdata/regionalparams/ACCREU_CGE.csv', 'regionstype': 'IMAGE26'}}
model = MIMOSA(params)
regions

Dictionary of all regions with optional dictionaries defining, optionally, manual values for certain parameters for that specific region.

  • Type: dict

  • Default: {'CAN': None, 'USA': None, 'MEX': None, 'RCAM': None, 'BRA': None, 'RSAM': None, 'NAF': None, 'WAF': None, 'EAF': None, 'SAF': None, 'WEU': None, 'CEU': None, 'TUR': None, 'UKR': None, 'STAN': None, 'RUS': None, 'ME': None, 'INDIA': None, 'KOR': None, 'CHN': None, 'SEAS': None, 'INDO': None, 'JAP': None, 'OCE': None, 'RSAS': None, 'RSAF': None}

Example usage: 

params = load_params()
params["regions"] = {'CAN': None, 'USA': None, 'MEX': None, 'RCAM': None, 'BRA': None, 'RSAM': None, 'NAF': None, 'WAF': None, 'EAF': None, 'SAF': None, 'WEU': None, 'CEU': None, 'TUR': None, 'UKR': None, 'STAN': None, 'RUS': None, 'ME': None, 'INDIA': None, 'KOR': None, 'CHN': None, 'SEAS': None, 'INDO': None, 'JAP': None, 'OCE': None, 'RSAS': None, 'RSAF': None}
model = MIMOSA(params)

input

input > variables

GDP

Data source of GDP

  • Type: datasource

  • Default: {'variable': 'GDP|PPP', 'unit': 'currency_unit', 'scenario': '{SSP}-Baseline', 'model': 'IMAGE 3.4', 'file': 'inputdata/data/data_IMAGE_SSP_updated.csv'}

Example usage: 

params = load_params()
params["input"]["variables"]["GDP"] = {'variable': 'GDP|PPP', 'unit': 'currency_unit', 'scenario': '{SSP}-Baseline', 'model': 'IMAGE 3.4', 'file': 'inputdata/data/data_IMAGE_SSP_updated.csv'}
model = MIMOSA(params)
emissions

Data source of baseline emissions

  • Type: datasource

  • Default: {'variable': 'Emissions|CO2', 'unit': 'emissionsrate_unit', 'scenario': '{SSP}-Baseline', 'model': 'IMAGE 3.4', 'file': 'inputdata/data/data_IMAGE_SSP_updated.csv'}

Example usage: 

params = load_params()
params["input"]["variables"]["emissions"] = {'variable': 'Emissions|CO2', 'unit': 'emissionsrate_unit', 'scenario': '{SSP}-Baseline', 'model': 'IMAGE 3.4', 'file': 'inputdata/data/data_IMAGE_SSP_updated.csv'}
model = MIMOSA(params)
population

Data source of population

  • Type: datasource

  • Default: {'variable': 'Population', 'unit': 'population_unit', 'scenario': '{SSP}-Baseline', 'model': 'IMAGE 3.4', 'file': 'inputdata/data/data_IMAGE_SSP_updated.csv'}

Example usage: 

params = load_params()
params["input"]["variables"]["population"] = {'variable': 'Population', 'unit': 'population_unit', 'scenario': '{SSP}-Baseline', 'model': 'IMAGE 3.4', 'file': 'inputdata/data/data_IMAGE_SSP_updated.csv'}
model = MIMOSA(params)

custom_constraints

constraint_variables

Dictionary of variable names with associated path to file containing values for that variable

  • Type: dict

  • Default: None

Example usage: 

params = load_params()
params["custom_constraints"]["constraint_variables"] = None
model = MIMOSA(params)
disabled_constraints

List of constraint names to be disabled

  • Type: list

  • Default: None

Example usage: 

params = load_params()
params["custom_constraints"]["disabled_constraints"] = None
model = MIMOSA(params)

Time- and region-dependent parameters

TFP

Description not provided.

  • Units: dimensionless
  • Scenario: SSP2
baseline_GDP

Data source of GDP

  • Units: usd*trillion/yr
  • Scenario: SSP2
  • Source: IMAGE 3.4, GDP|PPP
  • Data file: inputdata/data/data_IMAGE_SSP_updated.csv
baseline_carbon_intensity

Description not provided.

  • Units: GtCO2/usd/trillion
  • Scenario: SSP2
cumulative_baseline_emissions

Description not provided.

  • Units: GtCO2
  • Scenario: SSP2
effortsharing_ecpc_annual_debt_repayment

Description not provided.

  • Units: GtCO2/yr
  • Scenario: SSP2

Available when:

params = load_params()
params['model structure']['effortsharing module'] = 'equal_cumulative_per_cap'
model = MIMOSA(params)
effortsharing_ecpc_historical_debt

Description not provided.

  • Units: GtCO2
  • Scenario: SSP2

Available when:

params = load_params()
params['model structure']['effortsharing module'] = 'equal_cumulative_per_cap'
model = MIMOSA(params)
percapconv_share

Description not provided.

  • Units: dimensionless
  • Scenario: SSP2

Available when:

params = load_params()
params['model structure']['effortsharing module'] = 'per_cap_convergence'
model = MIMOSA(params)
percapconv_share_pop

Description not provided.

  • Units: dimensionless
  • Scenario: SSP2

Available when:

params = load_params()
params['model structure']['effortsharing module'] = 'equal_cumulative_per_cap'
model = MIMOSA(params)

or

params = load_params()
params['model structure']['effortsharing module'] = 'per_cap_convergence'
model = MIMOSA(params)
population

Data source of population

  • Units: billion*people
  • Scenario: SSP2
  • Source: IMAGE 3.4, Population
  • Data file: inputdata/data/data_IMAGE_SSP_updated.csv
ssp_baseline_emissions

Data source of baseline emissions

  • Units: GtCO2/yr
  • Scenario: SSP2
  • Source: IMAGE 3.4, Emissions|CO2
  • Data file: inputdata/data/data_IMAGE_SSP_updated.csv

Regional parameters

economics

init_capital_factor

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.992 2.035 1.893 1.041 1.973 2.005 1.798 1.416 1.66 2.054 1.942 1.665 1.533 2.095 1.281 1.509 2.026 1.859 2.434 2.175 2.376 1.714 2.627 2.176 1.745 2.317
gdp_ppp_2010_div_gdp_mer_2010

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.998448 1 1.52913 1.89286 1.794 2.07975 2.42307 2.18646 2.62505 1.64231 0.891558 1.76475 1.55312 2.97402 2.64189 2.23634 1.88972 3.00643 1.29813 2.29921 2.36615 2.46135 0.850763 0.945245 3.0033 2.15323

MAC

kappa_carbonprice_1000_2030

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.914 1.138 0.862 0.924 0.326 0.468 1.225 0.685 0.305 0.769 1.474 1.531 1.275 1.046 1.569 1.103 1.315 0.815 1.501 1.299 0.888 1.193 1.551 0.295 0.924 0.21
kappa_carbonprice_1000_2050

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.956 0.945 0.642 1.085 0.352 0.512 1.821 0.675 0.65 0.842 1.447 1.349 1.48 1.17 1.827 1.615 1.38 1.101 1.089 1.068 1.008 1.082 0.868 0.32 1.063 1.181
kappa_carbonprice_1000_2070

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.821 0.817 0.497 1.583 0.4 0.506 1.661 0.716 0.492 0.731 1.541 1.526 1.782 0.971 1.534 1.633 1.316 1.374 1.386 1.115 1.065 1.04 0.829 0.151 1.432 0.542
kappa_carbonprice_1000_2100

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.563 1.134 0.621 1.796 0.179 0.476 1.415 0.981 0.638 0.527 1.951 1.825 2.395 1.035 0.731 1.705 0.862 1.256 2.247 0.87 1.764 1.382 1.078 0.199 1.183 0.574
kappa_carbonprice_2000_2030

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.813 1.014 0.804 0.902 0.315 0.46 1.216 0.813 0.372 0.814 1.299 1.519 1.215 1.054 1.41 1.096 1.219 0.868 1.657 1.346 0.801 1.217 1.668 0.325 0.828 0.255
kappa_carbonprice_2000_2050

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.862 0.889 0.596 1.052 0.364 0.52 1.582 0.726 0.642 0.896 1.303 1.361 1.364 1.154 1.611 1.674 1.288 1.168 1.049 1.153 0.97 1.108 0.797 0.269 0.955 1.061
kappa_carbonprice_2000_2070

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.813 0.731 0.514 1.359 0.359 0.505 1.667 0.755 0.514 0.727 1.462 1.266 1.985 1.005 1.426 1.555 1.401 1.424 1.189 1.219 1.078 1.016 0.927 0.118 1.377 0.543
kappa_carbonprice_2000_2100

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.863 0.896 0.462 1.663 0.161 0.436 1.71 1.044 0.652 0.567 1.65 1.486 2.507 0.794 0.749 1.55 1.063 1.507 2.095 0.979 1.838 1.018 1.08 0.139 1.436 0.439
kappa_carbonprice_200_2030

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.691 3.339 1.035 1.406 0.196 0.28 1.555 0.361 0.84 0.634 2.023 2.22 1.181 1.193 1.376 1.207 0.944 0.736 1.328 1.053 1.503 1.315 2.034 1.127 1.163 0.335
kappa_carbonprice_200_2050

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.611 1.591 0.973 1.29 0.177 0.275 3.456 0.563 2.143 0.591 1.501 1.735 1.848 1.059 3.85 2.722 2.01 0.971 1.075 0.845 1.262 1.123 1.045 0.758 1.349 0.975
kappa_carbonprice_200_2070

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.368 1.442 0.735 0.958 0.202 0.312 2.352 0.58 0.846 0.544 1.59 1.346 1.871 0.678 2.13 3.434 2.504 0.947 0.941 1.244 0.995 1.706 0.879 0.354 1.167 0.369
kappa_carbonprice_200_2100

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.232 1.834 0.686 0.81 0.14 0.666 1.46 0.864 0.785 0.581 3.336 1.119 1.092 0.529 0.996 1.675 2.065 0.883 1.559 0.972 1.071 2.085 1.016 0.336 0.849 0.621
kappa_carbonprice_300_2030

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.919 2.904 1.189 0.91 0.196 0.256 1.692 0.353 0.243 0.598 2.123 1.95 1.289 1.27 1.528 1.255 1.135 0.767 1.384 1.192 1.415 1.158 2.043 0.383 1.2 0.235
kappa_carbonprice_300_2050

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.696 1.417 0.916 1.316 0.234 0.296 3.354 0.525 1.32 0.669 1.615 1.476 1.805 1.141 3.685 2.219 1.985 0.994 1.141 0.848 1.249 1.033 1.092 0.501 1.322 1.344
kappa_carbonprice_300_2070

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.501 1.454 0.678 1.11 0.244 0.326 2.245 0.623 0.747 0.625 1.485 1.373 1.922 0.771 2.006 2.601 2.09 1.012 1.118 1.057 0.997 1.481 0.911 0.405 1.141 0.502
kappa_carbonprice_300_2100

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.512 1.895 0.635 0.897 0.16 0.605 1.443 0.843 0.825 0.607 2.977 1.348 1.207 0.597 1.011 1.663 1.773 0.9 1.883 0.846 1.065 2.17 1.063 0.414 0.882 0.692
kappa_carbonprice_4000_2030

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.81 0.959 0.804 0.897 0.366 0.483 1.131 0.932 0.392 0.796 1.189 1.574 1.161 1.141 1.297 1.141 1.114 0.891 1.697 1.343 0.825 1.183 1.679 0.276 0.695 0.297
kappa_carbonprice_4000_2050

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.913 0.933 0.621 1.092 0.378 0.528 1.447 0.714 0.633 0.914 1.282 1.341 1.205 1.119 1.535 1.579 1.221 1.197 0.985 1.149 0.954 1.176 0.715 0.264 0.934 1.051
kappa_carbonprice_4000_2070

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.824 0.722 0.473 1.346 0.382 0.495 1.669 0.715 0.506 0.773 1.402 1.289 1.974 1.016 1.475 1.515 1.496 1.458 1.155 1.235 1.113 1.095 0.796 0.102 1.356 0.509
kappa_carbonprice_4000_2100

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.884 0.823 0.468 1.291 0.171 0.473 1.548 0.935 0.749 0.632 1.572 0.986 2.299 0.78 0.864 1.594 1.145 1.586 1.752 1.029 1.511 0.976 1.198 0.131 1.516 0.442
kappa_carbonprice_500_2030

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.054 1.752 1.028 0.954 0.287 0.374 1.53 0.516 0.215 0.65 1.874 1.736 1.297 1.171 1.606 1.201 1.298 0.748 1.392 1.187 1.063 1.023 1.77 0.312 0.984 0.311
kappa_carbonprice_500_2050

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.428 1.13 0.836 1.082 0.348 0.435 2.718 0.625 0.739 0.813 1.654 1.276 1.631 1.275 2.78 1.672 1.724 1.014 1.201 0.866 1.146 1.045 0.965 0.354 1.185 1.655
kappa_carbonprice_500_2070

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.455 1.306 0.587 1.498 0.348 0.402 2 0.626 0.485 0.733 1.494 1.434 1.855 1.01 1.644 1.912 1.577 1.157 1.408 0.971 1.029 1.223 0.747 0.255 1.134 0.716
kappa_carbonprice_500_2100

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.895 1.961 0.616 1.108 0.219 0.565 1.531 0.722 0.596 0.704 2.639 1.584 1.617 0.923 0.879 1.667 1.385 0.938 2.517 0.856 1.346 2.047 1.155 0.385 0.934 0.797
kappa_rel_abatement_0.25_2030

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.914 1.609 1.059 0.963 0.331 0.418 1.535 0.31 0.686 0.754 1.686 1.572 1.191 1.171 1.424 1.163 1.132 0.848 1.272 1.141 1.205 1.089 1.607 0.735 1.12 0.482
kappa_rel_abatement_0.25_2050

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.196 2.362 0.778 1.676 0.733 1.33 4.77 1.548 1.209 0.681 1.496 2.142 2.08 0.774 5.109 3.802 2.56 0.784 0.792 0.736 1.272 1.698 0.738 0.719 1.363 0.907
kappa_rel_abatement_0.25_2070

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.804 1.616 0.744 0.771 1.225 1.195 3.251 1.032 0.741 0.666 2.25 1.266 2.185 0.7 2.844 4.536 3.566 0.757 0.709 0.792 0.931 2.813 0.73 0.587 0.83 0.619
kappa_rel_abatement_0.25_2100

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.713 2.764 0.706 0.884 0.565 1.203 2.254 0.896 0.682 0.637 4.711 0.728 0.728 0.64 0.779 2.629 3.348 0.719 1.861 0.712 1.13 3.271 0.728 0.546 0.688 0.659
kappa_rel_abatement_0.4_2030

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.979 1.28 0.793 0.784 0.195 0.303 1.521 0.343 0.331 0.536 2.044 3.214 1.622 1.093 2.433 1.213 1.715 0.648 4.769 2.097 0.866 1.492 4.634 0.362 0.929 0.335
kappa_rel_abatement_0.4_2050

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.63 1.531 0.885 1.325 0.331 0.531 2.464 0.743 1.615 0.318 1.575 1.585 1.71 1.016 2.518 1.907 1.803 0.936 1.054 0.717 1.319 1.171 1.012 0.62 1.412 0.587
kappa_rel_abatement_0.4_2070

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.435 1.455 0.668 0.887 0.468 0.455 1.833 0.662 0.711 0.285 1.491 1.424 1.688 0.477 1.73 1.917 1.762 0.884 0.777 1.263 1.009 1.5 0.763 0.198 1.2 0.212
kappa_rel_abatement_0.4_2100

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.278 1.488 0.705 0.8 0.167 0.76 1.267 0.853 0.737 0.427 1.885 1.167 1.115 0.395 1.034 1.373 1.403 0.87 1.547 0.989 1.071 1.619 1.007 0.16 0.814 0.486
kappa_rel_abatement_0.5_2050

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.37 1.218 0.982 1.174 0.333 0.397 2.057 0.594 1.176 0.477 1.342 1.243 1.425 1.07 2.068 1.519 1.502 0.996 1.074 0.908 1.14 1.024 1.046 0.778 1.177 1.21
kappa_rel_abatement_0.5_2070

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.261 1.22 0.776 1.027 0.361 0.35 1.545 0.608 0.894 0.48 1.233 1.18 1.452 0.678 1.419 1.54 1.43 0.988 1.031 1.047 0.992 1.22 0.963 0.144 1.069 0.166
kappa_rel_abatement_0.5_2100

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.417 1.509 0.772 0.93 0.156 0.732 1.242 0.914 0.907 0.683 1.848 1.235 1.156 0.595 1.008 1.377 1.29 0.944 1.884 0.94 1.04 1.576 1.037 0.134 0.931 0.75
kappa_rel_abatement_0.75_2050

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.297 1.135 0.884 1.103 0.312 0.367 2.797 0.623 0.921 0.755 1.838 1.268 1.855 1.286 2.814 2.184 1.758 1 1.253 0.858 1.15 1.016 1.014 0.609 1.204 1.507
kappa_rel_abatement_0.75_2070

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.328 1.231 0.78 1.684 0.355 0.452 1.679 0.742 0.782 0.766 1.628 1.494 1.739 0.896 1.438 1.846 1.371 1.099 1.365 1.013 1.015 1.172 0.897 0.55 1.099 0.61
kappa_rel_abatement_0.75_2100

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.815 1.591 0.742 1.559 0.252 0.743 1.506 0.828 0.815 0.746 2.112 1.943 4.583 0.799 0.91 1.826 1.227 0.94 2.786 0.898 1.804 1.577 1.164 0.563 0.951 0.847

COACCH

NoSLR_form

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic
NoSLR_b1

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.4743 0.47181 0.69609 0.69609 0.69609 0.69609 0.53224 2.30932 2.30932 0.35895 0.23106 0.33022 0.98854 0.79225 0.79225 0.79225 0.98854 2.32289 0.98408 1.37938 2.17792 2.17792 0.06869 0.35125 2.78145 2.30932
NoSLR_b2

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.58069 0.44773 0.63903 0.63903 0.63903 0.63903 1.52132 1.61944 1.61944 1.4799 0.42927 0.62763 0.08134 0.25203 0.25203 0.25203 0.08134 1.65998 0.60159 -0.07077 0.92635 0.92635 0.82064 0.91624 0.89046 1.61944
NoSLR_b3

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
— — — — — — — — — — — — — — — — — — — — — — — — — —
NoSLR_a (q=0.025)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.29422 0.3694 -2.65002 -2.65002 -2.65002 -2.65002 -0.74326 0.46934 0.46934 0.4965 0.19729 0.13447 -0.18372 0.05221 0.05221 0.05221 -0.18372 -0.17828 0.34082 -0.73092 -0.53761 -0.53761 0.25361 -0.42937 0.04302 0.46934
NoSLR_a (q=0.05)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.31979 0.46697 -2.17407 -2.17407 -2.17407 -2.17407 -0.50859 0.53237 0.53237 0.54653 0.31329 0.26594 -0.01031 0.1063 0.1063 0.1063 -0.01031 -0.09275 0.44427 -0.41766 -0.25306 -0.25306 0.31885 -0.28776 0.12536 0.53237
NoSLR_a (q=0.16)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.42399 0.68779 -0.1729 -0.1729 -0.1729 -0.1729 0.27446 0.72094 0.72094 0.68379 0.5963 0.5345 0.42977 0.36509 0.36509 0.36509 0.42977 0.33386 0.64532 0.37637 0.39027 0.39027 0.55941 0.25793 0.48619 0.72094
NoSLR_a (q=0.25)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.56472 0.75749 0.21881 0.21881 0.21881 0.21881 0.41705 0.80863 0.80863 0.78774 0.7334 0.7037 0.61931 0.56734 0.56734 0.56734 0.61931 0.47171 0.7423 0.6015 0.50011 0.50011 0.67463 0.56674 0.61329 0.80863
NoSLR_a (q=0.33)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.64952 0.81587 0.51141 0.51141 0.51141 0.51141 0.58116 0.87591 0.87591 0.85564 0.80069 0.80049 0.71449 0.67856 0.67856 0.67856 0.71449 0.61587 0.84261 0.77381 0.65053 0.65053 0.78411 0.70762 0.74356 0.87591
NoSLR_a (q=0.5)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
NoSLR_a (q=0.67)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.17068 1.18855 1.21305 1.21305 1.21305 1.21305 1.28207 1.10226 1.10226 1.14013 1.28029 1.24027 1.38408 1.31151 1.31151 1.31151 1.38408 1.17165 1.20854 1.28404 1.249 1.249 1.23685 1.22644 1.18843 1.10226
NoSLR_a (q=0.75)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.35378 1.29361 1.38975 1.38975 1.38975 1.38975 1.57599 1.17251 1.17251 1.19986 1.40823 1.38028 1.63931 1.54471 1.54471 1.54471 1.63931 1.29936 1.30494 1.44736 1.38746 1.38746 1.34558 1.33297 1.2631 1.17251
NoSLR_a (q=0.84)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.8597 1.47692 1.80677 1.80677 1.80677 1.80677 1.96985 1.26236 1.26236 1.30364 1.6113 1.56034 1.95178 1.73994 1.73994 1.73994 1.95178 1.49106 1.54711 1.5686 1.69613 1.69613 1.66646 1.62573 1.38906 1.26236
NoSLR_a (q=0.95)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
2.11387 1.74343 2.15031 2.15031 2.15031 2.15031 2.43829 1.39739 1.39739 1.66915 2.44542 2.19977 2.40257 2.17436 2.17436 2.17436 2.40257 1.86079 1.82666 1.77462 1.96406 1.96406 2.21647 1.97288 1.68602 1.39739
NoSLR_a (q=0.975)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
2.2284 1.82295 2.26222 2.26222 2.26222 2.26222 2.54206 1.45479 1.45479 1.83007 2.66921 2.3884 2.51056 2.2929 2.2929 2.2929 2.51056 2.00616 1.89786 1.8997 2.09689 2.09689 2.36114 2.06954 1.78961 1.45479
SLR-NoAd_form

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Linear Robust-Linear Robust-Linear Robust-Quadratic Robust-Linear Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Quadratic Robust-Linear Robust-Quadratic Robust-Quadratic Robust-Linear Robust-Linear Robust-Linear Robust-Quadratic Robust-Quadratic Robust-Linear
SLR-NoAd_b1

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.84384 2.54249 4.0592 4.0592 4.0592 4.0592 12.6565 -1.56287 -1.56287 3.6636 1.13554 0.30235 4.44677 1.5443 1.5443 1.5443 4.44677 3.33617 1.36009 9.9751 15.7593 15.7593 34.374 3.60863 5.47499 -1.56287
SLR-NoAd_b2

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
36.8898 20.8818 2.69844 2.69844 2.69844 2.69844 — — — 9.77887 — 9.59451 31.1549 3.26757 3.26757 3.26757 31.1549 — 83.9441 5.0497 — — — 19.5024 -14.3327 —
SLR-NoAd_b3

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
— — — — — — — — — — — — — — — — — — — — — — — — — —
SLR-NoAd_a (q=0.025)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.41923 0.29168 0.2824 0.2824 0.2824 0.2824 0.37093 2.71109 2.71109 0.27262 -0.09206 -0.01004 0.4885 0.34315 0.34315 0.34315 0.4885 0.28322 0.51649 0.69314 0.4927 0.4927 0.07705 0.45551 -0.23666 2.71109
SLR-NoAd_a (q=0.05)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.55316 0.43404 0.49024 0.49024 0.49024 0.49024 0.56604 2.53559 2.53559 0.41727 -0.06264 0.05694 0.55511 0.39143 0.39143 0.39143 0.55511 0.35029 0.55842 0.72075 0.56492 0.56492 0.11431 0.54965 -0.11766 2.53559
SLR-NoAd_a (q=0.16)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.73721 0.70967 0.69355 0.69355 0.69355 0.69355 0.74318 1.95032 1.95032 0.65563 0.06826 0.25601 0.72551 0.56143 0.56143 0.56143 0.72551 0.43549 0.75713 0.75047 0.71291 0.71291 0.33509 0.76789 0.26451 1.95032
SLR-NoAd_a (q=0.25)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.82081 0.82478 0.7858 0.7858 0.7858 0.7858 0.84855 1.65609 1.65609 0.79957 0.20565 0.35749 0.82979 0.66081 0.66081 0.66081 0.82979 0.52743 0.87065 0.78999 0.81038 0.81038 0.48935 0.84196 0.51949 1.65609
SLR-NoAd_a (q=0.33)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.89769 0.88333 0.88545 0.88545 0.88545 0.88545 0.91733 1.45059 1.45059 0.88045 0.35003 0.43312 0.89014 0.84505 0.84505 0.84505 0.89014 0.64376 0.92131 0.85158 0.88525 0.88525 0.65993 0.89174 0.68605 1.45059
SLR-NoAd_a (q=0.5)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
SLR-NoAd_a (q=0.67)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.14917 1.14185 1.12701 1.12701 1.12701 1.12701 1.08276 0.11675 0.11675 1.16149 4.30825 2.25129 1.11247 1.18513 1.18513 1.18513 1.11247 1.34354 1.11344 1.16177 1.09781 1.09781 1.22238 1.13303 1.23716 0.11675
SLR-NoAd_a (q=0.75)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.1999 1.21744 1.20904 1.20904 1.20904 1.20904 1.11491 -0.54021 -0.54021 1.24115 5.52835 2.4206 1.17445 1.27393 1.27393 1.27393 1.17445 1.47794 1.20668 1.22892 1.13531 1.13531 1.34433 1.20857 1.35701 -0.54021
SLR-NoAd_a (q=0.84)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.33064 1.34041 1.29276 1.29276 1.29276 1.29276 1.16929 -0.99394 -0.99394 1.32694 6.51144 2.88054 1.26502 1.38388 1.38388 1.38388 1.26502 1.59887 1.34175 1.37807 1.19595 1.19595 1.47547 1.33269 1.4601 -0.99394
SLR-NoAd_a (q=0.95)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.57666 1.5699 1.57301 1.57301 1.57301 1.57301 1.29533 -1.41897 -1.41897 1.60507 7.76783 3.65116 1.47509 1.72197 1.72197 1.72197 1.47509 1.78138 1.62651 1.59014 1.41149 1.41149 1.73205 1.69669 1.71319 -1.41897
SLR-NoAd_a (q=0.975)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.68906 1.72987 1.77381 1.77381 1.77381 1.77381 1.33937 -1.55666 -1.55666 1.78613 8.25834 4.08106 1.61287 1.87313 1.87313 1.87313 1.61287 1.94064 1.88883 1.75897 1.58532 1.58532 1.92956 1.96642 1.82747 -1.55666
SLR-Ad_form

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
Robust-Linear Robust-Linear Robust-Linear Robust-Linear Robust-Linear Robust-Linear Robust-Linear Robust-Linear Robust-Linear Robust-Linear OLS-Logistic OLS-Logistic Robust-Linear Robust-Linear Robust-Linear Robust-Linear Robust-Linear Robust-Linear Robust-Linear Robust-Linear Robust-Linear Robust-Linear Robust-Linear Robust-Linear OLS-Logistic Robust-Linear
SLR-Ad_b1

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
2.63477 1.39462 1.27856 1.27856 1.27856 1.27856 6.45004 -0.6333 -0.6333 1.72333 0.27858 0.29745 3.0949 0.71403 0.71403 0.71403 3.0949 1.23678 3.49017 2.50575 9.29209 9.29209 3.37771 2.17176 24.6195 -0.6333
SLR-Ad_b2

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
— — — — — — — — — — 23.426 8.43084 — — — — — — — — — — — — -190.844 —
SLR-Ad_b3

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
— — — — — — — — — — 18.3999 16.6899 — — — — — — — — — — — — -90.8833 —
SLR-Ad_a (q=0.025)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.28606 0.21264 0.50315 0.50315 0.50315 0.50315 0.45611 1.80862 1.80862 0.2466 0.02513 0.17776 0.45718 0.53768 0.53768 0.53768 0.45718 0.64663 0.3027 0.65086 0.47516 0.47516 0.30394 0.43204 0.49181 1.80862
SLR-Ad_a (q=0.05)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.416 0.34828 0.5658 0.5658 0.5658 0.5658 0.50792 1.68653 1.68653 0.5454 0.02615 0.18521 0.56101 0.72109 0.72109 0.72109 0.56101 0.6837 0.41484 0.66396 0.52395 0.52395 0.34369 0.59572 0.56145 1.68653
SLR-Ad_a (q=0.16)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.82922 0.75287 0.69852 0.69852 0.69852 0.69852 0.87817 1.43111 1.43111 0.71115 0.0343 0.20161 0.86427 0.76818 0.76818 0.76818 0.86427 0.7494 0.73017 0.74911 0.88124 0.88124 0.70253 0.82676 0.65192 1.43111
SLR-Ad_a (q=0.25)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.87873 0.85222 0.81367 0.81367 0.81367 0.81367 0.91148 1.35771 1.35771 0.79885 0.03992 0.22985 0.89417 0.86118 0.86118 0.86118 0.89417 0.8083 0.87404 0.81148 0.90734 0.90734 0.86849 0.87815 0.75849 1.35771
SLR-Ad_a (q=0.33)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.92632 0.9037 0.83174 0.83174 0.83174 0.83174 0.92818 1.23868 1.23868 0.89841 0.0477 0.26362 0.94711 0.88268 0.88268 0.88268 0.94711 0.86151 0.89128 0.87724 0.92573 0.92573 0.91245 0.93798 0.81678 1.23868
SLR-Ad_a (q=0.5)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1 1.00002 0.99999 0.99999 0.99999 0.99999 1 1 1 1 0.27972 0.54614 1 1 1 1 1 1 1 1 1 1 1 1 0.93489 1
SLR-Ad_a (q=0.67)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.1066 1.12238 1.2203 1.2203 1.2203 1.2203 1.05711 0.03689 0.03689 1.14764 1.79883 1.6986 1.08722 1.04828 1.04828 1.04828 1.08722 1.24148 1.05486 1.22399 1.05881 1.05881 1.0814 1.13982 1.21107 0.03689
SLR-Ad_a (q=0.75)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.1491 1.15827 1.30665 1.30665 1.30665 1.30665 1.16446 -0.50544 -0.50544 1.19513 1.94695 1.79288 1.15995 1.0774 1.0774 1.0774 1.15995 1.35973 1.15346 1.28026 1.11913 1.11913 1.14325 1.16626 1.30147 -0.50544
SLR-Ad_a (q=0.84)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.24424 1.18119 1.4849 1.4849 1.4849 1.4849 1.20796 -0.92052 -0.92052 1.35414 2.06018 1.86621 1.25014 1.23655 1.23655 1.23655 1.25014 1.54232 1.19562 1.52874 1.19921 1.19921 1.20612 1.27385 1.35812 -0.92052
SLR-Ad_a (q=0.95)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.38318 1.39933 1.84267 1.84267 1.84267 1.84267 1.36306 -1.48909 -1.48909 1.54234 2.45163 2.09597 1.42474 1.45917 1.45917 1.45917 1.42474 2.09861 1.33412 2.12924 1.32282 1.32282 1.35374 1.48076 1.47235 -1.48909
SLR-Ad_a (q=0.975)

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.484 1.43114 1.95586 1.95586 1.95586 1.95586 1.47835 -1.74829 -1.74829 1.75235 3.12795 2.46533 1.46578 1.56118 1.56118 1.56118 1.46578 2.27533 1.33978 2.36925 1.41681 1.41681 1.37144 1.56499 1.50629 -1.74829
combined_b1_NoAd

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.25233 0.52992 1.16099 1.16099 1.16099 1.16099 2.08399 2.1177 2.1177 0.68936 0.37028 0.25077 1.15535 0.94191 0.94191 0.94191 1.15535 2.73192 0.13132 2.54104 4.11009 4.11009 4.2831 0.55682 3.62678 2.1177
combined_b2_NoAd

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.71228 1.11041 0.77977 0.77977 0.77977 0.77977 1.70827 1.59635 1.59635 1.82676 0.44605 0.91932 1.0797 0.37266 0.37266 0.37266 1.0797 1.70926 3.13467 0.22774 1.15912 1.15912 1.32837 1.55338 0.54226 1.59635
combined_b1_NoAd-q0.025

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.0465 0.19124 -1.71336 -1.71336 -1.71336 -1.71336 0.18 0.56438 0.56438 0.2683 0.03277 0.0452 -0.10013 0.09271 0.09271 0.09271 -0.10013 -0.29828 -0.10505 -0.20302 -0.21889 -0.21889 0.34213 -0.05717 -0.08041 0.56438
combined_b2_NoAd-q0.025

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.64525 0.35869 -1.6537 -1.6537 -1.6537 -1.6537 -1.0614 0.69749 0.69749 0.82934 0.08315 0.08147 0.47275 0.05455 0.05455 0.05455 0.47275 -0.28199 1.51335 0.25864 -0.38332 -0.38332 0.24724 -0.10318 0.12071 0.69749
combined_b1_NoAd-q0.05

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.02889 0.24554 -1.28543 -1.28543 -1.28543 -1.28543 0.60765 0.74356 0.74356 0.33405 0.06367 0.08329 0.08241 0.1428 0.1428 0.1428 0.08241 -0.07216 -0.039 0.26116 0.54037 0.54037 0.50364 0.01192 0.24922 0.74356
combined_b2_NoAd-q0.05

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.81165 0.49671 -1.3203 -1.3203 -1.3203 -1.3203 -0.66792 0.80361 0.80361 0.95354 0.13344 0.18352 0.55336 0.07401 0.07401 0.07401 0.55336 -0.1367 1.68178 0.24471 -0.10292 -0.10292 0.3197 0.08655 0.1526 0.80361
combined_b1_NoAd-q0.16

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.03746 0.36575 0.20208 0.20208 0.20208 0.20208 1.29931 1.29117 1.29117 0.46208 0.14728 0.15616 0.54587 0.37327 0.37327 0.37327 0.54587 0.95365 -0.0106 1.39095 2.22746 2.22746 1.45064 0.24845 1.57591 1.29117
combined_b2_NoAd-q0.16

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.08042 0.77823 -0.01288 -0.01288 -0.01288 -0.01288 0.55647 1.1225 1.1225 1.23935 0.25712 0.41014 0.75927 0.15974 0.15974 0.15974 0.75927 0.57566 2.30609 0.19738 0.52748 0.52748 0.62921 0.72557 0.34083 1.1225
combined_b1_NoAd-q0.25

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.08565 0.40532 0.51763 0.51763 0.51763 0.51763 1.53871 1.55006 1.55006 0.54695 0.19809 0.20397 0.75064 0.54837 0.54837 0.54837 0.75064 1.31146 -0.01197 1.7474 2.65501 2.65501 2.10866 0.37215 2.14497 1.55006
combined_b2_NoAd-q0.25

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.25674 0.88571 0.25042 0.25042 0.25042 0.25042 0.79311 1.2713 1.2713 1.44312 0.31828 0.54594 0.87879 0.2227 0.2227 0.2227 0.87879 0.80902 2.65198 0.19325 0.65192 0.65192 0.80209 1.05571 0.36522 1.2713
combined_b1_NoAd-q0.33

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.10881 0.43627 0.76763 0.76763 0.76763 0.76763 1.73279 1.7448 1.7448 0.59805 0.23374 0.22993 0.85479 0.66405 0.66405 0.66405 0.85479 1.69391 0.04354 2.05663 3.12727 3.12727 2.83509 0.43187 2.64813 1.7448
combined_b2_NoAd-q0.33

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.39298 0.95066 0.45142 0.45142 0.45142 0.45142 1.05563 1.38499 1.38499 1.57166 0.34959 0.62875 0.94679 0.27296 0.27296 0.27296 0.94679 1.05405 2.84066 0.19944 0.80869 0.80869 0.97854 1.21651 0.42323 1.38499
combined_b1_NoAd-q0.5

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.25233 0.52992 1.16099 1.16099 1.16099 1.16099 2.08399 2.1177 2.1177 0.68936 0.37028 0.25077 1.15535 0.94191 0.94191 0.94191 1.15535 2.73192 0.13132 2.54104 4.11009 4.11009 4.2831 0.55682 3.62678 2.1177
combined_b2_NoAd-q0.5

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.71228 1.11041 0.77977 0.77977 0.77977 0.77977 1.70827 1.59635 1.59635 1.82676 0.44605 0.91932 1.0797 0.37266 0.37266 0.37266 1.0797 1.70926 3.13467 0.22774 1.15912 1.15912 1.32837 1.55338 0.54226 1.59635
combined_b1_NoAd-q0.67

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.30018 0.62713 1.36834 1.36834 1.36834 1.36834 2.36254 2.52309 2.52309 0.79302 0.89563 0.23068 1.5538 1.21641 1.21641 1.21641 1.5538 3.27116 0.23981 3.12076 4.84137 4.84137 5.23658 0.6637 4.35137 2.52309
combined_b2_NoAd-q0.67

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.98018 1.28884 0.93379 0.93379 0.93379 0.93379 2.15286 1.78235 1.78235 2.09015 0.62186 1.43511 1.22323 0.4735 0.4735 0.4735 1.22323 2.01113 3.54749 0.25592 1.41255 1.41255 1.63565 1.84561 0.62747 1.78235
combined_b1_NoAd-q0.75

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.37576 0.68109 1.52947 1.52947 1.52947 1.52947 2.56887 2.81122 2.81122 0.84078 1.09506 0.26346 1.81643 1.41445 1.41445 1.41445 1.81643 3.62279 0.25516 3.42405 5.21541 5.21541 5.75797 0.71665 4.66037 2.81122
combined_b2_NoAd-q0.75

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
2.14391 1.38596 1.05825 1.05825 1.05825 1.05825 2.60602 1.91128 1.91128 2.20618 0.69724 1.57237 1.30586 0.54299 0.54299 0.54299 1.30586 2.22975 3.84165 0.26441 1.54955 1.54955 1.78679 1.99135 0.65223 1.91128
combined_b1_NoAd-q0.84

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.5867 0.77472 1.85867 1.85867 1.85867 1.85867 2.86288 3.10565 3.10565 0.90638 1.27884 0.28638 2.14044 1.58557 1.58557 1.58557 2.14044 4.11756 0.37829 3.76454 6.00482 6.00482 6.3327 0.845 5.09787 3.10565
combined_b2_NoAd-q0.84

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
2.58565 1.54952 1.33652 1.33652 1.33652 1.33652 3.21537 2.06726 2.06726 2.38953 0.8009 1.81955 1.4217 0.60545 0.60545 0.60545 1.4217 2.55393 4.3295 0.30035 1.84959 1.84959 2.11671 2.33867 0.72849 2.06726
combined_b1_NoAd-q0.95

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.65265 0.9138 2.2281 2.2281 2.2281 2.2281 3.30778 3.49892 3.49892 1.12948 1.64649 0.4363 2.6211 1.98034 1.98034 1.98034 2.6211 5.05105 0.41056 4.29508 7.00479 7.00479 7.45183 1.04176 6.13778 3.49892
combined_b2_NoAd-q0.95

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
3.01163 1.82093 1.59549 1.59549 1.59549 1.59549 3.95158 2.29575 2.29575 3.02691 1.18004 2.44565 1.6681 0.75573 0.75573 0.75573 1.6681 3.17667 5.21898 0.34907 2.14796 2.14796 2.69834 2.88866 0.90479 2.29575
combined_b1_NoAd-q0.975

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.68202 0.96062 2.39934 2.39934 2.39934 2.39934 3.43136 3.65786 3.65786 1.24706 1.76649 0.46443 2.75084 2.09688 2.09688 2.09688 2.75084 5.45387 0.25693 4.66374 7.62998 7.62998 8.29416 1.13116 6.52253 3.65786
combined_b2_NoAd-q0.975

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
3.20533 1.96254 1.69526 1.69526 1.69526 1.69526 4.11769 2.39188 2.39188 3.32786 1.28434 2.68944 1.81443 0.80384 0.80384 0.80384 1.81443 3.42583 5.92629 0.39062 2.31148 2.31148 2.91735 3.14908 0.95725 2.39188
combined_b1_Ad

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.79734 0.6428 0.85284 0.85284 0.85284 0.85284 1.32305 2.23167 2.23167 0.57024 0.24914 0.3825 1.36799 0.8798 0.8798 0.8798 1.36799 2.47452 1.41199 1.6866 3.31717 3.31717 0.48281 0.61751 2.84369 2.23167
combined_b2_Ad

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.61961 0.46833 0.65791 0.65791 0.65791 0.65791 1.6166 1.61008 1.61008 1.50536 0.43145 0.63393 0.12706 0.26258 0.26258 0.26258 0.12706 1.67825 0.65314 -0.03376 1.0636 1.0636 0.87053 0.94832 0.89796 1.61008
combined_b1_Ad-q0.025

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.23196 0.21065 -1.76577 -1.76577 -1.76577 -1.76577 -0.0349 0.94343 0.94343 0.23033 0.04801 0.06186 -0.00814 0.08843 0.08843 0.08843 -0.00814 -0.31608 0.46492 -0.80827 -0.62954 -0.62954 0.14329 -0.03577 0.14468 0.94343
combined_b2_Ad-q0.025

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.18199 0.16977 -1.68394 -1.68394 -1.68394 -1.68394 -1.08729 0.74316 0.74316 0.74105 0.08498 0.0865 0.00595 0.01883 0.01883 0.01883 0.00595 -0.28413 0.22064 0.07582 -0.4328 -0.4328 0.22329 -0.37955 0.04132 0.74316
combined_b1_Ad-q0.05

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.28606 0.27987 -1.42465 -1.42465 -1.42465 -1.42465 0.13097 1.09847 1.09847 0.31141 0.07493 0.10543 0.20269 0.14735 0.14735 0.14735 0.20269 -0.11177 0.61471 -0.37213 0.04576 0.04576 0.16423 0.05755 0.37669 1.09847
combined_b2_Ad-q0.05

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.20189 0.21625 -1.37861 -1.37861 -1.37861 -1.37861 -0.72535 0.84637 0.84637 0.82269 0.13479 0.16903 0.02481 0.0344 0.0344 0.0344 0.02481 -0.14147 0.28866 0.05413 -0.16251 -0.16251 0.27881 -0.24454 0.115 0.84637
combined_b1_Ad-q0.16

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.46897 0.45324 -0.01086 -0.01086 -0.01086 -0.01086 0.84054 1.55377 1.55377 0.39571 0.14096 0.19894 0.75279 0.35649 0.35649 0.35649 0.75279 0.88915 0.94749 0.74929 1.85394 1.85394 0.32936 0.31074 1.38599 1.55377
combined_b2_Ad-q0.16

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.27848 0.32345 -0.0973 -0.0973 -0.0973 -0.0973 0.5012 1.15414 1.15414 1.03004 0.25636 0.33817 0.07447 0.10012 0.10012 0.10012 0.07447 0.56789 0.42586 0.00109 0.48248 0.48248 0.49412 0.26284 0.43699 1.15414
combined_b1_Ad-q0.25

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.55171 0.50311 0.27986 0.27986 0.27986 0.27986 0.94277 1.76197 1.76197 0.45155 0.17308 0.2583 0.95151 0.52487 0.52487 0.52487 0.95151 1.21829 1.10449 1.079 2.1229 2.1229 0.406 0.43289 1.74412 1.76197
combined_b2_Ad-q0.25

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.36212 0.3567 0.15519 0.15519 0.15519 0.15519 0.72131 1.29683 1.29683 1.18612 0.31527 0.44479 0.09125 0.15207 0.15207 0.15207 0.09125 0.79779 0.49162 -0.01254 0.58781 0.58781 0.59696 0.54744 0.55072 1.29683
combined_b1_Ad-q0.33

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.6073 0.53946 0.48636 0.48636 0.48636 0.48636 1.04333 1.92657 1.92657 0.49696 0.18939 0.29588 1.06568 0.61486 0.61486 0.61486 1.06568 1.56123 1.21058 1.33688 2.47145 2.47145 0.43172 0.4983 2.11196 1.92657
combined_b2_Ad-q0.33

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.41322 0.38391 0.34251 0.34251 0.34251 0.34251 0.97257 1.40689 1.40689 1.28914 0.34424 0.50621 0.10142 0.18033 0.18033 0.18033 0.10142 1.03807 0.55285 -0.0223 0.72968 0.72968 0.689 0.67844 0.66739 1.40689
combined_b1_Ad-q0.5

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.79734 0.6428 0.85284 0.85284 0.85284 0.85284 1.32305 2.23167 2.23167 0.57024 0.24914 0.3825 1.36799 0.8798 0.8798 0.8798 1.36799 2.47452 1.41199 1.68659 3.31717 3.31717 0.48281 0.61751 2.84369 2.23167
combined_b2_Ad-q0.5

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.61961 0.46833 0.65791 0.65791 0.65791 0.65791 1.6166 1.61008 1.61008 1.50536 0.43145 0.63393 0.12706 0.26258 0.26258 0.26258 0.12706 1.67825 0.65314 -0.03376 1.0636 1.0636 0.87053 0.94832 0.89796 1.61008
combined_b1_Ad-q0.67

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.91273 0.75269 1.03568 1.03568 1.03568 1.03568 1.51834 2.5426 2.5426 0.65174 0.47416 0.5925 1.78076 1.13082 1.13082 1.13082 1.78076 2.90987 1.64069 2.1472 3.92647 3.92647 0.53279 0.73428 3.41383 2.5426
combined_b2_Ad-q0.67

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.72286 0.55527 0.79822 0.79822 0.79822 0.79822 2.05115 1.7847 1.7847 1.71649 0.57108 0.80046 0.16229 0.3416 0.3416 0.3416 0.16229 1.9676 0.78143 -0.04557 1.30233 1.30233 1.06897 1.16028 1.07129 1.7847
combined_b1_Ad-q0.75

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.0133 0.80839 1.17221 1.17221 1.17221 1.17221 1.75967 2.74695 2.74695 0.68321 0.50533 0.64307 2.06066 1.31812 1.31812 1.31812 2.06066 3.22445 1.77774 2.38977 4.29676 4.29676 0.56587 0.77874 3.6454 2.74695
combined_b2_Ad-q0.75

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.83084 0.60305 0.91277 0.91277 0.91277 0.91277 2.50853 1.90354 1.90354 1.8061 0.6262 0.88886 0.18637 0.40068 0.40068 0.40068 0.18637 2.18176 0.84451 -0.05505 1.43887 1.43887 1.16128 1.25874 1.14066 1.90354
combined_b1_Ad-q0.84

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.284 0.8988 1.49043 1.49043 1.49043 1.49043 2.00369 2.98667 2.98667 0.75406 0.57602 0.73429 2.40378 1.48672 1.48672 1.48672 2.40378 3.69744 2.0341 2.63334 5.06023 5.06023 0.61394 0.91022 4.02184 2.98667
combined_b2_Ad-q0.84

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.12833 0.68559 1.18262 1.18262 1.18262 1.18262 3.11187 2.05293 2.05293 1.96374 0.71623 1.0057 0.21592 0.45156 0.45156 0.45156 0.21592 2.50332 0.99237 -0.05443 1.73579 1.73579 1.42775 1.53043 1.25596 2.05293
combined_b1_Ad-q0.95

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.44943 1.06184 1.78565 1.78565 1.78565 1.78565 2.37567 3.34265 3.34265 0.92502 0.80557 0.97581 2.91565 1.85038 1.85038 1.85038 2.91565 4.64064 2.36846 3.10201 5.78459 5.78459 0.71285 1.08724 4.90661 3.34265
combined_b2_Ad-q0.95

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.28133 0.80941 1.40891 1.40891 1.40891 1.40891 3.83929 2.27692 2.27692 2.50943 1.07873 1.41068 0.26057 0.56339 0.56339 0.56339 0.26057 3.12723 1.16768 -0.04679 2.00095 2.00095 1.88647 1.85513 1.52748 2.27692
combined_b1_Ad-q0.975

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.53632 1.1048 1.88129 1.88129 1.88129 1.88129 2.52208 3.49533 3.49533 1.02716 0.86143 1.06686 3.03798 1.95323 1.95323 1.95323 3.03798 5.00511 2.44094 3.34828 6.18098 6.18098 0.73012 1.14362 5.25599 3.49533
combined_b2_Ad-q0.975

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.35176 0.84567 1.48256 1.48256 1.48256 1.48256 4.00814 2.3723 2.3723 2.75293 1.1753 1.53253 0.27123 0.59435 0.59435 0.59435 0.27123 3.37176 1.2108 -0.04676 2.13691 2.13691 2.00608 1.9464 1.6271 2.3723

ACCREU

cold_related_mortality_perc_constant

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
4.88075e-08 5.42021e-08 6.3862e-08 6.76498e-08 5.37466e-08 4.89356e-08 5.75545e-08 4.55784e-08 6.52506e-08 8.02033e-08 8.19474e-08 6.17671e-08 5.733e-08 6.49743e-08 5.98236e-08 6.14434e-08 6.64393e-08 5.41655e-08 6.84413e-08 5.47358e-08 5.3516e-08 5.29922e-08 9.92718e-08 5.25536e-08 5.12974e-08 5.10046e-08
cold_related_mortality_perc_prod

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
-0.000105019 -0.000118085 -0.000103683 -7.06192e-05 -0.000145921 -0.000119892 -8.37322e-05 -7.33233e-05 -4.58902e-05 -9.05207e-05 -8.60361e-05 -0.000118105 -0.00010287 -0.000128576 -7.39362e-05 -0.000107924 -8.1656e-05 -0.000112409 -0.000157392 -0.000191234 -0.000118787 -0.000129042 -7.8457e-05 -0.000102382 -7.65489e-05 -5.17746e-05
combined_adapt_eff_cost_param

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
649.024 9.08328 128.409 351.651 29.3606 81.5068 1143.38 79.3995 120.966 201.971 54.3225 277.797 231.956 356.377 480.575 412.589 23.7417 94.9994 109.399 13.6725 73.6351 269.517 76.1154 247.891 129.709 180.456
combined_adapt_eff_max_effectiveness

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.295478 0.184676 0.227584 0.27651 0.28034 0.313955 0.436034 0.673988 0.741767 0.391438 0.243692 0.362461 0.242368 0.594006 0.473584 0.411766 0.181016 0.574926 0.271366 0.388141 0.425954 0.506185 0.228344 0.220594 0.501699 0.392637
heat_related_mortality_perc_constant

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
9.99527e-08 9.9942e-08 8.15623e-10 9.92771e-11 9.9974e-08 9.99795e-08 9.99332e-08 9.99885e-08 9.94987e-08 2.50246e-11 4.05127e-11 9.95939e-08 9.99288e-08 7.28703e-11 9.9748e-08 1.75719e-10 7.01198e-11 9.99807e-08 4.69483e-11 9.9974e-08 9.99815e-08 9.99806e-08 2.01259e-11 9.99466e-08 9.99806e-08 9.9969e-08
heat_related_mortality_perc_prod

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
6.82189e-05 6.74551e-05 7.85294e-05 8.14757e-05 0.000127104 8.85308e-05 0.000118756 0.000108929 7.07649e-05 8.3307e-05 4.46161e-05 8.75322e-05 0.000101057 0.000140905 0.000127776 0.000116481 0.000118868 0.000185499 0.000106811 0.00018225 0.000146104 0.000133295 6.18548e-05 4.49393e-05 0.000140481 7.47071e-05
labourprod_adapt_eff_cost_param

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
838.587 9.09088 167.548 453.076 15.3569 77.3781 155.095 310.535 2224.94 382.408 64.8438 377.683 313.809 1208.91 784.678 4250.12 19.6125 34.1373 99.5532 14.4663 42.5105 134.231 38.0253 249.873 307.24 493.89
labourprod_adapt_eff_max_effectiveness

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.227089 0.175469 0.189941 0.213578 0.220532 0.198524 0.185123 0.150091 0.154047 0.233878 0.22673 0.222412 0.202123 0.182163 0.173215 0.216762 0.162527 0.20156 0.246399 0.263412 0.192978 0.203656 0.229985 0.18437 0.180705 0.172986
labourprod_benefit_cdd_constant

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.0133408 -0.000758361 0.00387553 -9.60512e-05 -0.000884945 0.00487239 -0.00159526 3.34998e-06 0.00016982 0.000451791 0.0233958 0.00645043 0.00448171 0.00204652 -0.00458324 -0.000997274 0.00144126 -0.000183153 0.0187731 -0.0064838 -6.81314e-05 -2.94305e-07 0.000359141 0.0166307 -9.79181e-05 -0.000570637
labourprod_benefit_cdd_linear

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
-0.0309175 -0.0161103 -0.0072201 -0.000300453 -0.000329404 -0.00897185 -0.00147882 -3.68421e-06 -0.00144822 -0.00475774 -0.0277183 -0.0118586 -0.00765728 -0.00804245 -0.00294553 -0.00261434 -0.00414625 -0.000441606 -0.02791 -0.00907773 -8.43193e-05 -4.07082e-08 -0.0153623 -0.0208101 -0.000902437 -0.000316853
labourprod_noadapt_ead_constant

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
-0.0194372 -0.0152297 -0.0299718 -0.0149445 0.00110321 -0.016583 0.00167477 -0.0308535 -0.0278375 -0.0124258 -0.0162945 -0.00864758 -0.0130399 -0.00814591 0.00113974 -0.000806302 -0.0118778 -0.00660955 -0.0292504 0.00226733 -0.0168634 -0.0090732 -0.010205 -0.0301248 -0.000427646 -0.0239355
labourprod_noadapt_ead_linear

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.0203491 0.0241706 0.028898 0.0209281 0.0107703 0.0187573 0.00567739 0.0333343 0.0275339 0.017443 0.0182617 0.0099978 0.013153 0.0080565 0.00438404 0.00434157 0.0189532 0.0112843 0.0317021 0.0167681 0.0242787 0.0129265 0.0176185 0.0315961 0.00804604 0.0276911
riverine_adapt_eff_cost_param

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
2630.47 271.924 545.756 1469.06 876.122 316.086 2056.26 90.7415 127.697 412.273 264.886 717.131 859.363 432.786 739.181 300.662 787.978 139.374 2704.31 51.3515 148.074 440.811 1726.48 2374.43 188.434 281.521
riverine_adapt_eff_max_effectiveness

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.830489 0.537174 0.791185 0.925913 0.806722 0.931521 0.913691 1 1 0.85383 0.656077 0.790075 0.781413 0.887007 1 0.847808 0.887498 0.9636 0.857118 0.923048 0.976418 0.948901 0.77247 0.761564 0.999999 1
riverine_noadapt_ead_constant

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.0025268 0.00228356 0.00329867 0.00200241 0.00287555 0.000102048 -7.12036e-05 -0.0178437 -0.0103543 0.00868786 0.00100639 0.000975265 0.00190109 0.00746966 -0.0010768 0.00125516 0.000122818 -0.00656713 -0.00102824 -0.00323492 -0.00982274 -0.00690265 0.000449932 0.00456575 7.60109e-05 -0.000277831
riverine_noadapt_ead_linear

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.000592019 -0.000850507 -0.000884518 0.00065412 0.000213752 0.00233881 0.00292933 0.0421985 0.0415114 0.000794573 -2.12764e-05 0.00179343 -0.000512524 0.00408199 0.00332312 0.00142876 0.000427969 0.0117824 0.00140256 0.00558353 0.0124057 0.00998967 0.00103331 -0.00115215 0.00516176 0.00667382
riverine_noadapt_ead_quadr

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
3.20864e-06 0.000175367 0.000278464 7.95569e-07 9.08552e-05 2.14702e-08 0.000455782 1.1148e-10 2.30796e-11 1.63891e-08 4.56861e-05 2.48787e-07 0.000139539 2.30803e-09 3.37188e-07 7.60241e-07 6.0282e-06 2.20022e-07 2.52181e-06 1.16431e-06 6.04399e-07 7.75926e-08 1.66716e-06 0.0002749 1.00234e-08 1.41514e-07
slr_adapt_eff_cost_param

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
2391.85 511.296 32190.8 21987.4 5242.89 7372.82 205054 16554.2 1.54622e+06 3.46546e+06 1345.08 117502 1.24901e+06 316042 0 13494.2 31437.8 3056.36 1204.63 763.869 2528.46 10183.1 1031.31 12127.5 58098.4 1.19759e+06
slr_adapt_eff_max_effectiveness

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.95853 0.735487 0.926342 0.798066 0.870009 0.714821 0.959072 0.918864 0.646403 0.805456 0.853224 0.810718 0.929408 0.760772 0 0.757542 0.945589 1 1 1 0.936419 0.86972 1 0.724451 0.0377673 0.413044
slr_noadapt_ead_constant

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.000167325 0.00027172 3.76234e-22 4.07349e-14 0.00178498 0.000939567 0.0114371 0.00331457 0.000778182 2.05779e-05 0.000731609 1.07149e-08 0.000408091 3.37779e-16 0 0.000437268 1.68191e-15 0.000480118 4.19566e-07 0.000491214 6.98202e-05 2.76444e-21 0.00114759 0.00081383 0.00334485 0.00095751
slr_noadapt_ead_power

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.91919 0.747655 0.495222 0.329108 0.2 1.52461 0.2 0.793453 2.48491 0.200024 1.45479 0.59386 1.06567 0.4362 0 0.796347 0.480895 2.39651 1.45713 2.24435 0.93726 0.504316 1.54406 0.614949 1.74538 1.37114
slr_noadapt_ead_prod

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.00499195 0.00615978 0.0556277 0.00225907 0.000817304 0.00652699 0.00346829 0.0142294 0.00188104 5.49538e-05 0.0510608 0.00513303 0.0030507 0.00281184 0 0.00251991 0.0222064 0.0175544 0.0741388 0.0269906 0.0516669 0.0431402 0.0710907 0.0053454 0.00577162 0.00314763

ACCREU_CGE

NoSLR_b1

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
-0.732158 -1.32817 4.14889 4.14889 0.364087 4.14889 2.19409 7.31095 7.31095 2.48906 -0.447327 0.000380699 2.19409 1.31823 1.31823 1.31823 2.19409 4.99653 1.47123 1.89664 5.35737 8.76788 1.47123 3.29729 8.76788 7.31095
NoSLR_b2

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
-0.394786 2.70178 0.72777 0.72777 4.40716 0.72777 2.25802 3.51719 3.51719 1.87909 1.28329 0.534203 2.25802 1.40867 1.40867 1.40867 2.25802 2.91441 0.871104 1.38757 1.14292 -1.31457 0.871104 0.130918 -1.31457 3.51719
NoSLR_a0.05

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.7837 -0.360949 0.563497 0.563497 0.584342 0.563497 0.562402 0.0768818 0.0768818 0.560028 0.536939 -0.41782 0.562402 0.64397 0.64397 0.64397 0.562402 0.52502 0.652981 0.535146 0.531416 0.00219056 0.652981 0.559449 0.00219056 0.0768818
NoSLR_a0.50

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1 1 1 1 1 1 1 0.999994 0.999994 1 1 1 1 0.999999 0.999999 0.999999 1 1 1 1 1 1 1 1 1 0.999994
NoSLR_a0.95

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.104679 2.69195 1.30284 1.30284 1.46837 1.30284 1.35649 1.94391 1.94391 1.62527 1.54079 3.6279 1.35649 1.47065 1.47065 1.47065 1.35649 2.21466 1.42082 1.44666 1.49168 1.82287 1.42082 1.4351 1.82287 1.94391
NoSLR_b1_0.05

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
-1.30595 0.479403 2.33789 2.33789 0.212751 2.33789 1.23396 0.562079 0.562079 1.39394 -0.240187 -0.000159063 1.23396 0.848903 0.848903 0.848903 1.23396 2.62328 0.960684 1.01498 2.84699 0.0192066 0.960684 1.84466 0.0192066 0.562079
NoSLR_b1_0.50

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
-0.732158 -1.32817 4.14889 4.14889 0.364087 4.14889 2.19409 7.31091 7.31091 2.48906 -0.447327 0.000380699 2.19409 1.31823 1.31823 1.31823 2.19409 4.99653 1.47123 1.89664 5.35737 8.76788 1.47123 3.29729 8.76788 7.31091
NoSLR_b1_0.95

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
-0.0766413 -3.57537 5.40533 5.40533 0.534615 5.40533 2.97626 14.2119 14.2119 4.04539 -0.689237 0.00138114 2.97626 1.93865 1.93865 1.93865 2.97626 11.0656 2.09035 2.74378 7.99151 15.9827 2.09035 4.73194 15.9827 14.2119
NoSLR_b2_0.05

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
-0.704182 -0.975205 0.410096 0.410096 2.57529 0.410096 1.26992 0.270407 0.270407 1.05234 0.689048 -0.223201 1.26992 0.907144 0.907144 0.907144 1.26992 1.53013 0.568815 0.742556 0.607368 -0.00287965 0.568815 0.0732421 -0.00287965 0.270407
NoSLR_b2_0.50

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
-0.394786 2.70178 0.72777 0.72777 4.40716 0.72777 2.25802 3.51717 3.51717 1.87909 1.28329 0.534203 2.25802 1.40867 1.40867 1.40867 2.25802 2.91441 0.871104 1.38758 1.14292 -1.31457 0.871104 0.130918 -1.31457 3.51717
NoSLR_b2_0.95

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
-0.0413257 7.27305 0.948166 0.948166 6.47136 0.948166 3.06298 6.83711 6.83711 3.05402 1.97728 1.93804 3.06298 2.07166 2.07166 2.07166 3.06298 6.45444 1.23768 2.00734 1.70488 -2.3963 1.23768 0.187881 -2.3963 6.83711
slr_b1

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.7314 1.34485 6.95047 6.95047 2.06051 6.95047 5.46391 2.0683 2.0683 0.427499 1.11997 1.74267 5.46391 0.729692 0.729692 0.729692 5.46391 0.995344 2.91539 1.17004 7.50717 3.50782 2.91539 2.15076 3.50782 2.0683
slr_b2

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
3.40729 2.54319 -6.90156 -6.90156 1.43137 -6.90156 -4.22761 -5.44768 -5.44768 2.14444 11.1157 3.49709 -4.22761 3.78663 3.78663 3.78663 -4.22761 0.48533 11.6092 3.41159 -6.20077 -7.65709 11.6092 0.0389329 -7.65709 -5.44768
slr_a0.05

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.43887 0.504828 0.276967 0.276967 0.516495 0.276967 0.240477 0.712914 0.712914 0.433386 0.341114 0.361205 0.240477 0.417189 0.417189 0.417189 0.240477 0.442576 0.265783 0.443642 0.354522 0.634973 0.265783 0.520115 0.634973 0.712914
slr_a0.50

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1 1 1 1 0.999999 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0.999995 1 1 1 1 1 1
slr_a0.95

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.96963 1.69726 1.84981 1.84981 1.40467 1.84981 1.54178 1.2237 1.2237 1.82176 2.41524 1.84137 1.54178 1.88446 1.88446 1.88446 1.54178 2.30596 2.25024 3.00496 1.39835 1.57432 2.25024 1.39625 1.57432 1.2237
slr_b1_0.05

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.320989 0.678917 1.92505 1.92505 1.06425 1.92505 1.31394 1.47452 1.47452 0.185272 0.382036 0.62946 1.31394 0.304419 0.304419 0.304419 1.31394 0.440516 0.774863 0.519079 2.66146 2.22737 0.774863 1.11864 2.22737 1.47452
slr_b1_0.50

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
0.7314 1.34485 6.95047 6.95047 2.06051 6.95047 5.46391 2.0683 2.0683 0.427499 1.11997 1.74267 5.46391 0.729692 0.729692 0.729692 5.46391 0.995346 2.91539 1.17004 7.50717 3.50782 2.91539 2.15076 3.50782 2.0683
slr_b1_0.95

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.44059 2.28256 12.857 12.857 2.89433 12.857 8.42417 2.53098 2.53098 0.778801 2.70499 3.20889 8.42417 1.37507 1.37507 1.37507 8.42417 2.29522 6.56032 3.51593 10.4976 5.52242 6.56032 3.00299 5.52242 2.53098
slr_b2_0.05

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
1.49536 1.28387 -1.91151 -1.91151 0.739297 -1.91151 -1.01664 -3.88373 -3.88373 0.929368 3.79173 1.26316 -1.01664 1.57974 1.57974 1.57974 -1.01664 0.214796 3.08552 1.51353 -2.19831 -4.86204 3.08552 0.0202496 -4.86204 -3.88373
slr_b2_0.50

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
3.40729 2.54319 -6.90156 -6.90156 1.43137 -6.90156 -4.22761 -5.44768 -5.44768 2.14444 11.1157 3.49709 -4.22761 3.78663 3.78663 3.78663 -4.22761 0.485331 11.6092 3.41158 -6.20077 -7.65709 11.6092 0.0389329 -7.65709 -5.44768
slr_b2_0.95

CAN USA MEX RCAM BRA RSAM NAF WAF EAF SAF WEU CEU TUR UKR STAN RUS ME INDIA KOR CHN SEAS INDO JAP OCE RSAS RSAF
6.7111 4.31645 -12.7666 -12.7666 2.0106 -12.7666 -6.51805 -6.66632 -6.66632 3.90665 26.8471 6.43942 -6.51805 7.13575 7.13575 7.13575 -6.51805 1.11915 26.1234 10.2517 -8.67084 -12.0547 26.1234 0.05436 -12.0547 -6.66632