Merge pull request #37 from raddleverse/harmonize-scc-changes

Update Repo to Include Updates Made for SCC

src/ciam.jl

@@ -59,6 +59,12 @@ function initciam(xsc, params, initparams, m::Model; fixed::Bool = true, t::Int
         end
     end
 
+    # set the VSL parameter to missings as a dummy and set vsl to be calculated
+    # endogenously
+    dummy_vsl = Array{Union{Missing, Float64}}(missing, length(dim_keys(m, :time)), length(dim_keys(m, :ciam_country)))
+    update_param!(m, :slrcost, :vsl_ciam_country, dummy_vsl)
+    update_param!(m, :slrcost, :vsl_exogenous, false)
+
     # Set the rest of the parameters - to use update_leftover_params! we need To
     # specific the component as well as the parameter name
     params_dict = Dict()
@@ -92,7 +98,7 @@ function get_model(;initfile::Union{String, Nothing} = nothing, fixed::Bool=true
 
     set_dimension!(m, :time, t)
     set_dimension!(m, :adaptPers, length(params["at"]))
-    set_dimension!(m, :regions, xsc[2])
+    set_dimension!(m, :ciam_country, xsc[2])
     set_dimension!(m, :segments, xsc[3])
 
     if GAMSmatch

src/slrcost.jl

@@ -91,13 +91,17 @@ using Mimi
     rsigA = Parameter(index = [segments])                       # rsigA in GAMS code
     rsigB = Parameter(index = [segments])                       # rsigB in GAMS code
 
-
     # ---Storm damage parameters---
     floodmortality = Parameter()                # Flood deaths as percent of exposed population; (Jonkman Vrijling 2008) (0.01)
 
-    # We make VSL an exogenously calculated variable for each region,
-    # and `vsl` is then simply pulled from `vsl_ciam_country` 
-    vsl_ciam_country = Parameter(index = [time, ciam_country], unit = "million US\$2010/yr") # Value of statistical life (million 2010$)
+    # if TRUE, then VSL is exogenously calculated for each country and set in vsl_ciam_country, then each segment is set by looking up its country
+    # if FALSE, then VSL is endogenously calculated using vslel and vslmult as well as other endogenous socioeconomics for each segment
+    vsl_exogenous = Parameter{Bool}(default=true) 
+
+    vsl_ciam_country = Parameter(index = [time, ciam_country], unit = "million US\$2010/yr") # Value of statistical life (million 2010$) (only used for exogenous calculation of vsl)
+    vslel = Parameter(default = 0.5)    # Elasticity of vsl (0.5) (only used for endogenous calculation of vsl)
+    vslmult = Parameter(default = 216)  # multiplier on USA GDP (216)(only used for endogenous calculation of vsl)
+
     vsl = Variable(index = [time, segments], unit = "million US\$2010/yr")     # Value of statistical life (million 2010$)
 
     # ---Wetland Loss Parameters---
@@ -256,9 +260,6 @@ using Mimi
                 end
                 v.areaparams[m, :] = [p.area1[m] p.area2[m] p.area3[m] p.area4[m] p.area5[m] p.area6[m] p.area7[m] p.area8[m] p.area9[m] p.area10[m] p.area11[m] p.area12[m] p.area13[m] p.area14[m] p.area15[m]]
 
-                # Calculate vsl - pull VSL from vsl_ciam_country parameter for the proper region
-                v.vsl[t, m] = p.vsl_ciam_country[ti1, rgn_ind]
-
                 # Greenland segments are treated differently (RFF Model does not include Greenland)
                 if isgreenland(m, p.xsc)::Int == 1
                     v.ypc_seg[t, m] = 22642 * 1.01^1   # FLAG: assumes t is an index (1-20)
@@ -270,6 +271,17 @@ using Mimi
                     v.landvalue[t, m] = min(v.coastland[t, m], (v.land_appr[t, rgn_ind] * v.landdata[rgn_ind]))
                 end
 
+                # Calculate VSL
+                if p.vsl_exogenous
+                    v.vsl[t, m] = p.vsl_ciam_country[ti1, rgn_ind] # pull VSL from vsl_ciam_country parameter for the proper region
+                else # endogenous calculation of VSL
+                    if isgreenland(m, p.xsc)::Int == 1 # Greenland segments are treated differently
+                        v.vsl[t, m] = 1e-6 * p.vslmult * p.ypcc[ti1, p.rgn_ind_usa] * (v.ypc_seg[t, m] / p.ypcc[ti1, p.rgn_ind_usa])^p.vslel
+                    else
+                        v.vsl[t, m] = 1e-6 * p.vslmult * p.ypcc[ti1, p.rgn_ind_usa] * (p.ypcc[t, rgn_ind] / p.ypcc[ti1, p.rgn_ind_usa])^p.vslel
+                    end
+                end
+
                 v.capital[t, m] = p.kgdp * v.ypc_seg[t, m] * v.popdens_seg[t, m] * 1e-6
                 v.coastArea[t, m] = calcCoastArea(view(v.areaparams, m, :), p.lslr[t, m])
 
@@ -286,9 +298,6 @@ using Mimi
                         # v.popdens_seg[ti,m]=p.popdens_seg_merkens[ti,m]
                     end
 
-                    # Calculate vsl - pull VSL from vsl_ciam_country parameter for the proper region
-                    v.vsl[ti, m] = p.vsl_ciam_country[ti, rgn_ind]
-
                     # Special treatment for Greenland segments
                     if isgreenland(m, p.xsc)::Int == 1
                         v.ypc_seg[ti, m] = 22642 * 1.01^i   # FLAG: assumes i is an index (1-20)
@@ -302,6 +311,17 @@ using Mimi
 
                     end
 
+                    # Calculate VSL
+                    if p.vsl_exogenous
+                        v.vsl[ti, m] = p.vsl_ciam_country[ti, rgn_ind]
+                    else # endogenously calculate VSL
+                        if isgreenland(m, p.xsc)::Int == 1  # Special treatment for Greenland segments
+                            v.vsl[ti, m] = 1e-6 * p.vslmult * p.ypcc[ti, p.rgn_ind_usa] * (v.ypc_seg[ti, m] / p.ypcc[ti, p.rgn_ind_usa])^p.vslel   
+                        else
+                            v.vsl[ti, m] = 1e-6 * p.vslmult * p.ypcc[ti, p.rgn_ind_usa] * (p.ypcc[ti, rgn_ind] / p.ypcc[ti, p.rgn_ind_usa])^p.vslel   
+                        end
+                    end
+
                     v.capital[ti, m] = p.kgdp * v.ypc_seg[ti, m] * v.popdens_seg[ti, m] * 1e-6
                     v.coastArea[ti, m] = calcCoastArea(view(v.areaparams, m, :), p.lslr[ti, m])
                     v.wetlandloss[tim1, m] = min(1, (localrate(p.lslr[tim1, m], p.lslr[ti, m], p.tstep) / p.wmaxrate)^2)