Update to reflect change in NLboxsolve.jl

RJDennis · Sep 10, 2022 · c1d4d40 · c1d4d40
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diff --git a/Project.toml b/Project.toml
@@ -1,7 +1,7 @@
 name = "SolveDSGE"
 uuid = "00bf1f32-23ad-54cc-bf6e-3216db8a43a2"
 authors = ["Richard Dennis <[email protected]>"]
-version = "0.5.4"
+version = "0.5.5"
 
 [deps]
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"

diff --git a/examples/example_aiyagari/model_aiyagari_processed.txt b/examples/example_aiyagari/model_aiyagari_processed.txt
@@ -0,0 +1,226 @@
+nx = 2 
+
+ny = 5 
+
+ns = 1 
+
+nv = 7 
+
+ne = 7 
+
+jumps_to_approximate = [2] 
+
+eqns_to_approximate = [6] 
+
+variables = OrderedDict("l" => 1, "k" => 2, "c" => 3, "muc" => 4, "lm" => 5, "rbar" => 6, "wbar" => 7) 
+
+function nlsolve_static_equations(f::Array{T,1},x::Array{T,1},p::Array{T1,1}) where {T<:Number,T1<:Real} 
+
+  f[1] = x[1] - ((0.60)*x[1] + (0.20)*sqrt(1.0-(0.60)^2)*0.0)
+  f[2] = x[6] - ((0.36)*((p[1])/(1.0))^((0.36)-1.0) - (0.08))
+  f[3] = x[7] - ((1.0-(0.36))*((p[1])/(1.0))^((0.36)))
+  f[4] = x[5]*(x[2]-(0.00)) - (0.0)
+  f[5] = x[3]^(-(1.00)) - (x[4])
+  f[6] = x[4] - (x[5] + (0.96)*(1.0+x[6])*x[4])
+  f[7] = x[3] + x[2] - (x[7]*(1.0)*exp(x[1]) + (1.0+x[6])*x[2])
+
+end 
+
+function static_equations(x::Array{T,1},p::Array{T1,1}) where {T<:Number,T1<:Real} 
+
+  f = Array{T,1}(undef,length(x)) 
+
+  f[1] = x[1] - ((0.60)*x[1] + (0.20)*sqrt(1.0-(0.60)^2)*0.0)
+  f[2] = x[6] - ((0.36)*((p[1])/(1.0))^((0.36)-1.0) - (0.08))
+  f[3] = x[7] - ((1.0-(0.36))*((p[1])/(1.0))^((0.36)))
+  f[4] = x[5]*(x[2]-(0.00)) - (0.0)
+  f[5] = x[3]^(-(1.00)) - (x[4])
+  f[6] = x[4] - (x[5] + (0.96)*(1.0+x[6])*x[4])
+  f[7] = x[3] + x[2] - (x[7]*(1.0)*exp(x[1]) + (1.0+x[6])*x[2])
+
+  return f 
+
+end 
+
+function dynamic_equations(x::Array{T,1},p::Array{T1,1}) where {T<:Number,T1<:Real} 
+
+  f = Array{T,1}(undef,7) 
+
+  f[1] = x[8] - ((0.60)*x[1] + (0.20)*sqrt(1.0-(0.60)^2)*x[15])
+  f[2] = x[6] - ((0.36)*((p[1])/(1.0))^((0.36)-1.0) - (0.08))
+  f[3] = x[7] - ((1.0-(0.36))*((p[1])/(1.0))^((0.36)))
+  f[4] = x[5]*(x[2]-(0.00)) - (0.0)
+  f[5] = x[3]^(-(1.00)) - (x[4])
+  f[6] = x[4] - (x[5] + (0.96)*(1.0+x[6])*x[11])
+  f[7] = x[3] + x[9] - (x[7]*(1.0)*exp(x[1]) + (1.0+x[6])*x[2])
+
+  return f 
+
+end 
+
+function dynamic_eqn_1(x::Array{T,1},p::Array{T1,1}) where {T<:Number,T1<:Real} 
+
+  f = x[8] - ((0.60)*x[1] + (0.20)*sqrt(1.0-(0.60)^2)*x[15])
+
+  return f 
+
+end 
+
+function dynamic_eqn_2(x::Array{T,1},p::Array{T1,1}) where {T<:Number,T1<:Real} 
+
+  f = x[6] - ((0.36)*((p[1])/(1.0))^((0.36)-1.0) - (0.08))
+
+  return f 
+
+end 
+
+function dynamic_eqn_3(x::Array{T,1},p::Array{T1,1}) where {T<:Number,T1<:Real} 
+
+  f = x[7] - ((1.0-(0.36))*((p[1])/(1.0))^((0.36)))
+
+  return f 
+
+end 
+
+function dynamic_eqn_4(x::Array{T,1},p::Array{T1,1}) where {T<:Number,T1<:Real} 
+
+  f = x[5]*(x[2]-(0.00)) - (0.0)
+
+  return f 
+
+end 
+
+function dynamic_eqn_5(x::Array{T,1},p::Array{T1,1}) where {T<:Number,T1<:Real} 
+
+  f = x[3]^(-(1.00)) - (x[4])
+
+  return f 
+
+end 
+
+function dynamic_eqn_6(x::Array{T,1},p::Array{T1,1}) where {T<:Number,T1<:Real} 
+
+  f = x[4] - (x[5] + (0.96)*(1.0+x[6])*x[11])
+
+  return f 
+
+end 
+
+function dynamic_eqn_7(x::Array{T,1},p::Array{T1,1}) where {T<:Number,T1<:Real} 
+
+  f = x[3] + x[9] - (x[7]*(1.0)*exp(x[1]) + (1.0+x[6])*x[2])
+
+  return f 
+
+end 
+
+individual_equations = Array{Function}(undef,7) 
+individual_equations[1] = dynamic_eqn_1
+individual_equations[2] = dynamic_eqn_2
+individual_equations[3] = dynamic_eqn_3
+individual_equations[4] = dynamic_eqn_4
+individual_equations[5] = dynamic_eqn_5
+individual_equations[6] = dynamic_eqn_6
+individual_equations[7] = dynamic_eqn_7
+
+function closure_chebyshev_equations(state,scaled_weights,order,domain,p) 
+
+  function chebyshev_equations(f::Array{T,1},x::Array{T,1}) where {T<:Number} 
+
+    approx2 = chebyshev_evaluate(scaled_weights[1],x[5+1:end],order,domain)
+
+    #f = Array{T,1}(undef,7) 
+
+    f[1] = x[6] - ((0.60)*state[1] + (0.20)*sqrt(1.0-(0.60)^2)*0.0)
+    f[2] = x[4] - ((0.36)*((p[1])/(1.0))^((0.36)-1.0) - (0.08))
+    f[3] = x[5] - ((1.0-(0.36))*((p[1])/(1.0))^((0.36)))
+    f[4] = x[3]*(state[2]-(0.00)) - (0.0)
+    f[5] = x[1]^(-(1.00)) - (x[2])
+    f[6] = x[2] - (x[3] + (0.96)*(1.0+x[4])*approx2)
+    f[7] = x[1] + x[7] - (x[5]*(1.0)*exp(state[1]) + (1.0+x[4])*state[2])
+
+    #return f 
+
+  end 
+
+  return chebyshev_equations 
+
+end 
+
+function closure_smolyak_equations(state,scaled_weights,order,domain,p) 
+
+  function smolyak_equations(f::Array{T,1},x::Array{T,1}) where {T<:Number} 
+
+    poly = smolyak_polynomial(x[5+1:end],order,domain) 
+    approx2 = smolyak_evaluate(scaled_weights[1],poly)
+
+    #f = Array{T,1}(undef,7) 
+
+    f[1] = x[6] - ((0.60)*state[1] + (0.20)*sqrt(1.0-(0.60)^2)*0.0)
+    f[2] = x[4] - ((0.36)*((p[1])/(1.0))^((0.36)-1.0) - (0.08))
+    f[3] = x[5] - ((1.0-(0.36))*((p[1])/(1.0))^((0.36)))
+    f[4] = x[3]*(state[2]-(0.00)) - (0.0)
+    f[5] = x[1]^(-(1.00)) - (x[2])
+    f[6] = x[2] - (x[3] + (0.96)*(1.0+x[4])*approx2)
+    f[7] = x[1] + x[7] - (x[5]*(1.0)*exp(state[1]) + (1.0+x[4])*state[2])
+
+    #return f 
+
+  end 
+
+  return smolyak_equations 
+
+end 
+
+function closure_hcross_equations(state,scaled_weights,order,domain,p) 
+
+  function hcross_equations(f::Array{T,1},x::Array{T,1}) where {T<:Number} 
+
+    poly = hyperbolic_cross_polynomial(x[5+1:end],order,domain) 
+    approx2 = hyperbolic_cross_evaluate(scaled_weights[1],poly)
+
+    #f = Array{T,1}(undef,7) 
+
+    f[1] = x[6] - ((0.60)*state[1] + (0.20)*sqrt(1.0-(0.60)^2)*0.0)
+    f[2] = x[4] - ((0.36)*((p[1])/(1.0))^((0.36)-1.0) - (0.08))
+    f[3] = x[5] - ((1.0-(0.36))*((p[1])/(1.0))^((0.36)))
+    f[4] = x[3]*(state[2]-(0.00)) - (0.0)
+    f[5] = x[1]^(-(1.00)) - (x[2])
+    f[6] = x[2] - (x[3] + (0.96)*(1.0+x[4])*approx2)
+    f[7] = x[1] + x[7] - (x[5]*(1.0)*exp(state[1]) + (1.0+x[4])*state[2])
+
+    #return f 
+
+  end 
+
+  return hcross_equations 
+
+end 
+
+function closure_piecewise_equations(variables,grid,state,integrals,p) 
+
+  function piecewise_equations(f::Array{T,1},x::Array{T,1}) where {T<:Number} 
+
+    approx2 = piecewise_linear_evaluate(variables[2],grid,x[5+1:end],integrals)
+
+    #f = Array{T,1}(undef,7) 
+
+    f[1] = x[6] - ((0.60)*state[1] + (0.20)*sqrt(1.0-(0.60)^2)*0.0)
+    f[2] = x[4] - ((0.36)*((p[1])/(1.0))^((0.36)-1.0) - (0.08))
+    f[3] = x[5] - ((1.0-(0.36))*((p[1])/(1.0))^((0.36)))
+    f[4] = x[3]*(state[2]-(0.00)) - (0.0)
+    f[5] = x[1]^(-(1.00)) - (x[2])
+    f[6] = x[2] - (x[3] + (0.96)*(1.0+x[4])*approx2)
+    f[7] = x[1] + x[7] - (x[5]*(1.0)*exp(state[1]) + (1.0+x[4])*state[2])
+
+    #return f 
+
+  end 
+
+  return piecewise_equations 
+
+end 
+
+unassigned_parameters = ["kbar"] 
+
+solvers = "Projection" 
diff --git a/examples/example_nkdsge_zlb/solution_file_nkdsge_zlb.jl b/examples/example_nkdsge_zlb/solution_file_nkdsge_zlb.jl
@@ -25,7 +25,7 @@ data = simulate(soln_nla,ss[1:4],100_000)
 
 # Use previous solution as initialization to solve with zlb imposed
 
-COBC = ChebyshevSchemeOBCStoch(ss,chebyshev_nodes,[11,11,11,15],11,6,[0.045 0.2 0.02 0.345; -0.045 -0.21 -0.03 0.31],lb,ub,tol,1e-8,maxiters,:lm)
+COBC = ChebyshevSchemeOBCStoch(ss,chebyshev_nodes,[11,11,11,15],11,6,[0.045 0.2 0.02 0.345; -0.045 -0.21 -0.03 0.31],lb,ub,tol,1e-8,maxiters,:lm_ar)
 soln_nlb = solve_model(dsge_nk_zlb,soln_nla,COBC,2)
 data_obc = simulate(soln_nlb,ss[1:4],lb,ub,100_000)