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Update search_and_matching.jl
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@Tortar
Tortar authored Nov 28, 2024
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Showing 1 changed file with 97 additions and 90 deletions.
187 changes: 97 additions & 90 deletions test/markets/search_and_matching.jl
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Expand Up @@ -2,100 +2,107 @@ using BeforeIT, Test, MAT, StatsBase
using Random

@testset "search and matching" begin
T = 1
Random.seed!(1)

parameters = BeforeIT.AUSTRIA2010Q1.parameters
initial_conditions = BeforeIT.AUSTRIA2010Q1.initial_conditions

T = 1
model = BeforeIT.init_model(parameters, initial_conditions, T;)

gov = model.gov # government
cb = model.cb # central bank
rotw = model.rotw # rest of the world
firms = model.firms # firms
bank = model.bank # bank
w_act = model.w_act # active workers
w_inact = model.w_inact # inactive workers
agg = model.agg # aggregates
prop = model.prop # model properties

BeforeIT.finance_insolvent_firms!(firms, bank, model)

agg.Y_e, agg.gamma_e, agg.pi_e = BeforeIT.growth_inflation_expectations(model)

agg.epsilon_Y_EA, agg.epsilon_E, agg.epsilon_I = BeforeIT.epsilon(prop.C)

rotw.Y_EA, rotw.gamma_EA, rotw.pi_EA = BeforeIT.growth_inflation_EA(rotw, model)

cb.r_bar = BeforeIT.central_bank_rate(cb, model)

bank.r = BeforeIT.bank_rate(bank, model)

Q_s_i, I_d_i, DM_d_i, N_d_i, Pi_e_i, DL_d_i, K_e_i, L_e_i, P_i =
BeforeIT.firms_expectations_and_decisions(firms, model)

firms.Q_s_i .= Q_s_i
firms.I_d_i .= I_d_i
firms.DM_d_i .= DM_d_i
firms.N_d_i .= N_d_i
firms.Pi_e_i .= Pi_e_i
firms.P_i .= P_i
firms.DL_d_i .= DL_d_i
firms.K_e_i .= K_e_i
firms.L_e_i .= L_e_i

firms.DL_i .= BeforeIT.search_and_matching_credit(firms, model)

N_i, Oh = BeforeIT.search_and_matching_labour(firms, model)
firms.N_i .= N_i
w_act.O_h .= Oh

firms.w_i .= BeforeIT.firms_wages(firms)
firms.Y_i .= BeforeIT.firms_production(firms)

BeforeIT.update_workers_wages!(w_act, firms.w_i)

gov.sb_other, gov.sb_inact = BeforeIT.gov_social_benefits(gov, model)

bank.Pi_e_k = BeforeIT.bank_expected_profits(bank, model)

C_d_h, I_d_h = BeforeIT.households_budget_act(w_act, model)
w_act.C_d_h .= C_d_h
w_act.I_d_h .= I_d_h
C_d_h, I_d_h = BeforeIT.households_budget_inact(w_inact, model)
w_inact.C_d_h .= C_d_h
w_inact.I_d_h .= I_d_h
C_d_h, I_d_h = BeforeIT.households_budget(firms, model)
firms.C_d_h .= C_d_h
firms.I_d_h .= I_d_h
bank.C_d_h, bank.I_d_h = BeforeIT.households_budget(bank, model)

C_G, C_d_j = BeforeIT.gov_expenditure(gov, model)
gov.C_G = C_G
gov.C_d_j .= C_d_j

C_E, Y_I, C_d_l, Y_m, P_m = BeforeIT.rotw_import_export(rotw, model)
rotw.C_E = C_E
rotw.Y_I = Y_I
rotw.C_d_l .= C_d_l
rotw.Y_m .= Y_m
rotw.P_m .= P_m

BeforeIT.search_and_matching!(model, false)

function run_search_and_matching(parameters, initial_conditions, T, m)
model = BeforeIT.init_model(parameters, initial_conditions, T;)

gov = model.gov # government
cb = model.cb # central bank
rotw = model.rotw # rest of the world
firms = model.firms # firms
bank = model.bank # bank
w_act = model.w_act # active workers
w_inact = model.w_inact # inactive workers
agg = model.agg # aggregates
prop = model.prop # model properties

BeforeIT.finance_insolvent_firms!(firms, bank, model)

agg.Y_e, agg.gamma_e, agg.pi_e = BeforeIT.growth_inflation_expectations(model)

agg.epsilon_Y_EA, agg.epsilon_E, agg.epsilon_I = BeforeIT.epsilon(prop.C)

rotw.Y_EA, rotw.gamma_EA, rotw.pi_EA = BeforeIT.growth_inflation_EA(rotw, model)

cb.r_bar = BeforeIT.central_bank_rate(cb, model)

bank.r = BeforeIT.bank_rate(bank, model)

Q_s_i, I_d_i, DM_d_i, N_d_i, Pi_e_i, DL_d_i, K_e_i, L_e_i, P_i =
BeforeIT.firms_expectations_and_decisions(firms, model)

firms.Q_s_i .= Q_s_i
firms.I_d_i .= I_d_i
firms.DM_d_i .= DM_d_i
firms.N_d_i .= N_d_i
firms.Pi_e_i .= Pi_e_i
firms.P_i .= P_i
firms.DL_d_i .= DL_d_i
firms.K_e_i .= K_e_i
firms.L_e_i .= L_e_i

firms.DL_i .= BeforeIT.search_and_matching_credit(firms, model)

N_i, Oh = BeforeIT.search_and_matching_labour(firms, model)
firms.N_i .= N_i
w_act.O_h .= Oh

firms.w_i .= BeforeIT.firms_wages(firms)
firms.Y_i .= BeforeIT.firms_production(firms)

BeforeIT.update_workers_wages!(w_act, firms.w_i)

gov.sb_other, gov.sb_inact = BeforeIT.gov_social_benefits(gov, model)

bank.Pi_e_k = BeforeIT.bank_expected_profits(bank, model)

C_d_h, I_d_h = BeforeIT.households_budget_act(w_act, model)
w_act.C_d_h .= C_d_h
w_act.I_d_h .= I_d_h
C_d_h, I_d_h = BeforeIT.households_budget_inact(w_inact, model)
w_inact.C_d_h .= C_d_h
w_inact.I_d_h .= I_d_h
C_d_h, I_d_h = BeforeIT.households_budget(firms, model)
firms.C_d_h .= C_d_h
firms.I_d_h .= I_d_h
bank.C_d_h, bank.I_d_h = BeforeIT.households_budget(bank, model)

C_G, C_d_j = BeforeIT.gov_expenditure(gov, model)
gov.C_G = C_G
gov.C_d_j .= C_d_j

C_E, Y_I, C_d_l, Y_m, P_m = BeforeIT.rotw_import_export(rotw, model)
rotw.C_E = C_E
rotw.Y_I = Y_I
rotw.C_d_l .= C_d_l
rotw.Y_m .= Y_m
rotw.P_m .= P_m

BeforeIT.search_and_matching!(model, m)
return bank, w_act, w_inact, firms, gov, rotw
end

# NOTE: as a test we use the expected values and standard deviations of the
# original implementation, with tolerance = 3*(standard deviation)
@test isapprox(mean([bank.I_h, w_act.I_h..., w_inact.I_h..., firms.I_h...]),
0.32975, atol = 3*0.0025351)
@test isapprox(mean([bank.C_h, w_act.C_h..., w_inact.C_h..., firms.C_h...]),
3.973, atol = 3*0.029366)
@test isapprox(mean(firms.I_i), 20.5075, atol = 3*0.12763)
@test isapprox(mean(firms.DM_i), 109.3163, atol = 3*0.68033)
@test isapprox(mean(firms.P_bar_i), 1.0031, atol = 3*0.0044726)
@test isapprox(mean(firms.P_CF_i), 1.0031, atol = 3*0.0044726)
@test isapprox(gov.C_j, 14752.2413, atol = 3*126.7441)
@test isapprox(rotw.C_l, 34188.1258, atol = 3*666.275)
@test isapprox(mean(firms.Q_d_i), 216.2474, atol = 3*1.2275)
@test isapprox(mean(rotw.Q_d_m), 535.7522, atol = 3*9.6082)
# original implementation, with tolerance = 3*(standard deviation) for
# both single-threaded and multi-threaded execution
for m in [true, false]
bank, w_act, w_inact, firms, gov, rotw = run_search_and_matching(parameters, initial_conditions, T, m)
@test isapprox(mean([bank.I_h, w_act.I_h..., w_inact.I_h..., firms.I_h...]),
0.32975, atol = 3*0.0025351)
@test isapprox(mean([bank.C_h, w_act.C_h..., w_inact.C_h..., firms.C_h...]),
3.973, atol = 3*0.029366)
@test isapprox(mean(firms.I_i), 20.5075, atol = 3*0.12763)
@test isapprox(mean(firms.DM_i), 109.3163, atol = 3*0.68033)
@test isapprox(mean(firms.P_bar_i), 1.0031, atol = 3*0.0044726)
@test isapprox(mean(firms.P_CF_i), 1.0031, atol = 3*0.0044726)
@test isapprox(gov.C_j, 14752.2413, atol = 3*126.7441)
@test isapprox(rotw.C_l, 34188.1258, atol = 3*666.275)
@test isapprox(mean(firms.Q_d_i), 216.2474, atol = 3*1.2275)
@test isapprox(mean(rotw.Q_d_m), 535.7522, atol = 3*9.6082)
end
end

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