Essential use of BeforeIT
We start by importing the BeforeIT library and other useful libraries.
import BeforeIT as Bit
using PlotsWe then initialise the model loading some precomputed set of parameters and by specifying a number of epochs. In another tutorial we will illustrate how to compute parameters and initial conditions.
parameters = Bit.AUSTRIA2010Q1.parameters
initial_conditions = Bit.AUSTRIA2010Q1.initial_conditionsDict{String, Any} with 21 entries:
"sb_inact" => 2.23847
"C_G" => [11482.3; 11556.2; … ; 14578.2; 14714.8;;]
"E_CB" => 1.0618e5
"D_RoW" => 0.0
"sb_other" => 0.590286
"L_I" => 236919.0
"omega" => 0.85
"r_bar" => 0.00164593
"N_s" => [123.0; 18.0; … ; 5.0; 60.0;;]
"C_E" => [17384.5; 17752.9; … ; 38786.7; 38617.8;;]
"D_H" => 219841.0
"K_H" => 4.05377e5
"L_G" => 2.32611e5
"pi" => [-0.00749736; -0.00789543; … ; 0.00530319; 0.00100796;;]
"w_UB" => 4.06546
"Y" => [1.04531e5; 1.05062e5; … ; 1.35709e5; 1.34636e5;;]
"Y_I" => [19804.6; 19944.1; … ; 36883.2; 36575.9;;]
"Y_EA" => 2.35485e6
"D_I" => 54049.0
⋮ => ⋮We can now initialise the model, by specifying in advance the maximum number of epochs.
T = 16
model = Bit.init_model(parameters, initial_conditions, T)Model(Workers{Vector{Float64}, Vector{Int64}}([0.7661282859097249, 0.7661282859097249, 0.7661282859097249, 0.7661282859097249, 0.7661282859097249, 0.7661282859097249, 0.7661282859097249, 0.7661282859097249, 0.7661282859097249, 0.7661282859097249 … 4.655745607447569, 4.655745607447569, 4.655745607447569, 4.655745607447569, 4.655745607447569, 4.655745607447569, 4.655745607447569, 4.655745607447569, 4.655745607447569, 4.655745607447569], [3.781806633594487, 3.781806633594487, 3.781806633594487, 3.781806633594487, 3.781806633594487, 3.781806633594487, 3.781806633594487, 3.781806633594487, 3.781806633594487, 3.781806633594487 … 22.981960001210958, 22.981960001210958, 22.981960001210958, 22.981960001210958, 22.981960001210958, 22.981960001210958, 22.981960001210958, 22.981960001210958, 22.981960001210958, 22.981960001210958], [6.973481059156249, 6.973481059156249, 6.973481059156249, 6.973481059156249, 6.973481059156249, 6.973481059156249, 6.973481059156249, 6.973481059156249, 6.973481059156249, 6.973481059156249 … 42.37769888790032, 42.37769888790032, 42.37769888790032, 42.37769888790032, 42.37769888790032, 42.37769888790032, 42.37769888790032, 42.37769888790032, 42.37769888790032, 42.37769888790032], [0.2697101055708983, 0.2697101055708983, 0.2697101055708983, 0.2697101055708983, 0.2697101055708983, 0.2697101055708983, 0.2697101055708983, 0.2697101055708983, 0.2697101055708983, 0.2697101055708983 … 11.337587012313522, 11.337587012313522, 11.337587012313522, 11.337587012313522, 11.337587012313522, 11.337587012313522, 11.337587012313522, 11.337587012313522, 11.337587012313522, 11.337587012313522], [1, 2, 2, 3, 3, 3, 3, 3, 3, 3 … 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]), Workers{Vector{Float64}, Vector{Int64}}([2.8287542404944714, 2.8287542404944714, 2.8287542404944714, 2.8287542404944714, 2.8287542404944714, 2.8287542404944714, 2.8287542404944714, 2.8287542404944714, 2.8287542404944714, 2.8287542404944714 … 2.8287542404944714, 2.8287542404944714, 2.8287542404944714, 2.8287542404944714, 2.8287542404944714, 2.8287542404944714, 2.8287542404944714, 2.8287542404944714, 2.8287542404944714, 2.8287542404944714], [13.963459838592984, 13.963459838592984, 13.963459838592984, 13.963459838592984, 13.963459838592984, 13.963459838592984, 13.963459838592984, 13.963459838592984, 13.963459838592984, 13.963459838592984 … 13.963459838592984, 13.963459838592984, 13.963459838592984, 13.963459838592984, 13.963459838592984, 13.963459838592984, 13.963459838592984, 13.963459838592984, 13.963459838592984, 13.963459838592984], [25.74799087814977, 25.74799087814977, 25.74799087814977, 25.74799087814977, 25.74799087814977, 25.74799087814977, 25.74799087814977, 25.74799087814977, 25.74799087814977, 25.74799087814977 … 25.74799087814977, 25.74799087814977, 25.74799087814977, 25.74799087814977, 25.74799087814977, 25.74799087814977, 25.74799087814977, 25.74799087814977, 25.74799087814977, 25.74799087814977], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1 … -1, -1, -1, -1, -1, -1, -1, -1, -1, -1], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]), Firms{Vector{Float64}, Vector{Int64}}([1, 1, 1, 1, 1, 1, 1, 1, 1, 1 … 62, 62, 62, 62, 62, 62, 62, 62, 62, 62], [10.822026659306621, 10.822026659306621, 10.822026659306621, 10.822026659306621, 10.822026659306621, 10.822026659306621, 10.822026659306621, 10.822026659306621, 10.822026659306621, 10.822026659306621 … 11.988103388298951, 11.988103388298951, 11.988103388298951, 11.988103388298951, 11.988103388298951, 11.988103388298951, 11.988103388298951, 11.988103388298951, 11.988103388298951, 11.988103388298951], [1.6631751855300485, 1.6631751855300485, 1.6631751855300485, 1.6631751855300485, 1.6631751855300485, 1.6631751855300485, 1.6631751855300485, 1.6631751855300485, 1.6631751855300485, 1.6631751855300485 … 3.4759574544453877, 3.4759574544453877, 3.4759574544453877, 3.4759574544453877, 3.4759574544453877, 3.4759574544453877, 3.4759574544453877, 3.4759574544453877, 3.4759574544453877, 3.4759574544453877], [0.042702129272078754, 0.042702129272078754, 0.042702129272078754, 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0.011078553057541721, 0.011078553057541721, 0.011078553057541721, 0.011078553057541721, 0.011078553057541721 … 0.012425621091468782, 0.012425621091468782, 0.012425621091468782, 0.012425621091468782, 0.012425621091468782, 0.012425621091468782, 0.012425621091468782, 0.012425621091468782, 0.012425621091468782, 0.012425621091468782], [0.009528627732528832, 0.009528627732528832, 0.009528627732528832, 0.009528627732528832, 0.009528627732528832, 0.009528627732528832, 0.009528627732528832, 0.009528627732528832, 0.009528627732528832, 0.009528627732528832 … 0.010357147774366318, 0.010357147774366318, 0.010357147774366318, 0.010357147774366318, 0.010357147774366318, 0.010357147774366318, 0.010357147774366318, 0.010357147774366318, 0.010357147774366318, 0.010357147774366318], [-0.26105054841223635, -0.26105054841223635, -0.26105054841223635, -0.26105054841223635, -0.26105054841223635, -0.26105054841223635, -0.26105054841223635, -0.26105054841223635, -0.26105054841223635, -0.26105054841223635 … 0.013413693877270037, 0.013413693877270037, 0.013413693877270037, 0.013413693877270037, 0.013413693877270037, 0.013413693877270037, 0.013413693877270037, 0.013413693877270037, 0.013413693877270037, 0.013413693877270037], [1, 2, 15, 3, 1, 3, 18, 1, 1, 3 … 1, 1, 1, 1, 1, 1, 42, 1, 1, 1], [10.822026659306621, 21.644053318613242, 162.3303998895993, 32.46607997791986, 10.822026659306621, 32.46607997791986, 194.79647986751917, 10.822026659306621, 10.822026659306621, 32.46607997791986 … 11.988103388298951, 11.988103388298951, 11.988103388298951, 11.988103388298951, 11.988103388298951, 11.988103388298951, 503.50034230855596, 11.988103388298951, 11.988103388298951, 11.988103388298951], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [10.822026659306621, 21.644053318613242, 162.3303998895993, 32.46607997791986, 10.822026659306621, 32.46607997791986, 194.79647986751917, 10.822026659306621, 10.822026659306621, 32.46607997791986 … 11.988103388298951, 11.988103388298951, 11.988103388298951, 11.988103388298951, 11.988103388298951, 11.988103388298951, 503.50034230855596, 11.988103388298951, 11.988103388298951, 11.988103388298951], [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 … 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [298.15365853658534, 596.3073170731707, 4472.304878048781, 894.460975609756, 298.15365853658534, 894.460975609756, 5366.765853658536, 298.15365853658534, 298.15365853658534, 894.460975609756 … 79.20833333333334, 79.20833333333334, 79.20833333333334, 79.20833333333334, 79.20833333333334, 79.20833333333334, 3326.7500000000005, 79.20833333333334, 79.20833333333334, 79.20833333333334], [7.65511425407355, 15.3102285081471, 114.82671381110323, 22.965342762220647, 7.65511425407355, 22.965342762220647, 137.7920565733239, 7.65511425407355, 7.65511425407355, 22.965342762220647 … 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0.35565736393550956], [12.384292053067, 24.768584106134, 185.764380796005, 37.15287615920099, 12.384292053067, 37.15287615920099, 222.91725695520603, 12.384292053067, 12.384292053067, 37.15287615920099 … 13.530111496595191, 13.530111496595191, 13.530111496595191, 13.530111496595191, 13.530111496595191, 13.530111496595191, 568.2646828569981, 13.530111496595191, 13.530111496595191, 13.530111496595191], [1.2548454674764378, 2.5096909349528755, 18.822682012146572, 3.764536402429314, 1.2548454674764378, 3.764536402429314, 22.5872184145759, 1.2548454674764378, 1.2548454674764378, 3.764536402429314 … 3.5771064837982878, 3.5771064837982878, 3.5771064837982878, 3.5771064837982878, 3.5771064837982878, 3.5771064837982878, 150.23847231952809, 3.5771064837982878, 3.5771064837982878, 3.5771064837982878], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0 … 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 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[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0 … 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [1.3061857958470853, 2.0220856873365403, 11.32878427669946, 2.737985578825996, 1.3061857958470853, 2.737985578825996, 13.476483951167834, 1.3061857958470853, 1.3061857958470853, 2.737985578825996 … 2.631055234104208, 2.631055234104208, 2.631055234104208, 2.631055234104208, 2.631055234104208, 2.631055234104208, 86.30259775371388, 2.631055234104208, 2.631055234104208, 2.631055234104208], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [11.889212387273586, 18.40550270753724, 103.11727687096484, 24.92179302780091, 11.889212387273586, 24.92179302780091, 122.6661478317559, 11.889212387273586, 11.889212387273586, 24.92179302780091 … 23.94848771160181, 23.94848771160181, 23.94848771160181, 23.94848771160181, 23.94848771160181, 23.94848771160181, 785.546679139869, 23.94848771160181, 23.94848771160181, 23.94848771160181], [6.447669663541786, 9.98153599952956, 55.92179836737067, 13.51540233551734, 6.447669663541786, 13.51540233551734, 66.52339737533403, 6.447669663541786, 6.447669663541786, 13.51540233551734 … 12.987566600381651, 12.987566600381651, 12.987566600381651, 12.987566600381651, 12.987566600381651, 12.987566600381651, 426.0118607863149, 12.987566600381651, 12.987566600381651, 12.987566600381651]), Bank{Float64}(89460.0, 6476.292527744357, 0.0, 126431.00000000012, 0.028359903595743693, 3695.3696336675207, 0.0, 0.0, 0.0, 0.0, 33636.12938055406, 18241.296726948145), CentralBank{Float64}(0.0016459319014481277, 0.0089810924595537, 0.9259668580654086, -0.003424572940686137, 0.0049629315732038215, 0.30996974466133875, 1.328593153520194, 106179.90000000002), Government{Float64}(0.9905949533296431, 0.09373211872949586, 0.011235005057648862, 0.0, 14732.121510837034, 232610.9, 2.238468336136841, 0.5902859043576301, [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], 0.0, 0.0), RestOfTheWorld{Float64}(0.962809216044625, 0.39260026877953946, 0.020320381298662014, 0.9662360466537488, 0.35492769963078624, 0.02122821278168188, 2.3548476e6, 0.0, 0.0019383188997990075, 0.38456173629534834, 0.0026219533879005877, 0.0025327891562467505, 0.9635784504324201, 0.5360029623199525, 0.006618207536795881, 0.0, 33097.63671130043, 34095.03119997918, [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], 0.0, [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], 0.0), Aggregates{Float64, Int64}([104531.39273728609, 105062.38754395355, 105399.12953350678, 106689.88106040593, 107938.33111423723, 108890.48532381697, 110110.17779727321, 110374.00540561741, 110808.89423399912, 111932.48072916963 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], [-0.007497362866886709, -0.007895434153021436, -0.0019938777296781562, -0.0035311300388783107, 0.001212170001002849, -0.001672412335241874, 0.001839696090252002, 0.004290005139261838, 0.00600429551344886, 0.0036060572293247772 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], 1.0, [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 … 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], 1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1), MutableNamedTuple(tau_VAT = 0.1528683933530887, tau_EXPORT = 0.0029486201783457183, tau_SIW = 0.17114894621657745, psi_H = 0.07125099957246343, tau_FIRM = 0.07701197259426128, H_inact = 4130, theta_DIV = 0.7858074440019603, I_s = [48, 2, 1, 1, 5, 2, 4, 1, 1, 1 … 14, 10, 13, 41, 20, 16, 7, 7, 2, 19], psi = 0.9096681249468772, tau_INC = 0.21340742230566648, zeta_b = 0.5, tau_CF = 0.08761417854834112, H_act = 4743, zeta = 0.03, mu = 0.026713971694295565, tau_G = 0.009147800682711324, theta_UB = 0.3585824478060919, T_prime = 54, tau_SIF = 0.21215146534992413, T = 16, zeta_LTV = 0.6, I = 624, products = MutableNamedTuple(a_sg = [0.37790282216028437 0.0 … 0.0 0.0; 0.0006712800413285777 0.8149348034258406 … 2.4029219530949635e-5 0.00019143106686926454; … ; 0.00037430822580994426 0.000357977071568566 … 0.3197327950788158 0.0011366219595362582; 0.0 5.36965607352849e-5 … 0.0 0.05594572929254256], b_CF_g = [0.0033476048872100555, 0.0, 0.0, 0.0008050086095806136, 0.0, 0.003306696048303853, 0.0030629933432974495, 0.0, 0.0, 0.0 … 0.0017883064872300512, 0.0, 0.0, 0.0, 0.0, 0.002291709084994238, 0.0, 0.0, 0.0, 0.0], b_CFH_g = [0.0006092803753845975, 0.0, 0.0, 0.004372477702289994, 0.0, 0.0, 0.06710603871527036, 0.0, 0.0, 0.0 … 0.0041711096896454745, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], c_E_g = [0.005090338238241512, 0.0005933402816643566, 1.793599921320476e-5, 0.007268146142708006, 0.05434404438533037, 0.02138421321578873, 0.023894091259534518, 0.028037089231640524, 0.005923381894006229, 0.011927802553688313 … 0.0014618202435669027, 0.0009447261124040238, 0.0001280209174610526, 0.0010477673386531637, 0.0, 0.0013030104043795392, 5.5260305268213854e-5, 0.0, 1.307076865739618e-5, 8.641230390167474e-6], b_HH_g = [0.011287997598927976, 0.0020040637862256817, 0.0003326837475323491, 0.00034402684015257527, 0.06305103828047173, 0.03068200872784047, 0.0003505790613555631, 0.0020473225369636873, 0.0, 0.0191077565617325 … 0.005591228759882936, 0.0004356874830029748, 0.014434120586233577, 0.03514505772295519, 0.024907176866291014, 0.013342154173060372, 0.009686226103767459, 0.011051272187723254, 0.0021206651420422927, 0.01721782824162338], c_G_g = [0.0, 0.0, 0.0, 0.0, 8.57086390274792e-6, 0.0, 0.0, 0.0, 2.4536198623552867e-5, 0.0 … 0.008555738848801895, 0.3324338967920097, 0.22067672180252998, 0.2370889178393625, 0.0477595425645907, 0.012942508661614227, 0.004667927760053456, 0.021757222045203074, 0.0, 0.002000708524749294], c_I_g = [0.016810689305736877, 0.004087420487057966, 0.00036885674795364003, 0.05818437780960789, 0.04895082866561155, 0.04689140072807505, 0.010101572733480902, 0.016066325760592727, 0.00037371898454196314, 0.041008926225895866 … 0.0018123421762754539, 0.000401097116716159, 0.0003479865324437806, 0.0006664256271585853, 0.0028556289501379516, 0.001307065586721844, 6.418152296577174e-5, 0.0, 3.538212163497461e-5, 0.00020458795490837936]), J = 156, G = 62, H = 8873, L = 312, theta = 0.05, C = [4.3800671000101816e-5 0.00010629745355671226 9.959785873214212e-5; 0.00010629745355671226 0.0004129178961230129 0.0003596689472264872; 9.959785873214212e-5 0.0003596689472264872 0.0004506370179043619]))Note that the it is very simple to inspect the model by typing
fieldnames(typeof(model))(:w_act, :w_inact, :firms, :bank, :cb, :gov, :rotw, :agg, :prop)and to inspect the specific attributes of one agent type by typing
fieldnames(typeof(model.bank))(:E_k, :Pi_k, :Pi_e_k, :D_k, :r, :Y_h, :C_d_h, :I_d_h, :C_h, :I_h, :K_h, :D_h)We can now define a data tracker, which will store the time series of the model.
data = Bit.init_data(model);We can run now the model for a number of epochs and progressively update the data tracker.
for t in 1:T
Bit.step!(model; multi_threading = true)
Bit.update_data!(data, model)
endNote that we can equivalently run the model for a number of epochs in the single command data = Bit.run!(model), but writing the loop explicitely is more instructive.
We can then plot any time series stored in the data tracker, for example
plot(data.real_gdp, title = "gdp", titlefont = 10)
Or we can plot multiple time series at once using the function plot_data
ps = Bit.plot_data(data, quantities = [:real_gdp, :real_household_consumption, :real_government_consumption, :real_capitalformation, :real_exports, :real_imports, :wages, :euribor, :gdp_deflator])
plot(ps..., layout = (3, 3))
To run multiple monte-carlo repetitions in parallel we can use
model = Bit.init_model(parameters, initial_conditions, T)
data_vector = Bit.ensemblerun(model, 4)BeforeIT.DataVector(BeforeIT.Data[BeforeIT.Data{Float64, Vector{Float64}, Matrix{Float64}}([72421.99999999999, 72518.37322607067, 73248.80532158085, 74257.23494594253, 74550.99947515756, 75265.89947616015, 75932.30278903125, 77068.61618030616, 77897.78823998675, 78343.92199499959, 78510.6563905724, 78913.24034277292, 78563.93669613641, 79541.82495532342, 79840.98640074341, 80732.35685801809, 80855.53106846288], [72421.99999999999, 72361.89986014062, 72868.52374642088, 73551.7253647399, 73216.23271147128, 73646.98019190867, 73790.7836061332, 74629.79784684921, 75053.94926307301, 75126.42962712508, 75136.95373397069, 74972.9900920728, 74406.43746678684, 74934.86486291028, 74807.76837209801, 75869.90518677288, 75598.70776469474], [64900.920495538034, 64999.145814252566, 65667.50473938012, 66583.80872629743, 66846.08119347953, 67488.37703296018, 68082.43904598114, 69115.351957679, 69893.72917491876, 70286.56579034486, 70426.03811913979, 70771.31698587484, 70437.40133125921, 71311.34460831457, 71568.52591361666, 72395.18128033061, 72491.36713979262], [64900.920495538034, 64858.89673425145, 65326.58256284111, 65951.20349875883, 65649.26387261366, 66036.74706770481, 66162.30961647414, 66928.21281035911, 67342.09689163583, 67399.97952767373, 67399.74178155109, 67237.60454060318, 66709.94756472083, 67181.08334097061, 67056.80817125375, 68034.87168568163, 67778.34005226033], [40512.94792630534, 40470.43291423182, 40761.646761707874, 41221.89778826686, 41404.45773515371, 41803.02663762069, 42209.24418046473, 42714.808905031015, 42912.54740162784, 43240.90308250234, 43441.040467798746, 43833.4995353644, 43765.9998083593, 44315.67811914507, 44509.180859358, 44842.67220786321, 45089.04584080248], [40512.94792630534, 40383.10959771185, 40550.02688383262, 40830.25320486506, 40663.14917534355, 40903.87142344352, 41018.816618176286, 41363.10876779251, 41345.925580178446, 41465.05025173863, 41574.323765002766, 41644.830602456976, 41449.96120175626, 41748.97109830668, 41703.298547018836, 42141.830378066355, 42157.580994941716], [14866.888022051655, 14906.526745315676, 15163.942902577963, 15152.833335144547, 15291.721719204601, 15394.446420964947, 15674.53069747706, 15998.316681433762, 16276.37105459867, 16200.535100507086, 15889.86984811097, 16041.303862892517, 16110.722440087025, 16434.38264563948, 16635.695473717336, 16204.343177427136, 16252.498738268247], [14866.888022051655, 14874.362835531145, 15085.21713951174, 15008.86798135657, 15017.937570715274, 15063.322148821346, 15232.46181587295, 15492.053691894029, 15682.164473724042, 15535.198253512222, 15207.061951907142, 15240.338761310446, 15258.164396973829, 15482.524361844335, 15586.972428675055, 15228.367266020483, 15195.842341571655], [15944.236265986641, 15963.498305870015, 16071.780136566866, 16572.48786548644, 16345.630719851933, 16506.545490869295, 16646.333059014498, 16903.575938249487, 17246.54051374683, 17560.27190301346, 17921.36451392802, 17921.989282924835, 17996.656360095865, 17662.519347692407, 17126.81462520442, 18333.319753780117, 18408.072681730173], [15944.236265986641, 15929.05376166949, 15988.341207575082, 16415.034534750732, 16052.977304472599, 16151.500709666521, 16176.856429682777, 16368.6662312588, 16616.915652270483, 16839.092271116137, 17151.260710824074, 17027.118885278604, 17044.29719768073, 16639.528967323367, 16047.131168988462, 17229.117117493686, 17211.27161973676], [15944.236265986641, 15948.937588727158, 16083.913126230806, 16300.353239643853, 16386.67959746477, 16520.05451512729, 16664.310163442497, 16916.563706345944, 17077.225866339024, 17203.520923626216, 17274.655050103494, 17384.71847592249, 17317.580256312045, 17526.59134109459, 17590.00542453921, 17770.713083737115, 17832.660201568815], [15944.236265986641, 15914.524462280784, 16000.41120710013, 16145.48542917494, 16093.291239859172, 16164.719163825246, 16194.326525728686, 16381.243004471553, 16453.782227777214, 16496.992633200964, 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0.002146371120876237, 0.002123116762736273, 0.0015816281960920869, 0.0016509509635169919, 0.00242343562079055, 0.0026585129857846857], [518.0834390395164 258.24326637797435 … 136.99722836422484 504.90462950861706; 512.6344745547001 255.52718190025848 … 135.5563542199769 499.5942737104988; … ; 573.1631925276813 284.7983716518881 … 149.0776618123824 549.1852602859292; 562.3786520751992 278.6128207282961 … 146.90181388095033 542.2495314920059], [518.0834390395164 258.24326637797435 … 136.99722836422484 504.90462950861706; 512.3580957010006 255.38941841940078 … 135.48327113319584 499.32492527699344; … ; 551.8790544102883 274.22252177723885 … 143.54173489732747 528.7915310926545; 540.2904798520942 267.6699303018851 … 141.1320490562802 520.95195734815])])Note that this will use the number of threads specified when activating the Julia environment. To discover the number of threads available, you can use the command
Threads.nthreads()2To activate Julia with a specific number of threads, say 8, you can use the command julia -t 8 in the terminal.
We can then plot the results of the monte-carlo repetitions using the function plot_data_vector
ps = Bit.plot_data_vector(data_vector)
plot(ps..., layout = (3, 3))