Revision 44fbd33f9511d5d15c3525ff921b6fb9683fd5be authored by Javier Barbero on 12 January 2022, 18:37:08 UTC, committed by Javier Barbero on 12 January 2022, 18:37:08 UTC
1 parent df8666d
deaprofitability.jl
``````# Tests for Profitability DEA Models
@testset "ProfitabilityDEAModel" begin

## Test Profitability DEA Model with Zofío and Prieto (2006) data
X = [5 3; 2 4; 4 2; 4 8; 7 9]
Y = [7 4; 10 8; 8 10; 5 4; 3 6]
W = [2 1; 2 1; 2 1; 2 1; 2 1.0]
P = [3 2; 3 2; 3 2; 3 2; 3 2.0]

# alpha = 0.5 CRS equals Input Oriented CRS
deaprofbl = deaprofitability(X, Y, W, P)

@test typeof(deaprofbl) == ProfitabilityDEAModel

@test nobs(deaprofbl) == 5
@test ninputs(deaprofbl) == 2
@test noutputs(deaprofbl) == 2

@test efficiency(deaprofbl) ≈ [0.388;
1.000;
0.765;
0.250;
0.159] atol = 1e-3
@test efficiency(deaprofbl, :CRS) ≈ [0.636;
1.000;
1.000;
0.250;
0.261] atol = 1e-3
@test efficiency(deaprofbl, :VRS) ≈ [0.682;
1.000;
1.000;
0.250;
0.360] atol = 1e-3
@test efficiency(deaprofbl, :Scale) ≈ [0.933;
1.000;
1.000;
1.000;
0.725] atol = 1e-3
@test efficiency(deaprofbl, :Allocative) ≈ [0.610;
1.000;
0.765;
1.000;
0.609] atol = 1e-3

@test efficiency(deaprofitability(targets(deaprofbl, :X), targets(deaprofbl, :Y), W, P)) ≈ ones(5) atol=1e-7

# Check defaults
@test efficiency(deaprofitability(X, Y, W, P, alpha = 0.5)) == efficiency(deaprofbl)
@test efficiency(deaprofbl, :Economic) == efficiency(deaprofbl)

# Print
show(IOBuffer(), deaprofbl)

# Test errors
@test_throws DimensionMismatch deaprofitability([1; 2 ; 3], [4 ; 5], [1; 1; 1], [4; 5]) #  Different number of observations
@test_throws DimensionMismatch deaprofitability([1; 2; 3], [4; 5; 6], [1; 2; 3; 4], [4; 5; 6]) # Different number of observation in input prices
@test_throws DimensionMismatch deaprofitability([1; 2; 3], [4; 5; 6], [1; 2; 3], [4; 5; 6; 7]) # Different number of observation in output prices
@test_throws DimensionMismatch deaprofitability([1 1; 2 2; 3 3], [4; 5; 6], [1 1 1; 2 2 2; 3 3 3], [4; 5; 6]) # Different number of input prices and inputs
@test_throws DimensionMismatch deaprofitability([1; 2; 3], [4 4; 5 5; 6 6], [1; 2; 3], [4 4 4; 5 5 5; 6 6 6]) # Different number of oputput prices and outputs
@test_throws ArgumentError efficiency(deaprofbl, :Error)
@test_throws ArgumentError normfactor(deaprofitability(X, Y, W, P)) # ERROR: ProfitabilityDEAModel has no normalization factor

# ------------------
# Test Vector and Matrix inputs and outputs
# ------------------

# Inputs is Matrix, Outputs is Vector
X = [2 2; 1 4; 4 1; 4 3; 5 5; 6 1; 2 5; 1.6	8]
Y = [1; 1; 1; 1; 1; 1; 1; 1]
W = [1 1; 1 1; 1 1; 1 1; 1 1; 1 1; 1 1; 1 1]
P = [1; 1; 1; 1; 1; 1; 1; 1]

@test efficiency(deaprofitability(X, Y, W, P)) ≈ ( sum(Y .* P, dims = 2) ./ sum(X .* W, dims = 2) )  / 0.25 atol = 1e-5

# Inputs is Vector, Output is Matrix
X = [1; 1; 1; 1; 1; 1; 1; 1]
Y = [7 7; 4 8; 8 4; 3 5; 3 3; 8 2; 6 4; 1.5 5]
W = [1; 1; 1; 1; 1; 1; 1; 1]
P = [1 1; 1 1; 1 1; 1 1; 1 1; 1 1; 1 1; 1 1]

@test efficiency(deaprofitability(X, Y, W, P)) ≈ ( sum(Y .* P, dims = 2) ./ sum(X .* W, dims = 2) )  / 14 atol = 1e-5

# Inputs is Vector, Output is Vector
X = [2; 4; 8; 12; 6; 14; 14; 9.412]
Y = [1; 5; 8; 9; 3; 7; 9; 2.353]
W = [1; 1; 1; 1; 1; 1; 1; 1]
P = [1; 1; 1; 1; 1; 1; 1; 1]

@test efficiency(deaprofitability(X, Y, W, P)) ≈ ( sum(Y .* P, dims = 2) ./ sum(X .* W, dims = 2) )  / 1.25 atol = 1e-5

end
``````

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