@pytest.mark.parametrize(
'TR,j,p,method,expected',
test_data,
ids=['SS, all j', 'SS, one j', 'TPI, all j', 'TPI, one j'])
def test_get_tr(TR, j, p, method, expected):
# Test the get_tr function
test_value = household.get_tr(TR, j, p, method)
print('Test value = ', test_value)
assert np.allclose(test_value, expected)
p1 = Specifications()
p1.e = 0.99
p1.lambdas = np.array([0.25])
p1.g_y = 0.03
r1 = 0.05
w1 = 1.2
b1 = 0.5
b_splus1_1 = 0.55
n1 = 0.8
BQ1 = 0.1
tau_c1 = 0.05
bq1 = BQ1 / p1.lambdas
net_tax1 = 0.02
j1 = None
p2 = Specifications()
p2.e = np.array([0.99, 1.5, 0.2])
p2.lambdas = np.array([0.25])
p2.g_y = 0.03
test_data,
ids=['SS, all j',
'SS, one j',
'TPI, all j',
'TPI, one j'])
def test_get_tr(TR, j, p, method, expected):
# Test the get_tr function
test_value = household.get_tr(TR, j, p, method)
print('Test value = ', test_value)
assert np.allclose(test_value, expected)
p1 = Specifications()
p1.e = 0.99
p1.lambdas = np.array([0.25])
p1.g_y = 0.03
r1 = 0.05
w1 = 1.2
b1 = 0.5
b_splus1_1 = 0.55
n1 = 0.8
BQ1 = 0.1
tau_c1 = 0.05
bq1 = BQ1 / p1.lambdas
net_tax1 = 0.02
j1 = None
p2 = Specifications()
p2.e = np.array([0.99, 1.5, 0.2])
p2.lambdas = np.array([0.25])
p2.g_y = 0.03
