[Python] AttributeError: 'SVARResults' object has no attribute 'k_exog_user'

I am using the following code to conduct a SVAR estimation:

data_q = pd.DataFrame({'GDP': GDP,
'CPI': CPI_q,
'Interest_rate': Interest_rate_q,
'Unemployment_rate': Unemployment_rate_q,
'Yearly_inflation': Yearly_inflation_q}).dropna()

#SVAR model
A = np.array([
[1, 0, 0, 0],
['E', 1, 0, 0],
['E', 'E', 1, 0],
['E', 'E', 'E', 1]
])
B = np.array([
[1, 0, 0, 0],
['E', 1, 0, 0],
['E', 'E', 1, 0],
['E', 'E', 'E', 1]
])

endogenous_vars = ['GDP', 'Interest_rate', 'Unemployment_rate', 'Yearly_inflation']
exogenous_vars=["CPI"]

svar_model = SVAR(data_q[endogenous_vars], svar_type='AB', A=A, B=B)
svar_results = svar_model.fit(2)
print(svar_results.summary(), '\n')

irf_svar = svar_results.irf(10)
irf_svar.plot(orth=True)
plt.show()


but it keeps crashing, always the same kind of error:

`self.summary = self.make()`


buf.write(self._coef_table() + '\n')

dim = k * model.k_ar + model.k_trend + model.k_exog_user

AttributeError: 'SVARResults' object has no attribute 'k_exog_user'

I tried to change the matrices A and B, the type of SVAR and including optional parameters, but stil does not work.

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