step6.py

# (c) 2022 - 2026 Open Risk (https://www.openriskmanagement.com)

import numpy as np
import pandas as pd
import pymrio

io = pymrio.IOSystem()

"""

Closed Models

Step 6 of the Academy Course [SFI32064](https://www.openriskacademy.com/course/view.php?id=64)


"""

sectors = ['S1', 'S2']
regions = ['R1']
Z_multiindex = pd.MultiIndex.from_product(
    [regions, sectors], names=[u'region', u'sector'])

Z = pd.DataFrame(
    data=np.array([
        [150, 500],
        [200, 100]]),
    index=Z_multiindex,
    columns=Z_multiindex
)

categories = ['final demand']
fd_multiindex = pd.MultiIndex.from_product(
    [regions, categories], names=[u'region', u'category'])

Y = pd.DataFrame(
    data=np.array([[0], [0]]),
    index=Z_multiindex,
    columns=fd_multiindex)

io.Z = Z
io.Y = Y

io.calc_all()

# Report
print("Z Table (Industry Transactions):\n", io.Z, "\n")  # input
print("Y Table (Demand): \n", io.Y, "\n")  # input
print("x Vector (Total Output): \n", io.x, "\n")  # x = Z + Y
print("A Table (Normalized Transactions): \n", io.A, "\n")  # A = Z / x
print("L Table (Leontief Inverse): \n", io.L, "\n")  # L = 1 / (I - A)

# Calculate the determinant det(I - A)

I = np.eye(2)

determinant = np.linalg.det(I - io.A)

print("The determinant is ", determinant)