def test_solve_farmer_model_y_t(setup_solve_farmer_model,
expected_solve_farmer_model):
calc_s_t, calc_c_t, calc_k_t, calc_y_t = solve_farmer_model(
**setup_solve_farmer_model)
assert_almost_equal(calc_y_t,
expected_solve_farmer_model["y_t"],
decimal=6)
# Set parameter values.
beta = 0.95
alpha = 0.3
delta = 0.1
rho = 0.9
# Set the number of time periods to simulate.
T = 100
# first 10 periods given
inital_productivity_state = [
0, -0.005, -0.009, -0.013, -0.022, -0.021, -0.019, -0.011, -0.012, -0.003
]
# Get simulation result.
s_t, c_t, k_t, y_t = solve_farmer_model(alpha, beta, delta, rho, T,
inital_productivity_state)
# plot time series.
time_1 = np.array(list(range(T)))
time_2 = np.array(list(range(T + 1)))
sns.set_style("whitegrid")
fig, ax = plt.subplots(figsize=(T / 8, T / 16))
# Productivity state, consumption, capital and output against time.
ax.plot(time_1,
s_t,
label="productivity state",
color="C7",
alpha=0.7,
linestyle='dashdot')