class testPerfForesightConsumerType(unittest.TestCase):
def setUp(self):
self.agent = PerfForesightConsumerType()
self.agent_infinite = PerfForesightConsumerType(cycles=0)
PF_dictionary = {
"CRRA": 2.5,
"DiscFac": 0.96,
"Rfree": 1.03,
"LivPrb": [0.98],
"PermGroFac": [1.01],
"T_cycle": 1,
"cycles": 0,
"AgentCount": 10000,
}
self.agent_alt = PerfForesightConsumerType(**PF_dictionary)
def test_default_solution(self):
self.agent.solve()
c = self.agent.solution[0].cFunc
self.assertEqual(c.x_list[0], -0.9805825242718447)
self.assertEqual(c.x_list[1], 0.01941747572815533)
self.assertEqual(c.y_list[0], 0)
self.assertEqual(c.y_list[1], 0.511321002804608)
self.assertEqual(c.decay_extrap, False)
def test_another_solution(self):
self.agent_alt.DiscFac = 0.90
self.agent_alt.solve()
self.assertAlmostEqual(self.agent_alt.solution[0].cFunc(10).tolist(),
3.9750093524820787)
def test_check_conditions(self):
self.agent_infinite.check_conditions()
self.assertTrue(self.agent_infinite.conditions["AIC"])
self.assertTrue(self.agent_infinite.conditions["GICRaw"])
self.assertTrue(self.agent_infinite.conditions["RIC"])
self.assertTrue(self.agent_infinite.conditions["FHWC"])
def test_simulation(self):
self.agent_infinite.solve()
# Create parameter values necessary for simulation
SimulationParams = {
"AgentCount": 10000, # Number of agents of this type
"T_sim": 120, # Number of periods to simulate
"aNrmInitMean": -6.0, # Mean of log initial assets
"aNrmInitStd": 1.0, # Standard deviation of log initial assets
"pLvlInitMean": 0.0, # Mean of log initial permanent income
"pLvlInitStd":
0.0, # Standard deviation of log initial permanent income
"PermGroFacAgg": 1.0, # Aggregate permanent income growth factor
"T_age":
None, # Age after which simulated agents are automatically killed
}
self.agent_infinite.assign_parameters(
**SimulationParams
) # This implicitly uses the assign_parameters method of AgentType
# Create PFexample object
self.agent_infinite.track_vars = ["mNrm"]
self.agent_infinite.initialize_sim()
self.agent_infinite.simulate()
self.assertAlmostEqual(
np.mean(self.agent_infinite.history["mNrm"], axis=1)[40],
-23.008063500363942,
)
self.assertAlmostEqual(
np.mean(self.agent_infinite.history["mNrm"], axis=1)[100],
-27.164608851546927,
)
## Try now with the manipulation at time step 80
self.agent_infinite.initialize_sim()
self.agent_infinite.simulate(80)
# This actually does nothing because aNrmNow is
# epiphenomenal. Probably should change mNrmNow instead
self.agent_infinite.state_now['aNrm'] += (-5.0)
self.agent_infinite.simulate(40)
self.assertAlmostEqual(
np.mean(self.agent_infinite.history["mNrm"], axis=1)[40],
-23.008063500363942,
)
self.assertAlmostEqual(
np.mean(self.agent_infinite.history["mNrm"], axis=1)[100],
-29.140261331951606,
)
def test_stable_points(self):
# Solve the constrained agent. Stable points exists only with a
# borrowing constraint.
constrained_agent = PerfForesightConsumerType(cycles=0,
BoroCnstArt=0.0)
constrained_agent.solve()
# Check against pre-computed values.
self.assertEqual(constrained_agent.solution[0].mNrmStE, 1.0)
# Check that they are both the same, since the problem is deterministic
self.assertEqual(constrained_agent.solution[0].mNrmStE,
constrained_agent.solution[0].mNrmTrg)
PFGICRawHoldsFHWCFailsRICFails_par = copy(base_params)
# Replace parameters.
PFGICRawHoldsFHWCFailsRICFails_par['Rfree'] = 0.98
PFGICRawHoldsFHWCFailsRICFails_par['DiscFac'] = 1
PFGICRawHoldsFHWCFailsRICFails_par['PermGroFac'] = [0.99]
PFGICRawHoldsFHWCFailsRICFails_par['CRRA'] = 2
PFGICRawHoldsFHWCFailsRICFails_par['BoroCnstArt'] = 0
PFGICRawHoldsFHWCFailsRICFails_par['T_cycle'] = 0
PFGICRawHoldsFHWCFailsRICFails_par['cycles'] = 0
PFGICRawHoldsFHWCFailsRICFails_par['quiet'] = False
# Create the agent
RichButPatientPFConstrainedAgent = PerfForesightConsumerType(**PFGICRawHoldsFHWCFailsRICFails_par)
# Check conditions
RichButPatientPFConstrainedAgent.check_conditions(verbose=3)
# Solve
RichButPatientPFConstrainedAgent.solve()
# Plot
mPlotMin, mPlotMax = 1, 9.5
plt.figure(figsize=(8, 4))
m_grid = np.linspace(mPlotMin, mPlotMax, 500)
plt.plot(m_grid-1, RichButPatientPFConstrainedAgent.solution[0].cFunc(m_grid), color="black")
plt.text(mPlotMax-1+0.05, 1, r"$b$", fontsize=26)
plt.text(mPlotMin-1, 1.017, r"$c$", fontsize=26)
plt.xlim(mPlotMin-1, mPlotMax-1)
plt.ylim(mPlotMin, 1.016)
make('PFGICRawHoldsFHWCFailsRICFails')