def setUp(self):
"""
Prepare to compare the models by initializing and solving them
"""
# Set up and solve infinite type
# Define a test dictionary that should have the same solution in the
# perfect foresight and idiosyncratic shocks models.
test_dictionary = deepcopy(init_idiosyncratic_shocks)
test_dictionary['LivPrb'] = [1.]
test_dictionary['DiscFac'] = 0.955
test_dictionary['PermGroFac'] = [1.]
test_dictionary['PermShkStd'] = [0.]
test_dictionary['TranShkStd'] = [0.]
test_dictionary['UnempPrb'] = 0.
test_dictionary['T_cycle'] = 1
test_dictionary['T_retire'] = 0
test_dictionary['BoroCnstArt'] = None
InfiniteType = IndShockConsumerType(**test_dictionary)
InfiniteType.cycles = 0
InfiniteType.updateIncomeProcess()
InfiniteType.solve()
InfiniteType.unpackcFunc()
# Make and solve a perfect foresight consumer type with the same parameters
PerfectForesightType = PerfForesightConsumerType(**test_dictionary)
PerfectForesightType.cycles = 0
PerfectForesightType.solve()
PerfectForesightType.unpackcFunc()
self.InfiniteType = InfiniteType
self.PerfectForesightType = PerfectForesightType
def __init__(self):
PFexample = PerfForesightConsumerType(
) # set up a consumer type and use default parameteres
PFexample.cycles = 0 # Make this type have an infinite horizon
PFexample.DiscFac = 0.05
PFexample.PermGroFac = [0.7]
PFexample.solve() # solve the consumer's problem
PFexample.unpackcFunc() # unpack the consumption function
self.cFunc = PFexample.solution[0].cFunc
self.a0 = self.cFunc(0)
self.a1 = self.cFunc(1) - self.cFunc(0)
def __init__(self, Rfree=1.001, CRRA=2):
PFaux = PerfForesightConsumerType(
) # set up a consumer type and use default parameteres
PFaux.cycles = 0 # Make this type have an infinite horizon
PFaux.DiscFac = 1 / Rfree
PFaux.Rfree = Rfree
PFaux.LivPrb = [1.0]
PFaux.PermGroFac = [1.0]
PFaux.CRRA = CRRA
PFaux.solve() # solve the consumer's problem
PFaux.unpackcFunc() # unpack the consumption function
self.cFunc = PFaux.solution[0].cFunc
# %%
do_simulation = True
# %%
# Make and solve an example perfect foresight consumer
PFexample = PerfForesightConsumerType()
# Make this type have an infinite horizon
PFexample.cycles = 0
# %%
start_time = time()
PFexample.solve()
end_time = time()
print("Solving a perfect foresight consumer took " +
mystr(end_time - start_time) + " seconds.")
PFexample.unpackcFunc()
PFexample.timeFwd()
# %%
# Plot the perfect foresight consumption function
print("Perfect foresight consumption function:")
mMin = PFexample.solution[0].mNrmMin
plotFuncs(PFexample.cFunc[0], mMin, mMin + 10)
# %%
if do_simulation:
PFexample.T_sim = 120 # Set number of simulation periods
PFexample.track_vars = ["mNrmNow"]
PFexample.initializeSim()
PFexample.simulate()