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WealthPortfolioConsumerType uses constructors #1498

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Sep 20, 2024
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WealthPortfolioConsumerType uses constructors #1498

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157 changes: 147 additions & 10 deletions HARK/ConsumptionSaving/ConsWealthPortfolioModel.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,8 +3,8 @@
import numpy as np
from HARK.ConsumptionSaving.ConsPortfolioModel import (
PortfolioConsumerType,
init_portfolio,
PortfolioSolution,
make_portfolio_solution_terminal,
)
from HARK.distribution import expected
from HARK.interpolation import (
Expand All @@ -14,11 +14,22 @@
MargValueFuncCRRA,
ValueFuncCRRA,
)
from HARK.Calibration.Assets.AssetProcesses import (
make_lognormal_RiskyDstn,
combine_IncShkDstn_and_RiskyDstn,
calc_ShareLimit_for_CRRA,
)
from HARK.Calibration.Income.IncomeProcesses import (
construct_lognormal_income_process_unemployment,
get_PermShkDstn_from_IncShkDstn,
get_TranShkDstn_from_IncShkDstn,
)
from HARK.ConsumptionSaving.ConsRiskyAssetModel import (
make_simple_ShareGrid,
)
from HARK.rewards import UtilityFuncCRRA
from HARK.utilities import NullFunc
from HARK.utilities import NullFunc, make_assets_grid


import numpy as np
from HARK.interpolation import LinearInterp


Expand Down Expand Up @@ -100,6 +111,129 @@ def __call__(self, omega):
return np.nan_to_num(chi)


# Trivial constructor function
def make_ChiFromOmega_function(CRRA, WealthShare, ChiFromOmega_N, ChiFromOmega_bound):
return ChiFromOmegaFunction(
CRRA, WealthShare, N=ChiFromOmega_N, z_bound=ChiFromOmega_bound
)


###############################################################################

# Make a dictionary of constructors for the wealth-in-utility portfolio choice consumer type
WealthPortfolioConsumerType_constructors_default = {
"IncShkDstn": construct_lognormal_income_process_unemployment,
"PermShkDstn": get_PermShkDstn_from_IncShkDstn,
"TranShkDstn": get_TranShkDstn_from_IncShkDstn,
"aXtraGrid": make_assets_grid,
"RiskyDstn": make_lognormal_RiskyDstn,
"ShockDstn": combine_IncShkDstn_and_RiskyDstn,
"ShareLimit": calc_ShareLimit_for_CRRA,
"ShareGrid": make_simple_ShareGrid,
"ChiFunc": make_ChiFromOmega_function,
"solution_terminal": make_portfolio_solution_terminal,
}

# Default parameters to make IncShkDstn using construct_lognormal_income_process_unemployment
WealthPortfolioConsumerType_IncShkDstn_default = {
"PermShkStd": [0.1], # Standard deviation of log permanent income shocks
"PermShkCount": 7, # Number of points in discrete approximation to permanent income shocks
"TranShkStd": [0.1], # Standard deviation of log transitory income shocks
"TranShkCount": 7, # Number of points in discrete approximation to transitory income shocks
"UnempPrb": 0.05, # Probability of unemployment while working
"IncUnemp": 0.3, # Unemployment benefits replacement rate while working
"T_retire": 0, # Period of retirement (0 --> no retirement)
"UnempPrbRet": 0.005, # Probability of "unemployment" while retired
"IncUnempRet": 0.0, # "Unemployment" benefits when retired
}

# Default parameters to make aXtraGrid using make_assets_grid
WealthPortfolioConsumerType_aXtraGrid_default = {
"aXtraMin": 0.001, # Minimum end-of-period "assets above minimum" value
"aXtraMax": 100, # Maximum end-of-period "assets above minimum" value
"aXtraNestFac": 1, # Exponential nesting factor for aXtraGrid
"aXtraCount": 200, # Number of points in the grid of "assets above minimum"
"aXtraExtra": None, # Additional other values to add in grid (optional)
}

# Default parameters to make RiskyDstn with make_lognormal_RiskyDstn (and uniform ShareGrid)
WealthPortfolioConsumerType_RiskyDstn_default = {
"RiskyAvg": 1.08, # Mean return factor of risky asset
"RiskyStd": 0.18362634887, # Stdev of log returns on risky asset
"RiskyCount": 5, # Number of integration nodes to use in approximation of risky returns
}

WealthPortfolioConsumerType_ShareGrid_default = {
"ShareCount": 25 # Number of discrete points in the risky share approximation
}

# Default parameters to make ChiFunc with make_ChiFromOmega_function
WealthPortfolioConsumerType_ChiFunc_default = {
"ChiFromOmega_N": 501, # Number of gridpoints in chi-from-omega function
"ChiFromOmega_bound": 15, # Highest gridpoint to use for it
}

# Make a dictionary to specify a risky asset consumer type
WealthPortfolioConsumerType_solving_default = {
# BASIC HARK PARAMETERS REQUIRED TO SOLVE THE MODEL
"cycles": 1, # Finite, non-cyclic model
"T_cycle": 1, # Number of periods in the cycle for this agent type
"constructors": WealthPortfolioConsumerType_constructors_default, # See dictionary above
# PRIMITIVE RAW PARAMETERS REQUIRED TO SOLVE THE MODEL
"CRRA": 5.0, # Coefficient of relative risk aversion
"Rfree": 1.03, # Return factor on risk free asset
"DiscFac": 0.90, # Intertemporal discount factor
"LivPrb": [0.98], # Survival probability after each period
"PermGroFac": [1.01], # Permanent income growth factor
"BoroCnstArt": 0.0, # Artificial borrowing constraint
"WealthShare": 0.5, # Share of wealth in Cobb-Douglas aggregator in utility function
"WealthShift": 0.1, # Shifter for wealth in utility function
"DiscreteShareBool": False, # Whether risky asset share is restricted to discrete values
"vFuncBool": False, # Whether to calculate the value function during solution
"CubicBool": False, # Whether to use cubic spline interpolation when True
# (Uses linear spline interpolation for cFunc when False)
"AdjustPrb": 1.0, # Probability that the agent can update their risky portfolio share each period
"sim_common_Rrisky": True, # Whether risky returns have a shared/common value across agents
}
WealthPortfolioConsumerType_simulation_default = {
# PARAMETERS REQUIRED TO SIMULATE THE MODEL
"AgentCount": 10000, # Number of agents of this type
"T_age": None, # Age after which simulated agents are automatically killed
"aNrmInitMean": 0.0, # 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
# (The portion of PermGroFac attributable to aggregate productivity growth)
"NewbornTransShk": False, # Whether Newborns have transitory shock
# ADDITIONAL OPTIONAL PARAMETERS
"PerfMITShk": False, # Do Perfect Foresight MIT Shock
# (Forces Newborns to follow solution path of the agent they replaced if True)
"neutral_measure": False, # Whether to use permanent income neutral measure (see Harmenberg 2021)
}

# Assemble the default dictionary
WealthPortfolioConsumerType_default = {}
WealthPortfolioConsumerType_default.update(WealthPortfolioConsumerType_solving_default)
WealthPortfolioConsumerType_default.update(
WealthPortfolioConsumerType_simulation_default
)
WealthPortfolioConsumerType_default.update(
WealthPortfolioConsumerType_aXtraGrid_default
)
WealthPortfolioConsumerType_default.update(
WealthPortfolioConsumerType_ShareGrid_default
)
WealthPortfolioConsumerType_default.update(
WealthPortfolioConsumerType_IncShkDstn_default
)
WealthPortfolioConsumerType_default.update(
WealthPortfolioConsumerType_RiskyDstn_default
)
WealthPortfolioConsumerType_default.update(WealthPortfolioConsumerType_ChiFunc_default)
init_wealth_portfolio = WealthPortfolioConsumerType_default


class WealthPortfolioConsumerType(PortfolioConsumerType):
time_inv_ = deepcopy(PortfolioConsumerType.time_inv_)
time_inv_ = time_inv_ + ["WealthShare", "WealthShift", "ChiFunc"]
Expand All @@ -114,10 +248,18 @@ def __init__(self, **kwds):

self.solve_one_period = solve_one_period_WealthPortfolio

def update(self):
super().update()
self.update_ChiFunc()

def update_ChiFunc(self):
if self.WealthShare == 0.0:
self.ChiFunc = None
else:
self.ChiFunc = ChiFromOmegaFunction(self.CRRA, self.WealthShare)
self.construct("ChiFunc")


###############################################################################


def utility(c, a, CRRA, share=0.0, intercept=0.0):
Expand Down Expand Up @@ -502,8 +644,3 @@ def solve_one_period_WealthPortfolio(
vFuncAdj=vFuncNow,
)
return solution_now


init_wealth_portfolio = init_portfolio.copy()
init_wealth_portfolio["WealthShare"] = 0.5
init_wealth_portfolio["WealthShift"] = 0.1
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