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light touch Market class refactoring #765

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merged 23 commits into from
Aug 13, 2020
Merged

light touch Market class refactoring #765

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98fd4a4
storing sow_var states and initial values in namespace
sbenthall Jul 21, 2020
fddb98d
Merge branch 'master' into sb-market
sbenthall Jul 21, 2020
8feb583
Merge branch 'master' into sb-market
sbenthall Jul 22, 2020
fabec0c
updates to KS model to fit market refactoring
sbenthall Jul 22, 2020
f8343cf
Merge branch 'sb-market' of github.com:sbenthall/HARK into sb-market
sbenthall Jul 22, 2020
9ee55c2
Merge branch 'master' into sb-market
sbenthall Jul 22, 2020
15682cd
update SmallOpenEconomy
sbenthall Jul 22, 2020
7444dc5
const_vars now in dictionary
sbenthall Jul 22, 2020
e6f1022
reap variables to dictionary
sbenthall Jul 23, 2020
0ef77f7
collect sow var dicts in with sow vars
sbenthall Jul 23, 2020
b7b91ab
adding ConsAggShockModel tests for Market history tracking
sbenthall Jul 23, 2020
7b78cd7
fixing trak_vars
sbenthall Jul 23, 2020
2220fa5
millRule returning a tuple of values same size/order as sow_vars
sbenthall Jul 23, 2020
206ca76
Merge branch 'master' into sb-market
sbenthall Jul 23, 2020
3b678d1
missed a sow_var in Small Open
sbenthall Jul 23, 2020
7694a56
Merge branch 'sb-market' of github.com:sbenthall/HARK into sb-market
sbenthall Jul 23, 2020
7e45b5b
Merge branch 'master' into sb-market
llorracc Jul 30, 2020
a6e2de9
replace OrderedDict with dict -- 3.7 dicts ordered by default
sbenthall Jul 30, 2020
3237b56
Merge branch 'sb-market' of github.com:sbenthall/HARK into sb-market
sbenthall Jul 30, 2020
9cc7428
Merge branch 'master' into sb-market
sbenthall Aug 4, 2020
85f204c
Merge branch 'master' into sb-market
sbenthall Aug 5, 2020
6c31ea8
Merge branch 'master' into sb-market
sbenthall Aug 13, 2020
f812249
Merge branch 'master' into sb-market
llorracc Aug 13, 2020
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242 changes: 119 additions & 123 deletions HARK/ConsumptionSaving/ConsAggShockModel.py
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Original file line number Diff line number Diff line change
Expand Up @@ -24,7 +24,7 @@

__all__ = ['MargValueFunc2D', 'AggShockConsumerType', 'AggShockMarkovConsumerType',
'CobbDouglasEconomy', 'SmallOpenEconomy', 'CobbDouglasMarkovEconomy',
'SmallOpenMarkovEconomy', 'CobbDouglasAggVars', 'AggregateSavingRule', 'AggShocksDynamicRule','init_agg_shocks','init_agg_mrkv_shocks', 'init_cobb_douglas','init_mrkv_cobb_douglas']
'SmallOpenMarkovEconomy', 'AggregateSavingRule', 'AggShocksDynamicRule','init_agg_shocks','init_agg_mrkv_shocks', 'init_cobb_douglas','init_mrkv_cobb_douglas']

utility = CRRAutility
utilityP = CRRAutilityP
Expand Down Expand Up @@ -616,7 +616,7 @@ def getEconomyData(self, Economy):
'''
self.T_sim = Economy.act_T # Need to be able to track as many periods as economy runs
self.kInit = Economy.KSS # Initialize simulation assets to steady state
self.MrkvInit = Economy.MrkvNow_init # Starting Markov state for the macroeconomy
self.MrkvInit = Economy.sow_init['MrkvNow'] # Starting Markov state for the macroeconomy
self.Mgrid = Economy.MSS*self.MgridBase # Aggregate market resources grid adjusted around SS capital ratio
self.AFunc = Economy.AFunc # Next period's aggregate savings function
self.DeprFac = Economy.DeprFac # Rate of capital depreciation
Expand Down Expand Up @@ -818,7 +818,7 @@ def getShocks(self):
# Get boolean arrays for current employment states
employed = self.EmpNow.copy()
unemployed = np.logical_not(employed)

# Transition some agents between unemployment and employment
emp_permute = self.emp_permute[self.MrkvPrev][self.MrkvNow]
unemp_permute = self.unemp_permute[self.MrkvPrev][self.MrkvNow]
Expand Down Expand Up @@ -1377,11 +1377,12 @@ def __init__(self,
'''
agents = agents if agents is not None else list()
params = init_cobb_douglas.copy()
params['sow_vars'] = ['MaggNow', 'AaggNow', 'RfreeNow',
'wRteNow', 'PermShkAggNow',
'TranShkAggNow', 'KtoLnow']
params.update(kwds)

Market.__init__(self, agents=agents,
sow_vars=['MaggNow', 'AaggNow', 'RfreeNow',
'wRteNow', 'PermShkAggNow', 'TranShkAggNow', 'KtoLnow'],
reap_vars=['aLvlNow', 'pLvlNow'],
track_vars=['MaggNow', 'AaggNow'],
dyn_vars=['AFunc'],
Expand Down Expand Up @@ -1442,13 +1443,14 @@ def update(self):
self.convertKtoY = lambda KtoY: KtoY**(1.0/(1.0 - self.CapShare)) # converts K/Y to K/L
self.Rfunc = lambda k: (1.0 + self.CapShare*k**(self.CapShare-1.0) - self.DeprFac)
self.wFunc = lambda k: ((1.0-self.CapShare)*k**(self.CapShare))
self.KtoLnow_init = self.kSS
self.MaggNow_init = self.kSS
self.AaggNow_init = self.kSS
self.RfreeNow_init = self.Rfunc(self.kSS)
self.wRteNow_init = self.wFunc(self.kSS)
self.PermShkAggNow_init = 1.0
self.TranShkAggNow_init = 1.0

self.sow_init['KtoLnow'] = self.kSS
self.sow_init['MaggNow'] = self.kSS
self.sow_init['AaggNow'] = self.kSS
self.sow_init['RfreeNow'] = self.Rfunc(self.kSS)
self.sow_init['wRteNow'] = self.wFunc(self.kSS)
self.sow_init['PermShkAggNow'] = 1.0
self.sow_init['TranShkAggNow'] = 1.0
self.makeAggShkDstn()
self.AFunc = AggregateSavingRule(self.intercept_prev, self.slope_prev)

Expand Down Expand Up @@ -1545,10 +1547,20 @@ def calcRandW(self, aLvlNow, pLvlNow):

Returns
-------
AggVarsNow : CobbDouglasAggVars
An object containing the aggregate variables for the upcoming period:
capital-to-labor ratio, interest factor, (normalized) wage rate,
aggregate permanent and transitory shocks.
MaggNow : float
Aggregate market resources for this period normalized by mean permanent income
AaggNow : float
Aggregate savings for this period normalized by mean permanent income
RfreeNow : float
Interest factor on assets in the economy this period.
wRteNow : float
Wage rate for labor in the economy this period.
PermShkAggNow : float
Permanent shock to aggregate labor productivity this period.
TranShkAggNow : float
Transitory shock to aggregate labor productivity this period.
KtoLnow : float
Capital-to-labor ratio in the economy this period.
'''
# Calculate aggregate savings
AaggPrev = np.mean(np.array(aLvlNow))/np.mean(pLvlNow) # End-of-period savings from last period
Expand All @@ -1575,9 +1587,8 @@ def calcRandW(self, aLvlNow, pLvlNow):
self.KtoLnow = KtoLnow # Need to store this as it is a sow variable

# Package the results into an object and return it
AggVarsNow = CobbDouglasAggVars(MaggNow, AaggPrev, KtoLnow, RfreeNow, wRteNow, PermShkAggNow, TranShkAggNow)
return AggVarsNow

return MaggNow, AaggPrev, RfreeNow, wRteNow, PermShkAggNow, TranShkAggNow, KtoLnow

def calcAFunc(self, MaggNow, AaggNow):
'''
Calculate a new aggregate savings rule based on the history
Expand Down Expand Up @@ -1678,12 +1689,12 @@ def update(self):
self.KtoLnow_init = self.kSS
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did I miss one here? i think so

self.Rfunc = ConstantFunction(self.Rfree)
self.wFunc = ConstantFunction(self.wRte)
self.RfreeNow_init = self.Rfunc(self.kSS)
self.wRteNow_init = self.wFunc(self.kSS)
self.MaggNow_init = self.kSS
self.AaggNow_init = self.kSS
self.PermShkAggNow_init = 1.0
self.TranShkAggNow_init = 1.0
self.sow_init['RfreeNow'] = self.Rfunc(self.kSS)
self.sow_init['wRteNow'] = self.wFunc(self.kSS)
self.sow_init['MaggNow'] = self.kSS
self.sow_init['AaggNow'] = self.kSS
self.sow_init['PermShkAggNow'] = 1.0
self.sow_init['TranShkAggNow'] = 1.0
self.makeAggShkDstn()
self.AFunc = ConstantFunction(1.0)

Expand Down Expand Up @@ -1779,8 +1790,21 @@ def getAggShocks(self):

Returns
-------
AggVarsNow : CobbDouglasAggVars
Aggregate state and shock variables for this period.
MaggNow : float
Aggregate market resources for this period normalized by mean permanent income
AaggNow : float
Aggregate savings for this period normalized by mean permanent income
RfreeNow : float
Interest factor on assets in the economy this period.
wRteNow : float
Wage rate for labor in the economy this period.
PermShkAggNow : float
Permanent shock to aggregate labor productivity this period.
TranShkAggNow : float
Transitory shock to aggregate labor productivity this period.
KtoLnow : float
Capital-to-labor ratio in the economy this period.

'''
# Get this period's aggregate shocks
PermShkAggNow = self.PermShkAggHist[self.Shk_idx]
Expand All @@ -1796,9 +1820,7 @@ def getAggShocks(self):
MaggNow = 1.0
KtoLnow = 1.0/PermShkAggNow

# Package the results into an object and return it
AggVarsNow = CobbDouglasAggVars(MaggNow, AaggNow, KtoLnow, RfreeNow, wRteNow, PermShkAggNow, TranShkAggNow)
return AggVarsNow
return MaggNow, AaggNow, RfreeNow, wRteNow, PermShkAggNow, TranShkAggNow, KtoLnow

# Make a dictionary to specify a Markov Cobb-Douglas economy
init_mrkv_cobb_douglas = init_cobb_douglas.copy()
Expand All @@ -1825,6 +1847,15 @@ def __init__(self,
agents=None,
tolerance=0.0001,
act_T=1200,
sow_vars=['MaggNow',
'AaggNow',
'RfreeNow',
'wRteNow',
'PermShkAggNow',
'TranShkAggNow',
'KtoLnow',
'MrkvNow' # This one is new
],
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When all the sow_vars are "Now", "Now" can be left out of the name...

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But I don't dare.

**kwds):
'''
Make a new instance of CobbDouglasMarkovEconomy by filling in attributes
Expand All @@ -1849,8 +1880,14 @@ def __init__(self,
params = init_mrkv_cobb_douglas.copy()
params.update(kwds)

CobbDouglasEconomy.__init__(self, agents=agents, tolerance=tolerance, act_T=act_T, **params)
self.sow_vars.append('MrkvNow')
CobbDouglasEconomy.__init__(self,
agents=agents,
tolerance=tolerance,
act_T=act_T,
sow_vars = sow_vars,
**params)

self.sow_init['MrkvNow'] = params['MrkvNow_init']

def update(self):
'''
Expand Down Expand Up @@ -2011,7 +2048,7 @@ def makeMrkvHist(self):
cutoffs = np.cumsum(self.MrkvArray, axis=1)
loops = 0
go = True
MrkvNow = self.MrkvNow_init
MrkvNow = self.sow_init['MrkvNow']
t = 0
StateCount = self.MrkvArray.shape[0]

Expand Down Expand Up @@ -2068,11 +2105,26 @@ def millRule(self, aLvlNow, pLvlNow):
and adds the Markov state index.

See documentation for calcRandW for more information.

Returns
-------
Mnow : float
Aggregate market resources for this period.
Aprev : float
Aggregate savings for the prior period.
KtoLnow : float
Capital-to-labor ratio in the economy this period.
Rnow : float
Interest factor on assets in the economy this period.
Wnow : float
Wage rate for labor in the economy this period.
MrkvNow : int
Binary indicator for bad (0) or good (1) macroeconomic state.
'''
MrkvNow = self.MrkvNow_hist[self.Shk_idx]
temp = self.calcRandW(aLvlNow, pLvlNow)
temp(MrkvNow=MrkvNow)
return temp

return temp + (MrkvNow,)

def calcAFunc(self, MaggNow, AaggNow):
'''
Expand Down Expand Up @@ -2247,14 +2299,14 @@ def update(self):
self.convertKtoY = lambda KtoY: KtoY**(1.0/(1.0 - self.CapShare)) # converts K/Y to K/L
self.rFunc = lambda k: self.CapShare*k**(self.CapShare-1.0)
self.Wfunc = lambda k: ((1.0-self.CapShare)*k**(self.CapShare))
self.KtoLnow_init = self.KtoLSS
self.Mnow_init = self.MSS
self.Aprev_init = self.KSS
self.Rnow_init = self.RSS
self.Wnow_init = self.WSS
self.sow_init['KtoLnow'] = self.KtoLSS
self.sow_init['Mnow'] = self.MSS
self.sow_init['Aprev'] = self.KSS
self.sow_init['Rnow'] = self.RSS
self.sow_init['Wnow'] = self.WSS
self.PermShkAggNow_init = 1.0
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Missed these?

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No, not missing because these are not sow_vars in KS

self.TranShkAggNow_init = 1.0
self.Mrkv_init = 0
self.sow_init['MrkvNow'] = 0
self.makeMrkvArray()

def reset(self):
Expand Down Expand Up @@ -2339,7 +2391,21 @@ def millRule(self, aNow, EmpNow):
wage rate based on each agent's current state. Just calls calcRandW().

See documentation for calcRandW for more information.

Returns
-------
Mnow : float
Aggregate market resources for this period.
Aprev : float
Aggregate savings for the prior period.
MrkvNow : int
Binary indicator for bad (0) or good (1) macroeconomic state.
Rnow : float
Interest factor on assets in the economy this period.
Wnow : float
Wage rate for labor in the economy this period.
'''

return self.calcRandW(aNow, EmpNow)

def calcDynamics(self, Mnow, Aprev):
Expand All @@ -2366,10 +2432,16 @@ def calcRandW(self, aNow, EmpNow):

Returns
-------
AggVarsNow : CobbDouglasAggVars
An object containing the aggregate variables for the upcoming period:
capital-to-labor ratio, interest factor, (normalized) wage rate,
aggregate permanent and transitory shocks.
Mnow : float
Aggregate market resources for this period.
Aprev : float
Aggregate savings for the prior period.
MrkvNow : int
Binary indicator for bad (0) or good (1) macroeconomic state.
Rnow : float
Interest factor on assets in the economy this period.
Wnow : float
Wage rate for labor in the economy this period.
'''
# Calculate aggregate savings
Aprev = np.mean(np.array(aNow)) # End-of-period savings from last period
Expand Down Expand Up @@ -2397,9 +2469,8 @@ def calcRandW(self, aNow, EmpNow):
Mnow = Rnow*AggK + Wnow*AggL
self.KtoLnow = KtoLnow # Need to store this as it is a sow variable

# Package the results into an object and return it
AggVarsNow = KrusellSmithAggVars(Mnow, Aprev, KtoLnow, Rnow, Wnow, MrkvNow)
return AggVarsNow
# Returns a tuple of these values
return Mnow, Aprev, MrkvNow, Rnow, Wnow

def calcAFunc(self, Mnow, Aprev):
'''
Expand Down Expand Up @@ -2455,81 +2526,6 @@ def calcAFunc(self, Mnow, Aprev):
return AggShocksDynamicRule(AFunc_list)


class CobbDouglasAggVars(HARKobject):
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replaced these container classes with tuples same size/order as sow_vars

'''
A simple class for holding the relevant aggregate variables that should be
passed from the market to each type. Includes the capital-to-labor ratio,
the interest factor, the wage rate, and the aggregate permanent and tran-
sitory shocks.
'''
def __init__(self, MaggNow, AaggNow, KtoLnow, RfreeNow, wRteNow, PermShkAggNow, TranShkAggNow):
'''
Make a new instance of CobbDouglasAggVars.

Parameters
----------
MaggNow : float
Aggregate market resources for this period normalized by mean permanent income
AaggNow : float
Aggregate savings for this period normalized by mean permanent income
KtoLnow : float
Capital-to-labor ratio in the economy this period.
RfreeNow : float
Interest factor on assets in the economy this period.
wRteNow : float
Wage rate for labor in the economy this period.
PermShkAggNow : float
Permanent shock to aggregate labor productivity this period.
TranShkAggNow : float
Transitory shock to aggregate labor productivity this period.

Returns
-------
None
'''
self.MaggNow = MaggNow
self.AaggNow = AaggNow
self.KtoLnow = KtoLnow
self.RfreeNow = RfreeNow
self.wRteNow = wRteNow
self.PermShkAggNow = PermShkAggNow
self.TranShkAggNow = TranShkAggNow


class KrusellSmithAggVars():
'''
Just a container class for aggregate data in the Krusell-Smith model.
'''
def __init__(self, Mnow, Aprev, KtoLnow, Rnow, Wnow, MrkvNow):
'''
Make a new instance of KrusellSmithAggVars.

Parameters
----------
Mnow : float
Aggregate market resources for this period.
Aprev : float
Aggregate savings for the prior period.
KtoLnow : float
Capital-to-labor ratio in the economy this period.
Rnow : float
Interest factor on assets in the economy this period.
Wnow : float
Wage rate for labor in the economy this period.
MrkvNow : int
Binary indicator for bad (0) or good (1) macroeconomic state.

Returns
-------
None
'''
self.Mnow = Mnow
self.Aprev = Aprev
self.KtoLnow = KtoLnow
self.Rnow = Rnow
self.Wnow = Wnow
self.MrkvNow = MrkvNow


class AggregateSavingRule(HARKobject):
'''
Expand Down
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