Skip to content

Commit

Permalink
Merge pull request #535 from econ-ark/FinalUpdatesToCheckConditions
Browse files Browse the repository at this point in the history 
Final updates for checkConditions before turnover to Seb and Mridul
  • Loading branch information
@llorracc
llorracc authored Feb 20, 2020
2 parents d1a8eb9 + 9d7f61c commit 1fce464
Showing 1 changed file with 55 additions and 61 deletions.
116 changes: 55 additions & 61 deletions HARK/ConsumptionSaving/ConsIndShockModel.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -1852,10 +1852,10 @@ def getPostStates(self):

def checkConditions(self,verbose=False,verbose_reference=False,public_call=False):
'''
This method checks whether the instance's type satisfies the Growth Impatience Condition
(GIC), Return Impatience Condition (RIC), Absolute Impatience Condition (AIC), Return
Impatience Condition (RIC), Finite Human Wealth Condition (FHWC) and Finite Value of
Autarky Condition (FVAC). Depending on the configuration of parameter values, some
This method checks whether the instance's type satisfies the Absolute Impatience Condition (AIC),
the Return Impatience Condition (RIC), the Finite Human Wealth Condition (FHWC) and the perfect foresight
model's version of the Finite Value of the Growth Impatience Condition (GIC_PF) and
Autarky Condition (FVAC_PF). Depending on the configuration of parameter values, some
combination of these conditions must be satisfied in order for the problem to have
a nondegenerate solution. To check which conditions are required, in the verbose mode
a reference to the relevant theoretical literature is made.
Expand Down Expand Up @@ -1902,22 +1902,22 @@ def checkConditions(self,verbose=False,verbose_reference=False,public_call=False
print()

#Evaluate and report on the Growth Impatience Condition
GIF = Thorn/self.PermGroFac[0]
self.GIF = GIF
GIFPF = Thorn/self.PermGroFac[0]
self.GIFPF = GIFPF

if GIF<1:
self.GIC = True
if GIFPF<1:
self.GICPF = True
if public_call or verbose:
print('The value of the Growth Impatience Factor for the supplied parameter values satisfies the Growth Impatience Condition.', end = " ")
print('The value of the Growth Impatience Factor for the supplied parameter values satisfies the Perfect Foresight Growth Impatience Condition.', end = " ")
if verbose:
print(' Therefore, the ratio of individual wealth to permanent income will fall indefinitely.')
print(' Therefore, for a perfect foresight consumer, the ratio of individual wealth to permanent income will fall indefinitely.')
print()
else:
self.GIC = False
self.GICPF = False
violated = True
print('The given parameter values violate the Growth Impatience Condition for this consumer type; the GIF is: %2.4f' % (GIF), end = " ")
print('The given parameter values violate the Perfect Foresight Growth Impatience Condition for this consumer type; the GIFPF is: %2.4f' % (GIFPF), end = " ")
if verbose:
print(' Therefore, the ratio of individual wealth to permanent income is expected to grow toward infinity.')
print(' Therefore, for a perfect foresight consumer the ratio of individual wealth to permanent income is expected to grow toward infinity.')
print()


Expand Down Expand Up @@ -2251,8 +2251,7 @@ def preSolve(self):

def checkConditions(self,verbose=False,public_call=True):
'''
This method checks whether the instance's type satisfies the Growth Impatience Condition
(GIC), Return Impatience Condition (RIC), Absolute Impatience Condition (AIC), Weak Return
This method checks whether the instance's type satisfies the Absolute Impatience Condition (AIC), Weak Return
Impatience Condition (WRIC), Finite Human Wealth Condition (FHWC) and Finite Value of
Autarky Condition (FVAC). When combinations of these conditions are satisfied, the
solution to the problem exhibits different characteristics. (For an exposition of the
Expand Down Expand Up @@ -2289,70 +2288,70 @@ def checkConditions(self,verbose=False,public_call=True):
# [url]/#Pat, adjusted to include mortality
# Thorn = ((self.Rfree/self.LivPrb[0])*(self.DiscFac*self.LivPrb[0]))**(1/self.CRRA)
Thorn = ((self.Rfree*self.DiscFac))**(1/self.CRRA)
GIF = Thorn/(self.PermGroFac[0] ) # [url]/#GIF
GIFPF = Thorn/(self.PermGroFac[0] ) # [url]/#GIF
GIFInd = Thorn/(self.PermGroFac[0]*InvEPermShkInv) # [url]/#GIFI
GIFAgg = Thorn*self.LivPrb[0]/self.PermGroFac[0] # [url]#/GIFA
GIFAgg = Thorn*self.LivPrb[0]/self.PermGroFac[0] # Lower bound of aggregate wealth growth if all inheritances squandered

# self.Rnorm = self.Rfree*EPermShkInv/(self.PermGroFac[0]*self.LivPrb[0])
self.GIF = GIF
self.GIFInd = GIFInd
self.GIFAgg = GIFAgg
self.Thorn = Thorn
self.PermGroFacAdj = PermGroFacAdj
self.EPermShkInv = EPermShkInv
self.InvEPermShkInv = InvEPermShkInv
self.DiscFacGIFMax = ((self.PermGroFac[0] )**(self.CRRA))/(self.Rfree) # DiscFac at growth impatience knife edge
self.DiscFacGIFIMax = ((self.PermGroFac[0]*InvEPermShkInv)**(self.CRRA))/(self.Rfree) # DiscFac at growth impatience knife edge
self.DiscFacGIFAMax = ((self.PermGroFac[0] )**(self.CRRA))/(self.Rfree*self.LivPrb[0]) # DiscFac at growth impatience knife edge
# self.Rnorm = self.Rfree*EPermShkInv/(self.PermGroFac[0]*self.LivPrb[0])
self.GIFPF = GIFPF
self.GIFInd = GIFInd
self.GIFAgg = GIFAgg
self.Thorn = Thorn
self.PermGroFacAdj = PermGroFacAdj
self.EPermShkInv = EPermShkInv
self.InvEPermShkInv = InvEPermShkInv
self.DiscFacGIFPFMax = ((self.PermGroFac[0] )**(self.CRRA))/(self.Rfree) # DiscFac at growth impatience knife edge
self.DiscFacGIFIndMax = ((self.PermGroFac[0]*InvEPermShkInv)**(self.CRRA))/(self.Rfree) # DiscFac at growth impatience knife edge
self.DiscFacGIFAggMax = ((self.PermGroFac[0] )**(self.CRRA))/(self.Rfree*self.LivPrb[0]) # DiscFac at growth impatience knife edge

#Evaluate and report on the Growth Impatience Condition
# [url]/#GIC
if GIF<=1:
self.GIC = True
if GIFPF<1:
self.GICPF = True
if public_call or verbose:
print('The value of the Growth Impatience Factor for the supplied parameter values satisfies the Growth Impatience Condition.', end = " ")
print('The value of the Perfect Foresight Growth Impatience Factor for the supplied parameter values satisfies the Perfect Foresight Growth Impatience Condition.', end = " ")
if verbose:
print('Therefore, a target level of the ratio of expected market resources to expected permanent income exists (see '+url+'/#onetarget).')
print(' Therefore, in the absence of any risk, the ratio of individual wealth to permanent income would fall indefinitely.')
print()
else:
self.GIC = False
self.GICPF = False
violated = True
print('The given parameter values violate the Growth Impatience Condition; the GIF is: %2.4f' % (GIF), end = " ")
print('The given parameter values violate the Perfect Foresight Growth Impatience Condition; the GIFPF is: %2.4f' % (GIFPF), end = " ")
if verbose:
print('')
print('Therefore, a target level of wealth does not exist. (see '+url+'/#onetarget)')
print('Therefore, the ratio of wealth to permanent income approaches infinity in the perfect foresight model. (see '+url+' for more).')
print()

if GIFInd<=1:
self.GICInd = True
if public_call or verbose:
print('The value of the Individual Growth Impatience Factor for the supplied parameter values satisfies the Individual Growth Impatience Condition.', end = " ")
if verbose:
print('Therefore, a target level of the individual market resources ratio m exists (see '+url+'/#onetarget).')
print('Therefore, a target level of the individual market resources ratio m exists (see '+url+'/#onetarget for more).')
print()
else:
self.GICInd = False
violated = True
print('The given parameter values violate the Individual Growth Impatience Condition; the GIFInd is: %2.4f' % (GIFInd), end = " ")
if verbose:
print('')
print('Therefore, a target ratio of individual market resources to individual permanent income does not exist. (see '+url+'/#onetarget)')
print('Therefore, a target ratio of individual market resources to individual permanent income does not exist. (see '+url+'/#onetarget for more).')
print()

if GIFAgg<=1:
self.GICAgg = True
if public_call or verbose:
print('The value of the Aggregate Growth Impatience Factor for the supplied parameter values satisfies the Aggregate Growth Impatience Condition.', end = " ")
if verbose:
print('Therefore, it is possible that a target level of the ratio of expected market resources to expected permanent income exists (see '+url+'/#onetarget).')
print('Therefore, it is possible that a target level of the ratio of aggregate market resources to aggregate permanent income exists.') # Need to provide reference
print()
else:
self.GICAgg = False
violated = True
print('The given parameter values violate the Aggregate Growth Impatience Condition; the GIFAgg is: %2.4f' % (GIFAgg), end = " ")
if verbose:
print('')
print('Therefore, a target ratio of aggregate resources to aggreg permanent income does not exist. (see '+url+'/#onetarget)')
print('Therefore, a target ratio of aggregate resources to aggregate permanent income does not exist.') # Need to provide reference
print()

#Evaluate and report on the Weak Return Impatience Condition
Expand All @@ -2362,15 +2361,15 @@ def checkConditions(self,verbose=False,public_call=True):
if WRIF<=1:
self.WRIC = True
if public_call or verbose:
print('The Weak Return Impatience Factor value for the supplied parameter values satisfies the Weak Return Impatience Condition (see '+url+'/#WRIC).')
print('The Weak Return Impatience Factor value for the supplied parameter values satisfies the Weak Return Impatience Condition (see '+url+'/#WRIC for more).')
print()
else:
self.WRIC = False
violated = True
print('The given type violates the Weak Return Impatience Condition with the supplied parameter values. The WRIF is: %2.4f' % (WRIF), end = " ")
if verbose:
print('')
print('Therefore, a nondegenerate solution is not available (see '+url+'/#WRIC.')
print('Therefore, a nondegenerate solution is not available (see '+url+'/#WRIC for more.')
print()

#Evaluate and report on the Finite Value of Autarky Condition
Expand Down Expand Up @@ -2403,17 +2402,16 @@ def checkConditions(self,verbose=False,public_call=True):
print('')

if verbose:
print('GIF = %2.6f ' % (GIF))
print('GIFInd = %2.6f ' % (GIFInd))
print('GIFAgg = %2.6f ' % (GIFAgg))
print('Thorn = %2.6f ' % (Thorn))
print('PermGroFacAdj = %2.6f ' % (PermGroFacAdj))
print('uInvEpShkuInv = %2.6f ' % (uInvEpShkuInv))
print('FVAF = %2.6f ' % (FVAF))
print('WRIF = %2.6f ' % (WRIF))
print('DiscFacGIFMax = %2.6f ' % (self.DiscFacGIFMax))
print('DiscFacGIFAMax= %2.6f ' % (self.DiscFacGIFAMax))
print('DiscFacGIFAMax= %2.6f ' % (self.DiscFacGIFIMax))
print('GIFPF = %2.6f ' % (GIFPF))
print('GIFInd = %2.6f ' % (GIFInd))
print('GIFAgg = %2.6f ' % (GIFAgg))
print('Thorn = AIF = %2.6f ' % (Thorn))
print('PermGroFacAdj = %2.6f ' % (PermGroFacAdj))
print('uInvEpShkuInv = %2.6f ' % (uInvEpShkuInv))
print('FVAF = %2.6f ' % (FVAF))
print('WRIF = %2.6f ' % (WRIF))
print('DiscFacGIFIndMax = %2.6f ' % (self.DiscFacGIFIndMax))
print('DiscFacGIFAggMax = %2.6f ' % (self.DiscFacGIFAggMax))

def Ex_Mtp1_over_Ex_Ptp1(self,mRat,verbose=False):
cRat = self.solution[-1].cFunc(mRat)
Expand Down Expand Up @@ -2603,15 +2601,11 @@ def getRfree(self):

def checkConditions(self,verbose=False):
'''
This method checks whether the instance's type satisfies the Growth Impatience Condition
(GIC), Return Impatience Condition (RIC), Absolute Impatience Condition (AIC), Weak Return
Impatience Condition (WRIC), Finite Human Wealth Condition (FHWC) and Finite Value of
Autarky Condition (FVAC). These are the conditions that are sufficient for nondegenerate
infinite horizon solutions with a 1 period cycle. Depending on the model at hand, a
different combination of these conditions must be satisfied. To check which conditions are
relevant to the model at hand, a reference to the relevant theoretical literature is made.
SHOULD BE INHERITED FROM ConsIndShockModel
This method checks whether the instance's type satisfies the Absolute Impatience Condition (AIC),
the Return Impatience Condition (RIC), the Growth Impatience Condition (GIC), the Weak Return
Impatience Condition (WRIC), the Finite Human Wealth Condition (FHWC) and the Finite Value of
Autarky Condition (FVAC). To check which conditions are relevant to the model at hand, a
reference to the relevant theoretical literature is made.
Parameters
----------
Expand Down

0 comments on commit 1fce464

Please sign in to comment.