def __init__(self, FluctuationsOneAssetIOU, agents=[], act_T=1000):
'''
Make a new instance of LuettickeEconomy by filling in attributes
specific to this kind of market.
Parameters
----------
FluctuationsOneAssetIOU : FluctuationsOneAssetIOUs
Class from Luetticke_code that solves the model
agents : [ConsumerType]
List of types of consumers that live in this economy.
act_T : int
Number of periods to simulate when making a history of of the market.
Returns
-------
None
'''
Market.__init__(self,
agents=agents,
sow_vars=['XNow'],
reap_vars=[],
track_vars=[],
dyn_vars=[],
tolerance=1e-10,
act_T=act_T)
self.FluctuationsOneAssetIOU = deepcopy(FluctuationsOneAssetIOU)
def __init__(self,agents=[],tolerance=0.0001,act_T=1000,**kwds):
'''
Make a new instance of CobbDouglasEconomy by filling in attributes
specific to this kind of market.
Parameters
----------
agents : [ConsumerType]
List of types of consumers that live in this economy.
tolerance: float
Minimum acceptable distance between "dynamic rules" to consider the
solution process converged. Distance depends on intercept and slope
of the log-linear "next capital ratio" function.
act_T : int
Number of periods to simulate when making a history of of the market.
Returns
-------
None
'''
Market.__init__(self,agents=agents,
sow_vars=['KtoLnow','RfreeNow','wRteNow','PermShkAggNow','TranShkAggNow'],
reap_vars=['pNow','aNow'],
track_vars=['KtoLnow'],
dyn_vars=['kNextFunc'],
tolerance=tolerance,
act_T=act_T)
self.assignParameters(**kwds)
self.update()
def __init__(self, agents=[], tolerance=0.0001, act_T=1000, **kwds):
'''
Make a new instance of CobbDouglasEconomy by filling in attributes
specific to this kind of market.
Parameters
----------
agents : [ConsumerType]
List of types of consumers that live in this economy.
tolerance: float
Minimum acceptable distance between "dynamic rules" to consider the
solution process converged. Distance depends on intercept and slope
of the log-linear "next capital ratio" function.
act_T : int
Number of periods to simulate when making a history of of the market.
Returns
-------
None
'''
Market.__init__(self,
agents=agents,
sow_vars=[
'KtoLnow', 'RfreeNow', 'wRteNow', 'PermShkAggNow',
'TranShkAggNow'
],
reap_vars=['pNow', 'aNow'],
track_vars=['KtoLnow'],
dyn_vars=['kNextFunc'],
tolerance=tolerance,
act_T=act_T)
self.assignParameters(**kwds)
self.update()
