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()