update notebooks

code/agents.py

@@ -58,7 +58,7 @@
 
 
 class TempConsumerType(AgentType):
-    def __init__(self, cycles=1, time_flow=True, **kwds):
+    def __init__(self, cycles=1, **kwds):
         """
         Make a new consumer type.
 
@@ -74,7 +74,7 @@ def __init__(self, cycles=1, time_flow=True, **kwds):
         None
         """
         # Initialize a basic AgentType
-        super().__init__(cycles=cycles, time_flow=time_flow, **kwds)
+        super().__init__(cycles=cycles, **kwds)
         # This estimation uses age-varying discount factors as
         # estimated by Cagetti (2003), so switch from time_inv to time_vary
         self.add_to_time_vary("DiscFac")
@@ -125,8 +125,6 @@ class PortfolioLifeCycleConsumerType(TempConsumerType, PortfolioConsumerType):
     def post_solve(self):
         for solution in self.solution:
             solution.cFunc = solution.cFuncAdj
-            share = solution.ShareFuncAdj
-            solution.ShareFuncAdj = lambda m: np.clip(share(m), 0.0, 1.0)
 
 
 class BequestWarmGlowLifeCycleConsumerType(

code/calibration/estimation_parameters.py

@@ -26,12 +26,12 @@
 # - Define all of the model parameters for SolvingMicroDSOPs and ConsumerExamples -
 # ---------------------------------------------------------------------------------
 
-exp_nest = 3  # Number of times to "exponentially nest" when constructing a_grid
+exp_nest = 1  # Number of times to "exponentially nest" when constructing a_grid
 aXtraMin = 0.001  # Minimum end-of-period "assets above minimum" value
-aXtraMax = 20  # Maximum end-of-period "assets above minimum" value
+aXtraMax = 100  # Maximum end-of-period "assets above minimum" value
 aXtraHuge = None  # A very large value of assets to add to the grid, not used
 aXtraExtra = None  # Some other value of assets to add to the grid, not used
-aXtraCount = 8  # Number of points in the grid of "assets above minimum"
+aXtraCount = 200  # Number of points in the grid of "assets above minimum"
 
 # Artificial borrowing constraint; imposed minimum level of end-of period assets
 BoroCnstArt = 0.0
@@ -44,9 +44,9 @@
 PermShkCount = 7
 # Number of points in discrete approximation to transitory income shocks
 TranShkCount = 7
-UnempPrb = 0.005  # Probability of unemployment while working
-UnempPrbRet = 0.000  # Probability of "unemployment" while retired
-IncUnemp = 0.0  # Unemployment benefits replacement rate
+UnempPrb = 0.05  # Probability of unemployment while working
+UnempPrbRet = 0.005  # Probability of "unemployment" while retired
+IncUnemp = 0.3  # Unemployment benefits replacement rate
 IncUnempRet = 0.0  # "Unemployment" benefits when retired
 
 final_age = 90  # Age at which the problem ends (die with certainty)
@@ -74,7 +74,7 @@
 )
 
 # Age-varying discount factors over the lifecycle, lifted from Cagetti (2003)
-DiscFac_timevary = np.genfromtxt("code/data/Cagetti2003.csv")
+DiscFac_timevary = np.genfromtxt("../data/Cagetti2003.csv")
 
 # Survival probabilities over the lifecycle
 liv_prb = parse_ssa_life_table(

code/tables/IndShock_estimate_results.csv

@@ -1,2 +1,2 @@
-DiscFacAdj,CRRA
-0.8783572029816282,3.5160942263466355
+DiscFacAdj,CRRA
+0.8783572029816282,3.5160942263466355