updates to tests and default init_ parameters for econ-ark#1022

sbenthall · Jun 24, 2021 · 5750e5c · 5750e5c
1 parent dfe4d98
commit 5750e5c
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Showing 4 changed files with 13 additions and 13 deletions.
diff --git a/HARK/ConsumptionSaving/ConsIndShockModel.py b/HARK/ConsumptionSaving/ConsIndShockModel.py
@@ -1535,8 +1535,8 @@ def prepare_to_calc_EndOfPrdvP(self):
     'CRRA': 2.0,          # Coefficient of relative risk aversion,
     'Rfree': 1.03,        # Interest factor on assets
     'DiscFac': 0.96,      # Intertemporal discount factor
-    'LivPrb': [0.98],     # Survival probability
-    'PermGroFac': [1.01],  # Permanent income growth factor
+    'LivPrb': [1, 0.98],     # Survival probability
+    'PermGroFac': [1, 1.01],  # Permanent income growth factor
     'BoroCnstArt': None,  # Artificial borrowing constraint
     'MaxKinks': 400,      # Maximum number of grid points to allow in cFunc (should be large)
     'AgentCount': 10000,  # Number of agents of this type (only matters for simulation)
@@ -2020,9 +2020,9 @@ def check_conditions(self, verbose=None):
             None
         ],  # Some other value of "assets above minimum" to add to the grid, not used
         # Income process variables
-        "PermShkStd": [0.1],  # Standard deviation of log permanent income shocks
+        "PermShkStd": [0.1, 0.1],  # Standard deviation of log permanent income shocks
         "PermShkCount": 7,  # Number of points in discrete approximation to permanent income shocks
-        "TranShkStd": [0.1],  # Standard deviation of log transitory income shocks
+        "TranShkStd": [0.1, 0.1],  # Standard deviation of log transitory income shocks
         "TranShkCount": 7,  # Number of points in discrete approximation to transitory income shocks
         "UnempPrb": 0.05,  # Probability of unemployment while working
         "UnempPrbRet": 0.005,  # Probability of "unemployment" while retired

diff --git a/HARK/ConsumptionSaving/tests/test_ConsGenIncProcessModel.py b/HARK/ConsumptionSaving/tests/test_ConsGenIncProcessModel.py
@@ -11,7 +11,7 @@
     "CRRA": 2.0,  # Coefficient of relative risk aversion
     "Rfree": 1.03,  # Interest factor on assets
     "DiscFac": 0.96,  # Intertemporal discount factor
-    "LivPrb": [0.98],  # Survival probability
+    "LivPrb": [1, 0.98],  # Survival probability
     "AgentCount": 10000,  # Number of agents of this type (only matters for simulation)
     "aNrmInitMean": 0.0,  # Mean of log initial assets (only matters for simulation)
     "aNrmInitStd": 1.0,  # Standard deviation of log initial assets (only for simulation)
@@ -32,8 +32,8 @@
     # Parameters describing the income process
     "PermShkCount": 7,  # Number of points in discrete approximation to permanent income shocks
     "TranShkCount": 7,  # Number of points in discrete approximation to transitory income shocks
-    "PermShkStd": [0.1],  # Standard deviation of log permanent income shocks
-    "TranShkStd": [0.1],  # Standard deviation of log transitory income shocks
+    "PermShkStd": [0.1, 0.1],  # Standard deviation of log permanent income shocks
+    "TranShkStd": [0.1, 0.1],  # Standard deviation of log transitory income shocks
     "UnempPrb": 0.05,  # Probability of unemployment while working
     "UnempPrbRet": 0.005,  # Probability of "unemployment" while retired
     "IncUnemp": 0.3,  # Unemployment benefits replacement rate
@@ -52,7 +52,7 @@
         )
     ),
     "PermGroFac": [
-        1.0
+        1.0, 1.0
     ],  # Permanent income growth factor - long run permanent income growth doesn't work yet
 }
 

diff --git a/HARK/ConsumptionSaving/tests/test_IndShockConsumerType.py b/HARK/ConsumptionSaving/tests/test_IndShockConsumerType.py
@@ -251,12 +251,12 @@ def test_infinite_horizon(self):
     "CRRA": 2.0,  # Coefficient of relative risk aversion
     "Rfree": 1.03,  # Interest factor on assets
     "DiscFac": 0.96,  # Intertemporal discount factor
-    "LivPrb": [0.99, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1],
-    "PermGroFac": [1.01, 1.01, 1.01, 1.02, 1.02, 1.02, 0.7, 1.0, 1.0, 1.0],
+    "LivPrb": [0.99, 0.99, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1],
+    "PermGroFac": [1.01, 1.01, 1.01, 1.01, 1.02, 1.02, 1.02, 0.7, 1.0, 1.0, 1.0],
     # Parameters that specify the income distribution over the lifecycle
-    "PermShkStd": [0.1, 0.2, 0.1, 0.2, 0.1, 0.2, 0.1, 0, 0, 0],
+    "PermShkStd": [0.1, 0.1, 0.2, 0.1, 0.2, 0.1, 0.2, 0.1, 0, 0, 0],
     "PermShkCount": 7,  # Number of points in discrete approximation to permanent income shocks
-    "TranShkStd": [0.3, 0.2, 0.1, 0.3, 0.2, 0.1, 0.3, 0, 0, 0],
+    "TranShkStd": [0.3, 0.3, 0.2, 0.1, 0.3, 0.2, 0.1, 0.3, 0, 0, 0],
     "TranShkCount": 7,  # Number of points in discrete approximation to transitory income shocks
     "UnempPrb": 0.05,  # Probability of unemployment while working
     "IncUnemp": 0.3,  # Unemployment benefits replacement rate

diff --git a/HARK/tests/test_core.py b/HARK/tests/test_core.py
@@ -83,7 +83,7 @@ def setUp(self):
     def test_solve(self):
         self.agent.time_vary = ["vary_1"]
         self.agent.time_inv = ["inv_1"]
-        self.agent.vary_1 = [1.1, 1.2, 1.3, 1.4]
+        self.agent.vary_1 = [1.0, 1.1, 1.2, 1.3, 1.4]
         self.agent.inv_1 = 1.05
         # to test the superclass we create a dummy solve_one_period function
         # for our agent, which doesn't do anything, instead of using a NullFunc