def test_small_open(self):
agent = AggShockConsumerType()
agent.AgentCount = 100 # Very low number of agents for the sake of speed
agent.cycles = 0
# Make agents heterogeneous in their discount factor
agents = distribute_params(
agent, "DiscFac", 3, Uniform(bot=0.90, top=0.94) # Impatient agents
)
# Make an economy with those agents living in it
small_economy = SmallOpenEconomy(
agents=agents,
Rfree=1.03,
wRte=1.0,
KtoLnow=1.0,
**copy.copy(init_cobb_douglas)
)
small_economy.act_T = 400 # Short simulation history
small_economy.max_loops = 3 # Give up quickly for the sake of time
small_economy.make_AggShkHist() # Simulate a history of aggregate shocks
small_economy.verbose = False # Turn off printed messages
# Give data about the economy to all the agents in it
for this_type in small_economy.agents:
this_type.get_economy_data(small_economy)
small_economy.solve()
def setUp(self):
agent = AggShockConsumerType()
agent.AgentCount = 900 # Very low number of agents for the sake of speed
agent.cycles = 0
# Make agents heterogeneous in their discount factor
self.agents = distribute_params(
agent, "DiscFac", 3, Uniform(bot=0.90, top=0.94) # Impatient agents
)
# Make an economy with those agents living in it
self.economy = CobbDouglasEconomy(agents=self.agents)
solve_agg_shocks_market = True
# Solve an AggShockMarkovConsumerType's microeconomic problem
solve_markov_micro = False
# Solve for the equilibrium aggregate saving rule in a CobbDouglasMarkovEconomy
solve_markov_market = False
# Solve a simple Krusell-Smith-style two state, two shock model
solve_krusell_smith = True
# Solve a CobbDouglasEconomy with many states, potentially utilizing the "state jumper"
solve_poly_state = False
# ### Example implementation of AggShockConsumerType
if solve_agg_shocks_micro or solve_agg_shocks_market:
# Make an aggregate shocks consumer type
AggShockExample = AggShockConsumerType()
AggShockExample.cycles = 0
# Make a Cobb-Douglas economy for the agents
EconomyExample = CobbDouglasEconomy(agents=[AggShockExample])
EconomyExample.makeAggShkHist() # Simulate a history of aggregate shocks
# Have the consumers inherit relevant objects from the economy
AggShockExample.getEconomyData(EconomyExample)
if solve_agg_shocks_micro:
# Solve the microeconomic model for the aggregate shocks example type (and display results)
t_start = process_time()
AggShockExample.solve()
t_end = process_time()
print("Solving an aggregate shocks consumer took " +
mystr(t_end - t_start) + " seconds.")
