def market__tatonnement(self, args):
import os
from src.bank import Bank
from src.household import Household
from src.firm import Firm
from src.environment import Environment
from src.transaction import Transaction
from src.market import Market
text = "This test checks market.tatonnement \n"
self.print_info(text)
#
# INITIALIZATION
#
environment_directory = str(args[0])
identifier = str(args[1])
log_directory = str(args[2])
# Configure logging parameters so we get output while the program runs
logging.basicConfig(format='%(asctime)s %(message)s',
datefmt='%m/%d/%Y %H:%M:%S',
filename=log_directory + identifier + ".log",
level=logging.INFO)
logging.info('START logging for test market__tatonnement in run: %s',
environment_directory + identifier + ".xml")
# Construct household filename
environment = Environment(environment_directory, identifier)
# generate a bank
bank = Bank()
bank.identifier = "test_bank"
environment.banks.append(bank)
# generate a firm
firm = Firm()
firm.identifier = "test_firm"
environment.firms.append(firm)
# generate a household
household = Household()
household.identifier = "test_household"
environment.households.append(household)
#
# TESTING
#
sellers = []
for agent in environment.households:
sellers.append([agent, agent.supply_of_labour])
buyers = []
for agent in environment.firms:
buyers.append([agent, agent.demand_for_labour])
starting_price = 0.0
price = 0.0
market = Market("market")
price = market.tatonnement(sellers, buyers, starting_price, 0.00000001,
0.01, 1.1)
print("Price found through tatonnement:")
print(price)
def market__tatonnement(self, args):
import os
from src.bank import Bank
from src.household import Household
from src.firm import Firm
from src.environment import Environment
from src.transaction import Transaction
from src.market import Market
text = "This test checks market.tatonnement \n"
self.print_info(text)
#
# INITIALIZATION
#
environment_directory = str(args[0])
identifier = str(args[1])
log_directory = str(args[2])
# Configure logging parameters so we get output while the program runs
logging.basicConfig(format='%(asctime)s %(message)s', datefmt='%m/%d/%Y %H:%M:%S',
filename=log_directory + identifier + ".log", level=logging.INFO)
logging.info('START logging for test market__tatonnement in run: %s',
environment_directory + identifier + ".xml")
# Construct household filename
environment = Environment(environment_directory, identifier)
# generate a bank
bank = Bank()
bank.identifier = "test_bank"
environment.banks.append(bank)
# generate a firm
firm = Firm()
firm.identifier = "test_firm"
environment.firms.append(firm)
# generate a household
household = Household()
household.identifier = "test_household"
environment.households.append(household)
#
# TESTING
#
sellers = []
for agent in environment.households:
sellers.append([agent, agent.supply_of_labour])
buyers = []
for agent in environment.firms:
buyers.append([agent, agent.demand_for_labour])
starting_price = 0.0
price = 0.0
market = Market("market")
price = market.tatonnement(sellers, buyers, starting_price, 0.00000001, 0.01, 1.1)
print("Price found through tatonnement:")
print(price)
def sell_labour(self, environment, time):
# First we find the market equilibrium price
# Important to note that this currently does
# not depend on the wealth of the buyers
# That is their demand may be higher than
# what they can actually buy, which may be ok
# We set the values necessary for tatonnement
# The list of sellers and their supply functions
sellers = []
for agent in environment.households:
sellers.append([agent, agent.supply_of_labour_solow])
# And the list of buyers and their demand functions
buyers = []
for agent in environment.firms:
buyers.append([agent, agent.demand_for_labour_solow])
# We may start the search for price at some specific point
# Here we pass 0, which means it'll start looking at a
# random point between 0 and 10
starting_price = 0.0
# We initialize the price
price = 0.0
# Put the appropriate settings, i.e. desired identifier
market = Market("market")
# And we find the market price of labour
# given supply and demand of the agents
# and tolerance of error, resolution of search
# and amplification factor for exponential search
price = market.tatonnement(sellers, buyers, starting_price,
0.00000000001, 0.01, 1.1)
environment.variable_parameters["price_of_labour"] = price
# now we use rationing to find the actual transactions between agents
for_rationing = []
for household in environment.households:
for_rationing.append(
[household, household.supply_of_labour_solow(price)])
for firm in environment.firms:
for_rationing.append([firm, -firm.demand_for_labour_solow(price)])
# And we find the rationing, ie the amounts
# of goods sold between pairs of agents
rationed = market.rationing(for_rationing)
#
# A (from) L (to)
# bank loan deposit
# household deposit labour
# firm labour loan
#
for ration in rationed:
# The labour is an asset (production factor) for the firm
# and a liability (promise to work) for the household
environment.new_transaction("labour", "", ration[1].identifier,
ration[0].identifier, ration[2], 0, 0,
-1)
random_bank = random.choice(environment.banks)
# Deposit is a liability of the bank
# and an asset of the household
environment.new_transaction("deposits", "", ration[0].identifier,
random_bank.identifier,
ration[2] * price,
random_bank.interest_rate_deposits, 0,
-1)
# Loan is an asset of the bank
# and a liability of the firm
environment.new_transaction("loans", "", random_bank.identifier,
ration[1].identifier,
ration[2] * price,
random_bank.interest_rate_loans, 0, -1)
# We print the action of selling to the screen
print(
"{}s sold {}d units of labour at a price {}f to {}s at time {}d."
.format(ration[0].identifier, ration[2], price,
ration[1].identifier, time))
logging.info(" labour sold to firms on step: %s", time)
