def __init__(self, record, VarList, current_year, db, pp_table_name, pp_table, land_dict, model_parameters):
'''
Construct the household class from the household table in the DB, and then add some other user-defined attributes.
record - a record in the household table in the DB.
VarList - the variable (or field) list of the household table in the DB
VarList = {paramName1: paramOrder1, paramName2: paramOrder2, ...}
Also initialize the household's own person instances here from the person table in the DB.
Also initialize the household's capital properties instance here.
'''
# Set the attributes (var) and their values (record) from the household table in the DB.
for var in VarList:
setattr(self, var[0], record[var[1]])
# Set the household and person variables (attributes) lists
self.hh_var_list = VarList
self.pp_var_list = DataAccess.get_var_list(db, pp_table_name)
# Set the current time stamp
self.StatDate = current_year
# Define own persons (members) dict of the household, indexed by PID
self.own_pp_dict = dict()
# Add respective persons into the persons dict of the household
for pp in pp_table:
if pp.HID == self.HID:
pp_temp = Person(pp, self.pp_var_list, current_year)
self.own_pp_dict[pp_temp.PID] = pp_temp # Indexed by PID
# Initialize the household's capital properties class instance
self.own_capital_properties = CapitalProperty(self, land_dict, model_parameters)
# Define an empty list of available business sectors,
# and another empty list of the business sectors that the household is in in the current year
self.own_av_business_sectors = list()
self.own_current_sectors = list()
# Define an empty list of participant policy programs
self.own_policy_programs = list()
# Initialize the household's energy class instance
self.energy = Energy()
# Define a variable indicating the household's preference type
'''
1 - Max Labor, Min Risk;
2 - Min Labor, Min Risk;
3 - Max Labor, Max Risk;
4 - Min Labor, Max Risk;
'''
self.hh_preference_type = int()
# Also define a variable indicating the preference toward risks
'''
True - risk aversion; False - risk appetite;
'''
self.hh_risk_type = True
# Define a variable indicating the household's business type
'''
0 - agriculture only
1 - agriculture and another business sectors; or one business sector which is not agriculture
2 - agriculture and more than one other business sectors
'''
self.business_type = int()
# Define a switch variable indicating whether the household is dissolved in the current year
self.is_dissolved_this_year = False
def __init__(self, record, VarList, current_year, db, pp_table_name, pp_table, land_dict, model_parameters):
'''
Construct the household class from the household table in the DB, and then add some other user-defined attributes.
record - a record in the household table in the DB.
VarList - the variable (or field) list of the household table in the DB
VarList = {paramName1: paramOrder1, paramName2: paramOrder2, ...}
Also initialize the household's own person instances here from the person table in the DB.
Also initialize the household's capital properties instance here.
'''
# Set the attributes (var) and their values (record) from the household table in the DB.
for var in VarList:
setattr(self, var[0], record[var[1]])
# Set the household and person variables (attributes) lists
self.hh_var_list = VarList
self.pp_var_list = DataAccess.get_var_list(db, pp_table_name)
# Set the current time stamp
self.StatDate = current_year
# Define own persons (members) dict of the household, indexed by PID
self.own_pp_dict = dict()
# Add respective persons into the persons dict of the household
for pp in pp_table:
if pp.HID == self.HID:
pp_temp = Person(pp, self.pp_var_list, current_year)
self.own_pp_dict[pp_temp.PID] = pp_temp # Indexed by PID
# Initialize the household's capital properties class instance
self.own_capital_properties = CapitalProperty(self, land_dict, model_parameters)
# Define an empty list of available business sectors,
# and another empty list of the business sectors that the household is in in the current year
self.own_av_business_sectors = list()
self.own_current_sectors = list()
# Define an empty list of participant policy programs
self.own_policy_programs = list()
# Initialize the household's energy class instance
self.energy = Energy()
# Define a variable indicating the household's preference type
'''
1 - Max Labor, Min Risk;
2 - Min Labor, Min Risk;
3 - Max Labor, Max Risk;
4 - Min Labor, Max Risk;
'''
self.hh_preference_type = int()
# Also define a variable indicating the preference toward risks
'''
True - risk aversion; False - risk appetite;
'''
self.hh_risk_type = True
# Define a variable indicating the household's business type
'''
0 - agriculture only
1 - agriculture and another business sectors; or one business sector which is not agriculture
2 - agriculture and more than one other business sectors
'''
self.business_type = int()
# Define a switch variable indicating whether the household is dissolved in the current year
self.is_dissolved_this_year = False
class Household(object):
'''
This is the definition of the household class
'''
def __init__(self, record, VarList, current_year, db, pp_table_name, pp_table, land_dict, model_parameters):
'''
Construct the household class from the household table in the DB, and then add some other user-defined attributes.
record - a record in the household table in the DB.
VarList - the variable (or field) list of the household table in the DB
VarList = {paramName1: paramOrder1, paramName2: paramOrder2, ...}
Also initialize the household's own person instances here from the person table in the DB.
Also initialize the household's capital properties instance here.
'''
# Set the attributes (var) and their values (record) from the household table in the DB.
for var in VarList:
setattr(self, var[0], record[var[1]])
# Set the household and person variables (attributes) lists
self.hh_var_list = VarList
self.pp_var_list = DataAccess.get_var_list(db, pp_table_name)
# Set the current time stamp
self.StatDate = current_year
# Define own persons (members) dict of the household, indexed by PID
self.own_pp_dict = dict()
# Add respective persons into the persons dict of the household
for pp in pp_table:
if pp.HID == self.HID:
pp_temp = Person(pp, self.pp_var_list, current_year)
self.own_pp_dict[pp_temp.PID] = pp_temp # Indexed by PID
# Initialize the household's capital properties class instance
self.own_capital_properties = CapitalProperty(self, land_dict, model_parameters)
# Define an empty list of available business sectors,
# and another empty list of the business sectors that the household is in in the current year
self.own_av_business_sectors = list()
self.own_current_sectors = list()
# Define an empty list of participant policy programs
self.own_policy_programs = list()
# Initialize the household's energy class instance
self.energy = Energy()
# Define a variable indicating the household's preference type
'''
1 - Max Labor, Min Risk;
2 - Min Labor, Min Risk;
3 - Max Labor, Max Risk;
4 - Min Labor, Max Risk;
'''
self.hh_preference_type = int()
# Also define a variable indicating the preference toward risks
'''
True - risk aversion; False - risk appetite;
'''
self.hh_risk_type = True
# Define a variable indicating the household's business type
'''
0 - agriculture only
1 - agriculture and another business sectors; or one business sector which is not agriculture
2 - agriculture and more than one other business sectors
'''
self.business_type = int()
# Define a switch variable indicating whether the household is dissolved in the current year
self.is_dissolved_this_year = False
def household_demographic_update(self, current_year, model_parameters):
'''
Annual demographic updates of the household.
'''
# Update the current time stamp
self.StatDate = current_year
# Reset the "dissolved this year" switch
# Note this is before the household existence bifurcation.
# So all households in society.hh_dict get this switch reset (every year).
self.is_dissolved_this_year = False
# Annual population dynamics (personal demographic status updates)
temp_pp_list = list()
for PID in self.own_pp_dict:
temp_pp_list.append(Person.personal_demographic_update(self.own_pp_dict[PID], current_year, model_parameters))
# Reset own persons (members) dict (own_pp_dict)
self.own_pp_dict = dict()
# Refresh own_pp_list
for p in temp_pp_list:
self.own_pp_dict[p.PID] = p
# Only the existing households proceed.
if self.is_exist == 1:
# Count alive members of the household who is not moved out
alive_members_count = 0
for PID in self.own_pp_dict:
if self.own_pp_dict[PID].is_alive == 1 and self.own_pp_dict[PID].moved_out == False:
alive_members_count += 1
# If the updated household has no alive and not-moved-out members, mark it as non-exist.
if alive_members_count == 0:
self.is_exist = 0
self.is_dissolved_this_year = True # Turn on this switch so that the household could be dissolved later in the society class
# Then deal with the deceased persons
for p in temp_pp_list:
# If p dies this year and p's spouse lives
if p.is_died_this_year == True and p.SpouseID != '0' and self.own_pp_dict[p.SpouseID].is_alive == 1:
# Then p's spouse's marital status changes
self.own_pp_dict[p.SpouseID].IsMarry = 0
self.own_pp_dict[p.SpouseID].SpouseID = '0'
# And p's own marital status is also marked changed
self.own_pp_dict[p.PID].IsMarry = 0
self.own_pp_dict[p.PID].SpouseID = '0'
return self
def household_economy(self, policies, business_sectors, model_parameters):
'''
The (annual) economic activities of the household. Including household's preference categorization,
policy-related decision-making,and production and consumption activities.
'''
# Determine the household's preferences
self.housedhold_categorization()
# Make policy decisions
self.household_policy_decision(policies, business_sectors, model_parameters)
# Do the business
# The second parameter, risk_effective = True, indicating it is a "real world" run this time,
# as opposed to the two "hypothetical" runs in the previous step, the policy decision step,
# when risk_effective = False. i.e. random factors don't take effect in households' economy decision-making process.
self.own_capital_properties = self.household_business_revenue(self.own_capital_properties,
business_sectors, model_parameters, risk_effective=True)
# Household's final accountings for the year
self.household_final_accounting(model_parameters)
def housedhold_categorization(self):
'''
Categorize the households according to their preferences toward risk and labor/leisure trade-off
For combined (risk + labor/leisure) household preference types:
1 - Max Labor, Min Risk;
2 - Min Labor, Min Risk;
3 - Max Labor, Max Risk;
4 - Min Labor, Max Risk;
For risk preference types:
True - risk aversion; False - risk appetite;
'''
# Risk Preference
# Define variables in the formula for risk preference determination
# is_truck
if self.own_capital_properties.truck > 0:
is_truck = 1
else:
is_truck = 0
# is_minibus
if self.own_capital_properties.minibus > 0:
is_minibus = 1
else:
is_minibus = 0
# house_size
house_size = self.own_capital_properties.house_area
high_school_kids = self.own_capital_properties.high_school_kids
p_risk = math.exp(6.702 + 0.749 * is_truck + 1.748 * is_minibus + 0.004 * house_size - 1.436 * high_school_kids + 0.775 * self.NonRural - 0.005 * self.Elevation) / (1 + math.exp(6.702 + 0.749 * is_truck + 1.748 * is_minibus + 0.004 * house_size - 1.436 * high_school_kids + 0.775 * self.NonRural - 0.005 * self.Elevation))
# Labor Preference
# p_labor = math.exp(0.461 * self.own_capital_properties.labor) / (1 + math.exp(0.461 * self.own_capital_properties.labor))
labor_pref = 0
if self.own_capital_properties.young_male_labor == 0 and self.own_capital_properties.kids == 0:
labor_pref = 0
else:
labor_pref = 1
if p_risk < 0.5:
if labor_pref == 1:
self.hh_preference_type = 1
self.hh_risk_type = True
else:
self.hh_preference_type = 2
self.hh_risk_type = True
else:
if labor_pref == 1:
self.hh_preference_type = 3
self.hh_risk_type = False
else:
self.hh_preference_type = 4
self.hh_risk_type = False
def household_policy_decision(self, policy_dict, business_sector_dict, model_parameters):
if self.own_capital_properties.farm_to_forest != 0: # Has already joined the farm to forest program
# Just apply the policies from the last year
self.household_apply_policy(model_parameters)
elif self.own_capital_properties.farm_to_forest == 0 and self.own_capital_properties.farmland != 0:
# Has not yet joined the farm to forest program, but has the potential to do so (household has farmland).
hyp_capital_1 = copy.deepcopy(self.own_capital_properties)
hyp_capital_2 = copy.deepcopy(self.own_capital_properties)
# Reset the self.own_policy_programs list
self.own_policy_programs = list()
# First, run the business and get the hypothetical household capital properties condition when no OPTIONAL policy programs apply.
# Note that the household's capital properties have been updated in the application process of the programs
for PolicyType in policy_dict:
if policy_dict[PolicyType].IsCompulsory == 1: # Only consider the compulsory programs
hyp_capital_1 = Policy.apply_policy_terms(policy_dict[PolicyType], hyp_capital_1, model_parameters)
self.own_policy_programs.append(policy_dict[PolicyType])
# Get all compensational revenues
compensation_1 = hyp_capital_1.cash - self.own_capital_properties.cash
# Do the business based on hyp_capital_1
hyp_capital_1 = self.household_business_revenue(hyp_capital_1, business_sector_dict, model_parameters, risk_effective=False)
# Get the total household revenues in this occasion
revenue_1 = hyp_capital_1.get_total_business_income() + compensation_1
# Second, get the hypothetical household capital properties condition when ALL policy programs are applied
# In this project's case, this means including an OPTIONAL program: the farmland to forest program
for PolicyType in policy_dict:
hyp_capital_2 = Policy.apply_policy_terms(policy_dict[PolicyType], hyp_capital_2, model_parameters)
# Get all compensational revenues
compensation_2 = hyp_capital_2.cash - self.own_capital_properties.cash
# Do the business based on hyp_capital_2
hyp_capital_2 = self.household_business_revenue(hyp_capital_2, business_sector_dict, model_parameters, risk_effective=False)
# Get the total household revenues in this occasion
revenue_2 = hyp_capital_2.get_total_business_income() + compensation_2
# Make the decision
'''
self.hh_preference_type:
1 - Max Labor, Min Risk;
2 - Min Labor, Min Risk;
3 - Max Labor, Max Risk;
4 - Min Labor, Max Risk;
'''
if self.hh_preference_type == 1 or self.hh_preference_type == 3: # Prefers Labor
if revenue_2 > revenue_1:
# Then join in the programs
for PolicyType in policy_dict:
if policy_dict[PolicyType].IsCompulsory == 0: # Add the optional programs into household's own programs dictionary
self.own_policy_programs.append(policy_dict[PolicyType])
else: # Prefers Leisure
if compensation_2 > self.get_min_living_cost(model_parameters):
# If all compensational revenues, including those from participation in the optional programs,
# is higher than the household's minimum living cost,
# Then join in the programs
for PolicyType in policy_dict:
if policy_dict[PolicyType].IsCompulsory == 0: # Add the optional programs into household's own programs dictionary
self.own_policy_programs.append(policy_dict[PolicyType])
# When the decision is made,
# Apply the policies to get the renewed household's own capital properties condition
# to get prepared for the "real world" run.
self.household_apply_policy(model_parameters)
# # If the household joins in the farmland to forest program this year,
# # remove the land parcels in their own_capital_properties.land_properties_list,
# # and mark these farmland parcels' succession start year as this year.
# for program in self.own_policy_programs:
# if program.PolicyType == 'FarmToForest_After':
# for farmland_parcel in self.own_capital_properties.land_properties_list:
# farmland_parcel.is_ftof = 1
# farmland_parcel.succession_start_year = self.StatDate
# self.own_capital_properties.land_properties_list.remove(farmland_parcel)
def household_apply_policy(self, model_parameters):
# Update the household's own capital properties conditions according to the policy decisions
# and also get compensational revenues (done in the policy class)
for program in self.own_policy_programs:
self.own_capital_properties = Policy.apply_policy_terms(program, self.own_capital_properties, model_parameters)
def household_business_revenue(self, hh_capital, business_sector_dict, model_parameters, risk_effective):
'''
The process of a household doing business.
business_sector_dict: all business sectors. i.e. society.business_sector_dict.
risk_effective - whether the random risk factor takes effect in the calculation. True - real world; False: hypothetical.
'''
self.get_available_business(hh_capital, business_sector_dict)
self.get_rank_available_business(hh_capital, self.own_av_business_sectors, model_parameters)
hh_capital = self.do_business(hh_capital, self.own_av_business_sectors, model_parameters, risk_effective)
return hh_capital
def get_available_business(self, hh_capital, business_sector_dict):
'''
Get the available (enter-able) business sectors list for the household.
hh_capital: household's capital properties (factors of production) i.e. self.own_capital_properties;
business_sector_dict: all business sectors. i.e. society.business_sector_dict.
'''
# Reset the own available business sectors list
self.own_av_business_sectors = list()
if self.hh_preference_type == 1 or self.hh_preference_type == 2:
# Risk aversion. No loans. risk_type = True
for SectorName in business_sector_dict:
if business_sector_dict[SectorName].is_doable(hh_capital, risk_type=True) == True:
self.own_av_business_sectors.append(business_sector_dict[SectorName])
else:
# Risk appetite. risk_type = False
for SectorName in business_sector_dict:
if business_sector_dict[SectorName].is_doable(hh_capital, risk_type=False) == True:
self.own_av_business_sectors.append(business_sector_dict[SectorName])
def get_rank_available_business(self, hh_capital, business_list, model_parameters):
'''
Rank the business sectors in the household's available business sectors list according to the household's specific preference.
hh_capital: household's capital properties (factors of production);
business_list: the available business sectors list for the household.
'''
temp_sectors_list = list()
if self.hh_preference_type == 1:
'''
Max Labor, Min Risk - risk_type = True
'''
# Get the hypothetical profit of each sector if entered
for sector in business_list:
profit = sector.calculate_business_revenue(hh_capital, model_parameters, risk_type=True, risk_effective=False).cash - hh_capital.cash
temp_sectors_list.append((profit, sector))
# Rank the sectors by profit descendedly
temp_sectors_list.sort(reverse = True)
# Refresh the household's available business sectors list
self.own_av_business_sectors = list()
# Always place agriculture (if enter-able) in the first place
for item in temp_sectors_list:
if item[1].SectorName == 'Agriculture':
self.own_av_business_sectors.append(item[1])
temp_sectors_list.remove(item)
# Then add other sectors
for item in temp_sectors_list:
self.own_av_business_sectors.append(item[1])
elif self.hh_preference_type == 2:
'''
Min Labor, Min Risk - risk_type = True
'''
# Get the hypothetical labor cost of each sector if entered
for sector in business_list:
labor_cost = sector.calculate_business_revenue(hh_capital, model_parameters, risk_type=True, risk_effective=False).labor_cost - hh_capital.labor_cost
temp_sectors_list.append((labor_cost, sector))
# Rank the sectors by labor cost ascendedly
temp_sectors_list.sort()
# Refresh the household's available business sectors list
self.own_av_business_sectors = list()
# Add sectors
for item in temp_sectors_list:
self.own_av_business_sectors.append(item[1])
elif self.hh_preference_type == 3:
'''
Max Labor, Max Risk - risk_type = False
'''
# Get the hypothetical profit of each sector if entered
for sector in business_list:
profit = sector.calculate_business_revenue(hh_capital, model_parameters, risk_type=False, risk_effective=False).cash - hh_capital.cash
temp_sectors_list.append((profit, sector))
# Rank the sectors by profit descendedly
temp_sectors_list.sort(reverse = True)
# Refresh the household's available business sectors list
self.own_av_business_sectors = list()
# Always place agriculture (if enter-able) in the first place
for item in temp_sectors_list:
if item[1].SectorName == 'Agriculture':
self.own_av_business_sectors.append(item[1])
temp_sectors_list.remove(item)
# Then add other sectors
for item in temp_sectors_list:
self.own_av_business_sectors.append(item[1])
elif self.hh_preference_type == 4:
'''
Min Labor, Max Risk - risk_type = False
'''
# Get the hypothetical labor cost of each sector if entered
for sector in business_list:
labor_cost = sector.calculate_business_revenue(hh_capital, model_parameters, risk_type=False, risk_effective=False).labor_cost - hh_capital.labor_cost
temp_sectors_list.append((labor_cost, sector))
# Rank the sectors by labor cost ascendedly
temp_sectors_list.sort()
# Refresh the household's available business sectors list
self.own_av_business_sectors = list()
# Add sectors
for item in temp_sectors_list:
self.own_av_business_sectors.append(item[1])
def do_business(self, hh_capital, business_list, model_parameters, risk_effective):
'''
risk_effective - whether the random risk factor takes effect in the calculation. True - real world; False: hypothetical.
'''
# Reset the houosehold's current sector list
self.own_current_sectors = list()
if self.hh_preference_type == 1 or self.hh_preference_type == 3:
'''
1 - Max Labor, Min Risk; 3 - Max Labor, Max Risk;
'''
for sector in self.own_av_business_sectors:
hh_capital = BusinessSector.calculate_business_revenue(sector, hh_capital, model_parameters,
self.hh_risk_type, risk_effective)
self.own_current_sectors.append(sector)
if hh_capital.av_labor <= 0:
# Exit condition: household running out of its labor resource
break
elif self.hh_preference_type == 2 or self.hh_preference_type == 4:
'''
2 - Min Labor, Min Risk; 4 - Min Labor, Max Risk.
'''
# old_cash = hh_capital.cash
for sector in self.own_av_business_sectors:
if hh_capital.get_total_business_income() + hh_capital.compensational_revenues >= self.get_min_living_cost(model_parameters):
# Exit condition: this year's total income >= minimal living cost
break
else:
hh_capital = BusinessSector.calculate_business_revenue(sector, hh_capital, model_parameters,
self.hh_risk_type, risk_effective)
self.own_current_sectors.append(sector)
return hh_capital
def household_final_accounting(self, model_parameters):
'''
Household's final cash capital = own_capital_properties.cash - actual_living_cost - loan_payments
'''
actual_living_cost = self.get_actual_living_cost(model_parameters)
# Subtract living costs from cash reserve; if insufficient, go into debt.
if self.own_capital_properties.cash < actual_living_cost:
self.own_capital_properties.debt = self.own_capital_properties.debt + (actual_living_cost - self.own_capital_properties.cash)
self.own_capital_properties.cash = 0
else:
self.own_capital_properties.cash = self.own_capital_properties.cash - actual_living_cost
# Then pay the debts, if any, with up to half the household cash reserve.
payment = self.own_capital_properties.cash / 2
if self.own_capital_properties.debt > 0:
if payment <= self.own_capital_properties.debt:
self.own_capital_properties.cash = self.own_capital_properties.cash - payment
self.own_capital_properties.debt = self.own_capital_properties.debt - payment
else:
self.own_capital_properties.cash = self.own_capital_properties.cash - self.own_capital_properties.debt
self.own_capital_properties.debt = 0
# Then calculate the household's net savings
self.own_capital_properties.netsavings = self.own_capital_properties.cash - self.own_capital_properties.debt
# Finally, update the household's capital properties from the Capital Property Class
self.own_capital_properties.update_household_capital_properties(self)
def get_min_living_cost(self, model_parameters):
min_living_cost = self.own_capital_properties.preschool_kids * float(model_parameters['PreSchooleCostPerKidI'])\
+ self.own_capital_properties.primary_school_kids * float(model_parameters['PrimarySchoolCostPerKidI'])\
+ self.own_capital_properties.secondary_school_kids * float(model_parameters['SecondarySchoolCostPerKidI'])\
+ self.own_capital_properties.high_school_kids * float(model_parameters['HighSchoolCostPerKidI'])\
+ self.own_capital_properties.college_kids * float(model_parameters['CollegeCostPerKidI'])\
+ ( len(self.own_pp_dict) - self.own_capital_properties.preschool_kids - self.own_capital_properties.primary_school_kids
- self.own_capital_properties.secondary_school_kids - self.own_capital_properties.high_school_kids
- self.own_capital_properties.college_kids) * float(model_parameters['EverydayCostPerCapitaI'])
return min_living_cost
def get_actual_living_cost(self, model_parameters):
self.get_household_business_type()
if self.business_type == 0:
living_cost = self.own_capital_properties.preschool_kids * float(model_parameters['PreSchooleCostPerKidI'])\
+ self.own_capital_properties.primary_school_kids * float(model_parameters['PrimarySchoolCostPerKidI'])\
+ self.own_capital_properties.secondary_school_kids * float(model_parameters['SecondarySchoolCostPerKidI'])\
+ self.own_capital_properties.high_school_kids * float(model_parameters['HighSchoolCostPerKidI'])\
+ self.own_capital_properties.college_kids * float(model_parameters['CollegeCostPerKidI'])\
+ ( len(self.own_pp_dict) - self.own_capital_properties.preschool_kids - self.own_capital_properties.primary_school_kids
- self.own_capital_properties.secondary_school_kids - self.own_capital_properties.high_school_kids
- self.own_capital_properties.college_kids) * float(model_parameters['EverydayCostPerCapitaI'])
elif self.business_type == 1:
living_cost = self.own_capital_properties.preschool_kids * float(model_parameters['PreSchooleCostPerKidII'])\
+ self.own_capital_properties.primary_school_kids * float(model_parameters['PrimarySchoolCostPerKidII'])\
+ self.own_capital_properties.secondary_school_kids * float(model_parameters['SecondarySchoolCostPerKidII'])\
+ self.own_capital_properties.high_school_kids * float(model_parameters['HighSchoolCostPerKidII'])\
+ self.own_capital_properties.college_kids * float(model_parameters['CollegeCostPerKidII'])\
+ ( len(self.own_pp_dict) - self.own_capital_properties.preschool_kids - self.own_capital_properties.primary_school_kids
- self.own_capital_properties.secondary_school_kids - self.own_capital_properties.high_school_kids
- self.own_capital_properties.college_kids) * float(model_parameters['EverydayCostPerCapitaII'])
else:
living_cost = self.own_capital_properties.preschool_kids * float(model_parameters['PreSchooleCostPerKidIII'])\
+ self.own_capital_properties.primary_school_kids * float(model_parameters['PrimarySchoolCostPerKidIII'])\
+ self.own_capital_properties.secondary_school_kids * float(model_parameters['SecondarySchoolCostPerKidIII'])\
+ self.own_capital_properties.high_school_kids * float(model_parameters['HighSchoolCostPerKidIII'])\
+ self.own_capital_properties.college_kids * float(model_parameters['CollegeCostPerKidIII'])\
+ ( len(self.own_pp_dict) - self.own_capital_properties.preschool_kids - self.own_capital_properties.primary_school_kids
- self.own_capital_properties.secondary_school_kids - self.own_capital_properties.high_school_kids
- self.own_capital_properties.college_kids) * float(model_parameters['EverydayCostPerCapitaIII'])
self.AnnualTotalExpense = living_cost
return living_cost
def get_household_business_type(self):
if len(self.own_current_sectors) == 1 and self.own_current_sectors[0].SectorName == 'Agriculture':
self.business_type = 0
elif len(self.own_current_sectors) == 2:
if self.own_current_sectors[0].SectorName == 'Agriculture' or self.own_current_sectors[1].SectorName == 'Agriculture':
self.business_type = 1
else:
self.business_type = 2
self.HouseholdBusinessType = self.business_type
class Household(object):
'''
This is the definition of the household class
'''
def __init__(self, record, VarList, current_year, db, pp_table_name, pp_table, land_dict, model_parameters):
'''
Construct the household class from the household table in the DB, and then add some other user-defined attributes.
record - a record in the household table in the DB.
VarList - the variable (or field) list of the household table in the DB
VarList = {paramName1: paramOrder1, paramName2: paramOrder2, ...}
Also initialize the household's own person instances here from the person table in the DB.
Also initialize the household's capital properties instance here.
'''
# Set the attributes (var) and their values (record) from the household table in the DB.
for var in VarList:
setattr(self, var[0], record[var[1]])
# Set the household and person variables (attributes) lists
self.hh_var_list = VarList
self.pp_var_list = DataAccess.get_var_list(db, pp_table_name)
# Set the current time stamp
self.StatDate = current_year
# Define own persons (members) dict of the household, indexed by PID
self.own_pp_dict = dict()
# Add respective persons into the persons dict of the household
for pp in pp_table:
if pp.HID == self.HID:
pp_temp = Person(pp, self.pp_var_list, current_year)
self.own_pp_dict[pp_temp.PID] = pp_temp # Indexed by PID
# Initialize the household's capital properties class instance
self.own_capital_properties = CapitalProperty(self, land_dict, model_parameters)
# Define an empty list of available business sectors,
# and another empty list of the business sectors that the household is in in the current year
self.own_av_business_sectors = list()
self.own_current_sectors = list()
# Define an empty list of participant policy programs
self.own_policy_programs = list()
# Initialize the household's energy class instance
self.energy = Energy()
# Define a variable indicating the household's preference type
'''
1 - Max Labor, Min Risk;
2 - Min Labor, Min Risk;
3 - Max Labor, Max Risk;
4 - Min Labor, Max Risk;
'''
self.hh_preference_type = int()
# Also define a variable indicating the preference toward risks
'''
True - risk aversion; False - risk appetite;
'''
self.hh_risk_type = True
# Define a variable indicating the household's business type
'''
0 - agriculture only
1 - agriculture and another business sectors; or one business sector which is not agriculture
2 - agriculture and more than one other business sectors
'''
self.business_type = int()
# Define a switch variable indicating whether the household is dissolved in the current year
self.is_dissolved_this_year = False
def household_demographic_update(self, current_year, model_parameters):
'''
Annual demographic updates of the household.
'''
# Update the current time stamp
self.StatDate = current_year
# Reset the "dissolved this year" switch
# Note this is before the household existence bifurcation.
# So all households in society.hh_dict get this switch reset (every year).
self.is_dissolved_this_year = False
# Annual population dynamics (personal demographic status updates)
temp_pp_list = list()
for PID in self.own_pp_dict:
temp_pp_list.append(Person.personal_demographic_update(self.own_pp_dict[PID], current_year, model_parameters))
# Reset own persons (members) dict (own_pp_dict)
self.own_pp_dict = dict()
# Refresh own_pp_list
for p in temp_pp_list:
self.own_pp_dict[p.PID] = p
# Only the existing households proceed.
if self.is_exist == 1:
# Count alive members of the household who is not moved out
alive_members_count = 0
for PID in self.own_pp_dict:
if self.own_pp_dict[PID].is_alive == 1 and self.own_pp_dict[PID].moved_out == False:
alive_members_count += 1
# If the updated household has no alive and not-moved-out members, mark it as non-exist.
if alive_members_count == 0:
self.is_exist = 0
self.is_dissolved_this_year = True # Turn on this switch so that the household could be dissolved later in the society class
# Then deal with the deceased persons
for p in temp_pp_list:
# If p dies this year and p's spouse lives
if p.is_died_this_year == True and p.SpouseID != '0' and self.own_pp_dict[p.SpouseID].is_alive == 1:
# Then p's spouse's marital status changes
self.own_pp_dict[p.SpouseID].IsMarry = 0
self.own_pp_dict[p.SpouseID].SpouseID = '0'
# And p's own marital status is also marked changed
self.own_pp_dict[p.PID].IsMarry = 0
self.own_pp_dict[p.PID].SpouseID = '0'
return self
def household_economy(self, policies, business_sectors, model_parameters):
'''
The (annual) economic activities of the household. Including household's preference categorization,
policy-related decision-making,and production and consumption activities.
'''
# Determine the household's preferences
self.housedhold_categorization()
# Make policy decisions
self.household_policy_decision(policies, business_sectors, model_parameters)
# Do the business
# The second parameter, risk_effective = True, indicating it is a "real world" run this time,
# as opposed to the two "hypothetical" runs in the previous step, the policy decision step,
# when risk_effective = False. i.e. random factors don't take effect in households' economy decision-making process.
self.own_capital_properties = self.household_business_revenue(self.own_capital_properties,
business_sectors, model_parameters, risk_effective=True)
# Household's final accountings for the year
self.household_final_accounting(model_parameters)
def housedhold_categorization(self):
'''
Categorize the households according to their preferences toward risk and labor/leisure trade-off
For combined (risk + labor/leisure) household preference types:
1 - Max Labor, Min Risk;
2 - Min Labor, Min Risk;
3 - Max Labor, Max Risk;
4 - Min Labor, Max Risk;
For risk preference types:
True - risk aversion; False - risk appetite;
'''
# Risk Preference
# Define variables in the formula for risk preference determination
# # is_truck
# if self.own_capital_properties.truck > 0:
# is_truck = 1
# else:
# is_truck = 0
#
# # is_minibus
# if self.own_capital_properties.minibus > 0:
# is_minibus = 1
# else:
# is_minibus = 0
# house_size
house_size = self.own_capital_properties.house_area
high_school_kids = self.own_capital_properties.high_school_kids
# p_risk = math.exp(6.702 + 0.749 * is_truck + 1.748 * is_minibus + 0.004 * house_size -
# 1.436 * high_school_kids + 0.775 * self.NonRural -
# 0.005 * self.Elevation) / (1 + math.exp(6.702 + 0.749 * is_truck + 1.748 * is_minibus +
# 0.004 * house_size - 1.436 * high_school_kids +
# 0.775 * self.NonRural - 0.005 * self.Elevation))
p_risk = math.exp(6.702 + 0.004 * house_size - 1.436 * high_school_kids + 0.775 * self.NonRural -
0.005 * self.Elevation) / (1 + math.exp(6.702 + 0.004 * house_size - 1.436 * high_school_kids +
0.775 * self.NonRural - 0.005 * self.Elevation))
# Labor Preference
# p_labor = math.exp(0.461 * self.own_capital_properties.labor) / (1 + math.exp(0.461 * self.own_capital_properties.labor))
labor_pref = 0
if self.own_capital_properties.young_male_labor == 0 and self.own_capital_properties.kids == 0:
labor_pref = 0
else:
labor_pref = 1
if p_risk < 0.5:
if labor_pref == 1:
self.hh_preference_type = 1
self.hh_risk_type = True
else:
self.hh_preference_type = 2
self.hh_risk_type = True
else:
if labor_pref == 1:
self.hh_preference_type = 3
self.hh_risk_type = False
else:
self.hh_preference_type = 4
self.hh_risk_type = False
def household_policy_decision(self, policy_dict, business_sector_dict, model_parameters):
if self.own_capital_properties.farm_to_forest != 0: # Has already joined the farm to forest program
# Just apply the policies from the last year
self.household_apply_policy(model_parameters)
elif self.own_capital_properties.farm_to_forest == 0 and self.own_capital_properties.farmland != 0:
# Has not yet joined the farm to forest program, but has the potential to do so (household has farmland).
hyp_capital_1 = copy.deepcopy(self.own_capital_properties)
hyp_capital_2 = copy.deepcopy(self.own_capital_properties)
# Reset the self.own_policy_programs list
self.own_policy_programs = list()
# First, run the business and get the hypothetical household capital properties condition when no OPTIONAL policy programs apply.
# Note that the household's capital properties have been updated in the application process of the programs
for PolicyType in policy_dict:
if policy_dict[PolicyType].IsCompulsory == 1: # Only consider the compulsory programs
hyp_capital_1 = Policy.apply_policy_terms(policy_dict[PolicyType], hyp_capital_1, model_parameters)
self.own_policy_programs.append(policy_dict[PolicyType])
# Get all compensational revenues
compensation_1 = hyp_capital_1.cash - self.own_capital_properties.cash
# Do the business based on hyp_capital_1
hyp_capital_1 = self.household_business_revenue(hyp_capital_1, business_sector_dict, model_parameters, risk_effective=False)
# Get the total household revenues in this occasion
revenue_1 = hyp_capital_1.get_total_business_income() + compensation_1
# Second, get the hypothetical household capital properties condition when ALL policy programs are applied
# In this project's case, this means including an OPTIONAL program: the farmland to forest program
for PolicyType in policy_dict:
hyp_capital_2 = Policy.apply_policy_terms(policy_dict[PolicyType], hyp_capital_2, model_parameters)
# Get all compensational revenues
compensation_2 = hyp_capital_2.cash - self.own_capital_properties.cash
# Do the business based on hyp_capital_2
hyp_capital_2 = self.household_business_revenue(hyp_capital_2, business_sector_dict, model_parameters, risk_effective=False)
# Get the total household revenues in this occasion
revenue_2 = hyp_capital_2.get_total_business_income() + compensation_2
# Make the decision
'''
self.hh_preference_type:
1 - Max Labor, Min Risk;
2 - Min Labor, Min Risk;
3 - Max Labor, Max Risk;
4 - Min Labor, Max Risk;
'''
if self.hh_preference_type == 1 or self.hh_preference_type == 3: # Prefers Labor
if revenue_2 > revenue_1:
# Then join in the programs
for PolicyType in policy_dict:
if policy_dict[PolicyType].IsCompulsory == 0: # Add the optional programs into household's own programs dictionary
self.own_policy_programs.append(policy_dict[PolicyType])
else: # Prefers Leisure
if compensation_2 > self.get_min_living_cost(model_parameters):
# If all compensational revenues, including those from participation in the optional programs,
# is higher than the household's minimum living cost,
# Then join in the programs
for PolicyType in policy_dict:
if policy_dict[PolicyType].IsCompulsory == 0: # Add the optional programs into household's own programs dictionary
self.own_policy_programs.append(policy_dict[PolicyType])
# When the decision is made,
# Apply the policies to get the renewed household's own capital properties condition
# to get prepared for the "real world" run.
self.household_apply_policy(model_parameters)
# # If the household joins in the farmland to forest program this year,
# # remove the land parcels in their own_capital_properties.land_properties_list,
# # and mark these farmland parcels' succession start year as this year.
# for program in self.own_policy_programs:
# if program.PolicyType == 'FarmToForest_After':
# for farmland_parcel in self.own_capital_properties.land_properties_list:
# farmland_parcel.is_ftof = 1
# farmland_parcel.succession_start_year = self.StatDate
# self.own_capital_properties.land_properties_list.remove(farmland_parcel)
def household_apply_policy(self, model_parameters):
# Update the household's own capital properties conditions according to the policy decisions
# and also get compensational revenues (done in the policy class)
for program in self.own_policy_programs:
self.own_capital_properties = Policy.apply_policy_terms(program, self.own_capital_properties, model_parameters)
def household_business_revenue(self, hh_capital, business_sector_dict, model_parameters, risk_effective):
'''
The process of a household doing business.
business_sector_dict: all business sectors. i.e. society.business_sector_dict.
risk_effective - whether the random risk factor takes effect in the calculation. True - real world; False: hypothetical.
'''
self.get_available_business(hh_capital, business_sector_dict)
self.get_rank_available_business(hh_capital, self.own_av_business_sectors, model_parameters)
hh_capital = self.do_business(hh_capital, self.own_av_business_sectors, model_parameters, risk_effective)
return hh_capital
def get_available_business(self, hh_capital, business_sector_dict):
'''
Get the available (enter-able) business sectors list for the household.
hh_capital: household's capital properties (factors of production) i.e. self.own_capital_properties;
business_sector_dict: all business sectors. i.e. society.business_sector_dict.
'''
# Reset the own available business sectors list
self.own_av_business_sectors = list()
if self.hh_preference_type == 1 or self.hh_preference_type == 2:
# Risk aversion. No loans. risk_type = True
for SectorName in business_sector_dict:
if business_sector_dict[SectorName].is_doable(hh_capital, risk_type=True) == True:
self.own_av_business_sectors.append(business_sector_dict[SectorName])
else:
# Risk appetite. risk_type = False
for SectorName in business_sector_dict:
if business_sector_dict[SectorName].is_doable(hh_capital, risk_type=False) == True:
self.own_av_business_sectors.append(business_sector_dict[SectorName])
def get_rank_available_business(self, hh_capital, business_list, model_parameters):
'''
Rank the business sectors in the household's available business sectors list according to the household's specific preference.
hh_capital: household's capital properties (factors of production);
business_list: the available business sectors list for the household.
'''
temp_sectors_list = list()
if self.hh_preference_type == 1:
'''
Max Labor, Min Risk - risk_type = True
'''
# Get the hypothetical profit of each sector if entered
for sector in business_list:
profit = sector.calculate_business_revenue(hh_capital, model_parameters, risk_type=True, risk_effective=False).cash - hh_capital.cash
temp_sectors_list.append((profit, sector))
# Rank the sectors by profit descendedly
temp_sectors_list.sort(reverse = True)
# Refresh the household's available business sectors list
self.own_av_business_sectors = list()
# Always place agriculture (if enter-able) in the first place
for item in temp_sectors_list:
if item[1].SectorName == 'Agriculture':
self.own_av_business_sectors.append(item[1])
temp_sectors_list.remove(item)
# Then add other sectors
for item in temp_sectors_list:
self.own_av_business_sectors.append(item[1])
elif self.hh_preference_type == 2:
'''
Min Labor, Min Risk - risk_type = True
'''
# Get the hypothetical labor cost of each sector if entered
for sector in business_list:
labor_cost = sector.calculate_business_revenue(hh_capital, model_parameters, risk_type=True, risk_effective=False).labor_cost - hh_capital.labor_cost
temp_sectors_list.append((labor_cost, sector))
# Rank the sectors by labor cost ascendedly
temp_sectors_list.sort()
# Refresh the household's available business sectors list
self.own_av_business_sectors = list()
# Add sectors
for item in temp_sectors_list:
self.own_av_business_sectors.append(item[1])
elif self.hh_preference_type == 3:
'''
Max Labor, Max Risk - risk_type = False
'''
# Get the hypothetical profit of each sector if entered
for sector in business_list:
profit = sector.calculate_business_revenue(hh_capital, model_parameters, risk_type=False, risk_effective=False).cash - hh_capital.cash
temp_sectors_list.append((profit, sector))
# Rank the sectors by profit descendedly
temp_sectors_list.sort(reverse = True)
# Refresh the household's available business sectors list
self.own_av_business_sectors = list()
# Always place agriculture (if enter-able) in the first place
for item in temp_sectors_list:
if item[1].SectorName == 'Agriculture':
self.own_av_business_sectors.append(item[1])
temp_sectors_list.remove(item)
# Then add other sectors
for item in temp_sectors_list:
self.own_av_business_sectors.append(item[1])
elif self.hh_preference_type == 4:
'''
Min Labor, Max Risk - risk_type = False
'''
# Get the hypothetical labor cost of each sector if entered
for sector in business_list:
labor_cost = sector.calculate_business_revenue(hh_capital, model_parameters, risk_type=False, risk_effective=False).labor_cost - hh_capital.labor_cost
temp_sectors_list.append((labor_cost, sector))
# Rank the sectors by labor cost ascendedly
temp_sectors_list.sort()
# Refresh the household's available business sectors list
self.own_av_business_sectors = list()
# Add sectors
for item in temp_sectors_list:
self.own_av_business_sectors.append(item[1])
def do_business(self, hh_capital, business_list, model_parameters, risk_effective):
'''
risk_effective - whether the random risk factor takes effect in the calculation. True - real world; False: hypothetical.
'''
# Reset the houosehold's current sector list
self.own_current_sectors = list()
if self.hh_preference_type == 1 or self.hh_preference_type == 3:
'''
1 - Max Labor, Min Risk; 3 - Max Labor, Max Risk;
'''
for sector in self.own_av_business_sectors:
hh_capital = BusinessSector.calculate_business_revenue(sector, hh_capital, model_parameters,
self.hh_risk_type, risk_effective)
self.own_current_sectors.append(sector)
if hh_capital.av_labor <= 0:
# Exit condition: household running out of its labor resource
break
elif self.hh_preference_type == 2 or self.hh_preference_type == 4:
'''
2 - Min Labor, Min Risk; 4 - Min Labor, Max Risk.
'''
# old_cash = hh_capital.cash
for sector in self.own_av_business_sectors:
if hh_capital.get_total_business_income() + hh_capital.compensational_revenues >= self.get_min_living_cost(model_parameters):
# Exit condition: this year's total income >= minimal living cost
break
else:
hh_capital = BusinessSector.calculate_business_revenue(sector, hh_capital, model_parameters,
self.hh_risk_type, risk_effective)
self.own_current_sectors.append(sector)
return hh_capital
def household_final_accounting(self, model_parameters):
'''
Household's final cash capital = own_capital_properties.cash - actual_living_cost - loan_payments
'''
actual_living_cost = self.get_actual_living_cost(model_parameters)
# Subtract living costs from cash reserve; if insufficient, go into debt.
if self.own_capital_properties.cash < actual_living_cost:
self.own_capital_properties.debt = self.own_capital_properties.debt + (actual_living_cost - self.own_capital_properties.cash)
self.own_capital_properties.cash = 0
else:
self.own_capital_properties.cash = self.own_capital_properties.cash - actual_living_cost
# Then pay the debts, if any, with up to half the household cash reserve.
payment = self.own_capital_properties.cash / 2
if self.own_capital_properties.debt > 0:
if payment <= self.own_capital_properties.debt:
self.own_capital_properties.cash = self.own_capital_properties.cash - payment
self.own_capital_properties.debt = self.own_capital_properties.debt - payment
else:
self.own_capital_properties.cash = self.own_capital_properties.cash - self.own_capital_properties.debt
self.own_capital_properties.debt = 0
# Then calculate the household's net savings
self.own_capital_properties.netsavings = self.own_capital_properties.cash - self.own_capital_properties.debt
# Finally, update the household's capital properties from the Capital Property Class
self.own_capital_properties.update_household_capital_properties(self)
def get_min_living_cost(self, model_parameters):
min_living_cost = self.own_capital_properties.preschool_kids * float(model_parameters['PreSchooleCostPerKidI'])\
+ self.own_capital_properties.primary_school_kids * float(model_parameters['PrimarySchoolCostPerKidI'])\
+ self.own_capital_properties.secondary_school_kids * float(model_parameters['SecondarySchoolCostPerKidI'])\
+ self.own_capital_properties.high_school_kids * float(model_parameters['HighSchoolCostPerKidI'])\
+ self.own_capital_properties.college_kids * float(model_parameters['CollegeCostPerKidI'])\
+ ( len(self.own_pp_dict) - self.own_capital_properties.preschool_kids - self.own_capital_properties.primary_school_kids
- self.own_capital_properties.secondary_school_kids - self.own_capital_properties.high_school_kids
- self.own_capital_properties.college_kids) * float(model_parameters['EverydayCostPerCapitaI'])
return min_living_cost
def get_actual_living_cost(self, model_parameters):
self.get_household_business_type()
if self.business_type == 0:
living_cost = self.own_capital_properties.preschool_kids * float(model_parameters['PreSchooleCostPerKidI'])\
+ self.own_capital_properties.primary_school_kids * float(model_parameters['PrimarySchoolCostPerKidI'])\
+ self.own_capital_properties.secondary_school_kids * float(model_parameters['SecondarySchoolCostPerKidI'])\
+ self.own_capital_properties.high_school_kids * float(model_parameters['HighSchoolCostPerKidI'])\
+ self.own_capital_properties.college_kids * float(model_parameters['CollegeCostPerKidI'])\
+ ( len(self.own_pp_dict) - self.own_capital_properties.preschool_kids - self.own_capital_properties.primary_school_kids
- self.own_capital_properties.secondary_school_kids - self.own_capital_properties.high_school_kids
- self.own_capital_properties.college_kids) * float(model_parameters['EverydayCostPerCapitaI'])
elif self.business_type == 1:
living_cost = self.own_capital_properties.preschool_kids * float(model_parameters['PreSchooleCostPerKidII'])\
+ self.own_capital_properties.primary_school_kids * float(model_parameters['PrimarySchoolCostPerKidII'])\
+ self.own_capital_properties.secondary_school_kids * float(model_parameters['SecondarySchoolCostPerKidII'])\
+ self.own_capital_properties.high_school_kids * float(model_parameters['HighSchoolCostPerKidII'])\
+ self.own_capital_properties.college_kids * float(model_parameters['CollegeCostPerKidII'])\
+ ( len(self.own_pp_dict) - self.own_capital_properties.preschool_kids - self.own_capital_properties.primary_school_kids
- self.own_capital_properties.secondary_school_kids - self.own_capital_properties.high_school_kids
- self.own_capital_properties.college_kids) * float(model_parameters['EverydayCostPerCapitaII'])
else:
living_cost = self.own_capital_properties.preschool_kids * float(model_parameters['PreSchooleCostPerKidIII'])\
+ self.own_capital_properties.primary_school_kids * float(model_parameters['PrimarySchoolCostPerKidIII'])\
+ self.own_capital_properties.secondary_school_kids * float(model_parameters['SecondarySchoolCostPerKidIII'])\
+ self.own_capital_properties.high_school_kids * float(model_parameters['HighSchoolCostPerKidIII'])\
+ self.own_capital_properties.college_kids * float(model_parameters['CollegeCostPerKidIII'])\
+ ( len(self.own_pp_dict) - self.own_capital_properties.preschool_kids - self.own_capital_properties.primary_school_kids
- self.own_capital_properties.secondary_school_kids - self.own_capital_properties.high_school_kids
- self.own_capital_properties.college_kids) * float(model_parameters['EverydayCostPerCapitaIII'])
self.AnnualTotalExpense = living_cost
return living_cost
def get_household_business_type(self):
if len(self.own_current_sectors) == 1 and self.own_current_sectors[0].SectorName == 'Agriculture':
self.business_type = 0
elif len(self.own_current_sectors) == 2:
if self.own_current_sectors[0].SectorName == 'Agriculture' or self.own_current_sectors[1].SectorName == 'Agriculture':
self.business_type = 1
else:
self.business_type = 2
self.HouseholdBusinessType = self.business_type