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view/download model file: happiness_from_consumerism_or_altruism.nlogo
My model aims to explore the links among level of happiness of people with their own income and income of others.
The agents are represented by patches, they have an own income that it is used to buy the unique desirable good existing in the world; after the buying the agents make a comparison with others in the world and set their own status of happiness (represented as a dichotomy - happy or unhappy -). Agents when asked to compare can follow one of the two available behaviors:
- consumerist attitude: each agent characterizes himself as happy if he bought a greater amount of the good with respect to others agents in its reference group
- altruistic attitue: each agent characterizes himself as happy if he evaluate that the differences among agents in its reference group are quite small
After that agents work with the result of producing the good and receiving a wage.
SETUP button: create the world coherently with parameters indicated by user
GO button: start the simulation
increase_own_income_of_100%: when pressed doubles the income of all agents
- %_top: define the percentual of agents in the world that have do be classified as belonging to upper class (% of agents richer), the remaining one are classified as belonging to lower class
- radius_of_looking: fix a boundary to where agents can look to determine their reference group
- altruistic_satisfaction: only in altruistic context it defines the threshold until which the variance of good received makes an agent happy
- global_good_quantity: initial level of good available
- initial_income_reference: fix a sort of reference level for the initial distribution of income (in case of random distribution it is the max level assignable)
- behaviour: define the attitude that agents must follow
- work_behaviour: set the strategy of work that agents must follow
- mantain_stock: determine the policy about the eventually stock of good
- only_look_to_similar: tell agents if in the determination of reference group they have to consider everybody or rather only other agents belonging to their same category
The plots and monitor are self-explanatory.
The final result is not the only important thing, look also at the world during the intermediate step; some particular structures like temporary-aggregation may show up. Moreover if parameters named radius_of_looking or altruistic_satisfaction are greater then the adjustments in the world are faster.
It is interesting to control for the parameter only_look_to_similar and check the different patterns that arise.
Try also to hit the world with a shock as it is a complete unpredicted doubing of income, it is clearly observable that this has effects only when agents are in an altruistic context.
globals [sum_desired
available_good
sum_donated
sum_inequality
num_top
ordered_list_income
price_good]
patches-own [own_income
last_wage
comparison_group
others_received_mean
others_received_var
others_received_stdev
received
desired
donated
inequality
category
production
happiness]
to setup
clear-all
set price_good 10
ask patches [
;set own_income (random-gamma initial_income_reference 10) ;useful for changes on-the-fly
set own_income (random-float initial_income_reference)
set happiness one-of ["yes" "no"]]
evaluate_rank
assign_color
end
to evaluate_rank
set num_top (round(count patches * %_top))
set ordered_list_income reverse(sort([own_income] of patches))
;set ordered_list_income sort([own_income] of patches) ;useful for changes on-the-fly
ask patches [ifelse %_top != 0 [
ifelse (own_income >= item (num_top - 1) ordered_list_income) [set category "top"]
[set category "down"]]
[set category "down"]]
end
to assign_color
ask patches [
if (happiness = "yes") and (category = "top") [set pcolor 57]
if (happiness = "no") and (category = "top") [set pcolor 17]
if (happiness = "yes") and (category = "down") [set pcolor 55]
if (happiness = "no") and (category = "down") [set pcolor 15]]
end
to go
set available_good global_good_quantity
evaluate_rank
do_plots_income
ask patches [set last_wage own_income]
ask patches [compute_desired]
set sum_desired (sum [desired] of patches)
ask patches [receive]
evaluate_stock
ask patches [compute_reference]
if behaviour = "altruistic"[ask patches [donate]
set sum_donated (sum [donated] of patches)
set sum_inequality (sum [inequality] of patches)
ask patches with [donated = 0] [accept_donated]
ask patches [compare_altruistic]
ask patches [work]]
if behaviour = "consumerist"[ask patches [compare_consumerist]
ask patches [work]]
set global_good_quantity ((sum [production] of patches) + available_good)
assign_color
do_plots_happiness
ask patches [set others_received_var 0
set others_received_stdev 0]
tick
end
to compute_reference
if only_look_to_similar = "no" [set comparison_group patches in-radius radius_of_looking]
if only_look_to_similar = "yes" [set comparison_group patches in-radius radius_of_looking with [category = [category] of myself]]
set others_received_mean (mean [received] of comparison_group)
if count comparison_group != 1 [set others_received_var (variance [received] of comparison_group)
set others_received_stdev (standard-deviation [received] of comparison_group)]
end
to compute_desired
set desired (own_income / price_good)
end
to receive
ifelse global_good_quantity >= sum_desired [set received desired]
[set received (desired * global_good_quantity / sum_desired)]
set available_good (available_good - received)
set own_income (own_income - (price_good * received))
end
to evaluate_stock
if mantain_stock = "no" [set available_good 0]
end
to compare_altruistic
compute_reference
ifelse others_received_var <= altruistic_satisfaction [set happiness "yes"]
[set happiness "no"]
end
to compare_consumerist
ifelse received >= others_received_mean [set happiness "yes"]
[set happiness "no"]
end
to donate
ifelse received >= others_received_mean [set donated (received - others_received_mean)
set received (received - donated)]
[set inequality (others_received_mean - received)]
end
to accept_donated
ifelse sum_donated >= sum_inequality [set received (received + inequality)]
[set received (received + (inequality * sum_donated / sum_inequality))]
end
to work
if work_behaviour = "random" [set own_income (last_wage * random-normal 1 0.15)
set production ((own_income / price_good) * random-normal 1 0.05)]
if work_behaviour = "copying_other_people" [set own_income ((others_received_mean * price_good) * random-normal 1 0.0)
set production ((own_income / price_good) * random-normal 1 0.05)]
end
to do_plots_happiness
set-current-plot "lower_people"
set-current-plot-pen "happy"
plot count patches with [pcolor = green]
set-current-plot-pen "unhappy"
plot count patches with [pcolor = red]
set-current-plot "upper_people"
set-current-plot-pen "happy"
plot count patches with [pcolor = 57]
set-current-plot-pen "unhappy"
plot count patches with [pcolor = 17]
set-current-plot "diversity_in_world"
set-current-plot-pen "upper"
plot count patches with [category = "top"]
set-current-plot-pen "lower"
plot count patches with [category = "down"]
end
to do_plots_income
set-current-plot "income_average"
set-current-plot-pen "aver"
plot mean [own_income] of patches
set-current-plot "income_max"
set-current-plot-pen "max"
plot first ordered_list_income
set-current-plot "income_min"
set-current-plot-pen "min"
plot last ordered_list_income
set-current-plot "income_reference"
set-current-plot-pen "ref"
if %_top != 0 [plot item (num_top - 1) ordered_list_income]
end