Car Tax Model

;; VERSION 3-September-2020 6:00
;; With more cars

extensions [csv table]

breed [ cars car ]
breed [ buyers buyer ]

globals [
  coef_uv_list ; coefficient of utility variables list. Mind the order!
  mu_car       ; mu coefficient table for the nested logit at the second step
  c_car

  ;; buyers variable coefficients
  b-hh-size
  b-spending1 b-spending2 b-spending3 b-spending4
  b-sex
  b-age1 b-age2 b-age3 b-age4 b-age5 b-age6 b-age7 b-age8
  b-ocp1 b-ocp2 b-ocp3 b-ocp4

  ;; cars variabel coefficients
  b-fuelcost
  b-co2
  b-price
  b-kerbweight
  b-dimension
  b-gasoline
  b-manual
]

cars-own [
  variant
  brand
  fuelconsmp
  fuelcost
  co2
  price
  kerbweight
  len
  width
  height
  gasoline
  manual
  chosen?       ; boolean variable mobil dipilih oleh pembeli
  dimension
  cars_uv_list
  car_utility
]

buyers-own [
  hh-size       ; ukuran rumah tangga. Jumlah seluruh orang dalam rumah tangga. (rasio)

  ;; pengeluaran per orang per bulan berdasarkan World Bank (2019), 5 kelas
  spending1  ; <354 ribu
  spending2  ; 354 ribu - 532 ribu
  spending3  ; 532 ribu - 1,2 juta
  spending4  ; 1,2 juta - 6,0 juta
  ;spending5 >6,0 juta. Tapi kan tidak ada variabelnya.

  sex           ; jenis kelamin. (nominal)

  ;; usia, 9 kelas
  age1       ; 21 - 25 tahun
  age2       ; 26 - 30 tahun
  age3       ; 31 - 35 tahun
  age4       ; 36 - 40 tahun
  age5       ; 41 - 45 tahun
  age6       ; 46 - 50 tahun
  age7       ; 51 - 55 tahun
  age8       ; 56 - 60 tahun
  ;age9 >60 tahun.

  ;; pekerjaan, nominal
  occupation1  ; swasta
  occupation2  ; pelajar/mahasiswa
  occupation3  ; TNI/Polri
  occupation4  ; PNS
  ;occupation5  BUMN.

  ;; choice-related variables
  cset-size
  who-choice-set
  car-choice

  buyers_uv_list
  uv_list
  buyer_utility
  utility

  ; tables related to cars agentset
  table_lefthalf
  table_righthalf
  table_exp_nested_sums
  brand_list
  table_car_probs
]

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to setup
  clear-all         ;; start over the model clean
  file-close-all    ;; close any files open from last run

  set-buyers        ;; setup the car buyers condition using 'set-buyers' procedure
  set-cars          ;; setup the car condition using 'set-cars' procedure

  ;; setting the list for the utility function coefficients in the second step logit model
  ;; make sure not to change the order
  set b-hh-size 1
  set b-spending1 1 set b-spending2 1 set b-spending3 1 set b-spending4 1
  set b-sex 1
  set b-age1 1 set b-age2 1 set b-age3 1 set b-age4 1
  set b-age5 1 set b-age6 1 set b-age7 1 set b-age8 1
  set b-ocp1 1 set b-ocp2 1 set b-ocp3 1 set b-ocp4 1
  set b-fuelcost 1
  set b-co2 1
  set b-price -0.063
  set b-kerbweight 1
  set b-dimension 1
  set b-gasoline 1
  set b-manual 1

  set coef_uv_list (
    list b-hh-size b-spending1 b-spending2 b-spending3 b-spending4 b-sex
         b-age1 b-age2 b-age3 b-age4 b-age5 b-age6 b-age7 b-age8
         b-ocp1 b-ocp2 b-ocp3 b-ocp4 b-fuelcost b-price b-kerbweight
         b-dimension b-gasoline b-manual )

  ;; same goes for the buyers agent
  ask buyers [
    set buyers_uv_list ( list hh-size spending1 spending2 spending3 spending4 spending4 sex
    age1 age2 age3 age4 age4 age5 age6 age7 age8 occupation1 occupation2 occupation3
    occupation4 )

    set buyer_utility
    (b-hh-size * hh-size) + (b-spending1 * spending1) + (b-spending2 * spending2) + (b-spending3 * spending3) +
    (b-spending4 * spending4) + (b-sex * sex) + (b-age1 * age1) + (b-age2 * age2) + (b-age3 * age3) +
    (b-age4 * age4) + (b-age5 * age5) + (b-age6 * age6) + (b-age7 * age7) + (b-age8 * age8) +
    (b-ocp1 * occupation1) + (b-ocp2 * occupation2) + (b-ocp3 * occupation3) + (b-ocp4 * occupation4)
  ]

  ask cars [
    ;; asking cars to count their car-side utility value
    set car_utility (b-fuelcost * fuelcost) + (b-co2 * co2) + (b-price * price) + (b-dimension * dimension) +
                    (b-gasoline * gasoline) + (b-manual * manual) + (b-kerbweight * kerbweight)
  ]

  ;; making the c_car table
  set mu_car table:make
  set c_car table:make

  ;; storing each car brand with its own mu coefficient
  table:put mu_car "Aston Martin" 1.0   table:put mu_car "Audi" 1.5
  table:put mu_car "Bentley" 2.0        table:put mu_car "BMW" 2.5
  table:put mu_car "Chevrolet" 1.0
  table:put mu_car "Daihatsu" 1.2       table:put mu_car "Datsun" 3.5
  table:put mu_car "DFSK" 3.0           table:put mu_car "Dodge" 3.5
  table:put mu_car "Fiat" 1.4
  table:put mu_car "Honda" 1.3          table:put mu_car "Hyundai" -2.5
  table:put mu_car "Isuzu" 2.3
  table:put mu_car "Jaguar" 1.9         table:put mu_car "Jeep" 1.7
  table:put mu_car "KIA" 1.1
  table:put mu_car "Lamborghini" 1.1    table:put mu_car "Land Rover" 1.6   table:put mu_car "Lexus" 1.7
  table:put mu_car "Mahindra" 1.9       table:put mu_car "Maserati" 1.2     table:put mu_car "Mazda" 2.3
  table:put mu_car "Mercedes-Benz" 4.0
  table:put mu_car "MG" 4.0             table:put mu_car "MINI" 2.0         table:put mu_car "Mitsubishi" 3.0
  table:put mu_car "Nissan" 3.1
  table:put mu_car "Peugeot" 3.3        table:put mu_car "Porsche" 3.4
  table:put mu_car "Renault" 2.9        table:put mu_car "Rolls Royce" 1.7
  table:put mu_car "Suzuki" 2.9
  table:put mu_car "Toyota" 1.3
  table:put mu_car "Volkswagen" 1       table:put mu_car "Volvo" 1
  table:put mu_car "Wuling" 1

  ;; storing each car brand with its own car constant
  table:put c_car "Aston Martin" 1      table:put c_car "Audi" 1
  table:put c_car "Bentley" 1           table:put c_car "BMW" 1
  table:put c_car "Chevrolet" 1
  table:put c_car "Daihatsu" 1          table:put c_car "Datsun" 1
  table:put c_car "DFSK" 1              table:put c_car "Dodge" 1
  table:put c_car "Fiat" 1
  table:put c_car "Honda" 1             table:put c_car "Hyundai" 1
  table:put c_car "Isuzu" 1
  table:put c_car "Jaguar" 1            table:put c_car "Jeep" 1
  table:put c_car "KIA" 1
  table:put c_car "Lamborghini" 1       table:put c_car "Land Rover" 1   table:put c_car "Lexus" 1
  table:put c_car "Mahindra" 1          table:put c_car "Maserati" 1     table:put c_car "Mazda" 1
  table:put c_car "Mercedes-Benz" 1
  table:put c_car "MG" 1                table:put c_car "MINI" 1         table:put c_car "Mitsubishi" 1
  table:put c_car "Nissan" 1
  table:put c_car "Peugeot" 1           table:put c_car "Porsche" 1
  table:put c_car "Renault" 1           table:put c_car "Rolls Royce" 1
  table:put c_car "Suzuki" 1
  table:put c_car "Toyota" 1
  table:put c_car "Volkswagen" 1        table:put c_car "Volvo" 1
  table:put c_car "Wuling" 1

  setup-plots
  update-plots
end 

to set-buyers    ;; buyers procedure.
  ifelse not file-exists? buyers_file [
    user-message "Tidak ditemukan file 'file_read_buyers.csv'. Mohon periksa kembali nama atau lokasi file tersebut."
    stop ]
  [ file-open buyers_file ]

  ;; Membaca seluruh data dalam satu loop
  while [ not file-at-end? ] [
    ; here the csv extension grabs a single line and puts the read data in a list
    let baca (csv:from-row file-read-line ";")
    ; now we can use that list to create a turtle with the saved properties

    create-buyers 1 [
      set hh-size item 0 baca

      ;; setting spending1 - spending5 value
      ( ifelse
        item 1 baca = 1
        [ set spending1 1  set spending2 0  set spending3 0  set spending4 0 ]
        item 1 baca = 2
        [ set spending1 0  set spending2 1  set spending3 0  set spending4 0 ]
        item 1 baca = 3
        [ set spending1 0  set spending2 0  set spending3 1  set spending4 0 ]
        item 1 baca = 4
        [ set spending1 0  set spending2 0  set spending3 0  set spending4 1 ]
        [ set spending1 0  set spending2 0  set spending3 0  set spending4 0 ])

      ;; setting occupation1 - occupation5 value
      ( ifelse
        item 2 baca = 1
        [ set occupation1 1  set occupation2 0  set occupation3 0  set occupation4 0 ]
        item 2 baca = 2
        [ set occupation1 0  set occupation2 1  set occupation3 0  set occupation4 0 ]
        item 2 baca = 3
        [ set occupation1 0  set occupation2 0  set occupation3 1  set occupation4 0 ]
        item 2 baca = 4
        [ set occupation1 0  set occupation2 0  set occupation3 0  set occupation4 1 ]
        [ set occupation1 0  set occupation2 0  set occupation3 0  set occupation4 0 ] )

      set sex item 3 baca

      ;; setting age1 - age9 value
      ( ifelse
        item 4 baca = 1
        [ set age1 1  set age2 0  set age3 0  set age4 0
          set age5 0  set age6 0  set age7 0  set age8 0 ]
        item 4 baca = 2
        [ set age1 0  set age2 1  set age3 0  set age4 0
          set age5 0  set age6 0  set age7 0  set age8 0 ]
        item 4 baca = 3
        [ set age1 0  set age2 0  set age3 1  set age4 0
          set age5 0  set age6 0  set age7 0  set age8 0 ]
        item 4 baca = 4
        [ set age1 0  set age2 0  set age3 0  set age4 1
          set age5 0  set age6 0  set age7 0  set age8 0 ]
        item 4 baca = 5
        [ set age1 0  set age2 0  set age3 0  set age4 0
          set age5 1  set age6 0  set age7 0  set age8 0 ]
        item 4 baca = 6
        [ set age1 0  set age2 0  set age3 0  set age4 0
          set age5 0  set age6 1  set age7 0  set age8 0 ]
        item 4 baca = 7
        [ set age1 0  set age2 0  set age3 0  set age4 0
          set age5 0  set age6 0  set age7 1  set age8 0 ]
        item 4 baca = 8
        [ set age1 0  set age2 0  set age3 0  set age4 0
          set age5 0  set age6 0  set age7 0  set age8 1 ]
        [ set age1 0  set age2 0  set age3 0  set age4 0
          set age5 0  set age6 0  set age7 0  set age8 0 ] )
    ]

    ask buyers [
      set shape        "person"
      set color        green
      let bound-buyers random -45 - 5
      set xcor         random-xcor
      set ycor         random-ycor ]
  ]

  file-close ;; make sure to close the file
end 

to set-cars  ;; cars procedure.

  ifelse not file-exists? cars_file [
    user-message "Tidak ditemukan file 'file_read_cars.csv'. Mohon periksa kembali nama atau lokasi file tersebut."
    stop ]
  [ file-open cars_file ]

  ;; Membaca seluruh data dalam satu loop
  while [ not file-at-end? ][
    ; here the csv extension grabs a single line and puts the read data in a list
    let baca (csv:from-row file-read-line ";")
    ; now we can use that list to create a turtle with the saved properties
    create-cars 1 [
      set variant    item 0 baca
      set brand      item 1 baca
      set fuelconsmp item 2 baca
      set fuelcost   item 3 baca / 10000
      set co2        item 4 baca / 100
      set price      item 5 baca / 1000
      set kerbweight item 6 baca / 1000
      set len        item 7 baca
      set width      item 8 baca
      set height     item 9 baca
      set gasoline   item 10 baca
      set manual     item 11 baca ]

    ask cars [
      set shape        "car"
      set color        yellow
      let bound-cars   random 45 + 5
      set xcor         random-xcor
      set ycor         random-ycor
      set dimension    (len * width) / 10000000 ]
  ]

  file-close ;; make sure to close the file
end 




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to go
  first-step
  second-step
end 


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to first-step
  ask cars [
    set chosen? 0 ]

  first-stage

  ;; this is the equivalence to "tick" if you decide your model won't involve time frame.
  update-plots
end 

to first-stage  ;; buyers procedure.
  ask buyers [
    let a 4
    let b 1 / 6

    ;; set the number of cars choice set for each buyer
    ;; by the non-compensatory rule
    set cset-size round random-gamma a b

    set who-choice-set [who] of n-of cset-size cars ;; set buyers' car choice-set as an agentset
    set label cset-size
  ]
end 


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to second-step
  ask buyers [
    ;; table for storing each car's exponentials of utility.
    set table_lefthalf table:make
    foreach who-choice-set [
      x ->
      let c table:get c_car [brand] of car x
      let value (buyer_utility + ([car_utility] of car x) + c)
      table:put table_lefthalf ([who] of car x) (exp (value * table:get mu_car [brand] of car x))
    ]

    set table_righthalf table:make

    ;; procedures to make the table_righthalf table, table for storing aggregate utility
    ;; value for cars within the same brand.
    ; first make a list of list containing [["brand" utility_value]["brand 2" utility_value2]...]
    set brand_list []
    foreach who-choice-set
    [ x -> set brand_list lput (list [brand] of car x table:get table_lefthalf x) brand_list ]
    ; next sort the list of list by the brand name alphabetically
    set brand_list sort-by [[a b] -> first a < first b] brand_list
    ; after that we are going to make aggregated list of car brands and the corresponding value
    set brand_list make-righthalf brand_list
    ; now we assign that list to table_righthalf
    set table_righthalf table:from-list brand_list
    ; we also need a table for the exp(1 / mu_j * ln total exp(mu_j * Vij))
    set table_exp_nested_sums table:from-list make-exp-nested-sums brand_list

    ; now we can compute each car's probability
    let car_probs []
    foreach who-choice-set [
      id -> set car_probs lput list id count-exp id car_probs
    ]
    ; sort the cars based on their probability descending
    set car_probs sort-by [[a b] -> last a > last b] car_probs
    set table_car_probs table:from-list car_probs

    ; after each car has its own probability, we ask buyer to choose the car that
    ; has the highest probability value
    let highestp car first first car_probs
    set car-choice highestp
    ask car-choice [
      set chosen? 1
    ]
  ]

  update-plots
end 

;this is my version to make the righthalf table
;to-report make-righthalf [li]
;  let result []
;  let first_item item 0 li     ; first_item is also a list
;  let li-length length li
;  let li-end li-length - 1
;  foreach (range 1 li-length) [
;    ? -> ifelse ? != li-end
;    [ ifelse item 0 item ? li = item 0 first_item
;      [ set first_item replace-item 1 first_item (item 1 first_item + item 1 item ? li) ]
;      [ set result lput first_item result
;        set first_item item ? li ]
;    ]
;    [ ifelse item 0 item ? li = item 0 first_item
;      [ set first_item replace-item 1 first_item (item 1 first_item + item 1 item ? li)
;        set result lput first_item result ]
;      [ set result lput first_item result
;        set result lput item li-end li result ]
;    ]
;  ]
;  report result
;end

;this is JenB's version

to-report make-righthalf [li]
  ; this procedure assumes that li has been sorted
  ; uncomment this following code if above assumption is not used
;  let sorted-list sort-by [[a b] -> first a < first b] li
  ; prime the loop
  let pair-to-add first li
  let active-letter first pair-to-add
  let result []

  ; loop from the second item to the end
  foreach but-first li [
    pair ->
    ifelse first pair = active-letter
    ; in same first letter so add
    [ set pair-to-add (list first pair-to-add (last pair-to-add + last pair)) ]
    ; in different first letter so output and use this item as start of next chain
    [ set result lput pair-to-add result
      set pair-to-add pair
      set active-letter first pair
    ]
  ]
  ; append the final pair
  set result lput pair-to-add result
  report result
end 

to-report make-exp-nested-sums [li]
  let result []
  foreach li [
    pair ->
    let the-brand first pair
    let cmu table:get mu_car the-brand
    set result lput list the-brand ((1 / cmu) * (ln last pair)) result
  ]
  report result
end 

to-report count-exp [id]
  let p_num_lefthalf table:get table_lefthalf id
  let p_num_righthalf exp (1 / table:get mu_car [brand] of car id) * ln (table:get table_righthalf [brand] of car id)
  let p_denom_lefthalf table:get table_righthalf [brand] of car id
  let p_denom_righthalf sum table:values table_exp_nested_sums

  report (p_num_lefthalf / p_denom_lefthalf) * (p_num_righthalf * p_denom_righthalf)
end 



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to clear
  reset-ticks

  ask cars [
    set chosen? 0 ]

  ask buyers [
    set cset-size 0
    set label ""
  ]

  setup-plots
end