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Update telecommute frequency alternatives to differentiate 2 days per week and 3 days per week, also update CDAP and non-mandatory tour frequency UECs accordingly.
1 parent e28a03f commit 8034ae2

3 files changed

Lines changed: 40 additions & 36 deletions

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‎resident/configs/cdap_indiv_and_hhsize1.csv‎

Lines changed: 4 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -25,7 +25,8 @@ Base works from home 2016,(work_from_home),,coef_base_work_from_home_2016_N,
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Part time worker who works from home,(ptype == 2) & (work_from_home),,coef_part_time_worker_work_from_home_N,
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Part time worker who works from home,@(df.ptype == 2) & (df.work_from_home) & (PRE_COVID),,coef_part_time_worker_work_from_home_2016_N,
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Telecommutes 1 day per week,telecommute_frequency=='1_day_week',,coef_telecommute_1_day_week_N,coef_telecommute_1_day_week_H
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Telecommutes 2-3 days per week,telecommute_frequency=='2_3_days_week',,coef_telecommute_2_3_days_week_N,coef_telecommute_2_3_days_week_H
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Telecommutes 2 days per week,telecommute_frequency=='2_days_week',,coef_telecommute_2_3_days_week_N,coef_telecommute_2_3_days_week_H
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Telecommutes 3 days per week,telecommute_frequency=='3_days_week',,coef_telecommute_2_3_days_week_N,coef_telecommute_2_3_days_week_H
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Telecommutes 4 days per week,telecommute_frequency=='4_days_week',,coef_telecommute_4_days_week_N,coef_telecommute_4_days_week_H
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Full-time worker 2016 ASC,@(df.ptype == 1) & (PRE_COVID),coef_full_time_worker_2016_asc_M,coef_full_time_worker_2016_asc_N,
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Part-time worker 2016 ASC,@(df.ptype == 2) & (PRE_COVID),coef_part_time_worker_2016_asc_M,coef_part_time_worker_2016_asc_N,
@@ -36,7 +37,8 @@ Driving-age child who is in school 2016 ASC,@(df.ptype == 6) & (PRE_COVID),coef_
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Pre-driving-age child who is in school 2016 ASC,@(df.ptype == 7) & (PRE_COVID),coef_pre_driving_age_child_2016_asc_M,coef_pre_driving_age_child_2016_asc_N,
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Preschool child 2016 ASC,@(df.ptype == 8) & (PRE_COVID),coef_preschool_child_2016_asc_M,coef_preschool_child_2016_asc_N,
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Telecommutes 1 day per week 2016,@(df.telecommute_frequency=='1_day_week') & (PRE_COVID),,coef_telecommute_1_day_week_2016_N,coef_telecommute_1_day_week_2016_H
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Telecommutes 2-3 days per week 2016,@(df.telecommute_frequency=='2_3_days_week') & (PRE_COVID),,coef_telecommute_2_3_days_week_2016_N,coef_telecommute_2_3_days_week_2016_H
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Telecommutes 2 days per week 2016,@(df.telecommute_frequency=='2_days_week') & (PRE_COVID),,coef_telecommute_2_3_days_week_2016_N,coef_telecommute_2_3_days_week_2016_H
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Telecommutes 3 days per week 2016,@(df.telecommute_frequency=='3_days_week') & (PRE_COVID),,coef_telecommute_2_3_days_week_2016_N,coef_telecommute_2_3_days_week_2016_H
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Telecommutes 4 days per week 2016,@(df.telecommute_frequency=='4_days_week') & (PRE_COVID),,coef_telecommute_4_days_week_2016_N,coef_telecommute_4_days_week_2016_H
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Mandatory pattern unavailable if not worker or student,(is_student == False) & (is_worker == False),coef_UNAVAILABLE,,
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Mandatory pattern unavailable if not works from home,(work_from_home == True) & (is_student == False),coef_UNAVAILABLE,,

‎resident/configs/non_mandatory_tour_frequency.csv‎

Lines changed: 4 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -99,8 +99,10 @@ util_othdiscr_accessibility_visiting,Retail Accessibility for Visiting,othdiscr_
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# work from home and telecommute_frequency,,,,,,,,,
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util_work_from_home_and_iNM_tour_freq_2,Work From Home & Tour Frequency =2,(work_from_home) & (_total_indNM_tours == 2),coef_work_from_home_and_iNM_tour_freq_2,,,,,,
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util_work_from_home_and_iNM_tour_freq_3p,Work From Home & Tour Frequency =3p,(work_from_home) & (_total_indNM_tours >= 3),coef_work_from_home_and_iNM_tour_freq_3p,,,,,,
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util_telecommute_2_3_days_week_and_iNM_tour_freq_2,Telecommute 1 day per week & Tour Frequency =2,(telecommute_frequency == '2_3_days_week') & (_total_indNM_tours == 2),coef_telecommute_2_3_4_days_week_and_iNM_tour_freq_2,,,,,,
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util_telecommute_2_3_days_week_and_iNM_tour_freq_3p,Telecommute 1 day per week & Tour Frequency =3p,(telecommute_frequency == '2_3_days_week') & (_total_indNM_tours >= 3),coef_telecommute_2_3_4_days_week_and_iNM_tour_freq_3p,,,,,,
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util_telecommute_2_days_week_and_iNM_tour_freq_2,Telecommute 2 days per week & Tour Frequency =2,(telecommute_frequency == '2_days_week') & (_total_indNM_tours == 2),coef_telecommute_2_3_4_days_week_and_iNM_tour_freq_2,,,,,,
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util_telecommute_3_days_week_and_iNM_tour_freq_2,Telecommute 3 days per week & Tour Frequency =2,(telecommute_frequency == '3_days_week') & (_total_indNM_tours == 2),coef_telecommute_2_3_4_days_week_and_iNM_tour_freq_2,,,,,,
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util_telecommute_2_days_week_and_iNM_tour_freq_3p,Telecommute 2 day per week & Tour Frequency =3p,(telecommute_frequency == '2_days_week') & (_total_indNM_tours >= 3),coef_telecommute_2_3_4_days_week_and_iNM_tour_freq_3p,,,,,,
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util_telecommute_3_days_week_and_iNM_tour_freq_3p,Telecommute 3 day per week & Tour Frequency =3p,(telecommute_frequency == '3_days_week') & (_total_indNM_tours >= 3),coef_telecommute_2_3_4_days_week_and_iNM_tour_freq_3p,,,,,,
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util_telecommute_4_days_week_and_iNM_tour_freq_1,Telecommute 1 day per week & Tour Frequency =1,(telecommute_frequency == '4_days_week') & (_total_indNM_tours == 1),,coef_telecommute_4_days_week_and_iNM_tour_freq_1,,,,,
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util_telecommute_4_days_week_and_iNM_tour_freq_2,Telecommute 1 day per week & Tour Frequency =2,(telecommute_frequency == '4_days_week') & (_total_indNM_tours == 2),coef_telecommute_2_3_4_days_week_and_iNM_tour_freq_2,,,,,,
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util_telecommute_4_days_week_and_iNM_tour_freq_3p,Telecommute 1 day per week & Tour Frequency =3p,(telecommute_frequency == '4_days_week') & (_total_indNM_tours >= 3),coef_telecommute_2_3_4_days_week_and_iNM_tour_freq_3p,,,,,,

‎resident/configs/telecommute_frequency.csv‎

Lines changed: 32 additions & 32 deletions
Original file line numberDiff line numberDiff line change
@@ -1,32 +1,32 @@
1-
Label,Description,Expression,No_Telecommute,1_day_week,2_3_days_week,4_days_week
2-
util_HasChildren0to5,Has children 0 to 5 years old,@df.num_young_children>0,,coef_HasChildren0to5_1day,coef_HasChildren0to5_234day,coef_HasChildren0to5_234day
3-
util_HasChildren6to12,Has children 6 to 12 years old,@df.num_children_6_to_12>0,,coef_HasChildren6to12_1day,coef_HasChildren6to12_23day,coef_HasChildren6to12_4day
4-
util_OneAdultInHH,One adult in hh,@df.num_adults==1,,coef_OneAdultInHH_1day,coef_OneAdultInHH_23day,coef_OneAdultInHH_4day
5-
util_Female,female,@df.female,,coef_Female_1234day,coef_Female_1234day,coef_Female_1234day
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util_PartTimeWorker,Part-time worker,@df.pemploy==2,,coef_PartTimeWorker_1234day,coef_PartTimeWorker_1234day,coef_PartTimeWorker_1234day
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util_Income60to100k,Income 60-100k,"@df.income.between(60000, 100000)",,coef_Income60to100k_1day,coef_Income60to100k_23day,coef_Income60to100k_4day
8-
util_Income100to150k,Income 100-150k,"@df.income.between(100000, 150000)",,coef_Income100to150k_1day,coef_Income100to150k_234day,coef_Income100to150k_234day
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util_Income150kplus,Income 150k+,@df.income > 150000,,coef_Income150kplus_1day,coef_Income150kplus_23day,coef_Income150kplus_4day
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util_0Autos,0 Autos,@df.auto_ownership==0,,coef_0Autos_1day,coef_0Autos_234day,coef_0Autos_234day
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util_1Auto,1 Auto,@df.auto_ownership==1,,coef_1Auto_1day,coef_1Auto_234day,coef_1Auto_234day
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util_3plusAutos,3+ Autos,@df.auto_ownership>=3,,coef_3plusAutos_1day,coef_3plusAutos_23day,coef_3plusAutos_4day
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util_DistanceToWork,Distance to work,@df.distance_to_work,,coef_DistanceToWork_1day,coef_DistanceToWork_234day,coef_DistanceToWork_234day
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util_calib_2020,scenario year is 2020,@scenarioYear==2020,,coef_calib_2020_1day,coef_calib_2020_23day,coef_calib_2020_4day
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util_calib_2025,scenario year is 2025,@scenarioYear==2025,,coef_calib_2025_1day,coef_calib_2025_23day,coef_calib_2025_4day
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util_calib_2035,scenario year is 2035,@scenarioYear==2035,,coef_calib_2035_1day,coef_calib_2035_23day,coef_calib_2035_4day
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util_calib_2050,scenario year is 2050,@scenarioYear==2050,,coef_calib_2050_1day,coef_calib_2050_23day,coef_calib_2050_4day
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util_2016,Model year is 2016,@PRE_COVID,,coef_2016_1day,coef_2016_23day,coef_2016_4day
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util_accomodation,Accomodation industry,@df.naics_code==721,,coef_accomodation_1234day,coef_accomodation_1234day,coef_accomodation_1234day
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util_agriculture,Agriculture industry,@df.naics_code==11,,coef_agriculture_1234day,coef_agriculture_1234day,coef_agriculture_1234day
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util_business_srv,Business services industry,@df.naics_code==54,,coef_business_srv_1day,coef_business_srv_23day,coef_business_srv_4day
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util_construction,Construction industry,@df.naics_code==23,,coef_construction_1day,coef_construction_234day,coef_construction_234day
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util_education,Education industry,@df.naics_code==61,,coef_education_1234day,coef_education_1234day,coef_education_1234day
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util_entertainment,Entertainment industry,@df.naics_code==71,,coef_entertainment_1day,coef_entertainment_23day,coef_entertainment_4day
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util_food_srv,Food services industry,@df.naics_code==722,,coef_food_srv_1234day,coef_food_srv_1234day,coef_food_srv_1234day
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util_government,Government industry,@df.naics_code==92,,coef_government_1day,coef_government_234day,coef_government_234day
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util_healthcare,Healthcare industry,@df.naics_code==62,,coef_healthcare_1234day,coef_healthcare_1234day,coef_healthcare_1234day
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util_manufacturing,Manufacturing industry,"@df.naics_code.isin([31,32,33])",,coef_manufacturing_1day,coef_manufacturing_234day,coef_manufacturing_234day
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util_mgmt_srv,Management services industry,@df.naics_code==55,,coef_mgmt_srv_1day,coef_mgmt_srv_23day,coef_mgmt_srv_4day
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util_military,Miliary industry,@df.naics_code==9000,,coef_military_1day,coef_military_234day,coef_military_234day
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util_retail,Retail industry,"@df.naics_code.isin([44,45])",,coef_retail_1day,coef_retail_23day,coef_retail_4day
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util_asc,Alternative specific constant,1,,asc_1day,asc_23day,asc_4day
1+
Label,Description,Expression,No_Telecommute,1_day_week,2_days_week,3_days_week,4_days_week
2+
util_HasChildren0to5,Has children 0 to 5 years old,@df.num_young_children>0,,coef_HasChildren0to5_1day,coef_HasChildren0to5_234day,coef_HasChildren0to5_234day,coef_HasChildren0to5_234day
3+
util_HasChildren6to12,Has children 6 to 12 years old,@df.num_children_6_to_12>0,,coef_HasChildren6to12_1day,coef_HasChildren6to12_23day,coef_HasChildren6to12_23day,coef_HasChildren6to12_4day
4+
util_OneAdultInHH,One adult in hh,@df.num_adults==1,,coef_OneAdultInHH_1day,coef_OneAdultInHH_23day,coef_OneAdultInHH_23day,coef_OneAdultInHH_4day
5+
util_Female,female,@df.female,,coef_Female_1234day,coef_Female_1234day,coef_Female_1234day,coef_Female_1234day
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util_PartTimeWorker,Part-time worker,@df.pemploy==2,,coef_PartTimeWorker_1234day,coef_PartTimeWorker_1234day,coef_PartTimeWorker_1234day,coef_PartTimeWorker_1234day
7+
util_Income60to100k,Income 60-100k,"@df.income.between(60000, 100000)",,coef_Income60to100k_1day,coef_Income60to100k_23day,coef_Income60to100k_23day,coef_Income60to100k_4day
8+
util_Income100to150k,Income 100-150k,"@df.income.between(100000, 150000)",,coef_Income100to150k_1day,coef_Income100to150k_234day,coef_Income100to150k_234day,coef_Income100to150k_234day
9+
util_Income150kplus,Income 150k+,@df.income > 150000,,coef_Income150kplus_1day,coef_Income150kplus_23day,coef_Income150kplus_23day,coef_Income150kplus_4day
10+
util_0Autos,0 Autos,@df.auto_ownership==0,,coef_0Autos_1day,coef_0Autos_234day,coef_0Autos_234day,coef_0Autos_234day
11+
util_1Auto,1 Auto,@df.auto_ownership==1,,coef_1Auto_1day,coef_1Auto_234day,coef_1Auto_234day,coef_1Auto_234day
12+
util_3plusAutos,3+ Autos,@df.auto_ownership>=3,,coef_3plusAutos_1day,coef_3plusAutos_23day,coef_3plusAutos_23day,coef_3plusAutos_4day
13+
util_DistanceToWork,Distance to work,@df.distance_to_work,,coef_DistanceToWork_1day,coef_DistanceToWork_234day,coef_DistanceToWork_234day,coef_DistanceToWork_234day
14+
util_calib_2020,scenario year is 2020,@scenarioYear==2020,,coef_calib_2020_1day,coef_calib_2020_23day,coef_calib_2020_23day,coef_calib_2020_4day
15+
util_calib_2025,scenario year is 2025,@scenarioYear==2025,,coef_calib_2025_1day,coef_calib_2025_23day,coef_calib_2025_23day,coef_calib_2025_4day
16+
util_calib_2035,scenario year is 2035,@scenarioYear==2035,,coef_calib_2035_1day,coef_calib_2035_23day,coef_calib_2035_23day,coef_calib_2035_4day
17+
util_calib_2050,scenario year is 2050,@scenarioYear==2050,,coef_calib_2050_1day,coef_calib_2050_23day,coef_calib_2050_23day,coef_calib_2050_4day
18+
util_2016,Model year is 2016,@PRE_COVID,,coef_2016_1day,coef_2016_23day,coef_2016_23day,coef_2016_4day
19+
util_accomodation,Accomodation industry,@df.naics_code==721,,coef_accomodation_1234day,coef_accomodation_1234day,coef_accomodation_1234day,coef_accomodation_1234day
20+
util_agriculture,Agriculture industry,@df.naics_code==11,,coef_agriculture_1234day,coef_agriculture_1234day,coef_agriculture_1234day,coef_agriculture_1234day
21+
util_business_srv,Business services industry,@df.naics_code==54,,coef_business_srv_1day,coef_business_srv_23day,coef_business_srv_23day,coef_business_srv_4day
22+
util_construction,Construction industry,@df.naics_code==23,,coef_construction_1day,coef_construction_234day,coef_construction_234day,coef_construction_234day
23+
util_education,Education industry,@df.naics_code==61,,coef_education_1234day,coef_education_1234day,coef_education_1234day,coef_education_1234day
24+
util_entertainment,Entertainment industry,@df.naics_code==71,,coef_entertainment_1day,coef_entertainment_23day,coef_entertainment_23day,coef_entertainment_4day
25+
util_food_srv,Food services industry,@df.naics_code==722,,coef_food_srv_1234day,coef_food_srv_1234day,coef_food_srv_1234day,coef_food_srv_1234day
26+
util_government,Government industry,@df.naics_code==92,,coef_government_1day,coef_government_234day,coef_government_234day,coef_government_234day
27+
util_healthcare,Healthcare industry,@df.naics_code==62,,coef_healthcare_1234day,coef_healthcare_1234day,coef_healthcare_1234day,coef_healthcare_1234day
28+
util_manufacturing,Manufacturing industry,"@df.naics_code.isin([31,32,33])",,coef_manufacturing_1day,coef_manufacturing_234day,coef_manufacturing_234day,coef_manufacturing_234day
29+
util_mgmt_srv,Management services industry,@df.naics_code==55,,coef_mgmt_srv_1day,coef_mgmt_srv_23day,coef_mgmt_srv_23day,coef_mgmt_srv_4day
30+
util_military,Miliary industry,@df.naics_code==9000,,coef_military_1day,coef_military_234day,coef_military_234day,coef_military_234day
31+
util_retail,Retail industry,"@df.naics_code.isin([44,45])",,coef_retail_1day,coef_retail_23day,coef_retail_23day,coef_retail_4day
32+
util_asc,Alternative specific constant,1,,asc_1day,asc_23day,asc_23day,asc_4day

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