Article Figures & Data
Figures
- Figure 1
Plastic Bag Usage in Store A (Treated) and Store B (Control): Pre-and Postintervention of the Token Program A: Plastic Bag Use for Store A (Treated) and Store B (Control) (Preintervention) B: Plastic Bag Use for Store A (Treated) and Store B (Control) (Postintervention)
- Figure 2
Effect of a Token Program on Plastic Bag Use
Tables
Variable Mean Std. Dev. Description Disposable bag 0.38 0.48 1 if customer used a plastic bag, 0 otherwise (dependent variable) Token 0.85 0.36 1 if after implementation of token program, 0 otherwise StoreA 0.70 0.46 1 if observation comes from the store A (treated convenience store), 0
otherwiseTotal items 2.09 1.44 Total number of items purchased per transaction Small items 1.29 1.19 Number of small items purchased per transaction (can of soda or smaller) Medium items 0.63 0.97 Number of medium items purchased per transaction (any items in
between small and large)Large items 0.17 0.50 Number of large items purchased per transaction (2 liters of soda, half-
gallon of milk, 6-packs of bottled water)Evening 0.62 0.49 1 if purchase occurred in evening (after 5 p.m.), 0 otherwise Weekday 0.93 0.26 1 if the purchase occurred Monday through Friday, 0 otherwise Preceding customer 0.38 0.48 1 if the previous customer used a plastic bag, 0 otherwise Female 0.49 0.52 Gender of the customer: 1 if female, 0 otherwise Percentage of plastic
bag use0.44 0.13 Percentage of the customer using plastic bags for each day before
interventionTrend 4.5 2.36 Trend representing each day before the intervention of token program
(since we had 8 control days, trend represented as 1, 2…,8)Dependent Variable Coefficient Std. Error p-value Trend 0.004 0.016 0.777 Trend*StoreA 0.015 0.013 0.262 Constant 0.388 0.071 0.000 R-squared 0.139 Note:The dependent variable is the daily percentage of customers using at least one plastic bag. Results are based on a robust ordinary least squares estimation.
Characteristic Total (n=436) Store A (n=282) Store B (n=154) p-value Testing Store A=B Gender 0.719 Female 0.56 0.55 0.57 Race 0.728 Black 0.19 0.18 0.2 White 0.65 0.66 0.62 University 0.000 status Freshman 0.49 0.41 0.63 Sophomore 0.26 0.28 0.22 Junior 0.15 0.20 0.07 Senior 0.07 0.08 0.06 Graduate 0.02 0.02 0.01 Staff 0.01 0.01 0.01 Living 0.109 location University 0.82 0.80 0.86 dorms Off-campus 0.11 0.12 0.09 <10 min. walk Off-campus 0.06 0.07 0.05 further away Frequency 0.000 of visiting store A Never 0.14 0.05 0.29 Rarely 0.18 0.15 0.25 Sometimes 0.33 0.36 0.29 Often 0.35 0.44 0.17 Frequency 0.000 of visiting store B Never 0.33 0.48 0.06 Rarely 0.20 0.22 0.15 Sometimes 0.26 0.19 0.39 Often 0.21 0.11 0.40 Before Intervention After Intervention Characteristic (n=436) Total (n=148) Store A (n=96) Store B (n=52) p-value Store A=B Total (n=288) Store A (n=186) Store B (n=102) p-value Store A=B Gender 0.596 0.955 Female 0.49 0.47 0.52 0.60 0.60 0.60 Race 0.915 0.728 Black 0.18 0.19 0.15 0.19 0.17 0.22 White 0.62 0.62 0.65 0.66 0.69 0.60 University status 0.044 0.001 Freshman 0.54 0.45 0.71 0.46 0.39 0.59 Sophomore 0.24 0.30 0.13 0.27 0.27 0.27 Junior 0.16 0.19 0.10 0.15 0.21 0.06 Senior 0.04 0.03 0.02 0.09 0.10 0.07 Graduate 0.01 0.02 0.00 0.02 0.02 0.01 Staff 0.01 0.01 0.02 0.01 0.01 0.00 Living location 0.514 0.123 University dorms 0.86 0.84 0.88 0.80 0.77 0.85 Off-campus 0.08 0.08 0.08 0.13 0.14 0.10 <10-min. walk Off-campus further 0.05 0.06 0.04 0.07 0.08 0.05 away Frequency of visiting
store A<0.001 <0.001 Never 0.11 0.03 0.27 0.15 0.06 0.30 Rarely 0.19 0.17 0.23 0.18 0.14 0.26 Sometimes 0.34 0.35 0.31 0.33 0.36 0.28 Often 0.36 0.45 0.19 0.34 0.44 0.16 Frequency of visiting
store B<0.001 <0.001 Never 0.27 0.38 0.06 0.36 0.52 0.06 Rarely 0.21 0.25 0.15 0.19 0.21 0.15 Sometimes 0.34 0.24 0.52 0.22 0.17 0.32 Often 0.18 0.13 0.27 0.23 0.10 0.47 Model I Model II Model III Model III’ Coefficient Marginal Effect Coefficient Marginal Effect Coefficient Marginal Effect Coefficient Marginal Effect Token 0.044
(0.212)0.006
(0.031)0.021
(0.235)0.003
(0.030)0.248
(0.295)0.035
(0.042)0.273
(0.229)0.039
(0.032)storeA 1.031***
(0.335)0.148***
(0.048)1.243***
(0.376)0.160***
(0.048)1.001***
(0.340)0.143***
(0.049)1.021***
(0.334)0.147***
(0.048)Token*StoreA –0.747***
(0.258)–0.114***
(0.041)–0.915***
(0.279)–0.128***
(0.042)–0.788***
(0.260)–0.115***
(0.043)–0.795***
(0.259)–0.115***
(0.058)Total items 1.516***
(0.052)0.218***
(0.004)1.521***
(0.053)0.218***
(0.004)1.517***
(0.053)0.218***
(0.004)Small items 1.310***
(0.055)0.169***
(0.005)Medium items 2.054***
(0.076)0.265***
(0.006)Large items 2.969***
(0.146)0.383***
(0.015)Evening 0.281***
(0.106)0.040***
(0.015)0.275**
(0.113)0.036**
(0.015)0.325***
(0.111)0.047***
(0.016)0.280***
(0.108)0.040***
(0.015)Weekday –0.359*
(0.184)–0.052*
(0.026)–0.178
(0.192)–0.023
(0.025)–0.415**
(0.189)–0.059**
(0.027)–0.346*
(0.185)–0.050*
(0.026)Preceding customer 0.184**
(0.073)0.026**
(0.011)0.165**
(0.077)0.021**
(0.010)0.166**
(0.074)0.024**
(0.011)0.174**
(0.073)0.025**
(0.011)Female 0.174***
(0.066)0.025***
(0.009)0.127*
(0.070)0.016*
(0.009)0.176***
(0.066)0.025***
(0.009)0.172***
(0.066)0.025***
(0.009)Constant –4.960***
(0.402)–5.316***
(0.445)–5.023***
(0.421)–4.986
(0.406)Middle –0.393***
(0.128)–0.056***
(0.018)Token*Middle –0.257**
(0.128)–0.037**
(0.018)Token*End Observer FE Yes Yes Yes Yes Cashier FE Yes Yes Yes Yes Week FE No No Yes No Pseudo R–squared 0.329 0.388 0.331 0.330 Model III” Model IV Model IV’ Model IV” Coefficient Marginal Effect Coefficient Marginal Effect Coefficient Marginal Effect Coefficient Marginal Effect Token 0.273
(0.229)0.039
(0.033)0.231
(0.335)0.030
(0.043)0.236
(0.252)0.030
(0.032)0.236
(0.252)0.030
(0.032)StoreA 1.021***
(0.334)0.147***
(0.048)1.223***
(0.378)0.157***
(0.049)1.233***
(0.375)0.159***
(0.048)1.233***
(0.375)0.159***
(0.048)Token*StoreA –0.795***
(0.259)–0.115***
(0.040)–0.963***
(0.281)–0.129***
(0.045)–0.960***
(0.280)–0.128***
(0.042)–0.960***
(0.280)–0.128***
(0.042)Total items 1.517***
(0.053)0.218***
(0.004)Small items 1.313***
(0.056)0.169***
(0.005)1.310***
(0.055)0.169***
(0.005)1.310***
(0.055)0.169***
(0.005)Medium items 2.059***
(0.076)0.265***
(0.006)2.056***
(0.076)0.265***
(0.006)2.056***
(0.076)0.265***
(0.006)Large items 2.966***
(0.147)0.381***
(0.015)2.966***
(0.146)0.382***
(0.015)2.966***
(2.966)0.382***
(0.015)Evening 0.280***
(0.108)0.040***
(0.015)0.316***
(0.119)0.041***
(0.015)0.269**
(0.114)0.035**
(0.015)0.269**
(0.114)0.035**
(0.015)Weekday –0.346*
(0.185)–0.050*
(0.026)–0.225
(0.197)–0.029
(0.025)–0.171
(0.193)–0.022
(0.025)–0.171
(0.193)–0.022
(0.025)Preceding customer 0.174**
(0.073)0.025**
(0.011)0.150*
(0.077)0.019*
(0.010)0.158**
(0.077)0.020**
(0.010)0.158**
(0.077)0.020**
(0.010)Female 0.172***
(0.066)0.025***
(0.009)0.128*
(0.069)0.016*
(0.009)0.125*
(0.070)0.016*
(0.009)0.125*
(0.070)0.016*
(0.009)Constant –4.986***
(0.406)–5.376***
(0.458)–5.324***
(0.447)–5.324***
(0.447)Middle –0.389***
(0.138)–0.050***
(0.018)End –0.222
(0.137)–0.029
(0.018)Token*Middle –0.393***
(0.128)–0.056***
(0.018)–0.389***
(0.138)–0.050***
(0.018)Token*End –0.257**
(0.128)–0.037**
(0.018)–0.222
(0.137)–0.029
(0.018)Observer FE Yes Yes Yes Yes Cashier FE Yes Yes Yes Yes Week FE No Yes No No Pseudo R–squared 0.330 0.391 0.389 0.390 Note:n = 5,513. Standard errors appear in parentheses. Model I uses the total number of items purchased, and model II splits the total number of items purchased into small, medium, and large items. Models III and IV repeat models I and II, respectively, except that models III and IV consider week fixed effects. Models III’ and IV’ repeat model III and IV, respectively, except that models III’ and IV’ consider groups of weeks instead of individual week fixed effects. Models III” and IV” repeat models III and IV, respectively, except that models III” and IV” consider interaction between token and groups of weeks instead of individual week fixed effects.
↵* p < 0.1
↵** p < 0.05
↵*** p < 0.01
In this issue
Jump to section
Related Articles
Cited By...
- No citing articles found.