Data for: Of the first five US states with food waste bans, Massachusetts alone has reduced landfill waste
Data files
Aug 27, 2024 version files 959.63 MB
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bans_thresholds.csv
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boulder_population.csv
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boulder_waste.csv
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bt_with_power_data.csv
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composting_capacity_all_states.csv
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composting_effect.csv
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composting_infrastructure_all_states_gov.csv
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disposal_effect_size2.csv
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food_generators_MA.csv
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food_generators_VT.csv
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municipal_effect.csv
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plac_for_histogram4_composting.csv
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plac_for_histogram4.csv
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plac_for_histogram6_composting.csv
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plac_for_histogram6.csv
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plac_sf.csv
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pool_estimates_All.csv
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population_2020.csv
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population.csv
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power_county_composting.csv
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power_county.csv
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power_gas_res.csv
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power_state_composting.csv
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power_state_p.csv
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power_state_pass_data.csv
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power_state_plac_no_r_sq_filter.csv
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power_state.csv
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power2_impexp.csv
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README.md
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sc_data_ghg.csv
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seattle_composting.csv
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seattle_disposal.csv
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sf_power.csv
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towns_coordinates_VT.csv
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tr_res_municipal_multiple_composting.csv
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tr_res_state_multiple_composting.csv
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uscities.csv
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wcs_2.csv
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xy_plot_data_passage.csv
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xy_plot_data.csv
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year_placebo.csv
Abstract
Diverting food waste from landfills is crucial to reduce emissions and meet Paris Agreement targets. Between 2014 and 2024, nine US states banned commercial waste generators---such as grocery chains---from landfilling food waste, expecting a 10–15% waste reduction. However, no evaluation of these bans exists. We compile a comprehensive waste dataset covering 36 US states between 1996 and 2019 to evaluate the first five implemented state-level bans. Contrary to policymakers' expectations, we can reject aggregate waste reductions higher than 3.2%, and cannot reject a zero-null aggregate effect. Moreover, we cannot reject a zero-null effect for any other state except Massachusetts, which gradually achieved a 13.2% reduction. Our findings reveal the need to reassess food waste bans, using Massachusetts as a benchmark for success.
README: Data for: Of the first five US states with food waste bans, Massachusetts alone has reduced landfill waste
https://doi.org/10.5061/dryad.bzkh189h4
In this repository, we provide all the data and necessary information for replication of our paper titled "Of the first five US states with food waste bans, Massachusetts alone has reduced landfilled waste". We include all the raw data and software we used to produce all tables and figures in this paper. Additionally, for easy replication, we include some outputs generated by our code, such as power analysis results. These are available in the "Data from Code" section.
Raw data
- Waste data: includes all the data we use for our analysis (power2_impexp.csv)
- Note: in this file "disposal" refers to state-generated MSW for disposal. That is, we have (i) used only the MSW fraction of the total waste and (ii) excluded the imported waste and included waste exports. (For more details, please see sections A.1.2 and A.1.3 of the SM). When county_name is NA it implies that the relevant state reports at the state level.
- Waste characterizations data: (wcs_2.csv)
- Food waste generators lists: (food_generators_MA.csv & food_generators_VT.csv). The names and addresses of these businesses have been redacted.
- Food waste processors lists: (composting_infrastructure_all_states_gov.csv, composting_capacity_all_states.csv). When a field is NA it implies that the information is not available.
- Other data:
- Population of US counties: needed to create the per capita waste disposal (population.csv)
- US Cities: coordinates of US cities---needed to estimate the minimum distance between generators and processors (uscities.csv, town_coordinates_VT.csv)
Code
Primary analysis
- placebo_all.RMD: calculation of the placebo confidence intervals ("power") (right panel of Fig. 2)
This script also includes:
* the statistics of the placebo distributions for state-level bans (Table S6)
* the calculation of the placebo confidence intervals for city-level specifications (right panel of Fig. S7)
* the calculation of the placebo confidence intervals for anticipatory rob check (right panel of Fig. S9)
2. xy.R: main results for the point estimate of the ATT of the bans + the building of the SC for the treated states (left panel of Fig. 2)
This script also includes the calculation of the point estimate of the ATT + the SC for city-level bans (left panel of Fig. S7)
Data section
- data_section: producing all the data-related figures and tables (Fig. 1, Fig. S2, Fig. S3, Table S4)
- WCS: calculations regarding the expected effect of the bans (Table 1, Fig. S1)
This script also includes an analysis of the WCSs of treated and non-treated states in our sample (Fig. S4)
Mechanism
infrastructure_gov.R: includes analyses related to the final section of the paper, the potential drivers of MA's ban's success (Fig. 3, Fig. 4, Fig. S9)
Robustness checks
- year_placebo: produces results for California-specific provision (Fig. S8)
- composting: all analyses regarding bans's effects on composting (Fig. S10)
- ghg: all analyses regarding emissions (Fig. S5, Fig. S6, Table S8)
- xy_passage: all analyses regarding bans's anticipation effects (left panel of Fig. S9)
- diff_in_diff: all analyses for the difference in differences specification (Table S7)
Intermediate data
These files include intermediate data that have been produced at midpoints in the code. They are needed to replicate parts of the code without running every script (e.g., run xy.R without running placebo_all.RMD)
- Expected effects
- State-level expected effects for each phase: (disposal_effect_size2.csv)
- (Robustness check) City-level expected effects (municipal_effect.csv)
- (Robustness check) Effects of the bans on composting (composting_effect.csv)
- Time series of actual and synthetic disposal
- Detailed results of the time series for state-level and city-level bans (xy_plot_data.csv)
- Summarised results of the ATT estimates for state-level and city-level bans (bt_with_power_data.csv)
- (Robustness check) Detailed results of the time series for state-level bans (xy_plot_data_passage.csv)
- (Robustness check) Detailed results of the time series when using methane emissions as the main outcome (sc_data_ghg.csv)
- (Robustness check) Detailed results of the California provision placebo distribution (year_placebo.csv)
- (Robustness check) Summarised results of the estimates of the ATT when using composting as the main outcome for state-level
- (tr_res_state_multiple_composting.csv) & for the city-level bans (tr_res_municipal_multiple_composting.csv)
- Placebo distribution results
- Detailed results of the state-level placebo distribution (power_state_plac_no_r_sq_filter.csv) & the for the aggregate case (pool_estimates_All.csv)
- Summarised results of the state-level placebo distribution (power_state.csv)
- (Robustness check) Detailed results of the county-level placebo distribution (plac_for_histogram4.csv, plac_for_histogram6.csv)
- (Robustness check) Summarised results of the county-level placebo distribution (power_county.csv)
- (Robustness check) Detailed results of the SF placebo distribution (plac_sf.csv)
- (Robustness check) Summarised results of the SF placebo distribution (sf_power.csv)
- (Robustness check) Summarised results of the county-level placebo distribution (power_county.csv)
- (Robustness check) Detailed results of the state-level placebo distribution when assuming the passage date as implementation date (power_state_pass_data.csv)
- (Robustness check) Summarised results of the state-level placebo distribution when assuming the passage date as implementation date (power_state_p.csv)
- (Robustness check) Detailed results of the state-level placebo distribution when using methane emissions as the main outcome (power_gas_res.csv)
- (Robustness check) Detailed results of the California provision placebo distribution (year_placebo.csv)
- (Robustness check) Summarised results of the state-level placebo distribution when using composting as our outcome (power_state_composting.csv)
- (Robustness check) Detailed results of the county-level placebo distribution when using composting as our outcome (plac_for_histogram4_composting.csv, plac_for_histogram6_composting.csv)
- (Robustness check) Summarised results of the county-level placebo distribution when using composting as our outcome (power_county_composting.csv)
Definition of variables
Raw data
- power2_impexp.csv: - year: the calendar year for which waste is reported - state_id: the state for which waste is reported - county_name: the county for which waste is reported (NA if the state reports waste at the state level) - type: the disposition method of waste (can be disposal, composting, food_donation, etc.) - tons: the amount of waste in tons
- wcs_2.csv: - Activity: the disposition method of waste (only Disposal)\ - state_id: the state for which waste is reported - City: the jurisdiction where the WCS was conducted (if statewide then it applies to the whole state) - year: the year when the WCS was conducted - generator_category: the category of a generator generating the reporting waste - material: the category of the material (see SM for additional details) - tons: the amount of waste reported (NA if the WCS is in %) - percent: the percent of waste reported (some states only report the fraction in their WCSs) (NA if the WCS is in tons) - need_to_find: binary variable. =1 if the state does not report the breakdown between commercial and non-commercial waste (NA otherwise)
- food_generators_MA.csv - DEP_Code: the unique code assigned to the generator by MassDEP - Name: the name of the generator (has been redacted) - Street_Add: the address of the generator (has been redacted) - Town_City: the town the generator is located - Type: the type of generator (F: Food and Beverage Manufacturers/Processors, W: Wholesale Distributors, IH: Institutions-Healthcare Facilities, IS: Institutions -Independent Schools, IC: Institutions -Colleges/Universities, IP: Institutions -Correctional Facilities, C: Resorts and Conference Facilities, G: Supermarkets and Grocery Stores, R: Restaurants) - ZIP_Code: the zip code of the generator - tons: the estimated annual generation in tons - Lat: the latitude of the generator - Long: the longitude of the generator - X_Coord: The Massachusetts State Plane coordinates (not used) - Y_Coord: The Massachusetts State Plane coordinates (not used) - Status: The Status field denotes whether the potential food waste generator was definitively matched (M) or the highest ranking tie of one or more locations (T). - Score: the longitude of the composting facility
- food_generators_VT.csv - X: The Vermont State Plane coordinates (not used) - Y: The Vermont State Plane coordinates (not used) - ID: the unique ID of the generator - FSG_Name: the name of the generator (redacted) - TonsPerWeek: the estimated generation of food waste in tons per week - TYPE1: the classification of the generator by the Vermont state agency - TYPE2: the classification of the generator by the Vermont state agency - TYPE3: the classification of the generator by the Vermont state agency - Address: the address of the generator (redacted) - Town: the town the generator is located in - County: the county the generator is located in - ZIP: the ZIP code of the generator
- composting_infrastructure_all_states_gov.csv - state_name: the name of the state in which the composting facility is located - composting_facility: the name of the relevant composting facility (has been redacted) - lat: the latitude of the composting facility - long: the longitude of the composting facility - date_type: the source of the data (only gov meaning some government agency) - capacity: the annual capacity of the facility in tons
- composting_capacity_all_states.csv - state_id: the state for which the capacity is reported - capacity: the capacity of the state's composting network - year: the year for which we report the capacity
Methods
The raw data for this paper have been received by individual states in PDF or Excel files. (For each state there might be several PDF or Excel files for each year.) In the data we uploaded on GitHub, we transferred these raw data (the various pdfs and excels) into a single CSV file and have created a standardized waste outcome---specifically, state-generated, municipal solid waste (MSW) disposal. In the README file, we include more details regarding all the other supporting data and code we have used.