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The Welfare Effects of Food Choice Nudges: Theory and Field Experimental Evidence
Last registered on May 26, 2017


Trial Information
General Information
The Welfare Effects of Food Choice Nudges: Theory and Field Experimental Evidence
Initial registration date
May 25, 2017
Last updated
May 26, 2017 3:43 PM EDT
Primary Investigator
University of Chicago
Other Primary Investigator(s)
PI Affiliation
University of Southern California
PI Affiliation
University of Chicago
Additional Trial Information
In development
Start date
End date
Secondary IDs
Interventions that encourage healthy eating are becoming widespread across the world as a way to combat the obesity epidemic. An increasingly prevalent intervention is the use of nudges, which attempt to change behavior without restricting the individual’s choice. However, even if the nudge is successful at encouraging healthy eating, it is unknown whether the nudge is welfare increasing or welfare reducing for the individual. To answer this question, we develop a structural model and conduct a door-to-door food delivery field experiment where we randomize whether 1) individuals receive a calorie-and- nutrition information nudge and 2) whether we offer the food immediately or with a delay. To parse out welfare effects, we allow some individuals to sort in or out of the nudge by providing a pre-announcement flyer. This design allows us to measure the welfare effects of the nudge, and whether these effects interact with present bias when delivery of the food is immediate versus when it is delayed.
External Link(s)
Registration Citation
Jimenez-Gomez, David, John List and Anya Samek. 2017. "The Welfare Effects of Food Choice Nudges: Theory and Field Experimental Evidence." AEA RCT Registry. May 26. https://doi.org/10.1257/rct.2190-1.0.
Former Citation
Jimenez-Gomez, David et al. 2017. "The Welfare Effects of Food Choice Nudges: Theory and Field Experimental Evidence." AEA RCT Registry. May 26. http://www.socialscienceregistry.org/trials/2190/history/18044.
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Experimental Details
Our main intervention consists on a door-to-door food sale, where we offer one of two boxes for purchase (at a discount): a fruit and nut box (the healthier option) and a sweets box (the less healthy option).
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
The outcomes are 1) whether or not the subject opens the door to the solicitor, including whether the opt-out box on the flyer is checked in the treatments with flyer, 2) subject’s choice of purchase (no purchase, fruit and nut box, sweets box). Baseline treatments (no flyer delayed – with info and no flyer delayed – without info) also get a short questionnaire asking them about nutrition knowledge, attitudes towards nutrition information and healthy eating and willingness to pay/valuation for the foods.
Primary Outcomes (explanation)
For each food box we also calculated nutrition information using the product labels and USDA’s information about items that do not have a label (i.e., apples, blueberries). For processed foods, added sugar was calculated by taking the average amount of sugar in a “sugar free” version of each item and subtracting from the nutrition label of the actual item. For produce (vegetables/almonds) there are no added sugars.
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Out of selected neighborhoods in the Los Angeles area, we randomize households (by route, with approximately 20 households per route) into one of sixteen treatments, following a 2x2x2x2 design along the following dimensions:

* Price, $1 or $2 per basket
* Whether subjects receive a nudge with calorie and nutritional information (see extra materials).
* Whether the individuals are warned in advance with a flyer (see extra materials).
* Whether delivery of the food purchase is immediate or delayed.
Experimental Design Details
We will run the following regressions, including dummies for each treatment assignment. The outcome variables for each regression are: Door open (0,1) Purchase (0,1) Purchase F&N (0,1) Purchase Sweets (0,1) Purchase cond. on door open (0,1) Purchase F&N cond. on purchasing (0,1) Purchase Sweets cond. on purchasing (0,1) We will alternatively report the results using these additional measures: Calories purchased Added sugar purchased Fat purchased Saturated fat purchased Sodium purchased Fiber purchased All regressions will include RA, time-of-day and city (the experiment spans across different suburbs) fixed effects. We will separately estimate these with additional demographic data that we collect, including: 1) RAs will record estimated race, gender, age bracket (young, adult, older adult) and whether individual or household made the decision, which we include as covariates 2) Census-tract level income data, and the prices of each food at 2 nearby stores (averaged by store/week). Our post-estimation tests of interest are: 1) Comparing flyer vs. no flyer door opening rates. Lower door opening rates may be an indication of lower welfare, and higher door opening rates may be an indication of higher welfare. We will compare flyer, flyer with information about health benefits, and no flyer. 2) Comparing food choice in flyer vs. no flyer conditions. Different purchase rates and food choices may be an indication of sorting. For example, we may expect healthier food purchases in Flyer-Information relative to No Flyer-Information if the flyer induces higher health-conscious people to sort in. 3) Comparing food choice in immediate versus delayed. Different purchase rates and food choices may indicate present bias. For example, we expect more purchases of the Sweets box in immediate versus delayed. 4) Since the design is 2x2 (Immediate/Delayed and Information/No Information) crossed with Flyer/No Flyer, we also wish to look at different 2-way comparisons to understand the impact of the Information nudge under each treatment and with/without pre-notification as we expect these to vary. 5) Comparing $1 vs $2 treatment we expect a simple demand effect: more purchases at $1 than at $2. But this is not one of our key questions for the reduced form analysis.
Randomization Method
Randomization using a computer. When we generate routes, we generate a block of “flyer” routes and a block of “non-flyer” routes. Within the blocks, we then use an excel formula to randomly assign them to $1 Immediate with info, $1 Immediate with no info, $1 Delayed with info, $1 Delayed with no info, $2 Immediate with info, $2 Immediate with no info, $2 Delayed with info, $2 Delayed with no info.
Randomization Unit
The unit of randomization is at the "route" level, each route has about 20 households. Some routes may have fewer or more households in order to complete the full block of houses.
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
800 routes, with 20 households each.
Sample size: planned number of observations
16,000 households.
Sample size (or number of clusters) by treatment arms
About 1,000 households per each of 16 treatments.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The minimum detectable effect is 1/8 of a standard deviation, calculated to have a power of 80%, using the treatment effect from Sadoff, S., Samek, A. S., & Sprenger, C. (2015). Dynamic Inconsistency in Food Choice: Experimental Evidence from a Food Desert. We use this treatment effect as a baseline, because of the similar context of a door-to-door food choice intervention.
Supporting Documents and Materials

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IRB Name
University of Southern California University Park Institutional Review Board
IRB Approval Date
IRB Approval Number
IRB Name
University of Chicago IRB AURA
IRB Approval Date
IRB Approval Number
Post Trial Information
Study Withdrawal
Is the intervention completed?
Is data collection complete?
Data Publication
Data Publication
Is public data available?
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)