Coarse and granular nutritional labels

Last registered on June 21, 2021


Trial Information

General Information

Coarse and granular nutritional labels
Initial registration date
June 20, 2021
Last updated
June 21, 2021, 11:50 AM EDT



Primary Investigator

Columbia University

Other Primary Investigator(s)

Additional Trial Information

In development
Start date
End date
Secondary IDs
I study how consumers respond to nutritional labels with different levels of granularity.
The study is motivated by the fact that public authorities often adopt simple categorical labels. These labels convey information and promote healthy, ethical, or energy-friendly behavior. Empirical and experimental literature has shown that these coarse labels can have a significant impact on consumers. On the other end, Information theory (starting from Blackwell 1951) predicts that consumers would learn more, and be better off, if regulators used granular labels (more detailed) instead of coarse labels (e.g., high vs. low score). This prediction relies on consumers being able to understand and process equally well the label information both when it is coarse and detailed. Boundedly rational consumers might be able to process coarse information, but not detailed one, and for this reason might be better off with coarse labels.
In this project, I focus on food choice and I study how consumers respond to different labels. I plan to conduct an online field-framed experiment in which I manipulate the granularity of the nutritional information provided to the decision maker.
Each participant will complete a series of incentivized choices between packaged food products, with the opportunity of receiving one of the selected products. The design allows comparing the healthiness of consumer choices under different labeling regimes, and test whether consumers make healthier choices when more detailed information is provided. If consumers have limited capacity to process detailed labels, they will be responsive to coarse information, but less responsive when the information is detailed.
Finally, I collect separately individual preferences over levels of calories. I combine product choices and declared preferences to study whether detailed information improves the choices, after controlling for individual preferences.
External Link(s)

Registration Citation

Ravaioli, Silvio. 2021. "Coarse and granular nutritional labels." AEA RCT Registry. June 21.
Experimental Details


Participants complete a food choice task. In each trial, they select one among the food products available.
Based on the treatment, the products are presented with different types of nutrient labels (different granularity) to indicate the calorie amount of the products.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Do labels affect choices?
The primary outcome variable is how participants change the choice probability of different products in response to the label information.

The primary hypotheses are that:
- coarse labels generate healthier and better choices than the control: positive effect from treatment1 (control) to t2, and from t2 to t3
- detailed labels are less effective than coarse ones: negative effect from treatment 3 to t4.

Healthier choices are defined in accordance with the number of calories per serving of the selected products. The variables of interest are:
- average amount of calories (across different trials)
- probability of choosing a healthy food option: 1) with respect to the current trial (calories below the median value in the current choice set), and 2) with respect to the whole range of possible products in the category (products with less than 150 Calories per serving).

Better choices are defined in accordance with self-reported preferences (participants will be asked to rank products based only on the calorie amount).
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Do labels affect the search process?
The secondary variables of interest are
- response time: time to take the decision
- information collection: the probability of consulting the nutrient fact information on the back of the package of each product (mousetracking data)

The hypotheses are that more detailed labels generate
- faster responses
- lower information collection (fewer consultations of the back of package information)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The experiment will be conducted online. Participants are recruited with Prime Panels (managed by CloudResearch).
Participants complete a food choice task. In each trial, they select one among the food products available. Each product is displayed with its front-package image (box of the product), back-package image (nutrition facts), brief description, and price.

Participants are randomly assigned to different treatments (label regimes), that differ only in the information provided in the front-package image of the products. In all the treatments, the existing nutritional claims and label information are removed from the package (e.g. sugar content, fat content, claims such as “low-fat”) and are replaced with a new label (that indicates the number of calories per serving) according to the calories of the product and the treatment.

Participants are randomly assigned to one out of four treatments, that differ only in the content of the calorie label:
1) no label (control),
2) two levels: low calorie (60-149 Calories), high calorie (150-240 Calories)
3) four levels: very low calorie (60-109 Calories), low calorie (110-149 Calories), high calorie (150-189 Calories), very high calorie (190-240 Calories)
4) ten levels: 3% daily value (about 60 Calories), 4% daily value (about 80 Calories), ... 12% daily value (about 240 Calories).
The number of calories is the amount per serving indicated in the Nutrition Facts label, and the percent daily value refers to the FDA recommendation.

Each participant completes 80 trials (choice sets), picking one product from each choice set. The trials differ in
- number of options available (40 trials with 2 products, 40 trials with 4 products)
- product categories (40 trials with cereals, 40 trials with snacks)
- prices (40 trials with lower prices for low-calorie products, 40 trials with lower prices for high-calorie products).
The products in the choice sets are the same for all the participants. The order of appearance of the trials and the position of the products on the screen are randomized at the individual level.
Experimental Design Details
Randomization Method
Randomization is done by Qualtrics, the platform on which the experiment is run.
Randomization Unit
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Approximately 800 individuals
Sample size: planned number of observations
Approximately 800 individuals, each of whom will make 80 choices.
Sample size (or number of clusters) by treatment arms
Approximately 200 individuals for each of the four treatment arms.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
Columbia University in the City of New York
IRB Approval Date
IRB Approval Number


Post Trial Information

Study Withdrawal

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Is the intervention completed?
Data Collection Complete
Data Publication

Data Publication

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Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials