The Economics of the Public Option: Evidence from Local Pharmaceutical Markets

Last registered on October 21, 2021


Trial Information

General Information

The Economics of the Public Option: Evidence from Local Pharmaceutical Markets
Initial registration date
October 19, 2021

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
October 21, 2021, 9:21 AM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated
October 21, 2021, 9:27 AM EDT

Last updated is the most recent time when changes to the trial's registration were published.



Primary Investigator

Stanford University

Other Primary Investigator(s)

PI Affiliation
University of Pennsylvania
PI Affiliation
University of California Berkeley
PI Affiliation
Pontificia Universidad Catolica de Chile

Additional Trial Information

Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
This field experiment informs the broader question about the effects of competition by state-owned firms on market outcomes. The study design is motivated by two facts. On the one hand, substantial price differences have been documented across private and public pharmacies. On the other hand, few consumers have registered and purchased products from the latter, despite being eligible to it. The goal of the field experiment was to study whether (lack of) information about public pharmacies affected awareness about it, pharmacy choice patterns, and perception about local politicians (who are accountable for their implementation).
External Link(s)

Registration Citation

Atal, Juan Pablo et al. 2021. "The Economics of the Public Option: Evidence from Local Pharmaceutical Markets." AEA RCT Registry. October 21.
Experimental Details


We designed an intervention to address information frictions. First, it could be the case that households are simply unaware of the existence of public pharmacies as an option in their choice sets. Lack of awareness of public pharmacies, may explain why families are not taking
advantage of them. Second, it could be the case that, while aware of its existence, households are already familiar with private pharmacies location and attributes, while not so for public pharmacies. If searching those characteristics is costly, then it might deter households from taking advantage of public pharmacies. The treatment takes the form of informational flyers that are specific to each local market. The flyer provides information about the existence of a public pharmacy in the county and two general features of it, namely the fact that it offers lower prices than private pharmacies and that it may take longer to deliver the products. It also includes information about location, contact information, hours of attention and eligibility requirements.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
On the economic side, we focus on consumer knowledge, perceived prices, perceived waiting times, enrollment, purchase behavior. On the political side, we focus on self reported voting behavior for the incumbent mayor or her party.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We designed a field experiment to study whether the availability of public pharmacies affected consumer shopping behavior. To induce variation in awareness about the public pharmacy in their local market, we implemented an informational intervention. The decision to provide information was based on a survey we conducted before the experiment, which revealed that consumers were only partially informed along two dimensions. First, some households were unaware of the existence of a public pharmacy in their county. Second, even when households knew about the pharmacy, they were not perfectly informed about the lower prices and other attributes. The existence of imperfect information provides us with a unique opportunity to randomly expose consumers to public pharmacies using our experiment, and thus to measure individual responses to them.

The treatment consisted of an informational flyer. It provided information about the existence of a public pharmacy in the county, and stated that it offered lower prices and longer waiting times than private pharmacies. Additionally, it included its location, contact information, opening hours, and eligibility requirements. We delivered the flyer to consumers coming out of private pharmacies in the 20 counties with public pharmacies in Santiago. The information was tailored to each county.

In terms of recruitment, enumerators approached consumers leaving a private pharmacy in each county and assessed their eligibility. Eligible participants were those who (i) lived and were registered to vote in the county, (ii) had purchased a prescription drug, and (iii) were not registered in the public pharmacy. Those who accepted to be part of the study, answered the baseline survey. Once the survey was completed, participants were randomly assigned to treatment and control groups. The enumerator only learned the assignment of the individual after completing the survey. We implemented this survey between October 12 and 20, 2016, right before mayoral elections. Two months after the baseline survey, we conducted a follow-up survey to measure the same variables as in baseline. We implemented this survey by phone.
Experimental Design Details
Randomization Method
Randomization was implemented at the point of survey, within the electronic form.
Randomization Unit
Individual level randomization.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
826 individuals enrolled in the study.
Sample size: planned number of observations
826 individuals enrolled in the study.
Sample size (or number of clusters) by treatment arms
507 individuals were assigned to the treatment group, 319 were assigned to the control group.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
University of Pennsylvania
IRB Approval Date
Details not available
IRB Approval Number


Post Trial Information

Study Withdrawal

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Is the intervention completed?
Data Collection Complete
Data Collection Completion Date
Final Sample Size: Number of Clusters (Unit of Randomization)
Was attrition correlated with treatment status?
Final Sample Size: Total Number of Observations
Final Sample Size (or Number of Clusters) by Treatment Arms
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials