Understanding Privacy Preferences Around the Developing World

Last registered on May 13, 2024


Trial Information

General Information

Understanding Privacy Preferences Around the Developing World
Initial registration date
May 07, 2024

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
May 13, 2024, 12:22 PM EDT

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


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Primary Investigator

Harvard University

Other Primary Investigator(s)

PI Affiliation
PI Affiliation

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Privacy is increasingly regarded as an important consideration for consumer protection in digital financial services (DFS), with privacy preferences and attitudes governing many online choices and behaviors. However, these preferences remain one of the least understood topics in social science. This problem is even more pronounced in low- and middle-income countries (LMICs), since most work on privacy preferences is conducted in the US and Europe.

Privacy considerations may differ significantly in LMICs compared to other rich countries for many reasons. If privacy is considered a luxury, then the significant income disparities between LMICs and richer nations could affect the perceived tradeoffs. Further, intrinsic privacy preferences may differ across countries due to different cultural contexts, political and historical reasons or demographics. The use of DFS in LMICs also differs from countries that digitized earlier. For example, many LMICs moved directly from cash to mobile payments, bypassing credit and debit cards, which could influence the formation of beliefs of privacy.

This project aims to describe and understand individuals’ privacy preferences and attitudes online — what do people prefer in terms of privacy protection and how do they consider trade-offs? How do they reason about privacy? What drives their privacy-related behaviors? And how does the structure of privacy preferences and attitudes differ across individuals within and across countries?
External Link(s)

Registration Citation

Hoong, Ruru (Juan Ru), Andrew Kao and David Yang. 2024. "Understanding Privacy Preferences Around the Developing World." AEA RCT Registry. May 13. https://doi.org/10.1257/rct.12399-1.0
Sponsors & Partners

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Experimental Details


The bulk of this project is descriptive. We also randomize showing respondents videos emphasizing different privacy concerns by governments and corporations. The intervention consists of the order in which videos are shown to surveyed respondents: in one intervention, we show videos produced by Google first, and videos produced by DuckDuckGo and about the government second. In the other intervention, we reverse this order.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Measures of privacy. These include:
1. Existing measures of privacy constructed by other academics and survey organizations from across the world
2. Usage of privacy-enhancing tools and behaviors
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We will randomly show videos about privacy developed by corporations and governments to respondents.
Experimental Design Details
Not available
Randomization Method
Randomization will be conducted by survey software.
Randomization Unit
Randomization will be at the individual level.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Approximately 1000 individuals per country, oversampling some countries (US and China).
Sample size: planned number of observations
>20,000 individuals
Sample size (or number of clusters) by treatment arms
>10,000 individuals per treatment arm (Google videos first or last).
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
The Committee on the Use of Human Subjects (Harvard IRB)
IRB Approval Date
IRB Approval Number