Digital Technology, Meritocracy and Rent-seeking, Experiment in China

Last registered on September 22, 2025

Pre-Trial

Trial Information

General Information

Title
Digital Technology, Meritocracy and Rent-seeking, Experiment in China
RCT ID
AEARCTR-0016833
Initial registration date
September 19, 2025

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
September 22, 2025, 6:48 AM EDT

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

Locations

Region

Primary Investigator

Affiliation
Renmin University of China

Other Primary Investigator(s)

Additional Trial Information

Status
Completed
Start date
2023-09-01
End date
2025-09-20
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
The advancement of digital technology enables governments to access vast amounts of data, raising concerns about centralization and privacy infringement. However, many local governments actively pursue digital governance initiatives, prompting a key question: What motivates local officials? One explanation is that digital technology creates rent-seeking opportunities. This paper conducts a randomized experiment involving more than 2,000 Chinese civil servants, introducing two information interventions: merit intervention and low-pay intervention. Participants choose between automated and manually managed projects. We find that when officials receive both merit-intervention and low-pay intervention, they exhibit a stronger preference for retaining human discretion in digital governance, favoring automated technologies over manually managed projects. Using a list experiment, we show that officials recognize the rent-seeking opportunities embedded in automated governance and, after treatment, display greater tolerance for corruption. We attribute this to the sharp contrast between the intense competition for public office and the relatively low salaries. We also rule out alternative explanations, including technocratic enthusiasm, distrust in technology, power-seeking motives, and prosocial behavior. Our findings provide new insights into the political economy of digital governance by shedding light on the motivations driving government officials to adopt digital technologies.
External Link(s)

Registration Citation

Citation
Chen, Junkai. 2025. "Digital Technology, Meritocracy and Rent-seeking, Experiment in China." AEA RCT Registry. September 22. https://doi.org/10.1257/rct.16833-1.0
Experimental Details

Interventions

Intervention(s)
Intervention (Hidden)
Intervention Start Date
2023-09-02
Intervention End Date
2025-09-19

Primary Outcomes

Primary Outcomes (end points)
The advancement of digital technology enables governments to access vast amounts of data, raising concerns about centralization and privacy infringement. However, many local governments actively pursue digital governance initiatives, prompting a key question: What motivates local officials? One explanation is that digital technology creates rent-seeking opportunities. This paper conducts a randomized experiment involving more than 2,000 Chinese civil servants, introducing two information interventions: merit intervention and low-pay intervention. Participants choose between automated and manually managed projects. We find that when officials receive both merit-intervention and low-pay intervention, they exhibit a stronger preference for retaining human discretion in digital governance, favoring automated technologies over manually managed projects. Using a list experiment, we show that officials recognize the rent-seeking opportunities embedded in automated governance and, after treatment, display greater tolerance for corruption. We attribute this to the sharp contrast between the intense competition for public office and the relatively low salaries. We also rule out alternative explanations, including technocratic enthusiasm, distrust in technology, power-seeking motives, and prosocial behavior. Our findings provide new insights into the political economy of digital governance by shedding light on the motivations driving government officials to adopt digital technologies.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We conducted a randomized trial on over 2000 Chinese civil servants, which included two types of information interventions - merit intervention and low-pay intervention. During the merit intervention stage, we randomly informed some respondents of the competition ratio for this year's civil service exam - the competition ratio for popular positions is above 1000:1, in order to stimulate their sense of elite as winners of the civil service exam. During the low-pay intervention phase, we randomly told some respondents about the news of civil service pay cuts and asked them to recall whether they had experienced pay cuts. After each information intervention, we also raised a series of questions to test the effectiveness of the information intervention.
Experimental Design Details
Randomization Method
Randomization done in office by a computer
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
2000 individuals
Sample size: planned number of observations
3000
Sample size (or number of clusters) by treatment arms
1000 individuals each group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
School of Finance, Renmin University of China
IRB Approval Date
2024-09-01
IRB Approval Number
N/A

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials