Technology Restrictions and Talent Allocation: A Survey Experiment

Last registered on January 06, 2025

Pre-Trial

Trial Information

General Information

Title
Technology Restrictions and Talent Allocation: A Survey Experiment
RCT ID
AEARCTR-0014865
Initial registration date
January 04, 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
January 06, 2025, 12:37 PM EST

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

Locations

Region

Primary Investigator

Affiliation
University of Michigan

Other Primary Investigator(s)

PI Affiliation
Sichuan University
PI Affiliation
Dongbei University of Finance and Economics

Additional Trial Information

Status
On going
Start date
2024-12-05
End date
2025-01-10
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study investigates the impact of U.S. technology restrictions on the college major choices of Chinese students. Since 2018, the U.S. government has introduced policies targeting China's high-tech industries. These policies probit the export of high-tech products to specific Chinese companies, primarily in sectors such as aerospace, pharmaceuticals, electronics, and computing. Given the reliance of these industries on U.S. technologies and the intensifying U.S.-China tensions, the restrictions are expected to have significant implications for China's industrial structure and labor market. While recent research has examined how Chinese firms are adapting to these restrictions and how the Chinese government is responding with industrial policies like subsidies and R&D support, little is known about the impact of these policies on students' educational and career decisions.

On one hand, these restrictions could negatively affect job prospects in the restricted industries if they stifle growth, potentially discouraging top students from pursuing related majors. On the other hand, these restrictions could incentivize domestic innovation and production in these fields. Combined with supportive government policies and funding, they could create new opportunities, making these majors more appealing. Moreover, foreign restrictions could evoke a sense of patriotism, encouraging students to pursue careers in the restricted fields.

Understanding this dynamic is critical, as the allocation of top talent has long-term implications for the development of high-tech industries. If fewer high-achieving students choose majors in restricted fields, these industries may face challenges in fostering growth and innovation. Conversely, if restrictions attract more top talent, they could drive independent innovation and development despite external restrictions.

To address these questions, we will conduct a survey experiment with approximately 1,000 high school juniors and seniors in China who are preparing for college entrance exams. Students will be randomly assigned to one of two groups: a treatment group that is exposed to information about U.S. technology restrictions targeting specific high-tech fields, and a control group that receives a placebo message of similar length unrelated to the restrictions. The information treatment aims to simulate the policy shock for students who are unaware of the restrictions and to increase the salience of these policies for those already aware.

For both groups, we will collect data on demographics, family background, and students’ intentions to pursue majors that are more or less related to the restricted fields. By comparing major preferences between the treatment and control groups, we aim to assess how the U.S. restrictions influence students' intentions toward majors in the restricted fields. Additionally, we will investigate potential mechanisms driving these decisions by eliciting students’ expected returns for different majors, their nationalistic values, and their reasons behind their major choices. This study seeks to provide new insights into how U.S.-China tensions influence talent allocation and shape China's educational and economic landscape.
External Link(s)

Registration Citation

Citation
Li, Xiao, Wenhua Liu and Huayu Xu. 2025. "Technology Restrictions and Talent Allocation: A Survey Experiment." AEA RCT Registry. January 06. https://doi.org/10.1257/rct.14865-1.0
Experimental Details

Interventions

Intervention(s)
Students will be randomly assigned to one of two groups: a treatment group that is exposed to information about U.S. technology restrictions targeting specific high-tech fields, and a control group that receives a placebo message of similar length unrelated to the restrictions. The information treatment aims to simulate the policy shock for students who are unaware of the restrictions and to increase the salience of these policies for those already aware.
Intervention (Hidden)
Intervention Start Date
2024-12-05
Intervention End Date
2025-01-10

Primary Outcomes

Primary Outcomes (end points)
students’ intentions to pursue specific majors
Primary Outcomes (explanation)
We use a 5-point Likert scale to measure intentions for different majors, where 5 represents having very strong intention and 1 represents having little to no intention. We elicit students' intentions for six majors, where three majors are closely related to the restricted fields and the others are less related to restricted fields. For ease of interpretation, we may convert the Likert scale into dummies, indicating whether students have the strongest or strong intentions for each major.

Secondary Outcomes

Secondary Outcomes (end points)
expected returns for specific majors
Secondary Outcomes (explanation)
We use a 5-point Likert scale to measure students' expected returns for different majors, where 5 represents very high returns and 1 represents very low returns. Students' expected returns are elicited for the same set of majors used in the primary outcome—three closely related to the restricted fields and three less related. For ease of interpretation, we may convert the Likert scale responses into binary variables, indicating whether students expect very high or high returns for each major.

Experimental Design

Experimental Design
We will conduct a survey experiment with approximately 1,000 high school juniors and seniors in China who are preparing for college entrance exams. Students will be randomly assigned to one of two groups: a treatment group that is exposed to information about U.S. technology restrictions targeting specific high-tech fields, and a control group that receives a placebo message of similar length unrelated to the restrictions. The information treatment aims to simulate the policy shock for students who are unaware of the restrictions and to increase the salience of these policies for those already aware.

For both groups, we will collect data on demographics, family background, and students’ intentions to pursue majors that are more or less related to the restricted fields. By comparing major preferences between the treatment and control groups, we aim to assess how the U.S. restrictions influence students' intentions toward majors in the restricted fields. Additionally, we will investigate potential mechanisms driving these decisions by eliciting students’ expected returns for different majors, their nationalistic values, and their reasons behind their major choices. This study seeks to provide new insights into how U.S.-China tensions influence talent allocation and shape China's educational and economic landscape.
Experimental Design Details
Randomization Method
randomization done by survey platform using algorithms
Randomization Unit
individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
N.A.
Sample size: planned number of observations
1,000 high school juniors and seniors
Sample size (or number of clusters) by treatment arms
roughly 500 students in the control group, and 500 students in the treatment group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Peking University Institutional Review Board
IRB Approval Date
2024-11-12
IRB Approval Number
IRB00001052-24138

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