AEA RCT Registry

Trial Information

General Information

Title

Worker Perceptions of Young Firms

RCT ID

AEARCTR-0014259

Initial registration date

September 02, 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

September 12, 2024, 5:24 PM EDT

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

Locations

Country

Netherlands

Region

Primary Investigator

Name

Mikael Paaso

Affiliation

Erasmus University

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Ratchanon Chotiputsilp

PI Affiliation

Erasmus University

Contact Investigator

Additional Trial Information

Status

In development

Start date

2024-09-04

End date

2025-12-31

Keywords

Finance & Microfinance, Lab, Labor

Additional Keywords

Entrepreneurship

JEL code(s)

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

In this project, we study worker perceptions of young firms using two separate survey experiments (note: we are also planning to run a field experiment, which we would register separately once logistical details are worked out). We show participants job ads where the firm type is randomized to test whether people report a higher willingness to apply for an otherwise identical job if it is offered by a young firm. Using this data, we attempt to estimate whether young firms need to offer higher wages to attract workers for observably similar jobs. In addition to this, we ask whether common stereotypes about young firms as employers are true - whether they offer more upside, long-term career benefits, independence and possibilities to advance.

External Link(s)

Registration Citation

Citation

Chotiputsilp, Ratchanon and Mikael Paaso. 2024. "Worker Perceptions of Young Firms." AEA RCT Registry. September 12. https://doi.org/10.1257/rct.14259-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

We show people hypothetical job advertisements with some features randomized. The specific randomized elements are described in the "hidden" section describing the intervention. We will run two version of the experiment, one on Prolific and one targeted at students in the MSc Finance and Investments programme at the Rotterdam School of Management.

Intervention Start Date

2024-09-04

Intervention End Date

2025-01-01

Primary Outcomes

Primary Outcomes (end points)

The likelihood of accepting a job if offered (1-5 Likert scale)
The estimated salary premium / discount a person is willing to accept for a given job
In the survey, we ask participants to explain their reasoning for applying for a job. We will use this question to create a sample of respondents whose rating is based on the firm ("noise reduction sample"). This will filter out participants who are not interested in or qualified for the role. We will do this by feeding the answers to OpenAI's API with the prompt "Does this response relate to the company? Respond either YES or NO"

Primary Outcomes (explanation)

The Likert scale is clear.
The salary premium will be estimated in a manner similar to Colonnelli et al (2024)

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

We show people hypothetical job advertisements with some features randomized. The specific randomized elements are described in the "hidden" section describing the intervention. We will run two version of the experiment, one on Prolific and one targeted at students in the MSc Finance and Investments programme at the Rotterdam School of Management.

Experimental Design Details

Not available

Randomization Method

Randomization done via Qualtrics.

Randomization Unit

Each hypothetical job will be randomized. Therefore an individual will see multiple treatments.

Was the treatment clustered?

No

Experiment Characteristics

Sample size: planned number of clusters

RSM: We will distribute the survey to all incoming students (about 400). The response rate is uncertain.
Prolific: We will aim for a sample size of 500

Sample size: planned number of observations

400*7 jobs = 2800 user-job observations RSM 500*7 = 3500 user-job observations Prolific

Sample size (or number of clusters) by treatment arms

Sample size per treatment is 700 for the RSM sample (2800 jobs / 4 possible treatments)
In the Prolific arm, the sample size per treatment is 3500/4 = 875

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Supporting Documents and Materials

IRB

Institutional Review Boards (IRBs)

IRB Name

Rotterdam School of Management IRB-E

IRB Approval Date

2024-06-10

IRB Approval Number

ETH2324-0861