Green jobs and motivations

Last registered on August 03, 2022


Trial Information

General Information

Green jobs and motivations
Initial registration date
July 29, 2022

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
August 03, 2022, 2:34 PM EDT

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



Primary Investigator

Università di Bologna

Other Primary Investigator(s)

PI Affiliation
Erasmus University Rotterdam

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
The ecological transition of the economy that is advocated to contrast climate change must be supported by the creation, in parallel, of green jobs and workers capable and willing to work for them. For this purpose, public and private actors from the green sectors need to define incentive-compatible tools so as to attract skilled workers. While the extant literature is rich in studies approaching the restructuring of greener sectors, there is a lack of knowledge about the behavioural motivations underlying job applications for a job in a green or polluting sector. What is most striking is the potential difference in short- and long-term financial incentives gave the opposite trends of the two sectors, as well as the potential inducing mechanism of social pressure for preferring green jobs.
External Link(s)

Registration Citation

Dini, Giorgio and Chiara Natalie Focacci. 2022. "Green jobs and motivations." AEA RCT Registry. August 03.
Experimental Details


Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
For each respondent, we obtain a ranking of the options from Option A to Option F. This implies that for each respondent we will have 6 scores from 1 to 6 associated with the options from A to F. For instance, respondent 1 will have its six choices linked to each one of the options available. Each match from the values 1-6 is uniquely linked with one of the options.

From this variable, we compute an index called greenness that represents the choice by each respondent of the green job openings. This variable is created by averaging the scores for the green options (D,E and F).

Additionally, we create three variables regarding the trend of the salary. These variables are generated by taking the mean of the options with the same salary trend (i.e., decreasing, constant and increasing).

For each job opening, we generate a count variable that takes a value equal to the number of respondents that selected that job opening as the first, second, third, forth, fifth and sixth.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Subjects are hired through the platform Prolific for £0.59 (£8.85/hour) and are asked to complete an online survey on Qualtrics. After completing the consent form, they are randomly assigned to either the control or treatment group. All participants are initially provided with information regarding job openings and their features in line with the idea that they have to make a decision relevant to their career. For this purpose, we ask them to carefully look at all career prospects.

The table below features the sector of the company, distinguishing between polluting and not polluting, and the future yearly wage level associated with each decade the subject would work at the company in question. These career wage prospects are shown to participants and presented in the table below for convenience. For simplicity, the retirement benefits are the same after forty years of work. Options A, B and C are jobs in a carbon-intensive sector in companies that cause pollution and climate change. Options D, E and F are jobs in a low-carbon sector in companies that drive the ecological transition of the economy. The wage level is different across all options. Options A and D show a decreasing wage over the years. Options B and E show a constant wage over the years. Options C and F show an increasing wage over the years.

After answering some understanding questions relative to the career prospects, participants in the treatment group are treated with social pressure. Particularly, they are told that in their community, some of the people would rather not apply for a job in a polluting company because of the damages it potentially causes to their health and the planet. They are also treated with the following information; namely, applying for a job in the low-carbon sector helps to promote the green economy, as well as safeguard the planet. We enhance social pressure for treated individuals by adding that part of their community agrees that opting for a green job is the best solution for society. Subjects in the control group are not treated with any specific information. All participants are asked to make a decision with respect to what job they would like to apply for. They are asked to rank the above-mentioned job options following the order of job applications they would send out, with 1 and 6, respectively, indicating their favourite and least favourite job option.

The survey ends with a short questionnaire. We ask questions relative to their age, gender, level of education, risk preferences, whether they consider themselves extrovert or introvert, and whether they have a small or large circle of friends. Participants are then asked about their employment status, the sector of employment, and the extent to which the company they currently work at is to be considered environmentally friendly. We also investigate their level of concern for the environmental situation in their community, for large-scale environmental damages, and for climate change more in general. In reference to this, we propose a last question where we ask what they think of the economy’s green transition. In particular, we ask them whether it can potentially affect the labour market in terms of creation or destruction of job opportunities.

Experimental Design Details
Randomization Method
Randomization done by software (Qualtrics)
Randomization Unit
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
600 individuals
Sample size: planned number of observations
600 rankings
Sample size (or number of clusters) by treatment arms
Around 300 individuals per treatment (two groups: treatment and control)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Around 233 (see document)
Supporting Documents and Materials


Document Name
Document Type
Document Description

MD5: e862a622b1cd76b38af5e414c84adaa4

SHA1: 2b517e7d0607f3a6e9a784950a5b0e3c794c55da

Uploaded At: July 29, 2022


Institutional Review Boards (IRBs)

IRB Name
ESL Research Ethics Review Committee
IRB Approval Date
IRB Approval Number
Analysis Plan

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Post Trial Information

Study Withdrawal

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Is the intervention completed?
Data Collection Complete
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials