University Education and Students' Willingness-To-Pay for Green Attributes of Prospective Jobs

Last registered on March 13, 2025
View Trial History

Pre-Trial

Trial Information

General Information

Title
University Education and Students' Willingness-To-Pay for Green Attributes of Prospective Jobs
RCT ID
AEARCTR-0015138
Initial registration date
March 03, 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
March 13, 2025, 8:17 AM EDT

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

Locations

Country
Italy
Region

Primary Investigator

Name
Andrea Marini
Affiliation
University of Ferrara
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Fabio Landini
PI Affiliation
University of Parma
Contact Investigator
PI Name
Ugo Rizzo
PI Affiliation
University of Ferrara
Contact Investigator

Additional Trial Information

Status
In development
Start date
2025-03-15
End date
2025-04-15
Keywords
Environment & Energy
Additional Keywords
Green transition, Jobs' green attributes, Stated preference experiment, Students' green attitudes, University education
JEL code(s)
C10, I23, J28, J31, J81, Q50
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study investigates the impact of university education on students’ green attitudes towards prospective jobs, addressing a critical gap in the literature on the determinants of sustainability-related behaviors. A behavioral survey experiment is conducted using a representative sample of 2,000 individuals aged 18-30 years, residing across all Italian regions. Participants without a university education background are also included in the sample in order to capture potential differences in green attitudes.
The survey experiment employs stated preference methods to estimate respondents’ Willingness-To-Pay (WTP) for green attributes in hypothetical jobs and examine its heterogeneity across individuals’ characteristics and behavioral traits (social and time preferences, risk tolerance, and competitiveness). Participants are asked to evaluate job scenarios that vary randomly in earnings and green attributes, providing probabilistic choices that allow for precise measurement of preferences, free from confounding equilibrium job-market factors.
The analysis integrates data from the green skills classification of university courses—developed in previous research—to assess how educational content influences students’ WTP.
External Link(s)

Registration Citation

Citation
Landini, Fabio, Andrea Marini and Ugo Rizzo. 2025. "University Education and Students' Willingness-To-Pay for Green Attributes of Prospective Jobs." AEA RCT Registry. March 13. https://doi.org/10.1257/rct.15138-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Throughout the survey, participants will respond to ten stated-preference experimental questions, each presenting two job offers, A and B. Each pair of job offers will vary randomly in monthly salaries and in the values of ten attributes. Six of these ten attributes can take one of two values: green (eco-friendly) or brown (not eco-friendly). The remaining four attributes can take on two values referring to some dimensions of working conditions, more desirable and less desirable respectively.

In each stated preference question, participants will indicate their probabilistic choice between JOB OFFER A and JOB OFFER B. This approach enables precise measurement of respondents' Willingness-to-Pay (WTP) for job attributes, free from confounding factors related to equilibrium conditions in the job market.
Intervention Start Date
2025-03-15
Intervention End Date
2025-04-15

Primary Outcomes

Primary Outcomes (end points)
The key outcome is the participants' Willingness-To-Pay (WTP) for each green attribute of hypothetical jobs.
Primary Outcomes (explanation)
To derive each individual's WTP for each green attribute, we first need to estimate, using a probabilistic model, two parameters in the indirect utility function: the individual's marginal utility of each green attribute and the individual's marginal utility of the wage.

Secondary Outcomes

Secondary Outcomes (end points)
The secondary outcome is the participants' Willingness-To-Pay (WTP) for each desirable attribute of hypothetical jobs.
Secondary Outcomes (explanation)
To derive each individual's WTP for each desirable attribute, we first need to estimate, using a probabilistic model, two parameters in the indirect utility function: the individual's marginal utility of each desirable attribute and the individual's marginal utility of the wage.

Experimental Design

Experimental Design
In the first section of the survey, participants are asked to respond to a set of questions on demographic characteristics, including gender, age, ethnicity, region of residence, education level, employment status, unemployment status, and occupation. Also, for those attending or who have attended university courses, additional questions cover the academic year of enrolment, course name, and university attended.
In the second section, we elicit information on a range of behavioral traits, that is risk tolerance, time preferences, competitiveness, and social preferences –altruism, reciprocity, and trust– using experimentally validated survey questions.

Afterwards, the survey involves ten stated-preference experimental questions. Each of these questions displays a pair of hypothetical job offers, namely JOB OFFER A and JOB OFFER B. Each job offer is described by ten attributes characterizing both the occupation and the company providing it, along with the offered monthly salary. Of these ten attributes, six can take on two values: one brown and one green (brown = not environmentally sustainable; green = environmentally sustainable). The remaining four attributes can take on two values referring to some dimensions of working conditions, more desirable and less desirable respectively. The offered monthly salary is always randomly assigned across JOB OFFER A and JOB OFFER B.
Experimental Design Details
Not available
Randomization Method
For each of the ten experiment questions, the randomization of the salaries offered and the values of the changing attributes is ensured through a programming language (JavaScript).
Randomization Unit
Individual.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
There is no cluster.
Sample size: planned number of observations
The sample consists of 2,000 individuals aged between 18 and 30 residing in all Italian regions. Each individual is expected to respond to ten stated preference questions.
Sample size (or number of clusters) by treatment arms
The treatment is the same for all the individuals.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
REB - Research Ethics Board
IRB Approval Date
2025-02-28
IRB Approval Number
69394
Analysis Plan

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information