Willingness to Pay for Firm Training and Further Job Attributes

Last registered on April 16, 2024


Trial Information

General Information

Willingness to Pay for Firm Training and Further Job Attributes
Initial registration date
April 08, 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
April 16, 2024, 1:06 PM EDT

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


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Primary Investigator

Technical University of Munich

Other Primary Investigator(s)

PI Affiliation
Technical University of Munich
PI Affiliation
ifo Institute

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
We run a choice experiment that induces exogenous variation in job attributes. The key features of the experimental design follows Maestas et al. (2023). We aim at identifying workers' willingness to pay for firm training. Additionally, we investigate willingness to pay for other job attributes, in particular working hours, flexibility, autonomy, contract type and leadership.
External Link(s)

Registration Citation

Brosch, Hanna, Philipp Lergetporer and Florian Schoner. 2024. "Willingness to Pay for Firm Training and Further Job Attributes." AEA RCT Registry. April 16. https://doi.org/10.1257/rct.13321-1.0
Sponsors & Partners

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Experimental Details


We run an online discrete choice experiment among employees in Germany to estimate their willingness to pay (WTP) for firm training. The discrete choice experiment is part of a longer questionnaire that focuses on firm training.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Respondents’ choice between two hypothetical jobs
Primary Outcomes (explanation)
We use respondents’ choice between two hypothetical jobs to estimate the willingness-to-pay for firm training and other job characteristics.

Secondary Outcomes

Secondary Outcomes (end points)
We are also exploring heterogeneity in WTP for firm training.

Therefore, we plan to perform heterogeneity analyses with respect to
(i) respondents’ own educational attainment/skill level
(ii) respondents’ exposure to structural change (automation risk)
(iii) respondents’ age

Additional we will perform an exploratory analysis on further heterogeneities by respondents’ type of job (e.g., job characteristics), prior firm training participation, and other respondent characteristics.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The experimental design aims at identifying the workers’ WTP pay for the job attribute firm training. Additionally, we plan to analyze workers' willingness to pay for job attributes other than firm training. The key features of the experimental design follows Maestas et al. (2023).

Each respondent participates in five stated-preference experiments. In each experiment, survey respondents are asked to select between two jobs (A and B), each defined by a partially varying set of job attributes and wages.

For each respondent, we defined a baseline job around which job attributes would vary. The baseline job was the respondent’s current job in order to generate hypothetical jobs that would appear realistic to the respondent. For this purpose, the respondents were asked about their current occupation, job attributes and wage prior to the discrete choice experiment. To make the hypothetical jobs more realistic, the occupation of the job never varied and was set to the current occupation of the respondent while the remaining six job attributes varied when selected and the wage always varied. In the following, we describe how we create the variation.

Starting from the respondent’s baseline job, we create hypothetical Job A and Job B by randomly selecting two non-wage attributes to vary across the two hypothetical jobs. Within each of the two randomly selected attributes, attribute values are chosen at random sequentially, first for Job A and then for Job B without replacement.

While the non-wage attributes vary only when selected, the offered wage always varies
randomly across Job A and Job B. To achieve variation in the monthly wage, we proceed as follows:
I. Prior to the discrete choice experiment, respondents are asked to indicate their monthly net wage and their working hours. We calculate the hourly wage from this information.
II. The hourly wage is then multiplied by a randomly drawn weight from a normal distribution with mean 1 and standard deviation .1 (truncation of weights at 0.75 and 1.25).
III. If the hourly wage falls below the minimum wage, it is set to the minimum wage.
IV. The wage is then converted back to a monthly wage: we multiply the hourly wage with the (randomly varying) working time shown in the job offer and with 4.3 (weeks).

To increase statistical power, we avoid generating dominating jobs. A dominating job offers flexibility, job security and a higher wage than the other job. In this case, we switch the wages of the two jobs.

In every job choice, respondents see two jobs next to each other where two randomly selected job attributes and the monthly wage vary. Those three attributes are marked in red and all the other job attributes are the same as in their current job. The respondents were asked to select “Strongly Prefer Job A,” “Prefer Job A,” “Prefer Job B,” or “Strongly Prefer Job B.”

For the job attributes, the mapping from the survey questions to the discrete choice characteristics is as follows:

Firm Training:
“How many whole hours have you spent on firm training in the last 12 months?”
Mapping for DC attribute: “Firm training opportunities”
○ If <80 h: Without firm training opportunities
○ If >=80 h: With firm training opportunities

“There are very different working time arrangements. Which of the following is most likely to apply to your work?
a) Fixed working hours
b) Flexitime (with or without core working hours)
c) Trust-based working hours
Mapping for DC attribute: “Start and end of work”
- If a) : Set by the company
- If b) or c): Free choice

“How much freedom do you have in determining your work tasks and the way in which you carry out these tasks?
- little freedom
- a lot of freedom”
Mapping for DC attribute: “Work tasks”
- little freedom = little freedom
- a lot of freedom = a lot of freedom

“Do you have a fixed-term or permanent employment contract?
- Fixed-term employment contract
- Permanent employment contract“
Mapping for DC: “Employment contract”
- permanent = permanent
- fixed-term = fixed-term

Working Time:
How many hours are your contractually agreed working hours per week?
Mapping for DC: “Weekly working time in hours”
- Same integer as indicated, added up with: [-10,-5,0,5,10]

How much do you agree with the following statement? I have leadership responsibility in my current job.
Mapping for DC attribute: “Leadership responsibilities”
- I strongly agree, I somewhat agree = Yes
- Neither, I somewhat disagree, strongly disagree = No

We use the WTP for leadership responsibilities as a pilot for an unrelated project investigating gender differences in this job attribute.

Reference: Maestas, Nicole, Kathleen J. Mullen, David Powell, Till von Wachter, and Jeffrey B. Wenger. 2023. "The Value of Working Conditions in the United States and the Implications for the Structure of Wages." American Economic Review, 113 (7): 2007-47.
Experimental Design Details
Not available
Randomization Method
By a computer
Randomization Unit
At the individual level
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Sample size: planned number of observations
3,000 individuals making 5 choices over 2 job profiles resulting in 15,000 choices over 30,000 job profiles
Sample size (or number of clusters) by treatment arms
There are no treatment arms in our design, but the job characteristics vary randomly in each individual choice experiment.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
German Association for Experimental Economic Research e.V.
IRB Approval Date
IRB Approval Number