The following summary and thoughts on Mas and Pallais (Forthcoming in the AER, 2017) is taken in part from a report I put together for a course in labor economics. In this study, the authors present their results from the first large-scale field experiment attempting to elicit workers’ valuations of specific amenities (e.g. working from home, flexible hours, flexible scheduling). The paper provides a critical foundation for future research in understanding workers’ preferences over a variety of work arrangements that are commonly offered by employers.
Overview of Mas and Pallais (forthcoming AER 2017)
To gather data on workers’ willingness to pay (WTP) for different amenities, the authors recruit staffers for a national call center for the purpose of administering surveys unrelated to this project. Advertisements were posted online in 68 large metro areas, and potential applicants were able to click-through into the application, wherein they (optionally) listed their race, ethnicity, and gender. Next, the applicants specified which of two job opportunities they would prefer: the “baseline” job at a specified wage or a “treatment” job at a potentially different wage. The main treatments included: work from home (ability to work from home, Mon-Fri 9am-5pm), flexible scheduling (ability to choose how to allocate 40 hours per week), flexible hours (ability to choose the amount of hours up to 40 hours per week), and employer discretion (the employer sets your schedule every week with a one week notice, and work times can include weeknights or weekends).
In order to estimate the distribution of worker’s WTP, the authors randomly selected wages and assigned them to one of the two jobs. For each pair the applicant saw, one job always had the maximum wage of $16 per hour (or 19, depending randomly on the city) while the other had a wage within 5 dollars of the maximum wage (+/- $0.25, $0.50, $0.75, … , $2.75, $3, $4,or $5). The applicants were told that this choice would not affect their hiring decision, and would only be seen by the employer after a hiring decision had been made. Thus, this field experiment is a between-subjects design with around 7,000 applicants – 150 of whom have been offered a job with the “best amenities” (maximum wage that applicant saw, the ability to work from home, and scheduling flexibility).
From this experiment, the authors learned that the majority of workers do not value scheduling flexibility (setting the total number of hours or setting the schedule for 40 hours per week), but, on average, workers were willing to take an 8% pay cut to work from home (see Fig 4 reproduced from the paper below). Not surprisingly, workers had a strong distaste for the employer discretion job offer: the average worker was willing to take a 20% lower wage to avoid these jobs, and close to 40% of applicants preferred the baseline job even if the employer discretion offered a 25% higher wage. Although these average effects are important, the amount of heterogeneity in valuations was striking and leaves room for further investigation. For more results, consult Figures 2-6 from Mas and Pallais (Forthcoming in the AER, 2017).
As with all field experiments, external validity is a natural concern; do these results only apply to the subsample of applicants observed in the data (people who would apply for a position as a survey administrator), or do they generalize to the population at large? To address this issue, the authors presented numerous supplemental experiments as well as additional empirical work. In particular, to obtain a more nationally representative sample (as opposed to the self-selected sample of phone survey applicants), the authors asked essentially the same questions (this time, completely unincentivized) to participants in the Understanding America Study (UAS) (a nationally representative Internet panel conducted by USC, with around 6,000 total households). The results from this alternative data source were consistent with the field experiment. Since these specific questions are hypothetical, however, the robustness of these results isn’t totally assured; nevertheless, the evidence that more nationally representative samples of workers had similar valuations (as well as a number of robustness checks included in the full paper) increases my confidence in their results.
Finally, the authors do some preliminary exploration of workers’ heterogeneity in WTP for the various arrangements. In particular, using the UAS (where they have more data on covariates), they determine that workers tend to sort into their preferred arrangements (those with the highest WTP for an amenity tend to pay for it), and find that mothers of young children value the ability to work from home twice as much as men.
Overall, this paper provides one of the first in depth analyses of worker’s valuations for different job arrangements. Although some literature exists on this topic, much of it is imprecisely estimated, which makes this field experiment all the more valuable as it presents a novel approach to an old question. Moreover, the authors are very thorough in their work, providing a multitude of robustness checks for each of their major findings. Finally, the nature of the data collection is very rich as it allows readers access to the raw WTP averages, from which a distribution can be estimated. I perceive these to be the major strengths of this paper.
As with all papers, however, there are some shortcomings. The main issue, as I see it, is the incentive structure behind the field experiment: the results would be stronger if the hired applicants received their actual choice between baseline and “treatment” instead of the highest wage and most liberally arranged job. In this way, the authors break from a traditional field experiment, and produce more of what might be called a “survey experiment in the field”. Luckily, the applicants were very unlikely to know the details of the final job offer (the authors offered each successful applicant a job with the “best amenities”), so there is almost certainly no inadvertent impact on the workers’ answers.
I’m also curious why they chose the occupation they did: although perhaps the authors expected lower skilled workers would value the amenities more, I suspect that college graduates might actually be willing to pay much more for these options. It would be interesting to see if that is the case, since it seems (from the supply side) that companies like Google or Facebook offer many of these amenities and flexibilities.
In any case, I am looking forward to learning more about the heterogeneity of valuations for amenities. In particular, I’m curious about the points of excess mass that the authors discovered in the Cumulative Distribution Function of workers’ WTP. Since the CDFs in the figures above represent the proportion of workers who are willing to pay $X or less for the amenity, the large spikes at certain prices are perhaps indicative of some behavioral phenomena. For example, these spikes could potentially represent the price associated with the uncertainty of switching amenities away from the default, the mental cost of making a decision, or a reference point of some sort.
Ultimately, I believe there are many interesting questions to be asked about all of the findings presented in this paper, and expect to see this literature rapidly expand in the coming years.
Valuing Alternative Work Arrangements. American Economic Review. Forthcoming.