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Couples in different advanced economies face different opportunity costs when it comes to children, creating different pockets of DINKs across the globe.


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It Pays to Be Transparent

Author: Sam Kuhn
14 Nov 22

Pay transparency laws are transforming the recruitment landscape — but what are the direct effects of including compensation in a job ad?

Pay transparency laws are sweeping the nation – and they’re changing the game of recruiting. No longer do job seekers have to play a salary guessing game – they can feel confident throughout every step of the application process. The benefits for recruiters, however, are less obvious.

Since our recent research on Colorado’s “Equal Pay for Equal Work Act” was published in August, California and New York City have passed similar laws. Some back-of-napkin math indicates that nearly 30 million workers in the U.S. are now entitled to a pay range when applying to a job. That’s almost 20% of the entire labor force! 

At Appcast, we have access to billions of clicks on job ads, which signal interest from job seekers. So we wanted to study a simple question: When compensation information is included in a job title, how does that affect the online job board market? The answer: Across states and industries, including pay in a job title grabs the attention of those looking for jobs and reduces recruiting costs for employers

Analyzing job titles across 2022, we found that including a mention of pay reduced the average cost-per-click (total clicks per job divided by the cost to promote it) by 25%. By September, that difference had reached 35%. Initially, this difference was not nearly as pronounced. Perhaps as pay transparency became the labor market zeitgeist of 2022, job seekers were more inclined to seek out positions with pay included.

When broken down by industry, the difference in cost-per-click becomes even more stark. For education, it’s 53% lower! Healthcare (52%), Warehousing & Logistics (28%), and Manufacturing (36%) all have similarly lower CPCs when including pay information in a job title. 

Geographically, the same trends hold. Across state borders, 49 out of the 50 states all have lower CPCs for titles including pay. Some of the largest differences are in New York, Wisconsin, Oregon, and Maryland. 

To isolate the effect this is having on the entire labor market, we created a model that estimated the difference that including pay had on CPC. We found that including pay in a job title reduced the cost-per-click by $0.67, on average. This is across the entire online job board market in 2022, a stunning result. 

From an economic perspective, this makes near-perfect sense. When employers decide to show their cards and include pay information, they are going to attract more candidates against competition that doesn’t. 

What does this mean for recruiters?

The laws passed in Colorado, California, and other states present a competitive advantage for recruiters outside those locations. It is more than likely that other cities and states will pursue similar policies. Within the next five years, pay transparency could be the norm rather than a novelty. 

When we analyzed the economic impact of Colorado’s law in August we found that it increased the labor force participation rate (compared to Utah’s). Likewise, analyzing our own data, we found that including pay in the job title reduces cost-per-click. Advertising market-rate pay information in a job title is one of the easiest methods to attract new candidates – and gain a competitive edge over other employers. 

Methodology: We analyzed Appcast’s database on job clicks and applications since January 1st, 2022. We defined a job including pay information as including a dollar sign, while excluding the following terms: “Bonus”, “Sign On”, and “Sign-on”. This was done to isolate the effect of including an expected hourly or salaried number. In total, we analyzed 10.8 million jobs, of which 9.3 million jobs did not include pay information and 1.5 million did. The model used to estimate the change in cost-per-click is a multivariate linear model controlling for geographic and industry-specific variables, with a dummy variable indicating whether the title included pay.

Economic Data Analyst

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