Square Payroll Index Methodology
The Square Payroll Index measures compensation of service workers in the retail and food and drink sectors in the United States using data from Square Payroll. Our sample includes more than 200,000 employees working at retail and food and drink establishments that use Square’s platform.
Our methodology is broadly similar to that used by the Federal Reserve Bank of Atlanta’s Wage Growth Tracker, which is based on Daly, Hobijn, and Wiles (2012).
We calculate average hourly earnings by taking the sum of regular wages, overtime wages, and tips divided by the sum of hours an employee worked in a given pay period. Earnings are pre-tax and before other deductions. Base wage only includes regular wages. We restrict our sample to the last payroll run per employee per employer in a given month.
We further restrict our sample by excluding the following:
- Pay stubs that show a regular wage that is below the current federal minimum wage for tip-based workers ($2.13).
- Pay stubs that do not report any hours in the pay period.
- Commissions, or bonuses and other one-time payments.
- Businesses that are not in the retail and food and drink sectors.
We identify sellers in the food and drink and retail sectors using company models that categorize businesses based on onboarding information and processing activity. The overall nationwide index includes a sample of workers from the food and drink and retail sectors. Finally, the national index is constructed after weighting the series to be geographically representative of the United States population. The data are not seasonally adjusted.
To report growth rates, we begin with our constructed wage and hourly earnings data table. We match the wages and hourly earnings of individual-business combinations observed in both the current month and 12 months earlier using anonymized identifiers assigned to employees and businesses when they onboard Square Payroll. We calculate the median of the distribution of 12-month wage and earnings changes for each month and report the 3-month moving average. The series is weighted to be geographically representative of the United States population.
The matched dataset, which is used for the Growth Tracker, likely includes more tenured workers than does the sample of all earners, which is used to report the actual median wages and earnings observed. This is because matching requires earnings in the current year and the previous year, so the sample excludes workers who have less than one-year of experience at that business.
We also report the Square Payroll Index at the metropolitan area level. We assign payrolls to a metropolitan area by matching the employee work location zip code on each pay stub to its currently delineated core-based statistical area as defined by the United States Office of Management and Budget.
We additionally report a Non-Metropolitan index which includes businesses located in a zip code that is not part of a core-based statistical area.
About the Researcher
Ara Kharazian is the Research and Data Lead at Square and the principal researcher and developer of the Square Payroll Index. Prior to joining Square, he was an economic consultant at Cornerstone Research, where he worked on matters in antitrust, consumer pricing, and market manipulation. Ara holds a degree in economics from Tufts University where he received the Eugene Fama Scholarship in Economics. His insights on consumer, labor, and business trends have been cited in the New York Times, Bloomberg, and the Australian Financial Review.