Howard Risher is a consultant and writer on federal pay and performance issues. He was the managing consultant for the studies leading to the 1990 Federal Employees Pay Comparability Act and is the author of 'Planning Wage and Salary Programs.' (File)
The latest barrage in the ongoing war to control federal pay is a Wall Street Journal column, “Guess Who Makes More Than Bankers: Their Regulators” by Paul Kupiec, an AEI Resident Scholar. A longer version of the column is on the AEI website. The federal pay data are from the FedSmith database at FedsDataCenter.com .
The column prompts a central question – What is fair pay for federal employees? Surveys show the public will accept salaries in line with the pay of workers in similar jobs in non-federal organizations. That is the basis for planning salaries in the overwhelming majority of employers. To be completely fair, the value of the federal benefits package should be added for a comparative “market analysis”.
But Kupiec’s comparison of ‘regulator’ pay with those in the banking industry is misleading. Yes, banking has executives with mega-pay packages -- It’s hard to feel sorry for Jamie Dimon, who took a 37 percent cut in 2013 to $11.8 million -- but it also employs more than 500,000 tellers who earn on average less than $25,000. The average pay in the industry may be, as Kupiec reported, $49,540, based on Bureau of Labor Statistics data, but it’s a meaningless number. BLS data also shows the 9,700 professional “athletes and sports competitors” earned an average $79,130. Star players are paid like Dimon.
Pay data are only meaningful when compared with others in similar or related jobs. At this point, that’s the basis for managing virtually every pay system except the General Schedule. And columns like Kupiec’s will continue to feed the public’s concern with government pay until credible job-to-job comparative data are compiled.
An educated guess is that over 100 pay surveys are conducted annually across the country. Some data sources are suspect but many are solid and used routinely by employers for salary planning. They are all based on ‘benchmark’ or commonly defined jobs, with the pay data summarized in descriptive statistics – means, percentiles, etc. Those comparisons are easy to understand, even for individuals who have not studied statistics.
Unfortunately government today does not compile the needed data. The annual gap analysis, based on BLS data, is not the answer, for several reasons.
For one, OPM and the Pay Agent refused to use the BLS results for several years after the methodology was changed in the mid-1990s, dropping the use of benchmark survey jobs. It was used only after statistical ‘bandaids’ were developed to address problems. Now it is a Rube Goldberg contraption, not the simple process used by other employers to compare salaries with market levels.
The BLS data are not used as a primary source by any corporation in this country. In the years after the methodology was changed, BLS tried to convince employers to use the data but the effort was unsuccessful.
The cost of producing the BLS survey data is never released but based on the budget it could be as high as $25 million. For comparison, if applicable surveys were purchased from a consulting firm, the cost would be roughly $25,000 (with discounts for participants).
The report of the Pay Agent does not include the information a third party would need to verify the results. The conclusions have never been confirmed with an independent analysis.
In contrast to other surveys, the BLS surveys ‘establishments’ with as few as one employee. Those ‘mom-and-pop’ businesses are not among the employers competing with government for talent. The sample of employers also includes several industries that are arguably irrelevant to government and its labor force, including retail, restaurants, hotels, mining etc.
The BLS survey was not planned to produce data for specific jobs. The focus is on developing a valid workforce sample to support the Employment Cost Index (ECI). The data are not reliable estimates of pay for specific jobs. This absence of job-specific data makes the survey of no value in assessing occupation specific problems like the STEM occupations or new college graduate starting salaries.
Now they are combining data from the National Compensation Survey and Occupational Employee Statistics program. That involves adding a whole new series of statistical equations.
The methodology ignores the most important distinction in market pay. In virtually every city, employers based in the central business district pay higher salaries than in the suburbs, but that is lost in the BLS data.
There have been no signs either side is going to concede. AEI is correct, there are overpaid jobs. But there are also many that are underpaid. Credible market data are needed to sort this out. Federal paychecks need to be fair to employees and to voters.