District workers are handsomely paid. The median salary in the District was $64,890 in 2014 or 1.8 times the median U.S. salary. One explanation usually offered for this high pay is the presence of the federal government (see here, and here). Not only does the government pay higher than the private sector in the District, it also supports the kinds of jobs (lobbyists, lawyers, contractors) with compensation packages they would not get anywhere else.
In this post, we show that District workers receive high salaries, not just because the federal government is here, but because District jobs (including administration, lobbying, and professional services) attract people who have skills and abilities highly rewarded anywhere.
We begin with some background: The District’s labor markets survived the great recession rather well. Between 2005 and 2014, the District added 64,880 new workers – a 10 percent increase in total employment. A one percent growth per year may seem meager, but during that period, national employment increased by 4 percent only, so the District did 2.7 times better than the nation.
But equally important is the change in the District’s occupational mix. Managers and professionals (lawyers, doctors, business and finance people, scientists, and engineers) made up 60 percent of the District’s workforce in 2014, up from 53 percent ten years earlier at the expense of sales and office jobs. While a shift towards management and professional jobs is a feature of the national economy, the pace of change is much faster in the District: Management and professional jobs increased by 3 percent in the US compared to 7 percent in the District.
The District has one of the highest concentrations of management, professional and technical jobs in the country. Within the Washington metro area, more of these jobs are in District proper. The share of management, professional and technical jobs in the greater metro area is 47 percent–higher than other metro areas with similar workforce composition. For example, in the Boston-Cambridge-Quincy, MA metropolitan area, the comparable share is 44 percent. In the San Francisco-San Mateo-Redwood City, CA metropolitan area, it is 41 percent.
Here is our question: Can we explain salaries by looking at what people do, without really worrying about where they work or what their job titles might be?
To answer this question, we used detailed occupational data from the Department of Labor and borrowed from the work of two economists. The U.S. Department of Labor’s O*NET program, the nation’s primary source of occupational information, collects data on each occupation including information across 35 different skills (including things like programming, active listening, and persuasion), 52 different abilities (for example, arm-hand steadiness, stamina, or originality), 42 tasks (collecting information, staffing, inspecting equipment, structures, or material) and 57 work contexts (for example, contact with others, frequency of decision making, time pressure). O*NET scores each occupation along each of these dimensions on a scale of 1 to 5 based on peer evaluations. This gives us 186 different scores for each occupation. Acemoglu and Autor further group these different skills, abilities, and tasks into three broad areas: abstract, routine, and manual (they have further subgroups, but to keep things simple, we used these three). Their methodology yields scores for abstract, routine, and manual dimensions of each occupation.
Abstract tasks and skills include things like data analysis, creative thinking, interpreting data for others, coaching, guiding, etc. Lawyers, teachers, physicians and managers–occupations that constitute the largest source of jobs in the district–score high on the abstract dimension. Occupations that score the highest in routine tasks (structured and repetitive work that relies on accuracy) include meter readers, bookkeepers, and cashiers—the office and retail workers, who are losing ground in our city. Finally, manual skills include operating machinery, or work that involves hands or body, so you will find in this group lots of construction and manufacturing workers—types of occupations that are relatively rare in the District.
To be clear, the scores do not necessarily reflect the skills of persons holding those jobs. Herman Melville worked as a customs inspector, and Einstein logged hours in the patent office. A parking attendant might be very good at math puzzles and could spend his weekend designing dungeons and dragons games. But he would not use these skills in his daily job.
You can click on this link to explore scores for occupations we find in the District.
Here are the same scores, this time grouped by broad occupation groups. Each dot represents an occupation and the gray lines give the median score for that broad group in each area. Management and professional occupations—the greatest source of employment in the District, score highest on abstract tasks (the median score is 5.4) and lowest on manual tasks. Many occupations have a routine element and most occupations demand little in terms of physical labor (the exception is construction and repair jobs). You can click on the image to see the details.
So how do these scores explain the median wages in the city? It turns out that salaries and abstract task skills are strongly correlated. A one point increase in abstract task scores increase median salary by $8,230. This is 13 percent of median salary paid in the District. The manual task scores, on the other hand, are negatively correlated with pay. Median salaries across different occupations decline by $3,000 per one unit increase in manual task scores, but notice from the graph that the variation in manual scores is smaller across occupations (and the relation is not as strong, you can see here). Routine tasks scores cannot explain salary differentials at all.
Is this strong relationship between abstract skills and abilities and wages unique to the District? It turns out, not. We find a similarly strong relationship between abstract tasks and skills and salaries in other jurisdictions. To compare, we provide the same information for Boston, San Francisco and Honolulu. Boston and San Francisco are relatively similar to the District in their labor composition, with a large concentration in management and professional occupations. Honolulu is different, with a larger concentration in service occupations. In all these locations, abstract skills are the most important determinants of pay.
When we think of incomes, we generally think of who we work for and what we do, but we can also think in terms of skills and competencies. Within every broad occupation group, incomes generally increase as one takes on more tasks that require abstract skills such as data analysis, problem solving and interpreting information. This matters, both at a personal level, as we choose to invest in our own or our children’s education, at for the entire city, as we consider workforce development options for many who have a hard time finding a job.
What exactly is this Data?
Occupation and wage data are from the U.S. Department of Labor’s May 2014 estimates. Description of O*NET’s occupation scoring is here. The data for the Acemoglu and Autor paper is available for download here. Here is where they explain how they construct the task measures.
The data we used for this post can be downloaded here.