Gender pay gap among the District’s workforce

The gender pay gap refers to the systematically lower wages women receive relative to men with similar talents and responsibilities.  A White House study tells us that the median wage for women equaled only 77 percent of the median wage for men across the nation–a pay gap of 23 percent. The pay gap exists between men and women with similar degrees, similar work experiences, and similar occupations.  The study mentions various factors that create this gap: family responsibilities such as child rearing generally fall on the women; or men tend to negotiate and seek promotions more aggressively.

But explanations offered for the gender pay gap, more often than not, do not settle the matter; rather they lead to new debates. Economists from the Federal Reserve Bank of St. Louis, for example, point out that broad comparisons are not appropriate for gender gap analysis and one must take into consideration differences in attainment, experience, and occupational choice as well as the intensity with which someone works. They argue that when one accounts for these differences the pay gap between men and women declines to five percent. There are even disagreements of the effects of childbirth: some argue that high-skilled women experience a smaller wage effect from taking time off for childbirth because of the demand on their skills, whereas others argue that the declining the declining birth rate among high-skilled, highly-paid women is evidence that childbirth hurts long-term wages.

We became curious: How about the District’s workforce? In this city with many workers on government pay schedules, do we have a gender pay gap that is significant? How does the gap change with age, marriage, education level, hours worked, or occupation? We looked at the annual wage and salary earnings of men and women.  (In this study, we use average wages, and not the median. The median salary is useful when data has very extreme values. But we are relying on American Community Survey for data, which already caps incomes and therefore throws out extreme values. Even then, the pay gap to some extent reflects the dominance of men among very highly paid workers. For example, among those who receive wage or salary income of $500,000 or more, men outnumber women by more than 3 to 1.) Here is what we found:

Overall gender pay gap

2014 data from the American Community Survey tells us, in that year, women made up 48 percent of the workforce (the nationwide share is 47 percent) and received only 42 percent of the wages. The average salary for women over the age of 21 in 2014 was $71,000 and for men it was $90,000. That is, women’s annual wage and salary earnings were 78 percent of men’s; putting the District’s gender pay gap at 22 percent compared to the national gap of 23 percent.

Gap by type of employer

The pay gap is greatest among workers of the private entities. Among for-profit firms, women, on average, receive 76 percent of the average wages paid to men; among non-profit firms, the comparable number is 77 percent. It appears that the government sector has a smaller pay gap, with a 16 percent gap among state and local government employees (largely D.C. government but also employees at charter schools, UDC, and other local entities); and the gap is 15 percent among federal government workers.

Has the gap been closing over time? To see this we look at the wage differentials among older and younger cohorts of workers. The gap generally widens by age across all four types of employers. For example, among for profit firms, the pay gap is only 7 percent for workers between the ages of 25 and 34; among the workers of non-profit firms, we don’t see a gap at all. However even when the gap is small at this age group, it does not tell us definitively that the gap will continue to be smaller when this cohort ages. This is because a small gap can widen over time even if the two groups received the same percentage increase in their wages. Viewed from this angle, it appears like the government sector, especially the federal government, has promotion practices that are most gender-blind, as the gap does not widen as quickly across cohorts.


How about education? The data suggest that in the private sector, having a college degree (or higher) does not necessarily close the pay gap.  This is significant, but is still not a definitive indicator of gender-dependent pay or discrimination. For example, if more men study STEM and gets jobs in science and technology fields, and more women study social sciences or humanities that feed into lower paying jobs, then a pay gap will exist for given degree in education. Data do tell us that 70 percent of STEM degrees awarded at universities and colleges indeed go to men.  This we can also see at the doctoral level: even though more women receive doctoral degrees than men in a given year, women are extremely underrepresented in STEM fields; they are also less likely to get a degree in physical sciences and business programs, which tend to lead to higher paying jobs.  But, even with professional degrees (doctors and lawyers) there is a significant gap of 25 percent between men and women.

Finally, for DC residents who make up a third of the District’s workforce, the gender gap is smallest at the federal government and private, for-profit firms, and widest among DC residents employed in a state or local government job.

Is there a marriage toll for women?

Among men and women who have never been married, the gender pay gap is only 6 percent. Among men and women who are married, the gender gap is 23 percent. A single woman (whether married or divorced) between the ages of 45 and 54 makes more than a single man in the same age group. A married woman of the same age group makes 23 percent less than married man in the same age group. Why could this be? Perhaps married women in this group work fewer hours, or they took time off to raise children, or took more flexible but lower paying jobs. In fact, the gap is much smaller among married women under the age of 34 (and presumably without children).  We can think of many other possible contributors: married men are happier, and perhaps for this reason more productive. (They make more than unmarried men as well: see here and here). Because their wives take over responsibilities at home, perhaps married men can dedicate more time to their work. Perhaps there are evolutionary reasons: men who have not been picked for a marriage by the age of 45 are just low in productivity. Perhaps it is selection bias in the other direction: women who are aggressive about their careers do not get (or stay) married. Perhaps employers low-ball the salaries of married women expecting that they would take more time off at some point in their career and perhaps just leave. Again, we do not have definitive answers.


Work hours

Gender pay gap is a feature of full time work.

When we look at men and women who work fewer than 30 hours, we see more women than men, and their wage and salary earnings are generally greater than men’s. But the size of District’s part time workforce is small—it stands at less than 10 percent of the total workforce in the District. Among those who report working 30 to 40 hours a week, the gender pay gap is 11 percent (464,000 workers report working 30 to 40 hours and half of them are women.)  Among those who report working over 40 hours (approximately 250,000 workers, 41 percent of whom are women) the gender pay gap is 21 percent.

This is a perfect example of how the same information can support exactly opposing policy solutions. One can look at the gap and see the need for interventions; others can look at it and conclude that the labor market can create many types of jobs that require different combinations of effort and wage that fit the needs, abilities or desires of all kinds of different workers. If that is the case, interventionist policies would actually reduce employment and hurt women more.


Industry and occupations

Dominance of women in a given industry does not guarantee a better pay.  For example, 70 percent of workers in the health care industry are women.  This includes not just people with medical occupations such as doctors and nurses, but also all other types of workers from managers to computer programmers who work for a healthcare company. In this industry, the gender pay gap is 36 percent. Women in construction—a male dominated industry—make more than men but this is because they are more likely to hold managerial or creative jobs, rather than working on the construction site.


So perhaps we should compare men and women doing the same job. Cutting and slicing the data gets precarious when we go down to individual occupation level, but we looked at occupations with more than 2500 men and 2500 women, and found only a handful of occupations where the pay gap is small or favor women. Physicians and surgeons in the District face a gender pay gap that is as wide as the healthcare industry: 37 percent! Looking at the lawyers—the gap is 73 percent. We can string together more explanations: more women go in-house (lower pay) or most women lawyers are younger.  But some other outcomes are puzzling: 63 percent of education sector employees are women; the industry gender pay gap is 23 percent. Among elementary and middle school teachers only (we are excluding administrators, and we don’t know if they are public charter school,  DCPS or private school teachers), the gap is 20 percent. Why?  What explains the gap for cashiers among whom women receive only 63 percent of what men earn? How about waiters and waitresses where the gap is 11 percent? Do they get fewer hours of work or does gender, ethnicity, or other characteristics–of the wait staff or the customers–play a role in how we tip waiters and waitresses?


Survey data could be idiosyncratic, especially given the small size of the District’s sample (but in this case we are using data from three states). Still the pay gap is there, even when one controls for age, marital status, or even down to occupation. Is this a sign of flexibility in the labor market? If all jobs required 40 hours a week (no more, no less), had the same degree of flexibility (or inflexibility) would the labor market outcomes be better for women? Or do firms knowingly take advantage of lower reservation wages for women? If so, why do women accept lower salaries when everything tells them to negotiate? There has been research that says women can be penalized for negotiating if they negotiate like men, suggesting that gender roles continue to play a role in the workplace.

We wonder what our readers think.

What exactly is this data? We use the American Community Survey micro data for 2014. We combine District of Columbia, Maryland, and Virginia data for respondents who report working in the District. Wage and salary income is what respondents report earning in a year.


Abstract abilities and skills are the best predictors of high wages in the District

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.

image012image003The 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.

image029When 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.

District’s labor market and workforce are intertwined with Maryland and Virginia

In 2014, nearly 774,000 workers reported working in the District of Columbia and they collectively earned $63.5 billion in wages and salaries. Of these workers, only 251,000 or 32 percent were District residents. The remainder were commuters from Virginia or Maryland, accounting for 68 percent of people employed in our city. The District’s share in total wages earned was even lower: District residents accounted for $18 billion of salaries and wages earned in the District. This is about 28 percent of all wages and salaries earned in the city.

Wage and Salary.jpg

In addition 89,000 District residents reverse-commuted to Virginia and Maryland, mostly working for private entities (76 percent including non-profits) and the federal government. This group collectively earned $6 billion in wages, compared to the $45 billion Maryland and Virginia commuters earned in the District.

Reverse commuters.jpg

The data reveal other trends. District residents who work in the District hold a disproportionate share of the lower-paying jobs: 44 percent of jobs that pay a wage of $30K or less are held by DC residents, compared to 32 percent of all jobs in the District. Virginia residents, on the other hand, tend to hold a larger proportion of higher paying jobs: 28 percent of jobs in the District and nearly 40 percent of all jobs that pay $100K or more.


The data also show that District residents dominate employment in the non-profit sector, one of the lowest paying sectors in the District.  Commuters from Virginia and Maryland, on the other hand, typically come to the District to work in the private sector and the federal government.


District’s labor market and workforce are tied deeply with those of Maryland and Virginia. If salaries are any indicators, the most educated and productive residents of our neighboring jurisdictions work in the District. In 2014, District residents who worked in the District reported wage earnings of $63,700 compared to $69,400 for commuters from Maryland, and nearly $95,000 for commuters from Virginia. But even within the same sector, District resident’s wages could be low: In the non-profit sector, District residents earned, on average, $68,500 in wages—13 percent less than Maryland workers and 20 percent less than VA workers.


Here are the data, in greater detail, for you to explore:

Resident employment and workforce.jpg

What exactly is this data?

The data is from the single-years PUMS release from American Community Survey for 2014. The analysis was done in SAS, and SAS files are available from the author.

Little evidence of the gig economy in the District

Much has been written about those who work in the “gig economy” (see here, and here), and those of us who try to count them. The term itself, however, is hard to define. Some think of the gig economy as work contingent on demand. Others include an element of technology that connects workers with potential sources of income.

A recent Government Accountability Office study offers various definitions, the narrowest of which produces an estimate of 7.9 percent of the workforce in the gig sector in 2010. But this group includes temps, on-call workers, and contractors: jobs that have been around forever.  Senator Mark Warner, in his recent op-ed at the Washington Post, cites that study (although the Post inadvertently links to a different report from 2000) to conclude that one-third of the U.S. labor force could be in the gig sector, and that these gig-workers “now find themselves piecing together two, three or more on-demand work opportunities to make a living” [emphasis added]. While it is true that the broadest of the GAO definitions produces an estimate of 40 percent of the workforce gigging, there is nothing new about these work arrangements GAO includes in the broad definition: independent contractors, self-employed individuals, and even part-time workers.  These work arrangements existed long before Uber opened for business.

There are good reasons to try to get a better handle on the gig economy. In the gig sector, the types of risks we typically think of as business risk—e.g., lack of customers because of bad weather, sick workers—become the worker’s problem. To be sure, even before the gig revolution, some sectors of the economy worked just like that. Cab drivers, for instance, never had much in the way of benefits such as healthcare, a pension, paid holidays or even sick days. It is no surprise that much of the gig work is beginning in sectors where workers, such as drivers, handymen, and baby-sitters, already took large risks.

The evidence that piecemeal work is replacing traditional employment in the United States is scant.  So we wondered: how about the District?  We ran into the same definitional problems about the gig economy when looking at the District’s data, but we decided to focus on the self-employed, specifically, those who characterize themselves as “self-employed in an unincorporated business they own.” For laymen, those are the people who pick up contract work, get a 1099 from the IRS at the end of the year, and pay self-employment taxes. The Bureau of Labor Statistics and the U.S. Census differentiate between the 1099’ers and self-employed who actually own a business that receives the monies for the services rendered, and in return pays a salary to the business owner, with proper deductions for social security and Medicaid. (This Pew piece on the characteristics of the self-employed provides a much more detailed explanation of the term).

We first look at the number of District taxpayers who have paid self-employment taxes. The data show that the total number of people who pay self-employment taxes has increased in the District from 35,000 in 2006 to nearly 49,000 in 2014. This is a very steep increase (36 percent overall and nearly 4.5 percent annualized) even when compared to the relatively rapid increase in the District’s population and tax filers (tax filers grew at about 2 percent per year during the same period).  But data show that the rapid increase in the number of filers who paid self-employment taxes occurred before 2010. In fact, since 2010, the share of tax filers who pay self-employment taxes has been stable at about 14 percent.


So why did the District see such a rapid expansion in reported self-employment? This, we suspect, has less to do with changes in the underlying economy and more to do with changes in tax policy. Beginning in 2002, the District started offering Earned Income Tax Credits, first at 10 percent of the federal credit, and by 2009, at 40 percent of the federal credit (one of the most generous such programs in the nation).  The credit targets low income families and single parents with children, and the key recipients of this benefit are those who file as head of households.

Since the policy changes began, both the number and the share of heads of households who pay self-employment taxes has increased.  In 2006, only 7 percent of filers who paid self-employment taxes were heads of households.  In 2010—one year after the benefits maxed at 40 percent of federal credit—this share doubled to 14 percent, and then reached 17 percent in 2012. During the same period, there were no significant changes in the share of singles or married filers who reported self-employment income.


One might say that tax data is not the best measure of the gig economy because it captures all taxpayers who pay self-employment income. In the District, for instance, a government employee who teaches a class at a college, or a professor who writes a paper for a non-profit, would all receive a 1099 and pay self-employment taxes. So the data are noisy, mixing moonlighters with the gig-workers.

So let’s turn to the American Community Survey, which inquires about the employment status of workers. Here we present data on District residents who characterize themselves as self-employed. And, surprisingly enough, we see a decline, both in levels and in shares.  In 2014, only 13,100 residents—2.4 percent of District residents older than 16—claimed to be mainly self-employed, down from the post-recession peak of nearly 18,000 self-employed residents (or 3.4 percent of those over the age of 16).  Self-employed persons increased slightly in the District during the recession, but since 2012—the time when resident employment really began to increase—self-employment has gone down.


In 2014, the self-employed in the District made up about 5 percent of total resident employment.  This figure has been relatively stable, except for 2012. Self-employment income has likewise been rather stable at 3 percent of personal income. District residents who are self-employed routinely generate about 70 percent of their income from their self-employment work.


Incidentally, the District’s self-employed residents—just like its employed residents—are better educated than those elsewhere in the United States. Nearly 60 percent of District’s self-employed have a graduate or a professional degree (compared to only 13 percent across the United States), and fewer than one in five completed schooling only up to high school (compared to 36 percent in the country as a whole).


Is it possible that the data are not capturing the gig economy? We can think of two reasons—one relatively unique to the District, and the other more general.

  1. It is possible that the District’s gig workers—the Uber drivers, the Amazon flex folks, the Taskrabbits—are not District residents, just like the many District workers who receive minimum wage do not live in the District.
  2. It is possible that some workers do not fully report their income because they do not realize that they must report earnings from Etsy, Sittercity, or airbnb.

It matters to us to measure the gig economy correctly because we need to be able to track the changes in the District’s economy and understand how work activities connect to incomes. We plan to dig a bit deeper, looking at who might be the gig workers in the District and what types of jobs they hold.

What exactly is this data? 

Data on the number of people paying self-employment taxes in the District by tax filer type is from the IRS (2013 data set is now public). Data on class of worker are from various years of ACS. DC data on self-employment has error terms of +/- 0.5 percent to +/- 0.7 percent depending on the year (or about 2,000 workers).

DC ’s post-recession surge in private sector employment is showing signs of slowing down

According to the US Bureau of Labor Statistics, the District of Columbia’s private sector employed 526,533 wage and salaried workers in June 2015 (averaged over three months). This June level was 7,267 (1.4%) above that of the prior year, a positive indicator of continued growth in the District’s economy.

The June employment level may also be a sign that the rapid increase in D.C.’s private sector employment that has occurred since the end of the US recession is slowing down. June was the second-slowest year-over-year increase since January 2011 (the other was 6,500 in September 2014). DC’s private sector job growth in June was about at the level that occurred before the recession’s onset, and was slightly under the average annual growth for the past decade (7,707).


Weaknesses in DC’s private sector are not economy-wide. Indeed, four of the District’s major sectors, ones that account for over half of all private sector jobs (professional services, business services, health, and organizations), added 9,067 jobs from June 2014 to June 2015, more than twice as much as in the previous year. The weakness came primarily from six sectors that together account for a little more than one-third of all private jobs: education, food services, accommodations, retail, information, and finance. Those sectors grew by about 6,600 from 2013 to 2014, but they fell by 1,900 in 2015.image004

What exactly is this data? The data is from the Bureau of Labor Statistics’ monthly data release on employment by industry area. All numbers are three-month moving averages of seasonally unadjusted data. This means the numbers for June of 2015 is the average of the monthly employment figures for April, May, and June.

The federal government is a stabilizing factor in the District’s economy, but its role is getting smaller

In March of 2015, for the first time since September 2011, the number of federal civilian employees working in the District showed an increase. If this is the end of a three year contraction in the federal employment, it is a modest one: the net increase was only 1,100 or 0.6 percent over the first quarter of 2014.

Looking back, fluctuations in federal jobs have been associated with major developments in the District’s economy. For example, federal cutbacks contributed to the conditions surrounding the establishment of the DC Control Board in 1995. More federal jobs helped the city cope with the aftermath of the 9/11 attacks and the Great Recession that began at the end of 2007. The recent loss of federal jobs appears, however, to have had only a moderate impact on the District’s economy, as total employment in DC rose by 33,634 over that period.image002

Three reasons help to explain DC’s economic resilience in spite of declining federal employment:

First, District’s private sector is growing in strength and diversity. Over the last 25 years, there has been a shift in DC’s labor market toward the private sector, a shift stronger in jobs than in earnings. From 1990 to 2015, DC lost 22,165 federal jobs (a 10.1 percent decline) while the private sector added 115,000 (a 28.3 percent gain). Adjusted for inflation, over that time federal wages and salaries grew 31.6 percent while the private sector wage and salaries grew 70.6percent, more than twice as fast. image004Looking back even further, to the period of federal cutbacks in the 1990s, we see an even more dramatic shift: From the second quarter of 1993 to the second quarter of 1999, DC lost 50,134 federal jobs, but the private sector gains during the same period offset only a third of this loss with a gain of 18,000 jobs. From 2011.3 to 2014.4, by contrast, the 49,200 gain in private sector jobs was about 3 times greater than the 16,166 federal jobs that were lost. About one-third of the new private sector jobs occurred in education, but increases occurred in a number of other sectors as well.

One thing to watch out is the difference in federal and private sector wages. Most private sector jobs that replace federal jobs pay much less, and if this trend continues, it will have implications on the type of workers and residents the District attracts.

Second, forces currently driving DC’s economy are less dependent on net growth of jobs located in DC. Starting in 2006, the year before the onset of the Great Recession, DC’s population started to increase, and from 2009 to 2014 it increased by 66,665 (11.3 percent). This increased attraction of the District of Columbia as a place to live has affected the economy in a number of ways, and the one most relevant here is that resident employment has been increasing more rapidly than the number of jobs located in DC.image006image008

This can occur for several reasons: more residents working outside of DC, more residents holding higher paying jobs, residents taking jobs of commuters who retire or otherwise leave, or residents working for themselves or as independent contractors.

Third, federal contracting possibly fuels some of the strength in the District’s private sector. In recent years, federal government expenditures for non-defense programs have shifted toward greater reliance on purchases of goods and services rather than compensation of employees. The change was particularly great starting around 2000; from 2000 to 2014, federal purchases went up 153 percent, compensation by 91 percent. The increase in purchases of services was particularly strong, tripling between 2000 and 2010 before tailing off a bit. Data on such purchases from DC’s private sector are not available, but a pattern here similar to the national one would help to explain some of the rapid growth of professional and technical services in DC. Agencies are more likely to contract with businesses or professionals in close proximity. Indeed, employment in professional and technical services increased 54 from the first quarter of 2000 to the last quarter of 2014—this is almost double the 28.4 percent pace for employment growth in all of DC’s private sector.image010

The recent decline in federal employment may not have upended the District’s economy, but the federal sector remains a vital component of the District’s economy. Federal spending accounts for 26.1 percent of all jobs in DC, 31.1 percent of all wages, and is a source of contracts for DC’s private sector. What happens with federal spending will therefore have considerable influence on the future growth in DC’s economy. If federal spending remains flat or declines, the rate of growth in employment and earnings generated by the District’s economy will depend on how the private sector performs. DC growth rates then could approach or surpass the US only if DC’s private sector outperforms the nation as a whole. For most of the past 3 1/2 years, DC’s private sector employment actually grew faster than the US average, but it has been below it for the past three quarters. Wage and salary growth in DC has been about the same as the US average.

Increases in federal employment and earnings were important for DC’s economy in recovering from the recession in 1990, the 9/11 attacks and recession in 2001, and, of course, the Great Recession from 2007 to 2011.3. Thus, the federal government’s stabilizing role will likely remain important for the District’s economy in the coming years.

You can find more on this topic in our most recent Monthly Economic and Revenue trends report.

 What exactly is this data? Employment data is from Bureau of Labor Statistics, and wage data is from the Bureau of Economic Analysis. Totals for jobs and wages include state and local government. DC resident wages and salaries estimated by the Office of Revenue Analysis, assuming wage and salary supplements are the same % for DC resident wages as for wages earned in DC. Detail may not add due to rounding. Government consumption data is from NIPA Table 3.10.5. Government Consumption Expenditures and General Government Gross, also from the Bureau of Economic Analysis, last revised on April 29, 2015.

What is happening to middle-wage jobs in the District?

Middle-wage jobs lost a lot of ground during the great recession, but they are making a comeback across the nation.  Yet high-wage and low-wage jobs are growing faster than the middle-wage jobs, suggesting that over time, the job market will be more polarized.

Is the job market in the District becoming more polarized?  To see this, we looked at employment and wage data by occupation for years 2005 through 2014 (BLS just released the 2014 data on March 25).  We then grouped the data by wage level (low, middle, or high).  Middle-wage occupations have median salaries that fall within the 25th and 75th percentiles of the annual wages paid in the District.  We define occupations with median wages below the 25th percentile as low-wage, and occupations with median wages above the 75th percentile as high-wage.

This grouping exercise reveals interesting things about our city. First, a low-wage job in the District pays a lot (but might not buy much): In 2014, the District’s 25th percentile of the annual wages, at $37,440, was greater than the U.S. median wage of $35,540.


Second, middle-wage jobs–the bulk of positions in professional and business service areas, health, and education–have grown through the recession, but they are no longer the engine of District’s economy.  These jobs never went away, but their growth declined with the recession, and never really boomed.  Occupations that pay low-wages—these include positions in retail, food services, grounds maintenance, and personal services—have more than recovered from the losses during the recession.  These jobs have been the biggest source of increase in employment since the official end of the recession.  Between 2011 and 2014, the District added about 21,000 low-wage jobs, easily reversing the loss of 7,500 jobs in this category during the recession.  Finally, high-paying jobs increased rapidly during the recession, first due to federal hiringand then with population growth, but the growth in these occupations have also slowed down.


The composition of middle-wage occupations could change over time.  Middle-wage occupations are changing either because these occupations are no longer needed in the District economy, or because these jobs are no longer middle-wage.  Between 2013 and 2014, middle-wage jobs declined by 9,700, partly because there were fewer accountants, property, real estate, and community association managers, fundraisers, counselors, and legal secretaries.  Another part of the decline was that some occupations typically considered to pay middle-level wages transitioned into low-level wage occupations. For example, office and administrative support workers (about 2000 of them in the District) made the permanent transition to low-wage workers around 2012.  Of course, some office and administrative support workers still get paid a middle-level wage, but if one were to look for a job in this occupation, chances are his or her salary would be less than $37,400.

The interactive graphs show the number of jobs paying middle-wages and the number of occupations that could be considered middle-wage under each major occupation category.


What exactly is this data? We used BLS Occupation Employment Statistics to construct a series of low-, middle-, and high-wage occupations.  Low-wage occupations are defined as occupations with annual median salaries below the 25th percentile of wages for the entire city in the same year.  High-wage occupations are defined as occupations with annual median salaries above the 75th percentile.  Middle-wage occupations lie in between.