The number of occupied apartment units in DC increased sharply last year

The increase tops the peaks of previous years

According to CoStar, a leading commercial real estate information firm, there were an estimated 174,917 occupied units in all classes of market rate apartment building in September 2017, an increase of 5,433 over the prior year. This was the largest one year gain since 2001, the period covered by the data base. The 5,433 one-year gain exceeded the annual gains that occurred before the Great Recession and following the relaxation of sequestration restraints.

graph 1

In 2005 DC’s population started to increase, with the city adding 125,000 residents by 2017, a 22% increase. Not surprisingly, this growth had an impact on the market for apartments. From 2005 to 2017.3 the net inventory of units increased by 35,615. This increase in supply was almost matched by growing demand as occupancy grew by 33,443. The overall vacancy rate rose only slightly—from 4.6% in 2005 to 5.1% in 2017.3.

The balancing by market forces of inventory and demand evident over the past decade is consistent with the modest decrease in the construction of new units that has occurred recently. In September there were 13,022 new units under construction, a decrease of 630 from a year earlier and of 1,687 from the peak pace of 14,709 in March 2017. While occupied units rose sharply over  the past year, inventory grew even more: a 6,727 net increase in inventory versus the 5,443 increase in occupied units. The vacancy rate in 2017.3 for all units also rose somewhat—to 5.1% from 4.7% a year earlier.

As noted in the accompanying chart, new construction began to accelerate in 2010. With some ups and downs, this was soon followed by annual increases in net inventory and in occupied units that have carried to the present time. Most of this activity involved Class A apartments. In the 7 years from 2010.3 to 2017.3, 88% of the net increase in apartment units and 84% of the increase in occupied units were accounted for by152 new Class A buildings. (Class A buildings are new or newly renovated, well located, generally larger buildings with higher rents.)   An increase of 69 Class B buildings accounted for about 15 % of the gains in inventory and occupancy. The number Class C buildings, representing about 38% of the District’s inventory of market rate units, declined over this time. Vacancy rates rose for Class A buildings, which require long lease-up periods, and fell for both Class B and Class C units.


graph 2

table 1

From 2009 to 2012, the three years in which DC experienced the largest annual increases in population over the past decade, the total increase in occupied apartment units for the three years was 4,987 (see the shaded area in the table below). This was less than the increased occupancy that occurred in the last 12 months. This suggests there have been some changes in the connections between a growing population and the city’s housing stock over the past 10 years or so. In the middle part of the decade of the 2000’s, more of the increase in population may have been accommodated by group homes or taking in roommates, by changes to single family or other smaller structures, or by owner-occupied units. Census Bureau estimates of DC’s population in 2017 will not be available until December, so comparison of population and housing unit changes over the past year is not yet possible. The ways in which the District and the owners of its housing stock adapt to changing demographics and housing patterns will no doubt continue to be an area of great interest.

table 2

table 3

About the data. The information is from CoStar’s historical data bases of market rate apartments which goes from the first quarter of 2000 to the third quarter of 2017.  The data includes the total for all apartment buildings as well as for buildings classified as Classes A, B, or C. CoStar Group, Inc. is an American commercial real estate information and marketing provider with headquarters in Washington, DC. Information in the CoStar data base is undated on a continuous basis.

The information here was included in the District of Columbia Economic and Revenue Trends report for October 2017, which was issued by the Office of Revenue Analysis of the Office of the Chief Financial Officer of the Government of the District of Columbia.


The Effect of Self-Employment on Personal Income Growth: Washington DC 2006-2014


The United States’ labor force has experienced great stresses and seen continuous change over the past decade. The recovery from the Great Recession and progressive technological change have combined to reshape how many workers participate in the labor market, the skills and attributes they possess, and their market compensation. As debates about the future of work in the United States swirl, a study by the Office of Revenue Analysis (ORA) looks at the characteristics of the self-employed and implications on their incomes after entering into self-employment.

The Self-Employed Population in DC

This study, which will be presented at the American Economic Association Annual Meeting in January 2018, looks at the self-employed population of DC, defined as people who actively work for money outside of the traditional employer-employee relationship. In order to identify the people who are actively self-employed on at least a part time basis, we use both Federal and DC individual income tax data to identify DC tax filers who meet at least one of these conditions below:

Fig 1_Corey

This identification process finds that the self-employed are about a fifth of all tax filers (between 45,000 and 56,000 tax filers in each of the years studied) in the District. They are spread relatively evenly across the eight wards of Washington, DC, are a bit younger than the overall tax-paying population, and are more likely to be married than the average DC tax filer.

The proportion of the population that is self-employed is also remarkably stable across time. The vast majority of the population is identified by one of the first three indicators shown in Figure 1, and fewer than a thousand in each year are identified solely because they take one of the smaller deductions. Roughly 75% are identified by more than one of the listed indicators.

Fig 2_Corey

A Look at Incomes

Compared to the overall distribution of DC tax filers, the self-employed subset is bi-modal. The figure below divides up the self-employed population into where they fall in the income percentiles for the entire District. There are 50 bars in this distribution, each representing two percentiles of income. All bars sum to 100 percent.
If the self-employed were evenly spread across the population, every bar would be at two percent, but we can see that the self-employed converge around the 11th and 99th percentiles in District income.

Fig 3_Corey

The self-employed population of DC has a higher mean income than DC as a whole. This helps it account for a larger percentage of the District’s total income than its percentage of the population as shown in Figure 2. At the lower income percentiles (i.e. bottom 25% and lower), the self-employed are generally less well off than the same percentiles for the rest of the population. The self-employed individuals at higher income percentiles (i.e. top 25% and higher) are much wealthier than the rest of the population at those same higher percentiles. Median incomes, however, between self-employed and non-self-employed residents are much more similar.  The impact of the recession is also more evident among the self-employed than among the rest of the population. Mean self-employed incomes fell each year from 2007 to 2010 and median income fell from 2008-2011, while the recession is not evident at all in the trend lines for the rest of the District’s taxpayers’ earnings. This is shown in Figure 4 below.

Fig 4_Corey

Some Determinants of Self-Employment

Using linear and logistic regression models (modeling approach to explain the relationship between a dependent variable and one or more explanatory variables), we examined four different time periods: 2006-2008; 2008-2010; 2010-2012; and 2012-2014 to identify possible determinants of self-employment and how they may have changed through the Great Recession and recovery. During the first year of each time period (i.e. 2006), the tax filer was not self-employed. In the second year of the time period (i.e. 2007) the tax filer met the criteria shown in Table 1 and was considered self-employed. The results compare the tax filer in the final year of the time period (i.e. 2008) to the first year in the period (i.e. 2006), prior to when the filer became self-employed.

We find that on average a wage drop in the first year of each time period is correlated with a roughly 5% increase in likelihood of becoming self-employed in the following year. This effect is greatest in the most financially troubled years from 2008-2012. During that time, the odds of becoming self-employed were twice as great among those who experienced a large wage and salary drop compared to those who did not. Interestingly, taking the mortgage interest deduction is as strongly correlated with becoming self-employed as experiencing a wage and salary drop.

Younger age is also correlated with becoming self-employed. The regression model implies that for every additional ten years of age, an individual is about 1% less likely to become self-employed in a given year.

Surprisingly, a filer’s level of total income had very little effect on their likelihood of becoming self-employed during our study periods. This indicates that self-employment is a phenomena that both high and low income individuals self-select into. This again speaks to the bi-modal distribution of the self-employed population as shown in Figure 3.

What Happens to Income After Becoming Self Employed?

Income gains do occur for those who become self-employed, but it seems that the gains are concentrated amongst those tax filers who were already in the top end of the income distribution prior to becoming self-employed. The rest of the self-employed population experienced an average decline in income after becoming self-employed in all study periods.

Those who became self-employed before the financial crisis and in the 2012-2014 period afterward experienced an increase in income. However, these income gains are confined to the top 10 percent of income earners in all periods. The gains that upper decile earners can expect from becoming self-employed are quite large, ranging from $14,000 to $50,000 depending on the time period. Conversely, becoming self-employed if you are in the lower 75% of the income distribution, led to short term losses ranging from $1,700 to $3,500 in the third year of each time period studied.

Some Takeaways on Self-Employment

Self-employment is a common phenomenon in the District, as over 20% of all tax filers in a given year can be classified as self-employed (on at least a part-time basis). We see that from 2006-2014, the number of self-employed residents has grown in line with the overall population growth in the city. We find that the self-employed subset of the population has a bi-modal income distribution and that the average newly self-employed individual is likely to experience net income decreases unless they are in the higher end of the income distribution prior to taking on self-employment.

One possible factor that explains this phenomenon of the income losses of those who switch to self-employment is that income gains may not be their ultimate goal. Being self-employed for many people may be a lifestyle decision that they make for greater flexibility, the pursuit of entrepreneurial endeavors reasons, or family obligations, among others, and not solely to earn more income. Indeed, a growing number of DC residents appear to be substituting slightly higher incomes to experience more work and lifestyle freedoms.

What exactly is this data?

I used administrative individual income tax records from the IRS and the DC Office of Revenue Analysis to identify self-employed DC residents in the years 2006-2014. Due to data limitations, however, our identification methodology cannot distinguish between an independent contractor, a small business owner or an occasional gig worker. The people we identify as self-employed are likely getting into vastly different lines of work and likely for vastly different reasons.