Are growth of the labor force and resident jobs slowing in DC? Maybe—and maybe not.

Seasonally-adjusted and unadjusted data from BLS currently tell different stories

Each month the US Bureau of Labor Statistics (BLS) estimates labor market statistics for all states and the District of Columbia. Labor market statistics include the labor force, resident employment, unemployment, and the unemployment rate. The data is reported on both a seasonally adjusted and unadjusted basis. Seasonal adjustment takes account of recurrent events during a year such as holiday employment that can mask trends in the data.

Typically, comparing data from the same month of the prior year eliminates the need for seasonal adjustment. Accordingly, it would be expected that there should be little difference between seasonally adjusted and unadjusted estimates of the annual change in DC resident employment from September 2017 to September 2018. Currently, however, the two data sets give very different pictures of the change over this time, leaving unanswered the question as to whether DC’s resident employment is or is not slowing significantly.

  • The seasonally-unadjusted data say that from September 2017 to September 2018 resident employment (measured by the 3-month moving average) increased by 3,870 (1.0%). By contrast, the seasonally-adjusted data peg the increase at twice that (8,067, a 2.1% gain).
  • The unadjusted data show quite a sharp decline in the amount of year-over- year growth since May 2018, while the adjusted data show an increase.
  • The unadjusted data peg growth over the past year at about half the annual average increase over the past 5 years. Seasonally adjusted, the growth is very close to the average of the past 5 years.          

Details are shown in the tables and charts in the appendix. As indicated there, the story is similar for the seasonally adjusted and unadjusted estimates of DC’s labor force.

The current difference between the one year change in the seasonally adjusted and unadjusted resident employment and labor force data is an unusually clear example of the difficulty in spotting changes in the economy by closely monitoring data as it is released each month or each quarter. As with Personal Income, population, and other data produced by federal agencies, labor market data is revised as more information becomes available.

As the labor force data is revised the current differences in the story about changes over the past year told by the seasonally-adjusted and unadjusted data will be resolved. However, it will likely not be until March 2019 when major annual revisions typically occur that the matter will be cleared up.

It should be noted, however, that the seasonally-adjusted and unadjusted data both tell the same story about unemployment: the amount and rate of unemployment fell over the past year.

Appendix

 

 

 

 

 

 

 

 

 

About the data. The labor market information is from the statistics released each month for the District of Columbia (along with all states) based on a population survey. The data include resident employment (persons over 16 years of age who say they are working on a full or part time basis); unemployment (persons over 16 years of age who are not working but say they are looking for work); labor force (the sum of resident employment and unemployment); and the unemployment rate (unemployment as a percentage of the labor force).

The data are reported on both a seasonally adjusted and not seasonally adjusted basis. For the month of September 2018 the data reflect the revisions which were part of the October 2018 release. The annual comprehensive revision to the data will occur in March 2019. All calculations here are based on 3-month moving averages (e.g., September 2018 is the average of July, August, and September as reported by BLS).

Seasonal adjustment is a statistical method for removing the seasonal component of a time series that exhibits a seasonal pattern. It is usually done when wanting to analyze the trend of a time series during a year independently of the seasonal components. It is common, for example,  to report seasonally-adjusted data for unemployment rates to reveal the underlying trends in labor markets.

An earlier version of this blog was included in the October 2018 District of Columbia Economic and Revenue Trends report issued by the Office of Revenue Analysis of the District of Columbia Office of the Chief Financial Officer.

 

 

Estimating the Effects of the Tax Cuts and Jobs Act (TCJA) on the City’s 2018 Income Tax Burdens

This is an analysis of the effects of the TCJA on individual income tax liabilities of District of Columbia residents. We estimate that under the new legislation, and in the aggregate, income taxes paid to the federal government for 2018 will be lower but income taxes paid to the District of Columbia government will be higher with the onus of the increased local income tax burden being borne largely by the city’s low to middle-income tax payers. (See here for a more in-depth statistical analysis of the TCJA, and see here for an extended discussion of the results discussed in this blog.)

The TCJA will affect the income tax liability of different District residents in various ways, depending on a tax filers circumstances, such as income, marital status, number of children, etc.  Using the Office of Revenue Analysis Income Tax Microsimulation Model, we estimate that for tax year 2018 (for which taxes are due April 15, 2019) the TCJA will cause city residents to pay $617.3 million less in federal income taxes but $56.4 million more in city income taxes. Figure 1 shows an estimated 76 percent of city filers will see a decrease in their federal tax liability, and figure 2 shows that 43 percent of the same city filers will see an increase in their District income tax liability.

Fig 1Figure 2_New

Distributional Effects of the TCJA

Of the estimated 76 percent that are likely to see reduced federal taxes in 2018, an estimated 40 percent of the reduced tax liability will go to residents of Wards 2 and 3. The remaining 60 percent of the reduced tax liability will go to residents of the remaining 6 wards (figure 3). This 60 percent is estimated to be further distributed in dollar terms as follows: 14 percent to filers with income less than $50,000, 19 percent to filers with income between $50,000 and $100,000 and 27 percent to those with income greater than $100,000.

Of the estimated 15 percent that will likely see higher federal taxes (from figure 1), 64 percent of the higher tax burden will be paid by residents of Wards 2 and 3, and an additional 22 percent will be paid by residents of the remaining 6 wards whose income is greater than $100,000 (figure 4).

Figure 3Figure 4

The above figures indicate that, in the aggregate, residents of Wards 2 and 3 will be significantly impacted. But the ward distribution of the impact of the TCJA on the city’s federal income tax liability largely reflects the District’s distribution of income by wards. Though each ward has an average of about 13 percent of the city’s income tax filers, Wards 2 and 3 account for 46 percent of the city’s annual income and 51 percent of income tax liability (as shown in figure 5).

Figure 5

Turning to the distributional impact of the TCJA changes on the District’s income tax liability, of the 39 percent tax filers (figure 2) with decreased District income tax liability, 56 percent are in Wards 2 and 3 (figure 6).   Of the tax filers outside of Wards 2 and 3 with lower tax liability, an estimated 14 percent have income less than $50,000 (figure 6). On the other hand, Wards 2 and 3 will only shoulder 29 percent of the increased District income tax liability and residents in the other wards and with income less than $50,000 will shoulder 18 percent of the increased local tax burden.

Figure 6Figure 7

Why did TCJA lower District resident’s federal tax liability, but raise their District income tax liability?

The main reason for differential impact of TCJA on federal versus the District income tax liability is the TCJA’s suspension of the personal exemption (for tax years 2018-2025). As figure 8 shows, Wards 2 and 3 only accounted for 19 percent of all personal exemptions in tax year 2015, while filers with income less than $50,000 who lived in wards outside Wards 2 and 3, accounted for nearly 50 percent of all District personal exemptions. On average, head of household tax filers (unmarried tax filers with dependents) claimed 3.62 exemptions on their tax returns in tax year 2015 (figure 9). Figure 10 shows that Wards 4, 7 and 8, have the highest share of dependents, accounting for 53 percent of the District’s dependents.  As such, tax filers in these wards will likely be most negatively impacted by the loss of the personal exemption with overall higher District income tax liability because of the TCJA changes, even with the almost doubling of the standard deduction. Our analysis suggests that the lack of a child tax credit like that in the federal tax structure is one of the major causes for expected higher District income tax burdens for lower income filers with dependents.

figure 8

fig 10

 

Combined Federal and DC Effects of the TCJA

Our analysis estimates that tax filers with income between $25,000 and $75,000 will experience an average increase between $155 and $173 in their 2018 District of Columbia income taxes. This translates into about a 0.2 percentage point increase in their average effective tax rate. In contrast, it is anticipated that filers with income greater than $500,000 will experience a decrease in their District of Columbia income taxes of roughly $1,000, and this translates into practically no change in their average effective tax rate.

When we consider the effect of the TCJA on the combined federal and local income taxes on District residents’ tax liability, it is estimated that only 17 percent of filers will see a net increase in their combined income tax liability and 64 percent of filers will see a net decrease in their combined income taxes. This suggests that for many filers the expected decrease in their federal income taxes is likely to offset the expected increase in their city income taxes for 2018.

Conclusion

At the federal level, it appears that a combination of the higher standard deduction and the higher child credit allows eligible low-income earners with dependents to lower their federal income liability despite the elimination of personal exemptions. The absence of such a credit at the District level appears to be a principle reason why many low-income earners with dependents will pay more income taxes to the District of Columbia government in 2018 under the new TCJA.

We estimate that the TCJA will make the District’s income tax structure less progressive than it otherwise would have been in 2018. That is, beginning in 2018 the District of Columbia effective income tax rates for many low income filers with dependents are estimated to increase slightly more, on average, than the effective income tax rates for city’s highest income filers.

In the last 5 years DC added 180 new apartment and condominium buildings with 22,348 units

The new units are essential to DC’s ability to absorb a growing population, but they are not the whole story

From 2012 to 2017 DC’s inventory of apartment and condominium housing units grew by a net of 22,348 according to CoStar, a real estate information firm that tracks developments in the District and many other locations. This 13.7% increase in housing units is a major element in the growth of DC’s population over that time, a relationship that will be looked at shortly. But first, a few details on the recent changes to the District’s stock of apartment and condominium units.

graph 1

table 1

  • Of the 22,324 net increase in units, 20,128 (90.1%) were in 95 apartments and 2,196 were in 84 condominiums. The average size of condominium buildings was much smaller, 26 compared to 212 for apartments. Condominiums therefore accounted for 47% of the buildings, but just 10% of the units. (In 2017, condominiums accounted for about 19% of the combined total multifamily units— condominium, apartment, and co-op—in the city.)
  • The number of new units delivered over the five years was 23,099, but 775 units, about one-half percent of DC’s stock of multifamily housing in 2012, were demolished or otherwise went out of existence.
  • The number of vacant apartment units increased by 2,374 over the past 5 years, and the vacancy rate rose from 6.5% in 2012 to 7.3% in 2017.
  • New construction at the end of 2017—11,179 apartment units and 1,614 condominium units—essentially continues the pace of recent development activity. It will take two or more years for all of this existing construction to deliver new units to inventory, and the amount of this new construction is more than half of the net increase in units that occurred over the previous 5-year period of 2012 to 2017. For apartments current construction is 56% of the prior 5 year net increase in units, and for condominiums the percentage is 74%.

Detail for each of these points are in the tables in Appendix 1.

Apartments, condominiums, and DC population dynamics

The number of occupied apartment and condominium units grew by 19,930 from 2012 to 2017. This is almost 2,400 less than the 22,348 net increase in inventory, but in percentage terms the gain in occupied units—12.9%—was greater than that of population over that time (9.2%).

table 2

table 3

Newly occupied apartment and condominium units clearly represent a major element in the demographic changes occurring in DC. Available data does not, however, make it possible to know exactly how much of the 58,342 growth in DC’s population from 2012 to 2017 was accommodated by the net increase in occupied apartments and condominiums described in the CoStar data. A judgment on this depends on the additional number of households associated with the increase in population—and this can only be estimated.

Definitions further complicate the task of trying to compare Census and CoStar information. For the Census Bureau, a household is equivalent to a housing unit occupied by DC residents. The resident household can be a single person, a small family, a large family, or a group of unrelated persons who share the unit. To be classified as occupied by CoStar, however, a unit need not only be occupied by a DC resident household (as defined by Census). Occupied units from the point of view of a property owner can also involve second homes, short-term rentals, corporate accommodations for employees and guests, units in transition waiting for a new owner or tenant to move in, or ones undergoing repairs. The growth in occupied units as defined by CoStar can thus easily exceed the increase in households as defined by Census.

That said, a reasonable place to start in connecting population increase to change in apartment and condominium occupancy is with the Census. In 2000 the ratio of population to households was 2.30, a ratio which fell to 2.27 in 2010. In that decade, the number of households grew faster than population (7.4% compared to 5.8%), and the ratio of the increase in population to the increase in households was only 1.80, suggesting that one of the features of population growth at that time was small households.

What of the period between 2012 and 2017? Was the increase in small households so great that the number of households grew faster than population, and the population/household ratio continued to get smaller? Or did population grow faster, resulting in a rise in the ratio? Among the factors contributing to this latter result would be more children and more people doubling up due to affordability issues.

Assumptions about an appropriate population/household ratio makes a big difference in assessing how many new households population growth has brought—and how much of that growth was accommodated by occupancy growth in apartment and condominium buildings. As noted above, the 2010 average population/household ratio was 2.27. That ratio applied to population growth over the 2012 to 2017 period yields an estimated growth in households of 25,701, a number that exceeds CoStar’s estimate of the increase in occupied units by 5,771.

The 2012-2016 American Community Survey 5 year estimate pegs the population/household ratio at 2.38. Applying that higher ratio gives 4,583 as the amount by which household growth exceeded the increase in occupied units. With ratios a little higher or lower than these averages new household growth exceeds the growth in occupied units. Only if the population/household ratio rises to 2.93 does the new household estimate equal that for the growth in occupied units. Under a range of plausible assumptions it appears likely that the District of Columbia added more households over the past five years than could live in newly occupied units in new apartment and condominium buildings. If this is the case, this means that other components of the housing stock—structures with four or less units—must have been able to absorb some of the increase in population.

table 5

Taken as a whole, the DC housing stock does provide room to accommodate some of the growth in population in units other than those in new apartment or condominium buildings. The Census Bureau’s American Community Survey estimated that for the 5-years 2012 through 2016 there were 306,711 housing units in DC, and that 160,750 (52.4%) of those units were in structures with 5 or more units. In other words, almost half of DC’s housing stock is in smaller buildings. Over the past 5 years more than 1,000 permits have been issued for projects with less than 5 units, and many smaller buildings can be reconfigured to accommodate more units.

table 4.PNG

In this connection, in the prior 5 year period— 2007 to 2012—larger buildings appear to have played a smaller role in accommodating population growth than in the most recent five years. From 2007 to 2012 Co-Star’s estimate of occupied units grew more slowly than population (6.9% versus 10.7%). The ratio of new population to the estimated increase in occupied apartments and condominiums was 6.1. (See Appendix 2. for more details.)

table 6

With the current pace of construction for apartment and condominium buildings much like that of the past few years, multi-family apartment and condominium projects will undoubtedly provide the largest share of the additional housing needed for DC’s growing population—provided, of course, that a sufficient number of households can afford to live in them. But the connection between increases in population and changes in the housing stock is a complex one, and DC’s changing demographics involve more than simply building large new apartment and condominium buildings for new people.

Appendix 1

Gross and net changes to inventory.

table 7

Apartment share.

table 8

Vacant units.

table 9

New construction.

table 10

Appendix 2

table 11.PNG

About the data. Data on DC multi-family housing buildings and units are for apartments, condominiums, and co-operative apartments of all classes in structures with 5 or more units as reported by CoStar, a real estate information company. The data was accessed toward the end of April. Population data and data from the American Community Survey are from the US Bureau of the Census. The housing and population data are all subject to revision by the source as more information becomes available.

This analysis looks solely at the statistical relationships between changes in DC population, households, and housing units.  It does not address issues related to affordability or homelessness.

An earlier version of this blog was included in the April 2018 District of Columbia Economic and Revenue Trends report issued by the Office of Revenue Analysis of the District of Columbia Office of the Chief Financial Officer.

 

 

High-Income Residents: Are They the Driving Force Behind DC’s Premium Apartments?

In a recent post, we concluded that the premium apartment rental market is the more popular and ascendant segment of the city’s housing market in the context of the current trend in net population growth. To further elaborate on this topic, we profile the tenants in the city’s Class A and Class B apartment buildings built after 2000 based on income tax data characteristics. The full research paper can be found here.

Economic Profile of Tenants

Table 1 tells us that in 2015 half of the residents who were income tax filers in the 88 Class A and Class B large and mid-sized apartment buildings that were built after 2000 had annual reported income of less than $57,428 and were under the age of 31.5. And, the vast majority of these tenants were single tax filers (unmarried and no dependents) and were relatively new[1] to the city.

table111.PNG

[1] We classify a new resident as someone who existed in the city’s income tax data in either 2013, 2014, and/or 2015, but did not exist in 2012 or prior.

Who is more likely to live in new apartment units?

Our data shows that there was a tripling in the number of premium apartment units delivered in 2013 compared to 2012. To better evaluate the data, we divided the buildings into two groups. The first cohort is comprised of all 2015 tax filers found to be residents in multifamily buildings that delivered between January 2000 and December 2012 (relatively older premium multifamily buildings). The second cohort is comprised of all 2015 tax filers found to be residents in multifamily buildings that delivered between January 2013 and December 2015 (newer premium multifamily buildings).  We then fit a statistical model to the data to determine the characteristics of new buildings versus older buildings.

Using T-tests, we find that the newer buildings tended to have units that were an average of 88.3 square feet (10.5 percent) smaller and cost 17.5 percent more per square foot (Table 2). We also found that individual tenants in newer buildings tended to have income that was on average of $9,884 (12.3 percent) less and 1.3 years younger than renters in older buildings.

table222.PNG

Using a statistical model to differentiate the characteristics of tax filers living in a newer building in 2015 versus older buildings, we calculate the probability that certain factors affect the choice of residing in newer apartment buildings instead of older buildings.

While the tenants in new and older apartment buildings are generally very similar, we were able to again tease apart a few distinctions in the two populations as well as a few contributing factors for their housing choices.

chart114.PNG

We find that income has almost no influence on whether a resident chooses to live in a newer or older apartment building (for every $100,000 increase in income, the probability to choose a newer building increases only about 4 percent). Age is also an important factor in determining how likely a resident will choose newer or older apartment units. Younger residents are more likely to reside in newer apartment buildings. For each additional year in age, existing residents are 0.8 percent less likely to reside in newer buildings, while this percentage is 0.2 percent for new residents. We also find that tenants commonly supplement their traditional wage/salary income with additional business income from entrepreneurial or other self-employment endeavors.[2]

Given that 83 percent of all tenants in these buildings are single filers (as shown in Table 1), we find that long time city residents who are head of household tax filers (unmarried income earning adults with dependent children) are 23 percent more likely to live in newer buildings compared to married residents. This is possibly due to the city’s affordable housing efforts to place low-income households in these new buildings via affordable housing programs.  And finally, single residents are more likely to reside in newer buildings compared to married filers, especially when they are relatively long-time residents.

[2] On government tax forms, adjusted gross income is comprised of wages and salaries, business income, investment gains or losses and other income.

Several Ways DC is Changing

In sum, we find the following results. First, 64 percent of the tenants in all the apartment buildings in this study tended to be new to the city. Second, the newest apartment units are smaller and more expensive, and their residents tended to be slightly younger and have less income than residents in the relatively older buildings. Third, residents in the newest units are more likely to have business income as part of their total reported income, which suggests there is an increased tendency for these residents to supplement their traditional wage and salary income with additional income from entrepreneurial or other self-employment endeavors. Lastly and surprisingly, the analysis shows a relatively strong increase in probability for residents in the newer buildings to be head of household filers. This is possibly due to the city’s affordable housing efforts to place low-income households in these new buildings via inclusionary zoning and various housing subsidy programs.

Conventional wisdom assumes that these newer buildings are attracting primarily high-income residents; however, we find that compared to older buildings, the city’s newest and pricier apartment buildings built during the recent residential construction surge (2013 and after) tend to attract a higher percentage of new residents to the city, and also attract a higher percentage of single, young residents with income below the city average. It appears that both the city’s demographics and apartment rental market are continuing to evolve and change in significant ways. And, it is very likely these changes will have considerable implications on the residential and economic patterns of the city in the years to come.

 

The Data

Using data from CoStar, we identified 88 Class A and Class B large and mid-sized apartment buildings (containing 21,203 total residential units) from across the city that were built after 2000. The list can be found here. This study also uses 2015 individual income tax data for all DC tax filers who listed their home address as being in one of the 88 apartment buildings mentioned above.

 

 

The Rise of the Premium Apartment Rental Market in the District of Columbia

Although the District of Columbia’s population is growing continuously since 2006, the city’s housing stock is growing at a slower rate (Figure 1). Since the Great Recession, this slower rate of annual growth in the housing stock is likely due in part to accelerating land and construction costs per square foot, the decreasing supply of available land lots, zoning, and the lack of preservation of family-sized housing units. Consequently, the city’s housing vacancy rate, which used to exceed 10 percent is currently approaching six percent (Figure 2). In other words, roughly 94 percent of the city’s housing units are occupied, whereas in earlier years it was closer to 90 percent. These factors have profound implications on how certain housing market sectors are evolving.

 Figure 1

Figure 1

Figure 2

Figure 2

 

 

 

 

 

 

 

 

When ranked among the states, the District of Columbia’s home ownership rate of 39.8 percent was the lowest in the nation as of the fourth quarter of 2017, according to the U.S. Census Bureau[1]. (New York and California had the next lowest rates of 51.1 and 55.1 percent, respectively.) One of the many reasons for this is likely the high cost of homes and home-ownership in the city. In 2000, half of the homes purchased in the city were priced below $178,250. But, with the median single-family home price nearly quadrupling by 2017, half of the homes purchased in the city were priced above $690,000, (Figure 3). On average, the median sale price for homes in the city increased 8.3 percent per year, while the consumer price index for the Washington area only grew on average by 2.3 percent a year over the same period.

Figure 3

Figure 3

Additionally, the number of single-family home and condo sales have grown at an average annual rate of 4.9 percent between years 2009 and 2017 (MRIS[2]). But since the city’s population has increased by an average of 15,653 people (2.5 percent) every year since 2010 (U.S. Census Bureau), a key factor in the city’s robust residential development simply appears to be population growth. Home ownership rates and population levels between 2010 and 2017 are shown in Figure 4.

Figure 4

Figure 4

For the many residents who choose to avoid a down payment and closing costs of tens of thousands of dollars on the purchase of a new home in the city, renting is the preferred housing option. Between the years 2013 and 2017, the city added over 4,200 multifamily units per year on average, in premium buildings (Class A and Class B) alone, to help accommodate the growing population (Figure 5).

Figure 5

Figure 5

In 2017, the average effective rent for a one-bedroom apartment in the city was $2,184 and $1,834 for a studio apartment (Figure 6). And, while these rental rates may be unnerving to some, rental rates have generally grown over time in line with the area’s consumer price index, unlike the prices for newly purchased homes.

Figure 6

Figure 6

Despite the very high expense of buying and owning a home in the District of Columbia, the number of single-family home and condominium sales have grown at a healthy average annual rate of 4.9 percent between years 2009 and 2017. But residential property developers, on the other hand, delivered apartments in new Class A and Class B buildings at an even healthier average annual rate of 14.1 percent during the same period. With respect to all relevant city trends, the premium apartment rental market appears to be the more popular and ascendant sector of the city’s housing market.

[1] https://www.census.gov/housing/hvs/data/rates.html

[2] Metropolitan Regional Information Systems, Inc.

New income and labor force data give a more positive 2017 year-end picture of DC’s economy

Although federal jobs are declining, income is rising, the job structure is more diverse, and unemployment is falling

In March the US Bureau of Economic Analysis (BEA) released its estimate of income in the District of Columbia for the last quarter of calendar year 2017 along with revisions to the prior three quarters of 2017. Also in March, the US Bureau of Labor Statistics (BLS) revised labor force data for the past several years for wage and salary jobs located in DC and employment of DC residents. Taken together, these new data provide a more positive picture of the District’s economy as the year drew to a close.

  • Income growth for DC residents is increasing.
  • Resident employment is rising and unemployment is falling.
  • Other sectors are picking up some of the slack in jobs and income from weakness in the federal sector.

Income in DC. The change in income is particularly striking. From the previous estimate it appeared that DC’s Personal Income growth was continuing to slow down in the 3rd quarter of 2017, falling to a rate of 2.2%. The new data raised the 2017.3 rate to 2.8%, which then jumped to 3.8% in the 4th quarter. Instead of a picture where income growth in the District continued to slow while the US increased at a faster rate, now DC’s Personal Income growth is estimated to be growing much closer to the national average.

graph 1

 

graph 2a     graph 2b    graph 2c

For DC residents, the turnaround is more pronounced for wages and salaries, which grew an estimated 5.5% in the 2017.4 quarter. This growth is consistent with recent collections for the withholding portion of DC’s individual income tax which have been very strong. For in the last quarter of 2017 those collections were up about 10% over the prior year. (It should be noted, however, that taxable DC income includes things like capital gains that are not captured in the income statistics; also, the recently enacted federal tax law complicates year-over-year withholding comparisons because, for example, some bonus payments may have been accelerated into 2017 that might otherwise have been paid in early 2018 so that corporations could reduce their 2017 corporate profits subject to 2017’s higher rates.)

graph 3.PNG

Changes in commuting patterns do not explain the recent upsurge in the wages of DC residents—in other words, DC residents are not capturing a greater share of the income earned in DC. To the contrary, the new data show that the commuter share of income earned in DC appears to have risen even faster than that earned by DC residents. Thus, in the 2017.4 quarter DC resident earnings grow by 4.1% while those earned by all persons working in DC rise 5.2%. This is a change from 2016 when resident earnings, though slowing down, still grew faster than all amounts earned in DC. (Earnings by this measure include proprietors’ income and benefits as well as wages and salaries, and the earnings of DC residents include amounts earned in the suburbs.)

table 1graph 4

 

 

Resident employment is rising and unemployment is falling. The new data show that resident employment increased by 1.5% from 2016.4 to 2017.4, no doubt a contributing factor to rising incomes of DC residents. The recent revision to the labor force data made a modest change to the end of year level of resident employment (a 0.3% increase of 976). The revision made a substantial change, however, to the picture of unemployment in DC. Whereas before it appeared that unemployment had increased by 1,479 from 2016 to 2017, the new data shows that it fell instead by 391. The primary reason for the decrease in unemployment, however, is that the revision reduced the amount of growth in the labor force while making little change in resident employment.

table 2

Picking up the slack. Revisions to the employment data made no material change in the number of jobs in DC at the end of the year (797,667, 200 less than previously estimated), or to the amount and rate of change (a 1% increase of 7,800, 133 more than previously estimated). The new data shows, however, that the federal sector lost 3,433 jobs from 2016, a 1.7% decline. Similarly, although federal wages grew by 3.1% from 2016 to 2017, this rate was little more than half that for the economy as a whole (5.7%). Although still by far the largest sector in the District’s economy, over the past year the federal civilian share of jobs slipped to 24.8% and its share of wages slipped to 30.5%.

table 3    table 4.PNG

table 4table 6

One of the positive elements in the new employment and income data is the extent to which other sectors of the economy seem to have picked up some of the slack resulting from weakness in the federal sector. On the job side, all other sectors of the economy grew 1.9%, faster than the US average of 1.6% for all non federal jobs. Wages of all other sectors of the economy grew 7.0%, faster than the US average of 4.7% for all non-federal wages and salaries.table 7.PNG

The new data show a shift in the composition of employment and wages in a way that, on balance, give a picture at the end of the year of increasing diversity in the industry mix of the District’s economy.

On the employment side:

  • 5,633 jobs were added to year-over-year employment change in four sectors: health, information, professional and technical services, and personal services. Instead of appearing to lose almost 200 jobs from 2016 to 2017, this group gained almost 5,500.
  • 4,900 jobs were cut from the year-over-year changes in jobs in three sectors: business services, food services, and education. (Even with the reductions, food services and education remain among DC’s leading sectors.)

At year end the leading non-federal sectors are summarized in the following table:

table 8

On the income side, the new data show particularly large gains in disbursements from a few sectors:

  • Almost three-quarters of the revised gain in wages in the 2017.3 quarter occurred in five sectors or subsectors: Information, real estate, management, arts and entertainment, and organizations and personal services. These five sectors accounted for only 17% of all DC wages in the last quarter of 2017.
  • Those five areas also accounted for 39% of all wage gains from 2016.4 to 2017.4.

At year-end the leading non-federal sectors for wage and salary disbursements are summarized in the following table:

table 9

About the data: The information is regularly reported information from the US Bureau of Labor Statistics (BLS) and the US Bureau of Economic Analysis (BEA). BLS publishes monthly statistics of wage and salary employment for the US and all states (including DC) and each March revises data from the prior years based on the availability of additional information. This analysis uses the amount for the years 2016 and 2017 as originally issued in December 2017 and the revised data for those years issued in March 2018. BEA issues Personal Income and other income statistics each quarter, often revising information from prior periods. This analysis uses the December 2017 release for 2016 and 2017 (through the 3rd quarter of the year) and the March 2018 release that revises prior data and includes the new estimate for the 4th quarter of 2017. Data used here may be subject to further revision by the agencies.

An earlier version of this blog was contained in the March 2018 District of Columbia Economic and Revenue Trends report.

 

 

 

 

 

 

 

From 2010 to 2017 net migration into DC was greater than that of 31 states

Housing demand and school enrollment are examples of how this migration has had an influence on the city’s economy

The Census Bureau estimates DC’s population was 693,972 as of July 1, 2017, an increase of 92,206 from the April 1, 2010 census. Although DC had more people than only two states in 2017, the amount of DC’s increase since 2010 was greater than in 19 states. In percentage terms DC’s 15.3% gain over the 7 years was almost three times the US average (5.5%) and greater than that in all 50 states. (The percentage gains in the 7 states with the most rapid increases in population—Colorado. Florida, Nevada, North Dakota, Texas, Utah, and Washington—ranged between 10.1% and 12.6%)

Net in-migration is the principal explanation for DC’s relatively rapid population gains. In other words, more people moved in than moved out.

  • Net migration into DC of 57,912 accounted for almost two-thirds (63.7%) of the city’s population increase.
  • DC’s net migration was greater than in 31 states. It represented a 9.6 % increase over DC’s total 2010 population, a higher percentage gain from migration than in every state except Florida (10.3%).
  • DC’s net migration was almost evenly split between international (47%) and domestic (53%).
  • The amount of net international migration into DC topped 14 states, but net domestic migration was even more striking: DC outpaced 35 states.

table 1

Migration also contributes to the part of DC’s population gain resulting from natural increase (which is births minus deaths).

According to the Census Bureau about one-third (36.3%) of DC’s population increase from 2010 to 2017 was due to natural increase. It should be noted, however, that many of the births that occurred in DC must have been to parents who migrated into the city during those seven years. In addition, the relatively young age of many migrants meant that few of them died in those years. In DC there were only 51.7% as many deaths as births over the period whereas for the US as a whole there were 66.1% as many deaths as births. Consequently, although DC had more births than only two states, the natural increase in DC’s population from 2010 to 2017 was greater than in 9 states.

Migration and age groups in DC. According to the economic forecasting company IHS Global Insight, 85% of the increases in DC’s population from 2010 to 2017 fell in two age groups: (1) 25 to 44 years and (2) under 15. Although migration can occur within any age range, these two age groups are closely tied to migration.

  • From 2010 to 2017 DC’s population between the ages of 25 and 44 grew by 54,071, a 26.3% increase that accounted for 58.6% of all growth in the city from 2010 to 2017. It is not possible to know how many of the additional 54,071 persons in this age group were migrants, but it can be no coincidence that this increase is close to the 57,912 net migration into DC reported by Census for the period. This age group is mobile and can easily move for employment reasons—and is also the age group most likely to have children.
  • From 2010 to 2017 DC’s population under 15 years of age grew by 24,436, a 29.2% increase slightly higher than that for the 25 to 44 age group. Accounting for 13.9% of the city’s population in 2010, children under 15 accounted for 26.5% of all growth from 2010 to 2017. Again, it is not possible to know how many of the additional children of this age either accompanied persons migrating to DC or were born to such migrants after they arrived, but surely many were.

The scale of the changes in migration and age groups that occurred between 2010 and 2017 would be expected to have many influences in the District’s economy, and this has been the case. For example, according to CoStar, a private sector firm that collects data on apartments and other commercial real property, from the first quarter of 2010 to the second quarter of 2017 there was an increase of 21,492 in occupied market rate apartment units in the District of Columbia. Similarly, enrollment in DC Public and Charter schools increased by 17,139 from the 2009-10 to 2016-7 school years, a 23.5% gain. Increases of these magnitudes in housing and school enrollments would not have been possible without the net in-migration experienced in DC from 2010 to 2017.

table 2

graph 1

The course of net migration will continue to have a great deal of influence on the the District’s economy. Migration is a net concept, meaning that it is the difference between those moving in and those moving out, so the questions surrounding migration have to do both with DC’s ability to attract new people and to retain those that are here.

According to Moody’s Analytics, an economic forecasting company, the nation’s population in the 20 to 30 age group is actually expected to decline over the coming years. From the first quarter of 2010 to the second quarter of 2017 there was a 22.6% increase in the 25 to 29 age group, whereas in the next five years Moody’s expects a 3% decline. To maintain its past inflow of young adults in this age group DC would therefore have to attract a larger share of the national total than was true of the past few years. In attracting people to DC an important question is also the city’s continuing ability to attract workers over 30 years of age who are not coming here for first or entry level jobs.

For retaining people who are here the key questions center on those 25 to 44 year-olds who have been at the center of DC’s recent population growth. What share of this age cohort will find sufficient job opportunities and housing options and secondary school options to keep them committed to staying in the District of Columbia?

There are, of course, many factors affecting migration into DC that are beyond the city’s control. These include developments in the national economy, federal spending policies that can make it easier or harder to find employment in DC’s key industry, and national policies affecting immigration that might reduce net international migration not only to DC but elsewhere in the country.

About the data.

This is the third of three blogs on DC population based on the December 2017 estimates of the US Census Bureau of DC population in 2017.

The population data for the District of Columbia for April 2010 and July 2017 are estimates from the US Bureau of the Census. The July 2017 data for DC and all of the states were released in December 2017 and contains an analysis of the components of natural increase and migration that explain the net changes in population from 2010 to 2017 for the US and for each jurisdiction.

Data on the age composition of DC population for the first quarter of 2010 and the second quarter of 2017 are estimates from the economic forecasting firm IHS Global Insight.

Changes in the 25-29 year-old age cohort in the US are from the economic forecasting firm Moody’s Analytics.

Data on occupied market rate apartment units in DC in 2010.1 and 2017.2 are from CoStar, a real estate information firm that tracks development in the District of Columbia and elsewhere in the nation.

Data on yearly enrollments in DC Public and DC Charter schools is from the DC Public Charter School Board.

An earlier version of this blog appeared in the February 2018 District of Columbia Economic and Revenue Trends report issued by the District of Columbia Office of Revenue Analysis, a component of the District of Columbia Office of the Chief Financial Officer.

Appendix table

table 3