Urban Density Gradient Analysis and Review of the Washington DC Metropolitan Statistical Area Jesse Benson Organizational Overview The Washington Metropolitan Area includes the city of Washington and the Federal District – the District of Columbia – and twenty-four additional counties and cities from the states of Maryland, Virginia, and West Virginia. It consists of two metropolitan divisions: the Bethesda-Gaithersburg- Frederick (MD Metropolitan Division) to the northeast and consisting of Montgomery and Frederick counties, Maryland; and the Washington- Arlington-Alexandria, DC-VA-MD-WV Metropolitan Division. The Washington Metropolitan Area is also part of the larger Washington-Baltimore- Northern Virginia, DC-MD-VA-WV Combined Statistical Area (CSA)1. Several Virginia cities are included in the list of counties within the Washington Metropolitan Area, the result of a Virginia state statute that defines municipalities independent of county organization and government. These cities are considered counties for census and MSA purposes. The counties – and cities – included in the Washington Metropolitan Area are as follows: 1. District of Columbia 10. Fairfax County, Virginia 18. Alexandria City, Virginia 2. Calvert County, Maryland 11. Fauquier County, Virginia 19. Fairfax City, Virginia 3. Charles County, Maryland 12. King George County, Virginia 20. Falls Church City, Virginia 4. Frederick County, Maryland 13. Loudoun County, Virginia 21. Fredericksburg City, Virginia 5. Montgomery County, Maryland 14. Prince William County, Virginia 22. Manassas City, Virginia 6. Prince George's County, Maryland 15. Spotsylvania County, Virginia 23. Manassas Park City, Virginia 7. Arlington County, Virginia 16. Stafford County, Virginia 24. Berkeley County, West Virginia 8. Clarke County, Virginia 17. Warren County, Virginia 25. Jefferson County, West Virginia 9. Culpeper County, Virginia

1 http://en.wikipedia.org/wiki/Washington_Metropolitan_Area

1 Urban Density Gradient Analysis and Review of the Washington DC Metropolitan Statistical Area PA 5202 - Spring 2007 Jesse Benson

The map below shows location of these twenty-five municipalities within the larger Washington Area MSA.

2 Urban Density Gradient Analysis and Review of the Washington DC Metropolitan Statistical Area PA 5202 - Spring 2007 Jesse Benson General Statistics The Washington MSA is relatively large, both in population and in area, ranked as the 8th largest MSA in the United States.2 Population in the 2000 Census was reported as 4,923,152 people, an increase of 16.6% from the 4,223,485 people counted in the 1990 Census. The most significant growth occurred in the MSA suburbs, where population increased by more than 20% during the 1990s from 3,616,585 people to a 2000 Census total of 4,351,094. Although not geographically large by Midwestern or Western standards, the Washington MSA, at approximately 6,500 square miles, is reasonably significant in size for the East Coast. The District occupies only 61 square miles. The remaining approximate 6,440 square miles are outside the central city. Comparison of household income levels between the District and the larger Washington Metropolitan MSA show suburban households earning 29% more than District homes in 1990 and 36.8% more in 2000 (see Median Income table below).

Median Income Washington Metropolitan Area, 1990 and 2000 Census Year District of Columbia (CBD) Suburbs 1990 (1989) $33,959.71 $51,768.98 2000 (1999) $43,857.10 $70,808.45

Income distribution for the entire MSA (using 1990 data only) shows that the Washington Metropolitan Area leans towards the upper-middle class, with 35% earning between $50-$99,999, a majority (51%) earning in the comfortable $37,500-$99,999 range, 11% living below the poverty threshold, and only 10% earned more than $100,000. For better or worse, household income levels in the District itself are much more evenly distributed across the four class quartiles. Data from the 1990 Census shows 24% living at or below the poverty threshold, 14% earning more than $100,000, and middle class incomes in the $37,500-$49,999 range (rather than in the $50,000-$74,999 range of the MSA middle class).

2 http://www.census.gov/population/cen2000/; http://en.wikipedia.org/wiki/Metropolitan_Statistical_Area

3 Urban Density Gradient Analysis and Review of the Washington DC Metropolitan Statistical Area PA 5202 - Spring 2007 Jesse Benson

Income Distribution Washington Metropolitan Area, 1990

Washington, DC MSA - Income Distribution, Census 1990 District of Columbia Income Distribution, Census 1990

$150,000 or more Less than $5,000 $125,000-$149,999 $150,000 or more $125,000-$149,999 3% 3% 2% 3% 2% $5,000-$14,999 $100,000-$124,999 Less than $5,000 $100,000-$124,999 8% 3% 9% 5% $75,000-$99,999 6% $15,000-$24,999 $5,000-$14,999 $75,000-$99,999 11% 15% 12% $50,000-$74,999 14%

$25,000-$37,499 $15,000-$24,999 17% 17% $37,500-$49,999 12% $50,000-$74,999 $37,500-$49,999 23% 16% $25,000-$37,499 19% Race considerations within the Washington Metropolitan Area can be summarized as follows: ƒ More than 50% white, but the percent is decreasing ƒ About 25% black, African, or African-American ƒ Growing Asian and Hispanic populations ƒ Hispanic population growing at fastest rate

4 Urban Density Gradient Analysis and Review of the Washington DC Metropolitan Statistical Area PA 5202 - Spring 2007 Jesse Benson

These statements are summarized in the two following charts.

Washington, DC - MSA Race Distribution, Census 1990

Other race Asian or Pacific Islander Hispanic origin: 0% 5% 5%

American Indian, Eskimo, or Aleut 0%

White Black Black 25% American Indian, Eskimo, or Aleut Asian or Pacific Islander White Other race 65% Hispanic origin:

Washington, DC - MSA Race Distribution, Census 2000

Native Hawaiian and Other Some other race Hispanic or Latino Pacific Islander 0% 11% 0% Asian 7% White 56% American Indian and Alaska Native 0% White

Black or African American American Indian and Alaska Native

Asian

Native Hawaiian and Other Pacific Islander

Black or African American Some other race 26% Hispanic or Latino

5 Urban Density Gradient Analysis and Review of the Washington DC Metropolitan Statistical Area PA 5202 - Spring 2007 Jesse Benson Density Expectedly, given the above-average population densities of East Coast agglomerations, the Washington Metropolitan MSA population densities are higher than those across the country. For instance, according to the 2000 Census, the three most densely populated states were New Jersey (1,134 people/mile2), Rhode Island (1,003 people/mile2), and Massachusetts (810 people/mile2)3. If placed similarly on this list, the Washington MSA would rank as the fourth with 756 people/mile2 – an increase of 108 people/mile2 from the density measured in the 1990 Census. Descriptive statistics for population density are shown for the two Census measurements, 1990 and 2000, in the following table. Range, median, and mean are provided for three geographical areas – 1.) Washington Metropolitan Area (MSA Total); 2.) District of Columbia/ Washington, DC (CBD); 3.) Suburbs. The two most interesting observations of these statistics are, first, the very large difference in mean density between the CBD and suburbs (nearly 12,000 more people/mile2 in the city) and, second, that this difference decreased substantially from 1990-2000 by 1,310 people/mile2 (from approximately 11,754 in 1990 to 10,344 in 2000) – a drop of 12%. In simplest terms, this change is the result of two forces – the loss of center city residents, alongside of suburban growth. The trend warrants further investigation, whether it be to determine who is relocating, why they are doing so, what are the influences of the job and housing market, what are family sizes and ages for people coming and going, or if there are pertinent public policies that need to be revisited.

Descriptive Statistics for Population Density Washington Metropolitan Area, 1990 and 2000 1990 2000 Geographical Area Range Median Mean Range Median Mean Density – Washington 1.3-60,737 3,465 5,814 0-57,507 3,916 6,233 Metropolitan Area (MSA TOTAL) Density – District of 0-60,737 13,227 15,415 0-57,507 11,809 14,702 Columbia (CBD) Density – Suburbs 0-40,163 2,722 3,660 0-46,007 3,352 4,358

Whatever the case, with the District bound by its border and unable to expand through annexation, this situation raises speculative questions regarding opportunities for future growth and revitalization within the Washington, DC, and older inner-suburban neighborhoods, as well as of the future influence of the city within the larger MSA, of the political and economic relationship between the District and its first-ring neighbors and the expanding – and wealthy – suburbs, and of the difficulty in addressing the needs of lower-income and lower-profile households in this high-profile national Capitol MSA.

3 ibid.

6 Urban Density Gradient Analysis and Review of the Washington DC Metropolitan Statistical Area PA 5202 - Spring 2007 Jesse Benson

Out-migration from the District CBD, likely in combination with suburban in-migration from outside the MSA, can be further examined in comparing the percent of people from 1990 and 2000 living in areas of higher than average densities. With 29% of the population living in above average density in 2000, and 31.4% in 1990, the numbers in this are not tipped as dramatically in favor of the suburbs as they were in the above comparison of density differences where the 12% drop in difference of mean density seemed to suggest that the city and suburbs were on a path towards parity. However, the fact that there was only a 2.4% reduction in the number of people living in areas of above-average density does not necessarily mean that the District is holding its own better than expected; instead, it could just mean that the people who left densely populated center city neighborhoods did so through relocating to suburban neighborhoods that also had population densities higher than average. It should also be noted that, while the population of the central city – Washington, DC – decreased, from 606,900 people in 1990 to 572,059 in 2000, this is not to suggest that the city was without regions where population density also increased. Density can be evaluated using the maps on the following page. In the first map, Density Gradient by Census Tract, 1990 Census, we find density highest at the center of the MSA, with a somewhat linear reduction in density moving out from the center. This is not a concentric linear relationship through successive zones of reduced density from center, but instead more of a near-linear relationship through a triangular-shaped zone with the center of the triangle being somewhere near the White House, and with the three vertices of the triangle being 10 miles north, southeast, and southwest of this center. The tracts of greatest density lie within this triangle; tracts of next greatest density either lie some within the triangle or contiguous to it. Beyond the triangle, the greatest density is found to the southwest and northwest, with growth to the east being limited by the Potomac River and Atlantic Ocean. Further from the center, there are three outlying areas of slight density increase in Charles and Frederick Counties, Maryland, and in Berkeley County, West Virginia.

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This pattern continues in the Census 2000 map. The outlying growth centers in Charles, Frederick, and Berkeley counties have expanded, but so have some other parts of the region that were not noticeable in the 1990 map, especially to the southwest of the city, along Interstate 95, the north along Interstate 495, and the northeast along Interstate 95. Growth along these corridors has resulted in increased density outside of the center city and has established new city centers in the suburbs.

8 Urban Density Gradient Analysis and Review of the Washington DC Metropolitan Statistical Area PA 5202 - Spring 2007 Jesse Benson

Regression Regression estimates the strength of a relationship between independent and dependent variables; in this case, the strength of the relationship between the independent variable of distance from CDB and the dependent variable of population density. The strength of this relationship increases when it can be shown that the density variance can be explained – increasingly – by the distance variable. Regression for the natural log of density (dependent) over the natural log of distance (independent) produces an R-square of 0.15 for 1990 and .38 for 2000, which means that only 15% of the original variability of the density in 1990 and 38% of the variability in 2000 can be explained as being caused by distance; leaving 85% and 62% residual variability unexplained.

Regression of Log Density Washington Metropolitan Area, 1990

Regression Statistics Multiple R 0.389368664 R Square 0.151607956 Adjusted R Square 0.150792978 Standard Error 2.404699049 Observations 1043

ANOVA Significance df SS MS F F Regression 1 1075.716 1075.716 186.0271 4.31E-39 Residual 1041 6019.663 5.782578 Total 1042 7095.379

Standard Upper Lower Upper Coefficients Error t Stat P-value Lower 95% 95% 95.0% 95.0% Intercept 9.572139146 0.180665 52.98295 8.3E-298 9.217631 9.926647 9.217631 9.926647 X Variable 1 -1.002197899 0.073479 -13.6392 4.31E-39 -1.14638 -0.85801 -1.14638 -0.85801

9 Urban Density Gradient Analysis and Review of the Washington DC Metropolitan Statistical Area PA 5202 - Spring 2007 Jesse Benson

Regression of Log Density Washington Metropolitan Area, 2000

Regression Statistics Multiple R 0.617390722 R Square 0.381171303 Adjusted R Square 0.380573401 Standard Error 1.253059813 Observations 1037

ANOVA Significance df SS MS F F Regression 1 1000.999 1000.999 637.5146 5.5E-110 Residual 1035 1625.114 1.570159 Total 1036 2626.114

Standard Upper Lower Upper Coefficients Error t Stat P-value Lower 95% 95% 95.0% 95.0% Intercept 10.53026884 0.109312 96.33206 0 10.31577 10.74477 10.31577 10.74477 X Variable 1 -1.076953736 0.042653 -25.2491 5.5E-110 -1.16065 -0.99326 -1.16065 -0.99326

The intercepts and coefficients for the regression enable the creation of a trend line. For 1990, this trend line is defined as [Natural Log of Density = - 1.002(Natural Log of Distance) + 9.572]. For 2000, the line is defined as [Natural Log of Density = -1.077(Natural Log of Distance) + 10.53]. The scattergrams on the following page show distribution of the 1,000+ observations for the distance/density relationship for Washington Metropolitan Area census tracts. The slope of both graphs is negative (-1.002 and -1.077 as shown in the above equations).

10 Relationship Scattergram for Density Relationship Scattergram for Density and Distance from CBD and Distance from CBD Washington Metropolitan Area, 1990 Washington Metropolitan Area, 2000

70,000 60,000

60,000 50,000

50,000

40,000

40,000

30,000

30,000

20,000 20,000

10,000 10,000 Population Density (persons per sqaurePopulation mile) Population Density (persons per squarePopulation mile)

0 0

020406080 020406080 Distance from CBD (Washington Monument) in Miles Distance from CBD (Washington Monument) in Miles

11 Conclusions Due to the size of the Washington Metropolitan Area, opportunities for growth are numerous, ranging from expansion of tourism, recreation, office parks, and manufacturing/industrial districts on the suburban fringe, to revitalization of the inner suburban – both first and second ring – housing stock and retail hubs. Settlement patterns reviewed through use of Census 1990 and 2000 show that there is activity across the MSA. The suburban counties are growing quickly. Incomes have increased significantly. Population growth is also occurring within the District itself, although it is limited to very specific and highly demanded real estate addresses and census tracts. Projections and patterns for the future will continue along the same paths that they did during the 1990s, and will be defined by the four guidelines. First, high-quality jobs and the availability of suburban land for development will inevitably attract additional people to the area and will increase the population of the suburbs. Second, revitalization of the center city and current interest in urban and downtown living will result in population growth for the District. Third, geographical and political boundaries prevent the District from becoming larger, which will result in the District becoming more densely populated. Fourth, the growth and prosperity of population centers and commercial nodes along transit routes outside of the central city will make it easier to commute between work in the District and suburban residence, and will both provide an escape from densely populated District neighborhoods and will increase the density of suburban communities.

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