Tag Archives: Population growth

JCHS: 2012 Population Estimates for Metropolitan Areas

by George Masnick
Fellow
The Census Bureau recently released 2012 population estimates for cities and towns to complement the 2012 population estimates for metropolitan areas released in March.  With these two sets o f data it is possible to examine the split between primary city and suburban population growth trends.  My favorite blogger about census data, Bill Frey of the Brookings Institution, quickly released a commentary on these new data with the lead sentences: “Big cities could be making a growth comeback after a rocky decade. Their growth rates are rising and, for the second year in a row, they are growing faster than their surrounding suburbs.” 
 
He goes on to note that: “Among the 51 metropolitan areas with more than one million residents, 24 saw their cities grow faster than their suburbs from 2011 to 2012. That was true of just 8 metro areas from 2000 to 2010. Metropolitan areas exhibiting the largest city growth advantages included Atlanta, Charlotte, Denver, and Washington, D.C.”
 
Frey based his analysis entirely on growth rates, but it is the growth numbers that are more relevant for understanding city versus suburban housing demand.  When population growth numbers are examined, only 12 metros had greater numerical growth in the cities versus in their suburbs. Only seven metros on Frey’s list of 24 cities with higher growth rates than their suburbs also had higher numerical growth (Austin, Columbus, Louisville, Nashville, New Orleans, New York and San Diego).  Cumulatively, overall suburban population growth in the nation’s 51 largest metro areas outstripped overall primary city growth for 2011-2012 by a ratio of almost 2:1 (Table 1).  Atlanta, Charlotte, Denver, and Washington, DC, the four metro areas Frey singled out for their large city growth advantage, had suburban growth numbers that exceeded city growth numbers in 2011-2012.  (Click table to enlarge.)
 masnick_table1
 
 
** Abbreviated name.  Primary cities are defined as the metropolitan area’s largest city and up to two additional cities with populations exceeding 100,000.
Nor are the places where cities have a numerical growth advantage necessarily trending to increase that advantage. Of the 12 metros where cities had more absolute growth in 2010-11, six didn’t sustain that advantage in 2011-12, and four saw a decline in the advantage.  Only two metros had city growth advantages that increased in 2011-2012 (data not shown).
The key to explaining the differences between growth rates and growth numbers, of course, is the fact that for most large metro areas the suburbs have more people than the cities. Of the nation’s 51 largest metro areas, only five had greater primary city populations in 2012.  Three are sprawling metros located in the South and West (Austin, San Antonio and Jacksonville), and the remaining two in this category butt up against other metros and geological barriers to suburban growth (San Jose and Virginia Beach).  The vast majority of suburbs contain more population than primary cities, with Atlanta having more than 11 times as many people living in the suburbs; Hartford, Orlando, Providence, and St. Louis around eight times as many, and Washington, DC over 6 times.  Percentage rates of growth calculated on such disparate population bases are really not comparable.
Primary city population growth has been reinforced in recent years by the aging of the echo boom into the young adult population, because young adults often move to cities to go to college or to work.  Large gains since 2005 in the 18-34 age group have helped turn city growth rates positive in many cases.  There were 3.8 million more 18-34 year olds in 2011 than there were in 2005.   Young adults who move to primary cities of large metros have made the 18-34 age group the largest of the three age groups plotted in Figure 1.  In the suburbs of these metros, the 55+ age group is the largest.
 masnick_figure1
Source: 2010 Decennial Census.  For a list of metro areas see Table 1.
 
There are three main demographic drivers of population change in the suburbs of large metropolitan areas.  First, and most important, is the aging of the suburban population. An aging population creates two pressures for population growth to slow.  The children of these households are themselves becoming adults, fleeing the nest and often heading for the city or to places outside of the 51 largest metro areas.  As these suburban households age, deaths also increase and births decrease.
The second driver of suburban population growth is the housing turnover of aging baby boomers.  Household dissolution from death or divorce could create opportunities to boost population growth from younger and growing households who replace them. Life cycle migration out of the suburbs of large metro areas by smaller baby boomer households as they enter the empty-nest stage or retire from the labor force does the same.  However, the Great Recession and its slow recovery has dampened housing turnover in recent years through a variety of mechanisms.  Among the most salient of these are high unemployment and slow wage growth; owners who would like to sell but are underwater with their mortgages; tight mortgage lending by banks; more people working past age 65; loss of home equity wealth that was counted on to partly fund retirement plans; and lower immigration levels reducing housing demand.
The third driver of population growth in the suburbs has historically been new housing construction that attracts in-migrants.  Again, new construction during the Great Recession and its slow recovery has been at historic lows, and suburban growth has slowed as a consequence.
Looking forward, the aging of the baby boom will continue to dampen population growth in the suburbs.  Most baby boomer households will simply age in place and decline in size. Over the next two decades, some housing that is freed up by household dissolutions by cohorts born before 1945 and by the oldest boomers, or by housing released by these cohorts who do retire to other places, will help mitigate population loss in the suburbs because those buying their houses are likely to be younger than the sellers and have larger household sizes.  But the greatest opportunities for housing turnover in the suburbs will not take place until baby boomer households dissolve in significant numbers beginning in 2030.
During the next decade, some of the factors that have depressed housing turnover in the suburbs in recent years should run their course.  New housing construction will be needed to accommodate adult population growth from aging echo boomers, and possibly the next wave of immigrants. This should largely take place outside of primary cities – where land is more readily available.
While I do concur with Frey’s point that large city population growth is a welcome positive for their health and vitality, I also agree with his suggestion that a rebounding housing market could lure echo boomers, immigrants, and retirees out of large cities in the future.  While suburban growth rates will never approach the levels experienced in their earlier years, the suburbs should continue to grow in population now and well into the future.

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JCHS: A Surge in Hispanic Household Growth?

A Surge in Hispanic Household Growth? The Challenge of Interpreting Short-Term Trends in Datasets that are Occasionally Adjusted

Interpreting year-to-year changes in annual surveys from the Census Bureau can be a tricky business, especially around decennial censuses.  Because it is the largest and most comprehensive count of the population, after each new decennial census is released, the smaller but more frequently issued surveys available from the Census Bureau, such as the Current Population Survey (CPS), Housing Vacancy Survey (HVS) and American Housing Survey (AHS), are updated, or “re-benchmarked” based on the findings from the new decennial census.  Prior to this, these surveys were controlled to extrapolations based off of the prior decennial census. While it is inevitable that ten years of extrapolation can lead controls to drift off course, failing to recognize when and how datasets are re-benchmarked to correct for this drift can lead to misinterpretations about short-term trends.  The danger is that the re-benchmarking adjustment can be misinterpreted as an actual trend that occurred in a single month or year, rather than what it really is: a discontinuity in the data due to an adjustment made to correct the net sum of ten years of extrapolation errors that had accumulated in the dataset since the last decennial census.
Take for instance, the following data overview in a recent online article:“The latest U.S. census figures, for June, show year-over-year Hispanic homeownership increased by 7.3 percent, from 6.2 million to 6.7 million. For black-owned households during the same time, the numbers dipped by 1.3 percent, from 6.3 million to 6.2 million. Likewise, whites’ homeownership also saw a slight decrease of about 1 percent, from 58.4 million to 57.8 million.” – National Journal

On its face, this data leads us to conclude that the number of Hispanic homeowners surged from June 2011 to June 2012, while at the same time the number of homeowners among both blacks and whites dropped significantly, and therefore without growth in Hispanic homeownership the overall number of homeowners in the US would have dropped significantly over the past 12 months instead of growing slightly as was reported.
However, the Census Bureau’s Housing Vacancy Survey (HVS) showed that both Hispanic and non-Hispanic homeownership rates dropped during the June 2011 to June 2012 period, a time wherein Hispanics also suffered higher than average unemployment rates. At first glance, the divergence in the two reports is puzzling. However, on the Census Bureau’s HVS website, there is a short but significant sentence under the “Changes in 2012” section of the Source and Accuracy of Estimates web page:
 
“Beginning in the first quarter 2012, the population controls reflect the results of the 2010 decennial census.”  – HVS Source and Accuracy of Estimates
This note is important, because the distribution of occupied households by tenure, race, and ethnicity of households is based on these population controls.  Therefore, any changes in the number of homeowners by race and ethnicity that spans across the first quarter of 2012 is also incorporating change due to the shift in the distribution of households by age, race, and tenure that occurred with the re-benchmarking of the survey..
The adjustment to Hispanic households due to the re-benchmarking appears to be significant. Looking at the Hispanic share of households in HVS before and after Q1 of 2012, we can see that the re-benchmarking in that quarter led to a significant upwards adjustment that forms a discontinuity in this series (Figure 1).  The existence of a discontinuity is corroborated by data from the Current Population Survey, which re-benchmarked to the 2010 Census in 2011. The CPS Table Creator allows us to see the impact of the re-benchmarking directly by comparing the Hispanic share of households in 2011 under both 2000 and 2010 Census weights.  It shows that the 2010 census weights raise the Hispanic share of households a full percentage point, from 11 to 12 percent, compared to the 2000 census weights.  In short, this all suggests that results from the 2010 Census found that the 2000 Census-based population extrapolations had been underestimating Hispanic household growth in the 2000s, and therefore these household counts needed to be shifted upwards in 2012 as a correction.
Figure 1:  The Shift to 2010-Based Population Controls in Q1 of 2012 in the HVS Coincides with an Apparent Discontinuity in the Hispanic Share of Householders
 
 030713_mccue_figure1

Source: JCHS tabulations of US Census Bureau, Housing Vacancy Survey data.

 
With the change in population controls in the HVS in Q1 of 2012, the amount to which the shift in the distribution of households towards Hispanic households was underestimated incrementally over the last ten years gets corrected all at once, and gets attributed as change measured between Q4 of 2011 and Q1 of 2012.  And as we see in Figure 2, the quarterly change recorded in Q1 of 2012 has a huge influence over our view of the recent trend in household and homeownership growth by Hispanic ethnicity.
Figure 2: Concurrent with the Switch to Census 2010-Based Population Controls, The First Quarter of 2012  Has a Large Influence on the Recent Trend in Hispanic and Non-Hispanic Household Growth 
 
030713_mccue_figure2
Source: JCHS Tabulations of the 1995-2011 AHS
Without the ability to compare alternative HVS household counts for Q1 of 2012 under both 2000- and 2010-based population controls, it is difficult to determine exactly how much of the change in Hispanic and non-Hispanic households and homeowners in 2011 to 2012 was due to the re-benchmarking and how much was due to actual change measurable in the survey.  We refrain from presenting alternative scenarios here, but because the quarter is such an outlier, most assumptions to smooth or discount that quarter of data would conclude with much lower Hispanic household and homeowner growth and much higher growth among non-Hispanics over the past year.
This post first  appeared on Housing Perspectives .
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