July data show 2.7 million extra young adults living at home

Updating this post with July data

Catherine Rampell tweeted a link to a Zillow analysis showing 2.2 million adults ages 18-25 moving in with their parents or grandparents in March and April. Zillow’s Treh Manhertz estimates these move-homers would cost the rental market the better part of a billion dollars, or 1.4% of total rent if they stay home for a year.

We now have the data through July from the Current Population Survey data to work with, so I extended this forward, and did it differently. CPS is the large, monthly survey that the Census Bureau conducts for the Bureau of Labor Statistics each month, principally to track labor market trends. It also includes basic demographics and living arrangement information. Here is what I came up with.*

Among people ages 18-29, there is a large spike of living in the home of a parent or grandparent (of themselves or their spouse), which I’ll call “living at home” for short. This is apparent in a figure that compares 2020 with the previous 5 years (click figures to enlarge):

six year trends

From February to April, the percentage of young adults living at home jumped from 43% to 48%, and then up to 49.4% in June and 48.7% in July. Clearly, this is anomalous. (I ran it back to 2008 just to make sure there were no similar jumps around the time of the last recession; in earlier years the rates were lower and there were no similar spikes.) This is a very large disturbance in the Force of Family Demography.

To get a better sense of the magnitude of this event, I modeled it by age, sex, and race/ethnicity. Here are the estimated share of adults living at home by age and sex. For this I use just July of each year, and compare 2020 with the pooled set of 2017-2019. This controls for race/ethnicity.

men and women

The biggest increase is among 21-year-olds, and women under 22 generally. These may be people coming home from college, losing their jobs or apartments, canceling their weddings, or coming home to help.

I ran the same models but broke out race/ethnicity instead (not separately for gender White, Black, and Latino, as the samples get small).

white black latino

This shows that the 2020 bounce is greatest for Black young adults (below age 26) and the levels are lowest for Latinos (remember that many Latinos are immigrants whose parents and grandparents don’t live in the US).

To show the total race/ethnic and gender pattern, here are the predicted levels of living at home, controlling for age:

raceth-gender

The biggest 2020 bounce is among Black men who have the highest overall levels, 59%, and White women having the lowest at 45%.

In conclusion, millions of young adults are living with their parents and grandparents who would not be if 2020 were like previous years. The effect is most pronounced among Black young adults. Future research will have to determine which of the many possible disruptions to their lives is driving this event.

For scale, there are 51 million (non-institutionalized) adults ages 18-29 in the country. If 2020 was like the previous three years, I would expect there to be 22.2 million of them living with their parents. Instead there are 24.9 million living at home, an increase of 2.7 million from the expected number (numbers updated for July 2020). That is a lot of rent not being spent, but even with that cost savings I don’t think this is good news.


* The IPUMS codebook, Stata code, spreadsheet, and figures are in an Open Science Framework project under CC0 license here: osf.io/2xrhc.

4 Comments

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4 responses to “July data show 2.7 million extra young adults living at home

  1. Hi Phillip
    Any chance I could get the raw data behind the first and last charts? Of course I would attribute the data to you. Thank you

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    • Hi Alex, if by raw data you mean the data to make the figures, yes, I’ll paste it below. If you mean the CPS microdata, I’m not supposed to share that but I can help you get it. Please link to the post. Happy to chat if you like.

      First figure:
      year month with parents
      2008 1 38.55665
      2008 2 38.87914
      2008 3 38.69946
      2008 4 38.66726
      2008 5 39.61969
      2008 6 39.62636
      2008 7 40.25215
      2008 8 39.5493
      2008 9 38.42844
      2008 10 38.30681
      2008 11 38.84722
      2008 12 39.82227
      2009 1 39.74659
      2009 2 39.98518
      2009 3 39.70016
      2009 4 39.59893
      2009 5 40.50216
      2009 6 40.71937
      2009 7 41.13106
      2009 8 40.94006
      2009 9 39.74147
      2009 10 39.34261
      2009 11 39.38538
      2009 12 39.27766
      2010 1 40.19937
      2010 2 40.15211
      2010 3 40.97244
      2010 4 40.84019
      2010 5 41.04207
      2010 6 41.67889
      2010 7 42.25612
      2010 8 42.00253
      2010 9 40.15858
      2010 10 40.34335
      2010 11 40.23833
      2010 12 40.73026
      2011 1 40.7027
      2011 2 40.59685
      2011 3 41.41482
      2011 4 41.44543
      2011 5 42.16846
      2011 6 42.74885
      2011 7 43.15535
      2011 8 42.42809
      2011 9 41.31924
      2011 10 41.51589
      2011 11 41.83724
      2011 12 42.62847
      2012 1 43.08289
      2012 2 42.64241
      2012 3 43.03194
      2012 4 43.0605
      2012 5 43.5802
      2012 6 43.83187
      2012 7 43.74673
      2012 8 43.17284
      2012 9 42.36815
      2012 10 42.26324
      2012 11 42.42387
      2012 12 42.16727
      2013 1 42.75641
      2013 2 42.56127
      2013 3 42.57597
      2013 4 42.95881
      2013 5 43.57063
      2013 6 44.07897
      2013 7 44.56165
      2013 8 43.63096
      2013 9 42.49306
      2013 10 42.43233
      2013 11 42.40975
      2013 12 43.22675
      2014 1 43.25664
      2014 2 42.98183
      2014 3 42.86612
      2014 4 42.58364
      2014 5 43.45578
      2014 6 43.63179
      2014 7 44.36956
      2014 8 43.52089
      2014 9 41.74788
      2014 10 41.94676
      2014 11 41.37336
      2014 12 42.33097
      2015 1 42.56209
      2015 2 42.5211
      2015 3 42.68177
      2015 4 42.35693
      2015 5 43.18686
      2015 6 43.49438
      2015 7 43.5111
      2015 8 43.22837
      2015 9 41.9293
      2015 10 41.52843
      2015 11 41.71131
      2015 12 42.21806
      2016 1 42.5613
      2016 2 42.95105
      2016 3 42.54842
      2016 4 42.15552
      2016 5 42.73203
      2016 6 42.85725
      2016 7 42.96103
      2016 8 42.56576
      2016 9 41.44548
      2016 10 41.38429
      2016 11 42.08328
      2016 12 42.091
      2017 1 42.23372
      2017 2 41.89931
      2017 3 41.89879
      2017 4 41.98476
      2017 5 42.44712
      2017 6 43.23956
      2017 7 43.37757
      2017 8 43.69612
      2017 9 42.53176
      2017 10 42.40167
      2017 11 43.29571
      2017 12 43.04031
      2018 1 42.60947
      2018 2 42.14982
      2018 3 41.35093
      2018 4 41.60259
      2018 5 42.26979
      2018 6 43.22698
      2018 7 43.55971
      2018 8 42.69726
      2018 9 42.05385
      2018 10 42.3882
      2018 11 43.07485
      2018 12 43.07066
      2019 1 42.7605
      2019 2 42.18407
      2019 3 42.47921
      2019 4 42.88332
      2019 5 43.3389
      2019 6 43.4116
      2019 7 43.5669
      2019 8 42.54157
      2019 9 42.18876
      2019 10 42.22175
      2019 11 42.87265
      2019 12 42.98013
      2020 1 42.41199
      2020 2 42.88401
      2020 3 45.17418
      2020 4 47.9059
      2020 5 48.27187
      2020 6 49.35247
      2020 7 48.74189

      Last figure:
      2017-2019 2020
      White men 0.458 0.508
      White women 0.395 0.449
      Black men 0.516 0.593
      Black women 0.427 0.485
      Latino men 0.449 0.500
      Latino women 0.419 0.470

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  2. Vally Azar

    Idk if I represent a large enough demographic to count but within a few months of me living at home my parent started demanding rent. So I’m kind of participating in the rent economy by alternative means even though I’m “living at home”.

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