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The homeownership rate vs. U.S. apartment performance

Oct 19, 2017, 16:03 PM by User Not Found

The U.S. homeownership rate—which stands at 63.7% (Q2 2017)—seems to have stabilized after falling below 63.0% for the first time since 1965. The drop is no surprise in the wake of a global financial crisis and a very large cohort of Millennials that have been delaying marriage, child-bearing and homeownership for a variety of reasons.

We set out to answer a few related questions:

  1. Is there a relationship between changes in the homeownership rate and multifamily performance (i.e. rent growth)?
  2. Can we expect further change in homeownership—and can we disentangle the drivers of that change?
  3. Which markets are most likely to experience future change in homeownership, and for what reasons?

We use the model[1] to demonstrate the impact of changes in homeownership on apartment rents, “shocking” the national apartment market by permanently raising the homeownership rate by one percentage point. The results indicate that, all else being equal, a permanent one percentage point increase permanently lowers rent levels by 2% over a two-year period (Figure 1).

Figure 1. The Effect of Changes in Homeownership on Rent, Quantified

Homeownership and Apts - Fig 1

Source: CBRE Econometric Advisors, Q2 2017.

Can we reasonably expect future change in the homeownership rate? We believe so, but we suspect it will vary from market to market. We focus on two primary forces that could bring change—one specific and one broad:

  1. Shifting age demographics. The older you are, the more likely you are to head a household and to own the home you’re in. This is true regardless of where or when. Even if preferences never change and we go on heading and owning households the way we do today, the relatively large, younger cohorts will naturally age into greater rates of homeownership.
  2. Shifting preferences (i.e. mean reversion). We are well below our long-run (relatively stable) homeownership rate. If history is an indication of the future, we should expect some degree of reversion to the mean.

The Data:

To help guide investment strategy, we wrote an algorithm to aggregate complex data at the market level. We used:

  • The Census’ American Housing Survey (AHS) micro-sample (household-level) data
  • 40+ years of history across a variety of file formats and other challenging nuances
  • Twelve chosen markets
  • Moody’s population forecasts by age

Methodology:

To examine the impact of demographic shifts on market-level homeownership, we applied today’s headship and homeownership rates to Moody’s forecasted populations by age.

To examine the effect of preferential shifts, we assume (naively) that headship and homeownership will return to their long-run means.

Figure 2: The Results

Homeownership and Apts - Fig 2

Source: Moody's, U.S. Bureau of the Census, CBRE Econometric Advisors; Q2 2017.

Summary:

For Los Angeles, Phoenix and Miami:

  • An aging population & mean-reverting preferences should push homeownership
  • All else equal, this would dampen multifamily demand & performance

For Seattle and Denver (also, Houston, Atlanta and Detroit):

  • The demographic outlook is favorable for multifamily…
  • But mean reversion could raise the homeownership rate

For Boston & New York (also Washington, D.C. and Chicago):

  • The demographic outlook is favorable for multifamily…
  • And mean reversion could lower the homeownership rate

As always, such results come with some important caveats:

  • Unlike other markets, Los Angeles homeownership has not been stationary over time. In fact, it has been steadily trending down over the past 40 years and a mean reversion is not a reasonable expectation in this market.
  • Despite rising homeownership rates, the number of renter-occupied households will continue to grow in most markets, driven by population growth and household formation. Chicago and Detroit will remain flat, while growth in New York City and Boston will be weak.

 


[1] We used a VAR for this analysis, although we did find consistent results under a variety of econometric specifications.

 

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