Austin’s Office Market Cycle Dampens with Tightly Coupled Supply and Demand
November 2016 I Vol. 2, ISSUE 11 I Download PDF
Much attention has been given to the strength of the Austin office market. Naturally, however, this has brought increased scrutiny in the form of questions around how long such a strong market can continue. Indeed, markets are dynamic, not static, often undergoing repeated cycles through time whereby the market rises, peaks, falls, and bottoms. Such market cycles typically manifest in vacancy, which measures changes in supply through deliveries of new construction, demand through net absorption, and existing stock inventory. Here, we use vacancy to examine Austin’s office market cycles, including their timing and duration. We then forecast how vacancy is likely to (not) change in coming quarters and years.
Figure 1 shows vacancies for Class A and B office buildings from 2000 through Q3 2016. Percent vacancy in Figure 1 is inversely related to the phase of the market cycle. Increases in vacancy equate with a falling market and decreases in vacancy equate with a rising market. The four stages of CRE market cycle can be seen in the rise, peak, fall, and bottom of office vacancies, a cyclic pattern that repeated itself over two market cycles from 2000-2007 and from 2007-2013. Austin’s CRE market has been cyclical, with a duration of 6.5 - 7.0 years.
Rather than moving into the anticipated falling phase of the market cycle in late 2013 or early 2014, Austin’s vacancy instead continued to decline to a low of 9.1% as of Q3 2016, creating an ever stronger office market. Figure 1 shows our statistical forecast for vacancy rates (dark blue circles) and their 80% prediction intervals (light blue boxes; 80% probability vacancies will be in this range). Vacancy will remain relatively flat in the near term, but may increase some with new deliveries. Currently, Austin has 47 buildings with 2.5 million sq. ft. under construction, but 64.1% is already preleased. Most of this RBA is expected to deliver before 2018. We can expect some modest increases in vacancy up toward 10% in 2017, but then declining quickly back into low-9%-range in 2018 and lower thereafter. Austin’s office market cycle is out of phase due to steady new supply being met by high demand, thereby preventing vacancy from entering the falling phase again.
Commercial real estate (CRE) is not a static, but rather a dynamic market. The industry fluctuates, whereby markets rise, peak, fall, and bottom, a market cycle that repeats itself through time. Although market cycles are often referred to as property “clocks,” this is a misnomer as CRE markets are much more variable than timepieces. For the United States as a whole, the office market cycle tends to be about 10 years, but market cycles vary within and among various metropolitan areas.
Whether an investor, office tenant, broker, or otherwise, an understanding of market cycles is critical, as they are associated with predictable changes in important CRE variables, including supply and demand as measured by vacancy, net absorption, rental rates, and deliveries of new construction. The “sell high, buy low” perspective of financial markets is applicable to CRE market cycles. For example, investors can maximize their return opportunities by timing the buying, selling and construction of their CRE products with down and up markets.
Vacancy is a key market indicator, as it measures changes in supply through deliveries of new construction, demand through net absorption, and existing stock inventory. Vacancy is empty space in sq. ft. of stock inventory of rentable building area (RBA) that is not occupied by a tenant, whether or not that space has a lease obligation or is available for lease or sublease. When expressed as a percentage, vacant sq. ft. is divided by total sq. ft. of stock inventory to produce a percent of market that is vacant. Percent vacancy is inversely related to the phase of the market cycle, such that increases in vacancy rates equate with a falling or bottoming market, whereas decreases in vacancy rates equate with a rising or peaking market.
With vacancy as an indicator variable, we examine market cycles of Austin’s Class A, Class B, and Class C buildings. We evaluate the extent to which Austin’s office market has predictable cycles, and determine the timing and duration of the cycles. In what phase is Austin’s market cycle currently, and where is it going? Forecasting how vacancies are likely to change in coming quarters and years can help tenants, landlords, and investors navigate the office market.
Figure 2A shows percent vacancy for Class A, Class B, and Class C office buildings in Austin from 2000 through Q3 2016. Current and past patterns in vacancy differ most strongly between Class C and Class A and B buildings. Both Class A and Class B office buildings show distinct cyclical patterns in peaks and troughs in vacancy from 2000 to 2013. In contrast, Class C buildings have not shown cycles in vacancy. Class C buildings have averaged 6.3% vacancy over the past 16 years, with a declining trend from a peak of 9.4% in 2004 to 4.1% in Q3 2016.
In contrast with Class C buildings, both Class A and Class B buildings show marked cycles in their vacancies, the patterns of which correspond to the rising, peaking, falling, and bottoming phases of the office market cycles from 2000-2007 and 2007-2014 (Figure 2A and 2B). The primary difference between Class A and B cycles were in their amplitudes, with Class A having bigger peaks and troughs (9-17% difference from peak to trough) than Class B (4-6% difference from peak to trough) (Figure 2A). We focus our analyses of market dynamics by combining Class A and B space (and omit Class C; see Figure 2B), as analyses of Class A and B separately show their cyclical behavior to be similar (aside from exact magnitude of peaks and troughs).
Figure 2B shows Austin’s market cycles of vacancy for Class A and B office space from 2000 to Q3 2016. The four stages of CRE market cycle can be seen in the rise, peak, fall, and bottom of office vacancies, a cyclic pattern that repeats for two market cycles, specifically from 2000-2007 and from 2007-2014. Because percent vacancy is inversely related to the phase of the market cycle, increases in vacancy equate with a falling or bottoming market, whereas decreases in vacancy equate with a rising or peaking market. From 2000-2003, office vacancy increased from <5% to >20%, bottoming in 2004 with vacancy of 20.4%. Then, from 2005-2007 the office market rose from 20% to 11% vacancy, eventually peaking in early 2007 at about 11.6%. This completed one market cycle. From early 2007 to late 2013 this market cycle repeated itself, hitting a peak of 11% vacancy in Q3 2013.
Periodicity is the tendency for recurrent patterns in time which may be regular or irregular in frequency. A regular periodic pattern has peaks and troughs that occur at the same fixed frequency through time, whereas an irregular but still cyclic pattern occurs when the peaks and troughs are repeated but not at the exact same fixed frequency. Austin’s CRE market cycle has certainly been periodic, but our statistical analyses indicate that its frequency is irregular, on the order of 6.5 to 7.0 years for both Class A and Class B buildings (Figure 2B). That is, from start to end, the office market cycle lasts between 6.5 and 7.0 years from peak to peak or trough to trough.
Rather than moving into a falling phase in 2013-2014, vacancy of Austin’s office market (all building classes, see figure 2A) continued to decline for an ever stronger and tighter office market (Figure 2B). In fact, since Q3 2014, vacancy has declined to 9.1% as of Q3 2016. Austin’s office market cycle is out of phase due to steady new supply being met by high demand, thereby preventing vacancy from climbing again.
Figure 1 on the first page shows our forecast for vacancy (blue circles) and 80% prediction intervals (i.e., 80% probability vacancies will be in the range) for the next nine quarters through the end of 2018. Based on the current data, our analyses and forecast indicate that vacancy will remain relatively flat in the near term, but may increase a touch in coming quarters with new deliveries.
Austin has 47 buildings with about 2.5 million sq. ft. of RBA under construction, which is currently 64.1% preleased. Most of this RBA is expected to deliver by the end of Q4 2017. With such preleasing, we can expect some modest increases of vacancy (both some new RBA and space to be backfilled) inching up close to 10%, but then quickly into 2018 dropping back down to low 9% and falling further toward 8% in 2018.
Commercial real estate data on office space were obtained from CoStar following the end of Q3 2016. The statistical analyses and data visualization were performed using the R software and programming language, including the ‘forecast’ package:
R Core Team (2014). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/.
The time series analyses were performed using both exponential smoothing and ARIMA methods. While exponential smoothing cannot adequately capture swings associated with cycles, it is often best for short term forecasts. In our case, the exponential smoothing captured more variation than the ARIMA model, though both were reasonable and on par with the other. We compared accuracy of the two time series and forecasting models using MPE, MAPE, and MASE. We examined the cyclic nature of vacancy in the office market using autocorrelations, which showed a highly significant partial autocorrelation of one lag, and a market cycle of ~28 quarters. Our statistical analyses also showed no seasonal/quarterly influences on vacancy.
Dr. J. Nathaniel Holland is a research scientist with 20 years of experience in using the scientific method to extract information from complex multi-dimensional data. He joined NAI Partners in 2014 as Chief Research and Data Scientist. At NAI Partners, Nat leverages his sharp intellectual curiosity with his skills in statistical modeling to guide data-driven business decisions in commercial real estate. Like many data scientists in the private sector, Nat joined NAI Partners following a career in academia. Prior to taking up data analytics at NAI Partners, he held professorial and research positions at Rice University, University of Houston, and the University of Arizona between the years of 2001 and 2014. Nat is the author of more than 50 scientific publications, and he has been an invited expert speaker for more than 60 presentations. Trained as a quantitative ecologist, he holds a Ph.D. from the University of Miami, a M.S. from the University of Georgia, and a B.S. from Ferrum College.