Research/Results

Moving 52-week average trend lines for lodging business performance metrics in Myrtle Beach area pre-recession and today

by Taylor Damonte, director of the Clay Brittain Jr. Center for Resort Tourism, Coastal Carolina University, and Robert Salvino, director of the Grant Center for Real Estate and Economic Development, E. Craig Wall Sr. College of Business Administration, Coastal Carolina University

If you missed the Grant Center’s 21st annual Economic Growth and Real Estate Summit on March 1, then we recommend you speak with anyone who was there about the invaluable insights they gained into such topics as capital costs and retail trends. Underlying much of the discussion was the question of where we stand with respect to the business cycle. While none of the experts at the event had a crystal ball, and nor do we, the question got us asking ourselves if a technical analysis of the Brittain Center’s data might provide any insights. The moving 52-week average rate of change for lodging business performance reflects the average direction and rate of change during the most recent year compared with the equivalent previous year. Each point on the graphs below reflects the 52-week average rate of change at a historic week in time. The slope of the lines reflects the rate of increase or decrease in the rate of change from week to week. The Brittain Center for Resort Tourism has been tracking the performance of a voluntary sample of nightly-rented hotels, condo-hotels and campsites located in the Myrtle Beach area since January 2003. In January 2006, the center also started tracking a stratified scientifically random sample of weekly-rented vacation properties (VRPs) in this area. The metrics being analyzed by the center are the 52-week average rate of change in average percent occupancy (APO), average daily rate (ADR), and average revenue per unit. Results for these two broad segments, the hotel, condo-hotel and campsite (HC-HC) segment, which consists of sleeping spaces rented on a nightly basis, and VRPs, which are sleeping units that are rented on a weekly basis, are graphed below. Calendar rental weeks are numbered one through 52 and are indicated on the horizontal axis of the graphs. Peaks and troughs in the 52-week average rate of change for each metric are labeled for ease of reading.

To the extent that lodging demand in the Myrtle Beach area results from leisure travel rather than from business travel, area-wide lodging occupancy and the associated revenue per available room (RevPAR) is believed to result primarily from discretionary spending. As such, the rate of change in RevPAR in the Myrtle Beach area may be thought of as one leading indicator of the business cycle. Consequently, the fact that the center’s estimate of the 52-week average moving rate of change in RevPAR fell to below zero at the end of Spring 2018 for the first time since August 2010 is interesting. Going back to the period prior to when the great recession is now known to have transpired, readers will want to note that in September 2005, the 52-week average rate of change for the center’s measure of APO fell to -2.2 percent. However, at that time the average rate of change in average daily rate (ADR) was still up 2.5 percent, leaving the rate of change in RevPAR at that time barely-positive. The rate of change in APO, ADR, and RevPAR rebounded during the following year and peaked by September 2006. Economic historians may recall that the Dow Industrial Average did not peak until July 2007. By that time, the rate of change in APO for the center’s sample of HC-HC properties had already dropped to negative 2 percent, and when it did the rate of change in ADR also became negative, dropping 2.5 percent below its long term average rate of change, which brought RevPAR into negative territory as well. While the moving average rate of change in APO for the center’s sample bottomed in March 2009, about the same time that the Dow bottomed, ADR, a measure of price, was sticky, holding on for an additional nine months before bottoming. As mentioned above, the moving average rate of change in RevPAR did not turn positive again until August 2010. Moving the discussion to current day, during the period May 2015 to February 2019, the rate of change in APO has ranged from 3.7 percent to -3.4 percent. However, during most of that period, until February 2018, the rate of change in ADR, being sticky, remained above 4 percent, so the rate of change in RevPAR remained positive. It wasn’t until May 2018 that the rate of change in RevPAR fell to below zero. The rate of change in APO rebounded during Summer 2018, lifting RevPAR once again. Nevertheless, by the end of September 2018, the moving average rate of change in RevPAR for the center’s voluntary sample of HC-HC properties was again negative. Of course, the beginning of this period of negative performance does coincide with the timing of Hurricane Florence. However, again we point out that as recently as May 2018 the moving average rate of change in RevPAR had already been negative for a short period of time. For a more fine grained analysis of lodging performance during the Hurricane Florence time frame, readers may want to look at our report in the November 2018 issue of the Grand Strander.

As mentioned above, the center began tracking performance for VRPs in January 2006. Peaks and troughs in the moving average rate of change for that segment are labeled below as well. The long-term 52-week average rate of change in APO for the Brittain Center’s scientifically random sample of Horry County VRPs (217 units weekly) has been 0.4 percent. Generally speaking, the business performance graphs for VRPs suggest a higher level of momentum than do the HC-HC business performance graphs, leading to higher peaks, and lower troughs in the trend lines. The rate of change for APO for the VRPs seems slower to respond to changes in the rate and direction of change in ADR and vice versus, than does the rate of change for these metrics in the HC-HC segment.

To summarize, the long-term 52-week moving average rate of change for the center’s sample of weekly-rented VRPs has been 3.6 percent. This metric current stands at -0.8 percent. The long-term 52-week average rate of change in RevPAR for the center’s sample of nightly rented HC-HCs since January 2006 has been nearly 2.5 percent. This metric currently stands at -1.9 percent, though it has been rising since the end of 2018. It should also be noted that though the long term average rate of change in APO for the center’s sample of HC-HCs since 2006 has been zero, this does not mean that there has not been a dramatic increase in demand for visitation in the area. In fact, the opposite is true. This can be seen in both hospitality fee and accommodations tax collections, and in the tourist population data tracked by D.K. Shifflet and Associates. For example, the Shifflet results indicate that the number of tourists visiting the area has grown from 14.6 million in 2006 to 19.6 million in 2017, an increase of more than 34 percent. With APO remaining constant, this suggests that there has been a roughly equivalent increase in the supply of lodging inventory during that time. This increase in inventory has been successfully absorbed into the local market, and along with it has come the associated direct, indirect and induced  growth  in jobs.

No one can say where the business cycle will take us in a year’s time, though the center’s current analysis of the 52-week moving average rate of change in the RevPAR of its sample of nightly-rented HC-HCs in the Myrtle Beach area does suggest at least one reason that some people may ask the question. If you would like to explore how you could participate in the center’s research and gain access to its current segment-level 52-week moving average results at any time, and to its weekly forecasts going out as far as six weeks into the future, please contact Taylor Damonte, tdamonte@coastal.edu, at Coastal Carolina University.