A strong performance for the Grand Strand’s hotels, condo-hotels, and campsites during the first half of 2019. So far in 2019, average occupancy for the Center’s voluntary sample of hotel, condo-hotel and campgrounds rented nightly is up by 1.7 occupancy points, or 3.2 percent, compared with the equivalent period of 2018. During the same time, the average daily rate increased by 1.3 percent, raising revenue per available room down by 4.5 percent.
by L. Taylor Damonte, Ph.D., director of the Clay Brittain Jr. Center for Resort Tourism, 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 lodging RevPAR in the Myrtle Beach area may be thought of as a 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 for the center’s sample of nightly-rented HC-HC lodging properties in the Myrtle Beach area rebounded during the following year and peaked in September 2006. Economic historians may recall that the Dow Industrial Average peaked 10 months later in 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. The moving average rate of change in HC-HC APO in the Myrtle Beach area led the business cycle coming out of the recession as well, bottoming in March 2009, six months prior to the Dow’s bottom in that year. Moving the discussion forward in time to the period since May 2015, the rate of change in APO for the center’s sample of HC-HCs has ranged from 4.7 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. Consequently, not until May 2018 did the rate of change in RevPAR turn negative. The rate of change in APO rebounded during summer 2018, lifting the rate of change in RevPAR above zero 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 turned 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.
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.
As mentioned above, the center began tracking performance for VRPs in January 2006. The long-term 52-week average rate of change in APO for the 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 versa, than does the rate of change for these metrics in the HC-HC segment.
So where does the above analysis leave us? To summarize, the long-term 52-week moving average rate of change in RevPAR for the center’s sample of weekly-rented VRPs since 2005 is 3.6 percent. This metric currently stands at -3 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 2.4 percent. This metric currently stands at -4.5 percent. Part of the sharp relative decline since this analysis was first published electronically in March 2019 is that last year the Easter and Passover religious holiday period included the last weekend of March and the first week of April. This can cause a temporary spike in the moving 52-week average trend lines. For example, in late April 2012 the moving average rate of change in APO briefly dipped below zero because during the year before Easter occurred at that time of year. Two weeks later, the moving average rate of change rebounded and began a rally that continued until June 2014.
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 APO, ADR, and RevPAR of its samples of lodging properties in the Myrtle Beach area prior to the great recession, and now, does suggest at least one reason that economists may want to watch the relative strength of lodging business performance in this market. The moving average rate of change in APO for the center’s random sample of VRPs in the Myrtle Beach area rallied briefly to 2.4 percent at the beginning of 2019, though it has since turned negative again. It seems a statement of the obvious to write that the Myrtle Beach area economy relies on the growth of tourism, and that the rate of growth in lodging business performance is an important indicator of tourism growth. Given the current rate of change in the center’s 52-week moving average metrics for lodging business performance, researchers at the center will be paying close attention to these business performance indicators at the end of the Easter and Passover period of 2019 and during the summer to come. 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, contact Taylor Damonte, email@example.com, at Coastal Carolina University.
The Myrtle Beach/Conway/North Myrtle Beach metropolitan area is the second-fastest growing metropolitan area in the United States for the third year in a row, according to the latest data from the U.S. Census Bureau. The Myrtle Beach area grew 3.8% last year with more than 1,400 people per month relocating to the area. In the last eight years, more than 104,000 people relocated to the Myrtle Beach area.
Business leaders and elected officials from Horry County often point out how important our local economy is to the overall state economy. Legislators from around the state know that Horry County is helping pay for the projects their constituents depend on. So, with the help of our Business Intelligence Officer, we crunched the numbers. There’s no need to speculate, Horry County is the engine for the state’s economy. Here are the facts: