How leading indicators can (and can’t) predict RevPAR
How leading indicators can (and can’t) predict RevPAR
05 OCTOBER 2016 8:20 AM

Revenue managers might view leading economic indicators as an Aladdin’s lamp for forecasting RevPAR, but sources said they must take care, challenge myths and adopt new science.

NASHVILLE, Tennessee—Academia and hotel-industry experience have come together to try to divine how the use of economic indicators can lead to better predictions of future revenue per available room.

Speaking at a Hotel Data Conference panel titled “Leading indicators of revenue per available room,” Woody Kim, Ph.D., professor at the Dedman School of Hospitality, Florida State University, and Steve Hood, SVP, research, STR, analysed commonly and not-so-commonly looked-at economic indicators and what effect they might have on predicting RevPAR.

Indicators consist of three types:

  • Leading indicators, which are changes that happen before the present time;
  • current/coincident indicators, or changes that happen at the present time; and
  • trailing/lagging indicators, or changes that happen after the fact.

Just as with the analysis of average daily rates, myths or blind paths have emerged in the science of analysing these economic indicators, Hood and Kim explained.

Does hotel demand increase with personal consumption expenditures?
It might sound logical that higher discretionary income would lead to more travel spend, but Hood said the bivariate relationship (the indicator’s “r” value) for that, r=0.58 (where 100 would be an absolute correlation), was not such a strong correlation.

“The largest three (spends for discretionary income) are housing, healthcare and groceries, with food and lodging coming in fourth,” he said. “Low down is gas, which obviously is volatile. In the recession, the first two segments that dipped were auto and furnishings. Auto has r=0.92, with a one quarter lead, while furnishings have a r=0.97, with a three quarters’ lead. Housing, not surprisingly, has r=0.96, with a four quarters’ lead.”

Among the highest correlation, though, was the r=0.98 score of wages against hotel spend, Hood said.

Does demand rise as gross domestic product improves?
Perhaps, but Hood and Kim said improvements in GDP translated to hotel demand of only r=0.73. Another related variable, the relationship between lodging take-up and gross private domestic investment, fared better, at r=0.80.

New science
Hood said the science of predicting demand, and thus RevPAR, was always changing and malleable.

STR, parent company of Hotel News Now, intends to study more in depth over the next year the relationship between numerous indicators and both pipeline and total revenue per available room, Hood said.

Such mathematics always comes with a caveat emptor, Kim said.

“Relying on the bivariate relationship is easy to understand, but it cannot explain the casual relations between the primary economic indicators and hotel performance,” he said. “The goal is to demonstrate the predictive power of multiple economic indicators in explaining hotel performance.”

Hood and Kim agreed that the best predictors of performance are:

  • Employment rate change, the most salient predictor of U.S. hotel demand;
  • health care and food changes, the most dominant predictor of U.S. hotel demand; and
  • housing changes, the strongest predictor of U.S. hotel demand.

Music City performs
As Nashville has hosted all eight editions of HDC, Hood and Kim gave attendees a deeper look into its hotel performance in relation to leading indicators.

Nashville is one of the U.S.’s fastest-growing cities, and that is evident in the approximately 12,000 hotel rooms in its pipeline, Hood said. He added that apart from the years of the recession, hotel demand in Nashville has increased more or less at the same rate as population growth.

Other leading indicators of Music City’s hotel health were that “ADR versus house prices comes in at r=0.94; demand versus compensation at r=0.96 and demand versus number of employees at r=0.97,” he said.

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