ATLANTA—PKF Hospitality Research, LLC (PKF-HR) released the results of their latest assessment of the accuracy of their Hotel Horizons forecasts for the U.S. lodging industry.
This is the third periodic review conducted by PKF-HR since 2005 and is an important and critical component of the firm’s forecasting efforts. “When we initially entered the econometric forecasting business 14 years ago, we committed ourselves to a process of continuous self-evaluation,” stated R. Mark Woodworth, president of PKF-HR. “The findings from these analyses inform the nuts and bolts of our ongoing forecasting efforts. Plus it enables our clients to overtly see that we strive to provide them with the most accurate forecasts upon which to make their important decisions.”
PKF-HR’s Hotel Horizons is a series of hotel forecast reports that analyze the historical and expected performance of U.S. lodging markets. Driven by a series of econometric forecasting models, the Hotel Horizons reports cover five years of supply, demand, occupancy, ADR and RevPAR for 50 major U.S. markets, as well as six national chain-scale segments and six national location categories.
Within each market forecast, separate estimates are prepared for upper-price and lower-price hotels. The model relies on historical lodging data from Smith Travel Research, as well as historic and forecast economic data from Moody’s Analytics.
“Overall, we remain pleased with our demonstrated accuracy. We have learned that the accuracy of our forecasts varies with changes in the business cycle, as well as size of the market to be forecast,” said Woodworth.
“As we have seen in the past, the long-term accuracy of our national forecasts of the U.S. lodging market in its entirety, the chain-scales and the location categories, is very high,” said John B. (Jack) Corgel, PhD., the Robert C. Baker professor of real estate at the Cornell University School of Hotel Administration and senior advisor to PKF-HR. “One area where we have seen improvement since our last assessment is in the accuracy of our short-term forecasts. We attribute the improvement in short-term forecast accuracy to the lessons learned during our 2010 accuracy assessment.”