Predicting Lodging Demand Trends in the U.S. Hotel Industry

John W. O’Neill, Yuxia Ouyang

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Future economic trends in the U.S. hotel industry are often discussed and debated at hotel investment conferences and elsewhere, typically without discussion of the underlying economic indicators that lodging prognosticators should track to predict lodging demand growth and decline. This research endeavors to rank the predictive ability of various economic variables and determine which may be the strongest predictors of lodging demand trends. In addition, we seek to identify a relatively small group of economic variables, that is, a consideration set that may best serve lodging prognosticators with determining the future direction of lodging demand. In our analyses, we evaluate both economic indicators and quarterly change in those indicators. Furthermore, we analyze autoregressive and moving average features of lodging demand in recent years. We present models that prognosticators may use to project lodging demand trends. Although there are a variety of variables that serve to predict lodging demand trends, gross domestic private investment (GDPI) is noted as a particularly effective predictor of lodging demand trends, and it has been effective over all the recent time periods we studied. This information should be beneficial to lodging practitioners/analysts as well as academics.

Original languageEnglish (US)
Pages (from-to)237-254
Number of pages18
JournalCornell Hospitality Quarterly
Issue number3
StatePublished - Aug 1 2020

All Science Journal Classification (ASJC) codes

  • Tourism, Leisure and Hospitality Management


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