A Flow-Through Analysis of the US Lodging Industry During the Great Recession

Purpose – The objective of this exploratory study is to investigate the “flow-through” or relationship between top-line measures of hotel operating performance (occupancy, average daily rate and revenue per available room) and bottom-line measures of profitability (gross operating profit and net operating income), before and during the recent great recession. Design/methodology/approach – This study uses data provided by PKF Hospitality Research for the period from 2007-2009. A total of 714 hotels were analyzed and various top-line and bottom-line profitability changes were computed using both absolute levels and percentages. Multiple regression analysis was used to examine the relationship between top and bottom line measures, and to derive flow-through ratios. Findings – The results show that average daily rate (ADR) and occupancy are significantly and positively related to gross operating profit per available room (GOPPAR) and net operating income per available room (NOIPAR). The evidence indicates that ADR, rather than occupancy, appears to be the stronger predictor and better measure of RevPAR growth and bottom-line profitability. The correlations and explained variances are also higher than those reported in prior research. Flow-through ratios range between 1.83 and 1.91 for NOIPAR, and between 1.55 and 1.65 for GOPPAR, across all chain-scales. Research limitations/implications – Limitations of this study include the limited number of years in the study period, limited number of hotels in a competitive set, and self-selection of hotels by the researchers. Practical implications – While ADR and occupancy work in combination to drive profitability, the authors' study shows that ADR is the stronger predictor of profitability. Hotel managers can use flow-through ratios to make financial forecasts, or use them as inputs in valuation models, to forecast future profitability. Originality/value – This paper extends prior research on the relationship between top-line measures and bottom-line profitability and serves to inform lodging owners, operators and asset managers about flow-through ratios, and how these ratios impact hotel profitability.

Second Quarter 2016: Slowdown for Large Hotels Continues; Small Hotels Have Now Slowed as Well

Our Standardized Unexpected Price (SUP) metric continues to show a decline in the price of large hotels, and now also the price of small hotels has eased—even though hotel transaction volume has increased. Although debt and equity financing for hotels remain relatively inexpensive, we are concerned that the total volatility of hotel returns is greater relative to the return volatility for other commercial real estate. If this trend continues, lenders will eventually start to tighten hotel lending standards. Our early warning indicators all continue to suggest that the downward trend in hotel prices should continue into the next quarter. This is report number 19 of the index series.

Third Quarter 2016: Hotels Exhibit Positive Momentum

Our Standardized Unexpected Price (SUP) metric showed an uptick in the price of large hotels during the third quarter of 2016, with a continued decline in the price of small hotels. Although debt and equity financing for hotels were still relatively inexpensive during this quarter, we remain concerned that the increasing relative riskiness of hotels compared to other commercial real estate suggests that lenders will eventually start to tighten hotel lending standards if this trend continues. Our early warning indicators continue to suggest an eventual downward trend in large hotel prices. This is report number 20 of the index series.

Living with Terminal Capitalization Rates: A Look at Real Estate Valuation Model Parameter Setting

This paper examines assumptions about future prices used in real estate applications of DCF models. We confirm both the widespread reliance on an ad hoc rule of increasing period-zero capitalization rates by 50 to 100 basis points to obtain terminal capitalization rates and the inability of the rule to project future real estate pricing. To understand how investors form expectations about future prices, we model the spread between the contemporaneously period-zero going-in and terminal capitalization rates and the spread between terminal rates assigned in period zero and going-in rates assigned in period N. Our regression results confirm statistical relationships between the terminal and next holding period going-in capitalization rate spread and the period-zero discount rate, although other economically significant variables are statistically insignificant. Linking terminal capitalization rates by assumption to going-in capitalization rates implies investors view future real estate pricing with myopic expectations. We discuss alternative specifications devoid of such linkage that align more with a rational expectations view of future real estate pricing.