Real personal income, not gross domestic product, is the best indicator to predict hotel demand.
ATLANTA—Market participants and analysts should pay close attention to periodic reports of personal income as the primary indicator of underlying strength or weakness of hotel demand.
While other economic measures correlate well with hotel demand across the United States and among chain scales and markets, it is personal income—specifically for modeling purposes real personal income—that dominates other economic measures for reliability and consistency.
Importantly, in the context of rising financial and global economic volatility, macroeconomic forecasters expect RPIs in the U.S. to rise between 3% and 4% over the next few years. Why is RPI such a reliable and consistent indicator of hotel demand? How can hotel managers and investors use this knowledge to make more informed decisions?
The personal income and hotel demand relationship
Over the past two decades of forecasting hotel markets, we found RPI to be the most reliable variable for explaining variation in hotel demand throughout the cycle. Hotels are exhibiting strong financial performance parallel with employment gains, income growth and other economic indicators.
Exhibit 1 presents compound annual growth rates from 2010 to present for U.S. hotel demand, RPI, real GDP and total employment. The same data is provided for several large markets. This data shows that in every market real personal income CAGRs equaled or exceeded those for real GDP and employment, in some cases by more than 100 basis points. Also, the real personal income CAGRs match hotel demand CAGRs more closely than other measures. Employment experienced strong growth during the past two years, while RPI growth has been consistently strong since 2010.
Five categories that comprise personal income
Dissecting the U.S. Bureau of Economic Analysis’ personal income measure into its components lends insight as to why real personal income is the dominant indicator of hotel demand strength. The BEA derives personal income from five categories of income: employee compensation; proprietors’ income; rental income; personal income on receipts from assets; and personal current transfer receipts.
Wage stagnation since the Great Recession has been a much-discussed but somewhat-misunderstood topic. Evidence exists that wage growth rates during the past few years are not substantially different than historical rates. Also, recent nominal wage growth, while hovering around 1%, must be considered in the context of very low inflation, recording year-over-year increases of less than 1% during most months since 2013. The other categories captured in the personal income data have overridden these weak wage gains as indicated by the 2.7% CAGR for real personal income from 2010 through 2015 (see Exhibit 1). The post-Great Recession RPI growth is well below the long-run (1980–2007) rate, which is approximately 6%.
Exhibit 2 presents the mix of personal income categories from 1970. Even as far back as 1970, wages and salaries only comprised 60% of personal income. This indicates that hotel demand has increasingly becoming a function of non-wage and salary income sources.
Why not GDP, PCE and disposable income for hotel demand forecasting?
In the previous section, we examined the categories of income that comprise the BEA’s measure of personal income. This metric is one among many governmental agency measures that tracks incomes within the U.S. Most notably, the BEA produces GDP and its component part personal consumption expenditures for aggregate income and consumer spending. The U.S. GDP consists of the four general output categories this equation:
- GDP = PCE (C) + business investment (I) + government spending + net exports (imports minus exports)
The main reason GDP is not as reliable an indicator of hotel demand as personal income is that the four components of GDP sometimes unexpectedly move in opposite directions, thus masking the strength of the two components that have the most meaning to hotel demand, personal consumption expenditures (C) and business investment (I).
As shown in Exhibit 3, this is what happened during several quarters since the Great Recession. Also, from 2006 to early 2008 GDP grew as the result of net exports and government spending, yet hotel demand was flat or negative as businesses cut back on investments and consumers began to spend less. At the national level, GDP works almost as well as real personal income in explaining hotel demand, but at the local level metropolitan real personal income dominates metropolitan GDP.
The correlation between personal income and personal consumption expenditures is quite high, so PCE may explain variation in hotel demand about as well as personal income in many forecasting models. Yet, PCE measures actual consumption expenditures while personal income informs about potential consumption expenditures. Forecasts of historical expenditures, if used to drive hotel demand forecasts, may not pick up shifts in expenditure patterns whereby personal income avoids this problem.
Why personal income and not disposable or discretionary income?
Personal income (PI), disposable income (D1I) and discretionary income (D2I) are related in the following ways:
- D1I = PI – direct taxes, where direct taxes include federal and state income taxes while indirect taxes, not reflected in the previous equation, include value add taxes, sales taxes and employer contributions to social security; and
- D2I = D1I – typical expenses, to maintain a certain standard of living (Rent or mortgage payments, utilities, insurance, medical, title, transportation, property maintenance, child support, food and sundries).
We trust forecasts of the aggregate personal income but have less faith in future estimates of direct taxes and certain specific living expense deductions. This is in part the result of the fact that federal and state tax law changes affect disposable income and are not easily forecast. Likewise, discretionary income is challenging to predict given the high level of volatility in food and utility prices.
There is evidence a shift in correlations among economic variables has occurred since 2010. Exhibit 4 shows the correlations among the alternative economic variables. We find that the association between changes in hotel demand and real personal income remained steady in recent years, while real GDP, disposable Income and gross national income have proven less consistent.
Personal income has increasingly become a function of non-wage income over recent decades as the economic activity has changed. What is important for the hotel industry is personal income reflects the potential for individuals to engage in travel and serves as a general indicator for judging the financial well-being of businesses to support travel. Since 2010, real personal income has more accurately matched hotel demand growth than other metrics, including employment and GDP. We forecast above long-term average growth in personal income—a signal of continued strong hotel demand.
Jack Corgel, Ph. D., is Managing Director of CBRE Hotels’ Americas Research and Professor of Real Estate at the Cornell University School of Hotel Administration.
Brett Edgerton is an Economist at CBRE Hotels’ Americas Research.