Intelligent Investment

Recent Urban Migrations and Hotel Markets

Long-run future economic activity and hotel business opportunity will materialize in outlying areas of major MSAs, medium and small cities, and tax and cost-of-living friendly states. Many urban centers and high tax states run counter to the trend.

June 18, 2021 9 Minute Read

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Unless you were assigned to work at the International Space Station during the past 16 months you know that during this period numerous U.S. city households and businesses relocated. The reasons include fear of COVID-19 contraction (early), greater opportunity to remotely work following the relaxation of pandemic stay-at-home orders, lower taxes and overall cost of living, and avoidance of rising crime and urban decay. Relocations can affect the political economy of subject locales in the U.S. Less clear are the possible consequences of recent migrations on the demand and supply dynamics in industries such as hospitality. (For more on space stations and hospitality check out ‘Could the Next Space Station Be a Hotel? Commercializing space is no longer a far-out idea. In fact, NASA is fully on board,’ Bloomberg Opinion May 6, 2021).

A May 1st Wall Street Journal article titled ‘The Great Culinary Migration’ chronicles cases of big names in the food world exiting large cities for the countryside and beaches. The potential consequence - if you did not move from the big city and favor fine dining you may need to take a road trip. For the hotel segment, cases can be made that the long-term effects of recent migrations could be either negligible (i.e., business as usual) or substantial. I consider both cases in this article. I began researching this topic with the belief that the demand mix for hotels – locations, room rate segments, and purpose of stay – will be noticeably altered coming out of the pandemic. My mind was changed a little after examining the empirical evidence although the prevailing trends and theory still signal that my initial predictions could be correct in the long run.

Theory Tell Us That….

During my teaching career whenever I proclaimed at the beginning of a class ‘today we will cover the theory of X’ the students who hedged their class attendance by sitting near the exits immediately and quietly departed. Others who decided to tough it out through the theory lecture heard me say that theory can help you make sense of situations encountered during your professional life that are otherwise confusing. The effects on hotel markets of the well-publicized moves of households and businesses during 2020-21 presents one of these situations.

Migration inside the borders of the U.S. since mid-2020 has taken two general forms – state-to-state (STS) and high density-to-lower density (HDLD). Some overlap exists across the two forms although for simplicity STS relocations are defined here to involve long distance moves and HDLD moves within the same MSA, nearby (e.g., moves from Manhattan to New Jersey are HDLD), and to rural locations. Let us assume the reasons behind STS and HDLD relocations are as stated in the first paragraph of this article. To understand whether the recent trends will continue or possibly operate in reverse, some longstanding economic theories from urban economics offer guidance.

Theory of STS Moves – Sixty-five years ago Charles Tiebout presented a hypothesis linked by a series of assumptions to competitive market theory.[1]  Simply stated, his idea is that many political jurisdictions exist with different collections of public services and tax structures; and consumers of these services and payers of associated taxes will relocate to get the best deals (i.e., popularly referred to as ‘voting with your feet’). The hypothesis could explain both STS and HDLD relocations but given the imbalance of taxes and growing availability of privately produced services (e.g., private and quasi-private charter schools) the explanation nicely fits with household and business STS moves from high tax to low tax states. The migration trend toward lower tax jurisdictions began before COVID-19 and before limitations on SALT deductions. Nevertheless, it is commonly held by commentators and researchers that the pandemic heightened the trend. The prediction coming out of theory for the post-pandemic era is that the steeper trend line will continue if large statewide public services/tax liability imbalances persist, and technology driven work anywhere adoption continues. Both seem likely!

Theory of HDLD Moves – The tradeoff between transportation costs and rents (and housing costs) is an important concept in urban economics for understanding how the land use patterns of cities change. Richard Muth was one of the pioneer model builders who refined this tradeoff.[2]  Earlier, economists recognized the importance of the bid/rent curve – the negative relationship between rents and distance from urban centers. Stated differently, rents and house prices are higher near city employment and other centers (e.g., retail, entertainment, cultural) and decline with distance farther away. The reason is that people seek to minimize the cost of getting to places they need or want to frequently visit. People also prefer cheaper location prices. Hence the tradeoff that Muth formalized in his model between housing costs and avoiding transportation costs, including the time to travel.

Muth’s model predicts that changes in either transportation costs or housing prices will change equilibrium locations. A reduction in transportation cost resulting from additional lanes added to major highways, for example, incentivizes households to move farther from city centers. Potentially the largest ever reduction in transportation cost has come with videoconferencing. The surprisingly gradual adoption of videoconferencing suddenly spring boarded during the COVID-19 pandemic and arguably serves as the foundation for the rise of working hours in less dense locations than city centers.

A second trade-off must be considered to formulate a long-run prediction of city internal structure changes. Agglomeration is a term to describe the phenomena of establishments and people beneficially clustering in urban centers. The advantages of nearness have been attributed to benefits from sharing, matching, and learning. Glaeser (1999) and others highlight innovation from creation and acquisition of shared knowledge as one of the most important agglomeration benefits.[3]  High density urban centers foster innovation. Videoconferencing enables efficient non-location specific communication likely without the same level of innovation.

A note on the comparative advantages and disadvantages of teleconferencing. Several studies pursued the question of comparative advantage including Danstadli et. al. (2012) who conduct surveys that directly address the purposes for each mode of business communication.[4]  This study and others find that home telecommunication provides a useful purpose for exchanging information but does not fulfill the needs of firms for creative thinking and making new business connections. The research suggests that the interpersonal issues surrounding home teleconferencing may not be as limiting to straightforward information exchange as for creative thinking and new business development.

The prediction coming out of urban economic theories for the post-pandemic era is that declining transportation costs from advancements in telecommunication technology will continue to induce lower densities across major U.S MSAs. However, the benefits of agglomeration represent a significant friction to dramatically lower densities until similar benefits can be realized without clustering. Evidence on pandemic–related density and innovation effects will come from future measurements and empirical research. Perhaps the hybrid working model will prove optimal for serving the needs of employees and those of businesses with respect to daily operations and innovation.


Most studies conducted during the latter stage of the pandemic report results for both types of relocations. I reviewed a sample of ten empirical studies from various sources. Exhibit 1 presents the date and sponsor of each study along with the data source(s) and major findings. A few reoccurring themes emerge from the results of these studies. First, a sizeable majority of recent relocations happened within the same geographic area. This finding suggests movers took advantages of lower transportation costs from teleconferencing which allowed them to benefit from lower housing prices (Muth model) and improved tax/public service relationships (Tiebout model) while remaining within commuting distance to their offices. Second, net out-migration from major U.S. cities was quite modest in relation to total population (e.g., 3-5%) although large in number. Anecdotal evidence suggests that many of these movers are knowledge workers in the top 10 percent of all wage earners. Yet the impact on smaller city and suburban populations from in-migration was meaningful both in percentage terms and numbers. Third, movers were young and mobile who work in jobs that can be remotely conducted. Fourth, New York City, San Francisco, and Seattle urban neighborhoods experienced by far the most out-migration. These cities are described as outliers and largely responsible for the pandemic relocation phenomenon to be labeled an ‘exodus.’ The idea that recent trends were amplified during the pandemic resonates.


Bottom Lines – Back to Thinking about Hotel Markets, Finally!

The findings from the empirical studies just presented and one’s own intuition leads to a set of straightforward conclusions about near-term shifts in hotel markets in the wake of the pandemic. New York, San Francisco, and possibly some other high cost-of-living large cities that experienced upticks in crime and civil unrest will be discounted. Second and third tier cites will receive a lift. Luxury, destination resorts, mid-price, extended stay, and lower price hotels will do well with continued strengths in leisure business however upscale, urban, upper-upscale hotels that depend heavily on business travelers and groups can be expected to underperform.

What about the long-term shifts? Recall, I advised my students to rely on theory when confronted with never-before-encountered situations. If Tiebout was still theorizing he would lecture us on the economic rationality of households and businesses moving to greener pastures to avoid persistent imbalances in taxes paid and services received. Central cities finances will likely necessitate the continuation of these imbalances well into the future. Muth would lecture us on the transportation cost reductions from advances in videoconferencing technology (the hologram cometh?) and how those reductions liberate households from locating centrally. Technological advances are seldom reversed (we will see about crypto). The involuntary work-at-home experiment proved the proposition. Not reported on here is a stream of research that shows work-at-home is no less productive than in-office work, innovations notwithstanding. All this yields a conclusion that long-run future economic activity and hotel business opportunity will materialize in outlying areas of major MSAs, medium and small cities, and tax and cost-of-living friendly states. Many urban centers and high tax states run counter to the trend. One of famed Wall Streeter Marty Zweig’s rules for investing is ‘the trend is your friend.’

[1] Tiebout, C. (1956), ‘A Pure Theory of Local Expenditures’, Journal of Political Economy, 64 (5): 416–424.
[2] Muth, R. (1969) Cities and Housing; the Spatial Pattern of Urban Residential Land Use. University of Chicago Press.
[3] Glaeser. E. L., (1999) ‘Learning in Cities,’ Journal of Urban Economics 46 (2): 254-277.
[4] Danstadli, J. M. et. al., 2012, “Video Conferencing as a Mode of Communication: A Comparative Study of the Use of Videoconferencing and Face-to-Face Meetings,” Journal of Business and Telecommunications 26(1), 65-91.

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Economics and Hotel Financial Performance

CBRE Hotel Research specializes in translating national and local economic conditions into measures of hospitality market and property-level financial performance.