How are new technologies shaping cities? Take aways from keynote speech by Prof. Albert Saiz (MIT) at the ERSA

Last week took place the 62nd Annual Meeting of the European Regional Science Association, where Professor Albert Saiz (MIT Center for Real Estate) provided some key insights to understand where cities are going in the era of remote work and the share economy. Remote work technologies, e-commerce and sharing economy are transforming the way that people (and firms) demand office, retail and hotel spaces across the city.

What are the major trends impacting cities? These are some of the major lessons from the keynote:

1. Remote Work Revolution: The advent of remote work technologies is triggering a seismic shift in the demand for office space by companies and the residential preferences of workers. With the ability to work from home either full-time or part-time, the imperative to reside close to the workplace is diminishing. This trend is particularly pronounced in areas where individuals can secure homes equipped for work, encompassing both the requisite space and essential amenities. So, who stands to gain from this mass migration? Emerging as likely beneficiaries are secondary cities endowed with top-notch amenities in proximity to major metropolises like Boston or NYC, where workers can relish an exceptional quality of life while retaining access to thriving job markets.

2. E-commerce: E-commerce technologies have allowed individuals to buy almost everything they wish online without the need to go to a brick-and-mortar store. This is changing the need to be close to stores to acquire the products or services that individuals demand. This is creating a shift in the role of physical stores and their distribution of stores across space. The role of stores providing high-end experience goods or services remain valuable in the era of the e-commerce revolution, as well as the last minute daily purchase stores.

3. Short term rental impacts on cities: Delving into the city's transformation by short term-rental platforms (e.g., Airbnb), it's impossible to ignore the growing scrutiny from both media and policymakers regarding the profound influence of short-term rentals on urban housing markets. The surge in short-term rental availability has sparked mounting concerns, especially in cities like Amsterdam and Barcelona. These concerns revolve around the accessibility of housing for local residents in coveted tourist hotspots. In such areas, the relentless demand for short-term rental properties exerts upward pressure on real estate prices, potentially exacerbating affordability challenges for those seeking to reside in the vibrant heart of the city, which is precisely where tourists aspire to stay.

A key question for policy makers is: Who suffers from the entrance of short term rentals in a city? Are low or high income households at risk of exclusion in those cities?

To illuminate this inquiry, Professor Saiz employed the rent-bid model as a guiding framework to elucidate the groups at risk of exclusion from these housing markets. This model delineates the evolution of rents across urban landscapes in relation to proximity to the city center— major concentration of amenities and employment opportunities. It assumes that individuals must incur certain transportation costs, encompassing both time and money, to access these coveted urban conveniences.

In a monocentric city scenario, households engage in a competitive bidding process for housing, ultimately dispersing across various zones within the city. Figure 1 vividly illustrates the spatial distribution of low-income households (depicted in red) and high-income households (in black). High-income households exhibit a greater willingness to invest in amenities owing to their enhanced financial capacity and appreciation for the city center's attractions, such as upscale dining establishments and cultural events like opera concerts.

This divergence in preferences is tangibly represented in the graph by the steeper slope of the bid lines for high-income households compared to those for low-income households. Consequently, high-income households submit higher bids for residences in close proximity to the city center, while their bids decrease relative to low-income households for properties situated farther from the urban core.

Figure 1. Bid-rent curve for high vs low income households

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Now consider the inclusion of Airbnb in the city. The investors in short-rental homes have an even higher appreciation for amenities offered by city centers (theatres, monuments, etc.), since tourists come exclusively to enjoy those amenities and disregard any other services that the city offer. In cities like Amsterdam or Barcelona, the rental income provided by short term rentals is also substantially to make the bids for units being potentially very high. This makes that rent-bid curve of Airbnb investors (in green in figure 2) is even steeper than that one of high-income households. As a result, if you see the type of households that Airbnb investors outbid are entirely high-income households that see themselves displaced out of the city center. The low income households were already outbidded by the high-income bidders in the initial scenario.

Figure 2. Bid-rent curve for high vs low income households with Airbnb

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If you want read more about the work of Prof. Albert Saiz on consumer cities, affordable housing or technology, check the website of the MIT Urban Economics Lab here.