The Promises and Pitfalls of Housing Search Digitalization

Where people live is crucial to their economic participation, affecting access to jobs, schools, and transportation. At Harvard University’s Joint Center for Housing Studies’ 2022 symposium on Bringing Digitalization Home: How Can Technology Address Housing Challenges?, we presented a research paper that explores the promises and pitfalls of digital housing search and how it may benefit some market participants more than others. The research continues themes from prior work exploring ways to promote financial inclusion through fintech. Focusing on the digitalization of the housing search (meaning increasing use of online platforms and tools to search for housing), our new paper examines how digitalization is changing the way people search for housing and the benefits and harms associated with these changes.

Why does the housing search matter?

Finding the right home can be time intensive and challenging, and a body of research demonstrates that persistent discrimination against marginalized group members can occur throughout the process.1 Homeseekers must sort through thousands of units in hundreds of neighborhoods in order to find the right home. As a result, homeseekers use aids and heuristics to shop for housing.

Research shows that these housing search mechanisms are heavily influenced by social structures and dynamics. For example:

  • White homebuyers are more likely to use White agents and Black homebuyers Black agents2
  • The neighborhoods with which people are familiar and within which they search for housing are influenced by their race and the race of their social networks3
  • Homeseekers of color often use specific techniques to avoid discrimination in their housing searches4
  • The complexity of the housing search has resulted in a market that has been dominated by gatekeepers (like agents and brokers) who have more information on market dynamics

These forces help produce neighborhoods that are segregated by race, ethnicity, and income.5 Residents of neighborhoods that are racially/ethnically segregated or low-income, especially those where poverty is concentrated, often have access to fewer services like childcare, banking, and high-quality schools,6 which can limit economic participation and opportunity.

Disrupting housing search patterns through digitalization

Moving the housing search online disrupts many of these patterns. Digitalizing housing searches can make information on units and neighborhoods more broadly available, more frequently updated, and more accessible to both those living near and far from the homes being listed. This accessibility of information can create new opportunities for residential mobility and change the power dynamics that result from information asymmetries between consumers and the real estate agents and brokers that work with them. These shifts could present opportunities to improve equitable access to housing for broader swaths of the population. However, real-world dynamics can also be replicated online, reproducing existing inequalities in the housing search and creating new barriers.

As a result, it is sometimes unclear whether the shift to online housing searches has truly equalized the housing search process. Three areas in particular underscore the opportunities and challenges inherent in housing search digitalization to date: improving information sharing, fostering nontraditional mobility, and shifting power dynamics between homeseekers and traditional market gatekeepers.

The digitalization of housing search improves information broadcasting, but with uneven reach.

Online platforms have made information about housing much more widely accessible. Offline housing searches often require asking family and friends, looking at listings in a newspaper, driving around neighborhoods looking for “for sale” or “for rent” signs, or hiring an agent to facilitate the search. Using offline methods also often makes it difficult to filter for multiple unit characteristics at once—price, location, number of bedrooms, etc.

With an online search, hundreds of listings appear all in one place and users can quickly select for different characteristics. This broader visibility of units could help diminish the role of social and structural factors that affect how people sort into units and neighborhoods by making it easier to learn about housing in unfamiliar neighborhoods. It also eliminates the need for agents and brokers during the search process, which is meaningful given the research evidence of historical and persistent steering and discrimination in the housing market by some of these actors.7 These changes could make the housing search more equitable by equalizing access to information about housing.

The empirical evidence, however, suggests that the online search may not quite be living up to its promise. Online rental platforms provide more information in wealthier, Whiter, and better-educated communities and less in Black and Hispanic neighborhoods relative to White ones.8 These differences can be self-reinforcing. For example, if lower-income communities or communities with many immigrants have more limited internet access, less comfort in using online search, or less ability to navigate English-language channels, they may be less likely to use online search, which could then dissuade landlords and home sellers from posting online, further reducing the availability of information in these neighborhoods.

Furthermore, online housing markets may be less transparent than they appear. Though information is increasingly online, housing markets are still hyperlocal and often governed by local norms. Homeseekers who conform to these norms (by providing cover letters for their applications, for example), often with the assistance of an agent or broker, may retain an advantage over homeseekers whose reliance on online information left them unaware of the norm. This could reinforce existing patterns of inequality if marginalized homeseekers are less aware of these local norms. This lack of transparency, coupled with variations in the amount and type of information available online for different types of units and neighborhoods, could produce segmented housing patterns.

Housing search digitalization fosters nontraditional residential mobility, although discrimination and privacy concerns remain.

The digitalization of the housing search has also enabled types of residential mobility that were historically more challenging. By providing information online, housing information is now available to non-local households, facilitating intercity, interstate, and even international moves.

Our paper notes that these impacts might be particularly relevant for international migrants, who face greater challenges to finding housing in their new country. Though the networks of settled immigrants remain important to facilitating international moves, these networks can be supplemented or replaced by online platforms, and ethnicity-, culture-, and language-specific online offerings have already emerged. Facilitation of long-distance moves has important implications for economic mobility: making long-distance moves easier and more efficient improves intermetropolitan labor market matching. This is especially relevant for younger people, who are more likely to rent and face longer-term earnings implications from failure to maximize their income due to geographic constraints.

Online housing search has also affected the market for shared housing, which has expanded from being predominantly a strategy used by students and as a safety-net during times of economic hardship to a more mainstream housing strategy. Though demographic, work, and housing trends have fostered the growth of this type of housing, the online search process has accelerated its expansion. Increased sharing of housing information online and use of online social networks to find housing has enabled new kinds of matches made online, expanding the viability of niche matches and facilitating the creation of households whose members did not previously know one another.

This online information sharing also presents some challenges. Online matching for shared housing requires the creation of digital identities. These online identities open up new avenues for discrimination. While the market for shared housing has always been affected by the desire to match with like-minded individuals (which could result in various forms of discrimination), finding shared housing online privileges those who can form (or perform) desirable digital identities9 and facilitates matching based on “fit.” Additionally, the use of personal characteristics by platforms in presenting housing ads opens up the possibility for algorithmic steering. Sharing more information online can foster more trust between potential housemates; however, creating these online identities also means sharing personal information with the online platforms, which often rely on data extraction as their financial model, raising privacy concerns.

Power dynamics are shifting, but evolving technology and practices raise new fair housing concerns.

The digitalization of the housing search has changed the roles of traditional market gatekeepers. The vast majority of homebuyers and many renters are using the internet to facilitate their housing search. This might mean that they no longer have to rely on an agent or broker, or they may have more information before reaching an agent, lessening the ability of the agent to shape the search process.

Despite fair housing laws, research has indicated that there are several stages of the housing search process in which discrimination may (and does) occur.10 Eliminating gatekeepers and making markets more legible could help homeseekers of color and other marginalized homeseekers obtain more favorable housing outcomes by eliminating discrimination at one or more stages of the process.

At the same time, new types of tenant screenings are expanding beyond traditional reference and credit checks and algorithmic steering can automatically present different types of searchers different results, which could exacerbate housing search inequalities.11

Equalizing access: a reality or an illusion?

In principle, digitalization can equalize access to housing search information and diversify information supplies. In practice, this promise is muted by a range of drawbacks.

Online housing information can be uneven and less transparent than it appears. Resulting information asymmetries may then worsen divisions by income or socioeconomic status.

Variations in who uses online search, the information available, and the types of units and neighborhoods marketed online can produce segmented information landscapes. This suggests that disadvantaged homeseekers may be making more inefficient housing decisions due to more incomplete information and may be limited in their ability to discover new neighborhoods.

Though the move online may mitigate some historical avenues for discrimination of various marginalized groups, the expanded choice set is often an illusion. Rather than disrupting discrimination itself, digitalization may simply change the setting for it, as technology can aid in discrimination and make it easier (via automated screening, for example) for the providers of housing units to choose homeseekers based on their preferences (or biases).

Policymakers and practitioners may be able to foster the benefits of a digital housing search while helping to mitigate the harms.

First, housing practitioners working with marginalized homeseekers can leverage online platforms’ information broadcasting to their advantage. For example, online platforms such as DAHLIA, from the City and County of San Francisco, have created an open-source, centralized application and listing platform for affordable housing.

Second, it is important for researchers and policymakers to continue to monitor the impacts of changing housing search behavior on housing equities and inequities. As people’s housing search patterns change and new technologies emerge, the potential disparities noted in our paper could be moderated or worsened.

Third, further research is needed to explore the extent to which the potential risks and benefits highlighted in our research are taking place. The data produced by online homeseekers can be one avenue for continued research; this data can be used to better understand market conditions, thothough researchers and policymakers should be cautious to consider the potential biases in these types of data.

Finally, online platforms could be examined more closely to identify improvements that address concerns around data collection, privacy, and new avenues for discrimination online.

You may also be interested in:


1. Maria Krysan et al., “Racial and Ethnic Differences in Housing Search” (Washington, D.C.: US Department of Housing and Urban Development, Office of Policy Development and Research, 2018). Turner, Margery Austin, Rob Santos, Diane K. Levy, Doug Wissoker, Claudia Aranda, and Rob Pitingolo. “Housing Discrimination Against Racial and Ethnic Minorities 2012.” Washington, DC: US Department of Housing and Urban Development, Office of Policy Development and Research, June 2013. Elizabeth Korver-Glenn, “Compounding Inequalities: How Racial Stereotypes and Discrimination Accumulate across the Stages of Housing Exchange,” American Sociological Review 83, no. 4 (August 2018): 627–56, doi: 10.1177/0003122418781774.

2. Krysan, Maria. “Does Race Matter in the Search for Housing? An Exploratory Study of Search Strategies, Experiences, and Locations.” Social Science Research 37, no. 2 (June 2008): 581–603.

3. Krysan, Maria, and Kyle Crowder. Cycle of Segregation: Social Processes and Residential Stratification. New York: Russell Sage Foundation, 2017.

4. Krysan, Maria, Kyle Crowder, Molly B. Scott, and Carl Hedman. “Racial and Ethnic Differences in Housing Search.” Washington, D.C.: US Department of Housing and Urban Development, Office of Policy Development and Research, 2018.

5. Krysan, Maria. “Does Race Matter in the Search for Housing? An Exploratory Study of Search Strategies, Experiences, and Locations.” Krysan, Maria, and Kyle Crowder. Cycle of Segregation: Social Processes and Residential Stratification. New York: Russell Sage Foundation, 2017.

6. Justin P. Steil, Jorge De la Roca, and Ingrid Gould Ellen, “Desvinculado y Desigual: Is Segregation Harmful to Latinos?” The ANNALS of the American Academy of Political and Social Science 660, no. 1 (2015): 57–76.

7. Turner, Margery Austin, Rob Santos, Diane K. Levy, Doug Wissoker, Claudia Aranda, and Rob Pitingolo. “Housing Discrimination Against Racial and Ethnic Minorities 2012.” Washington, DC: US Department of Housing and Urban Development, Office of Policy Development and Research, June 2013. Carrozzo, A. (2019, November 17). Undercover investigation reveals evidence of unequal treatment by real estate agents. Newsday. projects.newsday.com/long-island/real-estate-agents-investigation/. Korver-Glenn, E. (2018). Compounding Inequalities: How Racial Stereotypes and Discrimination Accumulate across the Stages of Housing Exchange. American Sociological Review, 83(4), 627–656. doi: 10.1177/0003122418781774.

8. Geoff Boeing, “Online Rental Housing Market Representation and the Digital Reproduction of Urban Inequality,” Environment and Planning A: Economy and Space 52, no. 2 (2020): 449–68; Geoff Boeing et al., “Housing Search in the Age of Big Data: Smarter Cities or the Same Old Blind Spots?,” Housing Policy Debate 31, no. 1 (2021): 112–26.

9. Maalsen, Sophia, Peta Wolifson, Dallas Rogers, Jacqueline Nelson, and Caitlin Buckle. “Understanding Discrimination Effects in Private Rental Housing.” Melbourne: Australian Housing and Urban Research Institute Limited, September 3, 2021. doi: 10.31235/osf.io/jdycg.

10. Elizabeth Korver-Glenn, “Compounding Inequalities: How Racial Stereotypes and Discrimination Accumulate across the Stages of Housing Exchange,” American Sociological Review 83, no. 4 (August 2018): 627–56, doi: 10.1177/0003122418781774.

11. Mara Ferreri and Romola Sanyal, “Digital Informalisation: Rental Housing, Platforms, and the Management of Risk,” Housing Studies, 2021, 1–19.

The views expressed here do not necessarily reflect the views of the management of the Federal Reserve Bank of San Francisco or of the Board of Governors of the Federal Reserve System.

About the Authors
Rocio Sanchez-Moyano is a senior researcher on the Federal Reserve Bank of San Francisco’s Community Development team. Her areas of expertise include housing and asset building, with a special interest in racial equity and the experiences of Hispanic and immigrant household. She holds a doctorate in city and regional planning from UC Berkeley. Learn more about Rocio Sanchez-Moyano, PhD
Geoff Boeing is an assistant professor in the University of Southern California’s Department of Urban Planning and Spatial Analysis and a Nonresident Senior Fellow at the Brookings Institution.
Julia Gabriele Harten is an assistant professor and Canada Research Chair in Data Innovation for Housing and Inclusive Urbanization at the University of British Columbia’s School of Community and Regional Planning.