The housing arbitrage index

How much is being saved by moving to someplace less expensive?

The AEI housing arbitrage index aims to measure the extent of how much money an individual could save by selling a home in their current location and moving to another.  The data for the index are based on actual homeowners who have sold one home and purchased a home at a new address – either within the same metro or elsewhere across the entire country.

Fundamentally, this arbitrage opportunity exists because of home price differentials across the country. For example in April 2021, the median sales price was $1,350,000 in San Jose and $390,000 in Phoenix. The median owner thus could in theory, pocket almost $1,000,000 by selling their home in San Jose and buying the median home in Phoenix and likely get a larger and newer home on a larger lot.

In the past, not many homeowners could take advantage of the opportunity as workers needed to live where they worked. However, because of the increase in Work from Home (WFH) in the aftermath of the pandemic, more people, especially higher income individuals, can now do so. The index details the arbitrage opportunity for those that have already moved.

Data Interactive

Background

Much like online shopping, Work from Home (WFH) appears to be here to stay. Post-pandemic levels will be much higher than pre-pandemic and will likely increase over time. Recent studies have estimated that perhaps 20-25% of the workforce will continue to WFH after the pandemic. That translates to an additional 20-25 million workers with the option to move. An additional WFH impact will be an increase in the number of employees working from satellite offices and flexible work spaces located near their homes.

Higher income workers, who have greater opportunities to WFH, are able to profit from arbitrage opportunities offered by vastly different home prices across metros and regions.

• Nearly ¼ of US households live in metros with an average median home price/median household income ratio of 6.9, while the rest of the country has a ratio of 3.3. And WFH buyer incomes are high.
• Example: in April 2021, the median sales price of a San Jose home was $1,353,000 (10.3x the 2019 median household income of $131,000) compared to $388,000 in Phoenix (5.7x the median income of $68,000).

As noted, home buyers value a home based upon its utility or nearness to amenities.

• Up until the pandemic, walkability was a utility that buyers would pay up for.
• WFH has caused new utilities to be more valued than walkability: greater living area and office space, room for children, larger lots, a new home, nearness to family, and access to open spaces.
• Working just 2 days a week at home is enough to change the utility equation.
• The outskirts of San Jose and the metros of Sacramento and Phoenix now have new utility as it relates to a WFH employee of a San Jose company. This utility change may cause both sales prices and intrinsic values to rise in these areas.

For the moment, it looks as if the pandemic and WFH have caused a shift in preference from walkability to nearby amenities to amenities provided within one’s home. This shift is largely concentrated in the 100 largest metros (accounting for 69% of sales) and across all price tiers. Within these 100, impact is greatest on the most walkable metros and the higher price tiers.

It is reasonable to assume that the same desire for walkability that existed in more dense and  large urban areas pre-pandemic, will ultimately be desired by buyers in more suburban areas, hence the logic of a focus on Walkable Oriented Development across the nation.

Index methodology

The housing arbitrage index traces individuals as they sold a home and bought another one someplace else. For all home sellers in the public records deed file, we query Melissa National Change of Address information whether a USPS mail forwarding request was requested.  We then check the public records deed file if the same individual purchased a home at that location. If we find a match, we then compare the home characteristics of the sold and purchased home. We trace moves that occurred after January 2018 and update the data quarterly.

The index is limited to homeowners who subsequently also purchased a home. By definition the index excludes renters as they do not own and are not visible in our data. This also includes owners who moved to rental or vice versa.

We report the Combined Statistical Area (CSA) or the Core-Based Statistical Area (CBSA), if the CBSA does not belong to a CSA. A CSA is a combination of adjacent metropolitan (MSA) and micropolitan statistical areas that can demonstrate economic or social linkage. A CBSA consists of one or more counties (or equivalents) anchored by an urban center of at least 10,000 people plus adjacent counties with economic or social linkage. For more details, see here.

To Contact the Authors

Edward Pinto, Director, AEI Housing Center ([email protected])

Tobias Peter, Assistant Director, AEI Housing Center ([email protected])

About the AEI Housing Center

AEI’s Housing Center (www.AEI.org/housing) undertakes evidence-based research that expands the body of knowledge concerning housing markets and finance. It provides objective and transparent housing market indicators at the national, metro, and fine geographic levels.