How CRE Investors Use Mobility Data - Part One

How CRE Investors Use Mobility Data - Part One

Today we adopt the persona of a commercial real estate investor who wants to use Unacast’s human mobility insights to research investment opportunities for a new mixed-use, low-rise residential property in the Northeast United States. 

Our investment thesis is that successful developments in the pandemic era will provide more urban-styled amenities in suburban areas, and more open space and suburban-feel in urban areas. We are targeting areas with less than 1,000 people per square kilometre. We want to create a development that features a large, public outdoors space, so people have room to roam with confidence in the pandemic era.

To do our research, we’ll use a combination of Unacast’s tools: our Migration Pattern datasets, the Neighborhood Insights dashboard, our Venue Explorer, and finally the Retail Impact Scoreboard

For starters, we want to understand how COVID-19 has affected long-term human migration patterns in and around New York City. Specifically, we want to know the areas people are moving away from and where they are relocating to, and how mobility patterns are changing as a result. 

Analyzing Migration Patterns

Starting with our Migration Patterns dashboard, we can immediately see that most of the states in the Northeast are experiencing net-outflows. New York, Connecticut, Delaware, DC, Maryland, Massachusetts, New Jersey, Pennsylvania, Rhode Island and Vermont all have negative migration patterns in the last few months. Only the comparatively less-densely populated states of Maine and New Hampshire have net inflows of migration.

Naturally, a certain degree of people movement is normal and can be often attributed to seasonal fluctuations i.e more people moving during the spring, students move to and from dorms, etc. To account for that effect and consequently uncover the magnitude of migration encouraged by the pandemic, we subtracted 2019 data from the current year and ranked state-by-state performance. When we do this, six Northeast states account for positions on the national top 10 in terms of human outflow: DC (#1), New York (#3), Massachusetts (#6), Maryland (#7), New Jersey (#9), and Rhode Island (#10). 

Zeroing-in on the big cities, one common effect we observe is a shift of population from densely populated centers of metropolises towards both not-so distant neighborhoods and other, less-densely populated areas of the same state. This is most clearly illustrated looking at New York City, where more than 28% of outgoing migration is to other areas of the state, and about another 37% of migration is to other Northeast states, most prominently New Jersey, followed by Pennsylvania and Connecticut. 

Because of this effect, which is similar in other large metropolitan areas of the Northeast, we are going to eliminate New York City, Boston, Washington D.C. and Baltimore from contention as a location for our new property -- we want to create an environment where people are going, not where they are leaving. Since New Jersey accounts for more inflow migration from NYC than any other nearby state, let’s focus on finding a desirable location in a less-densely congested area of New Jersey that’s trending above average recovery rates. 

Identifying Desirable Towns and Neighborhoods

We now have our Neighborhood Insights tab open. With this tool, we can closely examine human mobility patterns of towns and neighborhoods down to the Census Block Group level; that’s about 300-6,000 people, which is the smallest unit of measurement available. While a given CBG may represent just one building’s worth of people in Manhattan, in the suburbs, it could represent several blocks, or in a rural area, miles. With a glance to the left of the same screen, we can quickly get a breakdown of the traffic in each CBG and see the number of Residents, Locals, Workers, and Non-Locals including Tourists. This helps to interpret not just how many people are moving through a given area and when, but who they are and what they’re doing there.

To start, we’re going to eliminate the New Jersey counties of Bergen, Hudson, Essex and Union. They look attractive on the periphery, i.e. there’s a migration trend out of NYC and into each of these counties, but that’s a smoke screen. Most of those folks aren’t migraters at all. They’re formerly commuting Workers who already lived in those NJ counties to begin with. It’s just their foot traffic registers as belonging to Locals and Residents more often now based on the evolution of their mobility patterns as forced by COVID-19.

With those four counties out of the picture, we can now use Neighborhood Insights to quickly identify and select about 60 CBGs around the state of New Jersey that are on or near large public spaces, such as lakes and parks, and not too close to congested cities. 

We measure the effective ‘recovery rate’ of a given CBG as a percentage of return to pre-pandemic human mobility patterns. We can also compare data from a year ago, or specify specific dates and/or groupings of CBGs for comparison. A complete return to normal equals a 0% reduction in traffic versus the past, whereas a complete loss of traffic equals -100%. With a quick look at our selected grouping, we can tell the great majority of the CBGs we’ve selected are doing well in terms of recovery compared to their more congested urban peers. A full 90% (54) have already recovered to pre-COVID-19 levels of mobility, or better. 

One county, Hunterdon, records a split recovery rating, on the basis of one section of the county being more greatly impacted by a seemingly long term reduction in Worker traffic. It’s a nice area with plenty of green space and with just 110 people per km² it is a positively roomy area to build. But is there a growing community in Hunterdon that justifies a mixed-use lowrise built to house leasable space and draw enough traffic to support retail brands and services on the ground level? Iffy. Let’s keep looking.

Morris county, in the north of the state, seems to be in a similar boat as Hunterdon, until you look more closely. Though mobility currently sits at -23%, the same as in Hunterdon, the rate of recovery is much faster.  Why? Locals are appreciably more active in the area than they were pre-COVID or even in 2019 and visits from Non-Locals have leaped back to 2019 levels over the last month. Slowly but steadily, Workers are also returning to the area. There’s plenty of room to build with less than 400 people per km² and a couple promising communities for us to consider building in. A decent option but let’s keep looking.

Monmouth county in the south looks attractive. Most CBGs have recovered and the county is sparsely populated at 621,400 or 360 people per km². A number of communities are a potential fit for our lowrise project. But higher density levels on the preferred central coastline and waterways, accompanied by higher development costs and a longer haul to major inland highways are all suboptimal. So, if we choose to build in Monmouth, we want to look west along the I95 towards the turnpike. That’s exactly what we’ll do next.

In the next posts in this series, we’ll continue our CRE investor exercise to zero-in on specific communities in Monmouth county, use our tools to study how people are moving around them now versus in the past, and identify brands, venues and specific locations for our new development that stand to benefit as a result. Interested in learning more? Book some time with us below.

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