Sorting: Home Price is not the same as Rental Price

It’s more expensive to live in New York City than Omaha Nebraska. If you are only going to relocate to Denver for a couple of years, you should rent instead of buy. Housing prices suffer in Baltimore due to high crime rates. These are all statements that don’t need an explanation. Living in a city full of opportunity is going to cost more than in a city a fraction of its size. The commitment to purchase a property is both financially and emotionally taxing for a short stay. And high crime rates make just about any neighborhood a tough sell.

It is easy enough for consumers to observe these strong market indicators. But if we want to start digging deeper into what market prices of housing can tell us, than we must be a more careful about sorting.

If we wish to look at housing costs in an open market environment and break the values down in order to find market preferences for attributes tied to the neighborhoods, then we must choose between either (residential) home sales data or rental data. Otherwise, the statistical outcome will fail because these are two different market transactions.

Purchasing a property is a multi-year commitment. Renting is generally a year at a time. The rule of thumb on how long a buyer should anticipate staying in their home has varied over the years. Back when I first got in the business the benchmark was seven years. Between real estate fees to move- perhaps around 7.5% of value- and the closing costs of financing, a buyer requires several years of appreciation to break even on purchasing versus renting.

But I’d argue there is more to it than this sketch of dollars and cents of the buy versus rent decision. For comparison’s sake let’s consider the actions taken by a homeowner or a renter or an Airbnb occupant. They are all enjoying shelter in the same location of a city. An individual walks by an alley and there is a body lying near the dumpsters. The Airbnb people will probably finish their stay and not mention it to anyone, although they will probably rethink their choice of lodging for the following visit. The renter may or may not call an authority like the police. If bodies in alleys become a routine occurrence they will probably move.

I think you know where I’m going with this. The homeowner is the most likely to get involved and not only notify the authorities but follow through with contact to a city council member and so on. This is work done on behalf of the neighborhood with no financial compensation. It is a job taken on as an investor in the neighborhood who aspires to live in a safe and desirable environment. The homeowner is willing to make this investment whereas the Airbnb and renter are progressively less likely.

The relatively transient nature of renting can affect price in other ways. A consumer maybe willing to pay more to be near key features, especially arts and entertainment venues. The reasoning goes that they know this is a temporary situation so why not enjoy something that they will not have access to once they have to come down to earth and purchase a property. Or they choose over-the-top structural amenities and a higher level of finishes, again not available to them once the concession of a long-term purchase stretches their resources in other directions.

The analysis of rental prices in determining the implicit prices of neighborhood amenities are valuable. But will not yield the same results as the analysis of home prices since consumers are not purchasing the same items.

But what should be worth a mind-blown emoji and seems to be greatly ignored is the reliable impact of public goods on home prices. In addition to knowing a school district is worth $xxx of a home’s value, and all those other observations at the beginning of this post, just about anyone can run a regression on a laptop. Just go into the county records, collect the price of 100 similar homes by area, plug them into Xcel columns as well as FBI crime data relevant to area and school test scores for the property. Then go to Data Analysis>Regression>Ok and generate a lovely statistically significant relationship.

The relationship of price to crime and school performance is so strong it doesn’t even need the most general of sorting. But most other things will.