Market Data Market Reports Rental Market Data

Methodology: StreetEasy Rent Indices

We’ve updated our Rent Indices methodology as of July 2017. Check out the details on our latest methodology here.

“The rent is too damn high.”

It’s a common refrain in New York. And, in a city in which more than two-thirds of residents are renters, the cost of renting is not only a common topic of conversation amongst New Yorkers, it is an important public policy issue as well. Growing rent prices make it increasingly difficult for many New Yorkers to live here. As income growth stagnates across the country, a greater share of household income is being directed to the rent check. According to StreetEasy’s rent affordability study released in March 2015, the typical New York household will need to spend 59 percent of its annual income to afford the city’s median asking rent this year.

Cutting Through the Rent ‘Noise’

While it’s widely accepted that rent is high in New York City, the degree to which it has grown has been an open question. The most common measure to track rent growth is median asking rent. The primary benefit of this metric is that it is relatively straight-forward to determine. Simply, take all available listings in a given period and report the median price. Indeed, this has been StreetEasy’s default rent metric in the past and it continues to be the standard metric to help us understand the ‘typical’ rent price paid in a given area.

The median asking rent can produce surprising results, however. For example, Manhattan’s median asking rent in 2014 was $3,141, but in 2015 the median is $3,092 – a decline of about 1.6 percent. Reliance on the median asking rent would lead us to believe that rent prices are dropping in Manhattan, contrary to broad public perception.

What gives?

As we discussed in an earlier post on median sales prices, the median is subject to a number of problems. Chief among them is the inventory mix problem; median asking rent is dependent on the mix of rental inventory and the types of homes on the market in a given month or season. That inventory changes over time, and those changes make the median asking rent relatively volatile. ‘Noisy’ datasets are what economists call time series that have a high degree of volatility. In the case of New York City rent data, it’s about as noisy as the city’s streets.

To cut through the noise and to provide an accurate account of price growth across time, we built the StreetEasy Rent Indices. Similar to the StreetEasy Price Indices which track resale values across Manhattan and Brooklyn, the Rent Indices use a repeat-sales methodology but with rentals instead. In short, we track the changes in rent price across several years among unique rental properties that are listed on StreetEasy. This produces a smoother and far less volatile time series compared to median asking rent, as the graph below demonstrates.

[tableau server=”public.tableau.com” workbook=”indexVsMedian” view=”indexVsMedian” tabs=”no” toolbar=”no” revert=”” refresh=”yes” linktarget=”” width=”600px” height=”530px”][/tableau]

NYC Rent Growth is Steady and Consistent

According to the StreetEasy Rent Indices, the median rent across the city increased 16.1 percent since 2012, reaching $3,012 in October. In each of the four boroughs for which the StreetEasy Rent Indices cover, the rent growth between 2012 and 2015 has met or exceeded 15 percent. Queens has seen the greatest increase in rent. Since 2012, the median overall rent in Queens rose 37.7 percent to $2,468 in October.

A striking trend to note in this graph is the consistency with which rents have grown since 2012, the starting year for the Rent Indices. Unlike the sales market which experiences periodical price expansions and corrections, rents in New York have seen a slow and steady growth pattern. Apart from a seasonal slow-down in price growth that occurs within each market in the winter, rents have experienced an uninterrupted upward trajectory. Another notable exception is the Bronx. Unlike each of the other boroughs in which rents have never declined since 2012, the Bronx saw several months of decline in late 2013 and into early 2014. Once again during the most recent five months, the Bronx experienced consistent rent declines.

[tableau server=”public.tableau.com” workbook=”rentIndices” view=”rentIndices” tabs=”no” toolbar=”no” revert=”” refresh=”yes” linktarget=”” width=”600px” height=”530px”][/tableau]

Not surprisingly, rents in Manhattan have consistently been the highest among the boroughs. In October, the overall median rent in Manhattan reached an all-time high of $3,158, followed by Brooklyn ($2,672), Queens ($2,468), and the Bronx ($1,466). Rent in the North Brooklyn submarket, which includes Williamsburg and Greenpoint, surpassed Manhattan’s rent in November 2012. Ever since then, rents in the hipster haven have either been neck-and-neck with Manhattan or have pulled slightly ahead of it, highlighting the degree by which the rental market in parts of Brooklyn has transformed in recent years. To date, North Brooklyn is the only submarket in Brooklyn to have ever surpassed Manhattan rent, although Northwest Brooklyn has come close several times.

How We Did It

The StreetEasy Rent Indices are produced using a similar methodology to our flagship repeat-sales price metric known as the StreetEasy Price Indices. By including only valid and verified listings from StreetEasy and employing a repeat rentals approach, the Indices emphasize the changes in rent on individual properties and not between different sets of properties.

A specific rental property in a listing is identified and then matched with its sequence of listings over time. We are able to match properties with a high degree of accuracy because the StreetEasy rental database includes only exclusive listings from agents. Open listings from multiple sources are not accepted because agents have no incentive to uniquely identify the rental. Including such open listings would inappropriately over or under emphasizes certain properties in a given month. Rentals that are never declared as rented and removed from the site are not included in the Indices. This enables us to pinpoint the rent to a specific time period and reduce the (likely upwards) bias associated with unrealistic asking rents.

Once a clean dataset is created, a repeat rentals approach (similar to repeat sales) is used to form the final Indices. By using price changes between the repeat rental pairs, the inventory mix problem associated with a median asking rent time series is avoided because we utilize changes in rent on individual properties, and not between different properties.

The final part of the rental index construction process is to convert it into a dollar denomination. To do this without emphasizing only the properties rented in any single month, we use median rent information from the entire stock of rentals available over the last decade. The level of the repeat rentals index is set to minimize its difference from the entire history of median asking rent (for the given area) of rented properties, not just any random month. By incorporating median rent information across the entire history, we can more confidently interpret the value of the StreetEasy Rental Indices as the value of rentals in that region, not just the median asking rent of the unique properties listed for rent in any given month.

Rent data is sufficient enough to produce the StreetEasy Rent Indices in four of the city’s five boroughs. In Manhattan and Brooklyn, where rental listings on StreetEasy are the most numerous, we subdivide the boroughs into five distinct submarkets to get a more local read on rental trends.

Exit mobile version