Easily Identifying Comparable Sales in New York City

Finding comparable sales just got a whole lot easier!

In this analysis, you can browse three maps I built that show all office building, residential building, and single-family dwelling real estate transactions that have occurred in New York City over the past year.

This analysis makes it super easy to visualize the real estate market by combining publicly-available annual rolling sales data provided by the New York City Department of Finance with some creative mapping techniques.

Critically, this data is extremely up to date. These maps show the various transactions that occurred over the past 12 months based on New York City finance data as of October 11 — just five days ago! As usual, I am focusing solely on Manhattan.

Without further adieu, Here are all of the office building transactions that have taken place this year:

The most expensive transaction was 787 Seventh Avenue, which was scooped up by CalPERS for a cool $1.9 billion.

The midtown market inside which 787 Seventh Avenue resides also appears to be the hottest office building market in general. The area bounded by Broadway & Third Avenue (on the East and West) and Central Park & 50th Street (on the North and South) has had over $7.5 billion in real estate sales over the past year alone. Another huge deal was 550 Madison, which was purchased by Olayan America for $1.4 billion back in May.

A great feature of this map is that you have official purchase prices and square footages, so it’s very easy to do some quick calculations if you’re a real estate investor scouting office buildings.

This map shows residential buildings, both elevator buildings and walk-ups.

What stands out to me is the action north of Central Park. There were a number of transactions right along Central Park North and some big deals up in Harlem, Morningside Heights, Manhattanville, and Hamilton Heights.

It’s pretty easy to see the trend of residential real estate moving north, presumably because of attractive price points. 50,000 square feet north of Central Park is transacting between $10 and $30 million (with some outliers, of course) whereas similar square footage south of Central Park bottoms out around $30 million and commonly goes upwards of $50 million.

And for those of you looking to buy (or sell) a single-family home, this map is for you.

Single family home sales are primarily concentrated in the townhouse-heavy West Village and Upper East Side. Going rates look to be between $10 and $25 million depending on size, quality, and location.

Concluding Notes

I purposefully left condos and coops out of this analysis due to a technical issue with how the information was being displayed on Carto, but I do have thousands of data points on those fronts. I hope to have that sorted out next week so we can take a detailed look at how apartments are moving.

Happy comparing!

New York City Neighborhood Residential Affordability Gradient

In this article, I will paint a valuable residential real estate affordability gradient across every neighborhood in New York City by analyzing and mapping census data.

Real estate professionals can use this analysis broadly to understand price gaps between neighborhoods, target areas of future growth, and get a general feel for neighborhood residential affordability. People who are thinking about moving can also gain some insight into affordable neighborhoods about which they may not have previously known.

The methodology is simple. We look at the percent of owner-occupied housing valued within a specific price range as recorded in theAmerican Community Survey (ACS) housing data and then we map those values to neighborhood tracts as defined by PUMA (Public Use Microdata Areas) community districts.

Here’s what we find:

Percent of Owner-Occupied Housing valued $1,000,000 and up

Here’s how to read the map

The labels represent the percentage of owner-occupied housing in that area valued above $1M. The colors correspond to those values. Darker red means a high percentage of housing is in that price range. Lighter yellow means a low percentage of housing is in that range. This is what I call the “gradient” of city affordability.

From both real estate and urban development perspectives, this map is particularly important because the affordability gradient is essentially equivalent to a value maximization gradient. The darker areas are the most valuable areas and the lighter areas are the least valuable areas. If you hypothesize that the city is growing outwards from Manhattan, then you can easily project which areas are up and coming.

For example, 25-30% of owner-occupied housing in Central and East Harlem is valued over $1,000,000, but just across the river in Hunts Point, Longwood, Melrose, Concourse, High Bridge, and Mount Eden (all in the Bronx), less than 1% of owner-occupied housing is valued over $1,000,000. That’s an incredible gap in pricing for such a short physical distance between those areas. Real estate developers and urban planners have to ask why. What could be done to increase land values, create growth, and generate profit?

You can also see Bushwick as the next area of growth in Brooklyn. With just 1.6% valued above $1M, Bushwick is wedged between Williamsburg/Greenpoint at 16.2% above $1M and Bedford-Stuyvesant at 9.7% above $1M. That’s another huge price gap unexplained by distance.

It’s also interesting to note that the east side of Manhattan, classified in PUMA as the Lower East Side, Chinatown, Murray Hill, Stuyvesant Town, and Gramercy, appears to be significantly more affordable (less expensive) than the west side. In comparison to the west side, the east side has a much lower share of owner-occupied units above one million and a much higher share of units in the $500-999K bracket. If I were a real estate developer or potential homeowner, I’d be looking there for cheap opportunities within Manhattan (relatively speaking).

There is a lot you can learn from this simple map.

In addition to the $1M+ price point, the American Community Survey also includes a variety of different price ranges for us to review:

  • Less than $50,000
  • $50,000 to $99,999
  • $100,000 to $149,999
  • $150,000 to $199,999
  • $200,000 to $299,999
  • $300,000 to $499,999
  • $500,000 to $999,999 (Mapped Above)
  • $1M and up

For your viewing pleasure, I’ve mapped out each of the price points from $200,000 and up.

Percent of Owner-Occupied Housing valued $200,000 to $299,999

Between $200,000 and $299,999, a quick look at the units on the legend shows that there isn’t a ton of owner-occupied housing between that price range. The neighborhood with the highest percentage is Forest Hills/Rego Park, but only 26.4% of the housing in that neighborhood is in that range. Naturally, that means 73.6% of owner-occupied housing is outside of the $200-299K range. Hover over Forest Hills/Rego Park and you can see that ~56% of owner-occupied housing is above that price range and the rest is below it.

Regardless, Forest Hills/Rego Park has the highest percentage in that range. Some other options are Washington Heights/Inwood/Marble Hill, Hunts Point/Longwood/Melrose, Riverdale/Fieldston/Kingsbridge, Port Richmond/Stapleton/Mariner’s Harbor, Sunnyside/Woodside, and Concourse/High Bridge/Mount Eden.

Remember, this doesn’t mean you can’t find housing at this price range in other neighborhoods. It just means you’re more likely to find housing at this price range in these neighborhoods.

Percent of Owner-Occupied Housing valued $300,000 to $499,999

If $300,000 to $499,999 is your sweet-spot, Wakefield/Williamsbridge/Woodlawn, East Flatbush/Farragut/Rugby, Jamaica/Hollis/St. Albans, Queens Village/Cambria Heights/Rosedale, Brownsville/Ocean Hill, Port Richmond/Stapleton/Mariner’s Harbor, and East New York/Starrett City are all prime targets.

Percent of Owner-Occupied Housing valued $500,000 to $999,999

If you’re looking for housing between $500,000 and $999,999, you’re best off searching in Bensonhurst/Bath Beach, Bay Ridge/Dyker Heights, Bedford-Stuyvesant, Bayside/Douglaston/Little Neck, Astoria/Long Island City, and Greenpoint/Williamsburg. Those are the neighborhoods with the highest percentage of owner-occupied housing within that price range according to the ACS data.

A little bit about the data

The New York City Department of City Planning (NYC DCP) publishes an enormous amount of census data. You can browse through everything here.

The data I used for this analysis was the housing data provided by the American Community Survey (ACS) which is conducted annually. The specific dataset is located here (this links to an Excel spreadsheet hosted by NYC.gov).

For more information about the ACS, check out their website or their methodology documentation.

Additional Notes

  1. I used the most recent data available, but it’s from 2014, so it is a little old. That said, while housing prices have certainly changed (upwards), I think the overall gradient still applies. The general structure & profile of neighborhoods across the entire city would not have changed significantly over two years.
  2. The housing price data is collected via survey. It represents what the homeowners believe their homes would sell for on the market at the time the survey is taken. Naturally, this won’t be 100% accurate, but it should provide us with a reasonable ballpark.
  3. Shout out to Frank Donnelly of Baruch College CUNY for his exceptional tutorial on how to map a PUMA shapefile in Carto and then merge it with additional PUMA-level data. If you want to replicate what I did, go read Frank’s article.


You can generate a number of interesting insights from the $1M+ map. Look no further than the price gap highlighted by this map to explain why so many real estate developers have been scooping up properties in the South Bronx. Factor in major capital investments like the Second Avenue Subway expansion (whenever it’s finally done) that will drive economic growth and that area looks ripe.

You can also see that there are actually some affordable neighborhoods in New York City! And if you look hard enough, you can see that there are areas at low price points scattered everywhere. People looking for affordable housing aren’t limited to one or two areas, but they are mostly limited to the outer boroughs.

On a personal note, this analysis was a wonderful learning experience for me because it was my first exposure to dealing with and mapping out census data. Expect more from me in this same style. The census/ACS data available covers a wide variety of social, economic, and demographic measures.


Biggest New York City Developments Approved in August 2016

One of the best leading economic indicators with regard to real estate markets is construction permits. Construction permits can tell you where new projects are being built, how big those developments will be, what type of occupants those projects are for (commercial, residential, etc.), and a whole host of other insights.

Using this information, real estate developers and investors can project changes in supply. By understanding changes in supply, inquiring minds can get a better sense for how rents are changing and how neighborhoods are changing.

These are the biggest new building permits approved in New York City this August 2016:

August 2016 new building permits by square-footage.
August 2016 new building permits by square-footage.

This is built using the New York City Department of Buildings permit data which gets released on a monthly and weekly basis in Excel format. You can find this data here. What’s particularly great about this source of information is that it is timely. The PLUTO data that I love so much is only released yearly. NYC DOB permit data is released weekly.

In this post, I will explain the methodology I used to analyze permit data to visualize where the largest new developments currently in the pipeline are located.

The specific dataset I am using is located here (this will directly download the August 2016 zip file hosted on nyc.gov).

Due to computing constraints, I am limiting the permit data to the following rough locational boundaries:

The subset of permits that I am mapping falls roughly within this box.
The subset of permits that I am mapping falls roughly within this box.

This is important to note because the NYC DOB permit data is not geocoded, so I have to manually geocode it based on what we get from the DOB.

Data Analysis Sidebar: How to geocode non-geocoded New York City data

The best way I have found to manually geocode NYC data is to merge the non-geocoded data (permits) with geocoded data from PLUTO on a common field that accurately parallels location. Luckily, New York City’s borough-block-lot (BBL) system works perfectly.

Each line in PLUTO has a unique geocode (“the_geom”) corresponding to a unique borough-block-lot code (“borocode,” “block,” “lot”). And almost every other city datasource uses some form of BBL as an identifier. Depending on the source of data, use concatenations and your preferred lookup technique (index/match, vlookup, SELECT/WHERE, etc.) to pull geocodes from PLUTO into whatever datasource you’re looking at by matching BBLs.

In this case, I merged geocodes from PLUTO into the NYC DOB permit data, but the technique applies to pretty much every source of data New York City publishes. As you’ll see shortly, this allows me to map NYC DOB permit data through cartography software such as Carto.

The difficulty here is that the PLUTO data is enormous if you want to look at the entire city. There are millions of lots which translates into gigabytes of data even if you’re just downloading boro-block-lot information and no other tax lot data. That’s why most of my analyses are focused on Manhattan and a little bit of the outer boroughs. My Macbook Pro simply doesn’t have the processing power to handle all that data. (If somebody wants to donate a supercomputer or cloud-based solution to the data analytics cause then hit me up on LinkedIn.)

Back to the permits: Where are the biggest new projects?

Based on the data, these are the biggest developments that were approved in August 2016:

August 2016 NYC new building permits.
August 2016 NYC new building permits.

You’ll notice that the tallest new building (NB) permits are all in Manhattan, but there are a few projects in the Bronx that are very large from a square-footage basis.

The biggest project by far is 515 West 42 Street in Manhattan. A quick Google search confirms that this is a huge 350-unit residential building. Notice that The Real Deal posted this article on August 16 and they refer to the Department of Buildings data. This supports my earlier notion of the timeliness value provided by this weekly datasource.

You’ll also see a number of permits that don’t have any height or size information. This has to do with permit types. It appears that general construction permits will have this information, but structural and foundation permits will not. At this stage, I admittedly do not know a ton about the stages within the permitting process, but it’s something worth examining in greater detail in the future.

Now, here’s what we can create using the geocoding technique above:

Each dot represents a new building permit and the size of the dot represents the magnitude of the square-footage as stated on the permit. I factored out permits that do not have square-footage information and permits that were disapproved.

Again, please be aware that I cut the data off around the “e” in the “The Bronx” on that map. There were surely permits issued east of the “e,” but I cannot process all of the data with my current setup, so I focused more closely on Manhattan.

Next Steps

The value of this type of analysis is twofold. First, you have a visual aid that accurately represents where new developments are happening. Second, you have official quantification of both supply and type.

Building out this analysis over time and forecasting construction lengths (or finding estimates in public submittal data, if it exists) would give developers significant insight into the economic direction of the New York city real estate market. Add that to the list of things I need to do!