The Real Deal New York

Market reports proliferate, but how reliable are their numbers?

More brokerages get into the numbers game
By E.B. Solomont and Eileen AJ Connelly | November 19, 2014 10:30AM

From the November issue: Need market data? You’re in luck. The already-crowded field of real estate market reports is seeing even more competition these days, as firms that previously sat out of the market-report game get in on the action. William Raveis NYC became the latest brokerage to issue a monthly market report on Oct. 30, joining Douglas Elliman, the Corcoran Group, Citi Habitats and many, many more. [more]

  • pnr

    Nice Article! And this is a complain most brokers would also have ..”our numbers don’t match with XXX or XXX….”. However there are few points to be noted before reading the market report.

    · Everyone uses different criteria to define the market, some take properties 20,000 SF and above since that is more relevant to the clients they serve while others will take something like only 50,000 SF and above. Also are they looking at class A or B or all A,B and C.
    · Definition of submarkets are blur. Is Hudson Yards in MT or MTS?
    · All the reports are talking about market average with a std deviation of +/- 20%, but if reports start talking in statistical terms most won’t understand.
    · If developers/ funds / banks or investors look at a property they generally would get a submarket study done to get a better judgment of the numbers.
    · These “free” reports are like a barometer telling you which way the market is trending, absolute numbers will never be the same.

  • Noah Rosenblatt

    Hmm UrbanDigs here. I would have loved to chine in on this topic. The answer is simple – how did the firm cleanse, standardize, normalize and join sales data with rls data. After 6+ years cleaning manhattan data I can tell how bad that data is. Integrity issues, outliers, m is – assigned nhoods, removing 20+ prop types from acris that would poison the #s, successful join ratios to rls (otherwise u don’t get the correct ppsf or ldisc or days on mkt, etc). Then u got the duplicates problem that plagues both rls and acris.

    Then u got the issue of whether the firm had the correct bldg attributes on file – think prop type, bldg age, bldg service level, bldg nhood. What about alt addresses? Oh my that in and of itself is a major piece of this puzzle. Are u properly grouping all alt addresses to the correct bldg.

    The data is so bad that we spent over 4 years cleansing it. So when I see reports like this its clear to me why the #s differ from firm to firm.

    It’s not as simple as pit the data in xls and calculate the #s. Far more is involved and the question is how numbers oriented and how deep each firm.goes.