original loft asking prices are working with about the same frequency
To my mind, an asking price for a Manhattan loft is successful when it generates an offer from a qualified buyer that leads to a contract (more successful if it leads to multiple offers, but stick with basic success here, please). Another way to look at it is that owners of lofts that sell off an original asking price have done a better job of anticipating what buyers are willing to spend than owners who have to discount the ask to get a deal, and a much better job than owners who don’t succeed in attracting offers from qualified buyers. I believe that in periods of changing market conditions (especially, in markets in which buyers have relatively more leverage) it can be difficult for sellers to accurately predict where the buyer pool will bite. (Hence, my reference to sellers “chasing the market down” in 2009 in my June 16, Manhattan Loft Lab at 40 West 15 Street features building record, failed marketing, opposite styles, + more!.)
I have suspected that recent loft sellers were relatively better at predicting the sweet spot for the buyer pool than a year ago, but when I tested that surmise against my data … no deal! One the one hand, it hurts to be wrong; on the other hand, it is nice to have a data-driven answer to the question.
If you’ve spent any time with the Google Drive spreadsheet on which I share my Master List of downtown Manhattan loft sales below $6mm, you see a lot of color. For present purposes, the key color is blue, which I use in the original asking price column to highlight downtown Manhattan lofts that sold with no reduction in asking price. I generally add the colors after I do a update to the Master List, eyeballing the two asking price columns (“I” and “L”) for matches. (If I were a spreadsheet ninja I could automate that, I assume, but … never mind.)
The physical act of adding a fill color to a column, and then seeing how much that column fills with the fill color, can be startling, with sequences of five or six blue lines in a row. Hence, when I just completed a large update to my master List of downtown Manhattan loft sales, I added (what felt like) a lot of blue.
Going back to March 1, 2017, I counted this weekend 62 blue original asking prices, 44 not blue (or 58% of completed downtown Manhattan loft sales succeeded without reducing the original asking price). I looked at a similar period in 2016 and found … (wait for it) … a 55% success rate (86 blue, 70 not blue). (There were more data points in my 2016 set mostly because it takes a while for deeds to be filed, and if I ran this exercise again in a month for the period March 1 to June 8 there will be more data points, as more deeds reflecting closings in this period are filed.)
First reaction: hmmm, that’s hardly different. Second reaction: humility, with a touch of gratitude that I now have a factual basis regarding a previous suspicion.
Because I tend to get a bit anal about such data (once I look for it, ahem), I ran the same count for the same period in 2015: 97 blue listings and 41 not blue (or a success rate for original asking prices for downtown Manhattan lofts of 70%). Now that’s different! You don’t want such limited data sets (these are still small numbers, after all) to lead to rigid conclusions, but these limited sets imply that owners of Manhattan lofts were more successful at predicting where buyers were in a 100-day period two years ago than in the same 100-day period last year and this year.
Fascinating (to me)! But Your Mileage May Vary.
you may prefer different numbers to measure the Manhattan real estate market
I don’t compute the discount that successful Manhattan loft owners needed from asking prices to get deals that closed, but if you want to, the data points are in the Master List. Or, you could look to The Miller for the overall Manhattan market, as he reports the listing discount from last asking prices in his quarterly reports (for example, for the First Quarter of 2017, which shows 4.2%, compared to the prior quarter of 5.3%, and compared to the same quarter in the prior year of 2.1%). Good stuff, from a much larger data set, collected a bit more rigorously and comprehensively (ha!) than my Master List, measuring a slightly different thing.
More data is good!
the Manhattan loft marketing efforts that are invisible in this analysis
Permit me to make a distinction about what closed sales data reveals that is both obvious (in that it is definitional) and subtle (in that it is easy to overlook): closed sales data is not the only data in any market, as it omits, most specifically, Manhattan lofts that are offered for sale but not yet sold in any given period, as well as Manhattan lofts that were offered for sale and then taken off the market without selling.
The selection bias in my blue / not blue Column “L” as a window on how well loft owners predict buyer price interest is that it considers only loft owners who originally (blue) or eventually (not blue) predicted what asking price would lead to a deal that closed. In other words, only successful owners (those who become “sellers”) are included.
My excuse is that I am not as interested in those data points and that they are, in any event, relatively more difficult for me to track. (So much data, so little time ….)
about the colors …
The Master List also has green fill in Column “F” to highlight lofts that sold above the last asking price, yellow fill in Column “I” to highlight lofts that sold at the last asking price, some reddish fill in Column “K” to indicate if the loft found a contract within 30 days of the original listing date, and even a purplish fill in Column “B” if I have blogged here about that loft sale. You will also find the occasional red numbers (not fill, but character colors) which i have started to use to highlight a number that I think is weird, or interesting, or otherwise special; though I leave it to you to figure out why in each particular.