For the fifth month in a row, the Mark Company’s Pricing Index for new construction condominiums in San Francisco has dropped versus the month before.

And on a year-over-year basis, the price index is approaching negative territory having only recorded a 2 percent gain in January versus January 2015, trending down from a 20 percent year-over-year gain five months ago (at which point we reported a significant slowdown in sales).

In terms of inventory, there are currently 650 new condominiums for sale in San Francisco, which is 14 percent lower versus the same time last year but 15 percent higher versus the month before with 8,900 net-new units of housing under construction in San Francisco and building permits for another 5,900 units either issued, approved or in the works.

44 thoughts on “Price Index for New Condos in SF Drops for Fifth Month in a Row”
  1. When is “the Harrison” (tower 2 of One Rincon) supposed to drop into the active supply? Is that considered “new” or “resale”?

  2. More interesting to me from that same trend’s report from Mark is that the resale condo values have dropped 6% YOY. That seems steeper vs my own anecdotal reference points.

    [Editor’s Note: “Due to the shift in the mix of units sold during the month, the average resale price is not as reliable an indicator…”]

  3. If this trend continues it is healthy.

    SF RE, condo or SFH, has gotten historically unaffordable. A correction, smallish, is due.

  4. 650 new condominiums for sale and 8900 under construction. This is clearly more than needed, or more than the number of qualified potential buyers. There will be an over supply of new condos.

    1. “This is clearly more than needed”

      According to whom? And “[n]eeded” for what purpose? I guess building into a bubble is great when it helps fuel the speculation and boosts your property values, but when the market cools and the extreme distortion begins to ebb, additional supply feeds into the deflation of the bubble, so that’s bad. Is that what you mean?

      1. We have hundreds of homeless living in the streets of SF. Somehow I don’t think there will be a problem in absorbing excess supply should the bubble burst.

      2. It is exactly what is needed. They will go on to sell at slightly more reasonable prices in a timeframe similar to other hot real estate markets. We are going from white hot to red hot, and that is a very good thing.

    2. Not at all clearly more than needed. Perhaps more than needed at the current (incredibly unaffordable) price points. But not nearly enough to satisfy the demand for housing at more affordable rates. Build baby build…..we need a supply driven housing price drop!

      1. Thank you for agreeing with my frequent contention here that building high-end housing doesn’t help make housing more affordable (in fact, it does just the opposite).

        1. No. High prices encourage construction. And when that additional supply comes online it reduces price pressure. Maybe lowering prices if there is sufficient supply, maybe just slowing the rate of increase if not.

          1. You can regurgitate simplistic Econ 1 theory that applies to fungible goods in ideal markets, or you can be empirical and look at history (and bubbles are well documented). Bubble are not ideal markets – they are distortions, and supply and demand work differently in distorted markets (even orthodox economics admits as much). Unfortunately, every shmoe who’s taken Econ 1 and read about supply and demand thinks he or she understands everything about economics. Ten or twenty years later, people recall the theory of supply and demand as some sort of Absolute Law of Nature, but they’ve forgotten the ceteris paribus caveat that any competent professor cites to dissuade the eager student from applying Econ 1 theory universally.

            One of the characteristics of bubble markets is that, until the bubble pops, you can’t provide enough supply to satisfy demand, because speculators will keep borrowing money to play the market for as long as the bubble keeps inflating. Bubbles have no equilibria. . The bubble pops not because equilibrating supply has been added; it pops when credit can no longer sustain the parabolic increase in price, at which point, the price begins to drop. Adding supply to a bubble feeds the bubble, like firewood to a fire. After a bubble pops, the distortions in the market fade, and supply and demand theory is somewhat more applicable (not accurately, because price discovery is highly resistant on the way down). Applying simplistic Econ 1 supply and demand theory to housing markets doesn’t correlate with historical data, but that doesn’t stop the RE biz from citing the old chestnuts to justify their preferred policies.

            It looks like 2016 will be another Minsky moment in time.

          2. I don’t think anything I said is inconsistent with there potentially being another housing bubble. More generally, of course people’s future price expectation play into supply and demand and at what price levels this supply and demand exists at. How many people can afford a $1M home that they think will soon be worth $2M? And how many people can afford a $1M home that think they will soon be worth $750k? And in most cases a builder doesn’t have cash in hand when producing supply, so they have expectations for the price they will receive. Still, higher expected prices encourage construction and make projects pencil out that otherwise would not.

            By your own admission, bubbles can’t last forever and so if there’s a bubble when the bubble is over you still end up with more units online at lower prices.

          3. “By your own admission, bubbles can’t last forever and so if there’s a bubble when the bubble is over you still end up with more units online at lower prices.”

            I said as much.

            But the Fed is dedicated to propping up asset prices, prices are sticky on the way down, assets behave differently than commodities, many sellers are not obligated to sell, market strata are frequently not fungible, etc, etc, so price discovery can be much slower, inefficient, and inaccurate on the way down.

          4. “But the Fed is dedicated to propping up asset prices,”

            Yes, so the perception that the fed can provide a near infinite supply of liquidity drives down the value of safe and liquid investments and makes risky assets look better by comparison.

            What do you think would happen if the Fed looked like it was unwilling or politically unable to keep up this supply of liquidity?

            Scarcity or at least the perception of scarcity is a key factor in price expectations. Remember the selling points of ‘buy now or be priced out forever’ and ‘they aren’t making any more land’? That’s using scarcity to drive up price expectations.

            People have looked at housing prices in areas with abundant land and easy permitting. In these areas, supply can come online quickly and abundantly and this does reduce housing price run ups.

            Now I agree that you can have a bubble type situation where price expectations become so high and so divorced from reality that these expectations dominate all other rational factors. But enforcing supply scarcity does nothing to ease that situation and in fact probably makes it worse.

        2. The Washington Post ran an interesting article recently entitled, “The Poor Are Better Off When We Build More Housing for the Rich.”

          The piece drew on the findings of a nonpartisan California government study.

          Here’s the story. It’s worth a read, even if you still end up disagreeing.

          1. Thanks for the link. After reading the actual report by the Legislative Analyst (namelink) it appears there is a rather stunning little problem. They analyzed what they call “displacement” as well as rental costs and housing construction based on two temporal data points: the year 2000 and the average of the years 2009-2013, all from the US Census ACS data, which is an excellent source.

            But, recall some macro economic mega-forces were driving the bay area in the year 2000 and were so very different by 2009. And these contributed to the difference in the affordability index in the bay area in 2000 vs during the 2009-2011 recession. Their “analysis” ignores those forces. You can refresh yourself on that roller coaster ride with the graphs at Paragon Realty.

            It is like they measured the altitude of City Hall in SF and Walnut Creek, drew a straight line between them, and called that the slope, ignoring the little ups and downs and wet spots in between.

            There are similar problems with their other major cause-effect findings. In particular, much of the “more housing” was the sprawl being built in Contra Costa County east of 680 (Antioch, Brentwood…) and similar areas toward the edges where residential areas took over farmland. And many of those areas had some huge declines in the rents after the 2008 crash, and continuing through most of the 2009-2013 period they measure. Maybe the LAO should study why those areas were the hardest hit by the recession, maybe the very overbuilding/financing of market rate housing eventually caused the financial crisis and housing bubble collapse that reduced the rents for the poor. Gotta get the whole recipe right, else how we gonna repeat this triumph.

            Anyway, the LAO report does ask some important questions, but their simplistic analysis undermines their conclusions.

          2. @Jake, Those forces effected all communities equally, so they should not be factors unless you can prove otherwise.

            The findings is a not counter intuitive. Rather they are of common sense. A simple thought experiment can prove that. Lets say your budget ranges 3000-4000. If the newer and fancier condos drops into your range because of over-supply, you could pack up and move up because they offer better value, leaving your current $3000 one for the more needy. The trickle down then makes more units available at the lower end, thereby dropping the price there.

          3. Among “those forces” was the subprime lending and fraud that fueled the areas with the greatest percentage growth due to new housing in the study period. They were the hardest hit by the financial crisis, and had the highest foreclosure rates and the greatest drops in rent right into the 2009-2013 timeframe of this study.

            And “these forces” could be very localized: “across the county there is a statistically significant difference in the age of the housing stock in neighborhoods with low and high rates of foreclosure….While newer neighborhoods in the eastern part of the county have high rates of foreclosure, Antioch’s older neighborhoods appear to be more insulated from the foreclosure wave. It is likely the disproportionate reliance on subprime mortgage products that puts homes in newer neighborhoods, like those in Antioch, at risk of foreclosure.” — “A Snapshot of Foreclosure In Contra Costa County,” Kristin Perkins, UCB.

            BTW, what you describe in your second paragraph is called “filtering.” It is a broader concept that also accounts for depreciation of older housing. The theory has been around since the 19th century and applied to analysis of housing in the US specifically for ~70 years.

            You can indulge in fantasies about finding homogeneous isotropic global economic theories, but the dismal science doesn’t afford the precision of the hard sciences, unless you can prove otherwise.

          4. You still haven’t proven that the forces were factors. Localization does not mean bias and the effect is still random, if not equal, on the communities in the study in question, and I can’t think of any reason to think otherwise. Your argument so far hasn’t brought up a reason either. If you still suspect, you could easily show the bias by running a t-test on their data.

            As for the thought experiment, it was not an exercise in theory. It is an example in reality of what you and I would do. But you could certainly draw a theory out of it by summing up the individual behaviors. It’s funny though, that you dismiss what you don’t agree as economic theories while insisting on your macro economic “mega forces” being factors without any proof.

          5. Just to be clear, here is the reason why I’m dismissing that the “mega force” was a factor. The areas that collapsed did so because they over-built. But the areas that didn’t over-built also collapsed, albeit to lesser extent. (My rent in SF in 2009 was reduced 20%). In other words, the “mega force” was just another macro economic boom/bust that reduced the rent according to the supply/demand in communities, which is the point of the study (“When we build more.., the poor are better off”) in conjunction with the displacement data.

          6. “albeit to a lesser extent”– no kidding, ever wonder why?

            And what was happening to your rent in the years before the recent financial meltdown and severe recession that collapsed prices? For most folks in the Bay Area rents were going up even though there was more housing being built. And new housing starts stopped with the collapse, yet rents went down too. Very hard to explain all of this if we leave out the localized impacts of the financial markets and recessions, ya know the ‘mega forces’ ignored by the LAO study.

            Now I’m not sure what your standards of proof are and this isn’t a court of law or a math exam. And you’ve made claims without any “proof” at all, aside from a trivial “thought experiment.”

            I haven’t dismissed any economic theories. To be fair to this study by the LAO, they don’t attempt to create any grand “theory” of housing, all they do is offer a fairly tepid “suggestion” to policy makers with several qualifications. Journalists and some uncritical Intertubers have tried to stretch the LAO’s weak analysis into greater substance.

            As for “running a t-test on their data,” well yes their data set is available in a spreadsheet, but so what? My main criticism is that this is an inadequate data set to support even the LAO’s suggestion, let alone much grander conclusions.

            At the very least if we want to see if ‘more market-rate makes cheaper for the poors’, then we have to look at more than two points in time, which the LAO should have done as the base ACS data is available by year. That was my point about mapping the topology from Concord to SF by only using the altitudes of the two city halls.

            You like randomness, then pick any two years at random and see if the data fits whatever your theory predicts, repeat that for enough random time intervals to establish significance. I await your proof. Otherwise, all you got is a narrow fact about a period in time (2000 to 2009-2013), with no justification for generalizing it into some theory of other times.
            If you don’t understand that the subprime lending debacle had greater effects on some communities than others and that in the Bay Area this aligns with the areas of both the greatest housing development during 2001 to crash and the greatest rent declines post crash, then you are welcome to the comfort of your toy supply-demand theories that exclude the impacts of finance. The reality in many low-income and poor communities in the Bay Area was not so comfortable, and rather brutal, and not random at all, as has been documented (proven?) by Kristen Perkins among others.

      2. Supply-driven price drop, too funny. Look at London, Tokyo, etc. You can bring millions more people in to an urban area and prices will likely increase. Not decrease.

        If you want prices to drop then have a 10-year moratorium on building new office space. Anyway this bubble is going to pop and hopefully thousands of never-profitable bay area startups will disappear and never return.

        1. the fact that more supply equates to moderation of housing price increases, and in some cases decreases is really undeniable. millions of cases of evidence over centuries. you earth is flat, and vaccinations are bad people really scare me.

        1. Anyone interested in real estate should learn about MInsky’s financial instability hypothesis, which describes how asset bubbles form. His insights don’t align with the neo-classical pseudo-science economics orthodoxy, so he’s still unknown outside of heterodox econ.

          1. speaking of Minsky and regarding your bubble hypothesis, how many of today’s homes for sale in SF are being purchased by “speculators” (and how did you arrive at that estimate)? what is the credit crunch you anticipate given still historically low interest rates that seem resistant to rising, mortgage terms that still limit liar loans, and still significant numbers of all money offers? most buyers still seem to be hedge buyers with little difficulty servicing their loans. (i’ve got 13 years left on my 20 year loan that is mostly covered by my tenant’s rent. i used to call myself a HENRY and felt i was only one health crisis from losing it all. this year the health crisis hit but the home is so far secure).

            for prices to really drop we seem to need both an overflow of supply and, given the really low percentage of homes for sale vs. the housing inventory, alot of people who need to sell…what’s the trigger for the latter?

          2. That’s the thing. The effect of price expectations on supply and demand are very real, but also very volatile.

            Why be in a hurry to sell if you believe your equity is only going up? Now what about if your equity is going down and you see all these shiny newer units coming online and competing with your increasingly dated older home?

            And a key point is that an expectation based change in supply is highly correlated with an inverse effect in demand and may likely be correlated with other local economic factors such as investors valuation expectation for local tech companies. And maybe even with national or global markets.

            I think that’s the key thing to look at is the degree to which factors are correlated and may contribute to positive or negative feedback.

            This is different from typical selling pressured caused by factors such as divorce, job loss from a diversified job base and health issues which are more random and less correlated with other factors.

            Good luck with your own health problem though!

          3. moderneddie: The housing bubble that popped in ’07/’08 was a primary bubble. It spawned the derivatives bubble that was even larger in notional value, and posed even greater systemic risks. This time, the local housing bubble is a consequence of the local tech bubble that itself was a direct consequence of Fed-engineered, historically-expansionary monetary policy (QE1/2/3, ZIRP, Operation Twist). Credit is clearly drying up in the tech bubble, as anyone following the economy is aware. Almost every business day for the last six months, there have been stories about down rounds, layoffs, plunging stock prices, missed profit estimates, stumbling unicorns, hedge fund hemorrhaging, and ever more absurd “tech” launches trying to get that last on-demand disruptive cloud-based sushi delivery app through the door before this business cycle slams shut. Global markets are extremely volatile, and the .01% is screaming that they are no longer getting the higher returns on their capital that they feel entitled to.

            I think the current slowdown in local housing isn’t due primarily to the thousands of the units coming on-line, but to the faltering app bubble. The thousands of units that have and will come on line will lead to an oversupply that will become obvious as the koder-kidz pack up and move back home to ma and pa, and as speculators bail on falling knives. Asset prices function differently than commodity prices, and there are many mechanisms that prevent true price discovery (among them that the Fed’s primary – albeit instated – purpose is to boost asset values).

            This is the part that I’m most unsure about: how far the Fed will (and can) go to save what are now localized housing bubbles, mainly in urban areas connected to tech and energy sectors. Last time, the bubble was nationwide, and although I don’t like the way the Fed went about it (basically saving the .1% and letting everyone else rot), national housing prices would have gone much, much lower in the absence of QE and ZIRP. This time, the housing bubble is really only in a few markets, and – supposedly – derivatives tied to housing have been reduced, so the systemic effect of a housing correction in the Bay Area and a few other places may not be as severe. I don’t know, it’s over my paygrade, but I do believe we’re in for a wild ride…

          4. This is global Minsky going on. Even bloomberg and market watch are having weekly articles about a very real possibility of a global depression. Not a ‘correction’. Anybody that doesn’t realize this is still just reading the WSJ or damn Krugman on the liberal side.

            Commodities market has been dropping for almost a year, rail freight container freight dropping here for five months, as well as from China and out of Japan. Deutche Bank is teetering. Corporations spent over $7 trillion on stock buy backs in this hot money era. That corporate bond debt alone could crash us, and the world. Baltic Index lowest since they started counting…etc and damn etc.

            Any doubters that will actually read people ‘left of center’ (most of whom predicted the last crash) will come away knowing this is it. Obama followed the greenspan, clinton, bush policies to an even worse outcome. And at this point, there seems to be no chance of Yellen ‘put’ left…except maybe neg interest rates imposed, and QE4, both which will only delay the depression. I suggest Mike Whitney, Nomi Prins, William Black, Michael Hudson, Paul Craig Roberts, Pam Martens, Yves Smith, Wolf Street, and even Gretchen Morgenson of the NY Times sometimes.

            Thanks to the speculators, tens of thousands of my neighbors, and many our of jobs had to leave for another bubble binge. Thanks so much. Experts.

          5. “What is a HENRY? Have not heard that acronym.”

            High Earner Not Rich Yet, I assume.

            These are the people who can afford and thus provide demand for a $1M house they believe is going to $2M, but would be hurting to buy a $1M house going to $750k.

            They have the income to get the mortgage, but not the net worth to comfortably take an equity hit.

      1. High end, expensive rental housing (besides the mandatory/required BMR units.)

        Some of these rentals will be taking a haircut. I think Those developers that said, “wait, sure I can cash flow off new construction, $5500 small 2BR rentals” may be disappointed in the rents they will receive 1-2 years from now. Still not cheap enough to placate socialists like 2beers, but I’m not sure how attractive it will be to keep them as rentals. Unless the developer has/had deep pockets and wants to own and operate SF rentals long term. And given that the units will be off RC, for the long term thinker these may still make sense. Depends how much $bread$ they spent on per unit cost to build.

        1. My point being that most (if not all) those rentals are mapped as condos, and can be sold off as individual units. So when the high end/high rent party ends, who knows how many of these units will remain rentals 3-7 years from now. Good chance many will be sold to individual home owners at the next “up” cycle.

        1. You mean for sale condos? My WAG is that less than half will be for sale, the others as rentals. Maybe SS has a breakdown. I saw it somewhere, where they listed if the bldg is rentals or not.

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