Since the coronavirus pandemic took the shine off expensive (and cramped!) urban living, rents have tanked in some of the nation’s top cities. But when it comes to whether it makes more financial sense to buy a home or rent one, it turns out that, in many cases, buying is still your best bet.
In more than 15 of the 50 largest metros, buying a home was as or more affordable than renting in January 2021, according to a recent realtor.com® report, up from 13 markets before the pandemic. And, on top of that, there are several “borderline” cities where the monthly cost of buying a home is within 5% of the cost of the local median rent.
Even with the historic growth in home prices over the past year, the monthly cost of buying a home in many cities across the United States hasn’t changed—mostly because of incredibly low interest rates that dropped to 2.88% in January.
The economics team at realtor.com looked at the 50 largest metros, ranked by the number of households, to put together the report. It compared the monthly cost of buying a home with a 30-year fixed-rate mortgage at each city’s median listing price, including taxes and insurance, against the monthly rent for two- to four-bedroom apartments and houses in the area. Then the team ranked those numbers to see how they stacked up to local incomes. (Metro areas typically include a city and smaller nearby municipalities; the Chicago metro includes Elgin and Naperville.)
Cities in the Midwest and South tend to offer cheaper homes and a lower cost of living than coastal California and other big tech hubs like Austin, TX, and Seattle. That’s because land is often cheaper and more abundant, construction is less expensive, zoning regulations are often fewer, plus some cities just don’t have as much demand for housing.
“Some of these, they’re Rust Belt markets. Each one of these markets has a net population loss, so that, of course, is going to create an abundance of supply and lower demand than a place that has a net population gain,” says James Wise, an Ohio-based real estate broker and host of HoltonWiseTV.
And yet overall, the number of places where it makes more sense to rent is higher. Looking at the 50 largest metros, the monthly cost to purchase a median home in January 2021 was $1,988, compared with the median monthly rent of $1,727.
But notoriously expensive California and other West Coast metros lead the list of the highest-priced cities where, financially, it makes more sense to rent because the monthly cost of a mortgage far exceeds the median rent. These places also tend to have incomparable natural beauty and outdoor access and are popular vacation destinations. Two had median list prices over $1 million.
These more expensive markets tend to have a higher share of well-paying (often tech) jobs occupied by a high concentration of young professionals who have plenty of cash to spend.
“Wherever there are high-paying jobs and employers supporting them, you’re beginning to see higher-end rental complexes that can start at $3,500,” says Ramesh Rao, a Coldwell Banker Global Luxury agent based in Silicon Valley. “When these people start looking at buying a median price home, their total cost toward any kind of roof over their head goes up two times.”
But for many of these folks, Rao says, it just feels better to pay $3,500 toward equity than give it to someone else. Throw in the tax savings and potential appreciation, that’s what keeps people buying these pricey places despite the monthly math.
So where are the best places to buy a home, or to rent one? Take a look.
Welcome to the Social Security Q&A. You ask a Social Security question, our expert provides the answer.
You can learn how to ask a question of your own below. And if you would like a personalized report detailing your optimal Social Security claiming strategy, click here. Check it out: It could result in receiving thousands of dollars more in benefits over your lifetime!
Today we return to a question we received from Douglas late in 2019. At that time, he wrote:
“My wife is three months older than me. She will take Social Security in March at 66 years old. Her full retirement age (FRA) benefit is $1,145 a month; mine is $2,412 a month.
Can I take spousal benefits when she retires, take my full retirement three months later in June, and allow her to take spousal benefits at that time?”
Following is how we replied to Douglas’ original question.
Part of the plan won’t work
Douglas, part of your plan will not work. It has always been the case that claiming spousal benefits prior to one’s FRA leads automatically to a claim for one’s retirement benefits. So, you will not be able to claim spousal benefits for three months, or any other amount of time, prior to your FRA without triggering your own retirement benefits.
Had you been born in 1953 or earlier, you could have employed the “restricted application” strategy. This strategy would have had you claim spousal benefits at your FRA, assuming your wife had claimed her benefits. Then, you could have claimed your retirement benefit in some future year. If you delayed claiming until 70, your monthly benefit would be 32% larger than it would be at age 66. But those born after 1953 are not eligible for this play.
Considering the above, I presume your plan will be for both of you to claim at your FRAs. If you do that, your wife will receive $1,145 a month plus a small spousal supplement when you claim of $61, for a total of $1,206. Of course, you will get $2,412.
The question remains as to whether your claiming choices are optimal for your situation. I used my firm’s software to explore what the optimal claiming ages are for you two. The answer depends a great deal on your life expectancies.
For normal life expectancies — 82 for you and 86 for your wife — the optimal claiming ages are 66 for your wife and 68 for you. At 68, your monthly benefit would be $2,798. (Note that your wife’s spousal supplement does not increase beyond the $61 shown above.) Given these life expectancies, your benefits will outlive you since they will shift to your wife in the form of widow’s benefits. Extending the time period that you (and your wife) will receive your benefits increases the payoff from claiming at a later age.
This result is even more evident for long life expectancies, such as 88 for you and 92 for your wife. In this instance, we recommend that your wife claim at 66 and that you delay claiming until age 70. At that age, your benefits would be $3,183.
Clearly, Doug’s plans needed some inexpensive professional help.
Got a question you’d like answered?
You can submit a question for the “Social Security Q&A” series for free. Just hit “reply” to the Money Talks News newsletter and email your question. (If you don’t already receive the newsletter, you can sign up for free, too: Click here, and the sign-up box will pop up.)
You also can find all past answers from this series on the “Social Security Q&A” webpage.
I hold a doctorate in economics from the University of Wisconsin and taught economics at the University of Delaware for many years.
In 2009, I co-founded SocialSecurityChoices.com, an internet company that provides advice on Social Security claiming decisions. You can learn more about that by clicking here.
Disclaimer: We strive to provide accurate information with regard to the subject matter covered. It is offered with the understanding that we are not offering legal, accounting, investment or other professional advice or services, and that the SSA alone makes all final determinations on your eligibility for benefits and the benefit amounts. Our advice on claiming strategies does not comprise a comprehensive financial plan. You should consult with your financial adviser regarding your individual situation.
Disclosure: The information you read here is always objective. However, we sometimes receive compensation when you click links within our stories.
Investing is an exciting prospect. But today, we’re going to discuss why stock picking is hard. We’ll talk about the “efficient market hypothesis,” and why you should understand it. And then, in light of “EMH”, what might a simple investor do?
Table of Contents show
Stock picking is exciting!
A dollar invested today might be worth two dollars tomorrow. If you pick the right companies.
Your nest egg will grow and you’ll retire in prosperous comfort. If you pick the right companies.
Catch a theme, here? How do I pick the right companies? I guess I’ll see what the stock picking experts say.
CNBC says I should buy General Motors. The Wall Street Journal says I should buy Ford. But the Motley Fool says we’re in a bear market and I shouldn’t buy anything.
Who is right? There are so many choices, so many buyers and sellers, so much information. How does a simple individual like me stand out from this crowd to make my profit?
Enter the Efficient Market Hypothesis (EMH)
This question—how can one person stand out from the crowd and repeatedly beat the market for a profit?—is the heart of the efficient market hypothesis (EMH).
It states that the market processes information efficiently. The market is really smart–probably smarter than you. The prices that the market sets are accurate. Therefore, the odds that you’ll be able to pick the right companies–buy low, sell high–are low. Beating the market is tough to do.
There are a few different variants of EMH, but they all share a few commonsense assumptions.
Assumption #1: Many agents
First, EMH is built upon the fact that the market is comprised of many buyers and sellers (or “agents”).
The market isn’t just a few dozen dudes shouting numbers and holding up their fingers at the stock exchange. It’s thousands and thousands of very smart people (and their computer programs) devoting their working lives to the task of stock picking.
Why does this matter? Because large groups of experts tend to come to better consensus decisions than small groups of ignoramuses.
Assumption #2: Agents share information
Second, the efficient market hypothesis assumes that these agents are all working off of a common set of information and that new information spreads quickly.
The agents all know about different companies’ profit reports and future projections. They know about past performance and CEO history. If stock picking was a test, then EMH assumes that all the agents have attended the same classes and use the same textbooks. All agents know information equally
Some agents will come to conservative conclusions from that information, while other agents might be more optimistic. Individual agents aren’t perfect and might overprice or underprice an individual stock.
But as a whole—as a market—the price of a stock will accurately reflect all available information.
The overpriced agents and underpriced agents will average out, and the price that the market settles on will be reflective of the stock’s true value.
That’s the heart of EMH.
Different versions of EMH
My explanation is simple and won’t satisfy some of you. I know I’m leaving some details out. Let me explain the three well-known variants of EMH.
These variants carry different opinions about how much the agents know, and how quickly the agents gather their information.
Do the agents only get to see past information? Are they up to date on all the public news about a company? Do nosy agents even get to hear private information about a company?
Strong form EMH
The strong form of EMH states that stock prices reflect all information about a company. Past info, public info, and private info. There’s a strong connection between information and the market
Let’s say you want to invest in the Best Interest Group, a well-known media conglomerate.
BIG just decided that it will start a blog about baking cookies. This decision occurred in a private meeting among BIG executives. BIG will put a team together to bake cookies, run taste tests, write recipes, etc. This will all be done internally at BIG until the blog is launched (and made public).
According to strong form EMH, BIG won’t be able to keep its secret. Employees will talk. Rumors will spread. Information will percolate into the market–that cookie was so good!–and the market will react.
Stock picking will occur and the price of BIG will reflect its new cookie venture before the cookie news goes public.
Semi-strong form EMH
The semi-strong form takes a step back from the strong form. It states that public information instantly affects stock prices, but that private info stays private. There’s a semi-strong connection between information and the market.
This is the form that is considered most accurate.
The cookie blog doesn’t affect BIG‘s stock price until BIG shares news of the blog with the public. At that point, the market agents immediately react to the news. The agents evaluate the new info and decide to buy, sell, or hold their shares of BIG. Those purchases and sales immediately affect the price of BIG shares.
Weak form EMH
Weak EMH differentiates itself because it believes that the agents don’t immediately react to new public information. Instead, the agents are aware of all past information only. Future price changes are random. How might that work?
You notice that the price of BIG has decreased on six consecutive Tuesdays and increased on six consecutive Thursdays.
Boom. You’ve got a plan. Buy on Tuesday afternoon (after a decrease) and sell on Thursday afternoon (after an increase).
But weak EMH states that stock prices only reflect past market information, and any connection between past and future prices is random.
The pattern you saw–six consecutive weeks–is just like flipping a coin heads-up six times in a row. It’ll happen occasionally. But it has no bearing on whether the seventh flip with be heads or tails. It’s just randomness.
If you buy next Tuesday and sell next Thursday, your stock market success will be a coin flip.
Summary of the three forms of EMH
Weak form EMH – the market only accounts for past information. Future price changes are random.
Semi-strong form EMH – the market accounts for past information and present public information.
Strong form EMH – the market accounts for all information – past, public info, and private info.
Does the Efficient Market Hypothesis have legs?
Are these assumptions valid? I think so.
There are thousands of people stock picking in the market, looking for little edges here and there. So yes, there are many agents out there.
And in our information-rich society, it’s easy to see how all of these agents share information. What do I mean? By the time you hear about a stock picking tip, it’s too late. For example:
Big news from BIG
9:00 AM: Best Interest Group releases a great earnings report. Things are looking good for the company.
9:01 AM: Agents (most likely computerized) who monitor BIG see the news. The information affects their evaluation of the stock. They start buying BIG.
9:05 AM: The demand for BIG stock is increasing. The price starts going up.
9:10 AM: Agents who look for trends in the market see that something is up with BIG. They use the Internet to find the earnings report. Although the stock price has already increased by 4% over the past 10 minutes, they think it still has room to grow. They buy-in.
5:00 PM: Over the day, the information continues to spread. Investors look at BIG but see that it’s already gone up.
“Is there any more profit left for me?” they wonder. “Is it still undervalued? Will it continue to go up?”
Fewer investors are willing to buy in as prices rise, and the price begins to settle. The market closes. BIG went up 7% today.
6:30PM: I see on “Mad Money” that BIG had a big day. Jim Cramer (no relation) plays lots of sound effects. The information has now spread to me. I think, “It’s hot, I should buy it!”
Next day, 9:00AM: As a “smart” stock picker, I follow the “expert” advice and buy Best Interest Group for the new price, 7% higher than it cost yesterday morning.
Big problems with stock picking
What’s the issue?
The point of buying a stock is that you think the stock is undervalued. You think the price will go up in the future. But in my simple example, the speed of new information caused the price to go up before I bought it.
The market reacted to the good news quicker than I did. I bought at a price that the market already decided was accurate to the true value of the company. By the time I reacted, it was too late.
We can conclude the assumption of “information is shared quickly” makes sense.
What’s left for me to make my profit? The only way to beat the market is to:
Obtain information before everyone else
Process that information correctly
Do so consistently.
EMH states that these three requirements are too much for an individual to do. There is too much competition—too many other agents—for any one person to be faster, better, and more consistent.
If you try to handpick winners and losers, EMH states that you’ll end up performing the same as the entire market, and any variation from that (e.g. if you outperform the market) is random.
Some stock picking will make you look genius, but those will be mitigated by the picks that make you out a fool. In good times, you’ll do well. In bad times, you’ll do poorly.
What’s wrong with average stock picking?
First, you’re going to spend time to hand-pick these stocks. You’ll read, watch financial shows on cable TV, maybe play around with a spreadsheet or some graphs.
Second, some brokers charge fees to buy and sell. Those fees will add up.
You’re spending time and money to hand-pick stocks, and EMH states that you won’t perform any better than the market as a whole. Or, if you let an “expert” hand-pick those stocks on your behalf, you’ll save the time but also pay more in terms of an expense ratio fee.
What’s the alternative to stock picking?
Just buy the whole market. There’s no long-term advantage to hand-picking individual stocks. EMH concludes that paying high fees for “expert” opinions is a waste of money.
Any above-average performance is random, like a monkey throwing darts at a board. The monkey might hit a bullseye, but does that make the monkey an expert darts-man? (Hint: no, it does not make the monkey an expert darts-man).
Your best bet is to pay the smallest fees possible to buy a share of the whole market. How do you do that? They’re called index funds, and they have been revolutionizing the financial markets since the 1970s. Some of you might have heard about a problematic index fund bubble–I cover that too.
More reading about index funds:
Could EMH be wrong?
While EMH makes sense, it isn’t gospel. It’s just a hypothesis, and many economists are taking a scientific approach to poke serious holes in the theory.
For one, market agents have biases, and sometimes those biases won’t “average out” over the whole market.
And two, sometimes people are just dumb. Here’s a recent example comparing Zoom Video Communications against Zoom Technologies. The former makes the video conferencing software that has exploded in popularity due to COVID 19. The latter is a different company making a different product.
But you wouldn’t know that by looking at their stock prices.
While the “right” Zoom was up 100% (since the beginning of 2020) by mid-March, the “wrong” Zoom was up more than 2000%. Why? Because people messed up.
How does an efficient market not fix that?
Of course, there are other arguments against the efficient market hypothesis.
An irrational excitement might sweep the entire market, and an investment will be overpriced or underpriced, thus opening the door for a wise investor to move in and make legitimate money.
Many experts point towards cryptocurrency as an example of this “sweeping excitement.” The true value of cryptocurrency didn’t rise and fall by hundreds of percentage points over the course of one calendar year.
So why did the price rise and fall that much? How does EMH explain that?
Too complex = bad information
Another argument against EMH is that some investments are too complex for the market to grasp. If only 10 people in the world understand a particular investment, then how can the entire market evaluate it rationally?
The EMH assumption of “too many agents, too much competition” does not apply if only a tiny number of agents have a proper knowledge of the investment.
Some critics point towards individual events—e.g market crashes—as glaring evidence against EMH. If the market was all-knowing, why didn’t more people see the 2008 recession coming? Why weren’t there more “Big Short” people?
Countering the counter-points
The proponents of EMH have explanations for these examples. In short, EMH is concurrent with the explanation that some investments are “too complex.” This complexity explains the “bias” or the “market crash” outcomes.
Take cryptocurrency, for example. The value of cryptocurrency (according to a guy on YouTube) is based on complex mathematics and a deep understanding of how value is assigned to an asset. It’s graduate-level math and graduate level economics and graduate-level YouTube (Don’t forget to Like and Subscribe!).
It’s not an easy concept for most folks to understand.
When the cryptocurrency bubble expanded, it wasn’t based on widespread knowledge in a rational market. There weren’t thousands of knowledgeable investors saying, “I completely understand cryptocurrency technology, and I know why it’s undervalued.”
Instead, it was based on irrational excitement towards previous gains, and the fear of missing out on future profits. Fear and excitement are not rational.
On the Great Recession
Similarly, the market crash of 2008 was influenced by obscure and misunderstood investments in the housing market.
Subprime mortgages and collateral debt obligations were, according to EMH proponents, intentionally designed to be complex and difficult for most market agents to understand. Information about these housing investments was kept hidden, or the information that was made public was inaccurate.
In other words, the hallmark requirements of EMH—numerous knowledgeable agents and widespread information—did not apply to the 2008 Crash. And it was done that way intentionally.
Large investment firms believe in EMH so much that they are trying to manipulate the market (create complex investments, keep information private) in order to prevent the market from efficiently evaluating their investment vehicles.
By keeping information close to their chest, they believe they can fool the market and hoard the subsequent profits.
EMH makes a lot of sense if the market is an even playing field. But if the assets are too complex, EMH won’t apply. If the information about those assets is too far from the truth, EMH won’t apply.
Stock picking summaries
We covered why stock picking is hard, whether the market is “efficient,” and what we might do in response i.e. look into index funds.
At the end of the day, do what you will. But I’m avoiding dart-throwing monkeys. I’m not trying to out-compete all the other agents.
Average indexing is just right for me. It’s efficient.
Big gains are likely for economy this year even as COVID-19 damage lingers
Fed meeting:Powell says economy is ‘a long way’ from Fed’s goals and central bank has no plans to raise interest rates or reduce bond purchases
Should you fear higher yields?
Some investors worry that an increase in bond yields and longer-term interest rates will end the market’s runof steady gains. Remember, stocks have rebounded to record highs following a historic plunge last spring. These gains could be threatened because higher yields make it more expensive to borrow money, and that tends to slow down economic growth, which could be bad for stocks.
The numbers: The index of pending home sales fell 2.8% in January after four consecutive months of declines, the National Association of Realtors said Thursday. The index captures real-estate transactions where a contract was signed but the sale has not yet closed, making it an indicator of where existing-home sales will go in the months ahead.
The median forecast of economists polled by MarketWatch had called for a 0.5% decline in pending sales on a monthly basis.
“Pending home sales fell in January because there are simply not enough homes to match the demand on the market,” Lawrence Yun, the chief economist for the National Association of Realtors, said in the report. “That said, there has been an increase in permits and requests to build new homes.”
Compared to 2019, pending sales were up 13%, indicating that the housing market remains strong despite the weakness that has crept in during the winter months.
What happened: Pending sales didn’t fall across all regions, as contract signings increased slightly in the South. The largest decline in pending sales occurred in the West, where the index dropped 7.8%, closely followed by the Northeast (-7.4%).
The big picture: A record-low inventory of homes is leaving buyers with few options to choose from, and builders have even begun selling a vast array of properties that haven’t been built yet to meet this demand.
But there’s evidence that demand could begin to suffer as affordability concerns grow. “The timely weekly mortgage purchase applications index is signaling a slowing in activity,” said Rubeela Farooqi, the chief U.S. economist at High Frequency Economics, while citing mortgage application data from the Mortgage Bankers Association. The latest reading signified the lowest level for mortgage applications since mid-May of last year, Farooqi noted.
Some of the decline in the volume of mortgage applications was a reflection of the disruption in Texas caused by recent winter storms. But generally speaking, rising mortgage rates are reducing interest from home buyers to an extent. With prices also quickly rising, buying a home is becoming less and less affordable, which could hinder home sales in the months to come.
What they’re saying: “Home buyers are staying surprisingly active during the colder months. However, buyer demand is getting squeezed by a scarcity of ‘For Sale’ signs and rising mortgage rates,” said Realtor.com senior economist George Ratiu.
Extreme increases in lumber prices have caused some people to go bearish on new home sales. Not this one! If we play a version of rock, paper, and scissors with lumber prices and mortgage rates, mortgage rates will win. Mortgage rates have a much more significant influence on the new home sales market than lumber prices, even at their current highs.
Proof of this is the recent new home sales report released by the CensusBureau. New home sales beat expectations by a lot, and all the revisions to the last report were positive.
Last month, I wrote that we should have expected new home sales to moderate after their parabolic rise.
Sales are still working to find a sustainable trend after the massive distortion in all housing data lines due to COVID-19. This recent report, especially regarding the positive revisions to the last report, tells a solid story for new home sales in 2021 as long as rates stay low.
From Census: “Sales of new single-family houses in January 2021 were at a seasonally adjusted annual rate of 923,000, according to estimates released jointly today by the U.S. Census Bureau and the Department of Housing and Urban Development. This is 4.3% (±18.1%)* above the revised December rate of 885,000 and is 19.3% (±19.5%)* above the January 2020 estimate of 774,000.
When reviewing new home sales data, it is wise to keep an eye on the monthly supply. When the monthly supply is 4.3 and below, builders will have the confidence to continue building. This is especially true when the 3-month average is 4.3 months or below. Currently, inventory is at four months with a three-month average of 4.06 months of supply, so it’s looking pretty good. The revisions on this report showed a lower monthly supply than in the previous month.
The low monthly supply is why builders’ confidence is high, despite the massive spike in lumber prices. As a high school basketball coach in my previous life, I know that sometimes all that matters is that you shoot better than your opponents. Don’t overthink it. Better sales plus lower inventor equals increased builder confidence.
Today, the MBA’s purchase application data was also positive by 7% year over year, even with the President’s Day holiday and the Texas snowstorm — two factors that typically hurt applications. Positive year-over-year growth is a good thing.
So far this year, our year-over-year comparisons have been against a “pre-covid” housing market. March 18 is almost here, which means year-over-year comparisons of housing data are going to get funky. If you see scorching year-over-year growth – don’t be fooled that it will be a sustainable trend.
Purchase applications in 2021 have exceeded my estimated peak rate of growth of 11%. I expected to see a trend growth rate between 1%-11% year over year, up until March 18. We are currently trending at 12.375%. The substantial purchase application growth speaks well for housing sales 30 to 90 days out.
The take-home message is that sales are strong, which will contribute to hotter home prices. Right now, we want the rate of growth to cool down.
Next week for HousingWire, I will explain why we should expect to see some purchase application data show weaker year-over-year data in the second half of 2021. There is more to this story than higher mortgage rates.
Even on a foggy San Francisco morning, the view from Scott Simmons’ 25th-floor apartment stretches from downtown to Golden Gate Park. The home of the 42-year-old tech worker is also spacious for a one-bedroom, featuring hardwood floors, new appliances and granite countertops.
A year ago, when he was sharing a two-bedroom place with his brother, Simmons couldn’t have imagined living in an apartment like this one. But last fall, when Simmons heard about big rent declines during the COVID-19 pandemic, he discovered he could get way more for his money in the heart of San Francisco than in the neighborhood where he was doubling up in Oakland.
“It’s bananas,” Simmons said. “I never thought I was going to be someone who was going to have a nice view. It’s a luxury.”
Since March, when government stay-at-home orders began emptying downtowns of workers and shoppers, the average rent for a one-bedroom apartment in San Francisco has dropped nearly 30%, the largest decrease in the country. The tech capital has hundreds of thousands of employees well positioned to work remotely, and they have. Outside the city.
The pandemic’s toll on San Francisco has created a scenario long unthinkable in the Bay Area. For some renters — mostly middle- and upper-income earners — it’s now more affordable to live in the famously expensive city than in its bluer-collar neighbor, Oakland.
“If you would have told 15-year-old me that 15, 16 years down the road that Oakland was going to become more expensive it would have been literally shocking,” said Amar Saini, 32, an Oakland native who moved into a 12-story apartment building near the Bay Bridge this month to save money. “I just don’t believe it.”
San Francisco, even as rents decrease, remains the nation’s costliest big city. A one-bedroom apartment still typically rents for almost $2,000 a month, putting it far out of reach for many residents. But the steep drop in prices has surprised real estate watchers for both its depth and scale. Even landlords in tony neighborhoods like Pacific Heights and Russian Hill, who once were charging $4,000 a month for one-bedroom apartments, are lowering their prices and offering incentives like months of free rent to get tenants in the door.
The rent declines are a direct result of the pandemic. More than half the city’s employees are able to work remotely, according to the Bay Area Council Economic Institute, and tech firms like Twitter and Salesforce — the city’s largest private employer with more than 9,000 workers — have said employees can stay away from the office even after the pandemic ends.
Additionally, the pandemic has closed restaurants, bars and museums, while putting a premium on locales that offer people more space to work or their kids to attend school virtually. For San Francisco, a dense city that long has had some of the nation’s highest rents, all the changes have taken away many of the amenities that make city life vibrant. Data from the U.S. Postal Service show that 56,000 more people requested address changes out of San Francisco in 2020 than those moving in.
“Every man, woman and their dog is saying there’s no point living in downtown San Francisco if you’re not going into work,” said Nicholas Bloom, an economics professor at Stanford University who is studying remote work during the pandemic.
The stillness of once-bustling San Francisco neighborhoods can be jarring. In Union Square on a recent weekday, a handful of masked pedestrians and homeless residents roamed silently amid hotel lobbies, restaurants and luxury stores largely empty of customers. Closed businesses along Market Street, one of the city’s main commercial boulevards, were boarded up with plywood. Shops that remained open had signs displaying reduced hours.
A year ago, only about 1% of the units managed by members of the San Francisco Apartment Assn., the city’s largest landlord group, were vacant, said Janan New, its executive director. Now, she said, nearly a quarter are empty.
At a new, upscale apartment building across from Twitter’s headquarters on Market Street, the sales office is offering up to three months of free rent. If that’s not enough incentive, new arrivals can also get a year of free cable and internet, several personal training and massage sessions or have the landlord donate $1,000 to a local charity on the tenant’s behalf.
Such efforts to attract middle- and upper-income residents reflect the pandemic’s uneven economic impact. White-collar employees who are able to work from home have been far less affected than lower-income workers in service and hospitality industries.
Maria Marin and her husband, Francisco Rodriguez, were once able to crowd into a one-bedroom apartment near Bayview with their three young daughters. But after the pandemic hit, Marin lost her job as a housecleaner, and then her husband got COVID-19 and lost his warehouse job.
Unable to pay the $2,000 monthly rent, the family moved in with Marin’s mother near Potrero Hill. Ten people now share the three-bedroom home while Marin and her husband seek employment.
“In my situation, it’s not true that the rent is down,” said Marin, 35. “They ask you to make two or three times the rent to qualify for an apartment. And when you don’t have it, they hang up the phone.”
Rents have decreased in Oakland as well with the average one-bedroom now going for $1,625, according to Apartment List. But the 18% gap between Oakland and San Francisco prices is the narrowest since the real estate firm began tracking rents in 2017.
Before his move, Simmons enjoyed living in Oakland’s Uptown, a walkable community not far from the Fox Theater, and first looked for a new place around there.
But he found nicer apartments in San Francisco, and living there meant he could ditch his car. Simmons signed a lease for $2,800 a month in a 29-story building also across the street from Twitter. The landlord gave him $2,000 in debit cards as a bonus.
“I like walking places. I like meeting people. I like the busyness,” Simmons said. “This is the life I want.”
Soon after last spring’s stay-at-home orders went into effect, Armand Domalewski and his girlfriend decided to leave their roommates and look for an apartment together. They searched around Oakland’s Lake Merritt in the hopes of living near open space.
“Then we looked in San Francisco,” said Domalewski, 31, a data analyst. “Not only were the prices lower than I ever expected, they kept getting lower.”
The couple found a bright, second-floor apartment on a narrow, red brick street near Duboce Triangle for just under $3,000. “I walked in and said, ‘There’s a dishwasher, my God,’” he said.
A few months into their lease, another tenant in their building moved out and they got a call from their landlord. Domalewski feared the worst.
“You’re so conditioned to think, ‘Oh, my God, am I getting evicted?’” he said. “And then she was like, ‘I’m unilaterally lowering your rent.’ And we’re like, ‘This is crazy.’”
Rents have even become affordable for recent college graduates.
A few months after graduating from UC Berkeley, Sarah Abdeshahian got a job as an organizer with the Tenderloin Housing Clinic in San Francisco. She was astounded to be able to find her own one-bedroom apartment near the top of Nob Hill for $1,900 a month, a price that had been reduced by $400.
“The idea of an entire apartment to myself is an insane luxury to me,” said Abdeshahian, 22. “I thought of San Francisco as a place where only wealthy tech people could live, not someone working at a nonprofit just out of college.”
Even though rents have plummeted, they could bounce back. Tenants with long memories plan ahead.
Simmons said he could have moved into a newer apartment complex for the same money.
But he opted for an older building. It came with rent control.
The National Association of Realtors reported that existing home sales for January were at 6,669,000, which beat estimates. The year-over-year growth was an impressive 23.7%. The median sales price also jumped 14.1% year over year, which I warned could happen during the years 2020-2024. On a recent HousingWire podcast, I discussed the need for higher mortgage rates to cool down this growth rate.
Currently, the 10-year yield is 1.35%, which is now above a critical level that I have talked about for some time. We should all be jumping for joy as the bond market shows the American bears that America is back. Mortgage rates should also creep higher. When the 10-year yield gets into the range of 1.33%-1.60%, we will have achieved our goal for the “America is Back” economic model that I proposed last year, which I believe could only happen in 2021.
With the yield in that range, we can expect the mortgage rate to move up toward 3.375%. We still have a lot of work to do to earn the right to create this range in the bond market; the first would be hitting 1.60%, which we haven’t yet. The chart below shows the 10-year yield as of the close of Thursday. Today, bonds are selling off and yields are higher.
Mortgage rates are still meager, historically speaking, but 3.375% or higher may be enough to slow the home price growth rate – which, right now, is simply too hot. The days on the market went from 43 days last year to 21 days currently.
So far this year, the MBA purchase application data is running stronger than even I thought. This metric is a predictor trend of demand 30-90 days out. I believed the peak rate of growth in purchase applications would be around 11% year over year up until March 18th. It is trending at 13.1% this year, so we are off to a good start for 2021.
New home sales, existing home sales, and the builder’s confidence index that went parabolic towards the end of 2020 have stopped going up and started to fall. The last report on new home sales shows that housing data moderates and moves back to the trend.
The monthly sales prints for existing home sales show that this metric has stopped its parabolic move higher, but it still has not moderated enough. We still have not completely made up for the lost sales in 2020 due to COVID-19. We should have ended 2020 with 5,710,000 -5,840,000 in existing home sales but only realized 5,640,000. This number is only 130,000 higher than what we had in 2017, so this isn’t the booming speculative buying we saw during the height of the housing bubble years.
Once this makeup demand is exhausted, existing-home sales should moderate toward 6.2 million or even lower to get back to the trend. If existing home sales stay above 6.2 million on the monthly sales print for the entire year, we can consider the demand to be even better than expected.
For the rest of the year, the single most important and healthy event for the housing market would be higher mortgage rates to cool down home prices’ growth rate. We will see if mortgage rates rise high enough to cool demand and reduce the multiple bid situation we currently have in many markets.
Nobody wins when the housing market is too hot – not even sellers because they will need to find somewhere else to live. We have enough supply to grow sales to pre-cycle highs, but when choices are limited, the willingness to sell and move becomes less attractive.
Overall household debt increased by $206 billion in the fourth quarter of 2020 to $14.56 trillion, according to the Federal Reserve Bank of New York. The Fed said that increase was primarily driven by a dramatic increase in mortgage originations.
Mortgage debt balances broached the $10 trillion mark in the fourth quarter, increasing by $182 billion from the third quarter to $10.04 trillion at the end of December, the Federal Reserve Bank of New York’s Center for Microeconomic Data said Wednesday.
New mortgage originations, driven by record-low interest rates that propelled refinancings, totaled $1.2 trillion in the fourth quarter, surpassing volumes seen during the historic refinance boom in the third quarter of 2003, the New York Fed said.
“2020 ended with a substantial increase in new extensions of credit, driven by record highs of new mortgages and auto loan originations,” said Wilbert Van Der Klaauw, senior vice president at the New York Fed. “Notably, the overall median mortgage origination credit scores jumped up, reflecting a high share of refinances.”
Delinquency rates also continued to decline in the fourth quarter, attributed to forbearance exits provided by the CARES Act. The share of mortgages that transitioned to early delinquency dropped to 0.4% in the fourth quarter, according to the New York Fed’s data. As of late December, the overall share of outstanding debt that was in some stage of delinquency was 1.6 percentage points lower than the rate observed prior to COVID-19 in the United States.
From forbearance to post-forbearance: How to make the process effective
To accommodate the large volume of loans still in forbearance, mortgage servicers must have functional, flexible and effective forbearance processes in place. Here are some actionable steps to create that process.
Presented by: FICS
Roughly 121,000 Americans had a bankruptcy notation added to their credit reports in the fourth quarter, a decline from the third quarter and a new series low, the New York Fed reported.
While mortgage activity increased dramatically, credit card balances increased by just $12 billion in the fourth quarter, $108 billion lower than they had been at the end of 2019. That represented the largest year-over-year decline since the Fed began tracking the series in 1999.
Student loan balances and auto debt increased by $9 billion and $14 billion, respectively. Overall, non-housing balances (including credit card, auto loan, student loan, and other debts) increased by $37 billion during the fourth quarter but were lower year over year.
On Wednesday, a number of Democratic U.S. senators, including Elizabeth Warren, D-MA, lobbied President Joe Biden to cancel $50,000 in student debt for those with student loans. Biden has said he is only willing to cancel up to $10,000 per debtor.
The New York Fed also found that the median credit score of refinancers and repeat buyers was just below 800 at the end of 2020, about 60 points higher than that of first-time buyers.
“With a look to the series history, new mortgages are more prime — for even first-time buyers, median credit scores have slowly drifted up since 2002-06, when they hovered in the high 600s,” the New York Fed said in an accompanying report, called Liberty Street Economics.
The New York Fed noted that some 7.2 million mortgages were refinanced in 2020, which, while spectacular, was still less than half the 2003 total of 15 million.