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How serious are the errors in MLS sales price data? [stats]

For the first time ever, the accuracy of sales price data in the MLS has been analyzed, and the study’s authors express to us how these inaccuracies could have happened and what we must do now.

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For years, appraisers, economists, and other experts have quietly questioned the discrepancies between multiple listing services (MLS) prices the legal prices recorded on HUD-1 forms (and filed in local jurisdictions).

A new study published by the journal of the nation’s leading appraisal organization provides the first hard evidence that errors in sales prices reported by MLSs could be significant, especially when peak prices start to decline.

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Though the study’s scope was limited to one large MLS, its findings suggest that potential for similar errors in the nation’s 800 multiple listing services could have such serous impact on consumers that the three economists at Florida Gulf Coast University who conducted the study advised appraisers that are suspicious of a price to use another source for verification.

l6.25% of transactions overstated HUD1 data

Reported Price Errors: A Caveat for Appraisers” by Marcus T. Allen, PhD, Kenneth M. Lusht, PhD, MAI, SRA, and H. Shelton Weeks, PhD is published in the current issue of the Appraisal Journal.

The economists looked at 400 transactions in a Southeastern state from 2004 to 2008, including the two years prior to the peak price year of 2006 and the subsequent two years. They compared data from HUD1 forms with prices reported to their MLSs by listing brokers, usually after sales contracts were signed by before settlement.

They found that MLS-reported prices differed from HUD1 prices 8.75 percent of the time over the four-year period. Some 6.25 percent of the transactions overstated the HUD1 data and 2.50 percent understated the HUD-reported prices.

The largest overstated error was 21.44 percent of the of the HUD-reported price and the largest understated error was 1.09 percent of the HUD-reported price. The average overstated price was $14,038, or 6.69 percent of the HUD-reported prices.

Data suggests that errors were not random

Considering the size and complexity of MLS databases, an error rate of less than 9 percent of all sales over a four-year period is an issue to be addressed but not unexpected.

What rings alarm bells is the timeframe in which the errors occur.

Errors weren’t spread evenly over the time period, but doubled in 2006 to more than 15 percent of transactions, when prices peaked and began to fall in the Southeastern state, followed by nearly as many errors in 2007 and 2008, when the crash accelerated.

The timing of the errors suggested they were not random mistakes but were driven by marketplace conditions.

Are prices intentionally inflated?

From the evidence, the authors suggested two viable explanations for the market-driven error rates. The first was that some brokers intentionally inflated sold price information in the MLS, perhaps to make it appear that they negotiated a higher price for their clients.

If brokers and agents were overstating sales prices to bolster reputations seven or eight years ago, what’s happening today?

MLS sales price data is more important than ever for agents who want to “prove” their value to customers. The emergence of ratings services that use MLS sales data to rate agents and brokerages increases the pressure on brokers and agents to quantify their value to their customers and clients. Some rating services use public sales data to assess sales prices, others use MLS sales data and others allow agents to enter their own. MLS sales data also gives brokers a way to assess the value of agents in their local markets.

What could have caused the misstated prices

“I don’t think agents were deliberately misstating prices, though that’s a story that fits the facts,” Dr. Kenneth M. Lusht, one of the study’s three authors, tells us. Lusht is a Distinguished Professor of Real Estate at Florida Gulf Coast University, past president of the American Real Estate and Urban Economics Association, and a past trustee of the Appraisal Foundation.

“The second thing that could have happened, and it’s pretty likely, is that when you’ve got a down market, buyers get cold feet. They start thinking about not going through with the sale and giving up their deposit. So another story that’s consistent with what we found is that the price the broker submitted was the agreed upon price but between that the time he submitted it to the MLS and the settlement day the price was changed and the broker never changed the data because there is no incentive to do so.”

Lusht added that conveyances can add to the post-contract price. “In a down market that’s more likely to occur when a seller says, ‘Look, I’ll throw in the furniture to try to make the deal.’” Likewise, in down markets, sellers are more likely to subtract the cost of repairs rather than quibble over them at closing.

Whatever the cause of the errors, the study concluded, “Regardless of the motivation or source of the error, the result is the same – a misstated price.”

More research is now necessary

The authors admit that the study’s small size limits the generality of its conclusions. The geography and time frame might also be an issue. Prices in the Southeastern markets they studied were some the most volatile in the nation during the four years of the study – it was the height of Florida’s foreclosure crisis. Only one MLS was involved and policies toward gathering and checking price data vary by MLS. Much has changed in the world of MLS data and appraisal standards since 2008.

However, Lusht maintains that the problem of MLS errors is longstanding and certainly not limited to one or two markets. “I would say that any appraiser who has a reasonable amount of experience already knew there were errors in the MLS. They knew that it is very possible some of the prices weren’t right. But no one has ever measured it before and found how frequent the errors were or how big they might be.”

The study is receiving a lot of interest and Lusht believes more research is warranted.

“Maybe someone else will get interested in it and look at different areas to see if what we found is typical or not. My guess is that what we found here, we will find in other markets, especially during down markets,” he said

In search of a solution

MLS price data is valuable because it is current, and available within days of settlement. But if the Florida Gulf Coast University study is right, an average or one out of every twelve sales prices is wrong, and one out of every seven during down markets.

It can take local governments as long as three months to post official sales price data.

That’s why price reports like Case-Shiller and CoreLogic that only accept public data come out as late as two and a half months after the fact. That’s a long time when you’re a home seller or buyer trying to figure out what prices are doing in your market.

There’s no doubt that long delays seriously compromise the usefulness of public data.

Currency is a major reason the use of MLS price data is widespread. Hundreds of MLSs themselves and Realtor associations at the national, state, and local levels use the data in market reports for their members and the general public.

National web sites and brokerages, from Realtor.com to Redfin and RE/MAX use MLS price data in their reports. Hundreds of thousands of agents and brokers rely on it to counsel their clients and customers.

For MLSs themselves, the sale of data, including price data, has become a significant source of income that would be even more valuable if this issue of price errors can be resolved successfully.

And now for the solution

So where’s the solution? Is there a way to make MLS data more accurate or public data more timely or both?

One possibility has been created by TRID, the new closing process that took effect last October.

Lenders are required to provide their borrowers with final costs, including final prices three days before settlement. With final numbers available earlier than ever, will brokers be able to report prices to their MLSs months before they are posted in the courthouse?

Unfortunately, this solution may not be as easy as it looks. Privacy concerns are an issue and many lenders are resisting making the new TRID forms available to agents. Discussions are underway to work out a solution.

Other parts of the solution might include:

  • Double checking broker-supplied data when public data becomes available, an expensive proposition for MLSs that corrects errors after the fact, but doesn’t really solve the problem;
  • Better education and training to encourage agents and brokers to file corrected contract prices that have changed between contract signing and settlement;
  • Clearly label contract prices as pending sales and be sure they are replaced with sold prices after settlement. This might include user-friendly software, including mobile apps, that reminds agents to file price data and makes it easy to enter data. The software could also aggregate accurate price and sales data for agents and brokers to use in their marketing efforts;
  • Conduct additional research that builds upon the Florida Gulf Coast University study to identify market conditions, geographic regions, property types, seasons of the year and other factors that correspond to increased errors; and
  • Undertake periodic analyses of errors by MLSs to identify specific brokers and agents who might account for a preponderance of errors.

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Steve Cook is editor and co-publisher of Real Estate Economy Watch, which has been recognized as one of the two best real estate news sites in the nation by the National Association of Real Estate Editors. Before he co-founded REEW in 2007, Cook was vice president of public affairs for the National Association of Realtors.

Real Estate Big Data

Are people jumping back on the flipping bandwagon?

(REAL ESTATE NEWS) House flipping is fun to watch on tv, but the housing crash ended the big wave of investor flips – is it that time again?

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flipping houses

Just when you thought all those shows about flipping houses on HGTV were going to be obsolete, the entity behind the nation’s largest property database, ATTOM Data Solutions, drops news that home flipping may be on the rise in emerging markets.

ATTOM’s Q3 2017 U.S. Home Flipping Report found that there was an influx of flipping and market competition in 44 out of the 93 metropolitan markets.

“A more than nine-year low in the ratio of flips per investor is evidence of this increased competition,” Daren Blomquist, senior vice president at ATTOM Data Solutions, said at the release of the report on Thursday. “[This] is pushing many investors to new metro areas that often have weaker market fundamentals but also come with a bigger supply of discounted distressed properties to flip.”

In order to perform the statistical analysis included in the report, ATTOM maintained its analytical definition of flipping from previous years. The property data firm defines a flipped home as a property “sold in an arms-length sale for the second time within a 12-month period based on publicly recorded sales deed data” that was collected by their research firm.

Areas with the largest revitalized interest for flippers: Baton Rouge, Louisiana (up 140 percent); Winston-Salem, North Carolina (up 58 percent); Salem, Oregon (up 51 percent); Indianapolis, Indiana (up 51 percent); and Buffalo, New York (up 47 percent).

However, this flipping increase of 47 percent of markets is bucking the national trend of shifting away from flipping. Nationally, the report finds that while from Q3 to Q2, the rate of home flipping has decreased 0.5 percent, the overall home flip rate comparing Q3 2016 to Q3 2017 has stagnated at 5.1 percent. Also, return on investment (ROI) is decreasing, which might be driving this declining rate.

As detailed in the report, only 37 percent of major metropolitan markets are experiencing an increase of average gross home flipping return on investment (ROI) in Q3. The rest of markets? They’re experiencing an ROI downturn, receiving lowest average gross flipping ROI since Q2 2015.

“Home flipping profits continue to be squeezed by a dwindling inventory of distressed properties available to purchase at a discount and increasing competition from fair-weather home flippers often willing to operate on thinner margins,” Blomquist said.

It looks like we shouldn’t count out the creation of “Flip this House: Baton Rouge” coming soon to a TV near you.

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Real Estate Big Data

The average first time home buyer struggles with debt and down payments

(REAL ESTATE NEWS) For years, the first time home buyer has been squeezed out of the market, but for those qualifying, what are the traits of today’s average first timer?

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first time home buyer young couple renting divorce

While the nation’s housing supply tightens and home prices continue to rise, first time home buyers are also struggling to save enough for a down payment while burdened with student loan debt.

As a result, only 34 percent of 2017 home buyers were first time homeowners, a minor decrease from 35 percent in 2016, according to the National Association of Realtors 2017 Profile of Home Buyers and Sellers. This figure continues to fall away from the long-term historical market average of 39 percent, per the NAR.

The typical first time home buyer? A 32-year-old with an average household income of $75,000 who carries some lingering student loan debt.

While millennials are in their prime home buying years, the NAR found debt and saving for a down payment are the most significant home buying hurdles. A quarter (25 percent) of new first time buyers said saving for a down payment was the most difficult task they faced during the process and more than half (55 percent) said student loan debt delayed their home purchase.

Among the surveyed home buying newbies, 41 percent indicated they have student loan debt, which is up from the 40 percent recorded in 2016. And, the average debt balance has increased even more in the past year, reaching an average of $29,000 compared to $26,000 in 2016. More than half of debt-carrying buyers owe at least $25,000, too.

The typical first time home? A single-family home in a suburban area with a median purchase price of $190,000. And, as saving for a down payment is difficult for many young buyers, the average first time home buyer down payment averaged 5 percent in 2017, the lowest percentage recorded by the NAR since 2013. The average down payment figure also indicates such buyers finance nearly 10 percent more (95 percent) of their home purchases than repeat buyers (86 percent).

In addition to personal finance burdens, first time buyers have struggled to find affordable options as the housing inventory in many parts of the U.S. tightens and prices increase for what is available. When buyers are on a budget and balancing debt, this can dampen the dreams of homeownership and prolong the time spent searching for their first home. Overall, the 2017 NAR survey found the average home buying search lasts 10 weeks.

Regardless of reality, many currently believe that it’s just too expensive to buy.

“With the lower end of the market seeing the worst of the supply crunch, house hunters faced mounting odds in finding their first home,” said NAR chief economist Lawrence Yun. “Multiple offers were a common occurrence, investors paying in cash had the upper hand, and prices kept climbing, which yanked homeownership out of reach for countless would-be buyers.”

The NAR annual Profile of Buyers and Sellers survey is survey data-based snapshot of home buyers who have purchased a home in the past 12 months, which, for the latest report, meant between July 2016 and June 2017.

While the new first time home buyer stats may not be the most promising, these findings can help real estate professionals better understand the current housing market and better assist home buyers – especially younger buyers who may benefit from more guidance.

first time home buyer

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Real Estate Big Data

Retailers are selling off their real estate to survive

(REAL ESTATE NEWS) It’s no secret that retailers have struggled, and those that intend on surviving are looking to their most valuable assets to get creative with.

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retailers

With brick-and-mortar sales plummeting and more and more customers shopping online, retailers nationwide are laying off employees, shutting down stores, and desperately trying to adapt to changing conditions.

Department stores in particular are hurting. Decades ago, when department stores were having a heyday and browsing a huge inventory was a novelty experience, many companies like Macy’s, Lord & Taylor, and Sears bought or built enormous stores in prime locations.

Now, these companies are having a hard time moving inventory – but they sure do have some lucrative real estate. Many are leasing out parts of their stores to smaller retailers or as office space to startups and tech companies. Some are creating partnerships to share their store space. And some are simply selling these properties all together. Is this a savvy strategy for generating capital? Or the desperation tactics for sinking ships?

The number of companies selling some of their most noteworthy stores certainly gives credibility to what people are calling the “retail apocalypse.” In the past few years, Macy’s, who laid off 10,000 employees this year, has sold stores in San Francisco, Portland, Los Angeles, and Minneapolis. Sears began selling real estate two years ago, and many J.C. Penney locations have also closed down.

Hudson’s Bay Company, which owns Lord & Taylor and Saks Fifth Avenue, recently announced that they would sell their Fifth Avenue building in Manhattan to tech startup WeWork for $850 million. Lord & Taylor will then lease one or two floors from WeWork, who will use the rest of the building for their offices. Hudson’s Bay Company is also looking to sell another department store in Vancouver.

According to Garrick Brown, director of retail research for real estate broker Cushman & Wakefield, “some department store companies have real estate holdings that are move valuable than the retail business itself.” He says that some department stores are “getting choked” because they can’t face the facts that their giant locations are unnecessary and costly.

So while some companies, like Sears, may have waited until it was too late to make a last-ditch effort at selling their real estate, others may be selling or leasing their store locations as the next step towards the innovations they’ll need to survive.

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