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posted on 29 March 2017

February 2017 Pending Home Sales Index Improves?

Written by Steven Hansen

The National Association of Realtors (NAR) seasonally adjusted pending home sales index rebounded to the second highest level in a decade. Our analysis says the opposite but the rolling averages improved. The quote of the day from this NAR release:

... Looking ahead to the busy spring months, Yun expects to see continued ebbs and flows in activity as new supply struggles to replace listings that are going under contract at a very quick pace. ...

Analyst Opinion of Pending Home Sales

The unadjusted data shows the rate of year-over-year growth declined this month - but the more important rolling averages insignificantly improved. Because there is so much noise in the monthly numbers - the rolling averages are the best way to view the data.

I continue to see few signs that the residential sales market is improving. - except the words which come from the NAR.

Pending home sales are based on contract signings, and existing home sales are based on the execution of the contract (contract closing).

The NAR reported:

  • Pending home sales index was up 5.5 % month-over-month and up 2.6 % year-over-year.
  • The market [from Bloomberg / Econoday} was expecting month-over-month growth of 1.4 % to 3.0 % (consensus +1.8 %) versus the +5.5 % reported.

Econintersect's evaluation using unadjusted data:

  • the index growth rate decelerated 5.1 % month-over-month and down 2.4 % year-over-year.
  • The current trends (using 3 month rolling averages) are decelerating..
  • Extrapolating the pending home sales unadjusted data to project March 2017 existing home sales would be a 1.4 % contraction year-over-year for existing home sales.

From Lawrence Yun , NAR chief economist:

.... February's convincing bump in pending sales is proof that demand is rising with spring on the doorstep. Buyers came back in force last month as a modest, seasonal uptick in listings were enough to fuel an increase in contract signings throughout the country," he said. "The stock market's continued rise and steady hiring in most markets is spurring significant interest in buying, as well as the expectation from some households that delaying their home search may mean paying higher interest rates later this year.

Last month being the warmest February in decades also played a role in kick-starting prospective buyers' house hunt.

Looking ahead to the busy spring months, Yun expects to see continued ebbs and flows in activity as new supply struggles to replace listings that are going under contract at a very quick pace. This is especially the case at the lower- and mid-market price ranges, where choices are minimal and prices are being bid higher by multiple offers.

The homes most buyers are in the market for are unfortunately the most difficult to find and ultimately buy. The country's healthy labor market is translating to greater job security, but affordability is not improving because home prices in some areas are still outpacing incomes by three times or more because of tight supply. How much new and existing inventory there is on the market this spring will determine if sales can reach their full potential and finally start reversing the nation's low homeownership rate.

The National Association of Realtors (NAR) pending home sales index offers a window into predicting existing home sales. The actual home sale might appear in the month the contract was signed (cash buyers can close quickly), or in the following two months.

Econintersect forecasts unadjusted existing home sales by offsetting the pending home sales index one month. This forecast suggests unadjusted existing home sales of 415,000 in March 2017.

Using this methodology, 310,000 existing home unadjusted sales were forecast for February 2017 versus the actual reported number of 315,000 (which is subject to further revision).

Keeping things real - home sales volumes are only 2/3rds of previous levels.

Caveats on the Use of Pending Home Sales Index

According to the NAR:

NAR's Pending Home Sales Index (PHSI) is released during the first week of each month. It is designed to be a leading indicator of housing activity.

The index measures housing contract activity. It is based on signed real estate contracts for existing single-family homes, condos and co-ops. A signed contract is not counted as a sale until the transaction closes. Modeling for the PHSI looks at the monthly relationship between existing-home sale contracts and transaction closings over the last four years.

…… When a seller accepts a sales contract on a property, it is recorded into a Multiple Listing Service (MLS) as a "pending home sale." The majority of pending home sales become home sale transactions, typically one to two months later.

NAR now collects pending home sales data from MLSs and large brokers. Altogether, we receive data from over 100 MLSs & 60 large brokers, giving us a large sample size covering 50% of the EHS sample. This is equal to 20 percent of all transactions.

In other words, Pending Home Sales is an extrapolation of a sample equal to 20% of the whole. Econintersect uses Pending Home Index to forecast future existing home sales.

Econintersect reset the forecasting of existing home sales using the pending home sales index coincident with November 2011 Pending home sales analysis (see here) - as the NAR in November revised the historical existing home sales data.

The Econintersect forecasting methodology is influenced by the speed at which closings occur. When they slow down in a particular period - this method overestimates. The number of cash buyers are speeding up the process (cash buyers analysis here). A quick cash home sale process could begin and end in the same month. On the other hand, contracts for short sales can sometimes take months to close. Interpreting the pending home sales data is complicated by weighing offsetting effects in the current abnormal market.

Please note that Econintersect uses unadjusted data in its analysis.

Econintersect determines the month-over-month change by subtracting the current month's year-over-year change from the previous month's year-over-year change. This is the best of the bad options available to determine month-over-month trends - as the preferred methodology would be to use multi-year data (but the New Normal effects and the Great Recession distort historical data).



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