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June 2015 Pending Home Sales Index Headlines Say the Index Declined. Our View is Better.

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9월 6, 2021
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Written by Steven Hansen

The National Association of Realtors (NAR) seasonally adjusted pending home sales index declined. Our analysis of pending home sales is more rosey – and projects relatively good home sales. The quote of the day from this NAR release:

The demand is there for more sales, but the determining factor will be whether or not some of these buyers decide to hold off even longer until supply improves and price growth slows.

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 down 1.8% month-over-month and up 8.2% year-over-year (last month 10.4% year-over-year).
  • The market was expecting month-over-month growth of 0.4 % to 2.5 % (consensus 1.0%) versus the growth of -1.8 % reported.

Econintersect‘s evaluation using unadjusted data:

  • the index growth was up 3.1% month-over-month and up 11.1% year-over-year.
  • The current trends (using 3 month rolling averages) declined but remains in expansion.
  • Extrapolating the pending home sales unadjusted data to project July 2015 existing home sales, this would be a 7.7 % gain year-over-year for existing home sales.

Unadjusted 3 Month Rolling Average of Year-over-Year Growth for Pending Home Sales (blue line) and Existing Home Sales (red line)

z pending2.png

From Lawrence Yun , NAR chief economist:

…. although pending sales decreased in June, the overall trend in recent months supports a solid pace of home sales this summer. Competition for existing houses on the market remained stiff last month, as low inventories in many markets reduced choices and pushed prices above some buyers’ comfort level. The demand is there for more sales, but the determining factor will be whether or not some of these buyers decide to hold off even longer until supply improves and price growth slows.

… existing-home sales are up considerably compared to a year ago despite the share of first-time buyers only modestly improving. The reason is that the boost in sales is mostly coming from pent-up sellers realizing their equity gains from recent years.

Strong price appreciation and an improving economy is finally giving some homeowners the incentive and financial capability to sell and trade up or down. Unfortunately, because nearly all of these sellers are likely buying another home, there isn’t a net increase in inventory. A combination of homebuilders ramping up construction and even more homeowners listing their properties on the market is needed to tame price growth and give all buyers more options.

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 530,000 in July 2015.

Using Pending Home Sales to Predict Existing Homes Sales – Unadjusted Existing Home Sales (blue line) & Predictive Forecast Using Pending Home Sales Index (red line)

z pending1.PNG

Using this methodology, 525,000 existing home unadjusted sales were forecast for June 2015 versus the actual reported number of 573,000 (which is subject to further revision).

Unadjusted Year-over-Year Change in Existing Home Sales Volumes (blue line), 3 month rolling average (red line)

z existing1.PNG

Since November 2013 home sales showed a contraction year-over-year for the first time since 2011 – and October 2014 was the first month of expansion.

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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