Written by Steven Hansen
The National Association of Realtors (NAR) seasonally adjusted pending home sales index declined. The quote of the day from this NAR release:
… Already faced with climbing home prices and minimal listings in the affordable price range, fewer home shoppers in most of the country were successfully able to sign a contract. …
Analyst Opinion of Pending Home Sales
The unadjusted data shows the rate of year-over-year growth improved this month – but the rolling averages declined so I would more or less agree with he headline view. One should expect a significant decline in home sales in December as many home sales were expedited to close in November to beat the interest rate rise.
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 2.5 % month-over-month and down 0.4 % year-over-year.
- The market was expecting month-over-month growth of 0.3 % to 2.0 % (consensus +0.5 %) versus the contraction of 2.5 % reported.
Econintersect‘s evaluation using unadjusted data:
- the index growth rate was accelerated 1.2 % month-over-month and up 1.4 % year-over-year.
- The current trends (using 3 month rolling averages) are slightly decelerating..
- Extrapolating the pending home sales unadjusted data to project December 2016 existing home sales would be a 3.5 % contraction 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)

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From Lawrence Yun , NAR chief economist:
…. ongoing supply shortages and the surge in mortgage rates took a small bite out of pending sales in November. The budget of many prospective buyers last month was dealt an abrupt hit by the quick ascension of rates immediately after the election. Already faced with climbing home prices and minimal listings in the affordable price range, fewer home shoppers in most of the country were successfully able to sign a contract. ….
Healthy local job markets amidst tight supply means many areas will remain competitive with prices on the rise. Those rushing to lock in a rate before they advance even higher will probably have few listings to choose from,” said Yun. “Some buyers will have to expand the area of their home search or be forced to delay in order to save a little more money for their down payment.
Much more robust new home construction is needed to relieve inventory shortages and lessen the affordability pressures present throughout the country.
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 420,000 in November 2016.
Using Pending Home Sales to Predict Existing Homes Sales – Unadjusted Existing Home Sales (blue line) & Predictive Forecast Using Pending Home Sales Index (red line)
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Using this methodology, 360,000 existing home unadjusted sales were forecast for November 2016 versus the actual reported number of 415,000 (which is subject to further revision). [this discrepancy was likely the result of buyers pushing through home sales prior to the interest rate changes]
Unadjusted Year-over-Year Change in Existing Home Sales Volumes (blue line), 3 month rolling average (red line)
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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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