Written by Steven Hansen
The headlines for existing home sales say “December’s robust bounce back caps off the best year of existing sales (5.26 million) since 2006 (6.48 million)“. Our analysis of the unadjusted data shows that home sales did improve, but considerably less than the headlines – and consider even with this improvement that the rolling averages declined.
Econintersect Analysis:
- Unadjusted sales rate of growth accelerated 6.1 % month-over-month, up 6.1 % (no typo) year-over-year – sales growth rate trend declined using the 3 month moving average.
- Unadjusted price rate of growth accelerated 0.8 % month-over-month, up 4.7 % year-over-year – price growth rate trend is modestly improved using the 3 month moving average.
- The homes for sale inventory declined again this month, remains historically low for Decembers, and is down 3.8 % from inventory levels one year ago).
- Sales up 14.7 % month-over-month, up 7.7 % year-over-year.
- Prices up 7.6 % year-over-year
- The market expected annualized sales volumes of 5.000 to 5.450 million (consensus 5.20 million) vs the 5.46 million reported.
Unadjusted Year-over-Year Change in Existing Home Sales Volumes (blue line) – 3 Month Rolling Average (red line)
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The graph below presents unadjusted home sales volumes.
Unadjusted Monthly Home Sales Volumes
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Here are the headline words from the NAR analysts:
Lawrence Yun, NAR chief economist, says December’s robust bounce back caps off the best year of existing sales (5.26 million) since 2006 (6.48 million). “While the carryover of November’s delayed transactions into December contributed greatly to the sharp increase, the overall pace taken together indicates sales these last two months maintained the healthy level of activity seen in most of 2015. Additionally, the prospect of higher mortgage rates in coming months and warm November and December weather allowed more homes to close before the end of the year.”
“Although some growth is expected, the housing market will struggle in 2016 to replicate last year’s 7 percent increase in sales,” adds Yun. “In addition to insufficient supply levels, the overall pace of sales this year will be constricted by tepid economic expansion, rising mortgage rates and decreasing demand for buying in oil-producing metro areas.”
“First-time buyers were for the most part held back once again in 2015 by rising rents and home prices, competition from vacation and investment buyers and supply shortages,” says Yun. “While these headwinds show little signs of abating, the cumulative effect of strong job growth in recent years and young renters’ overwhelming interest to own a home5 should lead to a modest uptick in first-time buyer activity in 2016.”
“December’s rebound in sales is reason for cautious optimism that the work to prepare for Know Before You Owe is paying off,” says NAR President Tom Salomone. “However, our data is still showing longer closing timeframes, which is a reminder that the near-term challenges we anticipated are still prevalent. NAR advised members to extend the time horizon on their purchase contracts to address this concern, and we’ll continue to work with our industry partners to ensure 2016 is a success for consumers, homeowners and Realtors® alike.”
Comparison of Home Price Indices – Case-Shiller 3 Month Average (blue line, left axis), CoreLogic (green lin.
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To remove the seasonality in home prices, here is a year-over-year graph which demonstrates a general improvement in home price rate of growth since mid-2012.
Comparison of Home Price Indices on a Year-over-Year Basis – Case-Shiller 3 Month Average (blue bars), CoreLogic (yellow bars) and National Association of Realtors three month average (red bars)
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Econintersect will do a more complete analysis of home prices when the Case-Shiller data is released. The graphs above on prices use a three month rolling average of the NAR data, and show a 3.4 % year-over-year gain.
Homes today are still relatively affordable according to the NAR’s Housing Affordability Index.
Unadjusted Home Affordability Index
This affordability index measures the degree to which a typical family can afford the monthly mortgage payments on a typical home.
Value of 100 means that a family with the median income has exactly enough income to qualify for a mortgage on a median-priced home. An index above 100 signifies that family earning the median income has more than enough income to qualify for a mortgage loan on a median-priced home, assuming a 20 percent down payment. For example, a composite housing affordability index (COMPHAI) of 120.0 means a family earning the median family income has 120% of the income necessary to qualify for a conventional loan covering 80 percent of a median-priced existing single-family home. An increase in the COMPHAI then shows that this family is more able to afford the median priced home.
The home price situation according to the NAR:
The median existing-home price2 for all housing types in December was $224,100, up 7.6 percent from December 2014 ($208,200). Last month’s price increase marks the 46th consecutive month of year-over-year gains.
According to the NAR, all-cash sales accounted for 24 % of sales this month.
The percent share of first-time buyers was at 32 percent in December (matching the highest share since August), up from 30 percent in November and 29 percent a year ago. First-time buyers in all of 2015 represented an average of 30 percent, up from 29 percent in both 2014 and 2013. A separate NAR survey released in late 2015 revealed that the annual share of first-time buyers was at its lowest level in nearly three decades.
All-cash sales were 24 percent of transactions in December (27 percent in November) and are down from 26 percent a year ago. Individual investors, who account for many cash sales, purchased 15 percent of homes in December, down from both from 16 percent in November and 17 percent a year ago. Sixty-four percent of investors paid cash in December.
Unadjusted Inventories are below the levels of one year ago.
Total housing inventory at the end of December dropped 12.3 percent to 1.79 million existing homes available for sale, and is now 3.8 percent lower than a year ago (1.86 million). Unsold inventory is at a 3.9-month supply at the current sales pace, down from 5.1 months in November and the lowest since January 2005 (3.6 months).
Unadjusted Total Housing Inventory
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Caveats on Use of NAR Existing Home Sales Data
The National Association of Realtors (NAR) is a trade organization. Their analysis tends to understate the bad, and overstate the good. However, the raw (and unadjusted) data is released which allows a complete unbiased analysis. Econintersect analyzes only using the raw data. Also note the National Association of Realtors (NAR) new methodology now has moderate back revision to the data – so it is best to look at trends, and not get too excited about each month’s release.
The NAR re-benchmarked their data in their November 2011 existing home sales data release reducing their recent reported home sales volumes by an average of 15%. The NAR stated benchmarking will be an annual process, and the 2010 data will need to be benchmarked again next year.
Also released today were periodic benchmark revisions with downward adjustments to sales and inventory data since 2007, led by a decline in for-sale-by-owners. Although rebenchmarking resulted in lower adjustments to several years of home sales data, the month-to-month characterization of market conditions did not change. There are no changes to home prices or month’s supply.
Existing home sales is one area the government does not report data – and it is easy to assume that an organization whose purpose is to paint the housing industry in a good light would inflate their data. However, Econintersect is assuming in its analysis that the NAR numbers are correct.
The NAR’s home price data has been questioned by others also. However, Econintersectanalysis shows a very good home price correlation to Case-Shiller, CoreLogic’s HPI, and LPS, especially when three-month moving averages are used – as shown in the graph earlier in this article.
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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