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Real Estate Research provided analysis of topical research and current issues in the fields of housing and real estate economics. Authors for the blog included the Atlanta Fed's Jessica Dill, Kristopher Gerardi, Carl Hudson, and analysts, as well as the Boston Fed's Christopher Foote and Paul Willen.
In December 2020, content from Real Estate Research became part of Policy Hub. Future articles will be released in Policy Hub: Macroblog.
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November 18, 2014
Can the Atlanta Fed Construction and Real Estate Survey Predict Home Sales?
The slow recovery in housing remains an item of note in statements from the Financial Open Market Committee. That it's still something of a concern means that many people pay attention to housing-related data releases, several of which are due out this week, because they can shed some light on the direction of housing and the economy. The builder confidence index, released today, got things off to a good start by showing a four-point rise, from 54 to 58 (values greater than 50 mean that more builders view conditions as good rather than as poor). House starts and existing sales are due Wednesday and Thursday, respectively.
At the Atlanta Fed, we conduct a monthly survey of regional builders and real estate brokers to get their perspectives of the market. In August, we began to look at the results a little differently to see if they could tell us anything about subsequent housing-market data releases. In that exercise, we investigated the correlation between the expectations of our homebuilder contacts for construction activity and subsequent housing starts. We found that our builders are on point, more or less, and we reported on that discovery in an August post. We recently repeated the exercise, this time to explore the predictive power of the outlook for home sales of our homebuilders and residential brokers for subsequent new and existing home sales data releases. We report on our findings in this post.
Brokers and builders expect new home sales to rise
The September home sales data showed us that existing single-family home sales increased by 1.9 percent from the year-earlier level and new home sales increased by 22.6 percent. This news is fairly consistent with the reports we received from our real estate business contacts about September sales activity; more brokers and builders noted an increase than noted a decrease in home sales activity from the year-ago level.
But what exactly did our survey respondents tell us about their outlook for home sales? Diving deeper into the data, we find that brokers' and builders' outlooks remain mildly positive and that the two groups have tracked each other fairly closely in recent years. (In the pre-2011 period, brokers and builders diverged more sharply.) Specifically:
- Of builder respondents, 40.0 percent indicated that they expect new home sales to increase over the next three months, 32.0 percent expect activity to decline, and 28.0 percent expect home sales activity to remain about the same. The home sales outlook diffusion index value for builders was 0.08.
- Of broker respondents, 22.5 percent indicated that they expect new home sales to increase over the next three months, 27.5 percent expect activity to decline, and 50.0 percent expect home sales activity to remain about the same. The home sales outlook diffusion index value for brokers was -0.05.
The chart below features two scatter plots of the diffusion index value for the broker and builder home sales outlook on the horizontal axis and the year-over-year change in the three-month moving average of single-family home sales (for Alabama, Florida, Georgia, Louisiana, Mississippi, and Tennessee) on the vertical axis. Given that we are asking contacts to be forward-looking, we lag the contact responses.
Do home sales expectations correlate with subsequent sales data?
Three things stand out on this chart. First, if builders and especially brokers (who tend to be an optimistic lot) predict a decline, the subsequent home sales data release will probably be poor. Only a modest bit of net optimism is of little comfort—some of the worst declines occurred in years with net positive (albeit small net positive) outlooks.
Second, for builders, if the index is greater than 0.3, we find that sales generally grow—except for between August 2012 and April 2013, when sales did not match builders' optimism. When the broker index is above 0.3, sales either grow or decline by a smaller amount than when the index is negative. Like the builders, the broker panel missed the sales declines from August 2012 and April 2013. The brokers also missed the declining real estate market in 2006 to early 2007 (see the green triangles in the chart above)—despite a declining market, the broker index remained lofty until May 2007.
Third, the official statistics on housing sales could go either way when index values are between ‑0.1 and 0.3. This shouldn't come as a complete surprise, particularly because a diffusion index value near zero (regardless of whether that value is positive or negative) indicates that responses from contacts were mixed. And as we can see in the scatter plot above, large declines were much more likely given the time period covered.
A simple regression indicates that the outlook could explain just under 50 percent of the variation in sales measure, which indicates that our poll does a decent job of predicting subsequent sales. Given this finding, what do we now expect home sales to look like? The most recent downward trend in respondents' outlook puts the diffusion index in the center, suggesting that declines in seasonally adjusted sales over the next several months are just as likely as increases in sales.
The poll was conducted October 6–15, 2014. Sixty-five business contacts across the Southeast participated (40 residential brokers and 25 builders). To explore the latest poll results in more detail, please visit our Construction and Real Estate Survey page.
By Carl Hudson, director for the Center for Real Estate Analytics in the Atlanta Fed´s research department, and
Jessica Dill, senior economic research analyst in the Atlanta Fed's research department
December 4, 2013
Part 2: What Caused Atlanta's House Prices to Drop Again in 2011?
Note: This post is a follow-up to the November 8 post, "What Caused Atlanta's House Prices to Drop Again in 2011?"
Case-Shiller recently released its September data. Once again, the data show that Atlanta's year-over-year performance outpaced Case-Shiller's 20 metro area index—18.7 percent versus 13.3 percent, and Atlanta's low tier experienced its fifth consecutive month of year-over-year returns in excess of 50 percent (53.2 percent).
In the November 8 post, which explored the Case-Shiller house price tiers, we noted that from July 2011 to March 2012, both Atlanta thresholds—the low–middle and the middle-high—had noticeable declines, which corresponded to the time when the low tier's year-over-year performance began to recover. Given the methodology, we said that either all prices declined or a greater proportion of transactions came from lower-valued houses. Data on mortgage closings provide evidence consistent with the idea that investor activity in Atlanta's low tier influenced the market.
We can distinguish investor activity from "typical" house purchases by looking at the form of financing. Most owner-occupiers use mortgage financing whereas investors usually purchase with cash. Thus, if there is substantial investor activity in one of the three tiers, then we would expect that tier to be underrepresented in the number of mortgage closings.
To dig further into the issue of the 2011 house price drop, we looked at the distribution of mortgage closings by tier in the Lender Processing Services (LPS) Applied Analytics database. Residential mortgage servicing data from that database contain records from the servicing portfolios of the largest residential mortgage servicers in the United States. It covers about two-thirds of installment-type loans in the residential mortgage servicing market.
The chart displays the fraction of mortgage closings by Case-Shiller by tier from third-quarter 2008 to third-quarter 2013. We created the data for the chart by using each mortgage's sales price and assigning it to a tier as defined by the Case-Shiller thresholds for the month the mortgage closed (we excluded refinances). Once we'd bucketed the data this way, we calculated each bucket's percentage of the month's closing. If cash purchases were evenly distributed and the set of servicers in the LPS database is representative of Atlanta's overall market, we would expect each bucket to be one-third of the total.
From September 2008 to October 2011, the closings appear to be evenly distributed among the three buckets, with the shares varying between 25 and 43 percent. The average share for the low, middle, and upper tiers were 36 percent, 30 percent, and 34 percent, respectively. After November 2011, the low tier's share fell to an average of 18 percent, with a low share of 12.8 percent in May 2012.
Although the chart does not conclusively prove that investors entered the market en masse to purchase houses in Atlanta's low tier, the timing of the noticeable decline in the low tier's share of mortgage closings does coincide with the fall in Atlanta's low–middle and middle–high thresholds and the bottoming of the low tier's year-over-year price declines. More recently, the low tier's share of mortgage closings has been at its highest since November 2011—perhaps a sign that investor interest has cooled and we are now looking at a more normal market.
But with year-over-year prices in the low tier rising rapidly, let's hope buyers aren't expecting 50 percent year-over-year gains to be normal.
Carl Hudson, Director, Center for Real Estate Analytics in the Atlanta Fed's research department
November 8, 2013
What Caused Atlanta's House Prices to Drop Again in 2011?
What happened in Atlanta real estate the second half of 2011 and the first half of 2012? I asked myself this question after looking at the recent release of the Case-Shiller Home Price Indices for August. Atlanta home prices have recently been increasing at a faster rate than the composite index. Last month, the United States saw a 12.8 percent year-over-year increase in house prices while the Atlanta index rose 18.4 percent.
It wasn't long ago that things were much worse in Atlanta. From the pre-bust peak, the city experienced a 37 percent decrease in its Case-Shiller index versus a 33.8 percent decrease for the Case-Shiller 20-metro composite. From July 2011 to March 2012, Atlanta home prices took a second nosedive, almost as large as the initial bust in 2009 (see Chart 1). So what happened?
The Case-Shiller index is a repeated sales index, which means it uses the price change between two arms-length sales of the same single-family home. One way to gauge the amount of activity in a market is to look at the number of "sales pairs" in a period. To get a sense for whether Atlanta is experiencing particularly high volumes, we can look at Atlanta's sales volume relative to the nation's. In the third quarter of 2011, Atlanta's sales began to grow substantially, and Atlanta's share of composite sales pairs peaked in March 2012 at 9.7 percent, which is a much greater percentage than the 5 percent to 6 percent range from 2000 to 2005.
Around this time, many of the Atlanta Fed's local contacts reported that some investors were buying up distressed home to convert into rental property. Case-Shiller breaks its index into three price tiers—low, middle, and high. Looking at the tiers in Atlanta for the most recent data, the high end was up 12.9 percent year over year; the middle tier, 27.7 percent; and the low tier was up 52.5 percent. Looking back, we see that the growth rate in Atlanta's low-tier index started to recover in July 2011 (see Chart 2). It was not until March 2012 when the year-over-year changes in the middle and high tiers started their recent upward trends.
The price thresholds for the three tiers are computed using all sales for each period and are set so that each tier has the same number of sales. From July 2011 to March 2012, both thresholds (low–middle and middle–high) had noticeable declines (see Chart 3). Given the methodology, either all prices declined or a greater proportion of transactions came from lower-valued houses. Note that after March 2012, the breakpoints started to increase, which was the same time as when the year-over-year growth in the middle and high tiers started to improve.
Further work is needed in order to determine whether there really was a ramp-up in activity in the low end of the market. If such activity did occur, it raises the question as to what was driving the activity—could it have been investors? If not, how was this activity financed? Was this a case of inventory being absorbed, prices adjusting, and momentum moving from investors to "normal" buyers?
The low tier warrants attention given the fact that it may have driven Atlanta's recent house price performance. Understanding the July 2011 to March 2012 period may shed light on the factors that could influence the market going forward.
Carl Hudson, Director, Center for Real Estate Analytics in the Atlanta Fed's research department
July 24, 2013
The Shape of the Housing Recovery in Atlanta
As with politics, all real estate is local, and it seems that it is always someone else's neighborhood that's doing well. By all indications, housing is recovering in 2013. Nationally, starts and prices show promising growth. Even in Atlanta, Georgia—a hotbed of subprime lending and speculative construction before the crash—home prices have made a strong rebound, showing a 21 percent year-over-year increase in April 2013 (see the chart). In this post, we address the questions: What shape is this recovery taking? Will this rebound look a lot like the early 2000s? Or can we expect permanent changes to the urban landscape post-crisis?
Using zip code-level data from CoreLogic to take a closer look at home price recovery in Atlanta, we see that this rebound is not evenly distributed. Instead, variation in growth rates is much higher than it used to be. In general, Atlanta home prices have been very depressed, but at the same time, contacts have remarked that in hot, single-family markets, prices are up, multiple offers are made as soon as a property is listed, and there is a general shortage of homes "where people want to move." The data confirms and adds to this anecdotal evidence: Atlanta's strong price growth is concentrated in select intown markets, as well as in many of the areas hardest hit.
Prior to the crisis, home prices appreciated at about the same rate throughout the Atlanta metropolitan region. Yes, some areas were expensive and others affordable, but prices grew everywhere at roughly the same pace. But when the real estate market crashed in 2007, Atlanta home price rates of change began to diverge. In the past, zip codes with the highest growth rates grew 20 percent faster than zip codes with the lowest rates. Now, that ratio has risen to 300 percent.
To illustrate, the standard deviation in home price growth increased sharply during the crisis and continued to widen during the last year of recovery (see table 1). This pattern also describes the nationwide trend, although the increases in variation in Atlanta are more dramatic.
The obvious explanation for this is that during the crash, although prices fell everywhere, areas with concentrations of distressed properties fell more steeply, generating this variation. Now that the recovery is under way, though, will areas with a high density of distressed properties rebound? Or are these areas reset permanently at a lower level?
The evidence from Atlanta suggests that we will see a bit of both. Fast growth is concentrated in some of the areas that were hardest hit, as well as in some of the choicest neighborhoods in town. This extremely fast growth is paired with slow growth in many markets that never saw steep declines, generating a higher standard deviation in home prices.
The first map below shows year-over-year home price change during the recovery. The second map depicts peak and trough change, showing the depth of the decline. We see that two recovery stories emerge. First, north of I-20, areas that were quite resilient during the crisis and did not see strong declines are experiencing strong growth. Second, in the areas southeast of the interstate 285 perimeter, we see exurbs that were devastated by devaluation experiencing a strong rebound, with growth rates over 16 percent.
How can we best understand this pattern of recovery? We reviewed a few likely correlates with home price increase: household income, household size, and density of high-risk lending and speculative construction during the bubble. None of these factors was significantly correlated with the 2013 rebound. The peak-to-trough change is significantly correlated with the rate of recovery, suggesting that much of this recovery is a price correction. Longer commute times are also correlated with recovery, revealing that demand is increasing in places that are not close to job centers, though it's possible that commute times are simply a proxy for severity of the crash as these areas also experienced the strongest declines.
Contacts tell us that neighborhoods with better school districts are performing well and recent investor interest may also be playing a role. What is certain is that Atlanta's strong overall house price growth is driven by increases in areas hardest hit by the housing downturn and by a few centrally located markets, and that underneath the citywide average there is a lot more variation than we have experienced in the past.
We'd love to hear your thoughts about these trends!
By Elora Raymond, graduate research assistant, Center for Real Estate Analytics in the Atlanta Fed's research department/PhD student, School of City and Regional Planning, Georgia Institute of Technology, and
Carl Hudson, Director, Center for Real Estate Analytics in the Atlanta Fed's research department
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