Real Estate Research provides analysis of topical research and current issues in the fields of housing and real estate economics. Authors for the blog include the Atlanta Fed's Kristopher Gerardi, Carl Hudson, and analysts, as well as the Boston Fed's Christopher Foote and Paul Willen.
May 16, 2014
Are Single-Family Rental Securitizations Here to Stay?
In the fall of 2013, private equity firm Blackstone LP issued the first single-family rental (SFR) securitization: Invitation Homes 2013-SFR 1. In March, Colony Capital released another SFR securitization. The Invitation Homes 2013-SFR 1 was backed by 3,207 single-family rental homes concentrated in Arizona, California, Florida, Georgia, and Illinois. Deutsche Bank arranged the deal. There are a variety of estimates of the size of institutional investors’ activity in the SFR market, but with numbers like 90,000 to 150,000 homes and 15 to 20 billion dollars invested, most agree that we can expect more securitizations like these in the future. So what exactly is this new asset class, and how did it obtain its strong credit rating?
In this post, we look at how the structure of the Invitation Homes SFR emerged and compare it to more familiar commercial mortgage-backed security (CMBS) and residential mortgage-backed security (RMBS) classes to better understand the triple-A rating. We also consider some factors that could determine whether the SFR security class will stick around.
(For a nice discussion about the entry of institution investors into the rental market, read this second-quarter 2013 EconSouth article.)
Please note that much of the information that follows is based on reports from the rating agencies:
- Kroll Bond Rating Agency. "Kroll Bond Rating Agency Assigns Final Ratings to Invitation Homes 2013-SFR1". (November 11, 2013.)
- Kroll Bond Rating Agency. 17g-7 Disclosure (Invitation Homes 2013 SFR1).
- Moody’s Investor Services. “Moody's sees growth for single family rental securitizations; outlines rating approach.” (March 6, 2014.)
- Moody's Investor Services: “Moody's identifies key risk factors in securitizations of single-family rental properties.” (August 23, 2012.)
Commercial or residential—or both?
This product took a long time to come to market. For nearly two years, the industry discussed how to structure this new security class. Discussions in 2012 and 2013 about the rating and pricing of an SFR security focused on three gray areas. The first was housing market risk. Would housing markets, and the underlying value of investor-owned homes, appreciate on a market-wide basis?
The second was property management risk. Could scattered-site, single-family homes be managed cost-effectively? And with a lack of historical data for scattered-site, single-family rentals, how could credit rating agencies predict vacancy rates, maintenance costs, and income streams with any precision?
Finally, there was confusion about how to structure an SFR securitization and what tensions and risks would exist in that structure. There was also some uncertainty about whether an SFR securitization would be more like CMBS or RMBS. Like RMBSs, the underlying assets of SFRs are single-family homes. And many risks—for example, home price depreciation and household income—are the same as in the homeownership market (Joseph Hu 2011). But like CMBSs, the borrower is a corporation, not a homeowner, and the cash flow comes from rental, not mortgage, payments. That means the payments come from highly variable net operating income, which is sensitive to vacancy rates, market rents, and maintenance costs unlike the fixed-income streams of mortgages, which are sensitive to repayment and default risk but otherwise fairly predictable. Also like CMBSs, the sponsor of the SFR deal would be responsible for maintenance, meaning they might have to keep some cash on hand.
Equity pledges or first-priority mortgages?
These issues influenced the structure of the security. High maintenance costs associated with the rental properties created a nontrivial conflict. Ideally, in a security, assets are owned by a tax-neutral, special-purpose vehicle (SPV), with assets and liabilities perfectly matched. However, retaining cash flows for maintenance jeopardizes that tax-neutral status. Early discussions favored a structure in which the borrower, not the SPV, would retain ownership of the properties and instead of mortgages, equity pledges would collateralize the securitization. While these equity pledges might be preferable for maintaining properties and would be less transaction-intensive than issuing individual mortgages, equity pledges would create a weaker claim than first-priority mortgages for investors in the event of default. Further, equity pledges were not deemed to be as bankruptcy-remote as mortgages. All this meant equity pledges could be vulnerable to material consolidation in the event the sponsor were to become bankrupt or if the sponsor were to mismanage the properties, either selling them or borrowing further and creating competing liens on the properties (Matthew Clark 2013). For this reason, Moody’s and Kroll stated that they would cap securitizations using equity pledges at Baa or A.
Ultimately, the Invitation Homes/Blackstone SFR security used first-priority mortgages, not equity pledges, and secured a triple-A rating. In structure, the security is probably more like CMBS than RMBS. Deutsche Bank compared the instrument to CMBS, and the ratings agencies also leaned this way—Kroll and Moody’s compared the security to CMBS on the forms where they express their expectations for representations and warranties. Aspects of the transaction itself suggest that it is more like a CMBS deal than an RMBS one. For instance, the special servicer, Situs Holdings LLC, specializes in CMBS (not RMBS) workouts. Still, the security remains a hybrid. Kroll used a CMBS model to determine the probability of default and an RMBS model to determine severity, working on the assumption that the income-based approach typically used in valuating CMBSs would not be appropriate for pricing the sales of single-family homes in a distressed housing market. Similarly, Morningstar used both Cap Ex and HPI stress tests to generate ratings of the various tranches, feeling that both an income/expense approach and a sales approach to valuation were appropriate.
The structure of the securitization reflects a priority for enhancing an investor’s ability to take ownership and sell the homes in the event of a default, rather than other structures which might have prioritized management of homes to enhance rental income. Moody’s did not base its rating on an evaluation of the income streams from the properties, because the agency did not feel it had the ability to evaluate with certainty vacancy rates, maintenance costs, and other key factors. Instead, it based its rating on the strength of investor claims on the homes in the event of default, and estimated sales prices of the underlying properties assuming a distressed housing market. Another factor in the triple-A credit rating is that the security is overcollateralized. That is, the value of the collateral ($638M) is well above the value of the loans ($479M)—Invitation Homes took a 25 percent advance rate on these homes.
Will they last?
Some negative commentary has surfaced in the five months since the Invitation Homes offering. And S&P has come out strongly against the triple-A rating, arguing that without historical performance data there is too much uncertainty about income streams. Recent appraisals noted that several tranches were trading below par, and that rents had declined 7.6 percent due to increasing vacancy rates. Firms that had hoped to make margin by “pushing rent” or increasing rents every year are now talking about keeping rents stable in order to minimize turnover and the associated vacancy rates. So with all of these issues, how much staying power does the SFR securitization structure really have? To the extent that these transactions are driven primarily by the value of the underlying collateral and not by rental income, they begin to resemble trades that will decline as home prices approach normal levels. Indeed, many SFR investors and managers say they ultimately intend to sell single-family rentals back into the owner-occupied market either 1) when maintenance costs begin to outweigh the potential of the asset’s income stream or 2) it appears that, in the medium term, home prices and mortgage markets have recovered—and thus the opportunity for this market to exist disappears.
Other commentators suggests otherwise: this asset class will grow, possibly driven by fundamental demographic shifts such as increasing labor mobility and shifting preferences for rentals. These attributes, combined with stagnant wages and tight mortgage markets, suggest increased demand for single-family rentals. They may also suggest that SFR securitization represents a new normal.
By Elora Raymond, graduate research assistant, Center for Real Estate Analytics in the Atlanta Fed's research department, and doctoral student, School of City and Regional Planning at Georgia Institute of Technology
March 27, 2014
Limiting Property Tax Assessments to Slow Gentrification
A recent New York Times article on gentrification discussed a number of cities—including Boston, Philadelphia, and Washington, D.C.—that are planning to freeze property tax assessments for long-time homeowners in gentrifying neighborhoods. The concern is that rising house prices will also raise property assessments, forcing low-income residents to move to escape the greater tax burden and thereby accelerating the pace of gentrification. Although the desire to protect existing residents from gentrification appears to be new, laws capping assessment growth for all property or all primary homes ("homesteads") have been around since Californians passed Proposition 13 in 1978. After California, a number of additional states passed laws limiting how quickly an individual property's assessed value could increase. The bulk of these laws passed in the early eighties to the mid-nineties, and advocates for the law were concerned, at least in part, with limiting the size of local government. If this tax backlash of the previous decades is uncorrelated with more recent gentrification pressures, this may be a good test of statewide assessments caps.
Using a data set of low-income central-city neighborhoods that Dan Hartley of the Cleveland Fed assembled from the 2000 census and the 2007 American Community Survey, we can look at the share of neighborhoods that gentrified in capped and uncapped states. Hartley shows that a central city moving from below-median-MSA house price to above-median house price is a good indicator of gentrification. Relying on the table of statewide assessment caps that Haveman and Sexton compiled, we identify 10 states and the District of Columbia (plus the city of New York) with the strictest limits. In these states, assessed value can increase only at the rate of inflation or by a fixed percentage ranging from 2 percent (California) to 10 percent (Texas). Table 1 presents the share of neighborhoods that gentrified in capped and uncapped states.
Note that neighborhoods protected by assessment caps actually gentrified faster than those in states without them.
However, we might worry that the decision to impose statewide assessment caps was not random. In the case of Prop 13, rising home prices was certainly a factor in rising property taxes. It is possible that some underlying factor may drive statewide price up but also cause poor inner-city neighborhoods to appreciate faster than other homes in the metro area. One candidate is restrictive zoning laws that limit densification of already desirable neighborhoods. Such laws could both drive up aggregate house prices and push homebuyers into more marginal neighborhoods, causing them to appreciate relatively faster. However, assessment caps are only one possible response to rising property taxes. If voters wish to limit the growth in property taxes, they don't need capped assessments—they can restrict the growth in property tax revenues directly. At the same time, assessment caps that don't also cap the property tax rate don't actually constrain property taxes, but instead shift the tax burden from longtime owners to new buyers. In Table 2, we limit the sample to states that have a binding revenue growth cap or that jointly cap assessments and municipal tax rates. In this case, we assume that, conditional on imposing a tax expenditure limit, the decision to cap assessments rather than property tax revenue is random. We rely on the work by Hoyt, Coomes, and Biehl (2011) to identify various statewide tax expenditure limits.
Limiting the sample to states that have chosen to constrain the property tax in some way, we still observe assessment caps seeming to accelerate gentrification rather than slow it. How can that be? One possibility is that because these are state-wide limits, the caps have reduced the turnover in more desirable neighborhoods, driving new homebuyers to marginal central-city neighborhoods. In that case, targeted assessment caps that apply only to currently low-priced neighborhoods could still be efficacious. On the other hand, the existence of an assessment cap may increase the long-run return from "pioneering" in a low-priced neighborhood.
So far, we have been using change in relative house prices as our definition of gentrification. However, advocates for assessment caps are plainly concerned about the ability of homeowners to stay in their home in the face of rising home values. While the in-migration of higher-income residents and house prices are highly correlated, we do not observe the duration of time that existing residents remain in their home. Unfortunately, there are few individual-level data sets with sufficiently granular geography to allow such an analysis. As an alternative, we can look at the change in median income of residents. This value is available at the census-tract level in the 2000 census and the 2007 American Community Survey. Table 3 presents change in median income for all census tracts and for gentrifying tracts with and without assessment caps. While median incomes rose in gentrifying neighborhoods (even as they declined nationally), they rose faster in tracts subject to an assessment cap. However, this difference is not statistically different from zero (p value 0.303).
Finally, assessment caps do nothing for renters, who may be impacted much more immediately by rising neighborhood quality than homeowners. It is possible that assessment caps could still allow a small share of long-time owners to stay, and the observed effects are just dominated by the movement of renters. If we had access to administrative data with finer geographic identifiers, we could look at whether neighborhoods that gentrified with assessment caps now exhibit more income or racial heterogeneity than neighborhoods without. However, looking only at aggregate data, property taxes do not appear to be a primary driver of neighborhood change, and concerns about gentrification do not appear to warrant interfering with the assessment process.
Chris Cunningham, research economist and assistant policy adviser at the Federal Reserve Bank of Atlanta
December 23, 2013
Exploring Immigrant Contributions to Housing Demand
Since we relaunched the Real Estate Research blog earlier this year, I've contributed two posts exploring various aspects of housing demand. The first post considered what type of housing demand (renter-occupied versus owner-occupied) we should be expecting. The second post examined the long- and short-run trends in household formations to inform how much housing demand we could expect. A key factor in determining how both aspects play out is the trend in immigration. The inflow of the foreign-born population serves as one of just two channels that drive population growth and in turn household growth. (The other channel is the birth rate of the native-born population.)
Several studies since the housing downturn have explored the trend in immigrant inflows and projected household demand for the coming decade. According to a September 2010 working paper written by George Masnick, Daniel McCue, and Eric Belsky and released by the Joint Center for Housing Studies at Harvard, an increase of between 11.8 million and 13.8 million households, depending on whether you use low- or high-immigration assumptions, is projected between 2010 and 2020. Likewise, Dowell Myers and John Pitkin prepared a report earlier this year for the Research Institute for Housing America projecting an increase of 12.8 million households between 2010 and 2020, of which immigrants account for 4.12 million, or 32.2 percent. Looking back to previous decades, Myers and Pitkin note that the 4.03 million immigrant households that arrived between 2000 and 2010 accounted for 35.9 percent of the growth in households, while the 4.36 million immigrant households that arrived between 1990 and 2000 accounted for 31.8 percent. While it is nice to have a range in mind for how many immigrant households we can expect, it is only meaningful if it is accurate.
So how accurate are these projections? It depends on immigration policy discussions and the pending legislation on immigration reform. As a reminder, the White House released a blueprint in May 2011 in an effort to advance immigration reform. After some chatter in 2011 and 2012, a bipartisan bill (S.744: Border Security, Economic Opportunity, and Immigration Modernization Act) was introduced in April 2013 and then passed by the Senate in June 2013. While not much progress has been made on this particular bill since June, several groups have come to the table with reports on the various impacts of immigration in an effort to better inform the public and policymakers. In this vein, it seems worthwhile to consider some of the literature from academics and trade organizations investigating the impact of immigration on local housing markets.
Most recently, in October 2013, the Bipartisan Policy Center released a report with analysis that "demonstrates that...fixing our broken immigration system will benefit our economy." The sensitivity analysis measured the impact of reform to immigration policy on the housing market and found that "demand for housing units increases as new immigrants enter the economy and form households, accelerating the current housing recovery and fueling growth in this sector of the economy."
Jacob Vigdor, professor of public policy and economics at Duke University, has also looked into the impact of immigration. In a report released by the Partnership for a New American Economy and the Americas Society/Council of the Americas in September 2013, Vigdor estimates that each immigrant adds 11.6 cents to the price of the average home. Vigdor's analysis also revealed four additional findings about the impact of immigrants on the vitality of American communities. First, he found that the effects of immigration on house prices are strongest in the Sun Belt cities. (See this map with complete data for each of the counties studied.) Second, he concluded that immigrants tend to avoid places with the worst housing affordability problems. Third, Vigdor found that immigrants often revitalize less desirable neighborhoods in costly metropolitan areas. And lastly, he pointed out that immigration has stabilized declining rural areas and stanched the decline of Rust Belt cities. For more detail on these and other findings, check out a video clip of Vigdor's presentation of findings to an assembly of Atlanta Fed real estate business contacts.
It is worth noting that Vigdor was not the first to find that an inflow of immigrants causes house prices to rise. In a 2006 Journal of Urban Economics article, Albert Saiz demonstrated that an inflow of immigrants increases demand for housing, thereby causing rents and house prices to rise. Specifically, Saiz found that "an immigration inflow that amounts to 1 percent of the initial metropolitan area population is associated with increases in housing values and rents of about 1 percent." This increase in house price provides some benefit to existing homeowners, but the corresponding increase in rents has negative consequences for renter households, causing some to move away from the area.
There are certainly pros and cons on each side of the policy discussion around immigration reform. It seems rather important, though, to not lose sight of the mostly positive impact that immigrants have on local housing markets.
By Jessica Dill, senior economic research analyst in the Atlanta Fed's research department
July 17, 2013
Are Household Formations on the Verge of Taking Off?
In our discussions with real estate builders and developers, we often hear about references to trends in household formations. The prevailing sentiment seems to be that while household formations were tempered during the downturn, they are bound to pick back up any time now. More importantly, this belief is often cited as justification for ramping up acquisition and development activities.
After hearing numerous contacts cite their expectations for resurgence in household formations, we began to wonder more about the underlying trends. Have recent household formation dynamics fundamentally shifted from the long-run trend? Or have dynamics been stymied only temporarily before they eventually bounce back to the longer-term trend? And what effect will this bounceback have on housing demand?
To better understand these dynamics, we invited Andrew Paciorek, economist at the Federal Reserve Board of Governors, to discuss with staff and leaders from the business, civic, and not-for-profit communities his recently published working paper on the short- and long-run trends in household formation. (You can see his presentation on the Atlanta Fed website.)
Before jumping into the findings on trends in the data, it seems appropriate to acknowledge that the data come from three main sources at the Census Bureau: the Current Population Survey, the American Community Survey, and the decennial censuses. (See the chart below from the full presentation available here.) While each source has its strengths and weaknesses, the important takeaway is that they all tell a different story when viewed in isolation. This gives me some cause for concern when I think about trying to use these data alone as support for making development decisions.
Paciorek's research aims to isolate the drivers of household formation and, once they are better understood, use them to make an informed forecast about trends going forward. So, jumping now to the takeaways on the drivers of household formation, Paciorek finds that demographics (primarily aging) contribute the most to increases in household formation over the long run. Education and income, as well as rental costs, are also found to influence the decision to form a household. In the short run, rental costs, employment status, and income matter the most for decisions to form households.
With that as context, let's look back at the data. From 2001 to 2006, approximately 1.35 million new households were formed each year. Then from 2006 to 2011, the number of household formations dropped to 550,000 each year. Paciorek predicts that if the projected population growth of 2.2 million per year is achieved, we can expect 1.5 to 1.6 million new households to form each year. However, he gives an important caveat: there remain frictions. For example, the restricted availability of credit could temper spikes in household formations over the short run.
Paciorek's forecast is dependent on other data points materializing, but his prediction supports the idea that there will be a bounceback to, and possibly even above, the longer-run trend in household formation. If that bounceback is achieved, we could definitely expect to see an increase in housing demand. Perhaps our industry contacts are positioning themselves well after all.
We invite you to watch a video of the talk that Andrew Paciorek gave on June 24 and to contribute to the conversation by posting your comments below.
By Jessica Dill, senior economic research analyst in the Atlanta Fed's research department
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