Thursday, April 17, 2014

Favorable Financing Costs Not Impacting Remodeling Activity During Recovery

by Abbe Will
Research Analyst
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Solid growth is expected in the home remodeling market this year, according to the Leading Indicator of Remodeling Activity (LIRA) released today by the Joint Center. While annual growth is expected to decelerate some by the fourth quarter due partly to the ongoing sluggishness in home sales, home improvement spending is still expected to grow nine percent in 2014. In the near term, lower rates of household mobility and lean inventory levels of homes on the market seem to be helping the home improvement industry. That coupled with an aging housing stock and deferred expenditures during the recession have owners catching up with delayed remodeling projects this year. Another factor that would normally help boost remodeling spending is low financing costs, but as described below historically low interest rates are not having the same impact on home improvements in current market conditions.

Produced by the Remodeling Futures Program since 2007, the LIRA is a short-term indicator of national trends in home improvement spending. The LIRA is calculated as a weighted average of the annual rates-of-change of its component inputs, which are various economic measures that historically have had strong correlations and leads over remodeling activity. With the release of the First Quarter 2014 LIRA today, a decision was made to change the estimation model by removing the financial market conditions input (as measured by long-term interest rates), because the traditional relationship between interest rates and home improvement spending has significantly deteriorated in recent years. As seen in Figure 1, the impact of this change is slightly lower rates of growth in annual home improvement spending estimated for the past several quarters and substantially higher rates of growth projected for the next three quarters. Under the original LIRA estimation model, homeowner expenditures on remodeling projects are projected to increase about three percent in 2014, while the revised model projects spending will increase nine percent this year.

Note: The revised LIRA model excludes 30-year Treasury bond yields as an input and reweights the remaining inputs proportionally.  
Source: Joint Center for Housing Studies of Harvard University.  

Major changes to the LIRA estimation model have not been common. The last significant change occurred in 2008 when the LIRA was re-benchmarked from the Census Bureau’s Residential Improvements and Repairs Statistics (C-50) to the Construction Spending Value Put in Place (C-30). The reason for changing the LIRA model at this time is because since 2008, the severe housing and the mortgage market crash and subsequent Great Recession has caused unprecedented volatility in many of the LIRA inputs including the financing measure represented by 30-year Treasury bond yields. The theory behind including a financing measure in the LIRA model is that under more normal housing and economic environments, large home improvement projects are often financed by homeowners through home equity loans or lines of credit or cash-out refinancing of mortgages, and so the historically low financing costs of recent years would ordinarily encourage significant remodeling activity.  Yet under the current conditions of a stalled housing market and still lukewarm economic environment, homeowners have not been able to take advantage of historically low financing costs because of much reduced levels of equity in their homes since the housing crash, as well as tighter lending practices of banks. For these reasons, the historically low interest rates of the past two years did not have the same influence on remodeling activity as in the past. Since the fall in rates did not result in a jump in spending, the recent rise in rates are also not expected to have as much of a chilling effect on remodeling spending as in the past. 

Indeed, as shown in Figure 2, the relationship between the annual rates of change in home improvement spending and 30-year Treasury bond yields was fairly strong when the LIRA estimation model was last updated in mid-2008 with a correlation coefficient of 0.7 between 2000 and 2007 (remodeling spending and interest rates are inversely correlated so that when interest rates increase spending declines and vice versa). While long-term interest rates are historically quite stable, since the housing and mortgage market crisis interest rate changes became unusually volatile as interest rates fell to historic lows and again as rates move off of these lows. Not only have interest rate movements become much more volatile, but the direction of change no longer correlates well with remodeling spending. When including data from the more recent period that covers the downturn and recovery, the correlation coefficient between remodeling spending and long-term interest rates weakens considerably to 0.2 and in fact there is essentially no correlation between the two series after 2008. If the traditional relationship between financing costs and remodeling activity were still intact, much stronger growth in home improvement spending should have occurred when interest rates fell to historic lows in the aftermath of the housing crash, and now as interest rates return to their longer-term trend remodeling activity would be expected to decline considerably. Yet remodeling spending has seen relatively low and stable growth in the years following the downturn.

Note: The rate of change in Treasury bond yields are plotted inversely and with a four-quarter lead
Source: JCHS tabulations of Census Bureau’s C-30 and Federal Reserve Board 30 Year Treasury Bond Yields

Given the increased volatility in the C-30 benchmark data series and the LIRA inputs in recent years as the housing and home improvement markets have undergone severe cyclical downturns and sluggish recoveries, there is clearly a need for further testing of the LIRA estimation model moving forward to improve its stability. Each year on July 1st, the Census Bureau releases annual revisions to the C-30 for the prior two years, which provides a good opportunity for re-running LIRA input correlations and testing for further additions or substitutions of input variables that historically correlate well with remodeling spending, have strong leads over spending, and are also relatively stable over time. Any further changes to the LIRA model will be announced with the next quarterly release on July 24, 2014. For more information about the LIRA methodology and frequently asked questions (FAQs), please see the Joint Center for Housing Studies website.

Tuesday, April 8, 2014

Employment and Gateway Cities

by David Luberoff
Guest Blogger
From time to time, Housing Perspectives features posts by guest bloggers. Today's post was written by David Luberoff, senior project advisor to the Boston Area Research Initiative at Harvard’s Radcliffe Institute for Advanced Study.  David will be a panelist at an upcoming Joint Center for Housing Studies event, Opening the Gates of Opportunity: Realizing the Potential of Gateway Cities, taking place at Harvard on Friday, April 18.  More information about the event is below.

Historically, the gateway cities of Massachusetts have been important regional economic centers, drawing workers each day from neighboring cities and towns.  However, today many gateway cities attract fewer employees from surrounding communities while many residents of those cities travel to suburban jobs, according to data from the Census Bureau’s 2006-to-2010 American Community Surveys (ACS).

Lawrence, Massachusetts

As the table below shows, eight of the state’s ten most populous cities are gateway cities, which are defined as midsized urban areas where average household income and rates of Bachelor degree attainment are below the state average.  (The exceptions are Boston and Cambridge).  But only five gateway cities – Worcester, Springfield, Quincy, New Bedford, and Lowell – are on the top ten list of where jobs are located. The three gateway cities on the top ten list for population – Brockton, Lynn, and Fall River – are replaced on the top ten list for jobs by Waltham, Newton, and Framingham.

Even more striking, among the large gateway cities, Springfield and Worcester are the only places where the number of non-residents coming into the city to go to work exceeds the number of people leaving to work in other locales.  This doesn’t mean that no one commutes into gateway cities.  In general, however, the share of jobs held by local residents is higher in gateway cities (with the notable exception of Quincy).  Additionally, residents of gateway cities farther from metro Boston seem more likely to live and work in the same locale.

Consider, for example, patterns in Lawrence.  According to other data from the ACS, about 7,904 of the about 30,052 Lawrence residents who are workers have jobs in that city.  Another 2,665 work in Methuen, while between 800 and 1,200 work in Boston, Haverhill, Woburn, Andover, Danvers, and Wilmington. Of workers coming into Lawrence from other communities, 2,420 come from Methuen, 1,650 from Haverhill, and 860 from Lowell.  No other locality sends more than 350 people.  It’s also worth noting that more workers commute from Lawrence to nearby Andover (which has more than 30,000 jobs) than from any other locality, including Andover. (Click table to enlarge.)

These data suggest that policies designed to strengthen gateway cities should seek opportunities to make those localities more attractive to firms that draw employees from both the city and surrounding communities.  At the same time, policymakers should seek opportunities to better connect residents of the state’s gateway cities with jobs in suburban locales as well.

These and other challenges and opportunities of gateway cities will be discussed at a half-day event taking place at the Harvard Graduate School of Design next Friday, April 18th. Opening the Gates of Opportunity: Realizing the Potential of Gateway Cities is free and open to the public, but advance registration is required. Please register to attend or watch the live webcast on the Joint Center website (no registration required for the webcast). 

Thursday, April 3, 2014

The Role of Investors in Acquiring Foreclosed Properties in Low and Moderate Income Neighborhoods

by Chris Herbert
Research Director
In the fall of 2011 the What Works Collaborative convened a meeting of researchers, policy makers, and practitioners to help frame a research agenda to inform policy making on issues related to housing finance over the next several years. Among the issues discussed at the convening was the challenge of obtaining mortgage financing in lower‐income neighborhoods heavily impacted by the foreclosure crisis. At the time, the foreclosure crisis had yet to show signs of abating even as the main federal initiative to address the impact of concentrated foreclosures on communities across the country, the Neighborhood Stabilization Program (NSP), was beginning to wind down. Participants noted that while the NSP had been plagued by problems that had stymied efforts to expend program funding, private investors had emerged in markets around the country as a significant source of demand for foreclosed properties in heavily impacted neighborhoods, with the volume of financial investment made through private channels easily dwarfing those made with NSP backing. Yet, while it was clear that private investors were playing a substantial role in absorbing foreclosed properties and directing substantial capital into these areas, there was little systematic information available about the scale of investor activity, who the investors were, what strategies they were pursuing with the properties they acquired, or what the consequences would be for these neighborhoods of this substantial increase in investor activity.

To address this void, the What Works Collaborative funded a series of case studies in four market areas across the country representing a range of market conditions. In each market, the researchers focused on the activities of investors in acquiring foreclosed properties in low‐ and moderate‐income neighborhoods in the metropolitan area core county. The purpose of the research was to identify in each area the extent to which foreclosed properties were being acquired by investors, what scale investors were operating at, the strategies that investors were pursuing with these properties, whether they were engaging in rehabilitation of these properties, and ultimately what impact their activities were likely to have on the surrounding community. To address these issues the case studies combined quantitative analysis of available data on transactions involving foreclosed properties with qualitative information gathered through interviews with government officials, nonprofit organizations, investors, real estate agents, lenders, and other informed observers.  These are the four case studies, as well as a summary and synthesis of findings from the report series:

Thursday, March 27, 2014

JCHS Releases New Household Projections

by Dan McCue
Research Manager
Today, the Joint Center for Housing Studies posted its latest household projections. These new projections incorporate several updates to data that were made since our last projections in 2010. The 2013 projections use the Census Bureau 2012 Population Projections (released in late 2012 and early 2013), and also use more recent data to derive headship rates (ratios of households per person), specifically using data from the 2011-2013 Current Population Estimates and Current Population Survey March Supplements.   

Aside from the new data, the JCHS projection methodology remains largely unchanged from that used to create the 2010 series. The most notable change is that unlike in 2010 we do not make any adjustment to the Census Bureau’s population projections, as our concerns about what seemed to be overly high estimates of future immigration levels have now been addressed in the latest projections from Census. Since we are using the 2012 Census population projections as published, the 2013 JCHS household projections now contain high, middle, and low series, whereas the 2010 projections only had a high and a low series. The projections are also carried out an additional ten years, and so now extend to 2035.

The 2013 JCHS household projections are consistent with those from 2010.  In the near term (2015-2025), they call for annual household growth rates ranging from 1.16 million in the low series to 1.32 million in the high series, not far from the span of 1.15–1.36 million per year in our 2010 projections.  Differences between the 2013 and 2010 series largely follow differences in the underlying population projections (Figure 1).  Some difference is also due to updated headship rates, which are calculated for every 5-year age group by race and averaged across the years 2011, 2012, and 2013.  These are now slightly lower overall than those from 2007, 2008, and 2009 used in the 2010 projections (Figure 2).  (Click to enlarge.)

Sources: 2008 and 2012 Census Bureau Population Projections and 2010 JCHS Household Projections.

Note: Adult headship rates use CPS/ASEC household counts and Census July 1 Estimates of the population age 15 and older.  Source: JCHS tabulations of Census Bureau data.

Like the 2010 projections, our 2013 household projections also anticipate substantial growth in minority, senior, and single-person households in the coming decades (Figure 3).  In the 2015-2025 period for instance, minorities are projected to account for just over 76 percent of all household growth in each of the low-, middle-, and high- projections, with Hispanics alone accounting for 40 percent of total household growth. Additionally, growth in the number of households age 65 or older during this period is also expected to be 91 percent of the net change in households under the low projection and 81 percent in the high projection. As a result of the growth in senior households, single-person (4.4-4.7 million) and married-without-children households (4.0-4.3 million), two of the largest groups that comprise senior households, will together comprise nearly three quarters of all household growth in 2015-2025, but the number of married with children households will also see some growth as millennials age.

Source: 2013 JCHS Household Projections.

Tenure Scenarios Presented as Well

The report also includes a simple homeowner and renter projection scenario.  Under a steady-state scenario of constant homeownership rates by age, race, and household type, this analysis offers one look at how demographic changes in the composition of households may influence future homeownership rates. In this scenario, changing demographics are expected to be a positive influence on the overall homeownership rate through about 2025 (Figure 4).  After that time, the upward influence of the aging of the population gives way to greater downward pressure from young adult and minority household growth.  Figure 4 shows how downward pressure on homeownership rates is steepest in the high projections which, unlike the middle- and low-projections, expects no demographically driven growth in homeownership rates through 2025.

Note: Homeownership rates by age, race/ethnicity, and household-type are held constant. 
Source: Joint Center for Housing Studies tabulations of 2013 JCHS Household Projections.

Users of these estimates are cautioned that that they should be considered baseline projections and not a growth forecast. Actual household growth could deviate dramatically over short periods of time, as the projections reflect long-run, demographically driven trends and do not allow for any adjustments either upward or downward in response to changing economic conditions or cyclical factors.  Indeed, favorable economic conditions could increase headship rates above levels assumed in the projection and increase household growth, while a variety of factors could weigh down economic opportunities and result in lower household formation rates that depress future household growth.  

Monday, March 17, 2014

Build It and They Will Come – Or Will They?

by George Masnick
In a previous post, I suggested that elderly baby boomers may be less likely, in the future, to move to newly built “senior” housing in the numbers that many housing analysts expect. Baby boomers might indeed be better off if they did move – to new housing that is smaller in size, on one level, handicapped accessible, easier to care for, convenient to public transportation and/or within walking distance to shopping and services, more energy efficient, and generally more affordable (lower taxes, utility costs, upkeep, etc.).  It would appear likely that there would be a strong demand for such housing, and public and private initiatives are underway to create such housing. But will aging boomers move to it?

Arguing against a high demand for senior housing among aging baby boomers is the fact that most now live in owner occupied housing with which they are quite happy. Almost three quarters of those over the age of 45 in a recent AARP poll strongly agreed with the statement: “What I’d really like to do is stay in my current residence for as long as possible.” Owners over the age of 65 have had very low mobility rates (about 2 percent per year) that have shown no signs of increasing in recent years.  Large cohorts of young adults who will come of age over the next two decades will compete for newly built housing.  This could very well maintain recent patterns of housing consumption where the young are over-represented in newly built units and the elderly are under-represented relative to their share of all households.

In addition, there are hosts of demographic, social, and economic trends affecting aging baby boomers that argue against any significant future increase in geographic mobility for persons over the age of 65.  I will address a few in some detail and mention others in passing.

Longer Working Life – Labor force participation rates for those over the age of 65 have increased steadily since 2000, growing by 38 percent for men and 66 percent for women. Increasing life expectancy, high middle-age divorce rates coupled with lower remarriage rates among older women, and employment in jobs increasingly less likely to carry retirement benefits are all trends that support both the overall upward trend and the gender differential in elderly labor force participation. For many elderly in the labor force, going to work is something they look forward to and are not eager to give up.  An Urban Institute analysis of the 2002 Health and Retirement Survey found that over 95 percent of employed persons over the age of 65 agreed or strongly agreed that they enjoyed going to work. Longer working life will help to postpone retirement migration (although some retirees who move to retirement destinations might seek new employment there), and the longer retirement is delayed the more difficult it might be for individuals to relocate once retirement finally happens.  

More Two-Earner Households – Today, about 70 percent of baby boom wives are in the labor force (Figure 1). Given the 84 percent labor force participation of baby boom husbands, a clear majority of married couples are dual-earner households. As boomers age, we expect this cohort to have higher labor force participation rates for both men and women over the age of 65 than the generation that came before them.  This trend is significant for future elderly mobility rates.  When one spouse is “ready” to retire and the other is not (either because of age difference or preference to keep working), retirement mobility is less likely.  If both spouses postpone retirement, mobility over the age of 65 is even less likely.  

Age Differences Between Spouses – With delayed marriage and the high incidence of divorce and remarriage in the U.S., it becomes more likely that the next generation of elderly will have more marriages with large age differences between spouses. These trends further compound the effect of dual-earner couples on lowering residential mobility rates when the oldest spouse is ready to retire.

The Effects of the Great Recession – Just as one can argue that the Great Recession has given the elderly greater incentives to work later in life, the same factors have reduced housing turnover. Falling home values and loss of home equity, and a higher share with mortgages that are under water, have made selling one’s home and moving less attractive.  Even for those with low or zero outstanding mortgages, selling their home for significantly less than what it was worth before the Great Recession is a difficult pill to swallow.  There is always the hope that prices might soon rebound.  For many with mortgages that they have recently refinanced to take advantage of historically low interest rates, there might be a “lock in” effect that makes it more difficult to purchase a different house requiring a mortgage at higher rates.  These factors affect mobility rates of both the young and old. 

Population has Shifted to the South and West – Historically, retirement migration has favored Sunbelt states in the South and West.  But the majority of the population that will cross the 65+ age threshold over the next 20 years already live in the South and West (Figure 2a).  Shifting regional population concentration is a result of both historically higher birthrates in the South and West, and because these regions have been destinations for in-migrants, both domestic and foreign. A significantly higher share of the population age 45+ living in states the South and West were born in another state (Figure 2b).  In a very real sense, there is less of a need for Sunbelt retirement migration – yet another factor that could dampen aggregate baby boomer mobility rates in old age.

Source: 2012 American Community Survey from Census Bureau American Fact Finder – Table B06001

Movers vs. Stayers – Consistent with the very low mobility rates of elderly owners is the fact that a majority of owners age 65+ have been living in their current home for a long time.  According to the 2011 American Housing Survey, almost 60 percent of owners age 65+ have lived in their homes for over 20 years.  This share has been constant for the past decade.  The older the owner the higher the share, with 51 percent of owners age 65-74 being long-term residents, 64 percent who are age 75-84, and almost 75 percent of those age 85+ being 20+ year residents in their current home.  Those who are more prone to move are likely to do so when they are younger – leaving behind a residual group more likely to composed of stayers.   Many baby boomers with the highest propensities to move have already adjusted their housing before age 65 and may feel less of a need to do so in the future.

Later Age at Becoming Grandparents – More women are having their first child later in life.  Over the past four decades, the average age of first time mothers increased 4.2 years, from 21.4 years in 1970 to 25.6 years in 2011.  In many European countries, age at first birth is 3-4 years later, suggesting that there is still some room for upward movement in this trend in the U.S.  Birth rates for women over the age of 30 have increased steadily from the mid-1980s to the onset of the Great Recession (Figure 3).  Later age at childbearing has translated into later age at becoming a grandparent for the women’s parents. Today, many men and women in their 60s are becoming grandparents for the first time, and still more have a youngest grandchild who is still a toddler.  This would be particularly true for the more highly educated grandparents who were more likely to have had their own children at later ages.  While I can offer no hard data, I suspect that later age at becoming a grandparent should motivate older couples to hold onto their too-large houses to facilitate the regular (or occasional) visits from their children and young grandchildren.  Having young grandchildren would also perhaps make long-distance retirement migration less attractive.

In addition to the factors just mentioned, the development of the internet and all that it implies for communication with relatives and friends, shopping, health care, working from home, and a host of other details of daily living, could help older folks stay in their homes, if that is what they want to do, a bit longer than they might have in the past. Still, it must be acknowledged that by virtue of their very large numbers, aging baby boomers could contribute to a growing numerical demand for senior housing even if their mobility rates are lower than the previous generation’s.  My argument is that the demand just might not be as large as some are predicting. What seems certain, however, is that more focus is needed on helping seniors who are aging in place.  This includes such things as help in retrofitting and maintaining their housing; help with transportation; and supporting senior centers that provide meals, social activities, and information/advocacy across a wide scope of services that senior’s need.