Thursday, February 16, 2017

Defining the Generations Redux

by George Masnick
Senior Research Fellow
How should we define the baby boom, Generation X, and the millennial generation?

In a Joint Center blog published in 2012, I argued that using 20-year age spans for each generation would make it easier to compare them. Since many researchers still use generational definitions that span different and inconsistent age ranges, particularly for millennials, it is perhaps timely to reframe and restate my case.

In keeping with my recommendations, the Joint Center has long identified the cohort born between 1945 and 1964 as baby boomers.Those born between 1965 and 1984 are Generation X, and the cohort born between 1985 and 2004 are millennials (Figure 1). 

However, other analysts use several different earlier dates to usher in the millennial generation, apparently because they want to ensure that the oldest member of this cohort were considered adults at the dawn of the new millennium (i.e. they had turned 18 or 20 in the year 2000). This definition meant that by 2015, the oldest millennials were in their mid-30s, old enough to prompt compelling stories about how many 30-somethings were still living with parents, living in cities, forsaking marriage and childbearing, and delaying homeownership. In contrast, under my recommended cut-off dates, the oldest millennials turned age 20 in 2005 and didn’t start entering their 30s until 2015.

Besides making it easier to compare generations, there are several reasons why the millennial generation should start with those born in 1985 and turning 20 in 2005. As I noted in my 2012 blog, 1985 was the year that U.S. births once again exceeded 3.7 million, the approximate number that demarcated the beginning and the end of the baby boom, as well as the beginning and the end of the “baby bust” that defines Generation X.

Three other big changes occurred shortly after 2005 that significantly altered the way young adults live. First, social media participation skyrocketed. Facebook became available to everyone age 13 and older with a valid e-mail address in September 2006. Twitter became public in 2006. The first iPhone was released in June of 2007. As a result of these and other changes, the share of adults using social media rose from five percent in 2005 to 69 percent in 2016, according to a recent Pew Research publication.

Second, student loan debt outstanding more than tripled between 2005 and 2016, rising from $400 billion to over $1.3 trillion. This high level of debt is thought to affect everything from leaving the parental home, to getting married and starting a family, and purchasing a first home. 

Third, and perhaps most importantly, the economic changes that led to the Great Recession hit hardest among young adults who were in their 20s shortly after 2005. The unemployment rate of adults older than 25 without a high school degree rose from below six percent in late 2006 to 15 percent in mid-2009. (Those with a high school degree or more followed this trend within a year.) Unemployment rates of those with a high school degree or more have slowly improved, but still remain above pre-recession levels. Unemployment rates for those with less than a high school degree have returned to their pre-recession elevated levels, but people in this group generally are making less money and receiving fewer benefits than they did before the recession. Meanwhile, housing costs have returned to, or now exceed, their pre-recession levels.

Using equally broad 20-year age spans produces several important findings about the different generations. To start with, the millennial generation has been larger than the baby boom generation, now or at any other previous time since the boomers were age 10-29 in 1975 (Figure 2). Millennials now number almost 87 million compared to less than 79 million for baby boomers at the same age. This is in contrast to findings of a 2016 Pew Research study that compared generations using millennials with a smaller age range and found roughly equal numbers between these two generations in 2015 (75 million).

Using consistent age spans also shows the changing ways that immigration has affected the number of people in each generation. In 1995, when Generation X was age 10-29, it was smaller than the baby boom generation was in 1955, when it was the same age. However, because of immigration, by 2005, when Generation X was age 20-39, it already exceeded the number of baby boomers at the same age. 

Immigrants also make up a small but growing share of millennials. In 2015, 9.6 percent of millennials were foreign born compared to 21.4 percent of Generation X, and 15.3 percent of baby boomers (Figure 3). However, according to the latest Census Bureau population projections, the share of millennials who are foreign born is expected to rise to 20.9 percent in 2035 when they are age 30-49, which will boost the number of millennials to 97.3 million (Figure 4).  

* Data do not allow 85-89 year olds from 85+ age group

Finally, the constant-age-span approach allows us to identify significant generational differences in race and ethnicity. Overall, in 2015, 45.4 percent of millennials, 41 percent of Generation X, and 28.6 percent of baby boomers were minorities (i.e. non-Hispanic Blacks, non-Hispanic Asian/Others, or Hispanics of any race). Moreover, because of continued immigration, the share of millennials who are minorities is projected to rise to almost 50 percent in 2035 and the share of Generation X is projected to rise slightly to 42.4 percent. In contrast, the share of baby boomers who are minorities is projected to hold constant at 28.6 percent. 

These differences reflect changes for both foreign-born and native-born members of each generation. In 2015, fully 85 percent of both foreign-born millennials and foreign-born members of Generation X were minorities.  In contrast, only 78.5 percent of foreign-born baby boomers were minorities. Moreover, while 41.2 percent of native-born millennials were minorities, only 29 percent of native-born members of Generation X and 19.6 percent of native-born baby boomers were minorities (Figure 5).

* Data do not allow 85-89 year olds from 85+ age group

Looking forward to 2035, the size of the baby boom cohort will drop to about 60 million people because a growing number of baby boomers will pass away. Many millennials and members of Generation X will want to live in the housing units formerly occupied by those baby boomers. Their ability to do so will not only be shaped by the fundamental economic and social changes discussed above but also by whether the large numbers of racial and ethnic minorities in these two generations will have full access to those housing markets, and with it, the ability to achieve the American dream. 

Tuesday, February 7, 2017

When Do Renters Behave Like Homeowners? High Rent, Price Anxiety, and NIMBYism

by Michael Hankinson
Meyer Fellow
In theory, renters and homeowners disagree about proposals to build new housing in their communities, particularly if that housing is close to where they live. However, in practice, this is not always the case. 

Rather, in a new Joint Center working paper that is based on new national-level experimental data and city-specific behavioral data, I find that in high-housing cost cities, renters and homeowners both oppose new residential developments proposed for their neighborhoods. However, in high-cost markets renters are still more likely than homeowners to support citywide increases in the supply of housing. Since changes in city governments over the past several decades have generally strengthened the power of neighborhood-level opponents to proposed projects, my findings help explain why it is so hard to build new housing in expensive cities even when there is citywide support for that housing.

NIMBYism and the Rising Cost of Housing

Since 1970, housing prices in the nation’s most expensive metropolitan areas have dramatically increased. Real prices have doubled in New York City and Los Angeles and nearly tripled in San Francisco. Driving this appreciation is an inability of new housing supply to keep up with demand. Even accounting for the cost of materials and natural geographic constraints on supply, the dominant factor behind this decoupling of supply and demand is political regulation, such as limits on the density of new housing developments and caps on the number of permits issued by a localities’ government.
These limits are a classic example of the NIMBY (Not in My BackYard) phenomenon. Even if residents support a citywide increase in the supply of housing, they may still oppose specific projects in their neighborhood. This seeming disconnect between views on citywide and local development policies creates a classic collective action problem for those policymakers who must find ways to reconcile the conflicting views.  

Photo by Michael Hogan/Flickr

Despite its popularity as a scapegoat, there is no individual-level, empirical data on how NIMBYism operates and among whom.
 Students of urban politics generally assume that homeowners have strong NIMBY tendencies not only because they benefit from rising house prices but also because they worry that nearby new housing units, particularly nearby subsidized housing units, might decrease the value of their home.

There is less consensus on (or studies of) how renters view new development. New supply may help ease prices for renters but their pro-development views may not be reflected in local policies because renters are less likely to become politically involved than highly motivated homeowners.  Alternatively, renters might not favor new projects if they believe the units will increase demand in their neighborhood, which, in turn, will lead to increased housing prices. To date, however, there has been very little research on how renters view development projects and whether their views differ from those of homeowners.
Measuring NIMBYism

To measure NIMBYism and general support for new housing, I collected two unique datasets. I conducted the first experimental tests of NIMBYism through an online survey of 3,019 respondents across 655 cities in 47 states. Respondents were asked about their support for development policies, including whether they would support a 10 percent increase in their city’s housing supply, with the question customized to each respondent’s city, stating how many homes and apartments currently exist and how many more would be built. Respondents also participated in an experiment where they were presented with two housing developments and asked which of the two proposals they preferred for their city. Each proposed development was described using several attributes, such as height and affordability level. To measure NIMBYism, respondents were also told how far each the of developments would be from their home, from two miles away to ⅛ mile away. By randomly varying this distance along with the other attributes, I was able to measure respondents’ sensitivity to proximity (NIMBYism), holding all other attributes equal.

To supplement this national survey, I also conducted a 1,660-person exit poll during the 2015 San Francisco election. Voters at 26 polling locations were asked their opinions on several housing-related ballot propositions similar to those presented in the national survey.

When Renters Behave Like Homeowners

As noted, renters and homeowners are expected to disagree on support for new housing, with NIMBY homeowners opposing citywide and neighborhood development and renters likely supporting the new supply. In line with existing theory, homeowners in my national survey largely opposed the proposed 10 percent increase in their city’s housing supply (28 percent approval), while a majority of renters supported the new supply (59 percent approval). Likewise, when asked in the experiment which of two randomly generated buildings they would prefer for their city, homeowners exhibited consistent NIMBYism, preferring buildings that were farther away from their home. In contrast, renters on average did not pick buildings based on distance from their home. If anything, renters preferred affordable housing that was closer to their home, displaying a YIMBY or ‘Yes in My BackYard’ attitude. In short, homeowners and renters tend to have very different attitudes towards both NIMBYism and the citywide housing supply.

However, in high-rent cities, renters look far more like homeowners. Instead of paying little attention to the location of proposed new housing, renters in expensive cities are just as NIMBY towards market-rate housing as homeowners. Moreover, this renter opposition to nearby development does not mean they support less new development overall. In fact, renters in expensive cities show just as much support for a 10 percent increase in their city’s housing supply as renters in more affordable cities. The main difference between these groups of renters is their NIMBYism.

Results from the San Francisco exit poll show a similar combination of supporting supply citywide, but opposing it locally. When asked about a 10 percent increase in the San Francisco housing supply, both renters and homeowners expressed high levels of support, at 84 percent and 73 percent approval, respectively. But, somewhat surprisingly, when asked if they would support a ban on market-rate development in their neighborhood, renters showed far more NIMBYism than homeowners, with 62 percent of renters supporting the NIMBY ban compared to 40 percent of homeowners.

NIMBYism and How We Permit Housing

Renters in high-rent cities generally both want new housing citywide but behave like homeowners when it comes to their own neighborhood. These scale-dependent preferences present a policy challenge for keeping cities affordable. Over the past 40 years, city governments have increasingly empowered neighborhoods to weigh-in on housing proposals through formal planning institutions. In doing so, these decisions have amplified NIMBYism and the ability to reject new housing, without maintaining a counterweight for the broader interest for new supply citywide. In other words, while most residents may support new housing for the city as a whole, both homeowners and renters are willing and increasingly able to block that supply in their own neighborhood, effectively constraining the housing supply citywide. This is housing’s collective action problem.

In separate research, I am empirically testing the effect of these strengthened neighborhood institutions on the rate of housing permitting since 1980. Likewise, I am conducting further experimental research on what types of citywide housing proposals are able to win the greatest support among both homeowners and renters. Hopefully, by measuring the tradeoffs between the ‘city’ and ‘neighborhood’ in the politics of housing, we can better address the deepening affordability crisis facing many American cities.