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Does Doubling Up Mask Poverty? Examining How Change in Household CohabitationContributes to Change in Estimates of Young Adult Poverty over the Great Recession

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Full Title: Does Doubling Up Mask Poverty? Examining How Change in Household CohabitationContributes to Change in Estimates of Young Adult Poverty over the Great Recession

Short Title: Poverty among Young Adults and Cohabitation over the Great Recession

Article Type: Major Article

Keywords: young adults; young adult transition; poverty; cohabitation; the Great Recession;decomposition method

Corresponding Author: Chiho SongUniversity of WashingtonSeattle, WA UNITED STATES

Corresponding Author's Institution: University of Washington

First Author: Chiho Song

Order of Authors: Chiho Song

Order of Authors Secondary Information:

Manuscript Region of Origin: UNITED STATES

Abstract: The Great Recession disproportionately impacted the poverty of young adults ages 18-34. Scholars have argued that household cohabitation serves as adaptive response foryoung adults facing economic insecurity brought on by the recession. However, thisthesis has little systematic analysis. Using data from the Survey of Income andProgram Participation, this study uses a decomposition to examine the relationshipbetween change in the FPL poverty rate among young adults and prevalence ofcohabitation between 2004 and 2012. Results show that without the aggregatechanges in household cohabitation, estimates of young adult poverty over the GreatRecession would have been 25.8 percent higher. This suggests that labor marketconditions accounted for most of the increase in young adult poverty over this period,but these effects were considerably attenuated by cohabitation. Findings call forconsidering changes in household structure as key in understanding young adults'poverty.

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Poverty among Young Adults and Cohabitation over the Great Recession 1

Does Doubling Up Mask Poverty? Examining How Change in Household Cohabitation

Contributes to Change in Estimates of Young Adult Poverty over the Great Recession

Abstract

The Great Recession disproportionately impacted the poverty of young adults ages 18-34.

Scholars have argued that household cohabitation serves as adaptive response for young adults

facing economic insecurity brought on by the recession. However, this thesis has little systematic

analysis. Using data from the Survey of Income and Program Participation, this study uses a

decomposition to examine the relationship between change in the FPL poverty rate among young

adults and prevalence of cohabitation between 2004 and 2012. Results show that without the

aggregate changes in household cohabitation, estimates of young adult poverty over the Great

Recession would have been 25.8 percent higher. This suggests that labor market conditions

accounted for most of the increase in young adult poverty over this period, but these effects were

considerably attenuated by cohabitation. Findings call for considering changes in household

structure as key in understanding young adults’ poverty.

Keywords: young adults, young adult transition, poverty, cohabitation, the Great Recession,

decomposition method

Manuscript


Does Doubling Up Mask Poverty?: Examining How Change in Household Cohabitation

Contributes to Change in Estimates of Young Adult Poverty over the Great Recession

INTRODUCTION

Young adults ages 18-341 were among the hardest hit by the weakened labor market during the

Great Recession (2007-2009) (Danziger, Chavez, and Cumberworth 2012; Bitler and Hoynes

2015; Hoynes, Miller, and Schaller 2012). The unemployment rate among this age group jumped

from 8.8 percent in 2006 to 13.6 percent in 2011, a 55 percent increase (Payne and Copp 2013);

and poverty rate increased by 22 percent from 16.7 to 20.4 percent, the highest jump out of all

adult age groups (US Census Bureau 2015a). Despite improving labor market conditions

beginning 2009, young adults continue to experience employment insecurity and bleak economic

prospects (Davis, Kimball, and Gould 2015). Young adults have little or no work experience,

low skill-development, and tend to get more contractual and temporary jobs than adults with

better job skills and experiences (Antonucci, Hamilton, and Roberts 2014). The Great Recession

has exacerbated the increasing job insecurity of the post-industrial labor market, especially for

low-wage and temporary workers with basic education, many of whom would oftentimes be

young adults (Sandberg-Thoma, Snyder, and Jang 2015).

In harsh labor market conditions that heighten risks of unemployment and poverty, the

welfare state and the family can emerge as important institutions of support. Yet, young adults

are left out of the social welfare policy realm, both historically and normatively. The liberal

welfare state of the US promotes a strong notion of personal responsibility to manage risks, and

ascribes a ‘shame of dependence’ for youth unemployment and use of state-based welfare

1 Consistent with US Census Bureau (2015b, 2015c) and other studies (Aassve et al., 2013; Fursternberg

2010; Mykyta 2012; Schoeni and Ross 2005), the present study defines young adults as those ages of

18-34. Depending on research purposes, various operational definitions of young adulthood as a range

of years can be used (e.g., ages 20-29 in Addo (2014); ages 18-25 in Arnett and Tanner (2006); ages 18-

30 in Bitler and Hoynes (2015); ages 17-23 in Kaplan (2012); ages 19-34 in Matsudaira (2016)).


provision (Walther 2006). Young people are thus compelled to complete youth as transition

phase quickly and be economically independent as soon as possible (Antonucci et al. 2014).

Given dire economic employment opportunities and limited welfare state support for

young adults in the US, scholars have considered the role of the family, specifically household

cohabitation or ‘doubling up’ with family as well as friends, as an important private safety net

against economic insecurity associated with the recent recession (see Aldridge 2015; Bitler and

Hoynes 2015; Matsudaira 2016; Mykyta and Macartney 2011; Wiemers 2014). The role of

family resources in the US has become more central as a safety mechanism of antipoverty

assistance to young adults, especially those from poor families (Bitler and Hoynes 2015; Haider

and McGarry 2006), but remains understudied and less systematically analyzed compared with

the labor market and the state in academic research (Kaplan 2012; Wiemers 2014).

Most studies that examine household cohabitation view it primarily as an outcome or a

response to labor market conditions buffeted by the Great Recession (Bitler and Hoynes 2015;

Matsudaira 2016; Mykyta and Macartney 2012; Sassler, Michelmore, and Zhang 2014; Wiemers

2014). Few have examined the reverse notion: how household cohabitation may affect estimates

of young adult poverty as a function of labor market conditions. Although several scholars agree

that household cohabitation helps young adults save on rent and cut household costs during

economic hardships, little is known about how poverty rates are impacted directly by young

adults’ household cohabitation as a response to the Great Recession. The official poverty

measure by the US Census Bureau does not capture changes in household cohabitation, while

existing poverty scholarship has failed to take this into account, suggesting that “true” poverty

rate of this age group may be masked by cohabitation.


Thus, this study examines the relationship between changes in the federal poverty level

and household cohabitation among young adults between pre- and post-recession periods in

order to reveal how the private and hidden nature of cohabitation may mask poverty of this age

group. In the first section, I review literature regarding the changing economic and institutional

contexts confronting young adults: the labor market, the welfare state, and the family. Next, I

elaborate the decomposition method applied to analyzing young adults’ cohabitation and poverty

rate, followed by empirical results. Finally, I discuss main findings as well as limitations and

implications of this study for future research.

BACKGROUND

Young adulthood, as the life phase between the ages of 18 to 34, is a crucial transitional period

from adolescence to adulthood as individuals seek economic independence and residential

autonomy through education and employment (Aassve et al. 2013; Arnett and Tanner 2006). The

uncertainty of this “in-between” period includes a variety of transitions, such as completing

higher education, entering full-time jobs, moving into new living arrangements, getting married

or engaging in partnerships, and childrearing (Vickerstaff 2006; Furstenberg 2013). Despite

popular attention to those specific circumstances, young adults are rarely treated as a distinct

subpopulation in policy (Bonnie, Stroud, and Breiner 2014). In this sense, it is crucial to

understand current conditions of social and institutional support that can help young adults

navigate these uncertain times (Bonnie et al. 2014; Furstenberg 2010; Wiemers 2014).

To provide context for understanding young adults’ poverty in relation to household

cohabitation over the Great Recession, young adulthood is contextualized via a discussion of the

labor market, the welfare state, and the family in the post-industrial economy. Then, turning to


more recent times, the Great Recession, context for young adulthood and cohabitation, as

adaptive response to growing economic insecurity is presented.

THE LABOR MARKET, THE WELFARE STATE, AND THE FAMILY IN THE POST-

INDUSTRIAL ECONOMY

Young adulthood has become more challenging in the post-industrial economy, while the family

as the private safety net has likewise become strained due to demographic transitions and the

breakdown of the traditional family structure since the early 1970s. Yet, the US policy response

has been to retract governmental support to such challenges via its liberal welfare youth

transition regime. Policy has largely failed to deal with this accumulated strain stemming from

the changing family structure (Swartz 2008).

The Labor Market in the Post-industrial Economy

The socioeconomic transformations of post-industrialization have resulted in insecure situations

or ‘new social risks’ (Rovny 2014), to which young adults are particularly vulnerable due to their

specific life course stage (Antonucci et al. 2014). New social risks are distinct from the old forms

of social risks in that the labor market has replaced the state as the primary means of social

protection (Rovny 2014). Entry into an increasingly competitive labor market has become a

much more critical step that carries over into future job prospects, long-term careers and job

stability, thus concentrating new social risks upon young adults (Rovny 2014; Taylor-Gooby

2004). In response, young adults turn not only to the labor market, but also to the welfare state

and the family, as sources of basic economic security (Antonucci et al. 2014; Ranci 2010), within

the context of the mixed welfare economies of Western democracies (Esping-Andersen, 1990).


In the early 1970s, the labor market has been fundamentally restructured, as characterized

by de-industrialization and the loss of high paying, stable manufacturing jobs for workers of

limited education, the boom of the service sector, women’s increased entry into paid work, along

with the broader context of globalization and emerging information-driven economy (Sandberg-

Thoma et al. 2015; Taylor-Gooby 2004). Compounding the restructuring of the labor market was

the decline of labor unions, which has weakened the political power of the working class in the

postindustrial era (Hirsch and Macpherson 2003; Rosenfeld 2014). This has yielded more

‘atypical’ jobs such as part-time work, temporary contracts and low-wage ‘mini-jobs’ that don’t

carry social benefits (Rovny 2014).

Young adults in the labor market who lack skills and a minimum level of education are

the most impacted by de-industrialization. Before this restructuring (the postwar period through

the 1970s), large stable manufacturing sectors provided high levels of family-wage employment

for the mass of population. Those jobs did not require higher education levels of workers, and

even young adults with only basic education were thus able to sustain independence (Taylor-

Gooby 2004). Since the 1980s, stable employment in the manufacturing sectors has become

scarcer, making it increasingly difficult for low-skilled and low-educated workers to find work

(Taylor-Gooby 2004). Especially vulnerable are young adults, who are in a transitory phase of

life and have low-level skills and limited employment experience (Rovny, 2014). Further, young

adulthood has become protracted (Furstenberg 2013). Time spent in post-secondary education

has been significantly prolonged, as the job market that has become much more competitive also

required more specialized skills and knowledge from workers. The prolongation of pathways to

adulthood makes young adulthood a time of both individual risk and opportunity (Bonnie et al.


2014). This restructured labor market has challenged the capacity of the welfare state and the

family as two institutions providing economic and social support.

The Welfare State in the Post-industrial Economy

Faced not only with the growing job insecurity in the labor market but also a strong conservative

political offensive in an age of austerity, the welfare state transitioned from one of traditional

social protection to one requiring greater individual responsibility (Pintelon et al. 2013). This

welfare transition has retracted social welfare provisions from citizens (Pierson 2001; Rovny

2014) and prioritized work, making employment a primary obligation of the virtuous citizen

(Rovny 2014; Taylor-Gooby 2004).

Welfare state regimes in the context of young adults’ transitions can be characterized into

four ‘regimes of youth transition,’ formulated by Walther (2006)2: universalistic, employment-

centered, sub-protective, and liberal, each describing the impact of different institutional

arrangements on young adults’ transitioning to adulthood. In this typology, the US can be

considered a liberal transition regime. The primary characteristic of the liberal transition regime

is to emphasize individual rights and responsibilities rather than collective provisions. Also, in

this liberal transition regime, the labor market is highly flexible with lower level of qualifications

and education required of the workforce compared to other regimes. This regime has a fluid

labor market with many entrance and exit options, thus increasing the number of workers

confronting precarious conditions (Walther 2006).

2 Walter’s ‘regimes of youth transition’ is a modification of welfare regime typologies formulated by

Esping-Andersen’s (1990) and then later refined by Gallie and Paugam (2000). Esping-Andersen’s

typology of three welfare regimes (liberal, conservative and social-democratic) is based on different

degrees of commodification of welfare programs. Gallie and Paugam separates Esping-Andersen’s

conservative welfare regime into two: employment-centered and sub-protective welfare regimes.


Young adults in the liberal transition regime of the US face restricted welfare state

support and unique challenges of independence. The liberal transition regime assumes youth as a

transition phase that should be replaced as soon as possible by economic independence. Youth

unemployment is attributed to a culture of dependency. However, these normative assumptions

of early independence based on job security contradict with the bleak labor market conditions of

the time that could not guarantee job security. That welfare state context, compounded with the

post-industrial labor market, discussed above, has forced young adults into more unstable and

fragmented transitions. For instance, yo-yo transition referring to various forms of reversible

transitions such as returning to the parental home after a period of living independently reflects

this protracted volatility and uncertainty of young adulthood (Antonucci et al. 2014; Walther

2006). Instability of this period has become commonplace in jobs and education, but also in

terms of family structure and residential autonomy (Furstenberg 2013; Walther 2006).

The Family in the Post-industrial Economy

The family and its role for supporting young adults have undergone transitions and its structure

has destabilized, in the post-industrial economy marked by changes noted above (Bonnie et al.

2014; Rovny 2014). Since the 1960s, a new demographic transition occurred, following the first

transition of declines in mortality and fertility during the early 1900s (Furstenberg 2013). This

‘second demographic transition’ is characterized by delays in fertility and marriage, increases in

cohabitation, divorce, non-marital childbearing and single parenting, and increases in maternal

employment (McLanahan 2004). This transition has led to different trajectories for women. The

one trajectory is for women who delay childbearing and work in the labor market as mothers

reflecting gains in resources while the other is for women who are divorced and out-of-wedlock


childbearing reflecting losses. Thus, women are bifurcated: those who are advantaged follow the

first trajectory whereas those who are disadvantaged follow the second. This dichotomization of

women by class and resources widened disparities in parental resources that children get access

within the family system (McLanahan 2004).

Another important shift is the prolongation of young adulthood (Fursternberg 2013),

lasting now more than 15 years (White 1994; Silverstein and Bengtson 1997; Schoeni and Ross

2005; Swartz 2008; Swartz 2009). Several obstacles encumber young adults’ path to financial

independence. Some jobs in the new economy, such as entry-level jobs for which most young

adults qualify given their lack of experience, don't pay a living wage (Setternsten, Furstenberg,

and Rumbaut 2005; Swartz 2009). Moreover, young adulthood is characterized by formation of

identity and social relationships, both of which can incur high cost, for paying for clothes and

social activities and events, for example (Arnett 2004; Collins and van Dulmen 2006). Also,

educational attainment and skill building yield financial burdens for tuition and related costs, as

well as human resources, such as time and effort (Aquilino 2006; Schoeni and Ross 2005;

Waithaka 2014).

Younger generations have traditionally relied on their families to step in to make this

transition period into adulthood smoothly (Swartz 2009). However, the family has been strained

due to the decline of the traditional family system centered on male breadwinner and the increase

of female’s role not only in domestic care work but also in wage labor (Pintelon et al. 2013;

Taylor-Gooby 2004). Thus, the family is less able to transfer material resources and psychosocial

support activities to its younger members (Taylor-Gooby 2004). For instance, living

arrangements based on intergenerational relationships have become increasingly necessitated

(Swartz 2009).


With a challenging labor market and governmental inaction, the family system has been

less able to support younger generation, especially for those from the most disadvantaged

backgrounds. The family has lost capabilities for traditional direct investment in children

enjoyed by earlier generations. Thus, for young adults in the post-industrial economy and

dismantled welfare state, the family is not a means of support but a last resort. However, despite

of lacking material resources and direct giving, the family still functions as young adults’ private

safety net through household cohabitation, suggested by poverty scholars.

HOUSEHOLD COHABITATION AS ADAPTIVE RESPONSE OF YOUNG ADULTS TO

GROWING ECONOMIC UNCERTAINTY

Conceptualization of Household Cohabitation and its Historical Trend

Household cohabitation refers to sharing living arrangements including co-residence with

parents, a partner, non-relatives (Yelowitz, 2007) or relatives in multi-generational households

(Fry and Passel 2014). The most examined type of cohabitation of young adults is parental

cohabitation, as opposed to residence with marital partners, relatives, or non-relatives. Living

with parents may be considered a more resourced and more stable living arrangement, compared

with doubling up with other relatives or non-relatives. Failure to launch means staying at the

parental home even after reaching the legally defined adult age of 18, though this turning point

may be in terms of median home leaving age–21 for women and 22 for men in the US

(Furstenberg 2013; Iacovou 2002). The phenomenon of young adults moving out of their

parents’ home and only to later return has been termed “boomerang”. These two phenomena of

“failure to launch” and “boomerang” are depicted as social worry in the media. That parental

cohabitation has generated the most attention suggests that it is important and effective way of


responding to harsh economic conditions compared with other types of cohabitation, although

some scholars posit this importance as exaggerated in the US context (Danziger and Rouse

2007). Cohabitation has also been examined in relation to school enrollment (Mykyta, 2012;

Mykyta and Macartney 2011; Wiemers 2014) and fertility behavior (Morgan, Cumberworth, and

Wimer 2011). Couch surfing, or temporarily sleeping in a series of friends’ or other people’s

living rooms or improvised sleeping arrangements, has also recently emerged as a new and

alternative form of living arrangements or and even as a form of ‘invisible’ homelessness,

particularly by the youngest generation of young adults (McLoughlin 2013), but it has not been

considered as a type of cohabitation in the poverty and cohabitation literature.

Historically, evidence suggests that young adults’ cohabiting to help mitigate the impact

of challenging economic conditions is not a new phenomenon (Payne 2012; US Census Bureau

2015a). Across the years between 1940 and 2010, the trend of parental coresidence for young

adults ages 18-24 is U-shaped, peaking in the 1940s at 55 percent, declining to 37 percent in the

1960s, and then rising back up to 50 percent in 2010 (Payne 2012). For those ages 25-34,

meanwhile, the trend swung from 23 to 9 then to 20 percent in the same time frame (Payne

2012). Since the 1980s in post-industrial economy, young adults’ cohabitation has changed

substantially, paralleling increases in poverty at the time. Between 1980 and 2013, young adults’

parental cohabitation has expanded from 23 to 30 percent and their poverty increased from 14 to

20 percent (US Census Bureau 2015a). In essence, increased household cohabitation is in tandem

with more heightened economic challenges but the pendulum trend suggests that this relation is

not temporary but a perpetual adaptive response to persistent post-industrial economic

uncertainty, as most visibly depicted in the Great Recession.


Household Cohabitation, Poverty, and Unemployment in the Great Recession

Growing economic insecurity fueled by the economic downturn of the Great Recession –

declining employment opportunities and rising inequality – have undermined the material

foundation for many young adults to achieve education and employment depending on their

socioeconomic backgrounds, resulting in a “failure to launch” into economic independence or

“boomerang” back to their parental home (Hanson and Essenburg 2014). Through the recession,

poverty rates increased among young adults of any age and any education level (Grusky,

Western, and Wimer 2011). The poverty rate rise was most abrupt for young adults with less

than a high school education and younger sub-groups (ages 20-24 compared with ages 25-34)

(Grusky et al. 2011). In addition, rising poverty worsens the long-term economic prospects for

millions of jobless and unskilled young adults and their children, nearly half of whom are with

mothers who have completed high school or less (Grusky et al. 2011).

Scholars summarize how the recent recession affected young adults’ household

cohabitation as outcome. First, the number and proportion of young adult parental cohabitation

substantially increased over the recession period (Fry 2013; Jacobsen and Mather 2011; Mykyta

2012; Payne and Copp, 2013). More young adults cohabited, compared with the period just prior

to the start of the recession: the number of young adults in shared households increased by 11.9

percent (or 2 million) in spring 2010, compared to spring 2007 (Mykyta and Macartney 2012).

Second, the rates of parental cohabitation among young adults were different by individual

characteristics such as race, gender, and age groups and by family socioeconomic backgrounds

(Fry 2013; Hanson and Essenburg 2014; Jacobsen and Mather 2011; Payne 2012; Payne and

Copp 2013). The economic benefits associated with household cohabitation would be maximized

for young adult from the most advantaged backgrounds (Fry and Cohn 2011). Young adults


more likely to live with their parents are racial minorities, male, and those in their teens and early

20s (ages 18-24) (Fry 2013).

The association between young adults’ poverty and cohabitation is positive: young adults

with higher individual-level and family-level poverty status are more likely to reside in their

parental home (Mykyta 2012). Given higher risk of poverty, the recent recession coincided with

a growth in cohabitation among young adults (Payne 2012). In regard to unemployment,

previous research suggests a positive association between unemployment rates and cohabitation

rates: increased unemployment leads to increased cohabitation (Aassve et al. 2002; Iacovou

2010; Matsudaira, 2016; Sassler et al. 2014; Wiemers 2014). Recent research by Bitler and

Hoynes (2015) shows that the effect of the unemployment rate on young adult independent living

arrangements was larger in the Great Recession compared to the 1980s recession. For young

adults aged 18-30, a one percentage point increase in the unemployment rate decreased the

independent living arrangements by 1.33 in the 2000s vs. 0.5 percent in the 1980s, though both

effects were insignificant (Bitler and Hoynes 2015).

Poverty as a Function of Household Cohabitation

Specifically with regards to the Great Recession, most studies on household cohabitation

examine it as an outcome affected by unemployment and poverty originating from labor market

conditions (See, e.g., Bitler and Hoynes 2015; Matsudaira 2016; Mykyta and Macartney 2012;

Sassler et al. 2014; Wiemers 2014). The research consensus posits household cohabitation as an

adaptive individual-level strategy to help decrease housing costs and other related living

expenditures (e.g., utilities, housing or rental insurance, transportation, child care, food),

especially during times of economic crisis (Furstenberg 2010; Haurin, Hendershott, and Kim


1993; Mykyta and Macartney 2011; Settersten and Ray 2010; Payne 2012; Wiemers 2014;

Yelowitz 2007) and particularly critical for young adults’ transitional phase of life (Arnett and

Tanner, 2006).

However, few have examined the reverse notion: how cohabitation may affect estimates

of young adult poverty, given labor market conditions. The very recent policy report by Aldridge

(2015) conducted in the United Kingdom is one exception. Aldridge (2015) finds that a slight

increase (four percentage points) in the proportion of young adults aged 19-25 living with their

parents is linked with the decrease in poverty rate by 0.8 percentage points between 2000-2003

and 2010-2013. However, Aldridge (2015)’s analysis, based on counterfactual decomposition

methodology, does not provide testable estimates between young adults’ poverty and their

parental cohabitation. In addition, that approach does not account for confounding factors nor

does it specify the period of the Great Recession.

Young adults’ poverty and cohabitation are reciprocally caused: poverty may influence

the likelihood of cohabitation and simultaneously the level of support gained from cohabitation

may affect poverty. This endogeneity makes evaluating young adults’ poverty challenging. In a

metrical sense, determining economic well-being should be done through the quantification of

various forms of support from unmarried partners, friends, others in co-residence; however,

those types of support are elusive or difficult to quantify and often not considered. Consequently,

young adults’ de facto economic status may be masked by support associated with cohabitation.

Whereas cohabitation is most commonly analyzed as an outcome impacted by

unemployment or economic strain, there is less examination of cohabitation as adaptive response

that may mask or modify poverty rates among this age group during and after the Great

Recession. Because the official poverty measure by the US Census Bureau does not reflect


changes in household cohabitation, the measure may underestimate or mask young adult poverty

by not accounting for cohabitation as supporting mechanism.

Thus, this study examines poverty rate and household cohabitation among young adults

through the Great Recession, using a decomposition method, an advanced technique called

multivariate decomposition to nonlinear responses that address methodological limitations of

previous studies. First, I examine whether or not the rates of cohabitation among young adults

aged 18-34 increased over the period of the Great Recession (2004-2012). Second, I hypothesize

that increased cohabitation among young adults over the Great Recession attenuates estimates of

the official poverty rate increase over this period. Third, in addition, I hypothesize that parental

cohabitation makes a greater contribution to the decrease in official poverty rate estimates for

young adults over the recession, compared with the other three types of cohabitation (residing

with relatives, an unmarried partner, or non-relatives).

DATA

Data from the Survey of Income and Program Participation (SIPP)3 are used for analysis. The

SIPP is a nationally representative, longitudinal, multi-stage stratified sample of civilian, non-

institutionalized households in the U.S. that began in 1983 (Shaefer, 2014). Data collection for

the SIPP is more frequent (monthly) compared with other commonly used datasets, such as the

Census Population Survey Annual Social and Economic Supplement (CPS ASEC). Thus, the

SIPP presents more detailed information on factors that may frequently change, such as living

arrangements. Also, the SIPP’s oversampling of low-income households and minority groups

(Sassler et al. 2014) may offer insights on whether and how cohabitation patterns may be

3 The SIPP has advantages over the CPS ASEC: 1) month-level details with much shorter recall periods,

2) more detailed income and comprehensive public program participation variables, and 3) better

estimates of income and program participation (Shaefer, 2014).


different for these groups, about whom less is known, compared with their high-income and non-

minority counterparts. Moreover, poverty rate as assessed in the SIPP is aggregated over 12 time

points, unlike the CPS ASEC, that measure poverty at only one time point. Also, this dataset has

been utilized in other studies that have examined the relationship between labor market

conditions and living arrangements over the Great Recession (see, e.g., Sassler et al. 2014;

Wiemers 2014).

This study examines the SIPP 2004 and 2008 panels. The SIPP 2004 panel has waves 1-

12 covering from February in 2004 to January in 2007 while the SIPP 2008 panel has waves 1-

16 covering from September in 2008 to December in 2013. From the total sample, waves 1-11 in

the SIPP 2004 panel and waves 4-14 in the SIPP 2008 panel are selected to restrict the study

period as the pre- and post-recession periods. The SIPP 2004 waves 1-11 (from February in 2004

to September in 2007 for 44 months) has 775,351 person-month observations and the SIPP 2008

waves 4-14 (from September in 2009 to April in 2013 for 44 months) has 756,927 person-month

observations of young adults ages 18-34. Considering the official definition of the Great

Recession as a period from December 2007 to June 20094, as defined by the National Bureau of

Economic Research (NBER), this study assumes that the pre-recession period is defined as 2004-

2007 (3 years before the recession) and post-recession period as 2010-2012 (3 years after the

recession). This analysis is treating 2004 as being a representation of the favorable pre-recession

market and 2012 as a very bleak post-recession labor market for young adults. Then, for

decomposition, the years 2004 and 2012 for the pre- and the post-recession period, respectively,

are examined. Among the total sample (110,467 and 77,768 individuals as of January in 2004

4 Meanwhile, the Federal Reserve defines the beginning of the Great Recession as 2006 when new

housing construction declined with the bottom of the Great Recession in the summer of 2009

(Weinberg, 2013).


and 2012), the analytic sample has 24,099 and 16,103 young adults from the two panels that

were between 18-34 years old in 2004 and 2012, respectively5.

Poverty, as outcome, is defined as young adults being poor when their household’s total

pre-tax money income is less than US federal poverty line (US Census Bureau 2016). The

federal poverty line is determined using a set of income thresholds that vary by family size and

the number of children under age 18 (US Census Bureau 2016). Adopting the definition used by

previous scholars (Yelowitz, 2007; Mykyta, 2012; Mykyta and Macartney, 2012), household

living arrangements are conceptualized into two: 1) independent living: residing either alone or

with a spouse and/or natural, adopted, or step children under 18 only, and 2) cohabitation.

Cohabitation is categorized into four groups, applying Yelowitz (2007)’s categorization (See

appendix for details): (a) parental cohabitation, (b) cohabitation with other relatives, (c)

cohabitation with unmarried partners, and (d) cohabitation with unrelated individuals 6 .

Cohabiting thus means not just living together but it is defined by the type of relationship of each

individual to the household head in the household. As indicator for labor market conditions7,

age-specific8 (ages 16-34), state-level civilian unemployment rate from the Bureau of Labor

Statistics (BLS) is used.

Other measures include post-secondary school enrollment (enrolled full-time, part-time

or not enrolled during the given year), individual characteristics (age, gender, and race), and

5 The difference in the available sample for both years is due to a reduction in the sample size (attrition or

non-response) in wave 4-14 compared to wave 1 in the SIPP 2008 panel. 6 In the SIPP, unrelated individuals include housemate/roommate, roomer/boarder, and other non-relative. 7 Minimum wage may be considered as a labor market condition to affect young adults’ living

arrangement. However, its impact is still contested depending on perspectives (Sassler et. al. 2014).

Also, compared to unemployment rates, state-level minimum wages did not directly change during the

Great Recession. Thus, minimum wages are not included in the present study. 8 The Bureau of Labor Statistics offers age 16-19, 20-24, 25-35 unemployment rates. I aggregated these

data by state per year; unemployed young adults divided by the age-specific total civilian labor force in

each state per year. I only used 2004 and 2012 unemployment rates.


residential region (a combination of four regions and urban/rural) as control variables. Post-

secondary school enrollment is controlled for to avoid concerns about endogenous school

attendance and cohabitation decisions (Wiemers 2014). Since the prevalence of cohabitation

among young adults is different by age, gender, and race, and residential region, those factors are

controlled.

METHOD

This paper uses Powers, Yoshioka and Yun’s multivariate decomposition for nonlinear response

models that is an extension of the Oaxaca–Blinder regression-based decomposition method

(2011). Power et al.’s method allows for the testing of whether and to what extent changes in the

poverty rate are related to changes in household living arrangements, controlling for other

covariates. The decomposition method is conducted in three steps: 1) finding the difference in

the poverty rate between pre- and post-recession periods, 2) assessing the overall effect of

covariates on the difference in the poverty rate, and 3) assessing the individual effect of each

covariate on the difference in the poverty rate.

In step one, the probability of being in poverty is distributed as a logistic function,

P𝑖 =

exp(X𝑖β)

1 + exp(X𝑖β) (1)

where P𝑖 refers to the probability of the ith person being poor in the sample. A property of logit

specification is that the expected value of P is given by the average of the estimated probabilities

of X𝑖 multiplied by their coefficients, i.e. P̅ = F(Xβ)̅̅ ̅̅ ̅̅ ̅̅ (Gradin 2012; Powers et al. 2011). Before

performing the overall and detailed decomposition, I use a dichotomous variable describing the

two years (2004 and 2012) in the sample to separate the data into pre- and post-recession

distributions (A and B, respectively). Algebraically, the difference in the expected value of


poverty risk between year A (comparison group) and year B (reference group) is given by P̅A −

P̅B, and can be expressed as:

P̅A − P̅B = F(XAβA)̅̅ ̅̅ ̅̅ ̅̅ ̅̅ ̅ − F(XBβB)̅̅ ̅̅ ̅̅ ̅̅ ̅̅ ̅ (2)

In step two, equation (2) is rewritten by subtracting and adding a counterfactual term

F(XBβA)̅̅ ̅̅ ̅̅ ̅̅ ̅̅ ̅. Thus, the overall decomposition is defined as:

P̅A − P̅B = [ F(XAβA)̅̅ ̅̅ ̅̅ ̅̅ ̅̅ ̅ − F(XBβA)̅̅ ̅̅ ̅̅ ̅̅ ̅̅ ̅ ] + [ F(XBβA)̅̅ ̅̅ ̅̅ ̅̅ ̅̅ ̅ − F(XBβB)̅̅ ̅̅ ̅̅ ̅̅ ̅̅ ̅ ] (3)

The first term, F(XAβA)̅̅ ̅̅ ̅̅ ̅̅ ̅̅ ̅ − F(XBβA)̅̅ ̅̅ ̅̅ ̅̅ ̅̅ ̅ yields the aggregate characteristics (covariates) effect,

which fixes the vector of coefficients, βA, in order to quantify the effect of the covariates on the

change in poverty risk. Similarly, by fixing the covariates, XB, in the second term, F(XBβA)̅̅ ̅̅ ̅̅ ̅̅ ̅̅ ̅ −

F(XBβB)̅̅ ̅̅ ̅̅ ̅̅ ̅̅ ̅, we obtain the aggregate coefficients effect on the change in poverty risk.

In step three, the detailed decomposition allows us to evaluate the individual contribution

of each covariate and each coefficient to the difference in poverty risk. This is achieved by

applying weight parameters, WΔxk , and, WΔβ

k , to the kth aggregate characteristics effect ΔX𝑘and

coefficients effect Δβ𝑘, respectively (Powers et al. 2011). That is:

P̅A − P̅B= ∑ WΔxkK

k=1 [F(XAβA)̅̅ ̅̅ ̅̅ ̅̅ ̅̅ ̅ − F(XBβA)̅̅ ̅̅ ̅̅ ̅̅ ̅̅ ̅] + ∑ WΔβkK

k=1 [F(XBβA)̅̅ ̅̅ ̅̅ ̅̅ ̅̅ ̅ − F(XBβB)̅̅ ̅̅ ̅̅ ̅̅ ̅̅ ̅] (4)

where the kth weight component for WΔx is a fraction of the overall characteristics effect

WΔxk =

(XAk − XB

k ) βAk

∑ (XAk − XB

k) βAkK

k=1

(5)

and the kth weight component for WΔβ is a fraction of the overall coefficients effect

WΔβ

k =XA

k (βAk − βB

k )

∑ XAk (βA

k − βBk )K

k=1

(6)

and


∑ WΔx

k

K

k=1

= ∑ WΔβk

K

k=1

= 1 (7)

The specification in equation (4) describes the individual contribution of each covariate

and coefficient to the overall change in poverty risk. However, results should not be interpreted

as causal statements because the aim of the decomposition analysis is not to identify causal

relationships between the covariates and the poverty risk but to gain some insight into

associations between changes in the covariates and changes in poverty risk (Joo 2013).

Meanwhile, in order to guarantee the robustness of the decomposition results, two issues

should be addressed: the indexing problem and the identification problem in the detailed

decomposition (Powers et al. 2011). The former refers to the problem that the estimates of

characteristics and coefficients effect can be variable by switching the roles of the reference and

comparison groups. The latter refers to the problem that the coefficients effect is not invariant by

the choice of the referent (or omitted) category when dummy variables are used.

First, a solution to the indexing problem is to use the average logit coefficients from a

pooled sample of the two groups as the reference (or fixed) coefficients for the overall

decomposition (Fairlie 2014; Powers et al. 2011). By changing the reference coefficients from

βA to βB and the reference covariates from XB to XA in equation (3), a following equivalent

equation, i.e. [F(XAβB)̅̅ ̅̅ ̅̅ ̅̅ ̅̅ ̅ − F(XBβB)̅̅ ̅̅ ̅̅ ̅̅ ̅̅ ̅] + [F(XAβA)̅̅ ̅̅ ̅̅ ̅̅ ̅̅ ̅ − F(XAβB)̅̅ ̅̅ ̅̅ ̅̅ ̅̅ ̅] is yielded, which often provides

different results. The use of the average coefficients from a pooled sample can avoid the problem

that the decomposition results can be varied by choosing βA or βB as the reference coefficients.

Next, a solution to the identification problem is to transform the logit estimates into a

normalized equation and use the normalized equation for the detailed decomposition (Gang, Sen,

and Yun 2008; Powers et al. 2011). This is equivalent to taking the average of the estimates of

the coefficients effects obtained by every possible specification of the reference groups in a set


of dummy variables as the “true” contributions of individual variables to differentials. The use of

the normalized equation does not change our inference for the aggregate characteristics and

coefficients effects (Gang et al. 2008).

Following the solutions suggested by Fairlie (2014), Gang et al. (2008), and Powers et al.

(2011), I used the average logit coefficients from a pooled sample of the pre- and post-recession

periods and the normalized equation to resolve the indexing and identification problems.

RESULTS

DESCRIPTIVE RESULTS

Table 1 presents a summary of descriptive characteristics of the main variables used in the

decomposition analysis. The overall cohabitation rate among young adults aged 18-34 increased

by 8.9 percentage points from 44.2 to 53.1 percent between 2004 and 2012. However, that

increase is primarily explained by parental cohabitation while cohabiting with unmarried

partners and non-relatives in fact decreased. Parental cohabitation rate increased by 10.5

percentage points, making up for the 0.7 and 1.0 percent points decrease in rates of cohabiting

with unmarried partners and non-relatives, respectively; while cohabiting with relatives remained

at a consistent rate of 5.9 percent. This finding lends support for the notion of “failure to launch”,

which means young adults having to live with parents rather than an unmarried partner or

apartment mates due to economic necessity. After the Great Recession, more young adults chose

to cohabit, most commonly with their parents. Cohabiting with parents commonly covers rent

and most of household expenditures, but cohabiting with partners or non-relatives often still

requires young adults to pay for their share of rent or household costs, even as those costs are

less compared with living independently or alone.


The findings reveal that the changes were inconsistent across the four forms of

cohabitation between 2004 and 2012. Living arrangements were statistically different between

years (F=75.83, p<.001) as well as race/ethnicity (F=6.70, p<.001) and school enrollment

(F=67.84, p<.001). Over the span of nine years between 2004 and 2012, there were no

significant changes in demographics for age, gender, and residential region9 (F=2.04, p=.11;

F=.15, p=.70; F=.24, p=.94, respectively).

[TABLE 1 HERE]

LOGISTIC REGRESSION FOR YOUNG ADULT POVERTY BY PRE- AND POST-

RECESSION PERIODS

As an initial step before the decomposition analysis, a logistic probability model of the

likelihood of poverty using the maximum likelihood (ML) estimation is carried out. The

estimated logit coefficients are reported in Table 2.

I proceed by discussing the logit estimates in the pre-recession young adult group. With

respect to household living arrangements, the coefficient “cohabiting with parents”, which is

strongly negative, suggests that young adults with parental cohabitation had significantly less

risk of poverty compared to those with independent living arrangements. In addition, controlling

for other variables, the association between young adult poverty and the dummy variables in

school enrollment is negative, suggesting that compared to young adults who were enrolled full-

time in school, those who were enrolled part-time or not enrolled in school have lower risk of

9 To test the significance of each variable between two periods, the Rao-Scott chi-square test (a designed-

adjusted version of the Pearson chi-square test) is used using svy: tab command in STATA (Rao and

Scott, 1984). It is reported as a design-based F statistic with its associated p-value. For proper use of svy

command, a new survey set is declared using svyset command. It can deal with the difference of the

strata variable between 2004 and 2012 yielded by the complex design in the merged data (Shaefer,

2014).


poverty. The estimated coefficients on sub-age groups show that older young adults were less

likely to be in poverty, compared to those aged 18 to 19. Additionally, female young adults had a

greater likelihood of being poor compared to male young adults. In regard to race, all the

minority groups relative to whites had higher risk of poverty, especially Blacks and Hispanics.

The negative association between young adult poverty and the dummy variables of residential

region suggest that relative to young adults residing in the South and in non-metropolitan area,

those residing in other areas were less likely to be poor. However, it is important to note that

because large sample sizes tend to yield statistically significant coefficients in the model, a

discussion of effect sizes would be beneficial. For instance, the association between young adult

poverty and state-level age-specific unemployment rate holding others constant is positively

significant, indicating that a 1 percentage point increase in the unemployment rate for young

adults would lead to a 16 percent increase in the odds of being in poverty (i.e. exponentiating the

logit coefficient of 0.146 is equal to 1.16).

The directionality of the partial association between poverty and other covariates holds

true for post-recession young adults: Controlling for other covariates, young adults with the

following characteristics or in the following categories are shown to have lower likelihood of

being in poverty: young adults residing in dependent living arrangements, enrolled part-time or

not enrolled, older, male, whites, non-South non-metropolitan areas, in states with lower

unemployment, compared with residing in independent living arrangements, enrolled full-time,

younger, female, minorities, South non-metropolitan area, in states with higher unemployment,

respectively. The magnitude and statistical significance of the coefficients are slightly different

compared to their pre-recession counterparts, however.

[TABLE 2 HERE]


DECOMPOSITION RESULTS OF CHANGES IN THE YOUNG ADULT POVERTY RATE

Table 3 presents the decomposition results. The first row shows the actual poverty rates of young

adults between 2004 and 2012 (9.88 percent and 13.74 percent). The next two rows separate the

3.86 percentage point increase in the poverty rate into the percentage points that can be attributed

to changes in the observed characteristics over time (explained; 1.36) and the percentage points

that are due to the coefficient effect and other unobserved characteristics (unexplained; 2.50).

These results indicate that about 35 percent of the poverty increase of young adults can be

attributed to differences in the observed characteristics of young adults, their geographic context,

and the local labor market conditions. The bottom half of Table 3 breaks down the total

explained difference (1.36 percentage point) into its component parts: household living

arrangements, state-level unemployment rate, and other control variables (i.e., school enrollment,

age, gender, race, and residential region).

The results show that the characteristics included in the model can explain about 35

percent of the poverty increase for young adults. The characteristic effect of changes in

household living arrangements is about a negative 1.0 percentage point, indicating that

equalizing the household living arrangements of the before- and after-recession groups would

increase the poverty difference by 25.8 percent. Put another way, without changes in household

living arrangements, estimates of young adults’ poverty would have increased by about 26

percent. This finding is consistent with those from other studies suggesting links between

estimates of young adults’ poverty rates and cohabitation (Aldridge 2015; Mykyta 2012; Mykyta

and Macartney 2011).


Meanwhile, this increased poverty is primarily driven by labor market conditions. The

changes in state-level age-specific unemployment rate between 2004 and 2012 would

independently explain a 1.9 percentage point increase in young adults’ poverty, accounting for

about 49 percent of the total poverty increase.

Further, three factors, school enrollment, gender, and race, have a statistically significant

but marginal role in explaining increased poverty for young adults. Approximately 3.0 percent of

the total poverty increase can be attributed to changes in school enrollment rate; 0.2 percent to

changes in gender composition; and 7.8 percent to changes in racial composition.

[TABLE 3 HERE]

Table 4 presents the differential contribution for the four types of household cohabitation

on changes in poverty. The net contribution of parental cohabitation to poverty is about a

negative 0.5 (-12.5 percent), the largest compared to other types of cohabitation. This indicates

that changes in parental cohabitation plays a much larger role in reducing the magnitude of the

total poverty increase, compared with other types of cohabitation. In contrast, the second most

influential form of cohabitation, living with an unmarried partner, only reduced the poverty rate

increase by .4 percent. It is also noteworthy that the net contribution of independent living to

poverty is sizeable, a negative 0.5 percent point (-13.4 percent). Living independently does not

always mean financial security. Instead, it may denote financial hardship due to difficulty

gaining access to resources and assistance from others, unlike their cohabiting counterparts. The

reduction in proportion of young adults living independently from the pre- to the post-recession

periods (from 55.8 percent to 46.9 percent in Table 1) may thus explain the sizeable contribution

of independent living arrangements to the relative risk of poverty.

[TABLE 4 HERE]


DISCUSSION

A key contribution of this study is to provide empirical evidence suggesting that young

adults’ poverty is underestimated without accounting for changes in their household cohabitation

as one type of living arrangements.

The findings suggest that increased household cohabitation for young adults, particularly

with their parents over the period of the Great Recession reduced the official poverty rate

estimate over what it would have been had cohabitation behavior remained static over this

period. Without the increase in household cohabitation as a presumably adaptive response, the

increase in young adult poverty would have been 25.8 percent higher from 3.86 to 4.85

percentage points. Given this considerable rate, poverty measures that do not account for

cohabitation, such as that by the US Census Bureau may be underestimating poverty.

However, the contribution of unemployment rates to poverty suggests that changes in the

labor market conditions account for 49.4 percent of the total increase in the young adult poverty

rate between periods. Thus, although increased cohabitation lessens young adults’ poverty rate, it

is the increased unemployment during the Great Recession that is the primary explanatory factor

for the increase in poverty rate among young adults.

In sum, macro forces impose a much more significant toll: the net contribution of labor

market conditions (49.4 percent) on the poverty rate of young adults was nearly twice greater

than that of household cohabitation (-25.8 percent) on poverty. Although labor market

mechanisms largely drove the increase in young adult poverty post-recession, these effects were

also notably attenuated by cohabitation adaptive response. Finally, it is noted that to the extent

that measures of poverty do not account for adaptive changes in cohabitation, the true poverty

rate of the young adult population may be considerably underestimated.


Whereas most studies on young adults’ cohabitation analyze it as an outcome affected by

broader socioeconomic conditions, this study contributes to current knowledge about

cohabitation by examining it as an explanatory factor for poverty rate. This analytical approach

on cohabitation reveals how individuals, such as young adults, resort to adaptive responses, such

as cohabitation, in the absence of more appropriate institutional supports in the retrenched U.S.

liberal welfare state, especially during prolonged economic recession.

The Great Recession yielded unprecedented high levels of unemployment and its impact

on young adults was disproportionately high (Danziger et al. 2012; Bitler and Hoynes 2015;

Hoynes et al. 2012). This sustained structural unemployment of young adults has posed as an

especially grave challenge to U.S. anti-poverty policy. The basic principle of U.S. poverty

alleviation is linked to employment, but harsh labor market conditions with higher

unemployment excluded young adults from the primary sector of the American workforce (Edin

and Kissane 2010). This study suggests that the economic consequences of high unemployment

among young adults may be significantly obscured by changes in cohabitation patterns.

However, American institutional supports have retracted and resources and services have

dwindled for young adults, especially those from disadvantaged families (Flanagan and Levin

2010; Sandberg-Thoma et al. 2015). With limited institutional support (Sandberg-Thoma et al.

2015), young adults have had no recourse but to turn to other means to address economic

challenges over the Great Recession.

Young adults may be cohabiting to try to avoid poverty, but the effects of individual-

level efforts were minimal compared with those of labor market conditions. At the individual-

level, young adults could acquire more resources through cohabitation on reducing their level of

poverty. However, at the aggregate level, those effects are highly likely to be just temporary and


peripheral, resulting in long-term politico-economic consequences for the next generation as well

as the current age group of young adults in the US.

Cohabitation among young adults may decrease their individual-level cost of living but it

may also increase the financial burden upon parents, their cohabiting partners or the entire

household in the long-term. For instance, the parents’ capacity to save for their future old age

needs may be undermined by the continued economic dependence of their young adult children.

Further, cohabitation with parents may not be a choice or an equal access for a large share of

young adults with familial conflicts and whose parents have limited resources that preclude

cohabitation.

Future research on young adults’ poverty and household living arrangements could refine

these findings in several ways: conduct analyses that allow causal inferences; account for more

extended time periods so that cohabitation patterns can be more closely tracked against economic

cycles; consider other structural conditions that may affect young adult poverty rates during

periods of economic shock such as state-level welfare transfers; account for confounding

variable such as fertility behavior and/or decisions; consider alternative measures of poverty

other than the FPL, such as measures based on relative income. In addition, the relative

availability of the parental household as a fallback resource is likely to differ by social class if

not race—thus contributing further to disparities in poverty rates by class and race during

economic downturns, particularly those from young and less educated, along with racial minority

groups, leading to higher risk of poverty (Grusky et al. 2011).


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TABLES

Table 1. Sample Characteristics of Young Adults, 2004-2012

Variable Percentage

Diff. 2004 2012

Household living arrangements:

Independent living 55.8 46.9 -8.9

Cohabiting with parents 28.3 38.8 10.5

Cohabiting with relatives 5.9 5.9 0.0

Cohabiting with unmarried partners 4.6 3.9 -0.7

Cohabiting with unrelated individuals 5.4 4.4 -1.0

State-level unemployment rate (age-specific) 8.1 11.4 3.3

School enrollment:

Enrolled full-time 18.8 24.8 6.0

Enrolled part-time 6.7 6.3 -0.4

Not Enrolled 74.6 68.9 -5.7

Age group:

Ages 18-19 12.0 12.2 0.2

Ages 20-24 29.9 30.3 0.4

Ages 25-29 28.1 28.9 0.8

Ages 30-34 30.0 28.6 -1.4

Gender:

Male 49.9 49.7 -0.2

Female 50.1 50.3 0.2

Race/ethnicity:

White 61.7 58.0 -3.7

Black 12.6 13.1 0.5

Asian 4.2 4.9 0.7

Hispanic 18.5 20.1 1.6

Other 2.9 3.8 0.9

Residential region:

Northeast, metro 14.7 13.9 -0.8

Northeast, non-metro 3.5 3.4 -0.1

Midwest, metro 16.7 15.9 -0.8

Midwest, non-metro 5.6 5.3 -0.3

West, metro 20.4 21.4 1.0

West, non-metro 3.2 3.4 0.2

South, metro 29.4 30.0 0.6

South, non-metro 6.4 6.7 0.3

N (raw count) 24,099 16,103

Note: Percentages are weighted by SIPP calendar-year weight. They may not total 100% due to rounding. Sources: Data from SIPP (year 2004 and 2012).


Table 2. Logistic Regression Modeling Young Adult Poverty, 2004-2012

Variable 2004 2012

Coefficient SE Coefficient SE

Intercept -2.382*** (0.204) -1.210*** (0.224)

Household living arrangements (ref: Independent

living):

Cohabiting with parents -1.244*** (0.085) -1.042*** (0.082)

Cohabiting with relatives -0.697*** (0.117) -0.877*** (0.124)

Cohabiting with unmarried partners -0.410** (0.127) -0.336* (0.146)

Cohabiting with unrelated individuals -0.766*** (0.129) -0.926*** (0.164)

State-level unemployment rate (age-specific) 0.146*** (0.020) 0.037* (0.016)

School enrollment (ref: Enrolled full-time):

Enrolled part-time -0.704*** (0.134) -0.520*** (0.137)

Not Enrolled -0.244** (0.078) -0.164* (0.079)

Age group (ref: ages 18-19):

Ages 20-24 -0.454*** (0.089) -0.253** (0.092)

Ages 25-29 -0.821*** (0.101) -0.528*** (0.111)

Ages 30-34 -1.050*** (0.103) -0.683*** (0.114)

Gender (ref: male):

Female 0.431*** (0.051) 0.376*** (0.055)

Race/ethnicity (ref: white):

Black 1.300*** (0.063) 1.273*** (0.077)

Asian 0.492*** (0.124) 0.213 (0.144)

Hispanic 1.132*** (0.066) 1.121*** (0.070)

Other 0.780*** (0.115) 0.614*** (0.127)

Residential Region (ref: South, non-metro):

Northeast, metro -0.339*** (0.102) -0.706*** (0.112)

Northeast, non-metro -0.312 (0.168) -0.798*** (0.172)

Midwest, metro -0.659*** (0.095) -0.799*** (0.106)

Midwest, non-metro -0.020 (0.117) -0.312* (0.127)

West, metro -0.916*** (0.098) -0.934*** (0.105)

West, non-metro -0.556*** (0.148) -0.621*** (0.159)

South, metro -0.513*** (0.085) -0.933*** (0.094)

N 24,099 16,103

Wald chi-square 1076.51*** 764.67***

Notes: 1) As a model goodness-of-fit test, Wald chi-square test is used. Standard errors are in parentheses. 2) *, **, and *** denote significance at the 10%, 5%, 1% levels, respectively.


Table 3. Decomposition of the Increase in Poverty Rate, 2004-2012

Percentage Share (%)

Estimated poverty rate

2004 9.88 -

2012 13.74 -

Change in the poverty rate 3.86 100.0

Explained 1.36*** 35.2

Unexplained 2.50*** 64.8

Contribution to the change in poverty rate

due to changes in the following variables:

Household living arrangements -0.99*** -25.8

State-level unemployment rate 1.91*** 49.4

Control variables: 11.6

School enrollment 0.12*** 3.0

Age 0.05 1.3

Gender 0.01 0.2

Race/ethnicity 0.30*** 7.8

Residential region -0.03 -0.7

Total contribution of all variables in poverty rate 1.36 35.2

Notes: 1) Share is calculated as a proportion to the observed poverty difference of 3.86% (= 13.74% -9.88%). 2) The second column is the contribution to the poverty rate and the third column is the contribution as a

percent of the change in the poverty rate. For instance, “household living arrangements” contribute -0.99

to the poverty rate, meaning that -25.8% of the total (+3.86) increase in the poverty rate between 2004

and 2012. The percentages are not exact due to rounding. 3) Total contribution of all variables in poverty rate equals to explained part of change in the poverty rate. 4) * p <.05, ** p < .01, and *** p < .001 (two-tailed).

Sources: Data from SIPP (year 2004 and 2012).

Table 4. Detailed Decomposition of the Increase in Poverty Rate by Household Living

Arrangements

Percentage Share (%)

Contribution to the change in poverty rate

due to changes in the following variables:

Household living arrangements: -0.99*** -25.8

Independent living -0.52*** -13.4

Cohabiting with parents -0.48*** -12.5

Cohabiting with relatives -0.00 -0.1

Cohabiting with unmarried partners -0.02** -0.4

Cohabiting with unrelated individuals 0.02 0.6


Notes: 1) The second column is the contribution to the poverty rate and the third column is the contribution as a

percent of the change in the poverty rate. For instance, “independent living” contribute -0.52 to the

poverty rate, meaning that -13.4% of the total (+3.86) increase in the poverty rate between 2004 and

2012. 2) All the five categories in household living arrangements are mutually exclusive. The estimates in the five

categories may not sum to -0.99 due to rounding. 3) * p <.05, ** p < .01, and *** p < .001 (two-tailed).

Sources: Data from SIPP (year 2004 and 2012)

Appendix

Table A1. Definition of Household Living Arrangements

Household Living arrangements Definition

Independent living A living arrangement in which the young adult

is living either alone or with a spouse and/or

natural, adopted, or stepchildren under 18 only

Cohabitation Cohabiting with parents A living arrangement in which the young adult

is living in a household with only family

members and at least one of those family

members is a member of an older generation

(e.g. parents, grandparents, uncles/aunts)

Cohabiting with other relatives A living arrangement in which the young adult

is living with other relatives (e.g.

brothers/sisters, uncles/aunts)

Cohabiting with unmarried

partners

A living arrangement in which the young adult

is living with unmarried partners

Cohabiting with unrelated

individuals

A living arrangement in which the young adult

is living with unrelated individuals

(housemates/roommates, roomers/boarders,

other non-relatives)

Note: Based on Yelowitz (2007).

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