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Debt Jobs or Housing: What’s Keeping Millennials at Home?

013 period may be leading to extended coresidence with parents for the most recent youthcohorts, and that the challenging youth job markets of the recent recession further obstructedyoung workers’ path to independence.

V. Discussion and Conclusions

This paper investigates young people’s parental coresidence rates in the CCP, and therelationships among coresidence decisions and local house prices, local employment conditions,and the student debt reliance of local college students. Evidence from the CCP shows thatcoresidence with parents has been persistently increasing for 25- and 30-year-olds since 1999,while the number of 25- and 30-year-olds living alone or with more than one non-parent hasdeclined (defining parents as people 15-45 years older than the youth). This trend is corroborated by similar analysis in the CPS. Simultaneously, homeownership has decreased for both agegroups. Both the fraction of individuals who have student debt and those individuals’ average balances have steadily increased over the same period.Panel estimates relying on geographic variation in economic conditions at the zip code-,county-, and state-level reveal mixed effects of local economic growth on young Americans’ propensity to live independently. While a one percentage point drop in state youthunemployment is estimated to increase the two-year rate of moving away from parents by 0.2 percentage points, a one standard deviation increase in house price gains over the two year period increases the probability that an independent youth moves home by 0.37 percentage points. On net, then, it appears to be not the overall strength of the local economy, but therelative circumstances of youth labor markets and goods markets where middle-aged parentstend to live and where independent youth tend to live, that shapes the trend in coresidence with parents.Finally, we find that a high state-level student loan balance per college graduate among ayoung person’s cohort both significantly increases the rate at which independent young peopletransition to living with their parents and significantly slows the rate at which dependent youthtransition away from their parents. Estimates indicate that a $10,000 increase in average studentdebt among a youth’s state cohort leads to a 0.81 percentage point increase in the likelihood ofmoving home to parents, and to a 2.63 percentage point

decrease

in the likelihood of moving outof one’s parents’ household. Given that student debt has been increasing since 1999, this

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Debt Jobs or Housing: What’s Keeping Millennials at Home?

30in the probability of leaving home. The intuition behind this relationship is straightforward, asindependent living is costly, and typically demands a stable income source. Moreover, the problem of mechanical endogeneity arising from location choices is particularly weak in thiscase, as youth unemployment is measured at the state level, so that in order to influence theunemployment calculation the youth would have to cross state borders.Student loans are, once again, estimated to encourage coresidence with parents. The Table 4,column (4), student loan coefficient is large, negative, and highly significant. It indicates that a$10,000 increase in average student debt per graduate in the youth’s state-cohort decreases the probability of moving out of her parent’s home over the two years by 2.63 percentage points.The student loan estimate is not sensitive to the inclusion of the state-cohort graduation rate,which, perhaps surprisingly, is estimated to be strongly negatively associated with moving awayfrom home.

As before, the aggregated state-cohort student debt reliance is purged of features ofthe individual student’s situation, or her parents’ level of supportiveness. As before, given thestate fixed effects included in the estimation, the effect of state-cohort student debt is identifiedusing variation between cohorts in a given state in student debt reliance, and to the specificationaccounts for time-fixed regional variation in degree of support for youth and education.Again, total unemployment and house prices can be taken as indicators of broader economicconditions, this time in the parent’s location. Here we find very modest estimates of the effect oflocal economic conditions on youths’ propensity to leave home, with modest and insignificantcoefficients on changes in county total unemployment, county median income, and zip codehouse prices over the period. This may be the net result of ambivalent effects of strengtheninglocal economic conditions on youths’ capacity for independence. While strengthening economicconditions may improve the ability of youth to secure employment and fund independenthouseholds, and of parents to bankroll moves away from home, strengthening local conditionsmay also give rise to increasing local prices, particularly housing prices, which encouragecontinued coresidence.In sum, estimates from the model of the flow away from parents paint a picture ofstagnation in response to weakening labor market opportunities and growing student debt burdens. They provide evidence that the escalating student debt we’ve observed over the 2003-

Recall that the combination of stock and flow model estimates reflect that state-cohorts with higher graduationrates move away from parents considerably more slowly, and also experience less churning in their locations

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Debt Jobs or Housing: What’s Keeping Millennials at Home?

increases prices, particularly house prices, and these increased prices drive the youth home to her parents.The reverse causality generated mechanically by the shifting populations in this case worksagainst our finding a positive effect of house prices on moving home, implying that this pointestimate of a 0.011 percentage point increase in the rate of moving home for every one percentincrease in local house prices over the January 2000 base prices is a lower bound estimate of thetrue effect. Further, the extent of this reverse causality problem may be large given that house prices are measured at the zip code level, and many young people may cross zip codes to returnto parents. Note that the 0.011 percentage point increase is reasonably substantial when oneconsiders the magnitude of the swings in house prices over the period. As noted, the standarddeviation of the zip code-level house price index over the period in our sample is 44.7.

Theaverage homeowner in the CCP experienced roughly a 50 percentage point increase in house price over the boom, and roughly a 25 percentage point decrease over the housing market bust.Additional variation in these experiences at the regional level enhances the effect of house priceson coresidence with parents estimated for this sample.On the other hand, the reverse causality problem actually works toward finding a spuriousnegative effect of total unemployment on moving in with parents, as unemployed youth leavingthe county at higher rates exert negative pressure on the unemployment coefficient. Further, thetotal unemployment coefficient becomes smaller and insignificant with the inclusion of income,graduation rate, and student debt. Together these mechanical endogeneity concerns lead us toinfer a substantial positive effect of housing costs in the independent location on the odds that achild moves home to parents, and a modest, possibly insignificant negative effect of both totalunemployment and youth unemployment in the independent location on moves home.The estimates in column (4) demonstrate a significantly higher rate of moving home instates with higher debt cost of a college degree in the youth’s graduating cohort. An increase of$10,000 in the debt cost of a degree is associated with a 0.8 percentage point increase in the probability of an independent young resident of the state moving home over the course of twoyears.

This effect is robust to controlling for the share of college graduates among the youth’s

Our effect is about twice the size of that estimated by Dettling and Hsu (2014), who study the effect of individual-level student debt on parental coresidence. Two factors may contribute to the difference in estimates. First, Dettlingand Hsu’s population is individuals age 18 to 30, which will lead their independent youth sample to be older thanours (since the likelihood of living with ones’ parents substantially decreases in age) and thus perhaps less sensitive

29cohort in the state, which, unsurprisingly, is associated with a lower propensity to move home.

These estimates provide further, and perhaps more credible, evidence of a positive effect ofgrowing student deb ...

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Debt Jobs or Housing: What’s Keeping Millennials at Home?

test the robustness of our student debt estimate by instrumenting student debt per graduate withthe four-year average of state education spending when the individual was age 18-21. Thisinstrument is extremely powerful, with a first-stage F-statistic of over 100,000, and plausiblyaffects parental coresidence through the intensive margin alone, particularly when considered atthe aggregate level. Two-stage least squares estimates of the model are presented in column (8)of Table 2; the estimated coefficient on student debt per graduate is nearly double its un-instrumented value and is highly statistically significant, suggesting that the extensive marginwas indeed biasing the effect of student debt on parental coresidence downward.

b. Flow home to parents from independent living

Table 3 reports the coefficient estimates for the moving home model in expression (2). Therelevant scales of measurement are as follows: The dependent variable is set to 100 for a youthwho moves and 0 for a youth who does not. Unemployment measures and the graduation rateamong current 24 year olds in the state, similarly, range from 0 to 100. Recall that the CoreLogichouse price index takes a value of 100 in January 2000 for each zip code, and hence measuresgrowth in house prices relative to January 2000.Our preferred specification appears in column (4) of Table 3. Here we find that an increasein local house prices has a positive and highly significant effect on the probability that the youngadult moves home. In fact, we estimate that a one standard deviation increase in the house pricechange over the two years leads to a 0.37 percentage point increase in the probability of a youthmoving home over two years. Further, looking across the Table 3 specifications, we see that thehouse price coefficient is particularly robust to the inclusion (or exclusion) of other regressors,such as local income, student debt reliance, and graduation rate.Total unemployment and the local house price index, taken together, provide a measureof the strength of local demand. As demand increases in the youth’s independent location, thatlocation’s total unemployment decreases and its house prices increase. We observe a negative, insome cases significant, coefficient on total unemployment and a positive and consistentlysignificant coefficient on house price index in the moving home regression. Together, theseresults suggest that strengthening local demand conditions in the youth’s independent locationincrease the likelihood that the youth moves back home. One interpretation of these results isthat, conditional on the youth labor market, stronger demand in the youth’s independent location

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Debt Jobs or Housing: What’s Keeping Millennials at Home?

coresidence among 25-year-olds.

Beginning with the red line, which depicts the predictedcoresidence rates from the baseline regression with time-varying characteristics, we fixcharacteristics at their 2000 (2003) levels, adding fixed characteristics in the order: totalunemployment, youth unemployment, house price index, household income, student debt pergraduate, and, finally, graduation rate. The top panel shows that changes in the overallunemployment rate, household income, and graduation rate have only very modest associationswith the rate of parental coresidence. The bottom panel of Figure 8 shows the additive proportionof the variation of parental coresidence that the stock model attributes to each covariate; itsuggests that house prices accounted for roughly 20% of the increase during the mid-2000s,while youth unemployment accounted for as much as 25% of the increase during the GreatRecession. However, student debt per graduate claims the largest share of the increase,accounting for as much as 50% of the increase in the likelihood of a young person’s living with parents.One challenge to the interpretation of the relationship between student debt per graduateand the rate of parental coresidence presented above is the possible existence of a secularunobserved trend in parental coresidence, perhaps related to a cultural change regarding young people’s living with their parents. If there exists such a secular cultural trend, then the correlation between parental coresidence and student debt per graduate (which has increased steadily,though at a slightly decreasing rate, every year on average across states) may be incidental. Wetest this conservative hypothesis by including a national linear time trend in our stockspecification, shown in column (6) of Table 2. Including a time trend attenuates all of theestimated coefficients, including the coefficient on student debt per graduate, but the student debtestimate remains positive and statistically significant at the 1% level, and both the youthunemployment rate and the house price index also maintain their positive and statisticallysignificant coefficients at the 10% level. Figure 9 shows a decomposition of these conservativeestimates, suggesting that, conditional on a secular cultural trend unrelated to student debt,student debt only explains about 10% of the increase in parental coresidence since 2004, withanother 10% being explained by house prices during the mid-2000s. An alternative specificationincluding year dummies instead of a linear time trend, a more flexible control for unobserved

Note that student debt is first measured in our data in 2003, and hence we delay the student debt and graduation baselines until data permit the addition of the student debt control. The estimates include an indicator for missingeducation measures, which is set to one during the earliest years of the sample.

26national culture shocks, yields very similar results. However, given that student debt is measuredat the state level (implying that, at the individual level, it is measured with extreme imprecision),this model is extremel ...

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Debt Jobs or Housing: What’s Keeping Millennials at Home?

increases the unemployment measures in the origin. Assuming movers are more likely to beunemployed than the population of young people overall, this mechanical source of endogeneitycould bias coefficients on the unemployment measures downward. Of course, to the extent thatthe unemployment measure responds with a lag rather than contemporaneously, the estimateswill not be biased. This seems to be a likely possibility. Further, this source of reverse causalityof youth residence choices is not a concern if moves to and from parents’ households all occurwithin the relevant location. For example, to the extent that all moves home or away occur withinthe same county, no unemployment coefficient will be affected.Assuming youth in our model influence the housing market as well, a similar type of reversecausality could affect the coefficients on house prices. Assuming that a child living in a parent’s basement does not lead the parent to demand more housing, the departure of a youth who lives athome has no effect on house prices. Hence we are less concerned about the effect of reversecausality on the house price coefficient in the moving out regression. A youth who has beenliving independently and returns home, however, leaves the origin housing market and thereforedecreases total housing demand in the origin. As each youth in the moving home regressionexerts this influence, this source of mechanical reverse causality could bias the estimatedcoefficient on house prices in the moving-home regression downward. As in the case ofunemployment, to the extent that the resulting effects on house prices appear with a lag, or thatmoves between parent and independent youth locations fail to cross locations, this is not aconcern. However, house prices in the estimation are measured at the zip code level, and so it isreasonably likely that youth moving back home will cross zip code lines and exert spuriousdownward pressure on house price effects in the moving-home regression.Standard endogeneity concerns deriving from observable and unobservable individual andlocal characteristics that are fixed over the two year window are accounted for by the transitionapproach we take to estimation. Obvious examples include child ability, parent generosity, and persistent regional characteristics. Remaining major concerns regarding the endogeneity ofchanges in local characteristics to youths’ transitions home and away seem most likely to arisefrom third factors determining both changes in local characteristics from

1 and youths’interest in living with parents. An immediate example is changing local economic conditions.Their effect is likely to be picked up by some combination of total employment and house pricemeasures. Given this, we interpret total employment and house price coefficients as though they

24contain both direct effects of employment and house prices, and indirect effects of localeconomic conditions. So far we have not found that this changes our inferences based on theestimates substantially. Concerns regarding third factors influencing local levels of student debtamong recent graduates are more relevant, and we discuss them along with the model results inthe following section, providing first-pass instrumental analysis to allay these concerns.

...

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Endogeneity concerns in the flow models

The most obvious endogeneity concerns in the context of our broader youth co-residencequestion involve individual student debt. Were we to estimate expressions (2) and (3) usingindividual student debt, the debt the young person has accumulated, and has not yet repaid,would presumably be endogenous to parental co-residence for a host of reasons. First, whether ayoung person is currently accumulating or paying down student debt presumably reflectsmeasured and unmeasured aspects of the youth’s broader financial and life circumstances, andthese, in turn, influence co-residence. Second, the literature has documented substantialheterogeneity in parents’ financial generosity.

At the individual level, parental generosity mayact as a third factor, determining both parental contributions for college, hence student debt, and parents’ willingness to house their adult children. Third, individual heterogeneity in features suchas debt-aversion, risk tolerance, and diligence may drive both the level or change in individualstudent debt and the decision to move home or away. Finally, individual ability and educationalattainment are likely both to be correlated with the student debt level and to influence co-residence with parents.Given the many sources of endogeneity of individual student loan level and growth to youthresidence outcomes, we estimate the dependence of co-residence with parents on student debt by proxying for student debt with the mean student debt cost of a degree in the youth’s state-cohort,as described above. We estimate both flow models including state fixed effects, and hence thecoefficient on state-cohort student debt is identified by changes across cohorts within a state inthe mean debt price of a degree. Such differences are relatively free of confounding familycharacteristics like generosity and debt aversion, and instead are influenced by changes (withinstate) from cohort to cohort in factors including tuition at state colleges and the generosity offederal, state, and institution-level grant and loan aid.

One possible concern regarding reverse causality arises from the individual youth’sinfluence on labor and housing markets in the location she leaves, should she decide to move. Ayouth who moves away from one location to another, if unemployed, can be expected todecrease the total and youth unemployment rates in the original location. If employed, she

Brown, Scholz, and Seshadri (2012), McGarry and Schoeni (1995).

Note that we control for state economic conditions that might otherwise appear in the mean state-cohort studentdebt price of a degree through youth unemployment, total unemployment, and house prices

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a. Stock of young people living with parents

Figure 7 shows that the trend in 25-year-old parental coresidence appears more similar tothe trend in student debt than to unemployment rates or the house price index at the nationallevel, but does not capture geographic variation in these relationships or allow us to weigh therelative contributions of each feature of the environment to a young person’s residence choice.As a first, descriptive, step, we estimate a model of the likelihood that, at a given time, a child isliving with his or her parents as a function of local socioeconomic conditions. In anticipation ofthe flow model to come, we consider individuals at two ages, 23 and 25. Define

as anindicator for whether individual

living in location

at time

coresides with her parents. Wemodel the likelihood that an individual lives with her parents as a function of the conditions inher locality one year earlier, including fixed effects by state to control for unobserved differencesin culture and policy.

We thus estimate the following linear probability model:

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Debt Jobs or Housing: What’s Keeping Millennials at Home?

18independence, that we observe for recent cohorts of young adults. Motivated by this potential inthe CCP, and by the questions raised by the relationships among the national trends, in thefollowing section we present an empirical model of parental coresidence. First, we describe alagged stock model explaining the revealed coresidence decisions of 23- and 25-year-olds as afunction of local unemployment, youth unemployment, house prices, and student debt per recentgraduate, a linear decomposition of which provides a simplified visualization of the conditionsassociated with parental coresidence. Then, to account for differences in the economiccharacteristics of regions where young people live alone, and where their parents live, weseparately model the flows of young CCP consumers into and out of parents’ households overtime as a function of changes in the economic and social conditions of young consumers’ initiallocations.

III. Empirical model

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aged 18-30, based on our own calculations in the CPS, followed a similar modest decline in the boom and then increased even more sharply, from 6.8 percent in late 2006 to a maximum of 14.8 percent in early 2010. Its recent recovery involves a decline from 14.8 percent at its 2010maximum to 11.3 percent in the end of 2012. The monthly CoreLogic house price index, hererepresented by the purple line, increased from a normalized value of 100 in January 2000 to a peak of 200 in 2006, fell to a 2011 trough of 134, and since then has moved through an unsteadyrecovery to reach 165 by late 2013. In sum, while aggregate student debts have followed a steep,unbroken upward trajectory since 2003, both employment and house prices have experienced a pronounced boom, bust, and recovery.One question, then, is to what degree the residence choices of the young track the recent, pronounced business cycle. To the extent that they move with the boom and bust, residencechoices may appear to be driven by economic conditions, such as youth labor markets and thecost of housing. To the extent that their changes are gradual and persist throughout the boom, bust, and recovery, however, they may appear to be driven instead by young consumers’ recent,unprecedented accumulation of student debt.In Figure 7, as before, the upward trend in coresidence with parents appears steady, andsuggests little direct relationship to broad economic indicators such as unemployment measuresand the house price index. This would seem to suggest that the decision to stay home with parents, or to move back in, relates more closely to the recent changes in the debt burden ofhigher education than to swings in youth labor markets and the cost of housing.However, the analysis presented in Figure 7 is unsophisticated, and, as such, poses morequestions than it resolves. In terms of the aggregate trends, the steady increase in coresidencewith parents may reflect not a failure to respond to aggregate conditions, but offsetting effects of,for example, job and housing markets on residence decisions among the young. The failure of allyouth residence decisions to reflect the recent recovery in employment and house prices remainsa mystery.Finally, these aggregate trends, while informative, may mask evolving local relationshipsamong housing cost, labor markets, and youth residence choices. The fine geographic data andlong panel of the CCP allow us to exploit time variation in local economic conditions and studentdebt reliance to learn more about the contributions of jobs, housing costs, and student debt at thelocal level to the decisive aggregate trends toward parents, and away from economic

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