Leaving home and poverty among youth : A cross-European analysis Arnstein Aassve, Maria Iacovou Stefano Mazzuco Maria A. Davia

Outline  Motivation  What is youth?  How do we define poverty?  Literature: what do we know?  Data: ECHP  Descriptive analysis  Welfare regimes  Empirical approach: PSM  Results  Conclusions

Motivation   Leaving the parental home, are all crucial life events contributing to the vulnerability of youth.   Large discrepancies across European countries in terms of the extent to which leaving home is associated with poverty   We use data from the ECHP and propensity score matching   and find that the event of leaving home does have an impact on entering poverty.   The strongest effect for Scandinavian countries, weakest among Mediterranean countries.

What is youth?  UN and EU: yrs  ESRC: 15-25, JRF  Here we conceptualise “youth” as a process of transition to adulthood:  in many countries these transitions have hardly begun by mid-20s.  Italy: median age at leaving home for men is 30.  Netherlands: mean age at first birth for women is 29.  Define three subgroups: 16-19, 20-24,

How do we define poverty? How we use the ECHP to compute household income and poverty rates: To compute household equivalent income in year t, we use income data pertaining to year t collected at year t + 1, summing this over all the individuals present in the household at year t and using an equivalence scale based on the numbers and ages of individuals present at year t (Heuberger, 2003). How we define poverty: poor households net equivalised household income income is below 60% of the median in the country

Literature: what do we know?   Eurostat (2002): the incomes of young people below age 24 are below national averages.   Cantó-Sánchez and Mercader-Prats (1999) : youth poverty due to temporary jobs.   Pavis, Platt and Hubbard (2000) key role of education   Smeeding et al (1999) and Berthoud and Robson (2003): single parenthood in Anglo-Saxon nations   Magadi et al (2005) : timing of first birth   Aassve et al (2005) : Employment, marriage, and cohabitation is associated VERSUS independent living having children and being without work are all associated with higher poverty risk.

The data: ECHP  Waves 1994 – 2001  UK, Ireland, Denmark, Finland, Netherlands, Belgium, France, Germany, Austria, Italy, Greece, Spain and Portugal  Several problems with the ECHP  But is reasonably good for comparative analysis.

What the data initially tell us: poverty rates are much higher away from parents

Welfare regime typology (Esping-Andersen+)  “Social-democratic”  (Denmark, Finland, Netherlands)  “Liberal”  (UK and Ireland)  “Corporatist” (Conservative)  France, Germany, Austria, Belgium  “Southern” (Residual)  Portugal, Italy, Spain, Greece

Empirical approach: PSM   WHY PROPENSITY SCORE MATCHING?   the leaving home event cannot be considered exogenous with respect to household income and therefore poverty  Average treatment effect on the treated (ATT): For those leaving home: The effect on entering poverty from leaving home.  Average treatment effect on the control (ATC): For those staying at home: The effect on entering poverty if they did leave home instead of staying behind

Empirical approach: PSM (II)   matching methods yield an unbiased estimate of the average impact of leaving home on treated   Algorithm: Nearest Neighbour Matching with a caliper of 0.01 (& radius for consistency checks)   psmatch2 module in STATA (Leuven and Sianesi 2003)

“Average Treatment Effect on Treated” is defined as: ATT=E(Y 1i | D i =1)-E(Y 0i | D i =1) (2) In (2) Y 1 is the potential outcome (entering poverty in our case) in the case the individual i receive treatment (here leaving home) and Y 0 is the potential outcome in the case the individual i does not receive the treatment (stay in the parental home). Thus E(Y 1i | D i =1) is observable whereas E(Y 0 | D i =1) is not, but an approximation is created through the matching. A naïve estimator of (2) would be: ATT=E(Y 1i | D i =1)-E(Y 0i | D i =0) But this assumes no selection bias. In order to remove the selection bias we implement the matching procedure. This is based on the critical assumption (CIA) that Y 0 independent of D| X States that treatment status is random conditional on some set of X

If CIA holds then bias depends only on observed variables. Under this assumption, E X (Y 0i | X i, D i =0) = E X (Y 0i | X i, D i =1), thus the ATT can be unbiasedly estimated by: ATT= E X (Y 1i - Y 0i | X i, D i =1) = E X (Y 1i | X i, D i =1) -E X (Y 0i | X i, D i =0). “Average Treatment Effect on Controls” (ATC) defined as ATC=E(Y1i| Di=0)-E(Y0i| Di=0) (3) In (3) we observe E(Y0i| Di=0) but not E(Y1i| Di=0), which has to be approximated via matching. Under the assumption of homogeneous treatment effect ATT and ATC should give the same results. But they are rarely homogenous. In our setting, for instance, we can hypothesise that young adults staying at home do so because they are aware of being highly at risk of entering poverty in the case they leave.

Composition of the sample

Selection equation: probability of leaving home  Year of the interview  Age in the moment of the interview  Gender  Number of siblings  Household income  Personal income from work  Whether the individual is a student  Whether the individual is inactive  Education attainment  Working status of mother and father  Education attainment of mother and father  Parental house is short of space

Results from matching: In the majority of countries we find ATT being lower than ATC. Poverty risk is an important reason for delaying the transition out of the parental home. Youths tend to delay leaving home because they their chances of entering poverty are higher if they leave. But for those who leave, their risk is smaller than for those who decide to stay behind in the parental home if they had left.

Results from matching: (II) For people under 25 there is a negative link between the propensity to become poor if youth leaves and the propensity to leave home (Belgium), except for Denmark and Finland, where those who leave have actually a lower probability of becoming poor if they leave than those who stay (if they left)

Results from matching: In the majority of countries we find ATT being lower than ATC. Poverty risk is an important reason for delaying the transition out of the parental home. Youths tend to delay leaving home because they their chances of entering poverty are higher if they leave. But for those who leave, their risk is smaller than for those who decide to stay behind in the parental home if they had left.

Results from matching: (II) This negative link between poverty risk and the probability of leaving home is no longer visible for those over 25 years old

Results from matching: The economic incentives to stay at home or to leave home are less and less pronounced with age, to the point that in some southern countries, women over 30 would face a lower risk of poverty if they left their parents than if they stay. By staying they may be showing a decision of supporting their parents, and not of being supported.

Results from matching: (II) There is no link between differential risk of poverty and exit from parental home amongst adults

Conclusions The higher risk of poverty amongst those who have left home in Scandinavian countries are corroborated in this dynamic perspective The elder the youth, the lower is the risk of poverty deterring the decision to leave home. Youths, regardless the poverty rates they face if they leave, tend to be rational: in those countries where youths who do not leave home would experience a higher poverty risk if they left than those who actually leave, the exit rates are really low, whereas in the Scandinavian countries this difference is negligible. It is rational to stay, and it is rational to leave: those who leave face a higher risk of poverty but, at the same time, are better sheltered from poverty than those who stay.