THE IMPACT OF HOUSING ON THE WELLBEING OF CHILDREN AND YOUNG ADULTS

David Blau, Nancy Haskell, and Donald Haurin

Department of Economics

Ohio State University

Funded by the MacArthur Foundation

MOTIVATION There is substantial interest in knowing which

factors affect child outcomes The inputs and mechanisms are numerous

Parental time inputs (quantity and quality) Resources received by the child (parental and

public) Family structure and composition The child’s home environment

Homeownership, crowding, quality of the home The child’s neighborhood environment

Most of these factors have been studied separately, but there are few/no studies of them all together

This knowledge is important for targeting public policy

SPECIFIC RESEARCH QUESTIONS

Do child and young adult outcomes depend on (controlling for other factors):The quality/quantity of housing a child is

exposed to (includes crowding and home environment)?

Whether the parents were renters or owners of the child’s dwelling?

BLAU & HAURIN’S RECENT STUDY: WHAT ROLE DO HOUSE PRICES PLAY IN CHILD OUTCOMES?

House prices (rents and owner-occupied prices) affect many household behaviors Quantity of housing consumed Own or rent the dwelling Annual savings Choice of neighborhood Family members’ labor supply Family structure: marriage and divorce, fertility Expenditures on goods

In response to capital gains on housing Residual income left after expenditures on rents or

annual costs of owning

In general, there is no specific prediction of the effect on children of house price variations in a reduced form model

B&H’S FINDINGS FROM THE REDUCED FORM MODEL ON THE EFFECT OF HOUSE PRICES

Higher house prices are associated with reduced math cognition in U.S. children (ages 6-14) The impact was stronger for

Hispanics Child being age 6-10 Very low mother’s aptitude test score

However, there are no effects of either owner-occupied or rental house price variations on children’s reading cognition or behavioral problems.

There are only a few significant effects of house prices on young adult outcomes. For example, if house prices are higher then: Youths’ wages are lower Being on welfare and convictions are lower

LITERATURE ON HOUSING AND CHILDREN

Hypothesized transmission mechanisms Crowding (Goux & Maurin-2005; Lien, Wu, Lin-

2008)—affects children’s ability to study, stress level, illness, more secondary cigarette smoke Multifamily buildings—have less play space Lot size effects not studied

Home environment (Parcel & Menaghan-1994; Todd & Wolpin 2003)—affects child cognition

Homeownership (Green & White-1997; Haurin, Parcel, Haurin 2003)-results in better parenting skills and self-esteem, abatement of lead paint

House quality—generally not studied Location—many studies of neighborhood

effects and school quality

GAPS IN THE LITERATURE The best known studies that find that

homeownership in the U.S. has a positive effect on child outcomes do NOT control for crowding or dwelling quality

The best known studies that control for parental inputs and other factors at best control for only the home environment

It is not clear which house characteristics have significant effects on children and young adults—important for policy targeting

Very little is known about issues related to the importance of the timing of housing inputs (i.e. when during childhood) and the impact of varying durations of exposure over a child’s life.

OUR PANEL DATA SOURCES

Parental data: National Longitudinal Survey of Youth: 1979-2008: only the women’s children are interviewedChild data: NLSY Child Supplements:

1986-2008 (we focus on 5 child outcomes)Young adult data: NLSY Young Adult

Supplements: 1994-2008 (focus on 8 outcomes)

House characteristics dataConfidential addresses from NLSY survey

data were matched to publicly available data sources that described house characteristics (e.g. Zillow)

HOUSE CHARACTERISTIC DATA

The housing data: (single family dwellings only) house & lot size bedrooms, total rooms structure type, structure age, and a quality measure “walkability” score = a measure of the nearness of

urban amenities. We created crowding measures (bedrooms/HH

size, square feet/HH size) NLSY reports whether HH owns or rents Survey has a measure of the internal home

environment (HOME scale), which can be separated into 3 components Cognitive stimulation Emotional support Quality of home’s interior

HOUSE CHARACTERISTIC DATA

We undertook a factor analysis and determined the set of house characteristics could be summarized in three factors Factor 1: house size and quality: mostly a

combination of square footage, number of rooms, crowdedness, and house quality

Factor 2: mostly a function of a combination of lot size, building age, neighborhood walkability.Factor 2 is large when lot size is small,

walkability is high, and dwelling age is high. (= typical U.S. urban housing)

Factor 3 is composed of the three components of the HOME scale, which we enter separately in the child outcome regressions

DYNAMIC MODEL-CHILD OUTCOMES Households maximize utility, subject to

an income constraint and parental time constraints. Child quality (q) is assumed to enter their utility function. It is produced with parent’s time (T), housing (H), other purchased goods and services (G), and it is influenced by other family demographics (X). We assume a “value-added” form for the child production function, μi is a “fixed effect.”

qit = θ0 + θ1Tmit + θ2Tfit + θ3Git + θ4Hit + θ5Xit + θ6qit-1 + μi + ηit + εit

ESTIMATION NOTESqit = θ0 + θ1Tmit + θ2Tfit + θ3Git + θ4Hit + θ5Xit + θ6qit-1 + μi + ηit + εit

The parameters are not age specific qit-1 summarizes the effects of all inputs prior to t,

there are no lagged effects of inputs Our set of X is quite large, reducing omitted

variable bias We try fixed effect specifications for

mothers (there are multiple children of one mother in the sample), thus controlling for omitted family background characteristics

the child (panel data), thus controlling for omitted child characteristics

Unobserved factors that vary over time require an instrumental variables approach, using Ivs for the housing factors (have owners’ price, renters’ price, and a gender composition IV). Not successful thus dropped

DEPENDENT VARIABLES: CHILD OUTCOMES

Child outcomes include PIAT Math score (cognition)2 PIAT Reading scores (cognition)Behavioral Problems Index (BPI)Body-Mass Index (BMI)—obesity

YOUNG ADULT OUTCOMES The young adult outcomes are a “one-

time” outcome, not a panel (no fixed effects).

We use OLS and the child’s history of the explanatory variables)High School Degree by Age 20Bachelors Degree by Age 25Ever Convicted by Age 20Ever Received Welfare by Age 20Average Log Wages After 21 Pregnant by Age 16Have children by Age 20

EXPLANATORY VARIABLES

Focal explanatory variables: Housing Factors 1 and 2, whether the household is a Homeowner, and the home quality index (a scale based on interviewer observations of whether: the play area is safe, the home is not cluttered, the

home is not dark/monotonous, the home is clean, and the building is safe.)

Control variables: Child’s age, sex, birth order Mother’s age, race, ethnicity, marital status (6

categories), AFQT (a measure of the mother’s ability or achievement), hours worked,

House is in a central city, the number of children in each of six age-sex categories (0-4, 5-11, 12-17).

ADDITIONAL EXPLANATORY VARIABLES THAT WERE TRIED

House structure type (single family, mobile home, condominium, multi-family)

Mother’s intervention in the family (used one)Participate in school activitiesKnows child’s friend’s namesKnows where child is most of the time

Quality of school index (mother’s opinion)

Proxies for expenditures on material inputs to childHousehold incomeNon-housing wealth

CHILD RESULTS (MOTHER F.E.)VARIABLES PIAT MATH READING REC READING COMP BEH PROB BODY MASS

lag_dept varb 0.27461887*** 0.48013235*** 0.26352014*** 0.24732933*** 0.37565680***

[0.013] [0.011] [0.017] [0.013] [0.017]

housing factor1 1.91584998** 1.38465432 1.91181299* -1.17387450* 0.08442946

[0.878] [0.847] [1.063] [0.682] [0.110]

housing factor2 1.30953140 0.59743950 -0.34802214 -0.16802484 -0.10408320

[0.808] [0.829] [1.141] [0.935] [0.143]

homeowner -1.18601630 0.01012311 -1.52589159 -0.48271750 0.10310215

[1.133] [1.120] [1.416] [1.046] [0.127]

interior home quality 0.00029664 0.00976363 0.02838968 -0.00888335 -0.00087736

[0.013] [0.013] [0.021] [0.012] [0.002]

home cog stim 0.05089811*** 0.03019980** 0.08454151*** -0.05347597*** 0.00085698

[0.012] [0.012] [0.013] [0.011] [0.002]

home emot support 0.00139261 -0.00580990 -0.00150006 -0.03727128*** 0.00160339

[0.012] [0.009] [0.012] [0.011] [0.002]

net worth 0.09956260 0.07045479 0.07358633 0.15667478 -0.04406942

[0.149] [0.135] [0.144] [0.146] [0.027]

income 0.17080029 -0.20118281 -0.03172373 -0.29521786 0.00751192

[0.227] [0.230] [0.259] [0.193] [0.025]

Observations 11,054 10,974 8,697 12,400 11,574

R-squared 0.0954 0.2644 0.1615 0.0839 0.3860

Number of kids 2433 2,427 2,309 2,568 2,506

CHILD OUTCOMES (SUMMARY)

The house size/quality/uncrowding factor has a significant positive effect on children’s math cognition and reading comprehension. It reduces behavioral problems.

The following variables have no effect on any child outcome The housing factor indicating small lots and high

walkability Interior home quality

The home being high in cognitive stimulation improves all outcomes except BMI

High emotional support reduces behavioral problems

Other significant variables (in general): male child, birth order, Black, Hispanic, number of

children, mom’s age, AFQT, married

YOUTH OUTCOMES (OLS)VARIABLES HS Degree BA Degree Convicted On Welfare Log Wage Pregant by 19

housing factor1 -0.03788258** 0.06838333** 0.01736281 0.02933567* -0.02694682 0.01583792

[0.017] [0.033] [0.014] [0.016] [0.029] [0.017]

housing factor2 -0.01716931 -0.02865617 0.00964459 0.03009287** 0.00399769 0.01145463

[0.013] [0.029] [0.011] [0.012] [0.020] [0.017]

Homeowner 0.11402392*** 0.10949539*** -0.03802355** -0.06868457*** -0.01474056 -0.06963596**

[0.030] [0.034] [0.018] [0.021] [0.025] [0.029]

interior home quality -0.00002127 -0.00049265 -0.00040877 -0.00013866 -0.00006564 -0.00007412

[0.001] [0.000] [0.001] [0.001] [0.001] [0.001]

home cog stim 0.00111811*** 0.00111393** 0.00020210 -0.00100931** 0.00074637** -0.00001562

[0.000] [0.000] [0.000] [0.000] [0.000] [0.000]

home emot support 0.00061711 0.00026059 -0.00080578** -0.00023589 0.00130253*** -0.00045550

[0.000] [0.000] [0.000] [0.000] [0.000] [0.000]

net worth 0.00472583 0.02913522** -0.00960662*** -0.00312635 0.01957024** -0.00914060

[0.004] [0.012] [0.003] [0.005] [0.009] [0.007]

income 0.00564729*** 0.00520138** 0.00077820 -0.00436415*** 0.00595574*** -0.00231852*

[0.001] [0.002] [0.001] [0.001] [0.002] [0.001]

Observations 4,304 2,006 5,395 4,516 3,110 2,625

R-squared 0.1587 0.2504 0.1124 0.2111 0.1453 0.2504

YOUTH OUTCOMES (SUMMARY)

The homeownership variable Increases the likelihood of High School and College degrees Reduces convictions, pregnancy, and being on welfare

The house size/quality/uncrowding factor has a significant positive effect on college degree. It increases being on welfare (?)

The following variables have no/little effect on any child outcome The housing urban location factor Interior home quality

The home being high in cognitive stimulation improves degrees and wages

High emotional support improves wages and reduces convictions

Other significant variables (in general): Net worth, income, male child, birth order, Black, Hispanic,

AFQT, married

COMPARISON OF CHILD AND YOUTH OUTCOMES

House size and the lack of crowding appears to be the most influential on child outcomes, but not on youth outcomes

Homeownership appears to be most influential on youth outcomes, but not child cognition or behavior This result stands up even if child outcomes

are included in the youth regression An example: outcome = get a BA degree

Factor 1 has a direct positive effect Factor 1 increases PIAT Math, which has a direct a

positive effect on getting a BA Factor 1 decreases behavior problems, which has

a direct positive effect of getting a BA

WHAT ARE THE RELEVANT HOUSING POLICIES?

U.S. housing policy has had various emphasis over the past 60 years Early policies - provide public housing, thus

achieving an “acceptable” standard of quality Successful in some cases, but not cost efficient

1970s and early 1980s - provide housing vouchers. Again the focus was primarily on housing improving quality. More success than public housing, but mostly rentals

U.S. housing policy, primarily in the 1990s and 2000s, was to encourage homeownership by reduce credit constraints introduce risk based pricing of mortgages allow mortgage interest and property taxes to be

deducted from federal income taxes set targets for minority/low income mortgage lending for

the Government Sponsored Enterprises.

POLICY IMPLICATIONS OF OUR RESULTS

Our results suggest support for both improving housing quality/quantity, reduced crowding, and increasing homeownership if the goal is to improve child and young adult outcomes.

However, our previous research suggested that it is NOT effective to generically subsidize either rents or the price of owner-occupied housing because there are too many other behavioral responses Don’t subsidize large lot suburban homes Establish housing quality targets & reduce

crowding (preferably in owner-occupancy) Encourage ownership of the property