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Health, happiness and parental education

Felix FitzRoy University of St Andrews

Michael Nolan (corresponding author)

University of Hull

Max Steinhardt Hamburg Institute of International Economics (HWWI)

First Draft, Please do not circulate

May 2011

Abstract

Using the German Socio-Economic Panel (GSOEP), we confirm many standard results of

„happiness economics‟, including strong positive effects of health, household income and

education, and the negative effect of reference-group income. In addition, and in contrast to

previous attempts to identify a direct influence of parental education on adult happiness, we

find a highly significant, positive effect of fathers‟ education on male happiness, and mothers‟

education on female happiness, but no cross-gender effects. This is surprising in view of the

widely accepted importance of maternal influence in early childhood. Maternal education is

also related to health, though income and employment have the strongest effects.

JEL classifications: D60, I24, I14

Keywords: Life satisfaction, parental education

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1. Introduction

“It is a well-known fact that the level of parents' education is strongly correlated with the

educational achievement of their children.” (Coneus and Sprietsma, 2009). This of course

implies a strong relationship of parental education with lifetime earnings, job-quality and

other measures of achievement (Francesconi et al, 2005). Recent research has emphasized the

importance of maternal influence in this intergenerational transmission of human capital

(Beller, 2009), and in particular, the time spent by mothers with their children in the decisive,

earliest years (Kalil et al, 2009). Furthermore, as Heckman (2011) and others have

emphasized, family has a vital role in developing the soft skills or non-cognitive, behavioural

characteristics that are just as important as cognitive skills for later achievements and welfare.

In parallel to this extensive literature there has also been rapid growth in research on

subjective well-being in several disciplines, including the economics of happiness and life-

satisfaction, described as a “revolution in economics” by a pioneer in the field (Frey, 2008),

and recently reviewed by Clark et al (2008), Oswald (2010) and others. Family relations,

including marriage and divorce turn out to be crucial for happiness (or unhappiness) in adult

life, but surprisingly, having children seems to reduce self-reported happiness. Even more

surprisingly, there does not seem to have been much direct contact between these two

literatures on differing roles of the family. A natural next step, which we pursue here, is thus

to look for any direct influence of parents‟ education and status on the self-reported health

and happiness of their adult children, after controlling for the effects of education, household

income, relative income and other factors which are important for well-being and strongly

correlated with parental education. Such a direct effect would then suggest that the behaviours

and skills encouraged by better educated parents yield non-pecuniary benefits of subjective

well-being, in addition to the usual measures of achievement such as income.

In a somewhat related approach, Oshio et al (2010) find strong effects of retrospectively

reported family poverty at age 15 on subsequent adult health and happiness, and also find

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poverty at 15 to depend on parents‟ education and status. They estimate a recursive model,

but do not test for any direct influence of parental status on adult health and happiness, (in

addition to the indirect effects via poverty). The two direct tests that we are aware of find no

influence of family on subsequent happiness when the usual controls are included.

Thus Hartog and Oosterbeek (1998) find no significant effect of parents‟ education on health

or happiness in a Dutch sample of about 1900 individuals, when the respondent‟s own

education is included, which is highly significant for explaining both dependent variables.

Winklemann (2006) considers a sample of 640 16-18 year olds in Germany and finds no

effect of living with only one (or neither) parent on happiness. Furthermore, both parents‟

education and household income fail to influence happiness in this youth sample. Mazumber

and Davis (2011) examine US data, and find some strong effects of parental income on child

health and other (objective) measures of well-being.

In the present paper, we start with the German Socio-economic Panel, a large representative

survey that started in 1984, and use the latest, 2008 cross-section of over 17,000 observations.

We extend Layard et al‟s (2010) set of explanatory variables, and confirm the strong negative

effect of relative income on a 10-point scale of subjective life-satisfaction or well-being

(SWB), as well as many standard controls. We have added self – reported health which has

the expected strong positive effect, and we also find that a written survey questionnaire,

instead of a face-to-face interview, significantly reduces reported SWB.

Our main interest is in the effect of mother and father‟s education, and both are highly

significant and positive in the aggregate sample. However when we consider men and women

separately we find a remarkable and unexpected result: only father‟s education remains

significant for men, and only mother‟s education remains significant for women, thus at least

partially contradicting the view that mothers‟ education is generally most important,

particularly in the early, formative years of childhood. When we split the sample into (former)

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West and East Germany, another surprising result emerges: both parents education lose

significance for East Germany, although all other coefficients are very similar between East

and West.

2. Data & descriptive statistics

The data used comes from the German Socio-Economic Panel (GSOEP), which is a

representative micro data set providing detailed information on persons, families and

households in Germany. The GSOEP was started in 1984 and has become a widely used

database for sociologists and economists. A major advantage is the comprehensive nature of

the data set, which combines objective indicators (e.g. income, employment status, family

structure), as well as subjective measures (e.g. life satisfaction, preferences, values). Since

2001, the GSOEP survey further collects retrospective information about childhood (Wagner

et al 2007). In our paper, we make use of the entire 2008 wave of the GSOEP and analyse the

nexus between happiness and parental education based on 17,031 individual observations.

Our dependent variable is an individual`s self-reported life satisfaction which is measured on

an 11 point scale. 0 is the lowest value, while 10 is reported by individuals who are very

satisfied with their actual life. Our main explanatory variables of interest in our analysis are

the mother`s and father`s education of a survey respondent. Based on biographical

information on parental background we code MotherEduc, respectively FatherEduc, as 1 if

the mother, respectively father, of the respondent has either an occupational education or at

least higher secondary education, or both. This comprehensive definition takes into account

the important role of vocational education in the German education system. Tables 1 and 2

show summary statistics of all variables used in the analysis, including our dependent and

main explanatory variables described above. While table 1 shows a breakdown of the sample

by gender, table 2 distinguishes between individuals living in West and East Germany.

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Table 1: Summary Statistics: West vs. East Germany

Overall Men Women Variable Obs Mean Std. Dev. Obs Mean Std. Dev. Obs Mean Std. Dev. Life Satisfaction 17031 6.99 1.74 8115 7.00 1.72 8916 6.98 1.76 Satisfied 17031 0.47 0.50 8115 0.47 0.50 8916 0.47 0.50 Age 17031 50.07 17.43 8115 50.05 17.26 8916 50.09 17.59 Sex 17031 0.52 0.50 8115 0.00 0.00 8916 1.00 0.00 Marriage 17031 0.61 0.49 8115 0.64 0.48 8916 0.58 0.49 Child 17031 0.47 0.50 8115 0.47 0.50 8916 0.47 0.50 Health 17031 0.48 0.50 8115 0.50 0.50 8916 0.46 0.50 Social 17031 0.72 0.45 8115 0.70 0.46 8916 0.73 0.44 Education1 17031 0.43 0.49 8115 0.44 0.50 8916 0.42 0.49 Education2 17031 0.30 0.46 8115 0.27 0.44 8916 0.33 0.47 Education3 17031 0.05 0.22 8115 0.06 0.24 8916 0.04 0.21 Education4 17031 0.22 0.41 8115 0.23 0.42 8916 0.21 0.40 Unemployed 17031 0.06 0.24 8115 0.06 0.23 8916 0.06 0.24 Not_working 17031 0.38 0.49 8115 0.33 0.47 8916 0.43 0.49 Working 17031 0.56 0.50 8115 0.62 0.49 8916 0.51 0.50 HH_income 17031 2842 1896 8115 2936 1904 8916 2756 1884 MeanIncome 17031 2832 739 8115 2928 775 8916 2745 694 MotherEduc 17031 0.58 0.49 8115 0.58 0.49 8916 0.58 0.49 FatherEduc 17031 0.80 0.40 8115 0.81 0.40 8916 0.80 0.40 Placechildhood 17031 0.61 0.49 8115 0.61 0.49 8916 0.61 0.49 Lang_parents 17000 0.09 0.29 8109 0.09 0.29 8891 0.09 0.29 Motherbirth 16477 1931 19.02 7820 1931 18.83 8657 1931 19.20 Interview 17031 0.42 0.49 8115 0.42 0.49 8916 0.41 0.49 Life Satisfaction measures self-reported life satisfaction on a 10-point scale. Satisfied is coded as 1 if the self-reported life satisfaction is larger than 7. Age describes the age of the respondent. Sex is coded as 1 if the respondent is female. Marriage is coded as 1 if the respondent is married and lives together with his/her partner. Child is coded as 1 if at least 1 child is living in the household. Health is coded as 1 if respondent describes his own health status as good or very good. Social is coded as 1 if the respondent undertakes any interactive social activity at least once per week. Education1 is coded as 1 if the respondent has primary school or lower secondary education (Hauptschule). Education2 is coded as 1 if the respondent has higher secondary education (Realschule). Education3 is coded as 1 if the respondent has an advanced technical college certificate (Fachhochschulreife). Education4 is coded a 1 if the individual has a high school diploma (Abitur). Unemployed is a dummy that takes the value 1 if the respondent is registered as unemployed. Not_working is coded as 1 if the respondent is not working but not registered unemployed. Working takes the value 1 if the respondent is working. HH_income measures the net monthly household income of the respondent. MeanIncome measures the average net monthly household income within the skill group (Age (6 categories), Sex, Education (2 categories), Region (East vs. West)) to which the respondent belongs. MotherEducation, respectively FatherEducation, is coded as 1 if the mother, respectively father, of the respondent has either an occupational education or at least higher secondary education, or both. Placechildhood is coded as 1 if the respondent spent his/her childhood within a city. Lang_parents is coded as 1 if at least one parent`s native language is not German. Motherbirth describes the birth year of the mother. Interview is coded as 1 if the interview was carried out using a written questionnaire. Source: GSOEP, 2008

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Table 1 shows no gender differences with respect to life satisfaction although females are on

average less active on the labour market and have a lower household income then men. The

average life satisfaction score is 7 for both men and women, which is fairly high compared to

self-reported life satisfaction in the US (Layard et al, 2010). The regional comparison in table

2 highlights that individuals in Western Germany are more satisfied than those in the New

Laender. This difference might be driven by the well-known regional disparities in

employment and income, which are also reflected in our data. Furthermore, table 2 highlights

distinct regional differences in both own and parental education. In particular, the difference

in maternal education is astonishing. While in Western Germany, 53% of all respondents have

or had a well-educated mother, 69% of the mothers in the East German sample belong to this

category.

Finally, figure 1 highlights the positive association between parental education and self-

reported life satisfaction of adults. Individuals with both parents having no higher education

exhibit the lowest share of respondents with a life satisfaction above average. The largest

share of people with a life satisfaction above 7 is found in the group in which both parents

have either a higher secondary education or a occupational education, or both.

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Figure 1

Table 2: Summary Statistics: West vs. East Germany

Overall West East Variable Obs Mean Std. Dev. Obs Mean Std. Dev. Obs Mean Std. Dev.

Life Satisfaction 17031 6.99 1.74 12484 7.11 1.73 4547 6.64 1.73 Satisfied 17031 0.47 0.50 12484 0.50 0.50 4547 0.38 0.49 Age 17031 50.07 17.43 12484 50.05 17.37 4547 50.13 17.58 Sex 17031 0.52 0.50 12484 0.52 0.50 4547 0.52 0.50 Marriage 17031 0.61 0.49 12484 0.63 0.48 4547 0.56 0.50 Child 17031 0.47 0.50 12484 0.48 0.50 4547 0.44 0.50 Health 17031 0.48 0.50 12484 0.49 0.50 4547 0.46 0.50 Social 17031 0.72 0.45 12484 0.74 0.44 4547 0.66 0.47 Education1 17031 0.43 0.49 12484 0.47 0.50 4547 0.31 0.46 Education2 17031 0.30 0.46 12484 0.25 0.43 4547 0.43 0.50 Education3 17031 0.05 0.22 12484 0.06 0.24 4547 0.03 0.17 Education4 17031 0.22 0.41 12484 0.22 0.41 4547 0.22 0.42 Unemployed 17031 0.06 0.24 12484 0.04 0.20 4547 0.10 0.31 Not_working 17031 0.38 0.49 12484 0.38 0.49 4547 0.37 0.48 Working 17031 0.56 0.50 12484 0.58 0.49 4547 0.52 0.50 HH_income 17031 2842 1896 12484 3033 2023 4547 2318 1361 MeanIncome 17031 2832 739 12484 3025 727 4547 2304 464 MotherEduc 17031 0.58 0.49 12484 0.53 0.50 4547 0.69 0.46 FatherEduc 17031 0.80 0.40 12484 0.78 0.41 4547 0.86 0.34 Placechildhood 17031 0.61 0.49 12484 0.60 0.49 4547 0.62 0.49 Lang_parents 17000 0.09 0.29 12465 0.12 0.33 4535 0.02 0.13 Motherbirth 16477 1931 19.02 12000 1931 18.86 4477 1931 19.46 Interview 17031 0.42 0.49 12484 0.39 0.49 4547 0.50 0.50 Source: GSOEP, 2008. For a description of the variables, see table 1.

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3. Empirical Analysis

To test the influence of parental education on self-reported life satisfaction we estimate the

following model:

(1) XßßH 210 ßFatherEducMotherEducß ,

where H measures self-reported life satisfaction at a 10-point scale, and X is a matrix of

individual covariates including individual characteristics like age, gender, income,

employment status and self-reported health as well as dummies for federal states. The

specification used allows maternal (ß1) and paternal (ß2) education to affect individual life

satisfaction in adulthood directly. At this point, we do not take into account that parental

education already might have influenced life outcomes at earlier stages in the life cycle. In

particular, we would expect that parental education positively affect educational attainment.

For this reason, we will run an additional multivariate probit regression in section X, that

accounts for the recursive structure of life outcomes. Furthermore, our specification does not

control for unobserved characteristics of the respondents and their parents. Therefore, we

cannot rule out that our estimates are driven by unobserved heterogeneity.

Our results in column (1) of table 3 are in line with the main findings of the recent happiness

literature (see Frey (2008), Clark et al (2008), Layard et al. (2010), Oswald (2010)). The

relationship between life-satisfaction and age is characterized by a U-shape profile:

satisfaction with life decreases with age until 50, and increases afterwards. Being married is

positively associated with individual well-being, while respondents with a child in the

household are less happy than the ones without children. The impact of health status,

education and work status is as expected positive. Furthermore, our results highlight the

important role of social interactions and contacts (e.g. sport, friends, and voluntary services).

The effect of absolute household income is around 0.59, but falls to 0.19 when relative

income is introduced. Our findings therefore confirm the importance of income comparisons

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for individual well-being. In addition to this, our results indicate that interview techniques

have a substantial impact on self-reported life satisfaction. In particular, respondents who use

a written survey questionnaire, instead of a face-to-face interview, report significantly lower

individual well-being scores. This finding has considerable implications for cross-country

comparisons and the design of future happiness studies.

The estimates in columns (2), (3) and (4) indicate that parental education has a sustainable,

direct influence on child and youth development that goes beyond inter-generational

transmission of educational attainment. In other words, even after controlling for health and

education of the respondents we find a positive and significant coefficient of both maternal

and paternal education. Including these variables means that education 2, the lowest level to

attain significance without including parental education, then loses significance, in contrast to

the higher education variables. On average, respondents with an educated mother,

respectively father, report a 0.08, respectively 0.10, higher subjective well-being than

individuals without a well-educated mother, respectively father. This means that having a

well-educated parent has half the effect on life-satisfaction as being married. Parental

education therefore appears to have a sizable direct impact on adult life satisfaction, in

addition to indirect effects through education and other earlier life-cycle influences.

By estimating a simple OLS model, we treat life satisfaction scores as cardinal and

comparable across respondents. However, this assumption is sometimes criticised in the

economic literature. We therefore also check robustness with results from an ordered logit

model. The estimates in column (1) in table 4 are qualitatively similar to the ones from our

benchmark specification. This is in line with the findings of Ferrer-i-Carbonell and Frijters

(2004) who demonstrate that the assumptions on cardinality or ordinality of answers to life

satisfaction questions have no substantial impact on the empirical results. Column (2)

provides results from a weighted OLS regression using cross-sectional weights for

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individuals. Our main findings are not affected by this measure, although some coefficients

lose statistical significance.

Table 5 provides estimates from subsamples stratified by gender and region. Columns (1) and

(2) highlight distinct differences between women and men with respect to parental education

and its importance for adult well-being. While the results from the entire sample have

indicated that education of both parents matter for happiness, the subsample regressions point

out that only the education of the parent with the same gender has relevance for individual life

satisfaction. In other words, the mother`s background influences only the well-being of her

daughters, while the father`s background only matters for his sons. We are not aware of any

such results in the literature on happiness, though various other role model effects are well-

known in other fields. Finally, columns (3) and (4) provide interesting insights about regional

differences in well being determinants between individuals between West and East Germany.

In particular, parental education seems to play no role for subjective life satisfaction in East

Germany, though the impact of own education is larger. Furthermore, the negative effect of

written interviews is approximately twice as large as in the West German sample.

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Table 3: Benchmark (1) (2) (3) (4) Age -0.02*** -0.02*** -0.02*** -0.02*** (0.005) (0.005) (0.005) (0.005) Age2 0.0002*** 0.0002*** 0.0002*** 0.0002*** (0.000) (0.000) (0.000) (0.000) Sex 0.03 0.03 0.03 0.03 (0.025) (0.025) (0.025) (0.025) Marriage 0.20*** 0.21*** 0.21*** 0.21*** (0.031) (0.031) (0.031) (0.031) Child -0.22*** -0.21*** -0.21*** -0.21*** (0.029) (0.029) (0.029) (0.029) Health 1.16*** 1.16*** 1.16*** 1.16*** (0.025) (0.025) (0.025) (0.025) Social 0.28*** 0.28*** 0.28*** 0.28*** (0.028) (0.028) (0.028) (0.028) Education2 0.08** 0.05* 0.05* 0.04 (0.031) (0.032) (0.032) (0.032) Education3 0.29*** 0.26*** 0.26*** 0.25*** (0.067) (0.067) (0.067) (0.068) Education4 0.24*** 0.20*** 0.21*** 0.19*** (0.051) (0.052) (0.052) (0.052) Not_working 0.72*** 0.71*** 0.71*** 0.71*** (0.068) (0.068) (0.069) (0.069) Working 0.67*** 0.67*** 0.66*** 0.66*** (0.064) (0.064) (0.064) (0.064) Log HH_income 0.59*** 0.58*** 0.58*** 0.57*** (0.027) (0.027) (0.027) (0.027) Log MeanIncome -0.40*** -0.41*** -0.41*** -0.41*** (0.110) (0.110) (0.110) (0.110) Interview -0.28*** -0.29*** -0.29*** -0.29*** (0.025) (0.025) (0.025) (0.025) MotherEducation 0.11*** 0.08*** (0.028) (0.030) FatherEducation 0.13*** 0.10*** (0.033) (0.036) Observations 17,031 17,031 17,031 17,031 R-squared 0.214 0.214 0.214 0.215 Results from OLS regressions. Dependent variable: Happiness. Controls for federal states are included. Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1

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Table 4: Robustness (1) (2) Ordered

Logit Weighted

OLS

Age -0.03*** -0.03** (0.006) (0.011) Age2 0.0003*** 0.0003*** (0.000) (0.000) Sex 0.05* 0.12** (0.029) (0.048) Marriage 0.24*** 0.22*** (0.036) (0.038) Child -0.25*** -0.17*** (0.034) (0.038) Health 1.39*** 1.24*** (0.031) (0.048) Social 0.30*** 0.30*** (0.032) (0.035) Education2 0.06 0.06 (0.037) (0.042) Education3 0.27*** 0.30*** (0.081) (0.087) Education4 0.21*** 0.17 (0.062) (0.120) Not_working 0.75*** 0.73*** (0.072) (0.111) Working 0.65*** 0.73*** (0.066) (0.077) Log HH_income 0.68*** 0.61*** (0.032) (0.041) Log MeanIncome -0.34** -0.41* (0.132) (0.245) Interview -0.31*** -0.30*** (0.030) (0.054) MotherEducation 0.09*** 0.09** (0.035) (0.041) FatherEducation 0.11*** 0.08* (0.041) (0.046) Observations 17,031 17,031 R-squared 0.216 Pseudo R-squared 0.0661 Log Likelihood -29758 Dependent variable: Life satisfaction. Controls for federal states are included. Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1

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Table 5: Subsamples (1) (2) (3) (4) Men Women West East Age -0.03*** -0.01 -0.01** -0.03*** (0.007) (0.007) (0.006) (0.010) Age2 0.00*** 0.00 0.00*** 0.00* (0.000) (0.000) (0.000) (0.000) Sex 0.04 0.02 (0.029) (0.047) Marriage 0.23*** 0.19*** 0.25*** 0.10* (0.046) (0.043) (0.036) (0.059) Child -0.19*** -0.25*** -0.19*** -0.31*** (0.042) (0.040) (0.033) (0.058) Health 1.13*** 1.18*** 1.21*** 1.00*** (0.035) (0.036) (0.029) (0.049) Social 0.28*** 0.28*** 0.27*** 0.31*** (0.039) (0.040) (0.034) (0.052) Education2 0.03 0.04 0.05 0.04 (0.046) (0.044) (0.037) (0.068) Education3 0.29*** 0.19* 0.21*** 0.44*** (0.094) (0.101) (0.076) (0.149) Education4 0.19** 0.19*** 0.17*** 0.28*** (0.077) (0.071) (0.061) (0.103) Not_working 0.87*** 0.57*** 0.74*** 0.67*** (0.105) (0.090) (0.094) (0.107) Working 0.89*** 0.47*** 0.70*** 0.60*** (0.097) (0.085) (0.089) (0.095) Log HH_income 0.64*** 0.52*** 0.52*** 0.76*** (0.040) (0.037) (0.030) (0.056) Log MeanIncome -0.34** -0.52*** -0.37*** -0.61** (0.168) (0.151) (0.123) (0.258) Interview -0.33*** -0.26*** -0.25*** -0.42*** (0.036) (0.036) (0.030) (0.048) MotherEducation 0.05 0.11*** 0.07** 0.09 (0.042) (0.042) (0.034) (0.063) FatherEducation 0.15*** 0.06 0.12*** 0.02 (0.052) (0.050) (0.040) (0.078) Observations 8,115 8,916 12,484 4,547 R-squared 0.236 0.201 0.203 0.217 Results from OLS regressions. Dependent variable: Life satisfaction. Controls for federal states are included. Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1

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4 Conclusions

The strong direct relationship we find between parental education and life

satisfaction in the presence of many controls does not seem to have been observed

before. The gender restrictions observed are surprising in view of the importance

usually attached to maternal influence on early development of long term

behavioural patterns. The lack of direct parental influence on later life satisfaction

in East Germany may reflect the more pervasive state educational system there,

including pre-school care, but clearly more research is needed to explain these

findings.

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