Disadvantage among Australian Young Mothersceebi.curtin.edu.au/local/docs/B4_-_2006Bradbury.pdf · Disadvantage among Australian Young Mothers ... young motherhood is a strong signal

147AUTHORS

Title

Disadvantage among AustralianYoung Mothers

Bruce Bradbury*, University of New South Wales

AbstractYoung mothers are one of the most disadvantaged groups in Australian society. Thispaper documents this disadvantage and shows how the relative disadvantage of youngmothers has increased over time.

Almost all teenage mothers and most mothers in their early 20s are reliantupon income support payments and both groups have low levels of education. By thetime they are in their early 30s, women who were young mothers are less likely to bepartnered, if partnered are more likely to have a low-income partner, and are lesslikely to be purchasing their own home. This concentration of disadvantage hasincreased over the last 20 years.

The main reasons for this disadvantage lie in the factors that determine fertilityat young ages rather than via the effect of young motherhood per se. Nonetheless,young motherhood is a strong signal of disadvantage, which could be used in theappropriate targeting of support services to disadvantaged mothers and their children.

IntroductionYoung mothers, and by extension their children, are among the most socio-economicallydisadvantaged groups in Australian society. Currently, there are around 11-12,000children born to teenage mothers in Australia every year. This birth rate is much lowerthan the rate three decades ago, and the Australian teenage birth rate is now relativelylow compared to other English-speaking countries, but higher than most non-Englishspeaking OECD countries.1 In addition to teenagers, however, the much larger groupof women who have their first child in their early 20s also experience significantdisadvantage.

*Bruce Bradbury, Social Policy Research Centre, University of New South [email protected]: This paper is based on research funded by the Department of Families,Community Services and Indigenous Affairs (FaCSIA). Valuable comments have been receivedfrom officers of this Department and two anonymous referees. Among other data sources, thispaper uses confidentialised unit record data from the Household, Income and Labour Dynamics inAustralia (HILDA) survey. This survey was initiated and is funded by FaCSIA and is managed bythe Melbourne Institute of Applied Economic and Social Research (MIAESR). The findings andviews reported in this paper, however, are those of the author and should not be attributed to eitherFaCSIA or the MIAESR.1 In 1998 the teenage birth rate was 18.4 per 1,000 compared to 52.1 in the US, 30.8 in the UK,20.2 in Canada, 13.1 in Germany, 9.3 in France, 6.5 in Sweden and 4.6 in Japan (UNICEF, 2001).© The Centre for Labour Market Research, 2006

147AUSTRALIAN JOURNAL OF LABOUR ECONOMICS

Vol. 9, No. 2, June 2006, pp 147 - 171

148AUSTRALIAN JOURNAL OF LABOUR ECONOMICSJUNE 2006

The main focus of this paper is on the socio-economic circumstances of womenand their families in the years after they become a young mother (e.g. when aged 30).This provides an indicator of the likely life-long living standards of these women andan indication of the economic conditions under which their children will be raised.However, the strong associations shown below should not necessarily be interpretedas implying that young motherhood causes disadvantage. An association between socio-economic outcomes and young motherhood can also arise from the fact that womenfrom a disadvantaged background are more likely to have their children when youngand are also more likely to be disadvantaged later on.

The policy implications of these two causal mechanisms are quite different. Ifyoung motherhood causes poor socio-economic outcomes then this supports policyinterventions to discourage early childbirth. Indeed in this case, providing direct supportto young mothers may be (partly) counter-productive if it also increases their fertility.An explanation deriving from socio-economic background, on the other hand, providesjustification for using young motherhood as an identifier to flag those families most inneed of additional support.

The socio-economic determinants of young motherhoodSeveral explanations have been advanced to explain the impact of socio-economicbackground on age at first birth.

Many women with poor labour market prospects, it is argued, will decide tobecome a mother as part of their pathway to adult status. Welfare culture theory suggeststhat this occurs via disadvantage leading to changed attitudes that in turn lead tobehavioural deviations from mainstream status attainment paths. Others argue that theattitudes of these women are not that different, but that having children provides apath to adult status, with this being particularly attractive to disadvantaged womenwho lack alternative opportunities via the labour market ( Stewart, 2003). Geronimus(1997), argues that poor labour market prospects, poor life expectancy and opportunitiesfor kin support make early childbearing a rational choice for black women in the US.

The opportunities in the labour market faced by young women are heavilyinfluenced by their educational attainment, and so education (or anticipated educationalattainment) is likely to be a strong influence on fertility. Indeed, human capital theorysuggests that education and fertility will be jointly determined based on the marginalbenefits to each form of behaviour (both financial and status benefits). Geronimus(1997), for example, argues that US minority women do not have the same returns toeducation as do white women and so early fertility is not as costly for them. Policiesthat increase returns to education as well as policies that increase returns to employmentare thus both likely to lead decreases in young fertility rates.

Both welfare culture theory and human capital theory have been used toprovide motivation for the US Personal Responsibility and Work Reconciliation actof 1996, which sought to reduce lone parenthood and associated young motherhood.Whether welfare incentives are responsible for young motherhood remainscontroversial,2 but there is some evidence that policy changes in the USA that haverequired young mothers to live with their parents and stay in school have decreasedfertility (Lopoo and DeLeire, 2005).2 See Haveman et al (1997) and Wolfe, Wilson and Haveman (2001).

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Disadvantage among Australian Young Mothers

In addition to these cultural and economic factors influencing young women’sdecision-making, other commentators have focussed more directly on the constraintson fertility control. In Australia, Taylor (1986, p. 389) has noted that ‘there is littleevidence for systematic planning to become mothers’ among young women whobecome pregnant.

This is a common finding in research in this area (Thompson, 2005). Ratherthan being a result of rational decision-making, (many cases of) young motherhoodmay reflect an inability to make such decisions. Socio-economic variations in youngmotherhood may be due to social class variations in knowledge of contraception, controlover relationships (e.g. with respect to unwanted sex) and the social and economicresources required to seek out and undertake abortions (particularly urban/ruraldifferences, Evans, 2002).

If reducing young motherhood is desired, these different explanations imply acorresponding range of options for policy intervention. Reducing the economicincentives for young childbearing might include increasing employment opportunities,restrictions on income support and increasing the returns to further education. Sinceemployment opportunities are better for women with higher education, policies thatincrease early educational attainment might also act to reduce fertility in the immediateyears following.

The explanations based on fertility control, on the other hand, suggest thatpolicies that manage to increase young women’s ability to control their fertility willhave a larger impact. The large fall in teenage pregnancy numbers after the legalisationof abortion in the early 1970’s (Figure 1 below) might be seen as an example of thistype of policy intervention.

The impact of young motherhoodThe desirability of reducing teenage fertility, however, rests on whether women whohave their first child when young would necessarily have had better socio-economicoutcomes if they had delayed their childrearing (or if their children would have hadbetter outcomes). Indeed, from a physiological perspective, having a child at 18 or 19may be better than having one at 35 (UNICEF, 2001). To the extent to whichdisadvantages flow from the event of being a young mother, these are most likely toarise in the socio-economic sphere.

One way to estimate the impact of young motherhood, while controlling forthe influence of difficult to measure social background characteristics, has been to usemiscarriages as an identifying instrument.3 Using this method, Hotz, Mullin and Sanders(1997) found that women in the US who had their children when below the age of 18actually did better financially than comparable women who had their children later inlife. The researchers speculated that the reason for this might be that teenage mothersachieve a more uninterrupted spell of on-the-job experience when they do enter theworkforce, than if they had had their children at a later age. Because teenage motherstend to come from disadvantaged backgrounds, this on-the-job experience is worth

3 Other approaches have also been used to capture unobservable background characteristics, thoughthese have more limitations than the miscarriage-based studies. These include comparisons ofsiblings and the use of cross-state policy variation as instruments (see Hoffman, 1998 and Holmlund,2005, for recent surveys).


more than any educational opportunities they might lose as a result of becoming mothersas teenagers.

Ermisch and Pevalin (2003), undertook a similar analysis using data from theBritish 1970 Cohort Study (BCS70). Compared to matched women who hadmiscarriages as teenagers, they also found that there was little adverse impact of havinggiven birth as a teenager on a woman’s qualifications, employment or pay by the timeshe reached 30 years of age. However, they also found evidence that these 30-year-oldwomen were less likely to be homeowners, and that their partners were more likely tobe unemployed and to have no educational qualifications beyond the age of 16. Theysummarise this by speculating that being a teen mother makes it harder for women todo well in the ‘marriage market’. (This result was not found in the US study).

Corresponding research has also been undertaken using Australian data fromthe Australian Longitudinal Study on Women’ Health (ALSWH) (Bradbury, 2006).This suggests that most of the association between young motherhood and latereconomic outcomes is due to unobserved background factors rather than any directcausal link. However, there is some evidence that having a young birth reduces theprobability of being legally married (though not being partnered per se), and increasesthe probability of being a lone parent at around age 30. These results may be due toyoung motherhood leading to mothers being less likely to be living with the father oftheir children. These results are broadly in line with the UK results to the extent thatthe main effects seem to be operating via partnering patterns.

The changing characteristics of young mothers in AustraliaThe objective of this paper is primarily descriptive, to show the socio-economiccircumstances of young mothers and to show how this has been changing over time.The next section of the paper examines the characteristics of Australian young mothersaround the year 2001. Section 3 then goes on to examine the longer-term outcomes ofmothers who are currently aged in their early 30s, but who had their first child whenyoung. This analysis takes advantage of the disaggregation by single year of ageavailable in the RADL version of the Census 1 per cent Household Sample File (HSF).Section 4 compares these patterns with the patterns of disadvantage found 20 yearspreviously (the 1981 Census 1 per cent HSF has single-year age data in the publicaccess file). For teenage mothers, in particular, the concentration of disadvantage hasincreased over time. The concluding section of the paper discusses the implications ofthe associations shown here for policy targeting.

2. The characteristics of young mothers in AustraliaThe past 80 years have seen dramatic changes in the fertility rates of Australian women.Figure 1 shows these rates for selected age ranges. Among teenagers, the birth ratereached its highest point in the early 1970s, at 54.5 births per annum per 1000 women.Subsequent years saw a rapid and then a steady drop in fertility, reaching 17.4 in 2002.For those aged 20-24, the peak birth rate years were about 10 years earlier followed byan even more rapid fall in fertility. Fertility has also decreased in the 25-29 age range,with the 30-34 age group now the modal age category giving birth in Australia.

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Figure 1 - Births per 1000 women 1921-2002 in selected age groups

Source: ABS Australian Historical Population Statistics – 4. Births, Cat No. 3105.0.65.001, 2004.

For the younger groups, the main reasons for the drop in fertility were probablythe legalisation of abortion in 1973, together with the growing importance of educationand labour market participation for young women.

Using birth register data, the ABS estimates that in 2003 there were around10,700 teenage confinements and 35,900 confinements among women aged 20-24.4

About 70 per cent of the teenage births were to women aged 18 or 19.Since most statistics on the characteristics of young mothers are based on the

stock of young mothers, it is useful to understand how these flow estimates (the numberof women entering young motherhood within a year) translate into estimates of the stockof young mothers (those who are young mothers at any given point in time). On the onehand, the stock of young mothers will be higher because a woman giving birth whenaged 17 might appear in the stock of teenage mothers over three years. On the otherhand, the skewed nature of the age distribution means that the stock could, in principle atleast, be lower than the annual flow. For example, if all teenage births occurred at the ageof 19.5 years, then the stock estimate would be only half that of the flow estimate.5

4 Alternative estimates of confinements from the national perinatal data collection are slightlyhigher, (in 2001, 12,400 and 38,700 respectively) possibly because of delays in birth registrationsABS, Births 2003, Cat No. 3301.0.5 To see this relationship, consider an example where all births occur to women wo are precisely19.5 years old, and there is one birth per month. The inflow is thus 12 births per annum and eachmother is a teenage mother for only 6 months. At any point in time the stock of teenage motherswill comprise all those who had a birth in previous 6 months, that is, a stock of 6 teenage mothers.In general, in a steady-state, the stock is equal to the inflow (1 birth/month in this example) timesthe duration (6 months of being a teenage mother). Other factors which reduce the duration ofyoung motherhood will also reduce the stock, but not change the inflow. These might includesome children born to teenagers being adopted out to non-teenage adoptive parents or being placedin the custody of fathers.


In the Commonwealth Department of Family, Community Services andIndigenous Affairs (FaCSIA) One per cent Longitudinal Data Set (1% LDS) therewere around 15,400 mothers aged under 20 receiving Family Tax Benefit in March2003. Another 91,300 were aged 20 to 24.6 These numbers are broadly consistent withthe flow statistics.

Table 1 - Characteristics of young mothers in 2001

Age

<20 20-24

% of each age group

Aboriginal or Torres Strait IslanderNo (including not stated) 88 94Yes 12 6

Social marital statusMarried in a registered marriage 13 33Married in a defacto marriage 37 28Not married 49 39

Highest level of schooling completedStill at school < <Did not go to school, Year 8 or below 4 2Year 9 or equivalent 20 9Year 10 or equivalent 39 30Year 11 or equivalent 13 18Year 12 or equivalent 16 38Not stated 4 4

Current student statusNon-student 84 89Student 16 11

Household typeOne family household 86 92Two and three family households 14 8

Housing tenureOwner/purchaser 17 27Rent: Housing authority or community 8 13Other renter 68 53Other incl not stated 7 6

Total 100 100Population estimate 9,900 83,300

Source: ABS 2001 Census, 1% Household Sample File, Expanded version.Notes: Young mothers are defined as women aged 15-24 living in private dwellings, whose‘relationship in household’ was coded as husband, wife, de-facto partner or lone parent, andwhose family type was coded as a couple or lone parent family with children under 15 years.Overseas visitors and people whose relationship or family type could not be coded are excluded.The symbol ‘<‘ denotes cells based on 1-3 cases in the sample file. The sample size is 1% of thepopulation estimte shown in the last row.

Puzzlingly, estimates from the 2001 Census 1% Household Sample File aremuch lower. In this data set, young mothers can be identified as women aged 15-246 This will be a slight underestimate of the stock of young mothers, as high income families, thosewhere the father is receiving the FTB, or where the FTB is taken via the tax system are not counted.However, for these age groups, we would expect these other groups to be small.

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who are the head (or the spouse of the head) of a family that includes children underage 15. Because the Census coding only permits one parent-child nucleus per family,this should also identify mothers who are living with their parents.

This definition excludes women living in non-private dwellings, overseasvisitors, people whose relationship or family type could not be coded and mothers notliving with their children on census night. Nonetheless, it is still surprising that thiscalculation only yields estimates of 9,900 and 83,300 mothers aged 15-19 and 20-24respectively.7

The most likely explanation for this discrepancy stems from problems in theCensus family relationship coding in multi-family households. Only a small fractionof young mothers are identified in the Census as living in multi-family households –ie with their parents (Table 1). It may be that many of the children in such householdsare being erroneously coded as children of their grandparents. On the other hand, thiscould also be explained if many of the young mothers were not living with their childrenon census night, which might occur if the grandparents were the main carers of thechildren.

Of the young mothers identified in the Census, 12 per cent of the teenagersgroup, and 6 per cent of those aged 20-24 identified themselves as Aboriginal or TorresStrait Islander. Both fractions are much higher than their prevalence in the population.8

About half of the younger group and 60 per cent of the older group were living with apartner (though bear in mind the data limitations described above). Only 16 per centof the younger group had finished year 12, compared to 38 per cent of the older group.

Of those who were identified in the Census as being young mothers, mostwere living in their own household. About two-thirds of the younger group were inhouseholds renting privately, though 27 per cent of the older group were living inowner/purchaser households. (The young mother herself might not have been thepurchaser). Very few were living in housing authority or community sector housing.

A multivariate analysis has been undertaken examining the association of age,education, indigenous status, birthplace and religion with the probability that a womanaged 15-24 is living with her child on Census night (detailed results available from theauthor). Apart from education, these can be considered exogenous variables (and theimpact of young motherhood on education levels is probably very weak, see Bradbury,2006).

The associations with indigenous status and education continue even whencontrolling for the other variables. For the disaggregation of birthplaces available inthe Census 1% Household Sample File (expanded version)9, three birthplace groupsstand out as having high probabilities of young motherhood; Lebanon, Western Europe(excl. UK Germany and the Netherlands) and the remainder of the Middle East.Birthplaces with lower rates of young motherhood are Hong Kong and the groupingIndonesia, Singapore, East Timor and Brunei. Though these differences are statistically7 This is from the expanded file (available via the ABS RADL system). The basic version of thefile (an independent 1% sample) yields estimates a few hundred higher.8 ABS, Births 2003, Cat No. 3301.0 documents the much higher fertility rates at lower ages amongAboriginal women. 9 See ABS Cat 2037.0, 2001 for the available categories. These detailed categories are only availablein the expanded file – accessed via the ABS RADL system.


significant, it should be noted that the sample sizes in many birthplace groups are verysmall. None of these associations are statistically significant when controlling for theother variables (particularly religion).

Figure 2 - Percentage of parents aged under 25 by SEIFA index ofdisadvantage: SLAs with >500 parents, 2001

Source: 2001 Census. Each circle represents an SLA, with the circle area in proportion to the SLApopulation.

In general, religion appears to be a better predictor of young fertility thanbirthplace. Compared to women who described their religion as ‘no religion’, thosewith a religion of Buddhism, Catholic, Greek Orthodox and Uniting Church had lowerodds of being a young mother, while Islamic women had a higher likelihood. Controllingfor birthplace and the other variables, only the Greek Orthodox and Islamic religionsremained significantly different.

In interpreting these patterns, it is relevant to draw upon the results of Robsonand Berthoud (2003) who compared outcomes for young mothers from differentbirthplace groups in the UK. There, as in Australia, some ethnic/religious groups havea much higher prevalence of young motherhood (in the UK, this is mainly women

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from South Asia). Robson and Berthoud conclude, however, that in those ethnic groupswhere young motherhood is common, young mothers do not have outcomes any worsethan those of the ethnic group as a whole. The 1% Census file contains too few casesto investigate this issue in Australia.

In general, young parents tend to live in more socially disadvantaged regions.Figure 2 shows the correlation between the proportion of parents who are aged under25 with the ABS SIEFA Index of Disadvantage across statistical local areas. The areaswith the extremely high young parenthood rates are generally rural regions in NorthernAustralia with large Aboriginal populations. The large outliers at the bottom left withlower than expected rates of young motherhood are urban areas in Sydney andMelbourne with high proportions of people whose religion is Buddhist or ChristianOrthodox.

Figure 3 - Mothers receiving family tax benefit in March 2003: Proportionreceiving different forms of income support by age

Source: Calculated from the FaCS 1% LDS (release to March 2003).Notes: Population is women receiving some FAL, FAH, FBH or FBL as at 7/03/2003 and with atleast one FTB eligible child aged under 16. Benefit categories are defined using the followingLDS payment codes. Disability/illness: DSP or SKA. Unemployment/training: NSA, YAL, AUS,NMA. Partner: PTA, CAR, WFA, WFD, PGL, PGP, PGN, PGY. Lone parent: PPS, WID, WDA,BVA.

Turning from Census to income support data, Figure 3 presents informationon the income support characteristics of mothers receiving Family Tax Benefit in March2003 (using the 1% LDS). Almost 9 in 10 teenage mothers were receiving incomesupport payments, mainly lone parent payments (Parenting Payment Single). Amongmothers aged 20-24, around 7 in 10 were receiving income support payments.

Note that a much higher proportion of young mothers were receiving lone


parent payment than were defined as being lone parents in the Census. This couldeither be due to the fact that the Census misses many young mothers living with theirparents (most of these would be receiving lone parent payments) or because the partnerrelationships identified in the Census are not treated as partner relationships in theincome support system (e.g. because of their transitory nature).

3. Longer-Term Outcomes2001 Census outcomesTo what extent does the socio-economic disadvantage associated with youngmotherhood persist into later life? In the expanded version of the 2001 CensusHousehold Sample File10 it is possible to compare the ages of mothers and childrenliving in the same household to calculate the mother’s age at first birth. We focus onmothers aged in their early 30s, as this is an age when many socio-economiccharacteristics are evident, but most children are still living at home with their mother.11

The age at first birth distribution is shown in Table 2. Of mothers aged in their early30s, 8.5 per cent were under 20 when they had their first birth and 30.6 per cent aged20 to 24.

Table 2 - Mothers Aged 30-34 in 2001: Apparent Age at Birth of First Child

Age at Birth of First Child Percent Number

<20 8.5 36,50020-24 30.6 130,70025-29 41.3 176,50030-34 19.7 84,100Total 100.0 427,800

Source: ABS Census 1% Household Sample File (Expanded version).Notes: The population for the table is women aged 30 to 34 who have at least one non-step childaged under 18 present in their (co-resident) family, and who do not have any children aged under15 temporarily absent from their family. Age at birth of first child is defined as the current age ofthe woman minus the age of the oldest child present. Note that in a small number of cases whereolder children have left the household, the woman’s age at birth may be erroneously coded to anolder age group (based on the mother’s age at the birth of a younger child) or the woman mightbe excluded from the table altogether (if there are no children remaining).

To assess the accuracy of this identification of former young mothers, we cancompare the number of women with apparent teenage first births with the teenagebirth numbers in the 1980s. If Table 2 has accurately identified all the women whowere teenage mothers, then it should show the number of teenage mothers as equal toapproximately 5 times the average number of teenage first births during the period1982 to 1990 (ignoring mortality and migration).12 Though we don’t have precise data10 The standard file only has age information in 5-year groupings.11 The family relationship coding problems identified in the previous section are unlikely to applyto women in this age group.12 For example, women aged 30 in 2001 were aged 19 in 1990, 18 in 1989 and so on. First births towomen aged 19 in 1990, 18 in 1989 and so on would contribute to the count of teenage birthsaccruing to 30-year olds in Table 3. Similarly for women aged 31 in 2001 etc. If birth rates at eachage were constant across the window, this would equal 5 times the per-annum rate of teenage firstbirths.

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on this, it is likely that there were about 11,000 first births to teenagers per annumduring this period13 – implying a total of 55,000 rather than the 36,500 shown in thetable.

Another source of comparison data is the first wave of the Household Incomeand Labour Dynamics in Australia (HILDA) survey, conducted in 2001. A similarcalculation using this data yields an estimate of 56,000 women aged 30-34 who hadbeen teenage mothers – similar to the estimate based on birth data but about 50 percent higher than the estimate derived from the Census. In this case, the estimate isprobably too high, as the HILDA data also includes women with step children in thehousehold. However, the combination of the birth data and HILDA comparisons doessuggest that the Census does not identify all the women who had been teenage mothers.

There are several possible reasons for this underestimation. Excluded fromTable 2 are households where there was a child temporarily absent on Census night, aswell as households where the Census form was not fully completed. (The HILDA dataare based on whether children usually live in the household). In addition, if a first-born child had left the household then the mother would either be excluded from thetable or classified according to her age at birth of her next child. This is most likely atthe upper end of the (mother’s) age range. For example, if a woman was aged 34, andhad her first child when aged 17, then the child will be aged 17 in 2001 and may haveleft the household. If the HILDA calculation is made excluding children living outsidethe household, the count of women who had been teenage mothers falls to 49,000,suggesting that children leaving the household explain between one-third and one-half of the observed discrepancy. The remainder of the gap appears to be due to childrentemporarily absent and households with incomplete Census forms.

It is not clear what impact these exclusions will have on the comparisonsbetween women with different ages at first birth shown below. Older children wholeave home are more likely to be from socially disadvantaged groups, and so theirabsence from the data will probably attenuate the differences between the mother’sage at birth groups. Children being temporarily absent and households with incompleteforms will be more evenly spread across the different age groups, and so their absenceprobably has less of an impact on the comparisons. (Unfortunately we cannot use theHILDA data directly, as the sample size is insufficient. Only 65 women aged 30 to 34had their apparent first child when a teenager).

In the next section, we use a slightly lower age range for mothers and observea higher number of women who were teenage mothers (approximately 44,000 in Table10 compared to 36,500 in Table 2). Nonetheless, the patterns shown there across ageat birth groups are quite similar to those shown in this section.

Table 3 shows the education level of these women in the Census, and Table 4their labour force status. Education is very strongly associated with age at first birth,with almost a quarter of the mothers who were teenage mothers not completing year10 (compared to only 2.4 per cent for those whose first birth was in their 30s).Correspondingly, only 2.3 per cent of the teenage mothers (and 5.5 per cent of those20-24 at first birth) had a degree or higher.13 ABS Cat No. 3301.0, 2003 issue, records 13,873 teenage births in 1988. For nuptial births, about80% of these were first births (ex-nuptial data is not available). This suggests there were about11,100 first births per annum.


Table 3 - Education level of mothers aged 30-34 in 2001 by apparent age atbirth of first child

Mother’s age at birth of first child (%)

Highest education level <20 20-24 25-29 30-34Under year 10 23.6 11.3 4.4 2.4Year 10 50.1 43.8 31.2 21.0Year 12 10.2 19.6 22.6 22.4Certificate or diploma 13.7 19.8 24.3 23.6Degree or higher 2.3 5.5 17.5 30.5Total 100.0 100.0 100.0 100.0(% not reported) (6.0) (1.8) (1.1) (1.0)

Source: ABS Census 1% Household Sample File (Expanded version).Notes: See notes to Table 2 for population and age at birth definition.

Table 4 - Labour force status of mothers aged 30-34 in 2001 by apparent ageat birth of first child


Labour force status <20 20-24 25-29 30-34Employed 41.8 53.2 55.8 52.3Unemployed 8.5 5.8 3.1 1.4Not in the labour force 49.7 41.0 41.2 46.2Total 100.0 100.0 100.0 100.0(% not reported) (3.0) (0.6) (0.6) (0.5)

Source:ABS Census 1% Household Sample File (Expanded version).Notes: See notes to Table 2 for population and age at birth definition.

Table 5 - Marital status of mothers aged 30-34 in 2001 by apparent age atbirth of first child

Mother’s age at birth of first child

Marital status <20 20-24 25-29 30-34Married 51.5 64.1 80.2 84.9Defacto marriage 11.0 12.7 6.3 7.5Single 37.5 23.2 13.5 7Total 100.0 100.0 100.0 100.0

Source: ABS Census 1% Household Sample File (Expanded version).Notes: See notes to table 2 for population and age at birth definition.

Table 6 - Education level of partners of mothers aged 30-34 in 2001 byapparent age at birth of first child


Highest education level of partner <20 20-24 25-29 30-34Under year 10 18.9 12.4 5.1 2.1Year 10 31.1 26.3 20.5 14.0Year 12 10.4 14.0 15.0 16.4Certificate or diploma 35.4 39.5 42.2 39.6Degree or higher 4.2 7.9 17.2 27.8Total 100.0 100.0 100.0 100.0

Source: ABS Census 1% Household Sample File (Expanded version).Notes: Includes both married and defacto partners. See notes to table 2 for population and age atbirth definition.

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The association with employment status is not as marked. Though the latterbirth mothers had higher qualifications, they were also more likely to have youngchildren in the household when they were aged 30-34. The highest employment rate isfound among those who had their first birth when aged 25-29 (55.8 per cent) and thelowest among the teenage mothers (41.8 per cent).

Figure 4 - Personal incomes of mothers aged 30-34 in 2001 by apparent ageat birth of first child

Source: ABS Census 1% Household Sample File (Expanded version).Notes: The figure shows the cumulative income distribution for each birth age group. That is, thevertical axis shows the percentage of mothers with incomes less than each given income level. Forexample, median incomes are the income levels (on the bottom axis) where the 50% line intersectsthe cumulative income distribution. See notes to table 2 for population and age at birth definition.

Figure 4 shows the cumulative personal income distribution for women ineach of the different age at first birth groups. This figure shows the proportion ofwomen with income below each income point, and so lines that are further to the rightin the figure indicate a higher income. The incomes of the women who had their firstbirth at a younger age are generally more concentrated in the middle of the incomedistribution (the cumulative distribution curve is steeper at middle incomes). Thisreflects the combination of a higher employment rate (because their children are older)but a lower wage rate (associated with lower education).

The implication of this is that up until the about 75th percentile ($500pw), theyounger birth age women have higher incomes (their curves lie to the right of thosefor older birth age women). After this point, however, the older first birth women havehigher incomes.

For most mothers in this age group, a key determinant of their living standardis the income of other household members – particularly their spouse. Table 5 shows


marital status across these birthplace groups. Those women who were younger at theirfirst birth are much more likely to be single in their early 30s than those with later firstbirths. This may be more a timing issue than an indicator of average marital statusover their lives. That is, partnered women are more likely to have children and thereare also lower separation rates among couples with young children in the household(Bradbury and Norris, 2005).

Among those who were partnered at the time of the Census, Table 6 shows theeducation level of their partner, and Table 7 their partner’s employment status. Theeducation patterns are similar to those for the mothers themselves, with much highereducation levels among the partners of the mothers who were older at first birth. Labourforce differences are more dramatic for fathers than for mothers, as men typicallydon’t reduce their employment when there are young children in the household. Amongthe partnered women who had their first child in their early 30s, 95 per cent hademployed husbands. Among those who had a teenage birth, only 78 per cent hademployed husbands.

The income implications of these differences are shown in Figure 5. For fathers,there are large income differences according to their wife’s age at first birth. For menwhose wife had just had her first child (the dotted line), the median income was around$870. For those whose wife had her first child as a teenager, the median income wasonly $550. At the lower end of the income distribution, only 10 per cent of men witha recent first child had incomes below $400 per week, compared to almost 30 per centamong men with teenage first-birth partners.14 This association of young motherhoodwith lower-income husbands could arise for two reasons. It might be due to youngmotherhood having a direct impact on success in the ‘marriage market’ (as found inthe UK by Ermisch and Pevalin, 2003). Alternatively (or in addition) it could be dueto assortative mating, whereby people from similar social backgrounds tend to partnerwith each other.

Table 7 - Labour force status of partners of mothers aged 30-34 in 2001 byapparent age at birth of first child


Labour force status of partner <20 20-24 25-29 30-34Employed 78.3 86.2 92.6 95.4Unemployed 8.6 5.1 2.8 2.5Not in the labour force 13.1 8.6 4.5 2.1Total 100.0 100.0 100.0 100.0(% not reported) (1.3) (0.3) (0.2) (0.4)

Source: ABS Census 1% Household Sample File (Expanded version).Notes: Includes both married and defacto partners. See notes to Table 2 for population and age atbirth definition.

All the associations described above work together to influence the wealthholdings of mothers in their early 30s. This is evident in housing tenure patterns, asshown in Table 8. Over three-quarters of mothers with their first birth in their 30swere owners or purchasers of their dwelling. This can be compared with only 42 percent among those who had been teenage mothers.14 A small part of these differences might arise from age differences in the husbands, even thoughwives’ ages are held constant at 30-34.

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Figure 5 - Incomes of partners of mothers aged 30-34 in 2001 by apparent ageat birth of first child

Source: ABS Census 1% Household Sample File (Expanded version).Notes: See notes to Figure 4.

Table 8 - Housing tenure of mothers aged 30-34 in 2001 by apparent age atbirth of first child


Housing tenure <20 20-24 25-29 30-34Owner/purchaser 41.6 59.8 71.5 77.0Renter 55.9 37.0 25.3 20.8Other 2.5 3.3 3.2 2.3Total 100.0 100.0 100.0 100.0(% not reported) (2.5) (1.7) (1.3) (1.0)Average housing costs ($/week) 149.7 159.7 161.2 184.4

Source: ABS Census 1% Household Sample File (Expanded version).Notes: See notes to table 2 for population and age at birth definition.

Long-term income support receiptAs noted in the previous section, in 2003, almost 90 per cent of mothers aged under 20and receiving Family Tax Benefit were receiving income support payments. The rateof income support receipt was also high among mothers aged 20-24, at 70 per cent.What are the longer-term patterns of income support receipt?

Table 9 shows the probability that a woman with a young child and receivinga parenting income support payment in 1996 was also receiving income supportpayment some seven years later (though many will have had intermediate periodswhen not receiving income support). Overall, two-thirds of these mothers were receiving


income support payments seven years later (i.e. when the relevant child was between7 and 12 years old, though there might be other children in the family as well). Therate of income support receipt was highest for mothers who were teenagers in 1996(79 per cent compared to under 70 per cent for the other age groups). Across the olderages, there are slightly lower rates among those initially aged 25-34 (compared tothose younger and older) but the difference is not large (3-5 percentage points).

Table 9 - Women with at least one child under age 6 and receiving parentingincome support in March 1996: Percentage receiving income support sevenyears later

Age in Percentage receiving income supportMarch 1996 Population estimate in March 2003

Partnered Lone parent Partnered Lone parent All

15-19 4,200 10,200 81 78 7920-24 20,800 37,400 58 76 6925-29 35,800 42,200 55 72 6430-34 36,200 28,600 56 76 6535-39 21,200 18,900 54 85 68

All 118,200 137,300 57 76 67

Source: Calculated from FaCS 1% LDSNotes: The population is women with at least one family payment eligible child aged under 6years who were receiving the Sole Parent Pension or Parenting Payment (SPP, PGN, PGL or PGPin the LDS) on 1 March 1996. Women receiving PPP in 1996 are classed as Lone parent, and theremainder as Partnered. The smaller number of women receiving disability or unemploymentpayments in their own right are not included (see Figure 3 for numbers in 2003). The samplesizes are 1% of the population estimates shown in the table. March 1996 was chosen as thestarting point because this lies at the end of the phase-in period for Parenting Payment. Thispayment commenced in mid 1995, but many couples remained on the previous payments (paidmainly to the father) until the end of 1995. See Bradbury and Norris (2005) Figure 4.1. Womenare defined as receiving income support in 2003 if their primary benefit received (as at 7 March)was classed as ‘income support’ in the LDS.

Indeed the difference between the youngest groups and the older groups issmall compared to the other outcome differences described above – and some of thisdifference may simply reflect the higher subsequent fertility of the younger mothers.The small difference in income support rates across the age groups suggests that muchof the difference in characteristics in younger vs older mothers is captured in theirdifferent rates of income support receipt when they initially become a mother (i.e. asshown in Figure 3). Within the group were receiving income support when their childwas young (the population of Table 9), the differences in later outcomes are not large– though teenage mothers do have poorer outcomes.

The difference between those who were initially lone parents and those whowere receiving partnered parent payments is also interesting. Generally, the former weremuch more likely to be receiving income support payments seven years later (76 vs 57per cent). The exception is teenage mothers. In this age group, both partnered and loneparent mothers had high rates of income support (81 and 78 per cent). Indeed, amongthose who were initially lone mothers, there is little difference across the age groups.The high rate of income support receipt among the initially partnered teenage mothersis the main reason for the high rate of later income support among teenage mothers.

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Though this result should be treated cautiously (the 1% LDS only includes 42partnered teenage mothers)15 it does suggest that being partnered does not guaranteefavourable long-term outcomes for teenage mothers.

4. Changes in the Social Class Gradient of Ageat First BirthHas the social class gradient of age at first birth changed over time? One explanationfor the variations in age of first birth across different social groups is that fertilitydecisions are influenced by women’s perceived opportunities in the labour market.These opportunities have increased significantly over the past three decades. It is thusconceivable that this change may have led to an increase in the social class gradient ofage at first birth. For example, in the USA, Ellwood, Wilde and Batchelor (2004), findthat the fertility gap between women of different education levels has substantiallyincreased over the last 20 years, despite the fact that college educated women nowmake up a higher percentage of the workforce.

This section examines changes in the social class gradient over the last twodecades; comparing outcomes measured in the 1981 and 2001 Censuses for womenwho had their children up to 15 years earlier. As in the previous section, the Censusdata on the age of children in the household can be used to estimate the age at whichwomen had their first child. Because it was more common in the 1980s for children toleave home at earlier ages, attention is restricted in this section to a slightly youngergroup of women; those aged 28 to 32. In addition, because the proportion of womenhaving any child by this age has decreased significantly over this period, women withno children are included in the comparison as well.

Table 10 - Estimated age at first birth distribution for women aged 28 to 32 in1981 and 2001

Age at Birth of First Child (%)

1981No children Estimated

<19 19-21 22-27 28-32 (yet) Total population

7.4 18.8 40.7 9.3 23.8 100.0 549,700

2001No children Estimated

<20 20-24 25-27 28-32 (yet) Total population

5.9 17.1 13.6 14.0 49.5 100.0 741,600

Source: ABS Census 1% Household Sample files, 1981 and 2001.

Table 10 shows the estimated age at first birth for these women in 1981 and2001. For both years, this is calculated as the difference between the woman’s age andthe age of her oldest child. However, because of differing data availability, the population

15 An approximate 95 per cent confidence interval for the fraction of partnered mothers receivingincome support in 2003 is from 69 to 93 per cent. The lower bound of this is nonetheless stillhigher than the proportion of older partnered mothers receiving income support.


exclusions vary slightly. In 1981 the Census also asked women how many childrenthey had given birth to (live births). We exclude the 8 per cent of cases where thenumber of children in the family was less than the number of live births. In these cases,the oldest child might have already left the household and so the age at first birth wouldbe over-estimated (this also excludes cases where a child was temporarily absent). Thisexclusion is not possible in the 2001 Census, though the trend for children to leave thehousehold later means that fewer cases would be excluded on this basis in 2001.

For 2001, women are grouped into age at first birth groups of under 20, 20-24,25-27, 28-29 and no children (yet). In 1981, a different age grouping is used. This hasbeen chosen so that the percentage of women in each category matches the percentagesin 2001 – to the extent to which this is possible given integer age data. Thus in 1981,7.4 per cent of women aged around 30 had a first birth when below age 19, whereas in2001, only 5.9 per cent of women had a first birth below age 20. Similarly, in 1981,26.2 per cent of the women had their first birth before age 22, compared to the 2001pattern of 23 per cent of women having their first birth before age 24.

Given that the distribution of age at first birth distribution has changed somuch over time, we can examine changes in the association of this with socio-economiccharacteristics in two ways. One approach is to fix the definition of young birth usinga fixed threshold. For example, we could compare the relative education level of womenwho had a teenage first birth in the two years.

Figure 6 - Concentration of education levels of women aged 28-32 with veryyoung first births, 1981 and 2001


165BRUCE BRADBURY


This ‘absolute’ comparison, however, may not be appropriate if we think ofage at birth as reflecting the outcome of a social sorting mechanism. In this case, itmakes more sense to use a relative definition of young births and identify these usingan (approximately) fixed proportion of all women (e.g. using the cut-offs shown inTable 10). In the comparisons with education and partner’s income below, we useboth types of young birth cut-off definition. As it turns out, the conclusions are verysimilar under both approaches.

When comparing education and income distributions over time, it alsonecessary to take account of the changing measurement of these variables. The incomequestion referred primarily to annual income in one Census, but weekly income in theother, and the income categories are not comparable because of inflation and realincome growth. Education is also defined differently in the two censuses. In 1981,people were asked about their age when they left school, and about any post-schoolqualifications. In 2001, people were asked which school years they had completedand any post-school qualifications.

Because of these changes, we use education and income as ordinal measuresof socio-economic characteristics and describe the relationship with young motherhoodusing concentration curves. Concentration curves are commonly used inepidemiological studies to describe the relationship between health characteristics andsocio-economic rankings. See, e.g. Castillo-Salgado et al (2001).

Figure 6 describes the education concentration curves in 1981 and 2001 forwomen who had been very young mothers. Each level of education is represented bya point on the concentration curve. For each point, the horizontal axis shows theproportion of all women whose highest level of education was this amount or lower.The vertical axis shows the proportion of young mothers who had this level of educationor lower. In 2001, young mothers are defined as those women having a first birthwhen aged under 20. In 1981, this definition is also used, together with two youngercut-offs which provide a sensitivity test. (The younger cut-offs in 1981 identify asimilar fraction of women as the under-20 cut-off in 2001).

If young mothers tend to have less education than all women, then the curvewill lie above the diagonal line of equality. The extent of bow away from the equalityline can thus be used as a measure of association between young motherhood andeducation level. For example, the point labelled ‘Highest education, year 10’ showsthat in 2001, 21 per cent of women aged 28-32 had a highest education level of year10 or lower (reading off the horizontal axis). Among those who had been a youngmother (with first birth prior to age 20), 59 per cent had this level of education (verticalaxis) – a ratio of 2.8. In 1981, young mothers were also more likely to have lowerlevels of education, but here the correlation is not quite so strong. Some 37 per cent ofall women had left school at age 15, compared to 65 per cent of young mothers (a ratioof 1.8). The concentration curve for 1981 is very similar using all three age cut-offs. Asummary measure of association is for the concentration curve is the concentrationindex, defined as the negative of twice the area between the curve and the diagonal.

In 2001, this was 0.501, compared to only 0.367 in 1981 (for births <19).16

16 The corresponding standard errors are 0.0030 and 0.0042, implying a statistically significantdifference (p<0.01).


Figure 6 thus shows that the association between education and (very) youngmotherhood has increased over the last 20 years – particularly for the education levelsheld by the less-educated half of the population (ie the left-hand half of the figure).

Figure 7 shows the education distribution using a broader definition of youngmotherhood. In 2001, this is for mothers aged under 25, while in 1981 this is formothers aged under 22. These comprise 23 and 26 per cent of the population of womenin this age group respectively (Table 10). In both years there is a tendency for youngmothers to have lower education levels than the average woman. There is a slightincrease in this association over time, but this is not as dramatic as for the youngermothers.

Figure 7 - Concentration of education levels of women aged 28-32 who wereyoung mothers (broadly defined), 1981 and 2001


Table 11 shows the relationship between age at first birth and the probabilityof being partnered in 1981 and 2001. In both years, the probability of being partneredat around age 30 increases with the age at first birth. Overall, women at around age 30in 2001 were 16 percentage points less likely to be partnered than women in 1981 (lastrow). Much of this is associated with a lower likelihood of having children by thatage. Among those with children, the difference is only 8 percentage points.

Within the group with children, the percentage point difference is greatestamong those with young first births. Among those having their first birth at aroundage 30, very similar proportions are partnered (94 vs 91 per cent). Among those withthe earliest first births, however, 76 were partnered at around age 30 in 1980 comparedto only 58 per cent in 2001. There has thus been an increase in the strength of theassociation between young first births and not being partnered at age 30.

167BRUCE BRADBURY


Table 11 - Proportion of women with partners when aged 28 to 32 by age atfirst birth, 1981 and 2001

Age at Birth of First Child

1981All, including

All with No children those with<19 19-21 22-27 28-32 children (yet) no children

75.7 84.0 90.2 93.7 87.7 44.6 77.4

2001All, including

All with No children those with<20 20-24 25-27 28-32 children (yet) no children

57.8 74.8 82.3 90.9 79.3 42.4 61.0

Difference (1981-2001)17.9 9.3 7.9 2.8 8.4 2.3 16.4


Figure 8 and Figure 9 look at the sub-group of women who were partnered ataround age 30 and examine the association between their age when they had their firstchild and their husband’s income. These figures are calculated in the same way asthose shown above, except that here women are ranked according to the income oftheir partner, rather than according to their own education level.

Figure 8 - Concentration curve of very young first births by partner’s income:women aged 28-32 in 1981 and 2001



Figure 9 - Concentration curve of moderately young first births by partner’sincome, women aged 28-32 in 1981 and 2001


In both years, partnered women who were young when they had their firstbirth tend to have husbands with lower incomes than the average partnered women(the concentration curve lies above the diagonal). For those who had their first birthswhen very young, this difference is particularly large in the more recent data (Figure8). For example, consider the two points denoted with solid dots in the figure. In 2001,about 35 per cent of all women had husbands with income below $600 per week.However, 61 per cent of young mothers had husbands with such incomes (a ratio of1.7). In 1981, a similar percentage of all women had husbands with incomes below$12,000 per annum (36%). In this year, however, only 48 per cent of young mothershad husbands with income in this range – a ratio of only 1.3. The concentration indexis correspondingly much higher (in absolute terms) in 2001 (-0.30 vs -0.13). Changingthe 1981 age cut-off does not change this conclusion.

As for education, using an older threshold for young motherhood in 2001shows both less association with income and also less change over time (Figure 9).Nonetheless the trend is in the same direction. The association between husband’sincome and age at first birth has increased significantly over time. We are unable totell from these data, however, whether this is due to an increased impact of youngmotherhood on success in the ‘marriage market’ or due to an increase in assortativemating over time.

5. ConclusionsThis paper finds very strong associations between socio-economic characteristics andage of first child. Part of this could be due to a direct impact of having a birth when

169BRUCE BRADBURY


young. However, research that has examined this causal link has generally found onlya small direct impact of young motherhood. That is, women who had children whenyoung would probably have had similar socio-economic outcomes even if they haddelayed their childrearing.17 The main negative impact (found in UK and Australiandata) seems to act via partnering processes. However, this impact appears to be smallcompared to the socio-economic selection effects that lead only some women to becomeyoung mothers.

Most of this research has focussed on the outcomes for mothers. Studying theoutcomes for the children of young mothers is more difficult, but some research doessuggest that there might be unfavourable outcomes for the children of young mothers(e.g. compared to their siblings who are born later) (Francesconi, 2004).

With respect to mothers at least, the fact that women who are young motherswould probably have similar outcomes even if they were to delay their childbearingsuggest that there is not much to be gained from trying to discourage young motherhood.Instead, the primary policy implication of the associations observed here should be toinform the targeting of service delivery to the most disadvantaged families. On theindicators considered here, teenage mothers appear as one of the most disadvantagedgroup in Australian society. Mothers aged 20 to 24 also appear as relativelydisadvantaged.

• Among the findings of this study, a few have particular policy relevance forincome support and other policies for this group.

• Over 10 per cent of teenage mothers (and 6% of mothers 20-24) are Aboriginalor Torres Strait Islander.

• Some ethnic/religious groups are more likely to be young mothers. Forexample, compared to those with no religion, those stating their religion asIslam are more likely to be young mothers, while those stating their religionas Buddhist, are less likely.

• Around 90 per cent of teenage mothers, and 70 per cent of mothers aged 2024 are receiving income support.

• About 80 percent of teenage mothers receiving income support are receivingincome support seven years later (though not necessarily continuously).However, the rate for all mothers is also high at 67 per cent. Teenage motherincome support recipients are thus more likely to be long-term recipients, butthe difference with other income support recipient mothers is not very large.

• A substantial fraction of teenage mothers are partnered (between a quarterand one half depending on definitions). However, this group is just as likelyas lone parents to be receiving income support seven years later. (For oldermothers of young children, those initially partnered are less likely to bereceiving income support later on).

• Young mothers achieve much lower levels of education, are less likely to bepartnered in their early 30s, and their partners are likely to have lower levelsof education and income.

17 These results apply to the sub-population of women who have a child when young. The researchdoes not address the possible impact of a young birth on those women who do not have such abirth. It is likely that the effect of a birth would be stronger for this group as these women generallyhave greater labour market skills.


• These associations between socio-economic characteristics and youngmotherhood (particularly teenage motherhood) have increased in strengthover the past 20 years – probably as a result of the greater involvement in thelabour market of women. Teenage mothers are now a much more marginalisedgroup than they were 20 years ago. This is the case even if we compare themwith mothers aged under 18 two decades ago.

ReferencesBradbury, B. (2006), ‘The Impact of Young Motherhood on Education, Employment

and Marriage in Australia’ SPRC Discussion Paper No. 148.Bradbury, B. and Norris, K. (2005), Family Dynamics in Australia Final Paper, Fluid

Families Project. Paper prepared for the Department of Family and CommunityServices under the Deed of Agreement for the Provision of Social PolicyResearch Services, June.

Castillo-Salgado, C. Schneider, C. Loyola, E. Mujica, O. Roca, A. and Yerg, T. (2001),‘Measuring Health Inequalities: Gini Coefficient and Concentration Index’,Epidemiological Bulletin, 22, Pan American Health Organization. [http://www.paho.org/English/SHA/be_v22n1-cover.htm]

Ellwod, D. Wilde, T. and Batchelder, L (2004), ‘The Mommy Track Divides: TheImpact of Childbearing on Wages of Women of Different Skill Levels’unpublished paper.

Ermisch, J. and Pevalin, D. J. (2003), “Does a ‘Teen-birth’ have Longer-term Impactson the Mother? Evidence from the 1970 British Cohort Study” ISER WorkingPaper No. 2003-28.

Evans, A. (2002), ‘The Outcome of Teenage Pregnancy: Temporal and Spatial Trends’,People and place, 11, 39-48.

Francesconi, M. (2004), ‘Adult Outcomes for Children of Teenage Mothers’,unpublished working paper, May.

Geronimus, A. T. (1997), ‘Teenage Childbearing and Personal Responsibility: AnAlternative View’ Political Science Quarterly 112, 405-430.

Haveman, R. Wolfe, B. Wilson, K. and Peterson, E. (1997) ‘Do Teens Make RationalChoices? The Case of Teen Non-marital Childbearing’ Discussion Paper no.1137-97, Institute for Research on Poverty http://www.ssc.wisc.edu/irp/

Hoffman, S. D. (1998), ‘Teenage Childbearing is not so bad after all … or is it? AReview of the New Literature’ Family Planning Perspectives 30, 236-9

Holmlund, H. (2005), ‘Estimating Long-term Consequences of Teenage Childbearing;An Examination of the Siblings Approach’ Journal of Human Resources, 40,716-743,

Hotz, V.J. Mullin, C.H. and Sanders, S.G. (1997), Bounding Causal Effects usingData from a Contaminated Natural Experiment: Analyzing the Effects ofTeenage Childbearing, Review of Economic Studies, 64, 575-603.

Lopoo, L M. and DeLeire, T. (2005), ‘Did Welfare Reform Differentially Influencthe Fertility of Young Teens? Assessing the Success of the ‘Living ArrangementsRule’ and the ‘Stay-in-School Rule’ Unpublished paper.

Robson, K. and Berthoud, R.(2003), ‘Young Motherhood and Disadvantage:A Comparison between Ethnic Groups,’ Working Papers of the Institute forSocial and Economic Research, paper 2003-29. Colchester: University of Essex.

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Stewart, J. (2003), ‘The Mommy Track: The Consequences of Gender Ideology andAspirations on Age at First Motherhood’ Journal of Sociology and SocialWelfare 30, 3-30.

Taylor, S. (1986), ‘Teenage Girls and Economic Recession in Australia: Some Culturaland Educational Implications’ British Journal of Sociology of Education 7,.379-95

Thompson, D. (with Bradbury, B.)(2005), Teenage Motherhood: Antecedents,Outcomes and Policy Responses Literature Review, Young Mothers Project,Paper for the Department of Family and Community Services under the Deedof Agreement for the Provision of Social Policy Research Services, Social PolicyResearch Centre, February 2005.

UNICEF (2001), A League Table of Teenage Births in Rich Nations Innocenti PaperCard, Issue No. 3, July. Florence: UNICEF Innocenti Research Centre http://www.unicef-icdc.org/publications/index.html

Wolfe, B. Wilson, K. and Haveman, R. (2001), ‘The Role of Economic Incentives inTeenage Non-Marital Childbearing Choices’ Journal of Public Economics 81,473–511.

Documents

Disadvantage among Australian Young Mothersceebi.curtin.edu.au/local/docs/B4_-_2006Bradbury.pdf · Disadvantage among Australian Young Mothers ... young motherhood is a strong signal