Young in Class: Implications for Inattentive/Hyperactive Behaviour Of

Young in Class: Implications for Inattentive/Hyperactive Behaviour of

Canadian Boys and Girls

Revision

March, 2013

Kelly Chen, Nicole Fortin, Philip Oreopoulos and Shelley Phipps

This research is being conducted as part of the Canadian Institute for Advanced Research (CIFAR) Programme on Social Interactions, Identity and Well-Being. The NLSCY data were access through the Atlantic Research Data Centre; we thank Heather Hobson for vetting our output.

Abstract

Are Canadian children who are young relative to their class-mates more likely to exhibit inattentive/hyperactive behaviours? If so, are there gender differences in the extent to which this is true? Do the effects on inattentive/hyperactive behaviours of starting school relatively young persist into adolescence?; and, if so, can this help to explain gender differences in educational outcomes, behaviours and aspirations of Canadian youth? Using data from the Statistics Canada National Longitudinal Survey of Children and Youth, we apply two research strategies to address these questions. A ‘difference in difference’ design compares children who are the same age in months, but live in provinces and/or time periods with different school start dates. A ‘regression discontinuity’ design compares scores for children living in the same province who were born just born and just after the relevant school entry cut-off. Both approaches find more inattentive/hyperactive behaviour for children who are young in class, especially if the child was more inattentive/hyperactive prior to school entry. When we control for child inattentive/hyperactive behaviour at ages 2/3, we find that being young in class exacerbates an underlying tendency toward inattentive/hyperactive behaviours and thus pushes more boys than girls into clinical levels. These effects persist into early adolescence and may contribute to gender differences in other early adolescent school-related behaviours, aspirations and outcomes.

Recent research emphasizes the idea that human capital acquisition is a cumulative

process (e.g., Cunha and Heckman, 2009; Currie, 2011; Conti and Heckman, 2012; Heckman,

Stixrud and Urzua, 2006). Both cognitive and non-cognitive capacities developed early in the educational process can enhance the productivity of later education; moreover, higher capacity in

one dimension is argued to complement the capacity to grow in another (e.g., an attentive child

can learn to read more easily). Thus, experiences at the very start of their school lives can have

long-run repercussions for children’s eventual educational success.

Attention of both scholars and popular media (e.g., Fortin et al., 2012; Gurian, 2009; Sax,

2007) has also recently been drawn to the fact that girls’ academic achievement has now

surpassed boys.’ Young women now comprise 60 percent of the undergraduate population in

most Canadian universities. In 2008, 36.5 percent of young Canadian women aged 25 to 29 had

university degrees compared to 24.1 percent of young men (Drolet, 2011).

In this paper, we explore the possibility that part of the explanation for boys’ lagging

academic motivation and achievement may originate in the early years at school. For example, if

boys come to dislike school a little less at the very beginning, this can snowball over the years

into significantly different educational attitudes/behaviours/outcomes. In particular, we focus

on inattentive/hyperactive behaviour as one important aspect of non-cognitive development that

has become more of a problem in recent decades, matters for educational attainment and has big

gender differences early in life. 1

1 U.S. data (e.g., Akinbami, et al., 2011; Child Trends, 2012; Garfield, 2012) show increased prevalence of Attention Deficit Hyperactivity Disorder (ADHD), a clinical level of the kind of behavior we study here. Attention- Deficit/Hyperactivity Disorder (ADHD) is among the most commonly diagnosed behavioural disorders for children in many countries (Elder, 2010; Faraone, et al., 2003; Skounti et al., 2007). ADHD is a developmental, neurobiological condition defined by the presence of severe and pervasive symptoms of inattention, hyperactivity and impulsivity which must be exhibited over a period of at least 6 months, before the age of 7 and in at least two contexts such as home and school (Daley and Birchwood, 2010; Loe and Feldman, 2007). Secular trends are hard to identify given changes in diagnostic practices, but increases in prevalence are apparent over the past 40 years (Perrin

A significant body of research indicates that children who are less attentive or more

hyperactive experience problems with human capital acquisition (see, for example, Daley and

Birchwood; 2010 or Loe and Feldman, 2007 for reviews of the medical/psychological literature).

For example, they score lower on math/reading tests, are more likely to have behavioural

problems at school and/or to repeat a grade (Loe and Feldman, 2007). Most of this research has

focussed on young school-aged children, but, negative implications of hyperactivity on academic

performance have also been found for adolescents (Birchwood, 2010) and even college students

(e.g., Frazier, et al., 2007).

However, not all studies have adequately controlled for the possibility that, for example,

the home environments of children with and without ADHD may differ (e.g., in terms of parental

income, health, etc).2 Thus, important recent economic contributions to the literature include

Currie and Stabile (2006) and Fletcher and Wolfe (2008) who confirm the negative impact of

ADHD on academic achievement in models exploiting sibling differences in samples

representative of the population. From our perspective, an important finding is that that

academic problems are present even for children with only some symptoms of

inattention/hyperactivity (i.e., they are a bit more wiggly/boisterous/distractible than other

children), even if ADHD is not diagnosed or even if hyperactivity is well below clinical levels

(Currie and Stabile, 2006).

Although it was once thought that ADHD symptoms disappeared during adolescence, a

growing body of research indicates that hyperactive/inattentive behaviours continue into

adulthood (Wilens, Biederman and Spencer, 2002). For example, there are follow-up studies of

et al., 2007). Current estimates suggest worldwide ADHD prevalence ranges between 4 and 10 percent (Faraone, et al., 2003; Skounti et al., 2007; Spencer et al., 2007). 2 This can be a particular problem for studies of clinical samples of children being treated for ADHD (see Bauermeister et al, 2007, Table 1).

4 clinical populations that demonstrate persistence of symptoms over time (Biederman et al., 1998;

McGee et al., 1991). And, longitudinal research also finds that early childhood inattention/hyperactivity has negative implications for academic outcomes both in adolescence

(Fletcher and Wolfe, 2007; Currie, et al., 2010) and even in adulthood (e.g., Daley and

Birchwood, 2009; Fletcher, 2013; Frazier et al, 2007).

There is surprisingly little ADHD research discussing gender differences. Indeed, since boys are much more likely to be treated for ADHD, clinical studies have a particularly male focus. However, population estimates indicate that many more girls exhibit symptoms of ADHD than are diagnosed (Gerson and Gerson, 2002); and, ‘ADHD females share with their male counterparts prototypical features of the disorder (e.g., inattention, impulsivity, and hyperactivity), [and] high rates of school failure’ (Wilens, et al., 2002). This is of particular interest for our study with its focus on gender and on inattentive/hyperactive behaviours that fall short of clinical ADHD.

Another branch of research upon which we build presents evidence that children who are young within grade at school are more likely to be diagnosed with ADHD (e.g., Elder, 2010;

Evans, 2010; Morrow, et al, 2012). Using U.S. data., Elder, for example, finds that 8.4 percent of children born in the month prior to the state cut-off for kindergarten eligibility are diagnosed with ADHD compared to 5.1 percent for those born in the month after. Morrow et al., 2012 report similar findings for B.C. Although these authors focus on the implications of being young in class for diagnosis of ADHD, we argue that it is also plausible that being young in class actually increases inattentive/hyperactive behaviour (though not necessarily to clinical levels).

Since young in class children can be almost one full year younger than some of their peers,

expectations for paying attention, sitting still, etc might be hard to achieve, leading them to ‘tune

out’ or ‘burst out’ with more boisterous behaviour both at school and at home.

Although the effects of hyperactivity are known to persist over the long-term, there is

some dispute in the literature about how long-lasting we might expect effects of being relatively

young in class to be. Bedard and Dhuey (2008) present evidence for a variety of countries (and

the Canadian province of BC) that relative school start age effects persist into the adult years;

Smith (2007), using the same BC data set, also finds evidence of effects persisting into the high

school years. On the other hand, Bertrand and Pan (2011) argue, using U.S. data, that effects

dissipate; Dobkin and Ferreira (2010), again in the U.S. context, argue that there are no long-

term implications for adult labour market outcomes since younger children, on the one hand,

have poorer academic outcomes during their school years, but, on the other hand, are more likely

to pursue further education.

Building on these different strands of literature, we pose three basic research questions::

1) Are Canadian children in kindergarten through grade 4 who are young relative to their class-

mates more likely to exhibit symptoms of inattentive/hyperactive behaviour at home as reported

by their parents,3 and if so, are there gender differences in the extent to which this is true? 2)

Longitudinally, do children who exhibit higher levels of inattention/hyperactive behaviour at age

2/3, before they enter public school have a particularly difficult time adjusting if they are young in class and is this particularly an issue for little boys?; 3) Do effects of being inattentive/hyperactive early in a child’s schooling career, perhaps exacerbated by being young at school, have negative effects on academic outcomes in early adolescence, and if so, do such

3 Note that this is not the same thing as asking if the child has ever been diagnosed with ADHD. We are also interested in inattentive/hyperactive behaviours well below clinical thresholds.

differences help to explain lagging school outcomes and disinterested behaviours/attitudes of

adolescent boys compared to girls (Fortin, et al., 2012). 4

Using microdata from the National Longitudinal Survey of Children and Youth (1994

through 2008), we use, first, a ‘difference-in-difference’ strategy to compare children of exactly

the same age (in months) living in different provinces and/or time periods with different school

start cut-offs so that some of the children are ‘young in class’ while others of the same age are

‘old in class.’ Second, we use a ‘regression discontinuity’ (RD) design (see Lee and Lemieux,

2010 for a ‘user’s guide’ to the RD approach) in which we compare hyperactivity scores for

children living in the same province who were born just before and just after the relevant school

start cut-off date. This is possible since the NLSCY provides exact day of birth for each child.

Third, we take advantage of the longitudinal structure of the NLSCY to control for

inattention/hyperactive behaviour observed at ages 2/3 and ask if being young in class

exacerbates a pre-existing tendency to be inattentive/hyperactive? Finally, we further exploit the

longitudinal nature of the NLSCY to test whether hyperactivity observed in the early years at

school (e.g., at ages six/seven) helps to explain differences between boys and girls at age 13/14

in terms of both parent reports of school achievement and young adolescent self reports of

educational attitudes/behaviours and aspirations.

1. Kindergarten/Elementary School Legislation in Ten Provinces

Provincial authority over education policy in Canada provides a significant level of variation

across time and place in rules about when children start school. Kindergarten (grade primary in

Nova Scotia) is available for five-year olds in all provinces, but what we principally exploit for

4 Fortin et al, 2012, demonstrate that while there has been growth in the high achievement of girls in the U.S. (i.e., probability of getting A’s), there has been growth in the likelihood of boys getting C’s.

our analyses is that the date by which the child must have turned five varies from September 1 to

March 1. Table 1 shows the nine different school entry cut-off dates used during our study

period.

Since a typical school year runs from September to the end of June in all provinces, children

are admitted to school at one time each year. Whether they qualify for entry depends on their exact date of birth. Because of the single entry age cut-off, some children will be admitted to school a full year earlier than others. For example, if the cut-off date is December 31 in a calendar year when a child turns five, it means that children who are born on or before December

31 will start school when they are 4 years and 8 months and become the youngest student in the class. On the other hand, children who are born on January 1 will have to wait till next year to enter kindergarten, which means they actually start when they are 5 years and 8 months, and become the oldest student in the class.

With the exceptions of Alberta and Saskatchewan, school entry age eligibility in Canada is

determined by the provincial Ministry of Education and is specified in provincial statutes that are

usually contained in provincial Education Acts. Within the provinces of Alberta and

Saskatchewan, school boards may set their own age requirements for entering school (see notes

to Table 1). For the purpose of this study, we utilize information on school entry age cut-off in eight provinces and school boards/districts of Alberta and six school boards in Saskatchewan that

can be identified by the Census Metropolitan Area (CMA) code available in the NLSCY. Data are directly compiled from provincial Education Acts and Department of Education or school board websites. We also use additional sources to help verify the compilation, including a survey

on school start age across Canada by the PEI Department of Education,5 and publications by

Statistics Canada that summarize school eligibility legislation.

As shown in Table 1, the most common cut-off date for school eligibility across provinces is

December 31. During our study period, six provinces (i.e. British Columbia, Manitoba (1987-

2000), Ontario (2001-2004), New Brunswick, Newfoundland and Labrador, six school districts

in Saskatchewan and 4 school districts in Alberta) used this cut-off date to determine eligibility for kindergarten. The second most common school-entry cut-off date is September 30, used in

Quebec and Nova Scotia. Otherwise, start date varies widely: for example, Calgary uses

September 1 while Edmonton uses March 1. Also, PEI and Manitoba have both made several

changes in cut-off date during our study period.

Of note is the fact that kindergarten is only mandatory in Quebec.6 Compulsory schooling

outside Quebec begins in grade one (see Oreopoulos, 2005 and 2006). Nevertheless, as we will

show, in all provinces nearly all families comply with the norms established through legislation

and begin public school with kindergarten at the ‘appropriate’ age.

2. Data Statistics Canada’s National Longitudinal Survey of Children and Youth (NSLCY) is a

nationally representative dataset of Canadian children that tracks their development and well-

being from birth to early adulthood, with data collection occurring at two year intervals. The first

survey round took place in 1994/95 with a nationally representative sample of 22,831 children

5 2003. http://www.ed.gov.nl.ca/edu/k12/kindergarten.html. 6Ontario and Quebec offer two grades of kindergarten: junior kindergarten and senior kindergarten. Junior kindergarten, which is attended by four-year-olds, is optional in both provinces, but senior kindergarten is mandatory for five-year-olds in Quebec. Other provinces have only one year of kindergarten (called ‘primary’ in Nova Scotia). Kindergarten usually runs on a half-day or every-other-day schedule, while starting in 2007 (?) and 2010 (?), Ontario and British Colombia introduced full-day Monday to Friday kindergarten. Starting in 2010, after our study period, kindergarten became compulsory in PEI. For more detailed description of kindergarten entry age in Canada, see Lefebvre, Merrigan and Verstraete (2009).

aged 0-11. In addition to following the original longitudinal children, a new cohort aged 0-1 was

added at each new cycle allowing the construction of a sizable repeated cross-sectional dataset.

Most information for children under the age of 10 is reported by a parent, specifically the parent selected as the person ‘most knowledgeable about the child (or, pmk – most typically the mother)

during a personal interview in the home.

In the first section of the paper, we select children between 4 and 9 years of age7 and who

are attending public school or publically funded Catholic schools. Since junior kindergarten is

only available in some provinces, our basic sample excludes children currently attending junior

kindergarten (though we later test the sensitivity of our results to having attended junior

kindergarten).8 To maximize our sample size, observations from cycles 1 through 8 (1994-2008) are pooled.

A nice feature of the NLSCY compared to data sets used in some other studies of the implications of being young in class is that we are able to match each child in the NSLCY to the province-mandated elementary school eligibility cut-off when he/she was 4/5 years old.9 That is,

we use the longitudinal nature of the data to select children with parent reports of province of

residence at kindergarten start age (i.e. 4/5 years old) who have been living in the same province

ever since. With these restrictions, we have a sample of 34,500 children.10

7 For the purpose of sample selection, we use the NLSCY ‘effective age’ since this determines the set of questions that will be asked about the child. Effective age is calculated as cycle year minus year of birth. 8 We also exclude a small number of children who did not live in either one- or two-parent families (e.g., those in foster care or institutions). For Alberta and Saskatchewan, children living outside of the CMA’s for which we know school start age rules are also excluded. 9 For example, Evans et al., (2010) do not have this information for any of the 3 data sets they employ. 10 Note that a child may appear more than once in the sample (e.g., at 6 and 8) since we are pooling observations across cycles. We have also estimated all models using a sample in which each child is randomly selected to appear just once with no substantive differences in our conclusions.

The measure of inattention/hyperactivity we use is based on parent11 reports. In all survey

years, parents of young children were asked to assess how often, in the home setting, their

child:12

□ “Can’t sit still or is restless?”

□ “Is easily distracted, has trouble sticking to any activity?”

□ “Can’t concentrate, can’t pay attention for long?”

□ “Is impulsive, acts without thinking?”

□ “Has difficulty waiting for his turn in games or groups?”

□ “Can’t settle to anything for more than a few minutes?”

□ “Is inattentive?” 13

For each behavior, the parent can choose: ‘never or not true’ (=0); ‘sometimes or somewhat true’

(=1); or, ‘often or very true’ (=2). Responses are summed to construct a scale ranging in value from 0 to 14, with a high score indicating the highest level of inattentive/hyperactive behaviour.

The mean hyperactivity score for our sample is 3.9, though boys have higher scores than girls

(4.6 compared to 3.6). To put these scores in perspective, children in the NLSCY reported by their parents to be taking the drug Ritalin, commonly prescribed for children diagnosed with

ADHD, have a mean score of 9.4. Distributions of the hyperactivity scores for 4 to 9 year old boys and girls are presented in Figure 1.

11 Although teacher reports are also available for three cycles, teacher response rates are extremely low, so that we do not regard them as a reliable source of information. Also, previous research (Elder, 2010) emphasizes that teacher perceptions may be particularly likely to be systematically correlated with a child’s age relative age to classmates. 12 Specifically, pmk’s are asked: “How often would you say [child’s name] …” 13 Earlier cycles also contained an additional question (‘fidgets’); we re-constructed the hyperactivity score to obtain cross-cycle consistently.

3. Basic Research Methods

As noted above, we use two sources of variation to identify the effects of relative age on

parent-reported inattentive/hyperactive behavior of Canadian children. First, across provinces

and time14 we exploit differences in school start age policies which mean some children of

exactly the same age (in months) are relatively young in class in one province but not another

(difference in difference design). Second, within province, we exploit the randomness in exact

date of birth for children born on either side of the school entry age cut-off and compare

outcomes of otherwise similar children who received distinct treatment due to the enrolment

eligibility legislation (regression discontinuity design).

Difference in Difference Design

Differences across the ten provinces in the cut-off dates for school entry as well as

changes in cut-off dates during our study period for some provinces provide sufficient variation

to allow us to compare children of exactly the same age in provinces with different cut-offs, so

that in one province, the child is ‘young in class’ while in the other, he/she is ‘old in class.’

(1) I/H i = α+ τ Young6mosip + β1 Ageinmonths i + β2 Grade i + β3 Cycle i + + λ Xi + ε i

where I/H i is the inattentive/hyperactivity score (based on parent report) for child i;

Young6mosipt is a dummy variable indicating that the child was born in the 6 months prior to the school-entry cut-off in that year and province; Ageinmonths i is the child’s age in months at the

14 However, the number of changes across time in school start age policies are more limited than the differences across provinces, thus, we rely more heavily on the cross-province policy variation.

15 time of the survey; Cycle i refers to the NLSCY cycle from which the observation is drawn

(beginning with Cycle 1 collected in 1994 through Cycle 8 collected in 2008); Grade i refers to

the child’s current grade at school; Xi includes child gender (in pooled boy/girl models), parental

education, log family equivalent income16, family structure and parent immigrant status. We

estimate the DID model with and without the additional covariates for the combined sample of

boys and girls as well as separately for boys and girls. Longitudinal weights are used for all

estimates; standard errors are clustered by province.

Regression Discontinuity Design

Following Elder (2010), our second approach to estimating the effect of a child being

relatively young in his/her class at school on parent reports of child hyperactivity is to compare

children living in the same province who were born shortly before compared to shortly after the

relevant school cut-off date. The RD approach has also been used to study a implications of

being relatively young in class for a variety of child outcomes (e.g., Dhuey and Lipscomb, 2010;

Dobkin and Ferreira, 2010) though no studies of which we are aware exploit the variation that

exists in school-entry policies across Canada (though see Bedard and Dhuey, 2006; Morrow, et

al., 2012; Smith, 2007 for studies using data within the province of British Columbia).

Intuitively, the idea of the RD strategy is that it is hard to think of any plausible reason

why, for example, a Nova Scotian child born in September would be more hyperactive than a

Nova Scotian child born in October of the same year except that the September child would be

the youngest in his or her class while the October child would be among the oldest. But, Figure

15 This is important, since inattentive/hyperactive behaviours change, generally diminishing with the child’s age (e.g., Spencer et al., 2007). 16 ‘Equivalent’ income is family income adjusted for the differing needs of families of different size, using a ‘square-root of family size’ equivalence scale.

1 shows that, in fact, Canadian children born just prior to the school cut-off date have higher

levels of inattention/hyperactivity than those born just after. This is evident both in the pooled

boy/girl sample and in separate estimates for boys and for girls (see Figure 2).

More formally, we estimate the following RD model:

(2) I/H i = α+ τ Youngi + γ f(bdi-ci) + β1 Province i + β2 Cycle i + β3 Grade i + λ Xi + ε i

where I/ H i is the inattentive/hyperactive score (based on parent report) for child i; Youngi is a dummy variable indicating that the child has a birth-date in the period immediately prior to the

17 school-entry cut-off; f(bdi-c) is a function of the number of days between the child’s exact

18 birthdate, bdi, and his or her relevant school-entry cut-off date; Province i is the child’s

province of residence; Cycle i refers to the NLSCY cycle from which the observation is drawn

(beginning with Cycle 1 collected in 1994 through Cycle 8 collected in 2008); Grade i refers to

the child’s current grade at school; Xi includes child gender (in pooled boy/girl models), parental

education, log family equivalent income,19 family structure, and parent immigrant status. Again,

we first estimate for a combined sample of boys and girls, adding a dummy for ‘boy’ to the set of

covariates; we then estimate separately for boys and girls. Longitudinal weights are employed

for all analyses; standard errors for the RD estimates are clustered at birth dates.

17 We have used windows around the school cut-off day ranging from one month before and one month after to six months before and six months after. 18 We have tried specifying f(bdi-c) as a linear, quadratic and cubic function. 19 Family incomes are in real 2006 Canadian dollars, using CPI with 2001 basket content. ‘Equivalent’ income adjusts dollar income to reflect differences in needs of families of different size. We use the Luxembourg Income Study equivalence scale (square root of family size) to make this adjustment.

4. Basic Estimation Results20

Difference in Difference Results

Difference-in-difference (DID) results are reported in Table 2.21 For both boys and girls, we find that children who are young in class have more parent-reported symptoms of

inattention/hyperactivity than their peers in other provinces/time periods who are the same age but who are positioned differently relatively to their class-room peers as a result of differences across place/time in school start cut-offs. The size of the ‘young in class’ effect of about 0.4

points is very similar for boys and girls (0.13 of a standard deviation for boys; 0.14 of a standard

deviation for girls).22 But boys have significantly higher inattentive/hyperactive scores than girls

(about 1 point relative to the over-all mean of about 4 points), so that this effect is more likely to push them into clinical levels than it does for girls. Relative to other key covariates, the size of effect for being young in class is roughly 60 percent as large as having a parent with a university level education, for example, though in the opposite direction. The young in class effect is larger than the lone-mother association for girls (about 80 percent as large for boys).23

Robustness Checks for the DID Estimates

Table 3 presents a series of robustness checks. Currie and Stabile (2006) have noted that there are strong negative associations between inattentive/hyperactive behaviour and human capital acquisition at well below normal ‘clinical’ levels of these behaviours (i.e., for children who are inattentive or boisterous but whose symptoms are far from being diagnosed as

20 OLS results for the linear inattentive/hyperactive score are reported in the paper. We have also estimated ordered probit models as well as an OLS model for log(hyperactivity score +1). The general nature of results is unchanged. 21 We have tried a variety of specifications for age in months. Higher order terms were generally not statistically significant and other conclusions were not affected. Hence, we report only the quadratic ‘age in months’ variable. 22Formal statistical tests reject the hypothesis of a significant difference in the size of the ‘young’ effect for girls and boys (i.e., the interaction of ‘boy’ and ‘young’ is never statistically significant in pooled models). Evans et al., (2010) also found no significant difference for boys compared to girls. 23 Bertrand and Pan (2011) also find that boys have a harder time in lone-mother families.

ADHD24). Thus, a first test of robustness is to see if being young at school increases parent reports of child inattentive/hyperactive symptoms at home for ‘non-clinical’ cases. This is done by excluding: 1) children who are reported to be on Ritalin; and, 2) children who are in the top

decile of the inattentive/hyperactive score. Relatively few children in our sample are reported to

be taking Ritalin (2.8 percent of boys; 0.8 percent of girls), so results are little affected by this

exclusion.25 The estimated coefficient for ‘young’ is only about half as large when we exclude

all children in the top decile of the inattentive/hyperactive behaviour score, but it remains

statistically significant.

Since our analysis defines children as young in class by comparing their birth date with

the legislated school start date for their province/time period, a concern might be that parents do

not always comply with the legislation. For example, if some parents are aware of the literature

on being ‘young in class,’ they may choose to hold their children back in order to provide an

advantage relative to peers (academic ‘redshirting’). This seems particularly likely if the child is

perceived as ‘not ready’ for school. If this is so, then we would have more ‘less able’ children in

the ‘old’ group, and we would underestimate the implications of being ‘young.’ However,

Appendix Table 2 indicates that, in Canada, only a very small number of children are not in

compliance with the school entry regulations in their year/province (at most 3 percent). Not

24 Attention-Deficit/Hyperactivity Disorder (ADHD) is among the most commonly diagnosed behavioural disorders for children in many countries (Elder, 2010; Faraone, et al., 2003; Skounti et al., 2007). ADHD is a developmental, neurobiological condition defined by the presence of severe and pervasive symptoms of inattention, hyperactivity and impulsivity which must be exhibited over a period of at least 6 months, before the age of 7 and in at least two contexts such as home and school (Daley and Birchwood, 2010; Loe and Feldman, 2007). 25 Perhaps surprisingly, given the availability of public health insurance in Canada, rates of treatment with Ritalin seems to be lower in Canada than in the U.S. (e.g., Currie and Stabile (2006) estimated that 1.4 percent of Canadian children aged 4 to 11 in 1994 took Ritalin, compared to 3.3 percent in of the same age and in the same year in the U.S.

surprisingly, then, we see almost no change in estimates if these children are excluded from our

sample.26

Another concern could be that some parents, aware of the ‘young in class’ literature,

attempt to time the month of their child’s birth to ensure that he/she is old in class. However,

Bedard and Dhuey (2006) find no evidence of such behavior in their study of 20 countries, nor

do we find a jump in birth frequency just after the school entry threshold in our data (see Figure

7, that uses pooled cycles of data for provinces without a change in school entry date).

It is also possible that some children born just after the school entry age cut-off, yet who

were perceived as ‘ready’ to start school were sent to private schools that might be more flexible

with respect to parental preferences. Again, this would suggest that we under-estimate the true

effect of birth date on inattentive hyperactive behaviour of children, if parents are more likely to

start particularly able children early. Again, to make sure this is not a significant problem, we

repeat our analyses for a sample that includes all children in the NLSCY regardless of their

schooling status (i.e., home-schooled or not) or type of school attended (public or private). Since

less than 4 percent of children in grades K through 4 attend private school in Canada, results are

also robust to adding children who are home-schooled or attending private schools back into the

sample (see Table 3).

A further issue is that some regions offer public junior kindergarten and some do not and

the availability of daycare varies across the country.27 Since having attended junior kindergarten

or structured daycare may later influence the child’s behaviour in kindergarten or grade one, we

control for whether the child attended a structured daycare or a junior kindergarten when he/she

26 Indeed, these results cannot be released from the Research Data Centre in order to avoid possible residual disclosure, given the very small numbers of children involved. This contrasts with U.S. findings of growing numbers of ‘redshirted’ children (e.g., Deming and Dynarski, 2008; Evans et al., 2010). 27 See, for example, Lefebvre and Merrigan, 2008 or Lefebvre, Merrigan, and Verstraete, 2009.

was 3/4. To do this, it is necessary to further limit our sample to children observed at age 3 or 4 and with answers to questions about attendance in junior kindergarten or formal daycare at that time. Again, our main causal findings about increased inattentive/hyperactive behaviour for children who are relatively young at school are unaffected by the inclusion of this control.28

Regression Discontinuity Results

RD results for the pooled boy/girl sample are presented in Table 4 which reports only the

estimated coefficient for ‘boy’ and for the ‘young’ variable. Again, we find that children who

are relatively young in class are reported by their parents to exhibit more inattentive/hyperactive

in the home setting. The RD results suggest that children who are young in school have scores

that are about 0.5 points higher than their peers on the ‘other side of the window.’ These

estimates are similar in magnitude to those obtained using DID methods. Again, while we find

boys to have significantly higher inattentive/hyperactive scores than girls (about 1 point), we

never find a statistically different impact of being young in class for boys than for girls. In the

estimates reported here, we include all covariates and use a linear specification for the distance

from cut-off function, f(bdi-c). We have also used quadratic and cubic specifications for the

running variable. Higher order terms are nearly always insignificant; main conclusions are not

affected, so results are not reported here in the interests of space. We report results for window

lengths of two and three months before/after the school cut-off date. The same series of

robustness checks are again carried out. Perhaps due to the smaller sample sizes, the RD

estimates are slightly less robust than the DID estimates. Nonetheless, the basic conclusion that

children who are relatively young in class exhibit more inattentive/hyperactive behaviour than

their relatively older peers generally holds.

28 While there is no association between having attended junior kindergarten at 3/4 and current inattentive/hyperactive score, we do find a correlation between having structured daycare at 3/4 and higher inattentive/hyperactive scores at 5/9. This is consistent the findings of Baker, Gruber and Milligan (2008).

In order for our interpretation that higher levels of inattentive/hyperactive behaviours are

caused by being young relative to class-mates, we do not want it to be the case that other

potential reasons for hyperactivity ‘jump’ near the school start-date cut-off. One very nice

feature of the RD strategy is that it is easily possible to test for discontinuities in observable

variables by estimating a set of regressions of the form of equation (2) for each of the covariates

in our data set (Dobkin and Ferreira, 2009 and Lee and Lemieux, 2010). We do this, for one, two and three-month windows and find no evidence of discontinuities around the cut-off for any

of the covariates except, as we would expect, that grade is statistically significant (and positive).

These results are available on request.

5. Is Being Young at School Harder for Children with Greater Inattention/Hyperactivity

Prior to School Entry?

The consensus in the medical literature appears to be that while ADHD diagnosis most often occurs during the elementary school years, symptoms of inattentive/hyperactive behaviour are typically already evident during the pre-school years (Loe et al., 2008). In this section we

make further use of the longitudinal nature of the NLSCY to ask whether increases in

inattentive/hyperactive behaviour associated with being young in class are larger for children

who arrive at school entry age with higher levels of inattention/hyperactivity? That is, do children who have troubles sitting still or paying attention find it harder to cope in a classroom

when they are among the youngest members of their class? To the best of our knowledge, this

question has not previously been studied in the literature, and may be particularly important for a

gender comparison, given that pre-school boys are more inattentive/hyperactive than girls (see

Figure 4).

Restricting the sample to children for whom we have parent reports of hyperactivity both at ages 2/3 and at ages 4 through 9, we estimate the following difference-in-difference29 specification:

(3) I/H i = α+ τ1 Young6mosip + τ2 I/H2/3i + τ2 Hyper2/3i X Young6mosip +

β1 Ageinmonths i + β2 Cycle i + β3 Grade i + λ Xi + ε i where I/H i is again parent-reported inattentive/hyperactive behaviour for the child at ages 4 through 9, and I/H2/3 i is the child’s inattentive/hyperactive score at age 2 or 3. We also include an interaction between inattention/hyperactivity at age 2 or 3 and the ‘young at school’ variable, to test whether symptoms of inattention/hyperactivity are exacerbated by being young at school, using both a linear specification for pre-school inattention/hyperactivity as well as categorical variables indicating the child’s pre-school I/H percentile (e.g., greater than 75th). Other explanatory variables are as described for the difference-in-difference model (1) above. Note that a further advantage of controlling for pre-school inattentive/hyperactive behavior is that if there is any gender bias in pmk reports (e.g., parents think ‘boys will be boys’ and so more boisterous), adding the score at age 2/3 means we are now effectively estimating a first difference model for the child’s inattention/hyperactivity score so that we need not be so concerned about this form of reporting bias, provided it is consistent over time.

Results for these models are reported in Table 5. Key findings are that: 1) there is strong persistence in reported inattentive/hyperactive behaviour; 2) being young in class nevertheless increases parent reports of inattention/hyperactivity, even controlling for scores reported prior to school entry; 3) children who are more inattentive/hyperactive pre-schoolers have the hardest time being young in class. Indeed, the total increase in inattentive/hyperactive score for a child who was in the top quantile of the pre-school distribution and young in class is 0.712 points

29 Our focus from here on is on the DID models where we have a larger sample size.

(0.264 + 0.448, or, about one quarter of a standard deviation). Since boys comprise 57 percent of

the toddlers in the highest quartile of the hyperactivity distribution, in this sense, being ‘young in

class’ is more of a boys’ issue.

6. Are Inattentive/Hyperactive Behaviours During Early School Years Predictive of

Educational Outcomes in Early Adolescence?

Our final question is whether higher levels of inattention/hyperactivity during early years at school matter for educational behaviours, aspirations and/or outcomes during adolescence; and, if so, whether gender differences in inattention/hyperactivity help explain observed differences in adolescent educational outcomes? Certainly, the literature arguing that the acquisition of both cognitive and non-cognitive skills is a cumulative process suggests

‘snowball’ effects from what happens early in life. And, if this is the case, gender differences in inattention/hyperactivity in early childhood, perhaps exacerbated by school entry laws, could be

a factor in explaining gender differences in educational outcomes, attitudes and aspirations by

early adolescence. We are particularly interested in aspirations, since, in other research, we have

found that differences in self-reported post-secondary aspirations have been the most important

factor in explaining historical changes in the relative educational outcomes of boys/girls in the

U.S. (Fortin, et al., 2012).

In order to address these questions, we now focus on a sample of 14 and 15 year old children for whom we also have complete data at 6/7. By this age, adolescents are themselves asked, with the consent of the parent, to fill out a paper and pencil survey which the Statistics

Canada interviewer promises will not be shown to the parent. Pmk’s also continue to answer

surveys about the child. We make use of both child-reported and pmk-reported data to measure

school-related outcomes.

First, we consider the issue of persistence of inattentive/hyperactive behaviour from

parent reports when the child is 6/7 to child self-reports at the age of 14/15. Specifically, we estimate by OLS:

(4) I/H14/15 i = α+ β I/H6/7 i + λ Xi + ε i

where Xi, as before, includes child gender, parental education, log family equivalent income, family structure, parent immigrant status and cycle. We report both OLS estimates and

IV estimates, in which we use Young6mosipt , indicating that the child was born in the 6 months

prior to the school-entry cut-off in that year and province, as an instrument for his/her hyperactivity score at age 6/7.

All estimates use longitudinal weights, with standard errors clustered at the province

level. As is clear from Table 6, the parent-reported score for the child at age 6/7 is a strong

predictor of the child’s own reports of his/her score at age 14/15, in both the OLS and IV

estimates. A child whose pmk-reported inattentive/hyperactive score was one point higher at age

6/7 is estimated to have a self-reported score that ranges from 0.20 (OLS) to 0.9 (IV) points

higher than his/her otherwise similar peers.

We next ask whether inattentive/hyperactive behaviour reported at age 6/7 is predictive

of other outcomes for adolescents at ages 14/15. We have chosen outcomes to reflect overall

performance at school, attitudes/behaviour, self-confidence and aspirations: 1) the pmk’s report

of the child’s over-all success at school. Specifically, the pmk is asked “Based on your

knowledge of his schoolwork, including report cards,” is [your child] doing overall?” Responses

possibilities are: Very well, well, average, poorly, very poorly; 2) The pmk’s report of whether

the child has ever repeated a grade at school; 3) The child’s report of whether he/she “does

homework when assigned:” all of the time, most of the time, some of the time, rarely or never;

4) The child assessment of whether he or she can ‘understand hard questions,’ rarely, sometimes,

often or very often; 5) “How important is it to you to get good grades?” Response categories include: Very important, somewhat important, not very important, not important at all; 6) ‘How

far do you hope to go in school,?’ with responses ranging from middle/school or junior high to

more than one university degree. Figures 8 through 13 illustrate, first, that adolescent girls have

better school-related outcomes than boys, with the exception that boys have more self-

confidence.

For each of these adolescent outcomes, we estimate:

(5) Yij = α+ β I/H6/7 i + λ Xi + ε i

where Yij is adolescent outcome j for child i and, as above, I/H6/7 i is his/her hyperactivity score

at age 6/7. We estimate specification (5) using both OLS and IV, again, using Young6mosipt as an instrument for the child’s inattentive/hyperactive behaviour at age 6/7.

Table 7 reports that inattentive/hyperactive behaviour at age six/seven is predictive of worse outcomes at ages 14/15 for all of the above outcomes, and using both OLS and IV estimation.

Since boys are more likely to have been inattentive/hyperactive before school entry, they would be more affected by being ‘young in class’ than girls. This has the potential to exacerbate the pre-existing differences between the genders early in their school careers. Given that child development is understood as a cumulative process, it is perhaps not surprising that we see negative links between early boisterous or inattentive behaviour and later attitudes toward school and post-secondary aspirations.

7. Conclusions

We find strong causal links between being young at school for Canadian children aged 4

through 9 and parent reports of inattentive/hyperactive behaviour at home and. Ours is the first

Canadian study to exploit variation across time and place in school entry cut-offs using

nationally representative data. In carrying out our analyses, we use both difference in difference and regression discontinuity research designs. Obtaining the same results using these two different research strategies is novel in the literature and strengthens our comfort in the plausibility of our conclusions. Importantly, increases are observed both for children with clinical levels of hyperactive behaviour and for those whose behaviour would classify them as well below clinical levels and, associations between being young in class and these behaviours is the same for boys and girls.

Given the longitudinal structure of our data, the National Longitudinal Survey of

Children and Youth, a contribution of our research is that we are able to control for parent reports of child inattentive/hyperactive behaviour at ages 2/3, before the children start school.

We find that being young in class exacerbates an underlying tendency toward inattentive/hyperactive behaviours, perhaps even pushing some children to clinical levels. Since boys are reported to have higher levels of inattentive/hyperactive behaviour prior to starting

school, in this sense, the problem we identify is more of a ‘boy’s’ than a ‘girl’s’ issue.

Finally, we examine the idea that higher levels of inattentive/hyperactive behaviour at age 6/7 are associated with lower academic achievements and aspirations at age 14/15; and, in particular, that differences in inattentive/hyperactive behaviour helps to explain subsequent gender differences in academic outcomes. Our data show that boys have significantly worse

24 academic performance than girls for all measures studied except self confidence. However, the size of the ‘boy’ coefficient falls considerably once we control for inattention/hyperactivity at age 6/7 (in both OLS and IV estimates. Researchers and policy makers concerned about the

‘boys’ problem’ in Canadian schools, might direct further research attention to understanding how to help very young boys make the transition into school.

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Figure 1.

Distribution of Pmk Reported Inattentive/Hyperactive Scores for Children Aged 4 to 9

.15

Density .1

.05

0 0 5 10 15 Inattentive/Hyperactive Behaviour Score Boy Girl

Figure 2. Illustration of Difference in Difference Estimation Approach. Inattentive/Hyperactive Scores for April to June Births versus October to December Births in Quebec and Ontario.

4.8

4.6

4.4

4.2 Quebec 4 Ontario

3.8

3.6

3.4 Young in QC but not ON Young in ON but not QC

Figure 3. Discontinuity in Inattention/Hyperactivity at School Start Date. Boys and Girls Aged 4 to 9.

PMK Assessed Hyperactivity Score 6 5 4 3 Mean Value 2 1 0 -10 0 10 15-Day Blocks of Age Relative to the Cut-Off Date

Note: Each circle represents the average hyperactivity score by 15-day blocks of age for all children aged between 4-11 years from 1994-2008 in the NLSCY. Relative age of zero (i.e. the middle of the x-axis) is the school entry age cut-off date for a province at a point in time when the child was 4/5 years old. The curve is predicted from a linear regression fitted on un-weighted individual observations that additionally controls for school grade, cycle dummies, province dummies and a third-order polynomial of the forcing variable (i.e days from cut-off).

Figure 4. Discontinuity in Inattention/Hyperactivity at School Start Date. Boys Compared to Girls at Ages 4 to 9.

PMK Assessed Hyperactivity Score - Boys PMK Assessed Hyperactivity Score - Girls 6 6 5 5 4 4 3 3 Mean Value Mean Mean Value 2 2 1 1 0 0 -10 0 10 -10 0 10 15-Day Blocks of Age Relative to the Cut-Off Date 15-Day Blocks of Age Relative to the Cut-Off Date

Figure 5. Distributions of Inattention/Hyperactive Scores at ages 2/3. Boys compared to Girls.

Distribution of Pre-Kindergarten Hyperactivity Score .2 .15 .1 Density .05 0

0 5 10 15 Hyperactivity Score

Boy Girl

Figure 6. Distribution of Pre-school Boys Compared to Pre-school Girls Across Hyperactivity Score ‘Quartiles’

40 35.8 35 31 30 26 24.7 25 22.5 21 19.6 20 Boys 15 Girls 15

0 Quartile 1 Quartile 2 Quartile 3 Quartile 4

Figure 7. Distributions of Birth Month, by Province

Nova Scotia

Newfoundland and Labrador .4 .4 .3 .3 .2 .2 Density Density .1 .1 0 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month of Birth Month of Birth

New Brunswick .3 Quebec

.4 .3 .2 Density .2 Density .1 .1

0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 0 Month of Birth Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month of Birth

Ontario British Columbia .4 .3 .3 .2 .2 Density Density .1 .1 0 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month of Birth Month of Birth

Figure 8.

Parent:"Based on Your Knowledge of His/Her Parent: "Has your child ever repeated a grade at Schoolwork, including report cards, how well is 7.6 school?" % your child doing overall at school?" % 8 60 49 50 6 5.4 Poorly 40 34 30 Average 29 27 30 4 20 Well 20 Very Well 2 7 10 4 0 0 Boys Girls Boys Girls

Child: "How often do you do homework when it Child: "How often can you understand hard is assigned? % questions?" % 33 45 41 35 39 40 38 30 27 35 Never 31 Rarely 25 22 30 Rarely 20 17 25 22 Sometimes 15 Some of 20 Often 14 the time 15 10 7 Most of 8 Very Often 4 5 10 6 5 the time 112 5 0 0 Boys Girls Boys Girls

Child: "How important is it to you to get good Child: "How Far Do You Hope to Go in School? % grades? " % 80 60 70 66.7 48 58.4 50 Jr. High 60 Not 39 HS important 40 50 at all Not very College 36.6 29 40 important 30 28 30.6 Univ 22 30 Somewhat 19 important 20 2+ 20 Degrees Very 10 10 important 10 6 4.4 2.5 0.6 0.3 11 0 0 Boys Girls Boys Girls

Table 1. Cut-Off Dates for Entry into Kindergarten in 8 Provinces and School Boards/CMAs of Alberta and Saskatchewan (1994 to 2008) September 1 September October November December December 31 January Last Day March 1 30 31 30 1 31 of February

Quebec PEI PEI Manitoba British PEI Alberta - Alberta Alberta – Nova Scotia (2005 (2004) (1994- Columbia (1994- Medicine Edmonton Calgary PEI (2006) and 1996) Ontario 2002) Hat Saskatchewan 2008) (7 school boards/CMAs)

Manitoba (1997-2000) New Brunswick Newfoundland and Labrador Alberta – Lethbridge – Red Deer – Lloydminster – Grande Prairie – Wetaskiwin Note: 1. 7 school boards/CMAs in Saskatchewan include Regina –Regina District School Division, Yorkton – Yorkton School Division, Moose Jaw – Moose Jaw School Division, Swift Current – Swift Current School Division, Saskatoon – Saskatoon District School Division, North Battleford – Battleford School Division, Prince Albert (cannot be linked with any school division, judging from the name so is not used in the analysis), and Estevan – Estevan School Division.

Table 2. Difference in Difference Estimates of the Effect of Being ‘Young in Class’ on Inattentive Behaviour at 4/9 for Children in Public Schools. Boys+Girls Boys Girls (1) (2) (1) (2) (1) (2) Mean Score 4.099 4.615 3.562 (St Deviation) (3.030) (3.157) (2.792) Young in Class 0.431*** 0.403*** 0.404*** 0.432*** 0.462*** 0.380*** (0.062) (0.030) (0.099) (0.084) (0.040) (0 .046) Boy 1.072*** 1.065*** -- -- (0.039) (0.030) Log Equivalent -0.219*** -0.219*** -0.218*** Household Income (0.052) (0.052) (0.063) Pmk University -0.671*** -0.615*** -0.737*** (0.071) (0.089) (0.104) Pmk College -0.311*** -0.226 -0.408*** Diploma (0.083) (0.197) (0.122) Pmk High School -0.242** -0.239 -0.254** (0.103) (0.213) (0.096) Step Family 0.711*** 0.788** 0.633*** (0.105) (0.213) (0.104) Lone Parent 0.488*** 0.581*** 0.387*** Family (0.085) (0.101) (0.096) Pmk Immigrant -0.312*** -0.410*** -0.212* (0.063) (0.081) (0.097) Child Age in 0.059** 0.029 0.041 0.016 0.080*** 0.043* Months (0.022) (0.019) (0.026) (0.017) (0.023) (0.022) Child Age in -0.0003** -0.0002 -0.0002 -0.0001 -0.0004*** -0.0003** Months Squared (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)

Number of 30970? 34500 15656 17454 15314 17046 Observations These models also include but do not report NLSCY cycle. Robust standard errors clustered at the provincial level are reported in parentheses. *** indicates statistically significant at 1 percent; ** indicates statistically significant at 5 percent; * indicates statistically significant at 10 percent. Note that the 'young' coefficient is robust to alternative specifications (linear and cubic) for age in months.

Table 3. Robustness Checks for DID Estimates of Being Young in Class on Inattentive Behaviour at 4/9. Excluding Children on Ritalin Excluding Children in Top Decile of Boy + Girl Inattentive Score Boys + Girls Boys Girls Boys + Girls Boys Girls Young 0.373*** 0.319*** 0.431*** 0.202** 0.128* 0.272*** (0.053) (0.079) (0.039) (0.067) (0.068) (0.077) Boy 0.964*** 0.673*** (0.031) (0.062) Number of 30402 15219 15183 28462 13952 14510 Observations

Including Children Not in Public School Restricting to Longitudinal Data to Control for System Attendance at Structured Daycare or Junior Kindergarten at Age 3/4 Boys + Girls Boys Girls Boys+Girls Boys Girls Young 0.425*** 0.387*** 0.472*** 0.364*** 0.337*** 0.400*** (0.053) (0.114) (0.032) (0.065) (0.093) Boy 1.066*** 1.086*** (0.037) (0.067) Attended Junior ------0.035 0.021 -0.078 K at Age 4-5 (0.065) (0.066) (0.105) Attended Formal ------0.341*** 0.318* 0.372** Daycare at 4/5 (0.098) (0.167) (0.116) Number of 32366 16377 16029 28152 14218 13934 Observations These models also include but do not report child age and age squared family income, parental education, family structure, immigrant status and NLSCY cycle. Robust standard errors clustered at the provincial level are reported in parentheses. *** indicates statistically significant at 1 percent; ** indicates statistically significant at 5 percent; * indicates statistically significant at 10 percent.

Table 4. Regression Discontinuity Estimates of the Effect of Being ‘Young in Class’ on Inattentive Behaviour of Boys+Girls at Age 4/9. All Excluding Excluding Including Controlling for Boys+Girls Children on Children in Children Not Attendance at Ritalin Top Decile of in Public Daycare or Junior Score School Kindergarten at Age 3/4 2-month window Mean Score 4.105 3.991 3.479 4.080 4.133 (St Deviation) (3.063) (2.954) (2.379) (3.058) (3.040) Young in Class 0.481** 0.431* 0.216 0.502* 0.150 (0.237) (0.222) (0.192 (0.237) (0.231) Boy 1.007*** 0.879*** 0.620*** 0.961*** 0.914*** (0.108) (0.106) (0.090) (0.110) (0.113) + Covariates x x x x x Number of 10156 9966 9286 10626 9125 Observations 3-month window Mean Score 4.085 3.975 3.466 4.068 4.109 (St Deviation) (3.067) (2.951) (2.369) (3.054) (3.044) Young in Class 0.540*** 0.437** 0.231 0.573*** 0.292 (0.198) (0.188) (0.154) (0.198) (0.195) Boy 0.962*** 0.847*** 0.605*** 0.932*** 0.947*** (0.088) (0.089) (0.075) (0.088) (0.092) + Covariates x x x x x Number of 15464 15174 14175 16189 13885 Observations These models also include f(bdi-ci), in a linear specification, grade, in a cubic specification, child gender, family income, parental education, family structure, immigrant status as well as province and NLSCY cycle. Robust standard errors clustering at distance from the cut-off are reported in parentheses. *** indicates statistically significant at 1 percent; * indicates statistically significant at 10 percent.

Table 5. Difference in Difference Estimates of the Effect of Being ‘Young in Class’ on Inattentive Behaviour at 4/9. Controlling for Hyperactive/Inattentive Behaviour at 2/3. (2) (3) (4) (5) Mean Score 4.115 4.115 4.115 4.115 (St Deviation) (3.036) (3.036) (3.036) (3.036) Young in Class 0.364*** 0.315*** 0.319*** 0.264* (0.084) (0.077) (0.079) (0.111) Boy 1.090*** 0.906*** 0.938*** 0.936*** (0.083) (0.073) (0.076) (0.074) Inattentive Score at 2/3 -- 0.400*** -- -- (0.004) Quartile of Inattentive Score at 2/3 Second -- -- 0.923*** 0.990*** (0.072) (0.169) Third -- -- 1.624*** 1.520*** (0.077) (0.075) Top -- 2.850*** 2.526*** (0.059) (0.105) Quartile X Young Interactions Second X Young ------0.132 (0.172) Third X Young ------0.041 (0.121) Top X Young ------0.448*** (0.145) + Covariates x x x x Number of Observations 25842 25842 25842 25842 These models also include but do not report child age and age squared family income, parental education, family structure, immigrant status and NLSCY cycle. Robust standard errors clustered at the provincial level are reported in parentheses. *** indicates statistically significant at 1 percent; ** indicates statistically significant at 5 percent; * indicates statistically significant at 10 percent.

Table 6. Estimates of Implications of Parent-Reported Inattentive Behaviour at 6/7 for Self-Assessed Inattentive Behaviour at Age 13/14. Boys+Girls. Using 'Young in Class' as IV. OLS OLS IV Mean Score 3.919 3.919 3.919 (St Deviation) (2.892) (2.892) (2.892) Inattentive Behaviour at 6/7 -- 0.189*** 0.898** (0.027) (0.323) Boy 0.358*** 0.174*** -0.512* (0.030) (0.030) (0.254) These models also include but do not report child age and age squared family income, parental education, family structure, immigrant status and NLSCY cycle. Robust standard errors clustered at the provincial level are reported in parentheses. *** indicates statistically significant at 1 percent; ** indicates statistically significant at 5 percent;* indicates statistically significant at 10 percent.

Table 7. Estimates of Implications of Inattentive Behavour at 6/7 for Outcomes at Age 14/15. Boys+Girls. Using 'Young in Class' as IV. Parent-Reported Educational Success Ever Repeated a Grade at School OLS OLS IV OLS OLS IV Mean Score 4.065 4.065 4.065 0.065 0.065 0.065 (St Deviation) (0.943) (0.943) (0.943) (0 .247) (0 .247) (0 .247) Inattentive -- -0.073*** -0.268* -- 0.014 0.079* Behaviour at 6/7 (0.004) (0.099) (0.007) (0.040) Boy -0.329*** -0.255*** -0.068 0.028** 0.011 -0.051 (0.026) (0.025) (0.124) (0.009) (0.006) (0 .044) Self-Reported ‘I Do Homework when Self-Reported ‘I Can Understand Hard Assigned’ Questions’ OLS OLS IV OLS OLS IV Mean Score 5.152 5.152 5.152 2.687 2.687 2.687 (St Deviation) (1.051) (1.051) (1.051) (0.850) (0.850) (0.850) Inattentive -- -0.037*** -0.401*** -0.024** -0.292** Behaviour at 6/7 (0.008) (0.092) (0.008) (0.115) Boy -0.256*** -0.217*** 0.202* 0.188** 0.219*** 0.474*** (0.055) (0.058) (0.108) (0.060) (0.060) (0.111) Self-Reported Importance of Getting Self-Reported Educational Aspirations Good Grades OLS OLS IV OLS OLS IV Mean Score 2.584 2.584 2.584 3.838 3.838 3.838 (St Deviation) (0.580) (0.580) (0.580) (0.905) (0.905) (0.905) Inattentive -0.005 -0.136** -- -0.031*** -0.254** Behaviour at 6/7 (0.007) (0.044) (0.005) (0.095) Boy -0.112*** -0.107*** 0.025 -0.279*** -0.232*** 0.002 (0.014) (0.009) (0.023) (0.017) (0.019) (0.096) These models also include but do not report child age and age squared family income, parental education, family structure, immigrant status and NLSCY cycle. Robust standard errors clustered at the provincial level are reported in parentheses. *** indicates statistically significant at 1 percent; ** indicates statistically significant at 5 percent; * indicates statistically significant at 10 percent.

Appendix Table 1. Example of Provincial Variation in Construction of ‘Young’ Variable for Difference in Difference Estimates. September 1 September October 31 December End March 1 30 31 February Calgary Quebec and PEI BC, SK, Medicine Edmonton Nova Scotia MB, ON, Hat NB, NL, Other AB January Young Young February Young Young March Young April Young Young May Young Young Young June Young Young Young July Young Young Young Young August Young Young Young Young September Young Young Young Young Young October Young Young Young Young November Young Young Young December Young Young Young Note: This example table using the most recent school cut-off dates. As noted in Table 1, some changes in school cut-off dates have taken place during our study period.

Appendix Table 2. Rates of Non-Compliance with School Entry Regulations. Children in Grades K through 4. Boys + Girls Boys Girls Newfoundland % 2.6 2.9 2.3 PEI % 0.0 0.0 0.0 Nova Scotia % 2.0 2.3 1.7 New Brunswick % 2.7 2.8 2.6 Quebec % 1.5 1.5 1.4 Ontario % 2.6 2.4 2.7 Manitoba % 2.3 1.5 3.0 Saskatchewan % 0.0 0.0 0.0 Alberta % 0.0 0.0 0.0 BC % 2.4 3.0 1.6