Long Run Outcomes of Child Labor

Stephanie Chapman∗

November 2, 2015

Abstract

In this paper I estimate the long term individual effect of child labor using a linked cen-sus sample from 1900 and 1910 to 1940. The sample consists of over 730,000 males fromthe US birth cohorts of 1884 to 1904. To solve the fundamental identification problem thatstarting work later implies higher school achievement under compulsory education laws, I usea difference in difference strategy to exploit both changes in minimum working age laws andcompulsory school start ages across 14 states. I find that the effect of starting work a year earlier- controlling for missed school - is an increase of $8 of annual income in 1940. While modest,this effect is roughly the same as the marginal benefit of an extra year of school controlling forage of allowed labor market entry. This implies that families during this time period were likelyoptimally allocating the time of work eligible children between work and school. To conclude,I discuss the implications of this research for modern policy design aimed at eradicating childlabor in developing countries. In particular, modern policy must account for the benefits ofwork to children if they intend to improve the welfare of those children.

1 Introduction

As many as 20% of American children aged 10-14 were gainfully employed in various indus-

tries in the late 19th and early 20th centuries, and while much has been done to study the short

term determinants and effects of child labor in modern developing nations, the long term ef-

fects of working as a child have not yet been examined. The rhetoric surrounding the effort to

abolish child labor in the early twentieth century focused on the detrimental effects of work-

ing, particularly missed school attendance and negative health outcomes, though it is not clear

∗I gratefully acknowledge assistance and comments on this paper from Matthias Doepke, Diane Schanzenbach, LeeLockwood, Seema Jayachandran, Lori Beaman, David Figlio and participants in the 501 graduate student seminar. Myparticular thanks go to Joe Ferrie for his assistance with the US census files and for many helpful comments. All errorsare mine.

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whether these fears were well-founded. If work were a response to extreme poverty, children

may be better off working than they would have been otherwise.

In this paper I develop an empirical strategy to separately identify the confounded effects of

working as a child and completing less education as a result of starting work earlier. Between

1880 and 1910, most states in the US implemented and/or changed both child labor and com-

pulsory schooling laws. Since compulsory entry ages and minimum working ages both change

the amount of education a child was required to receive, but only the latter changed both the

amount of education and work experience ex-post, they can be combined to produce separate

estimates of the effect of an extra year of school and an extra year of work experience on labor

market productivity in the long term. To this end I collected a panel of compulsory entry ages

and minimum working ages from several sources, both contemporary and historical.

Using a census sample linked from initial observations in 1900 and 1910 to outcomes in

1940, I demonstrate that once education is adequately controlled for there is a benefit to starting

work at a younger age. In fact the reduced form increase in income from an additional year

of legal work, holding schooling constant is about $7-$8 of annual income. The reduced form

effect of an extra year of schooling, holding work start age constant, is about $5-$7 of annual

income. While these effects are quite small, they are remarkably significant considering the

effects are observed when individuals are in their prime working years, between the ages of 40

and 60. These estimates also imply that children - or their parents - may have been rationally

allocating their time, inasmuch as the long term estimates of the impact of an extra year of

education is roughly equal to the long term impact of an extra year of schooling.

The question of what lasting effects child labor may have and through which channels those

effects operate is not just a question of historical curiosity, but also one of interest to modern

policy makers. Concern has been growing over child labor in developing nations (Edmonds

2007), but little work can be done on long run outcomes due to the fundamental data limitation

that in order to examine long run outcomes, the researcher must observing individuals long

after their work and schooling decisions have been completed. In this paper I speak to the mod-

ern policy questions about child labor by addressing the long term individual consequences of

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restricting child labor. The results of this paper reveal that allowing children to work at younger

ages may have long term benefits for their labor market productivity. In particular, these results

indicate that simply outlawing child labor may have negative long term consequences at the in-

dividual level, beyond the negative general equilibrium consequences outlined in the theoretical

literature on this topic (Doepke and Zilibotti 2005; Basu and Van 1998).

This paper proceeds as follows. Section 2 will address the historical background, the liter-

ature in this field and how this project fits into the literature. Section 3 discusses the potential

theoretical effects that working at young ages may have on children, as well as discussing the

channels of those effects. Section 4 describes the data that will used and section 5 outlines the

identification strategy. Section 6 describes and interprets the results, while section 7 concludes

by describing the relevance of these results for the modern policy debate over child labor, and

by describing future avenues of research.

2 Literature Review

It was not until the late nineteenth century that child labor in the US came to be seen as detri-

mental to children. In colonial America the virtues of hard work at all ages were extolled, and

children were encouraged to contribute to the family economy at as early an age as possible.

Early textile mills and factories in New England were largely staffed by women and children,

while men tended the family farms. A shift occurred in the national consciousness, however,

as children were more frequently employed outside the home away from their parents, and as

the jobs they performed were perceived as becoming more dangerous (Abbott 1908). When

the 1900 census showed an increase from the previous census in the number of children aged

10-14 engaged in gainful occupations, activists mobilized to lobby for child labor legislation

across the country, founding the National Child Labor Committee in 1904 (Hindman 2002).

Speaking to the questions plaguing many activists at the time, Moehling (2004) uses US

data from Bureau of Labor Statistics household surveys 1917-1919 to show that families with

working children and young adults (ages 10-24) had different expenditure patterns relative

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to households with fewer or without working children, demonstrating that children may have

enjoyed individual monetary benefits of working at young ages even though wages were largely

turned over to parents each pay period. This paper suggests support for positive income effects

impacting working children.

Most states passed or changed their child labor laws between 1880 and 1920. The extent

to which those laws were effective remains an empirical question, though it has been exam-

ined by several authors in recent times. Moehling (1999) demonstrates that child labor laws

(specifically, newly implemented minimum working age requirements) did not contribute to

the long-term decline in the rate of child labor, though she examines only one parameter of the

laws, and gives no particular attention to determining which laws may have been enforced. It is

clear that some of the laws were never intended to be enforced, but rather passed in reaction to

and in order to appease the national child labor movement. For instance, the legislation passed

in North Carolina was written and presented to the legislature by the textile manufacturers, the

chief employer of minors in that state (Hindman 2002). In support of the effectiveness of labor

laws passed during this period Puerta (2011) uses manufacturing data from the early 20th cen-

tury to show that industrial growth of the glass industry - historically dependent on child labor

- is lower in states with more restrictive child labor policies in the Ohio River valley, though

the extent to which this is due to endogenous choices of manufacturers is unclear.

Margo and Finegan (1996) demonstrate using laws during this period that compulsory ed-

ucation laws were only statistically effective in states with compatible labor laws. The finding

that compatible education and labor laws produce a binding constraint on behavior is replicated

by Angrist and Acemoglu (2000) and Moehling (1999), implying that the labor laws were more

binding than their counterparts requiring school attendance. Another possible interpretation is

that these laws were more effectively enforced in states in which laws were designed to be

compatible.

Recent papers have challenged the validity of previous studies of compulsory schooling

laws, repeating the analyses with different empirical approaches, or higher quality data. Clay,

Lingwall and Stephens (2012) find that compulsory schooling laws had a significant impact on

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schooling and income using similar data to mine, though only looking at the introduction of

new schooling laws rather than marginal changes in the laws. They find that laws introduced

between 1880 and 1927 had a significant impact on enrollment and attendance, and they find

using 1940 census data that laws introduced between 1898 and 1927 had a significant impact

on schooling achieved and earnings, outcomes I also examine. They estimate the return to

an additional year of schooling induced by these changes to be 8-10%. Stephens and Yang

(2014), however, challenge the results of previous papers using a “common trends” assumption

at the national level to identify the effects of changing compulsory education and child labor

laws using the 1905 to 1954 birth cohorts. They find that including region-specific time trends,

rather than national time trends, eliminates many of the returns to education implied by previous

research, suggesting that the gains found were a result primarily of unobserved regional trends,

rather than of schooling itself as was previously thought. For the analysis presented in this

paper I use primarily regional data, so this concern should be ameliorated.

Empirical studies using modern data focus primarily on the determinants of supply of child

labor, for instance showing that families in Ecuador will respond to cash transfers by reduc-

ing the labor supply of children by more than the value of the transfer (Edmonds and Shady

2012). Several authors have examined the tradeoff between work and school, concluding that

for most children in their studies, work and school (or studying at home) are not strong substi-

tutes (Akabayashi and Psacharopoulos 1999; Ravallion and Wodon 2000; Basu, Das and Dutta

2010), though in each of these studies complementary compulsory school laws were not in

place. While I will assume in this paper that there is a strict tradeoff between work and school,

in each of the states examined there are overlapping minimum working age and compulsory

schooling laws. As such, my estimates will be of the effect of delaying labor market entry by

an additional year when the legal environment necessarily requires that year be spent in school.

This will be useful in the modern policy debate, as long as any policy aimed at reducing child

labor also involves measures towards encouraging or mandating school attendance.

Interestingly, Ravillion and Wodon (2000) and Basu, Das and Dutta (2010) conclude from

their results that parents are rationally allocating their chilren’s time, a finding that I will repli-

5

cate in the long term to the extent that I find that the returns to an additional year of school and

the returns to an additional year of work are statistically indistinguishable.

Very few studies have yet examined the individual outcomes of child labor, and even fewer

attempt to examine long term outcomes. Beegle, Dehejia and Gatti (2009) examine the out-

comes of children after five years, and find that while children who worked are less likely to

still be in school and have achieved less education than their peers, they are twice as likely to

be working for wages. In their setting of rural Vietnam working for wages1 is associated with a

higher standard of living within the village, indicating that after five years, children who were

working initially are better off than their peers. They interpret these results as demonstration of

positive returns to work experience, though it is not clear to what extent the results are driven

by a natural age-income profile or by sample selection.

The paper in the development literature most closely related to this study examines long

term effects of child labor on adult income using survey data from Brazil that contains the

self reported labor market entry ages of adult men (Emerson and Souza 2007). They find

that there is a detrimental effect of starting work at young ages, but that at the entry age of

about 12 the effect reverses, and starting work earlier is beneficial later in life. This paper

is closely comparable to mine, however their approach is not as clean as my identification

strategy, as they simply make use of covariates to control for heterogeneity among individuals

in the determinants of their labor supply as children.

My paper will add to the current literature by examining heretofore difficult to asses long

term outcomes and by employing a novel strategy to cleanly identify whether children working

the US in the early part of the twentieth century were positively or negatively affected by their

work as children. In doing so I will add to the literature on compulsory education and child

labor in the US by providing an estimate of the returns to education and the returns to early

work experience. I will also contribute to the modern policy debate surrounding child labor in

developing countries by providing an estimate of the relative importance of school versus work

for those children who are most vulnerable. This information will inform policy makers of the

1as opposed to being a self-employed farmer

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types of policies that should be adopted to optimally affect the long term welfare of impacted

children.

3 Theoretical Background

It is not ex-ante clear whether banning child labor would result in improved long run outcomes

for the child, particularly when children are often working as a reaction to poverty experienced

by the family. The negative effects of child labor are well understood, though perhaps not as

well documented. Because of the time allocation problem of the child, a choice must be made

between school, work and leisure, so more work necessarily means less school or less leisure

time. Working will be detrimental to the child to the extent that he is missing school, or missing

leisure time that might be fundamental to childhood experiences. Additionally, if he is sent to

work in a dangerous job, there may be some long term negative effects such as diminished

labor capacity from severed limbs or injured lungs.

The positive effects of working are less obvious, but could perhaps be stronger than the

negative effects. There is a pure income effect from working: more labor means more income

and thus more consumption in the household. In the contexts in which child labor is debated,

families are often suffering from extreme poverty. While policy makers are well-intentioned,

on that margin families may be making a choice between sending a child to work and everyone

in the family eating, or sending that child to school and sacrificing the subsistence level of

consumption the income from the child would have brought to the family. Even if the family

made the hard decision to send a child to school despite the income loss, there are documented

connections between malnutrition and cognitive performance. Attending school under such

circumstances would likely have diminished the returns to education relative to the baseline

of an appropriately nourished child, which could have long run implications for the child’s

productive capacity.

If income effects dominate, it is also possible that there are strong spillover effects within

the household. It is documented empirically that children who were working during the time

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period I study turned most of their earnings over to their parents (Moehling 2004). While the

children retained some private value from their earnings, most of the benefit was likely enjoyed

at the household level, thus the work of one child would positively impact the rest of the (non-

working) household members. In this way, the benefit to a single child of working at a young

age is an underestimate of the social value the work could generate, particularly within the

framework of the household.

Beyond the pure income effects, there could be returns to work experience for the child that

could benefit him in the long run. This latter effect may especially be true of particular kinds

of work, such as apprenticeships. Finally, given that child labor is a household level decision,

it could be the case that there is selection among children in the household, and that those who

are employed at young ages are exactly those who would no longer benefit from additional

years of schooling. If this is the case, those children would certainly be better off continuing to

work rather than attending school. The ambiguity of theoretical channels through which labor

as a child may affect children highlights the need for an empirical study of these questions.

4 Data

Several sources are leveraged to develop the data set used in this project. The population of

boys in the US birth cohorts of 1884 to 1904 are linked based on their names, birth state and

birth years to match observations in 1900 and 1910 to outcomes in 1940, resulting in a sample

aged 36-56 in 1940. The IPUMS representative sample of the 1910 census is used to construct

county level control variables. Finally, the education and labor laws are collected from a variety

of sources in order to identify exogenous shifters of individual school going and labor market

entry behavior.

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4.1 Linked census samples

The linked census samples are constructed based on mathching the first and last names of each

individual as well as their state and a fuzzy match on their year of birth2. This results in over

700,000 observations. The 1884 to 1900 birth cohorts are taken from the 1900 to 1940 linkage,

while the remaining birth cohorts of 1901 to 1904 are taken from the 1910 to 1940 linkage. For

the purposes of this paper I will restrict the sample to those observed in fourteen states in the

upper Midwest and New England in their childhood3.

There is some evidence that the linking process results in a sample that is generally more

well-off than a representative sample would be. The most likely explanation for this bias in the

linking process is that those who were members of more literate and wealthy families in 1900

are more likely to have consistent data reported in the 1900 and 1940 censuses, and are thus

more likely to be matched and thus observed in this data set. If anything, this bias will work

against me because those that are most likely to have benefited from starting work at an earlier

age - those from poorer families in 1900 and in 1910 - are more likely to not be observed in my

sample.

There are over 730,000 individuals living in the fourteen states used to this analysis in 1900

and 1910 with non-missing income observations in 1940, which represents about 10% of the

total male population of the appropriate ages in the selected states. The median individual in

this data set has an eighth grade education, while over 95% have at least a fifth grade education

(of those that report education achieved by 1940). The upper quartile of reporting individuals

have 12 years of education while the top 10% report 16 years of school, or a college education.

The median individual reports $1000 of annual income in 1940, though a significant proportion

of individuals (approximately one third) report zero income. 99% of individuals report income

less than $5000, while 99.9% report income less than $10,000. To reduce the incidence of

extreme outliers, I drop observations greater than $10,000.

2up to +/- two years of their year of birth reported in 19403Those states are: Connecticut, Maine, Massachusetts, Rhode Island, Vermont, New Hampshire, New York, New

Jersey, Pennsylvania, Michigan, Indiana, Illinois, Wisconsin and Ohio

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4.2 IPUMS samples - County level variables

Representative samples of the US censuses have been digitized for public use. I used the 1910

IPUMS 1% sample to construct a percent urbanization and percent farm variable at the county

level to be used as control variables. Because the minimum working age laws were directed

specifically at non-farm occupations such as manufacturing, it is likely that more urbanized

counties will be differentially affected by the changing labor laws.

4.3 Education and labor laws

Data on education and labor laws are collected from four different sources. Information on

child labor laws, the minimum ages they implied, the years in which they changed and the fines

that they allowed is available in a spreadsheet compiled by Rebecca Holmes and published on

the website of Price Fishback. Ogburn (1912) contains information on whether the laws present

in each of the states included a provision for any sort of enforcement of the law, including a

categorization of the types of officials that are empowered to enforce the laws.

In all fourteen of the states examined here, the labor laws provided for special inspectors

and/or truant officers that were empowered to enforce both the child labor legislation and the

education legislation. I have used this information to define states that have “strong” labor laws

as those which have laws that provide both for fines and some sort of inspection or enforcement

of the law. It is clear both from current research and from contemporaneous accounts that

the effectiveness of the laws passed in this period differed widely across states, which could

contribute to the findings so far that child labor laws contributed little to the long run decline in

child labor over the first half of the twentieth century.

For the school entry ages required from 1880-1899, I used selected reports of the Depart-

ment of Education from 1885-1905. These reports were compiled by the Department of Ed-

ucation on a yearly basis, though the salient compulsory education ages were not reported by

state in all years. In order to fill in the gaps, I assumed that if two reports listed the same entry

ages in non-contiguous years and those years were sufficiently close together4, there were no

4In particular I was able to find reports of the compulsory entry ages at roughly three year intervals.

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changes in the laws in the intervening years. I added to this panel the school entry ages avail-

able in the data on Claudia Goldin’s website. Although some states had compulsory schooling

laws that specify school leaving ages inconsistent with the minimum working ages, I assume

throughout that the minimum working ages are the binding legal variable. A common theme

in the literature on compulsory schooling laws during this period (Margo and Finegan, 1996;

Angrist and Acemoglu, 2000) is that compulsory schooling laws were only effective in states in

which they were paired with an age compatible labor law, implying that the binding constraint

on school leaving was the outside option of the student rather than the legal imperative to stay

in school.

From these data I distill a number of variables. Given the year each law was passed and

the provisions of those laws, I assign to each child the minimum working age and the required

school entry age to which they were subjected. For instance, if a child turned 13 the year a state

changed their minimum working age from 12 to 13, I consider his relevant minimum working

age to be 12, rather than 13. From those two variables I calculate the required years of school

for each child as the difference between the minimum working age and the required school

entry age. If there is no minimum working age, I consider the required years of school to be

zero, even if there is a compulsory schooling law in the state at that time.

Table 2 lists the states included in my sample and features of their minimum working age

laws, while table ?? lists the states included and features of their compulsory school entry age

laws. In particular I will use fourteen states in New England and the Upper Midwest to iden-

tify the effects: Connecticut, Maine, Massachusetts, Rhode Island, Vermont, New Hampshire,

New York, New Jersey, Pennsylvania, Michigan, Indiana, Illinois, Wisconsin and Ohio. Of

these fourteen states, all had preexisting minimum working age requirements and compulsory

schooling laws, so all of the variation is generated from marginal changes in the minimum

working ages and mandatory entry ages. The minimum working ages range from 10-15, while

the compulsory entry ages are either 7 or 8. Of the fourteen states considered, 10 changed their

minimum working ages (Maine, Massachusetts, New Hampshire, Rhode Island, Vermont, New

Jersey, Pennsylvania, Michigan, Ohio and Wisconsin) while 5 changed their compulsory en-

11

trance ages (Connecticut, Maine, New York, Indiana and Michigan). The maps in figures 3 and

4 summarize this information. Note that of the states that changed their laws, only 2 changed

both laws in the time period examined (Maine and Michigan), and there was a delay between

the passage of the two laws, so there are cohorts in each state differentially affected by the two

different laws5.

5 Identification

The fundamental identification problem in examining the long run outcomes of child labor is

two-fold: identifying the effect of starting work sooner and identifying the effect of staying in

school longer. To the extent that joint compulsory school and child labor laws were coordinated

enough to induce a choice between work and school only rather than work, school and leisure,

the choice of whether to start work earlier involves a direct tradeoff between more work and

less school. To address this problem, I will use two sources of variation: changes in minimum

working ages and changes in compulsory school entry ages. Changes in the former induce

variation in both amount of school attained and labor market entry age, while changes in the

latter induce variation in schooling achieved only. Several other papers use similar sources of

variation (Lleras-Muney 2002, 2005; Acemoglu and Angrist 2000), though none during this

time period or in the same way as I use them.

5.1 Intuition: Case of CT and MA

For intuition, consider the case of Connecticut and Massachusetts. In 1902 both states altered

one of those two margins. Connecticut lowered their compulsory entry age from 8 to 7, while

Massachusetts raised their minimum labor age from 13 to 14 in the same year. This situation

is illustrated in figure 1. Children born prior to 1888 in both states were subject to six years

of compulsory schooling, in Connecticut between the ages of eight and fourteen and in Mas-

sachusetts between the ages of seven and thirteen. These children will serve as a control group.

5Maine changed the minimum working age in 1907, and the school entry age in 1902, while Michigan changed theminimum working age in 1885 and the school entry age in 1904

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Although the laws are changed in the same year, different birth cohorts are affected since more

children will have aged out of being affected by the change in the compulsory entry age in

Connecticut, while older children will still be affected by the change in the minimum working

age in Massachusetts. For children born between 1888 and 1895, those in Massachusetts will

be subject to seven years of compulsory schooling, while those born in Connecticut will be

subject to six years of compulsory schooling. Comparing these children to those in the control

group (born prior to 1888), would give the confounded estimate of both the effect of an extra

year of school and the effect of starting work a year later, since the difference being identified

is the difference between a child getting six years of education in Connecticut throughout the

time period with a child in Massachusetts getting six years of education in the pre-period, but

seven years of education in the post-period by virtue of the fact that he is starting a year later.

This can be seen clearly in the first panel of figure 2, which shows the symbolic represen-

tation of comparing the birth cohort of 1887 with the birth cohort of 1891. In this diagram, the

α’s are state fixed effects and the β ’s are birth cohort fixed effects. δ is the marginal effect

of starting work a year later only (separate from the effect of an extra year of school), while

γ is the marginal effect of getting an extra year of education. If we difference across the two

columns of this diagram, we eliminate the birth cohort fixed effects, and if we difference down

the rows of this diagram we eliminate the state fixed effects. What is left is the marginal effect

of starting work a year later (δ ), confounded with the marginal effect of gaining an extra year

of school (γ). This illustrates the fundamental identification problem with studying changes in

child labor laws only: delaying labor market entry by a year necessarily increases educational

attainment by a year, to the extent that children are required to be in school at the early teen

ages if they are not working. As a result, another source of variation in compulsory years of

education is required to separately identify the effect of starting work a year later and the effect

of requiring an additional year of schooling.

Looking at children born after 1895 gives us a way to look at the effects of these two

margins separately. Notice in figure 1 that all children born after 1895 in both Connecticut

and Massachusetts are subject to seven years of compulsory education, but how the two states

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arrived at seven years of education from six occurs on different margins. Comparing children

born in 1896 to those born in 1891 uncovers the pure marginal effect of an extra year of school.6

The diagram detailing the difference in difference estimates can be seen in the second panel of

figure 2. Here we see that when differencing across columns and rows, we are left with γ only,

the marginal effect of an additional year of schooling.

In principle, we could then take a third difference across these two sets of cohorts to elim-

inate the effect of an extra year of schooling, leaving only the effect of starting work a year

later. In practice, this is the same as comparing the birth cohort of 1896 to the birth cohort of

1887 directly, as can be seen in the third panel of figure 2. In this case, differencing across the

columns eliminates both birth cohort fixed effects and the effect of schooling, since children

in both states during each time period are subject to the same amount of education (six years

in 1887 and seven years in 1891). Differencing across the rows then eliminates the state fixed

effects, leaving only the estimate of the effect of starting work a year early, independently of

the effect of gaining an extra year of school.

5.2 Full Empirical Model

There is considerable cross-state and time series variation in these laws during this time period,

so this approach can be expanded to include more states. In particular I am considering birth

cohorts from 1884 to 1904, who would have been affected by educational law changes from

roughly 1890 to 1910, and labor law changes from 1898 to 1918 or so. Of the 49 relevant

legal divisions present in the Union during this time period (45 states, 3 territories and the

District of Columbia in 1900), 36 passed laws regarding their minimum labor age laws, 22 of

which induced marginal changes in the minimum legal working age (i.e. raising or lowering

the existing threshold rather than implementing a minimum age where there previously was

none). There was a similar volume of activity in compulsory schooling laws, with 24 states

passing laws relevant to compulsory entry ages, 10 of which were marginal changes.

6This assumes that the benefit of an extra year of school at the beginning of the school career is roughly equivalentto the benefit of an extra year of school at the end of the school career. During this time period I find this a plausibleassumption, though I will discuss it in greater detail in subsequent sections

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To replicate the difference in difference approach described over several observational units,

I will use state and birth cohort fixed effects with two policy- related independent variables. The

first is the minimum working age relevant to each group at the cohort × state level, denoted

by MLAst . The coefficient on this variable (δ below) will give the marginal effect of delaying

labor market entry by one year, independently of the effect of attending school for an additional

year. The second is the compulsory years of schooling variable discussed above, denoted by

CY Sst , namely the difference between the minimum working age and the compulsory school

start age relevant to each individual. The coefficient on this variable (γ below) will give the

marginal effect of an additional year of compulsory schooling only. Both of these estimates

are specific to those who are induced to change their behavior by the change in the law. The

relevant empirical specification is then

yist = αs +βt +δMLAst + γCY Sst +X ′istλ + εist (1)

where αs are state level fixed effects, βt are birth cohort fixed effects and the vector Xist contains

possible individual level control variables. In this paper I will use income in 1940 and highest

grade achieved by 1940 as outcome variables. Throughout I will assume that minimum working

age laws were more binding than school leaving ages, so the years of compulsory schooling

will be the difference between the compulsory school entry age and the minimum legal working

age.

For this approach to be valid, I make several assumptions about the structure of the problem.

First is the general “common trends” assumption made in all difference in difference specifica-

tions, that any trends seen at the birth cohort level are common across all states studied. While

there is some evidence that this may not nationally be true in this setting, there is evidence that

it is true regionally (Stephens and Yang 2014) and in this paper I will use only regional data

from New England and the upper Midwest.

I assume that the age-income profile of individuals is common across states and cohorts,

that is, that the underlying function transforming education and work experience into income

in 1940 is not specific to either the state or birth cohort. Additionally I assume that there is no

15

income effect of staying at home longer when younger, and that an extra year of school gained

at younger ages has the same marginal benefit as an extra year gained at older ages. That is,

I assume that the benefit of additional school on the staying home/school attendance margin

is the same as the benefit of additional school on the school attendance/labor market entry

margin. During this time period this seems a reasonable assumption, since presumably a new

early education curriculum was not being introduced when the school entry age was lowered,

but rather material was added to the end of the course of study. There is some concern that the

age at which children enter school has some sort of differential effect beyond the curriculum

taught in school, though this is something that may be investigated further in the literature on

returns to education.

Finally, I assume that the timing of the passage of compulsory education and minimum

labor age laws is sufficiently exogenous for it to seem random to individuals. Given that I am

studying individual birth cohorts, this assumption is plausible. Although the broader national

trends were towards the passage of these and similar laws, whether the law was passed in one

year or the next (and thus affected one birth cohort or the next younger cohort) should be

relatively random.

5.3 Interaction Effects: Empirical Model

There is reason to believe that some of these effects may be stronger or weaker in some areas

rather than in others. For instance, Fagernas (2014) finds that in states with birth registration

laws, minimum working age legislation was twice as effective at reducing the incidence of

children working. For this reason, I will consider whether the effects found vary by whether

the individual would have been subject to a birth registration law in his home state.

The empirical model for these effects is as follows

yist = αs +βt +ηBRst+δMLAst +ρ1MLAst ×BRst

+γCY Sst +ρ2CY Sst ×BRst +X ′istλ + εist

(2)

In this specification, δ and γ will still give the separately identified marginal effects of starting

16

work a year later and being subject to an additional year of compulsory schooling, respectively,

while η will give the effect on income and/or education of living in a state and birth cohort that

is subject to a birth registration law. Similarly, ρ1 and ρ2 will give the additional effect of being

on the margin of an additional year of school or a year less of work while also being subject to

a birth registration law.

6 Results

Table 3 shows that after controlling for the number of compulsory years of school, which takes

both the minimum labor age and the compulsory entry age into account, the minimum labor

age has no residual effect on the highest grade achieved by adulthood in the 1940 census. This

significant, if modest, effect on the highest grade achieved that is robust to the inclusion of

urbanization and farm percentage controls, as well as to the inclusion of interaction effects

for living in a state and birth cohort that is subject to a birth registration law. The effect of

an increase of one year of school required is about 0.04, or 4% of a year of school achieved,

which is comparable to the result of 5% of a year of school achieved for every additional

year of compulsory schooling found in Lleras-Muney (2005). Note that the effect of raising

the minimum working age and raising the compulsory school attendance age have effects of

roughly equal magnitude in columns 3 and 4 and are both significant, giving support to my

critical assumption that changes on each of these margins lead to similar changes in educational

attainment.

Table 4 shows the results of my core difference in difference specification. The coefficient

on the minimum labor age is the marginal effect on income in 1940 of living in a state which

mandates delaying labor market entry by one year, independent of the effect stemming from

an additional year of schooling, while the coefficient on required school years is the effect of

living in a state which requires an additional year of schooling on income in 1940, independent

of the implied effect of delaying labor market entry by an additional year. Changes in both of

these policy variables have marginally significant effects on income in 1940. An extra year of

17

work independent of years of schooling results in about an $6-$8 increase in income, while

an increase in the required years of school, independent of the labor market effects, results in

about a $5-$7 increase in income.

These effects are concentrated in states with birth registration laws. In those states, an

additional year of school required translates to an additional $20-$26 of annual income in 1940.

The negative effect of delaying labor market entry is also stronger for individuals affected by

a birth registration law: there is a significant negative effect of $29-$36 of annual income in

1940. Again for these specifications the effect of an additional year of school is of roughly

equal magnitude as the effect of delaying work for an extra year, implying that on the margin

an extra year of school may have carried roughly equivalent value in the long run as an extra

year of work.

While the marginal effects are modest, some perspective can be gained from examining the

largest possible change in policy variables given the ranges observed in the sample. The most

permissive working and school entry ages are 10 and 8, respectively, while the most restrictive

observed are 15 and 7. Changing from the first regime to the second would imply an increase in

the minimum working age of 5 years, and a change in the implied years of required schooling

of 6. From the results observed, that would result in an increase in highest grade achieved

by about 20% of a grade level. The effect on income is composed of a decrease of $40 per

year from missed work opportunities, but an increase of approximately $42 per year from the

increased school years, highlighting the result that in this time period, work and school seem

to be somewhat interchangeable.

Examining the results on logged income in 1940 in table 5 highlights that the effects on

individuals affected by birth registration laws may be operating on a different margin than the

the main effects. Studying logged income necessarily restricts attention to individuals who

have positive income in 1940. In these specifications the main effects are much stronger than

the interaction effects for individuals affected by birth registration laws, implying that the birth

registration laws may be operating more on the extensive margin of inducing individuals to

still be working in 1940, rather than operating on the intensive margin of increasing income for

18

those individuals affected by the laws. While the effects of an additional year of school and

delaying work by a year are still statistically similar, there is a larger gap between them in this

specification. This may imply that the negative effect of delaying work is concentrated on the

intensive margin, while the positive effect of additional years of schooling may be operating

more on the extensive margin, improving individuals’ probability of continuing to find gainful

employment in 1940.

The main result from this analysis is that it seems that delaying labor market entry for

one year has a negative effect on long run income that is roughly equal to the positive effect

of inducing an additional year of school for the same children. One possible explanation for

this result is that the first years of work may have “looked” more like school, in that children

were learning skills and trades in arrangements such as apprenticeships. Alternatively, it could

simply be the case that those children who were at risk to have their school going and labor

market behavior shifted by the changes in the laws are rationally situated on that margin. That

is, because the returns to an extra year of school and an extra year of work are approximately

the same, children who were at risk to be shifted by legislative changes were indifferent about

the exact age of labor market entry, at least on the financial margin of their long term labor

market returns. Collecting further information from the 1900 and 1910 census manuscripts

could shed light on this curious result, particularly since the recorded occupations of working

children could be used to assess the extent to which children engaged in apprenticeship-like

arrangements are driving the results.

7 Discussion

It is clear from the preceding results that there are positive effects of working and of attending

school, implying that the naive policy of simply banning child labor may have negative effects

on the most vulnerable citizens: the children such legislation is intended to protect. Any policy

maker concerned with reducing child labor should take into account the benefits children gain

from work and design their policies accordingly. For instance, a policy promoting both work

19

and school (by requiring school attendance for a work permit) would harness both of the effects

demonstrated here in the same direction, rather than forcing the effects to work in opposition.

Further work can be done on this topic to determine the exact mechanisms driving the

positive result uncovered here. Such research would further inform the types of policies that

could be undertaken in order to optimally benefit working and non-working children. At a

very local level this empirical approach can be used to examine differences between siblings

by including a family fixed effect. To the extent that each sibling’s working or school going

status is independent of the others, running this regression with a family fixed effect instead

of the state or time fixed effect would reveal the marginal effects of an extra year of school or

work on later life outcomes controlling explicitly for unobserved family characteristics.

It is possible, however, that whether children should work is a household level decision that

has household level consequences with potential spillover effects on siblings. To explore that

possibility I plan to examine whether each child’s outcome variables are related to his siblings’

work opportunities. It is easy to imagine that there would be household level income effects

of a single child working. In this case the difference between siblings in working households

would be diminished, rendering the family fixed effects approach less useful, however this

approach could afford a way to examine the mechanisms behind a positive effect of work. If

it is primarily an income effect, then there should be a similarly sized effect on non-working

siblings within a household. If, however, the effect primarily stems from work experience, on

the job training or a similar effect, then it should be private to the individual and not affect

siblings to the degree that a pure income effect would.

Of course, these approaches assume relatively random assignment of children within the

household to work and school, regardless of age or skill level. Beegle, Dehejia and Gatti (2009)

demonstrate that this may not be the case, that families in Vietnam may be systematically

sending smarter children to work, presumably to maximize the short term earning potential of

the family. Determining how to sort out these selection effects is a topic for future work, but a

topic of vital importance for policy design.

The results here demonstrate that there are positive returns to both work and school for

20

children that were on the margin of working when these laws were changed. This implies

that any policy aimed at reducing child labor should endeavor to at least replace the benefits

enjoyed from work by each child. Further, understanding the mechanisms at work here are

vital for constructing effective public policy in developing countries today. If the benefits to

children found here stem from work experience and are private to the individual, the program

may replicate the benefits of work by simply encouraging school attendance in addition to

work. If, however, the benefits operate primarily through an income effect channel within

the household, simply replacing the income of the child may benefit both the child and other

household members enjoying the spillover effects of the individual’s work.

Based on the dominant mechanism, a policy banning child labor may have a negative effect

understated by the effects on a single child. While the children studied here may be no worse

off in school than if they were working, if their income benefited their siblings the net benefit

of work could be far greater than the results reported in this paper. Failing to understand the

mechanisms could lead us to vastly understate the cost of a simple ban on child labor. This

underscores the necessity for further research to inform policy in the developing world today,

so we do not do more harm than good in pursuing the eradication of child labor.

21

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Journal of Sociology 14, 15-37

[2] Akabayashi, H. and Psacharopoulos, G. (1999) “The trade-off between child labour andhuman capital formation: A Tanzanian case study” The Journal of Development Studies35, 120-140

[3] Angrist, J. and Acemoglu, D. (2000) “How Large are Human-Capital Externalities? Evi-dence from Compulsory Schooling Laws” NBER Macroeconomics Annual 15, 9-59

[4] Basu, K., Das, S. and Dutta, B. (2010) “Child labor and household wealth: Theory andempirical evidence of an inverted-U” Journal of Development Economics 91, 8-14.

[5] Basu, K and Van, P. (1998) “The economics of child labor” American Economic Review88, 412-427

[6] Beegle, K., Dehejia, R. and Gatti, R. (2009) “Why should we care about child labor: theeducation, labor market and health consequences of child labor.” The Journal of HumanResources 44, 871-889

[7] Bursztyn, L. and Coffman, L. (2012) “The schooling decision: Family preferences, in-tergenerational conflict and moral hazard in the Brazilian Favelas” Journal of PoliticalEconomy 120, 359-397

[8] Clay, K., Lingwall, J. and Stephens, M. (2012) “Do Schooling Laws Matter? Evidencefrom the Introduction of Compulsory Attendance Laws in the United States” WorkingPaper

[9] Doepke, M. and Zilibotti, F. (2005) “Macroeconomics of child labor regulation” Ameri-can Economic Review 95, 1492-1524

[10] Edmonds, E. (2007) “Child Labor” Handbook of Development Economics

[11] Edmonds, E. and Shady, N. (2012) “Poverty Alleviation and Child Labor” American Eco-nomic Journal: Economic Policy 4, 100-124

[12] Emerson, P. and Souza, A. (2007) “Is Child Labor Harmful? The Impact of WorkingEarlier in Life on Adult Earnings” Working Paper

[13] Fishback, P., Holmes, R., Allen, S. and Kantor, S. Website for State Labor Laws in theEarly Twentieth Century [website listing]

[14] Goldin, C. and Katz, L. Website for Compulsory Education and Child Labor Laws byState (1900 to 1939) [website listing]

[15] Heady, C. (2003) “The effect of child labor on learning achievement.” World Development31, 385-398

[16] Hindman, H. (2002) Child Labor: An American History New York: M.E. Sharpe

[17] Holmes, R. (2003) “The Impact of State Labor Regulations on Manufacturing Input De-mand During the Progressive Era. Unpublished Ph.D. dissertation, University of Arizona

[18] Holmes, R. (2005) The Impact of State Labor Regulations on Manufacturing Input De-mand During the Progressive Era, Dissertation Summary. Journal of Economic History65, 531-532

22

[19] Landes, W. and Solomon, L. (1972) “Compulsory Schooling Legislation: An EconomicAnalysis of Law and Social Change in the Nineteenth Century” Journal of EconomicHistory 22, 54-91

[20] Lleras-Muney, A. (2002) “Were Compulsory Attendance and Child Labor Laws Effec-tive? An Analysis from 1915 to 1939” Journal of Law and Economics 45, 401-435

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23

Figure 1: Identification Intuition

Figure 2: Difference in difference box

Connecticut Massachusetts ∆(MA−CT )Birth cohort of 1887 αCT +β87 +14δ +6γ αMA +β87 +13δ +6γ αMA−αCT −δ

Birth cohort of 1891 αCT +β91 +14δ +6γ αMA +β91 +14δ +7γ αMA−αCT + γ

∆(Cohort1891−Cohort1887) δ + γ

Connecticut Massachusetts ∆(MA−CT )Birth cohort of 1891 αCT +β91 +14δ +6γ αMA +β91 +14δ +7γ αMA−αCT + γ

Birth cohort of 1896 αCT +β96 +14δ +7γ αMA +β96 +14δ +7γ αMA−αCT

∆(Cohort1891−Cohort1896) γ

Connecticut Massachusetts ∆(MA−CT )Birth cohort of 1887 αCT +β87 +14δ +6γ αMA +β87 +13δ +6γ αMA−αCT +δ

Birth cohort of 1896 αCT +β96 +14δ +7γ αMA +β96 +14δ +7γ αMA−αCT

∆(Cohort1896−Cohort1887) δ

24

Figure 3: Compulsory entry age law changes

Figure 4: Minimum labor age law changes

25

Table 1: Compulsory school entry ages

State Initial entry age(birth year 1884)

Year of change New entry age

Connecticut 8 1902 7Illinois 7 - -Indiana 8 (1899) 1902 7Maine 8 1902 7Massachusetts 8 1899 7Michigan 8 1904 7New Hampshire 6 1896 8New Jersey 7 - -New York 8 1909 7Ohio 8 - -Pennsylvania 8 (1895) - -Rhode Island 7 - -Vermont 8 - -Wisconsin 7 - -

Table 2: Minimum labor age laws

State Initial laborlaw date

Minimum labor age(birth year 1884)

Year ofchange

New minimumlabor age

Connecticut 1872 14 1890 16Illinois 1883 14 1906 16Indiana 1897 14 - -Maine 1875 12 1907 14Massachusetts 1852 13 1902 14Michigan 1871 12 1909 14New Hampshire 1871 10 1901/1911 12/14New Jersey 1874 15 1903 14New York 1874 14 - -Ohio 1877 12 1910 15Pennsylvania 1895 12 1905 14Rhode Island 1883 12 1906 13Vermont 1867 10 1906 12Wisconsin 1879 12 1907 14

26

Tabl

e3:

Eff

ecto

ned

ucat

iona

latta

inm

ent

(1)

(2)

(3)

(4)

(5)

(6)

Hig

hgr

ade

Hig

hgr

ade

Hig

hgr

ade

Hig

hgr

ade

Hig

hgr

ade

Hig

hgr

ade

Min

imum

labo

rage

-0.0

0891

-0.0

0940

0.03

01∗∗

0.02

97∗∗

0.01

240.

0114

(0.0

154)

(0.0

156)

(0.0

091)

(0.0

091)

(0.0

156)

(0.0

157)

Com

puls

ory

scho

olin

gye

ars

0.03

90∗∗

0.03

91∗∗

0.03

80∗∗

0.03

88∗∗

(0.0

126)

(0.0

128)

(0.0

135)

(0.0

137)

Com

puls

ory

entr

yag

e-0

.038

99∗

-0.0

3910∗

(0.0

126)

(0.0

128)

1910

Cou

nty

urba

n%

0.11

10.

111

0.11

1(0

.060

7)(0

.060

7)(0

.060

7)

1910

coun

tyfa

rm%

0.69

7∗∗∗

0.69

7∗∗∗

0.69

5∗∗∗

(0.1

03)

(0.1

03)

(0.1

03)

Bir

thre

gist

ratio

nla

w1.

969∗∗

1.87

2∗∗

(0.6

66)

(0.6

67)

Bir

thre

gist

ratio

nX

-0.2

42∗∗

-0.2

28∗∗

min

imum

labo

rage

(0.0

791)

(0.0

793)

Bir

thre

gist

ratio

nX

0.15

7∗0.

145∗

com

puls

ory

scho

olin

gye

ars

(0.0

665)

(0.0

669)

Con

stan

t9.

656∗∗∗

8.96

5∗∗∗

9.65

6∗∗∗

8.96

5∗∗∗

9.48

2∗∗∗

8.79

3∗∗∗

(0.1

78)

(0.1

87)

(0.1

78)

(0.1

87)

(0.1

78)

(0.1

92)

N76

7,91

375

6,19

576

7,91

375

6,19

576

7,91

375

6,19

51

All

spec

ifica

tions

incl

ude

stat

ean

dbi

rth

year

fixed

effe

cts.

2St

anda

rder

rors

(in

pare

nthe

ses)

clus

tere

dat

the

stat

eby

birt

hye

arle

vel.

3*

p<

0.05

,**

p<

0.01

,***

p<

0.00

1

27

Table 4: Effect on 1940 income

(1) (2) (3) (4)Income, 1940 Income, 1940 Income, 1940 Income, 1940

Minimum labor age -8.432∗ -8.344∗ -5.992 -6.143(4.057) (4.187) (4.272) (4.402)

Compulsory schooling years 5.456 6.934 4.973 6.744(3.480) (3.648) (3.643) (3.875)

1910 County urban % 287.9∗∗∗ 288.0∗∗∗

(15.51) (15.51)

1910 county farm % 528.4∗∗∗ 528.0∗∗∗

(24.35) (24.35)

Birth registration law 270.8∗ 222.5(129.0) (123.7)

Birth registration X -35.94∗ -28.73∗

minimum labor age (14.32) (13.82)

Birth registration X 26.29∗ 19.76compulsory schooling years (11.38) (11.13)

Constant 1420.0∗∗∗ 750.8∗∗∗ 1406.5∗∗∗ 736.6∗∗∗

(46.12) (48.38) (49.67) (53.23)N 726,737 715,777 726,737 715,777

1 All specifications include state and birth year fixed effects.2 Standard errors (in parentheses) clustered at the state by birth year level.3 * p < 0.05, ** p < 0.01, *** p < 0.001

28

Table 5: Effect on logged 1940 income

(1) (2) (3) (4)Log(income) Log(income) Log(income) Log(income)

Minimum labor age -0.0104∗∗∗ -0.0104∗∗∗ -0.00978∗∗∗ -0.0101∗∗∗

(0.00270) (0.00280) (0.00286) (0.00296)

Compulsory schooling years 0.00596∗ 0.00726∗∗ 0.00521∗ 0.00679∗

(0.00244) (0.00258) (0.00252) (0.00271)

1910 County urban % 0.236∗∗∗ 0.236∗∗∗

(0.0121) (0.0121)

1910 County farm % 0.310∗∗∗ 0.310∗∗∗

(0.0224) (0.0224)

Birth registration law 0.110 0.0709(0.0916) (0.0900)

Birth registration law X -0.0169 -0.0115minimum labor age (0.00999) (0.00988)

Birth registration law X 0.0155∗ 0.0107compulsory schooling years (0.00775) (0.00774)

Constant 7.266∗∗∗ 6.828∗∗∗ 7.268∗∗∗ 6.832∗∗∗

(0.0304) (0.0334) (0.0332) (0.0367)N 544,413 536,916 544,413 536,916

1 All specifications include state and birth year fixed effects.2 Standard errors (in parentheses) clustered at the state by birth year level.3 * p < 0.05, ** p < 0.01, *** p < 0.001

29