The Gender Gap in Turn-of-the-Century Swedish Manufacturing
Joyce Burnette
Wabash College
and
Maria Stanfors
Lund University
Abstract: This paper explores the wage gap among Swedish cigar workers and compositors circa
1900. We examine information on men and women holding the same jobs; such data are rare but
important for understanding the gender wage gap. Women’s hourly wage was about seventy
percent of men’s. Individual characteristics explain much of this gap, but not all of it. To explain
the remained of the wage gap we examine training and differences across firms. Wage profiles
indicate that women initially had a slightly higher average wage, but after about five years of
experience when female wages stagnated and male wages continued to grow, creating a
persistent male advantage. This wage pattern may have been caused by differences in training.
Women were less likely to be apprentices, but may have chosen less training if they expected
shorter tenures. We also find differences across firms by size and location.. Smaller, non-metro
firms treated men and women fairly; it was the larger, metro firms where we see different
opportunities for men and women.
Women have always earned less than men. For much of history men's greater strength
explains a large portion of the difference, but this raises the question of why the gender gap did
not disappear when the importance of strength waned. While industrialization in some cases
increased the demand for strength (Samuel, 1977, 1992), eventually machine power substituted
for human power. Around the turn of the twentieth century a strength-based gender gap was
being replaced by a gender gap based on other factors (Burnette, 2015). This paper examines
wage gaps during this transition, in two gender-mixed manufacturing occupations in turn-of-thecentury Sweden.
The turn of the twentieth century was a particularly interesting time for labor markets,
since around this time there was a transition from spot labor markets to internal labor markets.
During the nineteenth century most workers were hired in spot labor markets. Turnover was
high, and workers were paid their current marginal product. (Rosenbloom and Sundstrom, 2009)
Early in the twentieth century firms sought to reduce turnover and developed internal labor
markets (Jacoby, 1985; Owen, 1995). Thus, wage profiles from the nineteenth and twentieth
centuries look very different. In contrast to twentieth-century profiles which rise continually until
middle age, nineteenth-century wage profiles increase rapidly during youth, but are fairly flat for
adults (Hatton, 1997). The turn of the twentieth century saw the transition between the two labor
market regimes. Some aspects of internal labor markets, such as internal promotion and longterm employment, were already appearing in late nineteenth century (Sundstrom, 1988). Other
characteristics, such as delayed compensation and personnel departments, do not appear until
later.
We are particularly interested in the fact that, with the rise of internal labor markets,
firms offered different opportunities for advancement to men and women. Often men were
offered jobs with delayed compensation and women were not. Goldin (1986) suggests that firms
chose different incentive structures for men and women. Women were paid piece-rates, while
men, who had longer expected tenures, were incentivized with delayed compensation. Owen
(2001) suggests that men were the main beneficiaries of internal labor market policies instituted
in the 1920s, and that “men’s greater access to internal labor markets . . . meant that women took
on the status of residual workers” (p. 63). Historically large firms have been more likely than
small firms to adopt internal labor markets. Moriguchi (2003, p. 636) suggests that this is
1
because small firms find it harder to establish credible commitments to honor their side of the
implicit contract. Thus we compare large and small firms, to see if they offered men and women
different training opportunities.
This paper also expands this discussion outside of the Anglo-Saxon countries, where
most work on this transition has been located. Swedish labor markets could potentially be quite
different from those in the US or Britain, but our research suggests that they were not. The
Swedish industries we study have wage profiles that become flat early in a worker's career, as do
late nineteenth-century wage profiles in the US or Britain (Hatton 1997, Boot 2008).
The occupations we choose allow us to eliminate some potential causes of the gender
wage gap. We focus on two occupations that did not demand strength, cigar workers and
compositors, thus leveling the playing field with respect to gender. Compositors needed to be
literate, while cigar making required only manual skills. Technology was unimportant in cigar
making, while the printing industry was being altered by the linotype machine. In these
occupations women on average earned only about seventy percent as much as men. The cause of
this wage gap is not obvious. Women were not prevented from entering these occupations or
their unions. In fact, 35 percent of female cigar workers and 56 percent of female compositors
were union members. Wage discrimination was not widespread in nineteenth-century
manufacturing (Burnette 2015; Stanfors et al. 2014), and a large portion of the cigar workers in
our sample were paid piece-rates which did not vary by gender. Though there were earnings
differentials, men and women were not paid different wages (i.e., according to different tariffs).
We have a wide range of information about individual characteristics, which explain about half
of the gender wage gap for cigar workers and three-fourths of the wage gap for compositors.
After controlling for individual characteristics, a substantial portion of the wage gap
remains. The remaining gap is not likely due to pure wage discrimination. The study of gender
wage gaps is often confounded by occupational segregation and the fact that men and women
rarely held the same jobs. In the occupations that we study, men and women who had the same
job were paid the same wage form. Most of our cigar workers were paid gender-neutral piece
rates, limiting the opportunities for delayed compensation as well as discrimination. Among
cigar workers, 86 percent worked for piece rates, and men were slightly more likely to work on
piece rates than women.
2
While men and women faced the same wage structure, they may not have had the same
training. If men had training opportunities that women did not, they may have ended up with
higher wages. To explore possible differences in training we examine apprenticeship rates and
wage profiles. We find that women received less formal training in the form of apprenticeship.
Once we control for the experience level women were less likely than men to be apprenticed in
both occupations. Among compositors women's apprenticeships seem to have been shorter than
men's. Wage profiles also suggest that women received less training.
Differences in training, though, were not necessarily due to discrimination. It is possible
that women voluntarily chose different levels of training than men. Polachek and Siebert (1993,
p. 158) suggest that individuals who expect to spend less time in the workforce would choose
jobs with higher starting salaries and lower wage growth compared to individuals who expect to
spend more time in the labor force. Polachek (1981) suggests that women choose occupations
where the skill depreciation resulting from time out of the labor force is relatively small. England
(1982) questions this explanation, showing that predominantly female occupations do not have
smaller penalties for time out of the workforce than predominantly male occupations, suggesting
that women are not choosing occupations for their low rates of skill depreciation. Sandell and
Shapiro (1980) show that women who as teenagers said they expected to be in the labor force at
age 35 had higher returns to labor market experience than women who as teenagers expected to
be out of the labor force at age 35. This suggests that women who expect to spend more time in
the labor force invest more in on-the-job training. Among our Swedish workers, women started
at a slightly higher wage than men, but male wages quickly surpassed female wages, so there is
some possibility that women chose the lower amounts of training because they expected to leave
the occupation before the training paid off.
We also explore differences in the gender gap across firms. Part of the gender gap may be
due to the types of firms at which women worked. Our evidence suggests that the firm where you
worked mattered, and that it was the larger urban firms where women had fewer opportunities
than men. Gender gaps were larger at large firms and in cities. For cigar workers, larger firms
had more divergence in male and female wages, and the payoff to training was such that women
should have chosen more training if it was available to them. For compositors the gender gap
becomes insignificant when we include firm fixed effects, or when we limit the analysis to small
firms or non-metro firms. Controlling for characteristics, women at smaller firms were treated
3
the same as men. It was the larger firms where gender mattered. We conclude that some of the
larger firms were moving to twentieth-century labor patterns, where firms offered men and
women different opportunities
Data
Our data serve our research purpose very well. They come from government surveys of
entire industries that collected information on firms as well as detailed information about
individual workers, allowing us to match workers to firms. The Swedish Board of Commerce
(Kommerskollegium) surveyed the tobacco industry in 1898 and the printing industry in
1902/1903. While all workers in the industry were included in the survey, we confine our
analysis to cigar workers and compositors, which were the central and most common
occupations within each industry. We know hourly wage, tenure, and experience in the
occupation for every worker. Since workers are connected to firms, we are able to match the two
and examine whether firm characteristics such as size and location mattered for individual wage
profiles. More specifically, we can establish whether large firms had different wage profiles from
small firms and whether firms in big cities employed different wage profiles than firms
elsewhere.
Cigar production was the most important branch of the tobacco industry, accounting for
almost 70 percent of total employment. Cigar making is a three-stage process: preparation work,
rolling, and sorting and packaging. Preparation involved handling of the raw tobacco,
fermentation, and moistening. Rolling is undertaken either by hand or with the help of a wooden
mold. Finally, the cigars were placed on frames to dry, sorted by quality, and packed into boxes.
Compositing, or typesetting, was the most common occupational specialty in the printing
industry, accounting for 36 percent of total employment. Typesetting is the composition of text
by means of types. It requires the prior process of designing a font (sorts) which is stored in
some manner. During the letterpress era, moveable type was composed by hand for each page.
Cast metal sorts were composited into words and lines of text and bound together to make up a
page image called a forme, with all letter faces exactly the same height to form an even surface
of type, which was then mounted in a press, inked, pressed on paper.1 Hand composing was
1
Sometimes copies of formes were cast when subsequent printings of a text were anticipated, freeing the type for
other work. This process was called stereotyping.
4
rendered obsolete by continuous casting or hot-metal typesetting machines such as the linotype
machine and monotype at the end of the nineteenth century. The linotype enabled one machine
operator to do the work of ten hand compositors by automating the selection, use and
replacement of sorts, with a keyboard as input. This revolutionized typesetting as well as printing
- before the invention of the linotype, no newspaper in the world had more than eight pages.
Typesetting was especially important in newspaper and book printing but also in factories
producing other printed matters. It was skilled work with some working by hand and some by
machines, where work by machines was considered more challenging than work by hand.
Both cigar production and typesetting were factory-based, with a clear division of labor
according to skill. Cigar production in Sweden was at the time of survey craft-like and relatively
un-mechanized by international standards (Cox, 2003: 124; Elmquist, 1899: 64). Typesetting
was, by contrast, more modern and capital-intensive, increasingly involving modern machinery.
Raw tobacco preparation was unskilled work, whereas rolling and sorting were considered more
difficult and skilled work.2 Rolling required dexterity while sorters needed experience to grade
by quality. The traditional training period for cigar makers and sorters was at least two years but
the rapid expansion of cigar production and the introduction of cigar-making molds shortened
the learning process, and made apprenticeship less common by this period (Elmquist, 1899: 96–
98; Oakeshott, 1900: 565). Typesetting, on the other hand, required more formal skills, as
workers had to be literate, beyond the average at turn-of-the-century, even proficient at mirrorimage reading. Typesetting as a trade was growing with formal apprenticeship providing for
rejuvenation. There were 40-45 apprentices per every 100 skilled compositor depending on
specialty. Compositors worked with formatting and setting text and tables, but they also worked
with typesetting sheet music, and ads, etc.
In 1898, two-thirds of cigar workers were women, similar to the ratio prevailing in the
wider tobacco industry. Women were more likely than men to be on the lower rungs of the job
ladder, working as preparatory workers or bunch makers. In 1903, 13 percent of the compositors
were women, which is less than the 25 percent prevailing in the printing industry3. Women were
less likely to be among the most skilled compositors operating a machine, and were more likely
2
In a similar manner, North American cigar makers were also considered skilled workers (Cooper, 1987; Prus,
1990).
3
The printing industry was segregated with women dominating book binding and men dominating other
occupations, such as compositing.
5
to work by hand. Nevertheless, men and women with similar skills worked side by side within
individual factories (Collett, 1891: 460–473; Elmquist, 1899, 1909). Women could join the cigar
workers’ as well as the compositors’ unions, but fewer women than men chose to do so.
We restrict ourselves to workers for whom we have complete data. Since workers report
both weekly earnings and hours worked we are able to use hourly earnings as our dependent
variable (i.e., the natural logarithm of weekly earnings divided by hours worked during a normal
working week). This is particularly useful in the case of gender analysis, since the danger of
using weekly wages is that women may be paid less because they work shorter hours. We know
whether the worker was paid an hourly rate or a piece rate, but measure the hourly wage as
average earnings per hour in both cases. Earnings refer to wage earnings and do not include the
value of fringe benefits, which were trivial in the Swedish tobacco industry by 1898, but more
important in the printing industry. We include a control for the free housing benefit received by
some compositors.
The measure of experience available in these data sets is different from the one typically
used by labor economists. Following Mincer (1974), experience is usually defined as the number
of years since leaving school (age – years of schooling – 6). We do not have any information on
formal schooling for cigar workers, and have limited information for compositors. However, the
survey did ask workers what year they started in their occupation. This is a better measure of
experience because it is specific to the occupation. We also know how many years the worker
has been at the same firm.
Table 1 shows averages and shares by gender and occupation for the variables used in the
analyses. Compositors earned more than cigar workers, irrespective of gender, though they were
younger and had less experience. This reflects the fact that compositors were more skilled than
cigar workers. Women were less likely than men to be a member of a union or friendly society.
Men were, on the other hand, more likely to be married with children than women. Among cigar
workers, women were more likely to be preparation workers and less likely to be rollers. Among
compositors, women were less likely than men to work with the linotype machine. Table 1
confirms that there were important differences in individual characteristics, potentially correlated
with productivity, which may have contributed to the gender wage gap.
6
The Wage Gap
Female cigar workers earned 68 percent as much as men, and female compositors earned
70 percent as much as men. Table 2 shows gender wage ratios by occupational specialty. Part of
the wage gap was explained by sorting; wage gaps within occupational specialty were generally
smaller than the overall wage gap. The exception was preparation workers, for whom the gender
gap was greater than for cigar workers in general. In both occupations male and female
apprentices earned approximately the same wage. Female bunch makers earned more than male
bunch makers, but this seems to be explained by the fact that men left the job or were promoted
out of that occupation faster. There were few male bunch makers and none older than 18, while
the average age of female bunch makers was 25.
To examine how much of the wage gap can be explained by observable characteristics,
we first examine the coefficient on the female dummy in pooled regressions including both men
and women. Table 3 shows the results for cigar workers. The first regression estimates the raw
gender gap, and the second regression includes controls for experience in cigar making, tenure,
and age. We use a quadratic spline as the functional form for experience because this captures
the shape of the profile better than a simple quadratic (Burnette and Stanfors, 2015).4 While
experience in the occupation is quite important, firm tenure has little effect on the wage and is
generally not statistically significant. Instead of including age, which is correlated with
experience, we calculate the age at which the worker started in the occupation (age - experience)
and include that as a control. Married workers earned more than unmarried workers, and workers
with kids earned more, effects which could be due to both selection and incentives. Members of
unions and friendly societies earned more than other workers. Membership was probably an
indicator of commitment to the occupation. Among occupational specialties, sorters earned more
than rollers, and less skilled groups including preparation workers and bunch makers earned less.
Table 4 shows comparable results for compositors. The results are similar to those for
cigar workers, except for the fact that children had no significant effect on earnings. In this data
set we know whether each worker had any secondary education; the effect of secondary
education is positive but not large. There is also a wage premium associated with shift work.
Firms that operated at night or on Sundays paid more. This differential compensated the worker
4
The spline variable is max{0, age-k} where k is the break-point. We determine the break-point by estimating
functions with a wide range of k’s and choosing the break-point that gives the highest R-squared.
7
for the less desirable shifts, but also reflects the fact that only some firms operated shifts because
they concentrated in different branches of the printing trade.5 Technical skills paid off among
compositors; those who worked on the new linotype machine received a substantial wage
premium over hand compositors.
From Table 3, reporting results for cigar workers, we see that female cigar workers had a
wage penalty of 0.376 log points. Observable characteristics are able to explain a good portion of
the raw wage gap, which shrinks to 0.265 when we include controls for experience, tenure, and
age. Including measures of the individual’s family status and membership in a union or a friendly
society further reduces the wage gap to 0.208 log points, or slightly more than half of the original
wage gap. Lastly we include occupational measures: whether the worker is an apprentice, and
whether the worker is a preparation worker, bunch maker or sorter rather than a cigar roller.
These variables might be seen as outcomes of the labor market process, so it is not clear whether
we want to include them when assessing whether the market treats women fairly. If we do
include them the gender gap drops to less than half of the original size (46 percent).
For compositors we follow a similar process and are able to explain an even greater
portion of the wage gap. Without controls the gender gap is 0.341 log points (see Table 4).
Controls for experience, tenure and age reduce the gap to 0.179, and including individual
characteristics reduces the wage gap to 0.075 log points. For compositors, an important source of
the gender wage gap is the number of women who worked as machine compositors. Model 3
adds a control for machine compositors and tells us that being a machine compositors led to a
substantial increase in the wage (0.478 log points). Women, however, were less likely than men
to work on the modern linotype machines; while 7.5 percent of the men were machine
compositors, only 2.3 percent of the women were. Controlling for machine compositing reduces
the wage gap to 0.062, or just 18 percent of the original wage gap. Model 4 also add controls for
apprentices and foremen; here the wage gap is 0.065, or 19 percent of the original wage gap.
Thus far we have assumed that individual characteristics affected earnings in the same
way for both men and women. Since this assumption is often not correct, we run the same
regressions separately on the male and female sub-samples. Table 5 shows the results for cigar
workers. Both men and women got a wage benefit from having children. Men got a larger benefit
than women from membership in a union of friendly society. Figure 1 shows the experience5
For example, newspaper printers were more likely than book printers to work nights and Sundays.
8
wage profiles for cigar workers from Model 2 in Table 5. Comparing male and female wage
profiles, we find that females earned slightly more than males when they started work, but that
male wages overtook female wages at about three years of experience and remained higher
thereafter. After about five years of experience, female wages stagnated, while male wages
continued to grow until about seven years of experience. The fact that women’s wages stagnated
earlier means that for all but the least experienced workers men earned more than women.
Women’s lower wages were the result of lower wage growth rather than a lower starting wage.
For compositors (Table 6) women benefited more than men from being currently
married, but only men benefited from being previously married. Being a member of a friendly
society had a larger benefit for women than for men. There were substantial differences in the
returns to night and Sunday work. Women earned less at firms with night work (perhaps
because firms that engaged in night work didn't use women for that purpose) and gained
substantially more from Sunday work.6 Women also benefited more than men from being a
machine compositor. Figure 2 shows wage profiles for compositors from Model 3 of Table 6.7
Male and female wages were similar for the first four years, and then female wages shifted to a
much slower rate of growth. Male wages continued to grow rapidly for the first eight years, but
then stagnated. Because female wages continued to grow, there was wage convergence between
men and women (catching up at 38 years of experience). Most of the time, though, female wages
were substantially below male wages.
Among our workers, women earned about seventy percent as much as men. Women
earned less than men because they were less experienced, less likely to be members of a union or
friendly society, and less likely to be married. Among compositors, women were less likely to
have a secondary education. Observable characteristics explain about half of the wage gap for
cigar workers and four-fifths of the wage gap for compositors. While individual characteristics
were certainly important, they do not explain the whole gap, leaving us with a wage gap that is
difficult to explain. These occupations did not require strength, and there was no obvious
6
Firms that had night work hired fewer women (4.3% women compared to 13.2% women). However, it is also true
that firms that had Sunday work hired fewer women (2.4% women compared to 13% women).
7
We include the control for machine compositors when graphing this profile. Machine compositing was high-paid
but does not seem to be an occupation that you worked up to because 5 of the 14 women with less than a year of
experience in were machine compositors. If we fail to control for machine compositors the female wage profile
declines from zero to one years of experience.
9
discrimination. In the remainder of this paper we explore factors that may have contributed to the
remaining wage gap.
Training
One possible reason that women might have earned less than men of the same experience
level is that they spent less of their work time investing in training. Human capital theory
suggests that workers can give up some current output in order to invest in human capital that
pays off later in their career. The shape of the wage profiles is consistent with gender differences
in training investments. If men invested more in training they would start with lower wages, but
as their investments paid off they would achieve higher wages. Such differences in training may
have been formal or informal. We have some measures of formal training because we know
which workers were apprentices at the time of the survey. Unfortunately we don’t know whether
workers had been apprenticed in the past. Our data, though limited, suggest that women received
less formal training than men. Informal training is harder to measure. Wage profiles are
problematic, since we only have cross-sectional data, but are consistent with the hypothesis that
women invested less in training.
Evidence on the number of workers apprenticed in our data suggest that women received
less formal training than men. In cigar making women were clearly less likely than men to be
apprenticed. While ten percent of the male cigar workers surveyed were apprentices, only five
percent of the female cigar workers were. Among cigar workers with no more than five years of
experience, 40 percent of the males and 11 percent of the females were apprentices. Among
compositors women were less likely to be apprenticed once we control for their lower experience
levels. Overall a greater percentage of the female workforce were apprentices (32 percent of
women and 23 percent of men). However, this seems to be the result of the fact that women were
concentrated at low levels of experience. If we divide the workforce by experience groups each
group has a smaller percentage of females apprenticed. Among compositors with up to five years
of experience 73 percent of women and 83 percent of men were apprentices. Among compositors
with 6 to 10 years of experience, 7 percent of women and 10 percent of men were apprentices.
Thus women were only more likely to be apprentices at the time of the survey due to their lower
levels of experience. If we control for experience, fewer women than men are apprenticed in
both occupations.
10
Among compositors women also seem to have been apprenticed for shorter periods. To
demonstrate this we look at how the likelihood of being an apprentice changed with experience.
Figures 3 and 4 show the percentage of workers who were apprentices at each level of
experience. From these figures we can see that for male cigar workers apprenticeship seems to
have lasted 3 to 5 years. Men seem to have started their apprenticeships when they started in the
industry, and the number apprenticed falls distinctly after three years and after five years of
experience. Women did not necessarily start their apprenticeship when they started in the cigar
industry. More women with three years of experience were apprenticed than women with one
year of experience, and we find women with nine years of experience serving as apprentices. The
increase in the percentage apprenticed in the first few years is consistent with women working
for a time before starting their apprenticeship, or with the presence of casual workers who exited
the industry quickly and were never apprenticed. However, the presence of apprentices with nine
years of experience suggests the former explanation. The pattern for women is so irregular that it
is difficult to tell how long the typical apprenticeship lasted, so there is no clear evidence of
gender differences in the length of apprenticeship. For compositors, on the other hand, women
seem to have been apprenticed for a shorter time than men.
Figure 4 shows that the percent of women apprenticed in compositing increases between zero
and one year of experience, but from two through five years of experience the number of female
apprentices falls more sharply than the number of male apprentices. Between 4 and 5 years of
experience the likelihood a female will be apprenticed falls more than half, while the likelihood a
male will be apprenticed falls only one-sixth.
We conclude that women were less likely than men to enter apprenticeship in both
occupations, and that women typically had shorter apprenticeships in compositing. This suggests
that women received less formal training than men. We cannot measure informal training, but we
would expect it to follow similar patterns. The shape of the wage profiles is consistent with
differences in training. For workers just starting in the occupation, women earned slightly more,
suggesting that men were giving up more current output to invest in training. Men then gained
more than women over the first decade of employment, which is consistent with returns to
greater training.
If women did invest less in training, was this a voluntary choice or were they offered
different options from men? It is possible that women chose to invest less in training because
11
they expected to have a short working life. If the working life a woman expected was short
enough, it may have been rational for her to choose the “female” profile rather than the “male”
profile. We explore this possibility by examining which profile women would prefer.
In order to find out which profile women in cigar making and compositing would prefer,
let us suppose that they had a choice between the low-training (typically female) and hightraining (typically male) profiles, and ask under what circumstances they would have chosen the
low-training profile? We use the males profiles in Figures 1 and 2 as the high-training profiles,
and the female profiles as the low-training profiles. These profiles do not control for
apprenticeship, so they will take into account the fact that men's greater apprenticeship meant
lower wages early in their career.8 Table 7 shows the annual wage gain associated with choosing
the high-training male wage profile.9 For low levels of experience the wage gain is negative
because workers paid for their training by receiving lower wages during the training period. As
male wages surpass female wages the wage gain becomes positive. For some values of the
discount rate and expected years in the labor force the low-training profile maximized the present
value of income. At a discount rate of seven percent, it was rational for a woman to choose the
low-training if she expected a working life of four years or less in cigar making and six years or
less in compositing.
The average experience of female cigar-makers in our sample was eleven years (see
Table 1), and the median was seven years. Female compositors had an average experience of ten
years and a median experience of seven years. Since we have cross-sectional data, this estimate
of time in the industry is biased in two ways. First, observed median experience is an
underestimate of median experience because we observed uncompleted spells and most of the
women we observe would continue to work and acquire experience. On the other hand, at any
period of time we are less likely to encounter a given short spell than a given long spell. If we
randomly choose a date during a twenty-year period we are sure to encounter a worker who
worked the whole twenty years, but have only a five percent chance of encountering a worker
who worked only one year. This would cause us to underestimate the number of short spells.
These biases work in opposite directions but do not necessarily cancel out. We suspect that the
8
If apprentices earned less than other workers, and men were more likely to be apprentices, then low-experience
men will have lower wages due to their greater frequency of apprenticeship.
9
The wage gain is measured in krona per year, and assumes the each worker worked 55 hours per week and 50
weeks per year.
12
measured median is more likely to be an overestimate than an underestimate.10 If the typical
woman expected a working life of seven years, then she should have invested more in training,
and may have been constrained by firms who did not offer her the same opportunities as men.
However, if our estimate of tenure is biased upwards due to the fact that at any one point in time
we meet too few short-term workers, then the typical woman may have expected a shorter
working life and may have chosen lower levels of training to maximize her total expected
income. Below we will see that firm size mattered for this choice.
We find that women were less likely than men to be apprenticed in both industries, and
that they may have had shorter apprenticeships in compositing. Since the wage profiles cross, it
is possible that women chose the low-training wage profiles because they expected to withdraw
from the workforce in connection with marriage (or at least with childbearing) and spend only a
short time in the industry, but it is also possible that women did not have the option of choosing
the same training as men.
Firm Size and Location
We also explore the possibility that the unexplained portion of the wage gap was related
to the firms at which women worked. Differences across firms may have occurred because
women were sorted into different types of firms, or because some firms offered men and women
different opportunities. Including firm characteristics in the regression does not help explain the
wage gap for cigar workers, but for compositors the gender gap is completely explained if we
include firm fixed effects. To examine whether different firms were offering women different
contracts, we divide firms by size and location compare wage profiles and apprenticeship across
types of firms. We conclude men and women were treated more equally at smaller non-metro
firms, and that differences in opportunities were beginning to emerge at large firms.
First we examine whether adding firm characteristics further reduced the wage gaps
estimated in Tables 3 and 4. Table 8 presents the coefficients on firm characteristics and the
10
We attempt to correct for the biases by making two adjustments. First we assume that each spell of employment
is, on average, twice as long as the observed length. Second, to correct for the likelihood of encountering the spell,
we weight each spell by one over its length. These corrections result in average tenures of 5.6 for cigar workers and
6.7 for compositors, but a median tenure of only one year for both occupations. If we use the corrected median
tenure women would choose not to invest in training. However, the same method produces a corrected median
tenure of one year for male cigar workers and three years for male compositors, suggesting that the men would not
want to invest in training either.
13
female dummy from wage regressions that include all the control variables included in Model 3
of Tables 3 and Model 4 of Table 4. For cigar workers, firm characteristics do not help us
explain the gender gap. The female wage penalty, which was 0.17 in model 3 of Table 3,
increases to 0.19 when we add firm characteristics. This increase is probably due to the fact that
metro firms in the big cities Stockholm, Gothenburg and Malmoe hired more women and also
paid more. Controlling for the metro premium makes women look even more underpaid. If we
included firm fixed effects, so that we are looking at differences within firms, the female wage
penalty increases further to 0.21 log points. For compositors, however, differences across firms
seem to explain the gender gap. If we include firm size and location the female wage penalty
increases from 0.07 to 0.08. However, when we include firm fixed effects the coefficient on the
female dummy drops to 0.03 log points and becomes statistically insignificant. For compositors,
the portion of the wage gap not explained by individual characteristics can be explained by
sorting across firms. Within firms the gender gap is entirely explained by individual
characteristics.
Next we look for differences in the wage gap across types of firm. We divided firms in
two ways, by size and by location. Cigar firms were larger than printing firms, so to maintain
adequate number of observations we define the distinction between small and large differently
for each industry. Splitting each industry at the median, large cigar firms are those hiring more
than 90 workers, while large printing firms are those hiring more than 24 workers.
Table 9 shows the female wage penalty for wage regressions on different sub-samples of
the data. For cigar workers, the female wage penalty is systematically higher at larger firms and
at metro-firms. While the raw gender gap is higher outside of metro areas, this is entirely
explained by workers’ age and experience, and the gender gap is higher in big cities in Model 1.
The gender gap remains statistically significant at all types of firms, but women did relatively
better at small firms in non-metro areas. For compositors, the wage gap becomes insignificant at
small firms and non-metro firms. Female compositors received lower wages than men only at
certain firms.
There is also evidence that it was the larger, metro firms that offered different training
opportunities. As above, we explore both formal training through apprenticeships. Earlier we
saw that women were less likely than men to be apprenticed in both occupations. Table 10 shows
the percentage of workers apprenticed in different types of firms. In the cigar industry women
14
with less than six years of experience were always less likely than men to be apprenticed, in all
types of firms. Women with 6 to 10 years of experience were more likely than men to be
apprentices, but this is most likely due to women starting their apprenticeships later. In
compositing, women were as likely as men to be apprenticed in small firms and in non-metro
firms. It was the large, metro firms were women were less likely to be apprenticed.
Small printing firms also seem to have treated men and women the same in terms of
length of apprenticeship. The tendency of female compositors to be apprenticed for shorter
periods appears in large firms but not in small firms. Figure 5 shows the percentage of workers at
each experience level who were apprentices, as in Figure 4, but separately for small and large
firms. For small firms the pattern is approximately the same for men and women. For large firms
the patterns are clearly different. While almost all males were apprentices when they began, all
of the females with less than a year of experience were not apprentices. Because we have crosssectional data we cannot say whether this pattern is the result of women working for a time
before they became apprentices, or the result of the firm hiring a number of short-term female
workers who never become apprentices but left the firm before they acquired much experience.
Another important difference is that at four years of experience few women were apprentices but
most men were. This suggests that the apprenticeship period lasted longer for men, but only at
larger firms. We find that apprenticeship looked the same for men and women at small printing
firms, and that is was only at the larger firms where we observe gender differences. These
results are consistent with the results in Table 9 which suggest that the gender gap among
compositors was entirely explained by individual characteristics at small firms and only at larger
firms do we see an unexplained gender gap.
For compositors the gender difference in training may have been due to choice. Table 7
shows that compositors who expected to spend less than seven years in the industry should have
chosen the low-training profile. Given that women had lower tenure than men, it is possible that
differences in expected tenure explain the different apprenticeship rates at large printing firms.
Among cigar workers women were less likely to be apprenticed at all firms, but firms
seem to have differed in the options they provided. Examining the wage profiles of cigar
workers we again see important differences between small and large firms. Larger firms seem to
have offered opportunities for wage growth that smaller firms did not. At least, they did for men.
Figure 6 shows the wage profiles for men and women at small and large cigar firms. It clearly
15
shows the male and female wages were more similar at small firms than at large firms. At larger
firms women with ten years of experience earned less than their counterparts at small firms, and
men with ten years of experience earned more.
While women at smaller cigar firms may have chosen lower levels of training, such a
choice makes less sense for women at the larger firms. Table 11 shows wage gains similar to
those in Table 7, but separately for large and small cigar firms. At small firms women should
choose the low-training profile if they expected to spend seven years of less in the industry.
Since the observed median tenure is seven years it is perfectly reasonable to expect that women's
apprenticeship was lower in their firms because women chose to invest less in training. In larger
firms, however, where men obtained higher wages, women who expected to spend at least three
years in the industry would have chosen the high-training profile. Here it is less likely that the
difference in training was due to choice, and more likely that women wanted to received more
training but were not given the opportunity. We cannot say for sure whether the investment
patterns we observe were chosen or imposed because the choice would depend on a woman's
discount rate and her expected time in the industry, neither of which is known. However, we can
say that the wage patterns at small firms were more likely to lead women to choose low training
than the wage patterns at small firms. Since we observe even fewer women apprenticed at large
firms than at small firms, we suspect that training was not completely a matter of women's
choice at large firms.
We conclude that the opportunities women faced were related to the firm at which they
worked. For cigar workers, women were less likely to receive training at all firms, but this was
more likely to be a voluntary choice at small firms. For compositors the gender gap was
insignificant, and there was no difference in apprenticeship rates, at small firms, non-metro
firms, so the gender gap was a product of the larger metro firms. It is possible that the larger
metro firms were beginning to institute the types of policies associated with internal labor
markets and, as firms in the US did, offered different opportunities to men and women.
Conclusion
We find a gender wage gap of about thirty percent among cigar workers and compositors,
two occupations where men and women worked together and strength was not important.
Individual characteristics explain one-half to four-fifths of this wage gap. In this paper we
16
suggest that the remaining difference may be due to opportunities for training. At low levels of
experience women on average earned more than men, but men's wages quickly surpassed
women's wages and remained consistently higher. This pattern is consistent with men investing
more in training, accepting lower wages during the first few years in exchange for higher wages
later in their career.
Among cigar workers half of the wage gap remains unexplained even if we control for
firm characteristics. This gap may be due to women receiving less training than men; in all firms
women were less likely than men to be apprenticed. However, it was only at the larger firms that
women seem to have been constrained. At smaller firms training had a lower return and women
would have chosen training only if they expected to spend more than seven years in the industry.
While we cannot say what their expectations were, it is reasonable to explain the difference in
training as a choice. At larger firms, however, training had a higher return and women should
have been more likely to choose training. Since we don't see higher numbers of women
apprenticed at large firms, we conclude that women were not offered the same opportunities as
men.
Among compositors the gender gap is insignificant at small, non-metro firms. At these
firms the observed difference in wages is explained by individual characteristics. At small, nonmetro firms women were as likely to be apprenticed as men, and had apprenticeships of the same
length. At large, metro firms women were less likely than men to be apprentices, and were
apprenticed for shorter periods. It is possible that compositors at large firms chose not the be
apprenticed, since they would have to be in the labor market for at least seven years to make the
apprenticeship worthwhile.
The Swedish labor market for cigar workers and compositors was, for the most part, fair
to women. Most of the wage gap was explained by individual characteristics, and differences in
training were sometimes the result of women's choice. At the larger firms, however, we get hints
of the new twentieth-century labor market patterns, where men were offered better opportunities
for advancement, and thus earned more, than women.
17
References
Boot., H.M and J.H. Maindonald (2008). "New Estimates of Age- and Sex-Specific Earnings and
the Male:Female Earnings Gap in the British Cotton Industry, 1833-1906," Economic History
Review, 61: 380–408.
Burnette, J. (2015). “The paradox of progress: the emergence of wage discrimination,” European
Review of Economic History, 19: 128–148.
Burnette, J. and M. Stanfors (2015). “Estimating Historical Wage Profiles,” Historical Methods:
A Journal of Quantitative and Interdisciplinary History, 48: 35–51.
Collet, C. E. (1891). “Women’s Work in Leeds,” The Economic Journal, 1: 460–473.
Cooper, P. A. (1987). Once a Cigar Maker Men, Women, and Work Culture in American Cigar
Factories 1900–1919. Urbana, IL: University of Illinois Press.
Cox, H. (2003). “Tobacco Industry,” in J. Mokyr, (Ed.) The Oxford Encyclopedia of Economic
History. New York: Oxford University Press.
Elmquist, H. (1899). Undersökning af tobaksindustrien i Sverige. Stockholm:
Kommerskollegium.
Elmquist, H. (1909). Undersökning af tryckerier och därmed förenad handtering i Sverige.
Stockholm: Kommerskollegium.
England, Paula (1982) “The Failure of Human Capital Theory to Explain Occupational Sex
Segregation,” Journal of Human Resources, 17:358–370
Goldin, C. (1986). “Monitoring Costs and Occupational Segregation by Sex: A Historical
Analysis,” Journal of Labor Economics, 4: 1–27.
Hatton, T. (1997). “The Immigration Assimilation Puzzle in Late Nineteenth-Century America,”
Journal of Economic History, 57: 34–62
Jacoby, S. (1985). Employing Bureaucracy: Managers, Unions, and the Transformation of Work
in American Industry, 1900-1945. New York: Columbia University Press.
Mincer, Jacob, (1974). Schooling, Experience, and Earnings, Columbia Univ. Press.
Moriguchi, C. (2003). “Implicit Contracts, the Great Depression, and Institutional Change: A
Comparative Analysis of US and Japanese Employment Relations, 1920-1940,” Journal of
Economic History, 63: 625–665.
Oakeshott, G. (1900). “Women in the Cigar Trade in London,” Economic Journal, 10: 562–572.
18
Owen, L. (1995). “Worker Turnover in the 1920s: The Role of Changing Employment Policies,”
Industrial and Corporate Change, 4: 499–530.
Owen, L. (2001). “Gender Differences in Labor Turnover and the Development of Internal Labor
Markets in the United States during the 1920s,” Enterprise & Society, 2: 41–71.
Polachek, S.W. (1981). “Occupational Self-Selection: A Human Capital Approach to Sex
Differences in Occupational Structure,” Review of Economics and Statistics, 63: 60–69.
Polachek, S.W. and W.S. Siebert (1993). The Economics of Earnings. Cambridge: Cambridge
University Press.
Prus, M. J. (1990). “Mechanisation and the gender-based division of labour in the US cigar
industry,” Cambridge Journal of Economics, 14: 63–79.
Rosenbloom, J. and W. Sundstrom (2009). “Labor-Market Regimes in US Economic History,”
NBER Working Paper No 15055. Cambridge, MA: NBER.
Samuel, R. (1977). “Workshop of the World: Steam Power and Hand Technology in midVictorian Britain,” History Workshop, 3: 6–72.
Samuel, R. (1992). “Mechanization and Hand Labour in Industrializing Britain,” in Lenard R.
Berlanstein (Ed.) The Industrial Revolution and Work in Nineteenth-Century Europe. London:
Routledge.
Sandell, S. and D. Shapiro (1980). “Work Expectations, Human Capital Accumulation, and the
Wages of Young Women,” Journal of Human Resources, 15: 335–353.
Stanfors, M., T. Leunig, B. Eriksson and T. Karlsson (2014). “Gender, productivity and the
nature of work and pay: evidence from the late nineteenth-century tobacco industry,” Economic
History Review, 67: 48–65.
Sundstrom, William (1988). “Internal Labor Markets before World War I: One-the-Job Training
and Employee Promotion,” Explorations in Economic History, 25;424-445.
19
Table 1. Averages and shares (in percent) by gender for cigar makers (1898) and compositors
(1902/03).
Hourly wage (ore/hour)
Hours
Age
Age at start of work
Experience
Tenure
Firm Size
Cigar workers
Men
Women
24.20
16.40
(9.24)
(6.45)
56.85
55.85
(4.16)
(4.46)
34.42
29.58
(14.41)
(12.33)
14.24
18.63
(3.86)
(7.33)
20.17
10.95
(15.44)
(10.50)
7.56
5.59
(10.62)
(7.18)
112.26
139.97
(106.18) (129.43)
Compositors
Men
Women
38.31
26.86
(20.80)
(13.77)
56.66
57.29
(3.54)
(3.34)
29.21
27.10
(11.71)
(9.72)
14.71
16.65
(3.33)
(3.36)
14.50
10.45
(11.50)
(9.48)
7.30
6.02
(8.31)
(6.94)
68.68
46.68
(113.82)
(73.84)
Shares (in percent)
Secondary education
16
5
Union member
78
35
85
56
Member of friendly society
63
51
63
54
Married
42
19
39
8
Previously married
6
8
1
1
Kids at home
42
30
31
6
Night work
5
1
Sunday work
3
1
Free housing
2
2
Preparation worker
4
27
Bunch maker
5
15
Roller
83
47
Sorter
8
11
Machine compositor
8
2
Foreman
3
0
Apprentice
10
5
23
32
Metro Location
61
73
45
49
Number of observations
731
1,583
2,346
346
Standard deviations in parentheses.
Source: Specialundersökningar Tobaksindustrien 1898, Statistiska avdelningen, HIII b:1
samt HIII b:1 aa vol 1, Kommerskollegiets arkiv, National Archives (Riksarkivet),
Stockholm. Undersökning av tryckerier mm 1903, Avdelningen för arbetsstatstik, HII a:1
vol 1-6 samt HII a:2 vol 1-12, Kommerskollegiets arkiv, National Archives (Riksarkivet),
Stockholm.
20
Table 2. Hourly wages for men and women and wage gaps by occupation.
Compositors
All compositors
Compositor working by
hand
Compositor working by
machine
Apprentice
Cigar workers
All cigar workers
Preparation worker
Bunch maker
Roller
Sorter
Apprentice
Men
Women
Female-tomale ratio
38.3
43.0
26.9
32.4
0.70
0.75
68.0
55.4
0.81
14.1
13.7
0.97
24.2
17.3
8.6
25.0
29.9
12.0
16.4
11.1
13.0
19.4
21.0
12.2
0.68
0.64
1.51
0.78
0.70
1.02
Source: See Table 1.
21
Table 3. Coefficients of OLS wage estimations for cigar workers.
Raw
gender
wage gap
Model 1
Model 2
Model 3
–0.376
(0.020)
–0.265
(0.016)
0.294
(0.019)
–0.023
(0.003)
–0.009
(0.017)
0.023
(0.003)
0.002
(0.002)
–0.006
(0.006)
0.006
(0.004)
–0.028
(0.007)
–0.208
(0.016)
0.266
(0.018)
–0.022
(0.003)
0.004
(0.016)
0.022
(0.003)
–0.000
(0.002)
–0.002
(0.006)
0.004
(0.004)
–0.024
(0.007)
0.098
(0.021)
0.011
(0.030)
0.060
(0.019)
0.100
(0.015)
0.152
(0.015)
Constant
3.089
(0.016)
2.205
(0.052)
2.177
(0.050)
–0.172
(0.014)
0.211
(0.016)
–0.020
(0.002)
0.026
(0.014)
0.020
(0.002)
0.002
(0.002)
–0.005
(0.005)
0.005
(0.003)
–0.017
(0.006)
0.063
(0.018)
0.007
(0.026)
0.075
(0.016)
0.089
(0.013)
0.133
(0.013)
–0.370
(0.024)
–0.359
(0.018)
–0.351
(0.019)
0.117
(0.019)
2.442
(0.045)
R-squared
N
0.13
2,314
0.55
2,314
0.60
2,314
0.70
2,314
Female
Experience
Experience squared
Experience spline
Experience spline
squared
Tenure
Tenure squared/100
Age at start of work
Age at start of work
squared/100
Married
Previously married
Kids at home
Union member
Friendly society member
Apprentice
Preparation worker
Bunch maker
Sorter
Standard errors in parentheses.
Source: See Table 1.
22
Table 4. Coefficients of OLS wage estimations for compositors.
Female
Experience
Experience
squared
Experience
spline
Experience
spline squared
Tenure
Tenure squared
/100
Age at start of
work
Age at start of
work/100
Secondary
Education
Married
Raw
gender
wage gap
–0.341
(0.037)
Model 1
Model 2
Model 3
Model 4
–0.179
(0.021)
0.197
(0.017)
0.001
(0.002)
–0.191
(0.013)
–0.001
(0.002)
0.006
(0.002)
–0.012
(0.007)
0.052
(0.006)
–0.069
(0.010)
–0.075
(0.021)
0.151
(0.016)
0.002
(0.002)
–0.178
(0.012)
–0.003
(0.002)
0.001
(0.002)
0.001
(0.007)
0.041
(0.005)
–0.053
(0.009)
0.069
(0.018)
0.156
(0.025)
0.206
(0.062)
–0.006
(0.025)
0.203
(0.020)
0.118
(0.016)
0.350
(0.034)
0.078
(0.040)
–0.124
(0.048)
–0.062
(0.019)
0.169
(0.015)
0.001
(0.002)
–0.166
(0.012)
–0.001
(0.002)
–0.001
(0.002)
0.009
(0.006)
0.040
(0.005)
–0.052
(0.009)
0.063
(0.017)
0.137
(0.024)
0.141
(0.058)
–0.010
(0.023)
0.191
(0.019)
0.114
(0.015)
0.173
(0.033)
0.101
(0.038)
–0.102
(0.045)
0.478
(0.025)
–0.065
(0.018)
0.162
(0.015)
–0.005
(0.002)
–0.078
(0.012)
0.004
(0.002)
0.001
(0.002)
0.003
(0.006)
0.024
(0.005)
–0.031
(0.008)
0.049
(0.016)
0.123
(0.023)
0.134
(0.056)
–0.007
(0.022)
0.196
(0.018)
0.094
(0.014)
0.189
(0.032)
0.093
(0.036)
–0.088
(0.043)
0.455
(0.024)
–0.385
(0.024)
0.201
Previously
married
Kids at home
Union member
Freindly society
member
Night work
Sunday work
Free housing
Machine
compositor
Apprentice
Foreman
23
Constant
3.475
(0.013)
1.418
(0.074)
1.504
(0.068)
1.489
(0.064)
(0.037)
2.059
(0.071)
R squared
N
0.03
2,692
0.70
2,692
0.75
2,692
0.78
2692
0.80
2,692
Note: The spline breaks at 8 years of experience.
Source: See Table 1.
24
Table 5. Coefficients of OLS wage estimations (cigar workers), separately by gender, with
standard errors in parentheses.
Men
Experience
0.318
(0.026)
–0.019
(0.003)
–0.011
(0.024)
0.019
(0.003)
0.010
(0.003)
–0.021
(0.007)
0.002
(0.011)
–0.002
(0.026)
0.294
(0.025)
–0.019
(0.003)
0.013
(0.023)
0.019
(0.003)
0.001
(0.003)
–0.005
(0.007)
–0.006
(0.011)
0.016
(0.025)
0.058
(0.043)
0.041
(0.054)
0.089
(0.040)
0.118
(0.027)
0.177
(0.027)
Constant
1.935
(0.121)
R squared
N
0.65
731
Experience
squared
Experience
spline
Experience
spline squared
Tenure
Tenure squared
/100
Age at start of
work
Age at start of
work Sqrd/100
Married
Previously
married
Kids at home
Union member
Friendly society
member
Apprentice
Women
0.277
(0.022)
–0.023
(0.003)
0.012
(0.020)
0.023
(0.003)
–0.004
(0.004)
0.008
(0.012)
0.006
(0.004)
–0.028
(0.008)
0.251
(0.022)
–0.022
(0.003)
0.020
(0.019)
0.022
(0.003)
–0.002
(0.004)
0.007
(0.012)
0.004
(0.004)
–0.025
(0.008)
0.080
(0.025)
0.013
(0.035)
0.055
(0.022)
0.091
(0.018)
0.129
(0.018)
1.970
(0.114)
0.222
(0.025)
–0.016
(0.003)
0.024
(0.022)
0.016
(0.003)
0.004
(0.003)
–0.010
(0.007)
–0.018
(0.010)
0.046
(0.024)
0.043
(0.040)
0.027
(0.051)
0.100
(0.038)
0.128
(0.028)
0.163
(0.026)
–0.281
(0.043)
–0.194
(0.059)
–0.377
(0.054)
0.151
(0.035)
2.398
(0.120)
2.045
(0.060)
2.056
(0.059)
0.191
(0.018)
–0.018
(0.003)
0.024
(0.016)
0.018
(0.003)
–0.003
(0.003)
0.014
(0.010)
0.007
(0.004)
–0.021
(0.006)
0.040
(0.021)
0.018
(0.029)
0.065
(0.018)
0.071
(0.015)
0.112
(0.015)
–0.332
(0.030)
–0.388
(0.018)
–0.325
(0.020)
0.101
(0.022)
2.325
(0.050)
0.70
731
0.73
731
0.44
1,583
0.48
1,583
0.64
1,583
Preparation
worker
Bunch maker
Sorter
Note: The spline breaks at 8 years of experience for men and 6 for women.
Source: See Table 1.
25
Table 6. Coefficients of OLS wage estimations (compositors), separately by gender, with
standard errors in parentheses.
A. Men
Experience
Experience
squared
Experience spline
Experience spline
Squared
Tenure
Tenure
squared/100
Age at start of
work
Age at start of
work squared/100
Secondary
education
Married
Previously
married
Kids at home
Union member
Friendly society
member
Night work
Sunday work
Free housing
Model 1
0.212
(0.019)
0.001
(0.002)
–0.204
(0.014)
–0.001
(0.002)
0.007
(0.002)
–0.016
(0.007)
0.049
(0.006)
–0.065
(0.010)
Model 2
0.167
(0.018)
0.002
(0.002)
–0.191
(0.013)
–0.002
(0.002)
0.001
(0.002)
–0.001
(0.007)
0.038
(0.005)
–0.051
(0.009)
0.057
(0.018)
0.140
(0.025)
0.243
(0.065)
–0.002
(0.024)
0.189
(0.022)
0.115
(0.017)
0.386
(0.054)
0.054
(0.040)
–0.126
(0.051)
Machine
compositor
Apprentice
Foreman
26
Model 3
0.177
(0.017)
0.001
(0.002)
–0.183
(0.012)
–0.001
(0.002)
–0.000
(0.002)
0.005
(0.006)
0.037
(0.005)
–0.050
(0.009)
0.053
(0.017)
0.123
(0.024)
0.173
(0.062)
–0.005
(0.023)
0.176
(0.021)
0.108
(0.016)
0.221
(0.034)
0.080
(0.038)
–0.107
(0.048)
0.420
(0.025)
Model 4
0.171
(0.016)
–0.004
(0.002)
–0.089
(0.013)
0.004
(0.002)
0.002
(0.002)
–0.000
(0.006)
0.022
(0.005)
–0.029
(0.008)
0.041
(0.016)
0.112
(0.023)
0.165
(0.059)
–0.002
(0.022)
0.190
(0.020)
0.086
(0.015)
0.235
(0.032)
0.071
(0.036)
–0.079
(0.045)
0.405
(0.024)
–0.396
(0.027)
0.196
(0.036)
Constant
1.375
(0.079)
1.475
(0.073)
1.471
(0.069)
2.052
(0.076)
R squared
N
0.72
2,346
0.76
2,346
0.79
2346
0.81
2,346
Model 3
0.008
(0.079)
0.048
(0.016)
–0.364
(0.062)
–0.049
(0.016)
–0.002
(0.008)
0.029
(0.032)
0.066
(0.027)
–0.112
(0.065)
0.125
(0.078)
0.195
(0.098)
0.103
(0.180)
–0.109
(0.119)
0.220
(0.039)
0.202
(0.040)
–0.305
(0.138)
0.472
(0.212)
0.051
(0.114)
1.257
Model 4
0.065
(0.079)
0.029
(0.017)
–0.276
(0.065)
–0.030
(0.017)
–0.001
(0.008)
0.026
(0.032)
0.062
(0.027)
–0.111
(0.064)
0.111
(0.077)
0.192
(0.096)
0.100
(0.177)
–0.100
(0.117)
0.206
(0.039)
0.193
(0.039)
–0.316
(0.135)
0.453
(0.209)
0.014
(0.121)
1.177
B. Women
Experience
Experience
squared
Experience spline
Experience spline
Squared
Tenure
Tenure
squared/100
Age at start of
work
Age at start of
work squared/100
Secondary
Education
Married
Previously
married
Kids at home
Union member
Friendly society
member
Night work
Sunday work
Free housing
Model 1
–0.253
(0.093)
0.108
(0.020)
–0.568
(0.075)
–0.109
(0.020)
–0.003
(0.010)
0.024
(0.040)
0.055
(0.033)
–0.057
(0.081)
Model 2
–0.262
(0.086)
0.095
(0.018)
–0.470
(0.070)
–0.096
(0.018)
0.001
(0.010)
0.026
(0.037)
0.046
(0.031)
–0.041
(0.075)
0.219
(0.089)
0.161
(0.113)
–0.010
(0.208)
–0.017
(0.137)
0.227
(0.045)
0.182
(0.046)
–0.387
(0.159)
0.449
(0.245)
–0.012
(0.132)
Machine
27
compositor
Apprentice
(0.120)
1.660
(0.345)
1.737
(0.317)
1.286
(0.278)
(0.120)
–0.200
(0.056)
0.026
(0.318)
1.105
(0.118)
1.512
(0.281)
0.63
346
0.70
346
0.77
346
0.78
346
Foreman
Machine
compositor
Constant
R squared
N
Note: The spline breaks at 8 years of experience for men and at 4 years for women.
Source: See Table 1.
28
Table 7. Estimates of wage gain from a male wage profile relative to a female wage profile.
Years of
experience
0
1
2
3
4
5
6
7
8
9
10
Cigar workers
Wage gain
Cumulative
–26.61
–21.41
–8.90
12.26
42.15
79.29
120.55
143.89
145.82
144.01
142.16
Compositors
Wage gain Cumulative
–26.61
–46.63
–54.40
–44.39
–12.23
44.30
124.62
214.23
299.10
377.43
449.69
–23.25
8.02
16.96
–1.93
–74.56
–6.85
78.77
186.48
321.50
314.42
306.95
–23.25
–15.75
–0.94
–2.51
–59.39
–64.27
–11.78
104.35
291.46
462.49
618.53
Notes: Male and female wages are predicted wages for a worker who started work at age 16
and stayed at the same firm, from Model 2 for cigar workers and Model 3 for compositors.
The wage gain is equal to the predicted male wage less the predicted female wage (in krona
per year, assuming a work week of 55 hours and a work year of 50 weeks). The cumulative
wage gain provides the sum of the wage gain in each year discounted back to year zero at 7
percent interest.
Source: See Table 1.
29
Table 8. Gender Wage Gap Controlling for Firm Characteristics.
Female
Firm size
(workforce in
1000s)
Big city location
R squared
N
Source: See Table 1.
Cigar workers
Controlling for
Firm fixed
firm Size
effects
–0.191
–0.207
(0.014)
(0.016)
–0.045
(0.049)
0.107
(0.012)
0.71
2,314
Compositors
Controlling for
Firm fixed
firm size
effects
–0.080
–0.025
(0.018)
(0.021)
–0.068
(0.055)
0.194
(0.012)
0.75
2,314
0.82
2,692
0.87
2,692
Table 9. Estimates of the gender wage gap (i.e., coefficient of female dummy in log points)
among cigar workers and compositors from OLS regressions, by firm size and location.
Dummy
only
Model 1
Model 2
Model 3
Model 4
Cigar workers
Small firm
–0.353
–0.203
–0.152
–0.111
(0.028)
(0.022)
(0.023)
(0.020)
Large firm
–0.420
–0.346
–0.276
–0.240
(0.028)
(0.023)
(0.023)
(0.020)
Metro firm
–0.368
–0.319
–0.258
–0.223
(0.022)
(0.019)
(0.019)
(0.017)
Non-metro firm
–0.471
–0.160
–0.092
–0.096
(0.038)
(0.031)
(0.034)
(0.030)
Compositors
Small firm
–0.329
–0.181
–0.075
–0.063
–0.043
(0.050)
(0.027)
(0.027)
(0.026)
(0.025)
Large firm
–0.264
–0.132
–0.058
–0.048
–0.085
(0.052)
(0.033)
(0.031)
(0.029)
(0.028)
Metro firm
–0.343
–0.203
–0.107
–0.095
–0.112
(0.042)
(0.028)
(0.026)
(0.024)
(0.023)
Non-Metro
–0.374
–0.173
–0.074
–0.064
–0.043
firm
(0.054)
(0.029)
(0.028)
(0.027)
(0.026)
Note: Small firms are those with 90 workers or fewer for cigar workers and 24 workers or fewer
for compositors.
Source: See Table 1.
30
Table 10. Percentage apprenticed among cigar workers and compositors according to
years of experience, by gender, firm size and location.
All
Small firm
Large firm
Metro firms
Non-Metro
Cigar workers
0-5 years of
6-10 years of
experience
experience
Men Women Men Women
40.4
10.5
1.0
3.5
44.0
14.6
1.8
3.2
33.9
5.0
0.0
3.8
50.2
8.7
1.7
4.0
27.6
13.1
0.0
1.6
Compositors
0-5 years of
6-10 years of
experience
experience
Men
Women Men Women
82.6
73.1
10.4
6.8
85.4
86.9
12.3
12.2
77.8
43.5
8.3
0.0
72.2
50.8
8.1
5.1
87.1
88.4
12.2
8.6
Source: See Table 1.
Table 11. Estimates of wage gain from a male wage profile relative to a female wage profile.
Small firms
Large firms
Years of
Wage gain
Cumulative
Wage gain Cumulative
experience
0
–9.33
–9.33
–42.29
–42.29
1
–21.39
–29.31
–16.87
–58.06
2
–30.18
–55.67
17.28
–42.97
3
–30.42
–80.50
57.81
4.22
4
–17.24
–93.65
100.84
81.15
5
11.97
–85.12
141.42
181.98
6
56.16
–47.70
174.33
298.15
7
74.06
–1.58
201.91
423.88
8
72.75
40.76
205.58
543.53
9
67.88
77.68
204.08
654.54
10
63.34
109.88
202.43
757.44
Notes: Male and female wages are predicted wages for a worker who started work at age 16
and stayed at the same firm, from Model 2. The wage gain is equal to the predicted male
wage less the predicted female wage (in krona per year, assuming a work week of 55 hours
and a work year of 50 weeks). The cumulative wage gain provides the sum of the wage gain
in each year discounted back to year zero at 7 percent interest.
Source: See Table 1.
31
Figure 1. Experience-wage profiles for cigar workers, by gender.
3.2 3 lnwage 2.8 2.6 2.4 Men 2.2 Women 2 1.8 1.6 0 5 10 15 20 25 30 Experience Source: See Table 1.
Figure 2. Experience-wage profiles for compositors, by gender.
4 lnwage 3.5 3 Men 2.5 Women 2 1.5 0 5 10 15 20 25 Experience 32
30 Source: See Table 1.
Figure 3. Percentage of cigar workers currently apprenticed, by gender and experience.
50 Percent Apprenticed 45 40 35 30 25 Men 20 Women 15 10 5 0 0 2 4 6 8 10 12 Years of Experience Source: See Table 1.
Figure 4. Percentage of compositors currently apprenticed, by gender and experience.
120 Men Percent apprenticed 100 Women 80 60 40 20 0 0 2 4 6 8 Years of experience 10 Source: See Table 1.
33
12 Figure 5. Apprenticeship of compositors, by gender and size of firm.
A. Small firms
1.2 Percent Apprentices 1 Men Women 0.8 0.6 0.4 0.2 0 0 2 4 6 8 10 Years Experience B. Large firms
1.2 Men 1 Percent Apprnetices Women 0.8 0.6 0.4 0.2 0 0 2 4 6 Years Experience Source: See Table 1.
34
8 10 Figure 6. Wage profiles for cigar workers, by gender and firm size.
3.3 3.1 2.9 2.7 Men, small 7irms 2.5 Women, small 7irms 2.3 Men, large 7irms 2.1 Women, large 7irms 1.9 1.7 1.5 0 5 10 15 20 25 Source: See Table 1.
35
30