was pre-industrial society malthusian - university of...
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Was Pre-Industrial Society Malthusian? Evidence from England and New France
Gregory Clark (UC-Davis) and Gillian Hamilton (University of Toronto)
1
Fundamental to the Malthusian model of pre-industrial society is the assumption that higher income increased reproductive success. Despite the seemingly inescapable logic of this model, the empirical support for this vital assumption is surprisingly weak. Here we examine this relationship using large new cross-sectional sets of data on reproductive success, social status and income for both England and New France in the seventeenth century. We find that for seventeenth century England, a society seemingly in a Malthusian equilibrium, wealth strongly predicts reproductive success. But in land abundant New France, where population was growing rapidly, reproductive success was independent of income.
An essential assumption of the Malthusian model of pre-industrial society is that
population growth, birth rates minus death rates, increases with income per person. This
assumption, combined with the assumption of diminishing returns to land as a factor of
production, generates the long run Malthusian equilibrium where wages are at the subsistence
level. Figure 1 shows the vital assumption. However, tests of this assumption for pre-industrial
England, France and Japan have often failed to detect any link between either mortality and real
incomes or fertility and real incomes, to the point where some commentators dispute the
usefulness of the Malthusian model as the description of the pre-industrial world.1 Here we
develop two ways to test the Malthusian assumption for large cross sections of the population in
seventeenth century England and New France. Our results are a surprising mix. In England we
find strong support for the Malthusian model. But the data from New France strongly rejects it.
In the conclusion we consider whether these findings can be reconciled with the logic of the
Malthusian model.
Previous attempts to confirm this element of the Malthusian model have generally looked
separately at fertility (the preventive check) or mortality (the positive check), even though it is
the balance of these that determines reproductive success. The results, as noted, have been
mixed.
2
Real income, for example, varied dramatically from year to year in the pre-industrial
world because of harvest failures. Thus researchers have examined the correlation of grain
prices and mortality, fertility and marriage rates in countries such as England, France and Japan.
In all three cases they find high grain prices had at best modest effects on any of these variables.2
But perhaps short term fluctuations in real incomes were not the main determinants of
reproductive success. There were important variations in long term real wages in the pre-
industrial era. Real wages in England, for example, were at extraordinarily high levels in the
fifteen century and very low levels in early fourteenth and seventeenth century. Life expectancy
at birth does not seem to have been any higher in the high wage eras, certainly in the years 1538-
1800.3 But comparing life expectancy with wages across epochs will only reveal if there was an
inverse connection between income and wages under some conditions. Specifically the reason
for the variation in real wages across epochs has to be changes in fertility rates, as opposed to
changes in mortality rates at a given wage level created by changes in disease or climate.
That means that to test the relationship between income and reproductive success we
have to look at cross sections of the pre-industrial population. Here the results have been
surprisingly mixed. In England the famous study by Hollingsworth on the British peerage
suggested that despite their very high incomes of the Peerage before 1700 their life expectancy at
birth was lower than for the average person in England. Only after the late eighteenth century
did the aristocracy exhibit a higher life expectancy than the general population.4
But there are other sources that confirm the expected link between higher income and
lower mortality. Infant mortality rates in eight London parishes, for example, in the years 1538-
1653 can be compared with the percentage of the households in each parish which were
‘substantial’ in the tax listings of 1638. There is a clear association between household income
3
and a child’s chance of surviving the first year of life, with the richer parishes having less than
half the infant mortality of the poorer ones. Indeed the crude measure of household income used
here explains 62% of the variation in infant mortality rates.5
Razi finds evidence among the male property owners of medieval Halesowen of greater
life expectancy among tenants of more substantial holdings in the period before the onset of the
Black Death. Thus cottagers and small holders had a life expectancy of 20.8 years on taking up a
holding, while the substantial tenants had a life expectancy of 33.3 years. But in the years 1350
to 1400 after the onset of the Black Death this differential disappeared, with small and large
tenants having about the same life expectancy (Razi (1980)).
In France it has been possible to link family reconstitution studies for individual
communities with records of occupation, literacy and wealth. Earlier studies found little
relationship, or even a positive relationship between wealth and infant mortality.6 But
recent studies of individual communities in the eighteenth centuries by David Weir and Hajime
Hadeishi have found connections between wealth and reproductive success in line with the
Malthusian assumptions, looking at the experience of married males. Weir’s (1995) seminal
study, based on 47 families, found that the rich in Rosny-Sous-Bois produced more surviving
children than the poor. This relationship existed primarily because wealthier men married
younger women, and their offspring survived better. Hadeishi (2003) with a slightly larger
sample of 216 families similarly finds that wealthier families in Nuits had more births per year of
marriage. But the size of this effect is not great quantitatively, and the survival rates of children
are unknown. Given the sample sizes of these studies, replication on a larger scale is
worthwhile.
4
For colonial America Kantrow’s study of the demography of the elite, represented by 15
“founder families” in Philadelphia suggests that they had both very high fertility and low
mortality. Marital fertility for Philadelphia’s gentry was very high, close to the biological
maximum, with a total fertility of 9.9.7 The survival rate of these children was good, with crude
death rates among the gentry of only 21 per 1000 in the eighteenth century, compared to 42.6 for
the years 1722 to 1775 for the Philadelphia population as a whole.8 But other than this very little
is known about the relationship between socioeconomic status and mortality or fertility during
the colonial era.9
To shed more light on this subject, we examine the relationship between income or
socioeconomic status and surviving family size in two very different locations, England 1585 -
1636 and 17th century New France. We make use of two population samples which yield for a
large number of people in diverse occupations and economic circumstances estimates of the
numbers of surviving offspring at time of death. For England, we exploit a new individual level
data set that is able to better estimate the relationship between wealth and the numbers of
surviving offspring at time of death and for New France we make use of one of the best
reconstituted family data sets available—one that encompasses almost the entire population of
the colony. Our results are very different. In England there is a strong positive association
between surviving children and wealth, and a weaker but still positive association between
surviving children and occupational status. In New France there is no general association
between social status and reproductive success. In the conclusion we consider the reasons for
these very different results. We also consider whether they can be regarded as consistent with
the Malthusian interpretation of the pre-industrial world.
5
II. Evidence for Malthusian Constraints, England 1585 -1636
Parish register records of baptisms, burials and marriages which are the raw material of
demographic enquiry for pre-industrial England have been mute on the issue of reproductive
success and income or wealth, because of the difficulty of systematically linking family
reconstitution records with those on the material and social circumstances of families. There is
another source of information on pre-industrial demography, however, which has been employed
for the years before 1538 when parish registers began to be maintained on a regular basis. That
is the wills of testators. Robert Gottfried, for example, used wills as the main evidence for
demographic trends in East Anglia in the fifteenth century, and in Bury St. Edmunds in the years
before 1538 (Gottfried (1978, 1982)).
Here we use a sample of wills by male testators in the years 1585 -1636 to examine whether
individuals in pre-industrial England with higher incomes had greater reproductive success.
These dates were chosen because of the existence of a number of printed sources summarizing
comprehensive samples of wills in various locations for these years. Despite the assumed
Malthusian nature of the pre-industrial economy, English population unusually was growing at
the moderate rate of about 0.56% per year in this interval. Thus Wrigley et al. estimate that from
1586 to 1836 the average net reproduction rate, the average number of daughters living to
adulthood a woman would produce if she lived through the reproductive years, was 1.24
(Wrigley et al. (1997), p. 614). But evidence of population growth is not inconsistent with the
assumption that this was a Malthusian economy. Population growth could stem from slow
advances in technology or from changes in mortality or fertility rates within the Malthusian
framework. We can still test to see whether within these years those with more economic
success enjoyed greater reproductive success.
6
Wills were also not made by a random sample of the population, but were instead made by
those who had some property to bequeath.10 But the custom of making wills seems to have
extended fairly far down the social hierarchy, at least in East Anglia where most of our sample of
wills was drawn. Table 1 shows for the sample of 2,030 wills we use the major occupations
recorded. As the table implies higher income individuals were undoubtedly more likely to make
wills, but there are plenty of wills available for those at the bottom of the hierarchy such as
laborers, sailors, shepherds, and husbandmen.
Wills in this period seem have been made close to the death of the deceased typically. The
maximal time between the writing of the will and the death of the testator can be established by
comparing the date of the will with the date probate was granted. Figure 2 shows the distribution
of the maximum time between will writing and death in the sample we use here. 77% of wills
were probated within one year of their composition. Thus more than 77% of these wills were
made within a year of the decease of the testator, and give a picture of the testator’s surviving
children and their economic status at the time of their death. Only wills probated within 5 years
of their construction were included in the sample. The sample was also confined to written wills,
excluding “nuncupative” wills, which were oral declarations in extremis written down later by
witnesses, since we assume such wills were much less complete in listing surviving children and
assets.
Those who died of illnesses will be over-represented by wills as a share of all deaths, since
those who died suddenly from violence or accident would be less likely to leave wills. But other
evidence suggests that in pre-industrial England deaths from violence and accident would
typically represent less than 2% of all male deaths. Thus the biases from using wills to
investigate numbers of survivors will be limited.
7
The sample of wills used to test the Malthusian assumptions is composed mainly of wills
from testators in Essex and Suffolk, but includes a group of wills from London, as well as from
smaller towns outside this region such as Bristol and Darlington. Inclusion in the sample was
determined by what was available in published transcripts of wills for these years.
The wills employed contain some or all of the following information: occupation of the
testator, marital status (married, widowed, single),11 number and genders of children,12 number
of daughters known to be married, literacy of the testator,13 monies bequeathed, and to whom,
the number of houses bequeathed, whether land was bequeathed (generally the amount of land
was not specified) and other goods bequeathed that have an ascertainable value (silver spoons,
horses, cattle, sheep, pigs, grains). Some important information is almost never present,
however, such as the age of the testator. Since we shall see that one major predictor of the
number of surviving children is the assets of the testator, we show below that this was not just a
life cycle effect where wealth proxies for the age of the testator.
Below is the summary of a typical will from Suffolk in 1623
JOHN WISEMAN of Thorington, Carpenter (signed with X), 31 January 1623.
To youngest son Thomas Wiseman, £15 paid by executrix when 22. Wife Joan to be executrix, and she to bring up said Thomas well and honestly in good order and education till he be 14, and then she is to bind him as apprentice. To eldest son John Wiseman, £5. To son Robert Wiseman, £5 when 22. To daughter Margery, £2, and to daughter Elizabeth, £2. To son Matthew Wiseman, £0.25. Rest of goods, ready money, bonds, and lease of house where testator dwells and lands belonging to go to wife Joan. Probate, 15 May 1623. (Allen (1989), p. 266.)
Wills of this period, unlike the wills of the fifteenth century investigated by Gottfried,
seem to typically mention nearly all surviving children or their descendants. Table 2, for
example, shows the number of children, and of sons and daughters mentioned in wills by the
8
residence of the testator. Potentially some children were omitted from wills by being left no
bequest. But the evidence is that the numbers of omitted children must be small. Daughters
were much more likely than sons to be excluded from wills. Where they can be valued bequests
to daughters are generally smaller than for sons. Also daughters often received gifts at marriage
that seem to have been regarded as being their share of the inheritance. So if any children are
omitted they would be disproportionately daughters. Yet only in rural areas is their any evidence
of omitted daughters, in terms of more sons being mentioned than daughters. And the implied
numbers of omitted daughters overall is small: 5% of all daughters. In comparison Gottfried
finds for fifteenth century wills that at least 38% of daughters were omitted from the wills.14
Thus English wills of this period seem to give a good picture of the reproductive success of the
testators. And even if some daughters were missing this would bias the results discussed below
only if the omission was more frequent for high or low income testators.
As can be seen in Table 2 the average numbers of children per testator were modest. For a
population to be just reproducing itself the numbers of children surviving each male at time of
death would have to exceed two. It has to exceed two since some of these children are minors
who would die before they would reach the age where they would be potentially writing wills.
Testators in London circa 1620 were thus definitely not reproducing themselves. These outside
London in smaller towns, with 2.24 surviving children per testator, were potentially but not
assuredly reproducing themselves. Only for testators in the countryside can we be reasonably
confident that their successors were a growing population.
To simplify the occupation structure somewhat we organized male testators in both England
and New France into the seven social categories shown in Table 3. As can be seen in Table 4
these categories as a whole correlate well in England with other measures of social status,
9
literacy and assets bequeathed. But within each social group there are wide variations in the
economic position of the testator. There were some laborers as rich as the average craftsman or
trader, and some craftsmen as rich as the average merchant, cleric or attorney. Many
husbandmen were richer than the average yeoman. Similarly some laborers were literate, and
many yeomen illiterate.
The estimated assets of testators were constructed from the information in wills by adding
together the cash payments directed by the testator, with the estimated value of houses, land,
animals, grain, specified by the testator in the will. While land was bequeathed in 815 of the
wills in our sample, in only 124 cases, less than one in six, was the area specified. To infer the
area in the other 691 cases we regressed the land area in the 124 cases where the area was
specified on the number of houses bequeathed (HOUSES), the amount of cash bequeathed
(CASH), the value of the goods bequeathed (STOCK), an indicator for the literacy of the testator
(DLIT), an indicator for whether the person was called a yeoman (YEOMAN), and an indicator
of whether the person engaged in farming (DFARM). DFARM was set to 1 if the testator left
farm animals or grain in the will, or left farm implements. The estimated expression for the area
is
AREA = 4.980×HOUSES + 0.0315×CASH + 0.0336×STOCK + 3.519×DLIT (1.088) (0.0125) (0.0751) (2.371)
1.792×DLITUNKNOWN + 5.905×DYEOMAN + 3.937×DFARM (2.339) (2.358) (3.295)
R-squared = 0.62 N = 124, with the standard error of each estimated coefficient below in parentheses. In constructing the
value of the stock left a standard set of values was used: horses £5, cattle £4, sheep £0.5, pigs £2,
wheat (bu.) £0.21, barley/malt (bu.) £0.10, oats (bu.) £0.07, peas/beans (bu.) £0.12, silver spoons
10
£0.38. To normalize for changes in the price level over the years 1585 -1836 the “CASH”
variable in the above equation was constructed as the actual cash bequests in the will normalized
by the average price level in each of the decades 1580-9, 1590-9, 1600-9, 1610-9, 1620-9 and
1630-9.
We then constructed a monetary measure of the wealth bequeathed by the testator at the
time of death by adding to the value of the money and stock bequeathed an estimated value for
houses (£40 each) and for land (£10 per acre). For male testators where we have enough
information to estimate assets bequeathed the average value of assets equaled £230 in 1630s
prices (1.16 houses, 9.7 acres of land, £83 in cash bequests (in the prices of 1630-9) and £4 in
stock). The yearly earnings of a carpenter in this period would be about £18, so this is equal to
about 13 times the wage of a skilled manual worker.
Were the numbers of surviving children linked to the likely income of the person in these
years? To investigate this we consider both married testators, and all testators included those
unmarried (in part we proceed in this way because our data for New France concerns only
married men). Table 5 shows the estimated coefficients of a negative binomial regression of the
numbers of children on various characteristics of testators associated with income, including
literacy and occupational status, controlling for the residence of the testator.15 As can be seen
married testators in London left typically about 18% fewer children than those in rural areas.
Married testators in smaller towns typically have about 22% fewer surviving children.
Controlling for location, there are still a number of significant occupation effects, which
illustrate that many groups had higher numbers of surviving children than laborers and servants
(the omitted category). The relative magnitudes of these coefficients also reveal a pattern, with
the elite possessing the largest numbers of children. Figure 3 shows the numbers of surviving
11
children by these broad occupational classes, controlling just for residency, as inferred from the
negative binomial regression. Once we include literacy in the regression (columns 1 and 3),
which is highly correlated with occupational status, the coefficients on the high status trades
(gentry and merchant-professional) become smaller, but they are still positive and statistically
significant. Adding a control for literacy indicates that the literate have about 10% more
children, all else equal.
As we noted above the occupational labels used to form people into status classes are
imprecise. There are husbandmen who are literate and wealthier than yeomen who are illiterate.
There are carpenters who work for others and own no assets, and there are carpenters who are
employers and engage in building and leasing property. The estimated value of bequests is an
alternative measure of the economic status of males. We sorted males with information on
bequests into eight asset classes: no specific bequests, £0-9.99, £10-24.99, £25-49.99, £50-99.99,
£100-199.99, £200-499.99, £500-. We then looked at the association between the size of
bequests and the numbers of children. As Table 6 shows the association between assets and
surviving children is even stronger than for occupational status, even though we have a very
imperfect measure of assets. Figure 4 shows the estimated numbers of children per male of each
bequest class. For all married men someone with less than £10 in bequests would typically have
two children, while someone with £500 or more, four children. Assets predict survivors much
better than occupation. For a sample restricted to married men with asset information and
occupations the Pseudo R2 for assets is 0.027, while for status it is 0.008.
The strong positive association of bequeathed assets with numbers of surviving children
might be explained by assets proxying for the age of the testator, if assets were steadily
12
accumulated over the course of men’s lives. But we can rule this out as an explanation of the
association between assets and surviving children for a number of reasons.
First, we know from other data from the pre-industrial era, in particular David Weir’s
study of Rosny-Sous-Bois in 1747, that while there is some association between age and assets
for heads of households, age explains a tiny fraction of the variation in assets or incomes (Weir
(1995), p. 11). Further the association is not linear, but rather an inverted U. Average assets per
household are about the same from the 30s to the 60s, but they are smaller for those in the 20s or
in the 70s. Such a pattern of variation of assets with age would not explain the patterns we
discover above.
Second there is evidence from within our English sample that bequeathed wealth did not
increase much with age. Looking just at men who have been married at least once, an indicator
for the age of the testator which is independent of their success in producing offspring, is
whether at least one wife predeceased them. Married men who have been widowed at least once
on average will be considerably older than married men who have never been widowed. Column
2 of Table 6 tests this proposition by looking at the numbers of children per married testator
including an indicator for widowers. Widowers on average had 29% more children than married
men whose first spouse was still alive. Thus being a widower is an indicator for older testators.
Since in any marriage one spouse has to die first, this indicator for age should be
independent of anything about the testator’s circumstances other than those things dependent on
their age. Thus if testators tended to accumulate not just surviving children with age, but also
assets to bequeath, then looking at married men, those widowed being on average older should
have more assets. Table 7 reports a regression estimate for married men of assets as a function
of occupation, residence, and whether they were predeceased by a wife. Widowhood is
13
associated with a modest decline in assets bequeathed. Since we will not detect the existence of
the earlier wife in at least some cases where widowers had no surviving children by that spouse,
we also carried out this regression with the smaller subsample of married men with at least one
surviving children. This does not change the results. Indeed now being a widower is more
strongly associated with a smaller size of bequest. This may be because of dissaving by older
testators in the years prior to their deaths.
Thirdly, while we find in later samples that age is positively associated with probate
inventory wealth, age turns out to explain a tiny share of the variation in wealth across
individuals. Lindert (1985) contains information on a large sample of deceased in 1875, their
ages, occupations and probate wealth (wealth aside from real estate). Age is significantly
correlated with probate wealth. But the amount of the variation in wealth that age explains is
tiny. On its own age explains about 2% of probate wealth variation. Occupation in contrast
explains about 19% of the variation. And indeed if we add age variables to the regression once
occupation is already included it increases the R2 by a mere .006. Assuming that asset
accumulation over the life cycle was similar in 1580-36 to 1875 the amount of the variation in
assets that age explains will be trivial. Thus if assets are a good predictor of the numbers of
surviving children it must be for reasons other than that they are just a proxy for the age of the
testator. This strong association of assets and reproductive success is surprising since we have
such a weak measure of the assets bequeathed. The implication would be that the real effects of
wealth on reproductive success must be even stronger than the ones observed here.
Thus in seventeenth century England we see evidence of selective survival of the
offspring of individuals of certain characteristics. These are individuals who accumulate wealth,
14
or inherit it and do not dissipate it, and individuals with higher levels of literacy and higher
earning jobs.
III. Survival in a Frontier Society – Seventeenth Century New France
Settlement of New France began in the early 1600s. Quebec City was established in
1608 and Montreal in 1642. The population was small in the seventeenth century, only reaching
10,000 around 1681 and doubling that value in less than 30 years.16 The French that crossed the
Atlantic and settled in New France in the mid to late seventeenth century were disproportionately
urban and of a middling sort. Rural peasants appear to have been under-represented.17 Yet most
of the immigrants ended up settling the rural areas of New France, acquiring farms at first near
Quebec City, but soon spreading out in thin farms along the St. Lawrence River.
The data for New France consist of reconstituted family data elicited from birth, marriage,
and death Catholic parish records, linked across generations by demographers at the University
of Montreal.18 Reconstituting the native-born population has been particularly successful, in part
because Catholic parishes were established early in the colony's history in the early seventeenth
century, and few records have been lost through neglect or disaster.19 In addition, the colony's
early immigrants were exclusively Catholic by government decree. In some cases, the parish
records have been supplemented by census and notary records. These sources provide extra
information on family composition, literacy measured through the ability to sign one's name, and
occupation or status. There are omissions, but because of extensive cross-checking the gaps are
believed to represent a small minority of the native-born population. For example, Charbonneau
et al. (1993) estimate that 20,680 non-aboriginal people were born in the Quebec area before
15
1700, 19,580 of which are documented in this data set. Marriage and death information is
known in about 85 percent of cases (Charbonneau et al. (1993: 62)).
While these parish data capture the vast majority of the native-born population, the records
on immigrants are naturally much spottier and systematically over-represent immigrants who
married or died in the province. This is not expected to be a major source of bias because most
births and marriages occur after 1680, by which time the flow of immigrants had slowed and the
population was growing primarily through natural increase. Compared to colonial America,
New France was a relatively closed society.20
Linking all of these registers produces a record of each person's vital life history: for those
whose birth and death was recorded in the colony, we know whether they married, and if so, the
dates of each marriage (if there was more than one), known vital information about the spouse,
and the number and sequence of children produced from each marriage. If the spouse was born
outside the colony sometimes less is known about their birth date and place and hence their life
span.
The parish registers often included information on occupation. Occupation is more likely to
have been identified for married men, who left a longer paper trail in the marriage and birth
registers. An individual’s occupation often changed through his life, so to match most closely
our information from English wills, we used the male’s occupation listed on the document
closest to the time of his death.
Apart from this occupation coding, two sets of individuals that were likely wealthy have
been identified through information in the parish and notary public's records. 21 The first is
members and offspring of the nobility (Gadoury, 1991). French royalty conferred noble title,
which was inherited through the male line. The nobility were afforded privileges not enjoyed by
16
the typical resident.22 The second is members and offspring of the `bourgeois' class (Noguera,
1994). `Bourgeois' was often a self-appointed title taken by men with relatively high status
occupations, such as large-scale merchants or crown appointed officials (a complete list appears
in the data appendix). Because Noguera and Gadoury drew on occupation and other information
from all records, and not just the document closest to the time of the individual’s death, these are
more accurate measures of high-end socio-economic groups. In general, these two categories are
more selective than the socio-economic categories that utilize a single occupation record.23
The variable of interest is the number of children outliving their father. To measure this
all of an individual’s marriages and births are considered, hence we examine the survival of birth
children (excluding step-children). The restriction of the sample here to those who married
(which gives us information on their literacy and social status) means that we can only compare
these results to those of married males in England.
The sample consists of men who experienced their first marriage in New France between
1660 and 1710, for whom life span is known. Restricting the sample to those individuals with
known life span is clearly necessary given that we are focusing on surviving children. The
marriage year restriction is imposed because of potential sample biases that arise for marriage
after 1710. For instance, we restrict the sample of individuals born in the province to those born
before 1700 because the reconstitution does not extend beyond 1800 (hence life span information
may not be available for those born in the eighteenth century). As a result, information on
children’s life span is less likely to be available the later into the eighteenth century the birth
occurred. In addition, for marriages that occur late enough in the 1700s, family size may be
censured. Hence marriages after 1710 are dropped. The records are also somewhat spottier
17
before roughly 1660, so death information is less likely to be available for births that occurred
prior to this date.
3,019 men married for the first time between 1660 and 1710 (Table 8). Occupation is
identified for just over half of the men. Overall, just 9 percent are part of the elite, while another
11 percent are in the professional-merchant social group (see Table 3 for the occupations in each
category). Farmers comprised 14 percent of the sample. The husbandman category included
156 men, or another 4 percent of the sample, but almost all of these men were part of the
military. This clearly understates the relative importance of farming in New France. It is likely
that most of the individuals who did not declare an occupation in one of their parish records
worked the land in some capacity. The vast majority in the occupation “unknown” category
were born in the province: 82 percent, compared to an overall mean of 62 percent. They
overwhelmingly married in a rural setting (only 15 percent urban, compared to an average of 32
percent for all men) and they exhibited the same low levels of literacy as farmers, at roughly 15
percent.
As noted above, the literacy level was much higher for those in high social groups.
Sixty-five percent of the elite could sign their name, compared with less than 20 percent of either
farmers, laborers, husbandmen or those with an unstated occupation. Taken as a whole, just one-
quarter of men were able to sign their marriage registers, a much lower proportion than found in
England.
The overall average age at first marriage was 27.7 years. It was higher among the elite,
29.5 years of age, but also especially high among husbandmen (31.6 years of age). This was
likely due to the fact that these men were predominantly immigrants that arrived as single
18
soldiers. Farmers and those in the unknown category tended to be relatively young when they
married, at 28.2 and 26.4 years respectively.
Their typical spouse was 20 years old at the time of their marriage.24 Wives of the elite
were older (21.3 years of age), while the typical wife of a farmer or laborer was fairly young, at
18 and 19.2 years of age respectively. Married men lived, on average, to age 62. Their wives
had an average life span of 60 years. Farmers typically lived a few extra years, while those of
the elite had comparatively short lives. Fifty percent of men who were widowed remarried, with
those in the upper end of the social spectrum more likely to remarry than others.
Husbands fathered an average of 7.8 children during their first marriage (Table 9).
Counting all of their marriages, the total rises to 9.0 children. Just less than 4 of the children
from their first marriage (3.9) were living at the time of their death. Counting all of their
progeny, this total rises to 4.4 children.
Thus for the sample we consider, men in New France were producing more surviving
children than their relatively higher status counterparts who were leaving wills in England in the
seventeenth century. The average married person in the sample from England which just covers
small towns and the countryside left only 3.29 children at time of death. If we were to include an
allowance for the smaller numbers of surviving children in London average numbers of survivors
for will makers in England might be as low as 3.1. The differences are even greater then these
numbers would suggest since in the English data we have included as survivors children who
were themselves dead at the time of the testator’s death but who had left grandchildren
mentioned in the will.
In contrast to England, New France’s elite appears to have produced relatively small
families (Table 9). Considering surviving progeny from all marriages, the elite left just 3.3
19
children. At the other end of the spectrum, laborers were survived by 4.04 children. Farmers
were succeeded by five of their children and 4.5 of craftsmen’s children survived their fathers.
The relationship between wealth or social standing and fecundity does not appear clear cut,
however, as those in the merchant/professional category produced 4.9 survivors. Of course part
of the variation in survivorship may reflect the urban location of some families, as found in
England. To examine this, we replicate the regressions shown for England (Table 5), adding
decade dummy variables (the decade the husband was married) to account for the fact that
marriage market and social conditions may have changed over the 50 year period.
Table 10 illustrates that the number of surviving offspring was significantly lower among
men that were married in an urban setting, as commonly found. The numbers of survivors also
trended down over time.25 Controlling for urban marriage and the decade of marriage, the
surviving number of children born to the elite was significantly smaller than the number born to
laborers (the omitted category; see column 1), while merchants/professionals left more children
than laborers. The only other statistically distinguishable group was the husbandman category,
which had fewer surviving children than laborers. In New France (as noted), most individuals in
this category were soldiers, who may have been away from home more often than most married
men. Adding a further control for literacy (column 2) shows that the conditional relationship
between literacy and survivors was negative, although imprecisely measured.26 This also
contrasts with the positive relationship found among Englishmen (see Table 5).
Given the marked difference in behavior between the English and the New French, it is
worth distinguishing between native born and immigrants in the New French sample. Clearly
this is a blunt division given that assimilation may occur over an immigrant’s time in the
country, but we do not know how long immigrants were in the country prior to marriage.
20
Because we are counting survival of all of the children they fathered over their life time, and they
immigrated before marrying in New France, they clearly had many years to assimilate.
Differences still might arise, of course, if their access to resources in New France differed from
natives (controlling for occupation group), their marriages were delayed, or their preferences
with respect to family formation veered from the native born population. As noted, Weir (1995)
and Hadeishi (2003) found a positive relationship between wealth and fertility in eighteenth
century France—the source of New France’s immigrant population. We regress the surviving
number of children on social group, marriage decade dummy variables and the incidence of an
urban marriage for immigrants and native born individuals separately. Table 11 reports the
results for this series of negative binomial regressions. Examining columns 1 and 2 indicates
that the negative relationship between the elite and child survival was statistically significant
among both native born and immigrants. The magnitude of the effect was larger, however,
among the native born.
Because some of the observed relationship may reflect variation in longevity or women’s
age at marriage across social groups, controls for the age of marriage and life span of the
husband and wife are added in columns 3 and 4. While we cannot control for age of marriage
within the English sample, the French evidence suggests that the elite married young women,
which contributed to their larger family sizes. Recall that in New France the behavior of the elite
appears to have been different—wives of the elite were typically a bit older than most women
when they married (Table 8). Adding these controls to the regression illustrates that some (but
not all) of the smaller family size effect among the elite is explained by the shorter life span and
relatively old marriage age of these wives. Among the foreign born, surviving family size was
not statistically distinguishable from laborers once age and longevity are taken into account
21
(although the sign is still negative, the coefficient is smaller). The coefficient is also smaller
among the native born, but the relationship is still negative and precisely estimated. Either elite
immigrants (relative to other immigrants) were more like their counterparts in their birth country,
or they arrived when they were somewhat older and ended up with older wives. Because elites
in New France had both shorter lives and married (on average) older women, both factors
contributed to, but do not entirely explain, their smaller surviving family size.
To illustrate the variation in surviving family size across social groups, Figure 5 shows the
number of surviving children from all marriages, by social group, for immigrants and native
born, controlling for urban marriage (similar to Figure 3 for England).27 The clear gradation by
social group, so evident in the English data, is not apparent. In fact, in stark contrast to the
English sample, the elite had the smallest surviving family sizes and otherwise, there is little
pattern in the observed relationship between numbers of surviving children and occupational
group.
Hence in New France it appears that the selection of surviving offspring is very different
than in England, with much less variation in surviving family size across social strata and
individuals with lower literacy and those in lower social strata producing relatively more
surviving offspring.
IV. Conclusions
Wealthy or high status married men in England were surrounded by more children at their
death beds than their lower status compatriots. The relationship was evident if we classify men
by occupation, but is even stronger when we instead classify men by wealth bequeathed since
occupations were relatively loosely tied to economic resources. The relationship between
22
surviving family size and socioeconomic status was more muted in New France. To a first
approximation there seems little connection between place in the social hierarchy and
reproductive success.28 In early seventeenth century England the Malthusian mechanism for
bringing population into line with resources was in place, but there is no sign of this regulator in
the New World. The verdict on this vital assumption of the Malthusian model is thus rather
mixed. What could help to explain these findings?
The first possible resolution of these apparently contradictory results is that in the fluid
circumstances of a newly settled colony formal occupational titles may have had even less value
than in England in determining true economic status. New France was established with a land
tenure system that had feudal undertones, not unlike that in pre-revolutionary France. The King
of France appointed individuals, called seigneurs, to preside over large tracts of land
(seigneuries). The seigneurs granted plots to settlers (typically called habitants), in return for a
rent and some dues. These rents seem at least initially, when land was abundant relative to labor,
to have been low. They also seem to have been below market rates since habitants could sell the
land or pass it on to an heir in return for a fee to the seigneur.29 Hence the economic gap
between the seigneurs and the habitants may on average have been small, and economic gaps
within the groups much more important. Alan Greer, in his detailed study of rural New France,
concludes that
“unlike rural France in the eighteenth century…, with its fragmented peasantry composed of rich ‘laboureurs,’ landless proletarians, and an array of ‘haricotiers,’ ‘bordiers,’ and other intermediate groups scrambling to get by on a combination of revenues from handicrafts and the produce of their own small plots, the Lower Richelieu was inhabited by a largely homogeneous class of cultivators living in self-sufficient households, each possessing enough land to live on but not enough to dominate others.” (Greer, 1985: 21)
Most reports of the New France upper class, on the other hand, characterize them as not
that well off, compared to the French (or British) upper class. As Dechêne describes:
23
“the brakes on the colonial economy and easy access to land tended to reduce material
differences.” (Dechêne, 1992: 229) Dechêne describes the nobility as having both more
furniture and more luxurious furnishings in their homes than the typical habitant, but at least
some of them struggling with relatively low incomes and significant debt.30 In contrast, some of
the merchants were very wealthy. On average, those with post-mortem inventories left 20,000 to
35,000 livres (on the order of ten times the habitant’s lot), with five leaving more than 150,000
livres.31 In this case economic differences may also have influenced reproductive success in
New France, but the occupational labels we have are a very poor guide to economic
circumstances.
The second possible reconciliation of these results is that living standards in New France
were much higher than those in England. Suppose the positive relationship between income and
reproductive success only exists at income levels such as those in Figure 1 where the population
is just replacing itself, and that at higher incomes, where population is growing, there is no
relationship between income and reproductive success. Such a relationship between income and
reproductive success would be perfectly consistent with the Malthusian interpretation of the pre-
industrial world. For in equilibrium most societies have to find themselves close to the region
where births equal deaths and population is stable. New France was not near the Malthusian
equilibrium because of the recent arrival of Europeans with a new agricultural technology who
were still in the process of populating the land. Table 12 shows the number of survivors left by
married men in the two societies. For each social group in New France men left more survivors,
and the difference is particularly marked for the lowest group the “laborers.” So a second thing
potentially obscuring the relationship between reproductive success and occupation in New
24
France may be that even the poorest groups in New France had incomes well above the level
where reproductive success was sensitive to income differences.
Whatever the reason for the very different results in England versus New France, this
study suggests that we can in some circumstances identify the correlation between reproductive
success and economic circumstances which underlies the Malthusian model of the pre-industrial
economy. However, the experience of New France suggests that the Malthusian model may be
applicable only to long settled societies such as England, and may have less explanatory power
for the substantial periods where pre-industrial communities were away from the Malthusian
equilibrium.
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30
Table 1: The Major Occupations of Will Makers (All Wills)
Occupation
All
London
Towns
Countryside
Yeoman, Farmer 636 7 32 597 Husbandman 288 0 8 280 “Gentleman”, etc. 102 32 28 42 Laborer 79 0 2 77 Tailor 48 4 11 33 Weaver 40 0 3 37 Carpenter, joiner 39 0 8 31 Shoemaker 32 3 13 16 Clothier 29 0 8 21 Merchant 28 4 16 8 Blacksmith 25 2 2 21 Mariner 19 3 11 5 Sailor 17 2 2 13 Clerk, cleric 16 1 5 10 Tanner 15 0 11 4 Cook, Baker 14 2 8 4 Clothworker 14 4 6 4 Shepherd 14 0 0 14 Merchant Tailor 13 12 0 1 Haberdasher 13 9 3 1 Miller 13 0 1 12 Grocer 12 5 3 4 Attorney 11 10 1 0 Butcher 11 0 3 8 Glover 10 0 1 9 Innholder 10 1 2 7
All 2,032 174 287 1,570
31
Table 2: Surviving Children per Male Testator, England, 1585-1636
Residence
Number of wills with
information on children
Children per
testator
Sons per testator
Daughters per
testator
London 174 1.95 0.83 1.07 Town 287 2.24 1.12 1.10 Rural 1,569 2.86 1.48 1.38 ALL 2,030 2.69 1.37 1.31
Note: The numbers of sons and daughters in each row do not always add up to the total numbers
of children since in a few cases the number of children is known, but not the number of sons or
daughters.
Sources: Allen (1989), Atkinson (1993), Emmison (1989, 1990, 1991, 1995, 1998, 2000), Evans
(1987), Lang and McGregor (1993), Lea (1904).
32
Table 3: Occupation groupings (partial listing)
Category
Occupations
Elite (NF)
Gentry or noble or bourgeois
Gentry
Titled individuals (baron, countess, marquis, knight)
Noble Parent or individual inherited or awarded title from King of France
Bourgeois Parent had one of a number of high ranking government posts
Gentry (E) Titled individuals, gentleman
Merchants / professionals Merchants; notary, attorney, physician, surgeon, architect, seigneur (NF), military officer, King’s agents, ship’s captain, priest, school master, London citizens (E)
Farmer Farmer, yeoman
Trader Baker, butcher, brewer, miller, barber, chandler, innkeeper…
Craftsman All crafts
Husbandman Husbandman, fisherman, gardener, sergeant, ship gunner, soldiers.
Laborer Laborer, servant, sailor, voyageur (NF) Notes: NF = New France, E = England.
33
Table 4: Characteristics of the Social Categories, England
Social Group
Numbers of wills
giving asset information
Fraction
of testators literate
Average value of assets
bequeathed (£)
Minimum estimated value of assets
bequeathed (£)
Maximum
value of assets
bequeathed (£)
Gentry 53 0.89 702 20 5,896 Merchants/Professionals 83 0.88 277 0 1,914 Farmers 590 0.50 358 0 2,548 Traders 82 0.57 101 0 471 Craftsmen 241 0.40 97 0 495 Husbandmen 300 0.25 83 0 580 Laborers 86 0.14 52 0 263 Unknown 313 0.49 156 0 941
34
Table 5: Literacy, Status and Survivors, Male Testators, England
Independent Variable
Surviving Children
per married testator
Surviving
Children per married testator
Surviving
Children – all testators
Surviving
Children – all testators
Literate 0.100* (0.048)
- 0.080 (0.055)
-
Gentry 0.324*
(0.132) 0.362** (0.130)
0.244 (0.148)
0.274 (0.146)
Merchants / Prof 0.329**
(0.117) 0.368** (0.115)
0.372** (0.132)
0.404** (0.131)
Farmers 0.389**
(0.096) 0.399** (0.096)
0.441** (0.109)
0.449** (0.109)
Unknown 0.252*
(0.102) 0.257* (0.102)
0.163 (0.115)
0.168 (0.115)
Traders 0.180
(0.126) 0.188
(0.126) 0.234
(0.144) 0.242
(0.144)
Craftsmen 0.244* (0.104)
0.246* (0.104)
0.296* (0.119)
0.298* (0.119)
Husbandmen 0.212*
(0.102)
0.209* (0.102)
0.253* (0.116)
0.252* (0.116)
London -0.186* (0.086)
-0.174* (0.086)
-0.373** (0.094)
-0.364** (0.094)
Town -0.229** (.060)
-0.224** (.060)
-0.213** (0.069)
-0.209** (0.069)
Farm occupier
0.097* (0.046)
0.100* (0.046)
0.134* (0.054)
0.135* (0.054)
Constant 0.801
(0.093) 0.841
(0.091) 0.672
(0.105) 0.703
(0.103) N 1,788 1,788 2,030 2,030 Pseudo R2 0.008 0.008 0.009 0.009 Note: The method of estimation is a negative binomial (standard errors are in parentheses). The title of each column refers to the dependent variable in each regression. In columns 3 the constant refers to the average number of survivors for an illiterate person in the omitted occupational group (laborers, sailors, and servants) in a rural parish. * = statistically significant at the 5% level, ** = statistically significant at the 1% level.
35
Table 6: Literacy, Assets and Survivors, Male Testators, England
Independent Variable
Children,
all married
Children,
all married
Children, all
testators
Widower
- 0.258** (0.044)
-
Literate -0.005 (0.047)
0.006 (0.047)
-0.063 (0.054)
Bequests, £10-24
0.114 (0.088)
0.094 (0.087)
0.068 (0.097)
Bequests, £25-49 0.346**
(0.078) 0.335** (0.077)
0.370** (0.087)
Bequests, £50-99 0.378**
(0.075) 0.381** (0.074)
0.422** (.084)
Bequests, £100-199 0.364**
(0.071) 0.357** (0.070)
0.441** (.080)
Bequests, £200-499 0.512**
(0.065) 0.500** (0.065)
0.597** (.073)
Bequests, £500- 0.638**
(0.075) 0.637** (0.074)
0.735** (0.085)
No specific goods or monies bequeathed.
-0.536** (0.148)
-0.506** (0.147)
-0.495** (0.159)
Town -0.219** (0.062)
-0.202** (0.061)
-0.221** (0.069)
Farm Occupation
0.059 (0.043)
0.069 (0.043)
0.090 (0.050)
Constant 0.778 (0.059)
0.720 (0.059)
0.641 (0.065)
N 1,597 1,597 1,782 Pseudo R2 0.027 0.032 0.024 Note: The method of estimation is a negative binomial (standard errors are in parentheses). The title of each column refers to the dependent variable for that regression. In each case the constant refers to the average number of survivors for an illiterate testator in a rural parish with fewer than £10 in bequests. * = statistically significant at the 5% level, ** = statistically significant at the 1% level.
36
Table 7: Assets as a Function of Age, Married Male Testators, England
Independent
Variable
Assets per
married testator (£)
Standard error of estimate
Assets per married testator (£) (at least one surviving child)
Standard error of estimate
Widower
-35.9
18.8
-48.4*
20.0
Literate 130.9**
19.3 143.5**
21.4
Gentry 611.2**
55.9 624.5**
61.1
Merchants / Prof 188.4**
47.2 192.7**
60.0
Farmers 284.8**
34.4 303.3**
38.4
Unknown 95.4**
36.6 108.3**
40.8
Traders 48.6
37.6 46.8 54.2
Craftsmen 48.4
37.6 50.3
42.2
Husbandmen 22.7
36.4 19.8
40.6
Town -43.8* 24.3 -43.8*
24.3
Farm occupier 58.0**
17.9 70.5**
19.5
No specific bequests
-130.1**
40.7 -115.5*
58.8
Constant 8.4
33.4 1.1
37.4
N
1,599 1,368
Pseudo R2
0.241 0.248
Note: The method of estimation is a negative binomial. The constant refers to the average
number of survivors for an illiterate person in the omitted occupational group (laborers, sailors,
and servants) in a rural parish. * = statistically significant at the 5% level, ** = statistically
significant at the 1% level. Average Assets £232, married with at least one child.
37
Table 8: Husband’s characteristics: New France
N
Fraction Signed
Born in N
Marriage Age
Marriage Age Wife
Married in city
Life Span
Life Span Wife
Fraction Remarry
Elite 269 0.65 0.55 29.53 21.27 0.70 60.59 58.95 0.57
Merchant/Prof.
339 0.42 0.65 27.02 20.30 0.34 65.65 58.43 0.59
Farmer 414 0.15 0.46 28.21 18.00 0.36 64.14 61.16 0.42
Craft 251 0.35 0.44 28.05 19.32 0.53 62.17 57.24 0.57
Trader 63 0.22 0.19 29.86 19.77 0.52 63.15 59.13 0.52
Unknown 1329 0.14 0.82 26.42 20.38 0.15 60.76 60.42 0.48
Laborer 198 0.18 0.53 29.31 19.15 0.37 62.12 58.65 0.46
Husbandman
156
0.19
0.04
31.58
22.97
0.50
65.47
62.86
0.40
All 3019 0.24 0.62 27.67 20.07 0.32 62.26 59.88 0.50
38
Table 9: Average Number of Children by Social Group: New France Children Born Surviving Children
N First Marriage
All marriages
First marriage
All marriages
Elite 269 6.99 8.00 2.91 3.31
Merchant/Professional 339 8.46 10.06 4.17 4.87
Farmer 414 8.75 9.70 4.56 5.01
Trader 63 7.65 9.17 3.44 3.95
Craft 251 8.43 9.98 3.85 4.45
Unknown 1,329 7.69 8.83 3.93 4.40
Husbandman 156 6.85 7.58 3.06 3.50
Laborer 198 7.19 8.09 3.69 4.04
All
3,019
7.84
9.00
3.88
4.36
39
Table 10: Literacy, Status and Survivors: New France
(1)
(2)
Literate -0.025 (0.029) Elite -0.275** -0.268** (0.056) (0.056) Merchant/ prof 0.098* 0.103* (0.048) (0.049) Farmer 0.080 0.079 (0.051) (0.051) Unknown 0.053 0.052 (0.046) (0.046) Trader -0.084 -0.085 (0.096) (0.096) Craft 0.048 0.050 (0.054) (0.054) Husbandman -0.180** -0.181** (0.069) (0.069) Urban marriage -0.129** -0.125** (0.027) (0.027) Constant 1.677** 1.675** (0.075) (0.075) N 3,019 3,019 R squared
0.0137 0.0137
Notes: Dependent variable is the number of surviving children (all marriages). The method of estimation is a negative binomial. Robust standard errors are in parentheses. Decade-of-marriage dummy variables are not reported. The omitted trade is laborer. * = significant at the 5 percent level; ** = significant at the 1 percent level.
40
Table 11: Determinants of Surviving Children for Immigrants and Native Born in New France (1) (2) (3) (4)
Born in NF: No Yes No Yes Elite -0.202* -0.347** -0.103 -0.255** (0.085) (0.074) (0.076) (0.068) Merchant / prof 0.101 0.070 0.117 0.053 (0.075) (0.064) (0.070) (0.058) Unknown -0.034 0.027 -0.003 0.051 (0.079) (0.060) (0.073) (0.055) Husbandmen -0.106 -0.433 -0.040 -0.261 (0.087) (0.264) (0.083) (0.243) Farmer 0.096 0.062 0.067 0.009 (0.073) (0.070) (0.068) (0.066) Craft 0.140* -0.044 0.077 -0.088 (0.076) (0.080) (0.072) (0.079) Trader -0.014 -0.170 0.024 -0.265* (0.119) (0.144) (0.110) (0.123) Urban marriage -0.141** -0.107** -0.111** -0.052 (0.041) (0.037) (0.038) (0.033) Marriage age (h) -0.013** -0.013** (0.003) (0.004) Marriage age (w) -0.041** -0.035** (0.005) (0.004) Life span (h) 0.102** 0.099** (0.010) (0.006) Life span (w) 0.011 0.004 (0.006) (0.004) Life span squared (h) -0.001** -0.001** (0.000) (0.000) Life span squared (w) 0.000 0.000 (0.000) (0.000) Constant 1.669 1.652 -0.992** -0.498* (0.095) (0.132) (0.362) (0.248) N 1142 1877 1028 1665 R squared
0.017
0.015
0.067
0.068
Notes: Dependent variable is the number of surviving children (all marriages). The method of estimation is a negative binomial. Robust standard errors are in parentheses. Decade-of-marriage dummy variables are not reported. The omitted trade is laborer. * = significant at the 5 percent level; ** = significant at the 1 percent level. h = husband, w = wife.
41
Table 12: Average Number of Surviving Children by Social Group: Married
Males, New France vs England
New France
England
Elite 3.31 3.00
Merchant/Professional 4.87 2.95
Farmer 5.01 3.53
Trader 3.95 2.62
Craft 4.45 2.75
Husbandman 3.50 2.89
Laborer 4.04 2.42
All 4.36 2.94
42
Figure 1: The Basic Assumption of All Malthusian Models on Income and
Fertility
43
Figure 2: Time in Days between Will Composition and Probate, English
Sample, 1585 -1636
Note: Each bar in the figure shows the percentage of wills probated in the 30 day interval
centered on the number given below the bar.
44
Figure 3: Surviving Children by Occupation of Testator
Note: The figure shows the number of surviving children by occupation, controlling for urban
versus rural residency. The values are derived from the coefficients of the regression shown in
Table 5, columns 2 and 4. The coefficients must be transformed (due to the functional form of
the negative binomial estimation): ( )ieX iββ += 0 where represents the number of surviving
children depicted for the i
X
th trade, 0β is the estimated constant and iβ is the estimated coefficient
on the ith trade dummy variable.
45
Figure 4: Surviving Children by estimated assets of Testator
Note: the values shown are derived from Table 6, columns 1 and 3, illustrating the estimated
number of surviving children by asset group, controlling for urban location and literacy. See
notes to Figure 3 for the form of the transformation of the coefficients.
46
Figure 5: Number of Surviving Children (all marriages): New France
0
1
2
3
4
5
6
7
Laborer Unknown Craftsman Farmer Merchant Elite
Surv
ivin
g C
hild
ren
Foreign Native
Note: The values are derived from the coefficients from the negative binomial regression
coefficients in Table 11 (columns 1 and 2). To convert the coefficients to numbers of children,
the coefficients are transformed as described in the notes to Figure 3.
47
1 See, for example, Weir (1984).
2 See Wrigley and Schofield (1989), Weir (1984), Tsuyo and Hamano (2001).
3 We can see this by comparing the life expectancies given in Wrigley et al. (1997), p. 614, to
real wages in this era from Clark (2005).
4 The proportion of the population dying in their first 15 years of life was 29 percent for the
general population and 34 percent for the aristocracy in the first half of the seventeenth century.
In the years 1750-99, the proportion dying was roughly the same for the general population (30
percent), while it had fallen markedly for the aristocracy (21 percent). See Hollingsworth (1965:
54-7) and Wrigley et al (1997).
5 See Landers (1993): 186-8.
6 See Derouet (1980) and Charbonneau (1970) cited in Weir (1995), p. 17.
7 See Wells (1992): 92. Based on Kantrow (1980).
8 Calculated from Smith (1977), p. 871 (Table 3). For the gentry calculation, see Gemery (2000):
163-4.
9 Ferrie (2004) finds a negative relationship between personal wealth and mortality for mid
nineteenth century America.
10 It would seem that the work of the Cambridge Group on family reconstitution from parish
registers would provide a more representative measure of reproductive success. But before 1740
these measures are not linked to the literacy of the testator. And the occupations and the assets
of the bequeathed are again impossible to discern on a systematic basis. Thus the Cambridge
group can only look at reproductive success through the average behavior of villages of different
types.
48
11 Widowed was inferred from specific statements about former wife, or absence of wife in will
when children were left bequests.
12 If a child was dead at the time of the will, but had left grandchildren then this child was
counted.
13 (measured by whether the will was signed, the testator bequeathed books other than a bible, or
the testator had an occupation requiring literacy such as an attorney or cleric).
14 Gottfried (1978), pp. 190, 198.
15 A negative binomial regression form is employed because the dependent variable (number of
surviving children) is a nonnegative count variable (taking on values 0, 1, 2, 3 et cetera).
16 Charbonneau et al (1973: 43). This counts the non-natives only.
17 Choquette (1997: chapter 4).
18 The data were collected by the Programme de recherche en démographie historique (PRDH).
We thank Bertrand Desjardins for making them available to us. Researchers interested in
acquiring these data are directed to the PRDH web site: http://www.genealogie.umontreal.ca/
19 A number of studies document the creation of the data set. For example, Légaré (1988),
Légaré and Desjardins (1980), Légaré, LaRose and Roy (1975), and Nault and Desjardins (1988,
1989). See Hamilton and Siow (2002) for a more complete list.
20 The population of the colony was about 3,000 in 1666; 9,700 in 1681; 10,300 in 1688 and just
over 20,000 in 1716. Sources: Census of Canada, 1871, Vol.4; Dechêne (1992: 315); Harris
(1987); Dickinson and Young (1993: 67-70). Nault, Desjardins, and Légaré (1990: 274) report
that (principally male) immigration "became more and more marginal relative to the native white
population [after 1673]. Out migration, although significant at some moments, was negligible in
total." The high proportion of male immigrants led to a gender imbalance until the King of
49
France actively addressed it in the 1660s (by sending hundreds of single women to the colony).
(Landry, 1992)
21 Tax records (or comparable poll) from New France have not survived. Short of undertaking a
major archival project reading individual wills or estate inventories, there is no way to
systematically glean information on individuals’ wealth or income.
22 For example, the King of France offered some nobility large land grants, called seigneuries.
Not all seigneurs were member of the nobility (Harris, 1966). The aristocracy also qualified for
pensions and some received fur-trade licences. In addition, a substantial portion of those that did
not inherit title served as officers in the military and were given (lucrative) officers'
commissions. For more information on the nobility, see Gadoury (1991), Dechêne (1992), or
Greer (1997: 51).
23 The nobles make up 3 percent of the sample and the bourgeois add another 4 percent. These
small groups had the highest literacy (signature) rates: 65 and 70 percent respectively, compared
to 24 percent overall.
24 Wives are not restricted to first marriages.
25 The decade-of-marriage results are not reported (for space considerations), but are available
upon request.
26 The imprecision of the estimate stems from the colinearity between the occupation codes and
literacy. Dropping the occupation variables yields a statistically significant negative coefficient
on literacy. The raw means help to illustrate the magnitude of the difference: the number of
surviving children for was 4.1 children literate fathers and 4.4 children for illiterate fathers.
Results available on request.
50
27 Husbandman/military and traders have been omitted because of small sample size. The native
born sample for these two categories is 7 and 12 respectively.
28 The rather perverse outcome among the elite excepted. 29 There is, however, debate on how significant the burdens on tenants were. For summaries see
Francis, Jones and Smith (1992: 80-83) and Norrie, Owram and Emery (2002: 39-42).
30 It is difficult to determine the average circumstances of the nobles from Dechêne’s account.
She states that 17 of the nobles with post-mortem inventories had gross wealth of between 3,000
and 8,000 livres (not net of debts). This is not the full sample of nobles, but indicates that some
nobles were not well off. Dechêne (1992: 218).
31 Dechêne (1992: 220).