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2016 ; 27
(4
): 445-470
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The Reproductive Ecology of Industrial Societies, Part II : The Association
between Wealth and Fertility
#MMPMID27670437
Stulp G
; Sear R
; Schaffnit SB
; Mills MC
; Barrett L
Hum Nat
2016[Dec]; 27
(4
): 445-470
PMID27670437
show ga
Studies of the association between wealth and fertility in industrial populations
have a rich history in the evolutionary literature, and they have been used to
argue both for and against a behavioral ecological approach to explaining human
variability. We consider that there are strong arguments in favor of measuring
fertility (and proxies thereof) in industrial populations, not least because of
the wide availability of large-scale secondary databases. Such data sources bring
challenges as well as advantages, however. The purpose of this article is to
illustrate these by examining the association between wealth and reproductive
success in the United States, using the National Longitudinal Study of Youth
1979. We conduct a broad-based exploratory analysis of the relationship between
wealth and fertility, employing both cross-sectional and longitudinal approaches,
and multiple measures of both wealth (income and net worth) and fertility
(lifetime reproductive success and transitions to first, second and third
births). We highlight the kinds of decisions that have to be made regarding
sample selection, along with the selection and construction of explanatory
variables and control measures. Based on our analyses, we find a positive effect
of both income and net worth on fertility for men, which is more pronounced for
white men and for transitions to first and second births. Income tends to have a
negative effect on fertility for women, while net worth is more likely to
positively predict fertility. Different reproductive strategies among different
groups within the same population highlight the complexity of the reproductive
ecology of industrial societies. These results differ in a number of respects
from other analyses using the same database. We suggest this reflects the
impossibility of producing a definitive analysis, rather than a failure to
identify the "correct" analytical strategy. Finally, we discuss how these
findings inform us about (mal)adaptive decision-making.
|*Birth Rate/ethnology
[MESH]
|Adult
[MESH]
|Cross-Sectional Studies
[MESH]
|Developed Countries/*statistics & numerical data
[MESH]
|Female
[MESH]
|Humans
[MESH]
|Income/*statistics & numerical data
[MESH]
|Longitudinal Studies
[MESH]
|Male
[MESH]
|Reproductive Behavior/ethnology/*statistics & numerical data
[MESH]