It is commonly argued that because there are roughly the same number of men as women in the world, then monogamy is the natural state of life. Polygamy will result in some men getting all the women and other men being left celibate.
Most of us are well aware that men tend to kill themselves off more rapidly than women do through hard work, war, and risky recreational activities, and this generally results in a slightly higher number of women than men of marriageable age. This slight surplus means that polygamy is necessary in order for all women to marry.
However, there is a much bigger issue at play also. Historically, older men tended to marry younger women, because men would wait until they had a stable income to support a wife before marriage, while women would marry as soon as they were ready in the eyes of the culture. In polygamous societies, the average age gap would be even higher, as even if a man married his first wife at the same age as himself, he may be several years older before he is in a position to marry a second, but may marry her from the same "pool" of marriageable women.
In a stable population, such as most Western countries, that doesn't change anything. But in a growing population, this makes an enormous difference to the ratio of men to women.
We can explore this through a very simple "model" of marriage. Let us assume that every person in a country marries at the same age. For example, every man marries at 25, and every woman also marries at 25. Everybody under the age of 25 is single, and everybody over 25 is already married. If a man is polygamous, he marries both women simultaneously at 25. Obviously this is not realistic, but it's very easy to do maths on, and is easy to understand. In this model, the number of 25-year-old women per 25-year-old man is the average number of wives that a man can have in that society.
Alternatively, we can assume that every man marries at 30, and every woman at 25. With a 5-year average age gap, the number of 25-year-old-women per 30-year-old-man is the average number of wives a man can have.
Although it is simplistic, the results will indicate the number of women per men with that average age gap, even in a realistic situation with people marrying at a range of ages.
As a snapshot view, here are the number of women per men for the USA and Uganda, in 2009, assuming that every man marries at 30, but with an average age gap of 0 to 15 years between men and women. In other words, it is assumed that every woman marries a 30-year-old man, but marries at anywhere from 30 years (age gap 0) to 15 years old (age gap 15). The USA had a stable population in 2009 with similar numbers of people in each age bracket up to around 50, while Uganda had a growing population with more children than adults.
Number of women per man with 0-15 year age gaps:
Gap- - - - - - US - - - - - - UG
0 - - - 0.9816544 - - - 1.021994
1 - - - 1.0049443 - - - 1.071828
2 - - - 1.0256994 - - - 1.126634
3 - - - 1.0227835 - - - 1.187786
4 - - - 1.0016499 - - - 1.251112
5 - - - 0.9987847 - - - 1.316923
6 - - - 1.0053122 - - - 1.389926
7 - - - 0.9987586 - - - 1.469224
8 - - - 0.9950808 - - - 1.548478
9 - - - 1.0170579 - - - 1.629450
10 - - - 1.0340511 - - - 1.715154
11 - - - 1.0873899 - - - 1.795374
12 - - - 1.0663664 - - - 1.870610
13 - - - 1.0370312 - - - 1.946620
14 - - - 1.0243672 - - - 2.032000
15 - - - 1.0017633 - - - 2.119559
For the USA, in 2009, there were approximately equal numbers of 30-year-old men and women (interestingly, there were actually slightly fewer women than men, so not following the general men-die-faster principle). And it wouldn't have made any difference if men on average married younger women, there would have been approximately 1 woman per man regardless of age gap.
In Uganda, there were approximately equal numbers of 30-year-old men and women. However due to the growing population, with only a 4-year average age gap, there were 25% more women than men. In other words, 1 in 4 men could have two wives. With a 14-year average age gap, there were twice as many women as men - every man could be a polygamist.
Throughout human history, most populations would be growing even more rapidly than Uganda's today. The USA's stable population is highly artificial and driven by modern behaviour particularly hormonal contraceptives and abortion, and does not in any way reflect God's plan for people to "be fruitful and multiply". Even Uganda, by 2009, had lower birth rates than historically, due to the encroachment of modern Western behaviour and values. Most Biblical societies, and even historical Western societies, would have had even higher birth rates and therefore age would have an even stronger influence on the potential (and need) for polygamy.
To see the overall age structure of any country's population, check out https://www.populationpyramid.net.
That site gives an overview of the population structure, but does not directly calculate the ratio of women to men at different pairs of ages. These statistics are not readily available, but I've written a script to generate them. I intend one day to make an interactive webpage to let people explore these stats, but I'm taking too long to actually do that because I'm busy with other things. So I thought that rather than keep sitting on it I had better share some basic stats here, and the code I used to generate them, to let others take it further if you like.
Here is code for the statistical program "R", that will pull data from the US Census Bureau for any country in any year they have records for (try after around 1980-1990 if a query fails, some countries only have recent data), and calculate the number of females per male for any pair of male/female ages. You'll have to sign up for a US Census Bureau key to use it, but that's free (see code for instructions).
Most of us are well aware that men tend to kill themselves off more rapidly than women do through hard work, war, and risky recreational activities, and this generally results in a slightly higher number of women than men of marriageable age. This slight surplus means that polygamy is necessary in order for all women to marry.
However, there is a much bigger issue at play also. Historically, older men tended to marry younger women, because men would wait until they had a stable income to support a wife before marriage, while women would marry as soon as they were ready in the eyes of the culture. In polygamous societies, the average age gap would be even higher, as even if a man married his first wife at the same age as himself, he may be several years older before he is in a position to marry a second, but may marry her from the same "pool" of marriageable women.
In a stable population, such as most Western countries, that doesn't change anything. But in a growing population, this makes an enormous difference to the ratio of men to women.
We can explore this through a very simple "model" of marriage. Let us assume that every person in a country marries at the same age. For example, every man marries at 25, and every woman also marries at 25. Everybody under the age of 25 is single, and everybody over 25 is already married. If a man is polygamous, he marries both women simultaneously at 25. Obviously this is not realistic, but it's very easy to do maths on, and is easy to understand. In this model, the number of 25-year-old women per 25-year-old man is the average number of wives that a man can have in that society.
Alternatively, we can assume that every man marries at 30, and every woman at 25. With a 5-year average age gap, the number of 25-year-old-women per 30-year-old-man is the average number of wives a man can have.
Although it is simplistic, the results will indicate the number of women per men with that average age gap, even in a realistic situation with people marrying at a range of ages.
As a snapshot view, here are the number of women per men for the USA and Uganda, in 2009, assuming that every man marries at 30, but with an average age gap of 0 to 15 years between men and women. In other words, it is assumed that every woman marries a 30-year-old man, but marries at anywhere from 30 years (age gap 0) to 15 years old (age gap 15). The USA had a stable population in 2009 with similar numbers of people in each age bracket up to around 50, while Uganda had a growing population with more children than adults.
Number of women per man with 0-15 year age gaps:
Gap- - - - - - US - - - - - - UG
0 - - - 0.9816544 - - - 1.021994
1 - - - 1.0049443 - - - 1.071828
2 - - - 1.0256994 - - - 1.126634
3 - - - 1.0227835 - - - 1.187786
4 - - - 1.0016499 - - - 1.251112
5 - - - 0.9987847 - - - 1.316923
6 - - - 1.0053122 - - - 1.389926
7 - - - 0.9987586 - - - 1.469224
8 - - - 0.9950808 - - - 1.548478
9 - - - 1.0170579 - - - 1.629450
10 - - - 1.0340511 - - - 1.715154
11 - - - 1.0873899 - - - 1.795374
12 - - - 1.0663664 - - - 1.870610
13 - - - 1.0370312 - - - 1.946620
14 - - - 1.0243672 - - - 2.032000
15 - - - 1.0017633 - - - 2.119559
For the USA, in 2009, there were approximately equal numbers of 30-year-old men and women (interestingly, there were actually slightly fewer women than men, so not following the general men-die-faster principle). And it wouldn't have made any difference if men on average married younger women, there would have been approximately 1 woman per man regardless of age gap.
In Uganda, there were approximately equal numbers of 30-year-old men and women. However due to the growing population, with only a 4-year average age gap, there were 25% more women than men. In other words, 1 in 4 men could have two wives. With a 14-year average age gap, there were twice as many women as men - every man could be a polygamist.
Throughout human history, most populations would be growing even more rapidly than Uganda's today. The USA's stable population is highly artificial and driven by modern behaviour particularly hormonal contraceptives and abortion, and does not in any way reflect God's plan for people to "be fruitful and multiply". Even Uganda, by 2009, had lower birth rates than historically, due to the encroachment of modern Western behaviour and values. Most Biblical societies, and even historical Western societies, would have had even higher birth rates and therefore age would have an even stronger influence on the potential (and need) for polygamy.
To see the overall age structure of any country's population, check out https://www.populationpyramid.net.
That site gives an overview of the population structure, but does not directly calculate the ratio of women to men at different pairs of ages. These statistics are not readily available, but I've written a script to generate them. I intend one day to make an interactive webpage to let people explore these stats, but I'm taking too long to actually do that because I'm busy with other things. So I thought that rather than keep sitting on it I had better share some basic stats here, and the code I used to generate them, to let others take it further if you like.
Here is code for the statistical program "R", that will pull data from the US Census Bureau for any country in any year they have records for (try after around 1980-1990 if a query fails, some countries only have recent data), and calculate the number of females per male for any pair of male/female ages. You'll have to sign up for a US Census Bureau key to use it, but that's free (see code for instructions).
Code:
# Data comes from the US Census Bureau through the idbr package
# To obtain data:
# 1) install.packages('idbr')
# 2) Register for an api key at https://api.census.gov/data/key_signup.html
# See http://personal.tcu.edu/kylewalker/articles/walker-2016-spatial-demography.html
# To look up countries using FIPS country codes, find codes here:
# https://en.wikipedia.org/wiki/List_of_FIPS_country_codes
library(idbr)
idb_api_key('insert_key_here')
# Functions to calculate number of females per male for any country, year, and age choices
# Require FIPS country code
# ONE SEX RATIO
# One country, one year, one pair of male & female ages.
# Function:
sexratio <- function(ctry,yr,agem,agef) {
# Obtain data
male <- idb1(ctry, yr, sex = 'male', variables = c("AGE", "NAME", "POP"))
female <- idb1(ctry, yr, sex = 'female', variables = c("AGE", "NAME", "POP"))
# Extract desired years
nom <- as.numeric(subset(male,AGE==agem,select=POP))
nof <- as.numeric(subset(female,AGE==agef,select=POP))
# Calculate number of females per male and return
nof / nom
}
# Example usage
sexratio('NZ',2009,26,16)
# BULK SEX RATIOS
# Multiple countries, one year, one male age, multiple female ages (as per above table of results)
# Functions:
sexratio_getdata <- function(ctry,yr){
# Obtain data
male <- idb1(ctry, yr, sex = 'male', variables = c("AGE", "NAME", "POP"))
female <- idb1(ctry, yr, sex = 'female', variables = c("AGE", "NAME", "POP"))
list(male,female)
}
sexratio_process <- function(male,female,agem,agef){
# Extract desired years
nom <- as.numeric(subset(male,AGE==agem,select=POP))
nof <- as.numeric(subset(female,AGE==agef,select=POP))
# Calculate number of females per male and return
nof / nom
}
# Example usage:
maleage <- 30
femaleage <- c(30:15)
countries <- c("US","UG")
year <- 2009
numfemales <- matrix(data=NA,nrow=length(femaleage),ncol=length(countries),dimnames=list(maleage-femaleage,countries))
for(j in 1:length(countries)){
data <- sexratio_getdata(countries[j],year)
for(i in 1:length(femaleage)){
numfemales[i,j] <- sexratio_process(data[[1]],data[[2]],maleage,femaleage[i])
}
}
numfemales
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