# Births and week-ends, in France

This week, I have seen on the internet (sorry, I cannot find proper references) the graph produced here on the right: which birthday is most likely ? The fact that I have no further information is important, since I do not know in which country such a graph was obtained. At least, I know it should not be France…

In France, I have already mentioned that there is a strong week-end effect: nowadays, there is 25% less deliveries during week-ends than during the week. Calot (1981) observed already that there were less deliveries on Sundays. This has been confirmed more recently, e.g. in http://www.lepoint.fr/ or http://www.prepabl.fr/, with a significant difference between week days, and week-ends. Here  is the number of birth per day, over 40 years, with in blue the average trend during the week, and in red, during week-ends,

```naissance=read.table(
"http://freakonometrics.free.fr/naissanceFR2.txt")
attach(naissance)
date=as.Date(date)
plot(date, nbre,cex=.5)
t2=as.POSIXlt(date)
jour=t2\$wday
X=naissance\$date
Y=naissance\$nbre
J=jour
df=data.frame(X,Y,J)
library(splines)
regs=lm(Y~bs(X,df=20),data=df[jour%in%c(0,6),])
Yp=predict(regs,newdata=df)
lines(X,Yp,col="red",lwd=3)
regs=lm(Y~bs(X,df=20),data=df[jour%in%1:5,])
Yp=predict(regs,newdata=df)
lines(X,Yp,col="blue",lwd=3)```

If we look at the evolution of the ratio week-ends over weeks days, we have the following graph

```t2=as.POSIXlt(date)
jour=t2\$wday
jour=jour[1:(1982*7)]
nbre2=jour
for(i in 1:1982){
taux=sum(nbre[6:7+7*(i-1)])/
sum(nbre[1:5+7*(i-1)])/2*5
nbre2[1:5+7*(i-1)]=nbre[1:5+7*(i-1)]*taux
nbre2[6:7+7*(i-1)]=nbre[6:7+7*(i-1)]
nbre2[1:7+7*(i-1)]=
mean(nbre[1:7+7*(i-1)])/mean(nbre2[1:7+7*(i-1)])*
nbre2[1:7+7*(i-1)]
}
nbretaux=jour
for(i in 1:1982){
taux=sum(nbre[6:7+7*(i-1)])/
sum(nbre[1:5+7*(i-1)])/2*5
nbretaux[1:7+7*(i-1)]=taux
}
plot(date[1:length(nbre2)],nbretaux)
X= date[1:length(nbre2)]
Y=nbretaux
library(splines)
reg=lm(Y~bs(X,df=20))
Yp=predict(reg)
lines(X,Yp,col="red",lwd=3)```

In the beginning of the 70’s, during week-ends, there were 5% less deliveries, but 25% less around 2000. It is then possible to produce the same kind of graphs as the one above, per year of birth. And here, we clearly observe the importance of the week end effect (maybe also because of color choice)

```naissance=read.csv(
"http://freakonometrics.free.fr/naissanceFR.csv",
sep=";")
M=as.matrix(naissance[,3:ncol(naissance)])
BIRTH=as.vector(t(M))
YEAR=rep(1968:2005,each=12*31)
MONTH=rep(rep(1:12,each=31),38)
DAY=rep(1:31,12*38)
X=NA
for(y in 1968:2005){
sbase=base[YEAR==y,]
X=c(X,sbase\$BIRTH/sum(sbase\$BIRTH,
na.rm=TRUE))
}
base=data.frame(YEAR,MONTH,DAY,
BIRTH,BIRTHDAYPROB=X[-1])

m1=min(base\$BIRTHDAYPROB,na.rm=TRUE)
m2=max(base\$BIRTHDAYPROB,na.rm=TRUE)
y=1980
colr=rev(heat.colors(100))
sbase=base[YEAR==y,]
plot(0:1,0:1,col="white",xlim=c(-1,12),
ylim=c(-31,1),axes=FALSE,xlab=
paste("Naissance en",y,sep=" "),ylab="")
for(x in 1:nrow(sbase)){
a=sbase\$MONTH[x];b=sbase\$DAY[x]
polygon(c(a-.9,a-.9,a-.1,a-.1),-c(b-.9,b-.1,
b-.1,b-.9),col=colr[(sbase\$BIRTHDAYPROB[x]-m1)/
(m2-m1)*100],border=NA)
}
text((1:12)-.5,.5,c("J","F","M","A","M","J","J",
"A","S","O","N","D"),cex=.7)
text(-.5,-(1:31)+.5,1:31,cex=.7)```

OpenEdition suggests that you cite this post as follows:
Arthur Charpentier (May 19, 2012). Births and week-ends, in France. Freakonometrics. Retrieved August 11, 2024 from https://doi.org/10.58079/oull

## 4 thoughts on “Births and week-ends, in France”

1. Olivier says:

Je suppose que vous l’aviez déjà remarqué, mais vu le déficit évident les 4 et 5 juillets, ainsi que le 13 de tous les mois, je vote pour les États-Unis, comme pays d’origine des données. À cause évidemment de la fête nationale, et de leur peur assez forte du nombre 13 (pas de 13e étage, …).
J’ai du mal à le voir sur le dernier graphique (celui animé), mais retrouve-t-on un tel effet le 14 juillet chez nous ?

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