Demographic Change in France – Prenoms Rare

In my blogposts on demographic change in France I have discussed the growing percentage of kids of African origin in France. If estimated via the number of kids that are tested on sickle cell anemia, this percentage has surpassed 40% and has more than doubled since the year 2000. I counted the change in how many newborns are given typical Muslim names and could validate at least the growth rate of the sickle cell data, roughly a doubling between 2000 and 2015. It’s now 1.5 years since I analyzed the data and I decided to revisit the newest given name database, which is updated every year by the French bureau of statistics INSEE.

Re-checking the percentage of muslim names, I made the surprising discovery that since 2016 this percentage has stopped growing. For comparison, the number of names covered by my short list of muslim names is 13003, 26926, 25873 for the year 2000, 2015 and 2018. Given that the number of births has been dropping slightly, this translates into the percentage staying steady over 2015, 2016, 2017 and 2018.

If the muslim population from the Maghreb were the only sickle cell tested kids, this would translate to a steady 40% of kids with African origin. However, this is not the case. Subsaharan immigrants to France usually aren’t Muslims, so even if the percentage of Muslim kids has stopped growing, the original „sickle cell“ percentage might still be growing. (The sickle cell statistic has long been discontinued, for obvious reasons.)

Looking through the data I came across the prenoms rare, the rare first names. Under this moniker the kids are counted that have been given a relatively rare name. Contrary to the Muslim names, the percentage of prenoms rare has been steadily rising even in the last few years. I looked back a bit and made the discovery that this percentage has been doubling every twenty years or so since world war 2.

Given that the Muslim names had stopped increasing recently and given that this exponential growth seems to have started very early, surely before mass immigration, I was ready to interpret it as a trend of the French society towards greater and greater individualism or something. Then I decided to check whether the percentage of Muslim names in the different departments correlates with the percentage of prenoms rare:

It turns out that there is a significant correlation starting in the year 1949, that steadily increases as more and more departments have a count of Muslim names above zero until it reaches almost 0.80. In the early 2000s it suddenly starts dropping and has vanished by 2014. So what’s going on?

One thing that might contribute to killing off the correlation is that names of a 20% minority just aren’t as rare as names of a <10% minority. So Muslims might have slowly outgrown the prenoms rare marker. But the prenoms rare keep rising exponentially, so if Muslim names are getting less rare there has to be another driver of that growth. If we look at the intercept of the linear fit between the Muslim names and the prenoms rare percentage, that is the extrapolated prenoms rare for a department with zero Muslims, we get the following pattern over time:

There is something like 1% of rare names in the original French population and this probably doesn’t change too much. But starting in the 1970s there is an increase in the rare names independent of Muslims names that shows roughly a doubling every ten years or so. It seems probable that this is driven by non-Muslim immigration. However, when I look for the names that correlate strongest with prenoms rare over the different departments I get anything but rare names:

(0.47688124948411037, 1.8063429505759013e-76, ‘GABRIEL’),
(0.470505323840092, 3.2246147618498544e-74, ‘LIAM’),
(0.4416925115802408, 1.2859076223422156e-64, ‘MAËL’),
(0.4326625169376073, 8.57024632603287e-62, ‘MIA’),
(0.4206020094129121, 3.743600297108489e-58, ‘TIMÉO’),
(0.4190831094973139, 1.0503598293466153e-57, ‘ADAM’),
(0.4149723540036518, 1.6689711293740196e-56, ‘NOÉ’),
(0.4079050152026234, 1.7728242577990175e-54, ‘TIAGO’),
(0.4039208782138888, 2.342116862082597e-53, ‘KAÏS’),
(0.3975213210364356, 1.3754944258800354e-51, ‘EDEN’),
(0.39080880395597334, 8.963524732093063e-50, ‘ISSA’),
(0.39039340121367977, 1.1570834678410338e-49, ‘MILA’),
(0.3895565952224957, 1.9331033907637143e-49, ‘ISMAËL’) …

This seems to mostly pick up on urbanisation, which is in line with prenoms rare being driven by immigration. However, the hope to find actual names that represent the prenoms rare population comes to nothing. So again we are left without a sensible measure of the non-Muslim African population growth in France. But with the massive increase in prenoms rare it seems unlikely the entire „sickle cell“ percentage has petered off like the Muslim names.

3 thoughts on “Demographic Change in France – Prenoms Rare

  1. Perhaps seeing which names have the greatest negative correlation to prenoms rare could give some kind of clue? Is it impossible to get a random list of those prenoms rare to get an impression of what they’re like?

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    1. [‘CÉLESTE’, ‘ROXANE’, ‘OSCAR’, ‘THIBAULT’, ‘SIMON’, ‘EDOUARD’, ‘VALENTINE’, ‘CHARLES’, ‘CANDICE’, ‘ELOÏSE’, ‘ZÉLIE’, ‘GARANCE’, ‘LOUISA’, ‘LÉANE’, ‘SUZANNE’, ‘PAOLO’, ‘BASILE’, ‘ROBIN’, ‘CHARLIE’, ‘MÉLINE’, ‘ROMY’, ‘GASPARD’, ‘LISA’, ‘TAO’, ‘THIBAUT’, ‘AUGUSTINE’, ‘AUGUSTIN’, ‘LORIS’, ‘LEÏA’, ‘ALIX’, ‘VICTOR’, ‘ATHÉNAÏS’, ‘JUSTINE’, ‘ELSA’, ‘MARIN’, ‘MARLEY’, ‘JEAN’, ‘CHARLY’, ‘ADRIEN’, ‘MANON’, ‘VICTOIRE’, ‘NATHANAËL’, ‘SWAN’, ‘MILAN’, ‘RUBEN’, ‘HÉLÉNA’, ‘ANTONIN’, ‘THÉA’, ‘ÉLINE’, ‘TIMOTHÉE’, ‘NAËL’, ‘ADÈLE’, ‘EZIO’, ‘NICOLAS’, ‘LUCIEN’, ‘ÉLISE’, ‘QUENTIN’, ‘SÉLÉNA’, ‘LILIA’, ‘LUCY’, ‘MATHIAS’, ‘ELIO’, ‘JOSÉPHINE’, ‘ELISA’, ‘MARIA’, ‘MARION’, ‘MADDY’, ‘TRISTAN’, ‘LÉANDRO’, ‘OCTAVE’, ‘CLARISSE’, ‘APOLLINE’, ‘SALOMÉ’, ‘LISON’, ‘ALESSIO’, ‘ARIA’, ‘CÉLIA’, ‘LÉONIE’, ‘MARCEAU’, ‘CASSANDRE’, ‘LILY-ROSE’, ‘OWEN’, ‘GAUTHIER’, ‘MARGAUX’, ‘ESTEBAN’, ‘TYMÉO’, ‘MARLON’, ‘LEXIE’, ‘ANAÏS’, ‘ÉNORA’, ‘MAËLIE’, ‘LYAM’, ‘AMBROISE’, ‘LYA’, ‘MÏA’, ‘MÉLISSA’, ‘CALIE’, ‘CÉLIAN’, ‘THAÏS’, ‘LUIS’] Those are the 100 names in 2018 least correlated with PRENOMS_RARE across departments.

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