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  • Information on US$ billionaires was extracted from the Forbes list (www.Forbes.com, 2008 list), including wealth, origin of wealth (self-made, inherited, and growing inheritance) residence and citizenship, and number of children (listed for 910 of 1046; 866 with at least one child; 71 female, 795 male). We then searched the billionaire's name online using Google, and used the resulting pages to determine the sex of children. Resulting pages included Wikipedia, bibliographic sites, company websites, and newspapers (particularly marriage, birth and death announcements). For sex ratio analysis we used those billionaires for whom we could ascertain the sex of every child (350 male billionaires, 49 female billionaires). We compared the sex ratio of billionaires with the population sex ratio using a chi-squared test. We then divided region of citizenship and residency into western Europe, eastern Europe, North America, South America, Asia, Africa, and Australasia, to control for cultural differences. Most billionaires were from monogamous societies, with fewer than 20 from Arab countries. Some Asian countries limit the number of children born, which could also influence results. We fitted a full model including interaction effects between gender and region of citizenship and gender and region of residency and the main effects, and used Akaike's Information Criterion [33] to select the most parsimonious model,. We square root transformed number of children to more closely approximate normality [34] and excluded two male billionaires that had grossly outlying number of offspring (37 and 61), since the rest of the population each had less than 20 children. We used a generalized linear logistic model with a logit link function [35] to test if offspring sex ratio differed with the source of wealth using the proportion of sons as the response variable, and gender and wealth-source as factorial predictors. Previous researchers have used work achievement as a proxy for testosterone levels [23]. We therefore reasoned that those billionaires who were either self-made or were growing their inheritance were high achieving (‘high work drive’), whereas those that had inherited their wealth were not as high achieving in employment (‘low work drive’). We fitted a model including all interaction effects and used AICs to select the minimal adequate model.
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