wwbi_data |> dplyr::filter(indicator_code %in%c("BI.PWK.PRVS.FE.ZS", "BI.PWK.PUBS.FE.ZS")) |>mutate(sector =case_when(indicator_code =="BI.PWK.PUBS.FE.ZS"~"public", indicator_code =="BI.PWK.PRVS.FE.ZS"~"private")) |>select(-indicator_code) |>pivot_wider(id_cols = country_code:year, names_from = sector, values_from = value) |>#filter(year <= 2012) |>group_by(country_code) |>top_n(1, year) |>left_join(wwbi_country, by =c("country_code")) |>ggplot(aes(x = public, y = private)) +geom_point(aes(color = region), size =2) +geom_abline(slope =1, intercept =0) +geom_hline(yintercept =0.5, color ="brown") +geom_vline(xintercept =0.5, color ="brown") +geom_text_repel(aes(label = country_code), size =3.5, color ="darkgrey") +scale_color_brewer(palette ="Dark2") +labs(title ="Proportion of female as share of each sector",x ="Public sector",y ="Private sector") +theme_minimal() +theme(legend.position ="bottom", legend.title =element_blank())
Using data from the Worldwide Bureaucracy Index (using the most recent data available), we plot the proportion of women in each of the public and private sectors. The goal was to to recreate the image at Five facts about gender equality in the public sector, March 2019, which seems to have reversed the values for some of the countries (namely, the European and North American countries). The blog on Five facts on gender equity in the public sector, Sep 2021 seems to align with the information in ours. Notably, the proportion of women in the workforce is below 50% for the majority of countries, especially in the private sector. Women make up more than 50% of employees in the public sector in European and North American countries.
