Accrued-to-date pension entitlements in social insurance - nasa_10_pens1

Data - Eurostat

Author

na_item

Code

nasa_10_pens1 %>%
  left_join(na_item, by = "na_item") %>%
  group_by(na_item, Na_item) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

penscheme

Code

nasa_10_pens1 %>%
  left_join(penscheme, by = "penscheme") %>%
  group_by(penscheme, Penscheme) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

penscheme	Penscheme	Nobs
S1P	Pension schemes (core and not core accounts)	4776
S12PBI	Defined benefit schemes for general government employees classified in financial corporations	4412
S12P	Private pension schemes	4378
S12PB	Private defined benefit schemes	4346
S13PS	Social security pension schemes (not in core accounts)	4332
S13PBI	Defined benefit schemes for general government employees classified in general government (core accounts)	4198
S13PBX	Defined benefit schemes for general government employees classified in general government (not in core accounts)	4180
S12PC	Private defined contribution schemes	4026
S13PC	Defined contribution schemes of general government (core accounts)	3978
S14R	Counterparts: resident households	2770
S14NR	Counterparts: non-resident households	2220
S1PF	Private/Funded entitlements	142
S13PU	Unfunded entitlements	140

geo

Code

nasa_10_pens1 %>%
  left_join(geo, by = "geo") %>%
  group_by(geo, Geo) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

unit

Code

nasa_10_pens1 %>%
  left_join(unit, by = "unit") %>%
  group_by(unit, Unit) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

D62_P, S1P

Code

nasa_10_pens1 %>%
  filter(geo %in% c("FR", "DE", "IT"),
         # D62_P: Social insurance pension benefits
         na_item == "D62_P",
         # S1P: Pension schemes (core and not core accounts)
         penscheme == "S1P",
         unit == "MIO_EUR") %>%
  year_to_date %>%
  ggplot + geom_line(aes(x = date, y = values/1000, color = geo)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme_minimal()  +
  scale_x_date(breaks = as.Date(paste0(seq(1960, 2020, 5), "-01-01")),
               labels = date_format("%y")) +
  theme(legend.position = c(0.2, 0.85),
        legend.title = element_blank()) +
  xlab("") + ylab("") +
  scale_y_log10(breaks = seq(0, 1000, 100),
                labels = dollar_format(suffix = " Bn€", prefix = "", accuracy = 1))