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)	4714
S12PBI	Defined benefit schemes for general government employees classified in financial corporations	4356
S12P	Private pension schemes	4338
S12PB	Private defined benefit schemes	4304
S13PS	Social security pension schemes (not in core accounts)	4290
S13PBI	Defined benefit schemes for general government employees classified in general government (core accounts)	4142
S13PBX	Defined benefit schemes for general government employees classified in general government (not in core accounts)	4124
S12PC	Private defined contribution schemes	3992
S13PC	Defined contribution schemes of general government (core accounts)	3926
S14R	Counterparts: resident households	2770
S14NR	Counterparts: non-resident households	2220
S1PF	Private/Funded entitlements	140
S13PU	Unfunded entitlements	138

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))