hhcomp

Code

icw_sr_02 %>%
  left_join(hhcomp, by = "hhcomp") %>%
  group_by(hhcomp, Hhcomp) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

hhcomp	Hhcomp	Nobs
A1	One adult	84
A1_DCH	One adult with dependent children	84
A2	Two adults	84
A2_DCH	Two adults with dependent children	84
A_GE3	Three or more adults	84
A_GE3_DCH	Three or more adults with dependent children	84
TOTAL	Total	84

unit

Code

icw_sr_02 %>%
  left_join(unit, by = "unit") %>%
  group_by(unit, Unit) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

unit	Unit	Nobs
PC_DI	Percentage of disposable income	588

geo

Code

icw_sr_02 %>%
  left_join(geo, by = "geo") %>%
  group_by(geo, Geo) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

time

Code

icw_sr_02 %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}

time	Nobs
2015	217
2010	189
2020	182

2010

Code

icw_sr_02 %>%
  filter(time == "2010") %>%
  select(hhcomp, geo, values) %>%
  left_join(geo, by = "geo") %>%
  spread(hhcomp, values) %>%
  select(geo, Geo, TOTAL, everything()) %>%
  {if (is_html_output()) print_table(.) else .}

geo	Geo	TOTAL	A_GE3	A_GE3_DCH	A1	A1_DCH	A2	A2_DCH
AT	Austria	18.0	34.3	30.1	8.3	2.8	22.1	19.2
BE	Belgium	8.9	29.7	14.0	-0.3	-0.4	8.4	16.5
BG	Bulgaria	38.0	51.2	44.2	15.9	23.6	36.9	39.5
CY	Cyprus	12.2	22.3	6.1	21.8	-19.6	18.1	0.4
CZ	Czechia	23.9	32.6	31.9	13.4	11.8	24.7	27.1
DE	Germany	13.5	24.7	23.3	5.6	4.8	15.2	22.2
DK	Denmark	4.3	21.2	17.2	-4.1	-17.5	13.7	15.2
EE	Estonia	34.9	42.0	45.5	28.2	23.7	39.4	36.7
EL	Greece	-11.2	6.8	-12.2	-22.9	-53.8	1.8	-26.3
ES	Spain	16.1	26.0	16.6	16.5	-11.8	20.7	7.5
FI	Finland	22.2	40.1	25.2	21.2	6.2	26.8	17.0
FR	France	29.1	40.4	30.2	29.8	12.5	32.7	25.5
HR	Croatia	4.0	17.5	14.9	-11.5	-5.8	6.0	2.5
HU	Hungary	16.3	29.8	28.3	5.8	8.7	20.8	17.2
IE	Ireland	18.4	14.8	15.0	22.6	1.5	23.5	18.6
IT	Italy	26.4	43.6	27.8	22.5	-17.7	31.7	19.6
LT	Lithuania	22.8	39.4	34.7	11.6	-6.4	28.4	23.6
LU	Luxembourg	28.4	43.1	36.1	24.3	0.6	32.2	27.2
LV	Latvia	10.5	27.2	25.7	1.2	-7.4	14.5	12.6
MT	Malta	13.7	30.4	23.6	7.2	-28.4	12.8	2.2
PL	Poland	24.7	37.0	32.7	15.8	12.2	27.0	22.9
PT	Portugal	13.1	25.3	13.1	12.7	-15.1	21.8	2.7
RO	Romania	-5.1	9.6	-2.2	-14.5	-20.4	3.4	-9.8
SE	Sweden	18.0	31.1	30.7	8.9	1.4	27.0	24.5
SI	Slovenia	18.0	35.1	30.9	1.0	-4.4	22.1	18.8
SK	Slovakia	24.4	33.7	35.2	11.0	15.4	25.0	26.3
UK	United Kingdom	22.9	32.0	27.2	19.8	-5.9	25.9	25.4

2015

Code

icw_sr_02 %>%
  filter(time == "2015") %>%
  select(hhcomp, geo, values) %>%
  left_join(geo, by = "geo") %>%
  spread(hhcomp, values) %>%
  select(geo, Geo, TOTAL, everything()) %>%
  {if (is_html_output()) print_table(.) else .}

geo	Geo	TOTAL	A_GE3	A_GE3_DCH	A1	A1_DCH	A2	A2_DCH
AT	Austria	21.1	35.4	35.8	12.8	6.2	25.7	21.4
BE	Belgium	19.0	37.1	35.9	7.4	13.0	18.0	29.8
BG	Bulgaria	17.4	31.3	27.8	2.8	5.4	20.9	19.6
CY	Cyprus	10.5	18.6	12.3	4.7	1.3	11.6	10.9
CZ	Czechia	25.5	36.4	37.5	15.6	12.4	27.0	31.5
DE	Germany	14.9	29.3	32.1	4.8	9.4	18.8	24.4
DK	Denmark	25.6	47.1	41.3	12.1	13.4	29.6	41.0
EA	Euro area (EA11-1999, EA12-2001, EA13-2007, EA15-2008, EA16-2009, EA17-2011, EA18-2014, EA19-2015, EA20-2023)	20.7	30.5	25.6	14.7	9.3	24.5	22.3
EA20	Euro area – 20 countries (from 2023)	20.5	30.1	25.0	14.5	9.2	24.4	22.1
EE	Estonia	34.9	45.7	43.4	31.8	18.0	39.4	31.6
EL	Greece	-6.5	6.3	-6.9	-9.2	-28.4	3.6	-19.0
ES	Spain	19.2	28.4	14.8	23.0	-6.8	23.1	12.2
EU	European Union (EU6-1958, EU9-1973, EU10-1981, EU12-1986, EU15-1995, EU25-2004, EU27-2007, EU28-2013, EU27-2020)	20.1	30.2	25.7	13.2	3.9	24.0	21.8
EU27_2020	European Union - 27 countries (from 2020)	21.0	30.9	27.0	13.8	9.2	24.9	22.7
FI	Finland	19.5	30.5	30.4	15.7	10.3	26.6	16.8
FR	France	34.6	44.9	38.8	34.2	18.1	38.0	32.1
HR	Croatia	4.4	17.5	12.8	-5.6	-19.7	5.5	-1.7
HU	Hungary	14.6	24.1	27.0	5.8	5.7	17.1	17.0
IE	Ireland	25.2	27.8	25.8	23.7	14.6	27.7	25.9
LT	Lithuania	31.6	44.9	39.2	19.4	15.8	41.5	33.3
LU	Luxembourg	27.0	45.8	34.4	17.4	13.6	29.3	29.1
LV	Latvia	24.6	41.4	39.0	8.7	15.5	30.9	28.4
MT	Malta	17.8	33.3	20.1	19.4	-1.4	18.2	9.4
NL	Netherlands	15.8	31.9	34.3	-0.9	8.9	18.9	29.7
PL	Poland	29.5	38.3	35.6	19.3	10.2	33.5	27.9
PT	Portugal	18.9	30.9	22.1	16.9	-1.2	23.3	14.1
RO	Romania	10.9	22.8	13.9	2.5	-5.9	16.3	9.0
SE	Sweden	24.6	35.9	42.0	10.8	15.4	33.5	35.8
SI	Slovenia	22.8	33.0	27.2	18.1	-1.8	29.9	18.1
SK	Slovakia	17.6	32.7	32.3	-2.0	-2.6	18.3	17.5
UK	United Kingdom	15.0	26.2	16.2	9.7	-16.7	19.5	15.9

Germany, France, Sweden

Code

icw_sr_02 %>%
  filter(time == "2015",
         geo %in% c("SE", "FR", "DE")) %>%
  left_join(geo, by = "geo") %>%
  ggplot + geom_line(aes(x = hhcomp, y = values/100, color = Geo, linetype = Geo, group = Geo)) +
  scale_color_manual(values = viridis(4)[1:3]) + theme_minimal() +
  theme(legend.position = c(0.7, 0.9),
        legend.title = element_blank()) +
  xlab("household type") + ylab("Median saving rate by household type") +
  scale_y_continuous(breaks = 0.01*seq(-30, 50, 5),
                     labels = percent_format(accuracy = 1))