Risk Assessment Indicators - RAI

Name: Risk Assessment Indicators
Creator: François Geerolf
License: https://www.ecb.europa.eu/stats/ecb_statistics/governance_and_quality_framework/html/usage_policy.en.html

Data - ECB

Author

François Geerolf

Structure

Table: Average 2016-2022

Code

RAI |>
  filter(FREQ == "M") |>
  month_to_date() |>
  filter(date >= as.Date("2016-01-01")) |>
  group_by(DD_ECON_CONCEPT, Dd_econ_concept, REF_AREA, Ref_area) |>
  summarise(OBS_VALUE = mean(OBS_VALUE),
            Nobs = n()) |>
  print_table_conditional()

France

Table

Code

RAI |>
  filter(FREQ == "M",
         REF_AREA %in% c("FR", "U2")) %>%
  select_if(~ n_distinct(.) > 1) |>
  group_by(DD_ECON_CONCEPT, Ref_area) |>
  filter(TIME_PERIOD == max(TIME_PERIOD)) |>
  select(Ref_area, DD_ECON_CONCEPT, OBS_VALUE) |>
  spread(Ref_area, OBS_VALUE) |>
  arrange(-`France`) |>
  print_table_conditional()

DD_ECON_CONCEPT	Euro area (changing composition)	France
MMTCH	77.489803	78.7175248
ST1TMF	69.265326	77.4297507
SVLHHNFC	66.024092	43.0546169
IBL1TL	24.661764	36.7274763
LC1DHHS	NA	36.2383613
NDEPFUN	14.751824	15.5728683
LEVR	8.359727	7.1360742
GRNLHHNFC	NA	6.8113000
CT1DGGV	NA	4.3512863
SVLHPHH	16.570010	2.9907668
LMGLNFC	NA	1.1851746
LMGBLNFCH	NA	1.0233873
LMGLHH	NA	0.7114060
LMGOLNFCH	NA	0.2215068

SVLHHNFC, LC1DHHS

Code

RAI |>
  filter(DD_ECON_CONCEPT %in% c("SVLHHNFC", "LC1DHHS"),
         REF_AREA %in% c("FR", "U2")) |>
  month_to_date() %>%
  select_if(~n_distinct(.) > 1) |>
  mutate(Ref_area = ifelse(REF_AREA == "U2", "Europe", Ref_area)) |>
  add_flag_color("Ref_area") |>
  mutate(OBS_VALUE = OBS_VALUE/100) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Share of variable rate") +
  geom_line(aes(x = date, y = OBS_VALUE, color = color, linetype = Dd_econ_concept)) + 
  add_flags(3) + scale_color_identity() +
  scale_x_date(breaks = seq(1960, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
                     labels = percent_format(accuracy = 1))

CT1DGGV, SVLHPHH

Code

RAI |>
  filter(DD_ECON_CONCEPT %in% c("CT1DGGV", "SVLHPHH"),
         REF_AREA %in% c("FR", "U2")) |>
  month_to_date() %>%
  select_if(~n_distinct(.) > 1) |>
  mutate(Ref_area = ifelse(REF_AREA == "U2", "Europe", Ref_area)) |>
  add_flag_color("Ref_area") |>
  mutate(OBS_VALUE = OBS_VALUE/100) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Share of variable rate") +
  geom_line(aes(x = date, y = OBS_VALUE, color = color, linetype = Dd_econ_concept)) + 
  add_flags(3) + scale_color_identity() +
  scale_x_date(breaks = seq(1960, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
                     labels = percent_format(accuracy = 1))

SVLHPHH - Share of floating rates, Households

Table: Last Time

Code

RAI |>
  filter(DD_ECON_CONCEPT == "SVLHPHH") |>
  filter(TIME_PERIOD == max(TIME_PERIOD)) |>
  select_if(~n_distinct(.) > 1) |>
  select(REF_AREA, Ref_area, OBS_VALUE, OBS_VALUE) |>
  mutate(OBS_VALUE = round(OBS_VALUE, 1)) |>
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Ref_area))),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) |>
  select(Flag, everything()) |>
  arrange(OBS_VALUE) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

Table: Many dates

Code

RAI |>
  filter(DD_ECON_CONCEPT == "SVLHPHH",
         TIME_PERIOD %in% c(last_time, "2020-01", "2015-01", "2010-01", "2005-01")) |>
  select_if(~n_distinct(.) > 1) |>
  select(REF_AREA, Ref_area, TIME_PERIOD, OBS_VALUE) |>
  mutate(OBS_VALUE = round(OBS_VALUE, 1)) |>
  spread(TIME_PERIOD, OBS_VALUE) |>
  print_table_conditional()

REF_AREA	Ref_area	2005-01	2010-01	2015-01	2020-01	2026-08
AT	Austria	65.7	76.2	87.3	40.6	20.7
BE	Belgium	58.2	58.4	2.4	4.5	6.7
BG	Bulgaria	NA	96.2	84.0	97.3	99.7
CY	Cyprus	NA	61.7	95.1	90.7	12.0
CZ	Czech Republic	NA	NA	7.2	2.1	6.0
DE	Germany	19.1	21.6	13.2	11.6	13.1
DK	Denmark	70.1	49.2	NA	NA	NA
EE	Estonia	99.3	56.7	85.4	NA	98.0
ES	Spain	93.1	90.1	66.6	32.1	8.3
FI	Finland	97.8	97.5	96.8	97.6	94.8
FR	France	36.5	12.8	3.8	1.9	3.0
GR	Greece	84.4	72.2	93.1	70.2	25.0
HR	Croatia	NA	NA	84.9	20.5	1.7
HU	Hungary	58.1	84.4	44.1	2.1	7.2
IE	Ireland	93.6	84.1	66.0	25.8	6.3
IT	Italy	87.3	81.3	71.7	18.0	23.9
LT	Lithuania	97.9	84.7	89.8	97.8	95.9
LU	Luxembourg	88.5	NA	63.9	30.1	NA
LV	Latvia	72.3	84.4	NA	94.3	93.4
MT	Malta	NA	88.0	77.9	47.4	33.0
NL	Netherlands	43.2	24.9	19.9	17.4	23.2
PL	Poland	90.9	100.0	99.9	100.0	25.9
PT	Portugal	97.8	99.5	93.0	86.7	13.1
RO	Romania	NA	NA	89.9	73.6	25.2
SE	Sweden	NA	85.6	85.5	64.2	90.0
SI	Slovenia	99.1	98.1	93.4	55.5	2.0
SK	Slovakia	62.4	36.0	6.4	1.1	2.0
U2	Euro area (changing composition)	54.7	42.6	21.6	15.8	16.6

Germany, France, Italy, Spain, Netherlands

Code

RAI |>
  filter(DD_ECON_CONCEPT == "SVLHPHH",
         REF_AREA %in% c("FR", "DE", "IT", "ES",  "NL")) |>
  month_to_date() %>%
  select_if(~n_distinct(.) > 1) |>
  mutate(Ref_area = ifelse(REF_AREA == "U2", "Europe", Ref_area)) |>
  add_flag_color("Ref_area") |>
  mutate(OBS_VALUE = OBS_VALUE/100) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Share of variable rate, households (%)") +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  add_flags(5) + scale_color_identity() +
  scale_x_date(breaks = seq(1960, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
                     labels = percent_format(accuracy = 1))

Netherlands, Germany, Belgium, France, Europe

Code

RAI |>
  filter(DD_ECON_CONCEPT == "SVLHPHH",
         REF_AREA %in% c("NL", "DE", "BE", "FR",  "U2")) |>
  month_to_date() %>%
  select_if(~n_distinct(.) > 1) |>
  mutate(Ref_area = ifelse(REF_AREA == "U2", "Europe", Ref_area)) |>
  add_flag_color("Ref_area") |>
  mutate(OBS_VALUE = OBS_VALUE/100) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Share of variable rate, households (%)") +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  add_flags(5) + scale_color_identity() +
  scale_x_date(breaks = seq(1960, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
                     labels = percent_format(accuracy = 1))

France, Spain, Portugal, latvia, Lithuania, Estonia

Code

RAI |>
  filter(DD_ECON_CONCEPT == "SVLHPHH",
         REF_AREA %in% c("FR", "ES", "PT", "EE", "LT", "U2")) |>
  month_to_date() %>%
  select_if(~n_distinct(.) > 1) |>
  mutate(Ref_area = ifelse(REF_AREA == "U2", "Europe", Ref_area)) |>
  add_flag_color("Ref_area") |>
  mutate(OBS_VALUE = OBS_VALUE/100) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Share of variable rate, households (%)") +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  add_flags(6) + scale_color_identity() +
  scale_x_date(breaks = seq(1960, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
                     labels = percent_format(accuracy = 1))

France, Spain, Portugal

Code

RAI |>
  filter(DD_ECON_CONCEPT == "SVLHPHH",
         REF_AREA %in% c("FR", "ES", "PT")) |>
  month_to_date() %>%
  select_if(~n_distinct(.) > 1) |>
  add_flag_color("Ref_area") |>
  mutate(OBS_VALUE = OBS_VALUE/100) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Share of variable rate, households (%)") +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  add_flags(3) + scale_color_identity() +
  scale_x_date(breaks = seq(1960, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
                     labels = percent_format(accuracy = 1))

Italy, Sweden, Poland

Code

RAI |>
  filter(DD_ECON_CONCEPT == "SVLHPHH",
         REF_AREA %in% c("PL", "IT", "SE")) |>
  month_to_date() %>%
  select_if(~n_distinct(.) > 1) |>
  add_flag_color("Ref_area") |>
  mutate(OBS_VALUE = OBS_VALUE/100) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Share of variable rate, households (%)") +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  add_flags(3) + scale_color_identity() +
  scale_x_date(breaks = seq(1960, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
                     labels = percent_format(accuracy = 1))

Netherlands, Germany, Belgium

Code

RAI |>
  filter(DD_ECON_CONCEPT == "SVLHPHH",
         REF_AREA %in% c("NL", "DE", "BE")) |>
  month_to_date() %>%
  select_if(~n_distinct(.) > 1) |>
  add_flag_color("Ref_area") |>
  mutate(OBS_VALUE = OBS_VALUE/100) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Share of variable rate, households (%)") +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  add_flags(3) + scale_color_identity() +
  scale_x_date(breaks = seq(1960, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
                     labels = percent_format(accuracy = 1))

SVLHHNFC - Share of floating rates, Households, and Corporations

Table

Code

RAI |>
  filter(DD_ECON_CONCEPT == "SVLHHNFC",
         TIME_PERIOD %in% c(last_time, "2020-01", "2015-01", "2010-01", "2005-01")) |>
  select_if(~n_distinct(.) > 1) |>
  select(REF_AREA, Ref_area, TIME_PERIOD, OBS_VALUE) |>
  mutate(OBS_VALUE = round(OBS_VALUE, 1)) |>
  spread(TIME_PERIOD, OBS_VALUE) |>
  print_table_conditional()

REF_AREA	Ref_area	2005-01	2010-01	2015-01	2020-01	2026-08
AT	Austria	91.7	92.3	89.7	70.1	69.2
BE	Belgium	90.7	90.4	76.4	73.3	75.3
BG	Bulgaria	NA	98.7	95.8	95.8	98.1
CY	Cyprus	NA	85.4	96.1	94.2	55.9
CZ	Czech Republic	80.8	76.5	51.7	48.7	41.4
DE	Germany	61.5	72.6	59.4	61.3	68.8
DK	Denmark	76.4	64.5	43.6	50.2	70.8
EE	Estonia	92.0	71.1	80.4	83.6	97.7
ES	Spain	91.5	91.4	88.1	70.8	71.7
FI	Finland	94.3	NA	NA	94.8	NA
FR	France	64.8	45.3	39.8	32.3	43.1
GR	Greece	82.9	86.1	97.7	91.6	NA
HR	Croatia	NA	NA	88.8	57.8	54.6
HU	Hungary	95.3	94.5	75.0	52.4	37.0
IE	Ireland	83.0	87.3	82.3	67.3	45.2
IT	Italy	90.4	93.9	92.4	73.4	80.7
LT	Lithuania	93.6	88.3	93.9	89.1	79.3
LU	Luxembourg	98.4	99.1	95.0	91.3	84.8
LV	Latvia	72.6	82.3	80.1	95.3	91.4
MT	Malta	NA	98.7	89.4	59.6	66.7
NL	Netherlands	71.1	73.5	57.2	45.0	62.0
PL	Poland	94.5	93.6	86.6	90.2	57.1
PT	Portugal	95.7	95.9	90.9	74.8	43.3
RO	Romania	NA	96.6	85.9	67.3	59.3
SE	Sweden	NA	89.2	90.6	78.7	90.6
SI	Slovenia	89.5	93.5	91.5	78.9	53.5
SK	Slovakia	83.2	78.9	66.7	23.4	27.4
U2	Euro area (changing composition)	79.2	81.5	69.9	60.5	66.0

France, Spain, Portugal

Code

RAI |>
  filter(DD_ECON_CONCEPT == "SVLHHNFC",
         REF_AREA %in% c("FR", "ES", "PT")) |>
  month_to_date() %>%
  select_if(~n_distinct(.) > 1) |>
  add_flag_color("Ref_area") |>
  mutate(OBS_VALUE = OBS_VALUE/100) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Share of variable rate, households and firms (%)") +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  add_flags(3) + scale_color_identity() +
  scale_x_date(breaks = seq(1960, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
                     labels = percent_format(accuracy = 1))

Italy, Sweden, Poland

Code

RAI |>
  filter(DD_ECON_CONCEPT == "SVLHHNFC",
         REF_AREA %in% c("PL", "IT", "SE")) |>
  month_to_date() %>%
  select_if(~n_distinct(.) > 1) |>
  add_flag_color("Ref_area") |>
  mutate(OBS_VALUE = OBS_VALUE/100) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Share of variable rate, households and firms (%)") +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  add_flags(3) + scale_color_identity() +
  scale_x_date(breaks = seq(1960, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
                     labels = percent_format(accuracy = 1))

Netherlands, Germany, Belgium

Code

RAI |>
  filter(DD_ECON_CONCEPT == "SVLHHNFC",
         REF_AREA %in% c("NL", "DE", "BE")) |>
  month_to_date() %>%
  select_if(~n_distinct(.) > 1) |>
  add_flag_color("Ref_area") |>
  mutate(OBS_VALUE = OBS_VALUE/100) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Share of variable rate, households and firms (%)") +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  add_flags(3) + scale_color_identity() +
  scale_x_date(breaks = seq(1960, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
                     labels = percent_format(accuracy = 1))

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