Taxes and social contributions receipts - SNA_TABLE10

Data - OECD

Author

François Geerolf

Code 
load_data("oecd/SNA_TABLE10_var.RData")
load_data("oecd/SNA_TABLE10.RData")
load_data("oecd/SNA_TABLE1_var.RData")
load_data("oecd/SNA_TABLE1.RData")

Layout

  • OECD Website. html

Nobs - Javascript

Code 
SNA_TABLE10 %>%
  left_join(SNA_TABLE10_var %>% pluck("TRANSACT"), by = c("TRANSACT" = "id")) %>%
  rename(`TRANSACT Description` = label) %>%
  left_join(SNA_TABLE10_var %>% pluck("SECTOR"), by = c("SECTOR" = "id")) %>%
  rename(`SECTOR Description` = label) %>%
  group_by(TRANSACT, `TRANSACT Description`, SECTOR, `SECTOR Description`) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Data Structure

Code 
SNA_TABLE10_var$VAR_DESC %>%
  {if (is_html_output()) print_table(.) else .}
id description
LOCATION Country
TRANSACT Transaction
SECTOR Sector
MEASURE Measure
TIME Year
OBS_VALUE Observation Value
TIME_FORMAT Time Format
OBS_STATUS Observation Status
UNIT Unit
POWERCODE Unit multiplier
REFERENCEPERIOD Reference period

TRANSACT

Code 
SNA_TABLE10 %>%
  left_join(SNA_TABLE10_var %>% pluck("TRANSACT"), by = c("TRANSACT" = "id")) %>%
  rename(`TRANSACT Description` = label) %>%
  group_by(TRANSACT, `TRANSACT Description`) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

SECTOR

Code 
SNA_TABLE10 %>%
  left_join(SNA_TABLE10_var %>% pluck("SECTOR"), by = c("SECTOR" = "id")) %>%
  rename(`SECTOR Description` = label) %>%
  group_by(SECTOR, `SECTOR Description`) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
SECTOR SECTOR Description Nobs
TS13 General government 73886
TS1311 Central government 67506
TS1313 Local government 58869
TS13_S212 Total; General Government and Institutions of the EU 57931
TS1314 Social security funds 42839
TS212 Institutions of the EU 29343
TS1312 State government 22350
S1 Total economy 2711

Ex: D2D5D91 - Total receipts from taxes and social contrib., less various amounts

France, Germany, Italy

Code 
SNA_TABLE10 %>%
  filter(TRANSACT %in% c("D2D5D91"),
         LOCATION %in% c("FRA", "DEU", "ITA"),
         SECTOR == "TS13") %>%
  left_join(SNA_TABLE1 %>%
              filter(TRANSACT == "B1_GE",
                     MEASURE == "C") %>%
              select(obsTime, LOCATION, B1_GE = obsValue), 
            by = c("LOCATION", "obsTime")) %>%
  year_to_enddate %>%
  left_join(SNA_TABLE10_var$LOCATION %>%
              setNames(c("LOCATION", "LOCATION_desc")), by = "LOCATION") %>%
  select(LOCATION_desc, date, TRANSACT, obsValue, B1_GE) %>%
  group_by(LOCATION_desc) %>%
  mutate(B1_GE_trend = log(B1_GE) %>% hpfilter(1000000) %>% pluck("trend") %>% exp,
         obsValue = obsValue / B1_GE_trend) %>%
  na.omit %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = LOCATION_desc, linetype = LOCATION_desc)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.15, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Taxes and social contrib. (% of trend GDP)") + xlab("")

United Kingdom, Japan, United States

Code 
SNA_TABLE10 %>%
  filter(TRANSACT %in% c("D2D5D91"),
         LOCATION %in% c("JPN", "GBR", "USA"),
         SECTOR == "TS13") %>%
  left_join(SNA_TABLE1 %>%
              filter(TRANSACT == "B1_GE",
                     MEASURE == "C") %>%
              select(obsTime, LOCATION, B1_GE = obsValue), 
            by = c("LOCATION", "obsTime")) %>%
  year_to_enddate %>%
  left_join(SNA_TABLE10_var$LOCATION %>%
              setNames(c("LOCATION", "LOCATION_desc")), by = "LOCATION") %>%
  select(LOCATION_desc, date, TRANSACT, obsValue, B1_GE) %>%
  group_by(LOCATION_desc) %>%
  mutate(B1_GE_trend = log(B1_GE) %>% hpfilter(1000000) %>% pluck("trend") %>% exp,
         obsValue = obsValue / B1_GE_trend) %>%
  na.omit %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = LOCATION_desc, linetype = LOCATION_desc)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.15, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Taxes and social contrib. (% of trend GDP)") + xlab("")

Switzerland, Germany, Netherlands

Code 
SNA_TABLE10 %>%
  filter(TRANSACT %in% c("D2D5D91"),
         LOCATION %in% c("NLD", "CHE", "DEU"),
         SECTOR == "TS13") %>%
  left_join(SNA_TABLE1 %>%
              filter(TRANSACT == "B1_GE",
                     MEASURE == "C") %>%
              select(obsTime, LOCATION, B1_GE = obsValue), 
            by = c("LOCATION", "obsTime")) %>%
  year_to_enddate %>%
  left_join(SNA_TABLE10_var$LOCATION %>%
              setNames(c("LOCATION", "LOCATION_desc")), by = "LOCATION") %>%
  select(LOCATION_desc, date, TRANSACT, obsValue, B1_GE) %>%
  group_by(LOCATION_desc) %>%
  mutate(B1_GE_trend = log(B1_GE) %>% hpfilter(1000000) %>% pluck("trend") %>% exp,
         obsValue = obsValue / B1_GE_trend) %>%
  na.omit %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = LOCATION_desc, linetype = LOCATION_desc)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.15, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Taxes and social contrib. (% of trend GDP)") + xlab("")

Ex: TAXB - Total receipts from taxes and social contrib

France, Germany, Italy

Code 
SNA_TABLE10 %>%
  filter(TRANSACT %in% c("TAXB"),
         LOCATION %in% c("FRA", "DEU", "ITA"),
         SECTOR == "TS13") %>%
  left_join(SNA_TABLE1 %>%
              filter(TRANSACT == "B1_GE",
                     MEASURE == "C") %>%
              select(obsTime, LOCATION, B1_GE = obsValue), 
            by = c("LOCATION", "obsTime")) %>%
  year_to_enddate %>%
  left_join(SNA_TABLE10_var$LOCATION %>%
              setNames(c("LOCATION", "LOCATION_desc")), by = "LOCATION") %>%
  select(LOCATION_desc, date, TRANSACT, obsValue, B1_GE) %>%
  group_by(LOCATION_desc) %>%
  mutate(B1_GE_trend = log(B1_GE) %>% hpfilter(1000000) %>% pluck("trend") %>% exp,
         obsValue = obsValue / B1_GE_trend) %>%
  na.omit %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = LOCATION_desc, linetype = LOCATION_desc)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.15, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Taxes and social contrib. (% of trend GDP)") + xlab("")

United Kingdom, Japan, United States

Code 
SNA_TABLE10 %>%
  filter(TRANSACT %in% c("TAXB"),
         LOCATION %in% c("JPN", "GBR", "USA"),
         SECTOR == "TS13") %>%
  left_join(SNA_TABLE1 %>%
              filter(TRANSACT == "B1_GE",
                     MEASURE == "C") %>%
              select(obsTime, LOCATION, B1_GE = obsValue), 
            by = c("LOCATION", "obsTime")) %>%
  year_to_enddate %>%
  left_join(SNA_TABLE10_var$LOCATION %>%
              setNames(c("LOCATION", "LOCATION_desc")), by = "LOCATION") %>%
  select(LOCATION_desc, date, TRANSACT, obsValue, B1_GE) %>%
  group_by(LOCATION_desc) %>%
  mutate(B1_GE_trend = log(B1_GE) %>% hpfilter(1000000) %>% pluck("trend") %>% exp,
         obsValue = obsValue / B1_GE_trend) %>%
  na.omit %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = LOCATION_desc, linetype = LOCATION_desc)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.15, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Taxes and social contrib. (% of trend GDP)") + xlab("")

Switzerland, Germany, Netherlands

Code 
SNA_TABLE10 %>%
  filter(TRANSACT %in% c("TAXB"),
         LOCATION %in% c("NLD", "CHE", "DEU"),
         SECTOR == "TS13") %>%
  left_join(SNA_TABLE1 %>%
              filter(TRANSACT == "B1_GE",
                     MEASURE == "C") %>%
              select(obsTime, LOCATION, B1_GE = obsValue), 
            by = c("LOCATION", "obsTime")) %>%
  year_to_enddate %>%
  left_join(SNA_TABLE10_var$LOCATION %>%
              setNames(c("LOCATION", "LOCATION_desc")), by = "LOCATION") %>%
  select(LOCATION_desc, date, TRANSACT, obsValue, B1_GE) %>%
  group_by(LOCATION_desc) %>%
  mutate(B1_GE_trend = log(B1_GE) %>% hpfilter(1000000) %>% pluck("trend") %>% exp,
         obsValue = obsValue / B1_GE_trend) %>%
  na.omit %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = LOCATION_desc, linetype = LOCATION_desc)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme_minimal() +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.15, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Taxes and social contrib. (% of trend GDP)") + xlab("")