Value added and its components by activity, ISIC rev4, 2019 archive - SNA_TABLE6A_ARCHIVE

Data - OECD

Author

François Geerolf

Data Structure

Code 
SNA_TABLE6A_ARCHIVE_var$VAR_DESC %>%
  {if (is_html_output()) print_table(.) else .}
id description
LOCATION Country
TRANSACT Transaction
ACTIVITY Activity
MEASURE Measure
TIME Year
OBS_VALUE Observation Value
TIME_FORMAT Time Format
OBS_STATUS Observation Status
UNIT Unit
POWERCODE Unit multiplier
REFERENCEPERIOD Reference period

LOCATION

Code 
SNA_TABLE6A_ARCHIVE_var$LOCATION %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

TRANSACT

Code 
SNA_TABLE6A_ARCHIVE_var$TRANSACT %>%
  {if (is_html_output()) print_table(.) else .}
TRANSACT Transact
VA4 6A--Value added and its components by activity, ISIC rev4
P1A Output
P2A Intermediate consumption
B1GA Gross value added
D1A Compensation of employees
D11A of which: gross wages and salaries
B2G_B3GA Gross operating surplus and gross mixed income
K1A Consumption of fixed capital
B2N_B3NA Net operating surplus and net mixed income
D29_D39A Other taxes less other subsidies on production
B1_GE Gross domestic product (expenditure approach)

ACTIVITY

Code 
SNA_TABLE6A_ARCHIVE_var$ACTIVITY %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

MEASURE

Code 
SNA_TABLE6A_ARCHIVE_var$MEASURE %>%
  {if (is_html_output()) print_table(.) else .}
MEASURE Measure
C Current prices
V Constant prices, national base year
VP Constant prices, previous year prices
VOB Constant prices, OECD base year
DOB Deflator, OECD base year = 100

TIME_FORMAT

Code 
SNA_TABLE6A_ARCHIVE_var$TIME_FORMAT %>%
  {if (is_html_output()) print_table(.) else .}
TIME_FORMAT Time_format
P1Y Annual
P1M Monthly
P3M Quarterly
P6M Half-yearly
P1D Daily

VA in Manufacturing

Table

Code 
SNA_TABLE6A_ARCHIVE %>%
  filter(TRANSACT %in% c("B1GA", "B1_GE"),
         ACTIVITY %in% c("VC", "VTOT"),
         MEASURE == "C") %>%
  left_join(SNA_TABLE6A_ARCHIVE_var$LOCATION, by = "LOCATION") %>%
  year_to_date %>%
  mutate(VARIABLE = paste0(TRANSACT, "_", ACTIVITY)) %>%
  select(VARIABLE, LOCATION, Location, date, obsValue) %>%
  spread(VARIABLE, obsValue) %>%
  mutate(value = B1GA_VC / B1_GE_VTOT) %>%
  filter(!is.na(value)) %>%
  group_by(LOCATION, Location) %>%
  summarise(year1 = first(year(date)),
            value1 = first(value),
            year2 = last(year(date)),
            value2 = last(value)) %>%
  mutate_at(vars(value1, value2), funs(paste0(round(100*., digits = 1), " %"))) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

France, Germany, US

Code 
SNA_TABLE6A_ARCHIVE %>%
  filter(TRANSACT %in% c("B1GA", "B1_GE"),
         ACTIVITY %in% c("VC", "VTOT"),
         LOCATION %in% c("FRA", "DEU", "USA"),
         MEASURE == "C") %>%
  left_join(SNA_TABLE6A_ARCHIVE_var$LOCATION, by = "LOCATION") %>%
  year_to_date %>%
  mutate(VARIABLE = paste0(TRANSACT, "_", ACTIVITY)) %>%
  select(VARIABLE, Location, date, obsValue) %>%
  spread(VARIABLE, obsValue) %>%
  mutate(obsValue = B1GA_VC / B1_GE_VTOT) %>%
  na.omit %>%
  left_join(colors, by = c("Location" = "country")) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) + 
  scale_color_identity() + add_3flags + theme_minimal() +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.2, 0.5),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-7, 26, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Value Added in Manufacturing (% of GDP)") + xlab("")

Denmark, Switzerland, UK

Code 
SNA_TABLE6A_ARCHIVE %>%
  filter(TRANSACT %in% c("B1GA", "B1_GE"),
         ACTIVITY %in% c("VC", "VTOT"),
         LOCATION %in% c("GBR", "DNK", "CHE"),
         MEASURE == "C") %>%
  left_join(SNA_TABLE6A_ARCHIVE_var$LOCATION, by = "LOCATION") %>%
  year_to_date %>%
  mutate(VARIABLE = paste0(TRANSACT, "_", ACTIVITY)) %>%
  select(VARIABLE, Location, date, obsValue) %>%
  spread(VARIABLE, obsValue) %>%
  mutate(obsValue = B1GA_VC / B1_GE_VTOT) %>%
  na.omit %>%
  left_join(colors, by = c("Location" = "country")) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) + 
  scale_color_identity() + add_3flags + theme_minimal() +
  scale_x_date(breaks = seq(1920, 2025, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.2, 0.5),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-7, 26, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Value Added in Manufacturing (% of GDP)") + xlab("")

Spain, Italy, Portugal

Code 
SNA_TABLE6A_ARCHIVE %>%
  filter(TRANSACT %in% c("B1GA", "B1_GE"),
         ACTIVITY %in% c("VC", "VTOT"),
         LOCATION %in% c("PRT", "ESP", "ITA"),
         MEASURE == "C") %>%
  left_join(SNA_TABLE6A_ARCHIVE_var$LOCATION, by = "LOCATION") %>%
  year_to_date %>%
  mutate(VARIABLE = paste0(TRANSACT, "_", ACTIVITY)) %>%
  select(VARIABLE, Location, date, obsValue) %>%
  spread(VARIABLE, obsValue) %>%
  mutate(obsValue = B1GA_VC / B1_GE_VTOT) %>%
  na.omit %>%
  left_join(colors, by = c("Location" = "country")) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) + 
  scale_color_identity() + add_3flags + theme_minimal() +
  scale_x_date(breaks = seq(1920, 2025, 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(-7, 26, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Value Added in Manufacturing (% of GDP)") + xlab("")

Norway, Sweden, Finland

Code 
SNA_TABLE6A_ARCHIVE %>%
  filter(TRANSACT %in% c("B1GA", "B1_GE"),
         ACTIVITY %in% c("VC", "VTOT"),
         LOCATION %in% c("NOR", "SWE", "FIN"),
         MEASURE == "C") %>%
  left_join(SNA_TABLE6A_ARCHIVE_var$LOCATION, by = "LOCATION") %>%
  year_to_date %>%
  mutate(VARIABLE = paste0(TRANSACT, "_", ACTIVITY)) %>%
  select(VARIABLE, Location, date, obsValue) %>%
  spread(VARIABLE, obsValue) %>%
  mutate(obsValue = B1GA_VC / B1_GE_VTOT) %>%
  na.omit %>%
  left_join(colors, by = c("Location" = "country")) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) + 
  scale_color_identity() + add_3flags + theme_minimal() +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.1, 0.2),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 40, 2),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Value Added in Manufacturing (% of GDP)") + xlab("")

South Korea, Australia, New Zealand

Code 
SNA_TABLE6A_ARCHIVE %>%
  filter(TRANSACT %in% c("B1GA", "B1_GE"),
         ACTIVITY %in% c("VC", "VTOT"),
         LOCATION %in% c("KOR", "NZL", "AUS"),
         MEASURE == "C") %>%
  left_join(SNA_TABLE6A_ARCHIVE_var$LOCATION, by = "LOCATION") %>%
  year_to_date %>%
  mutate(VARIABLE = paste0(TRANSACT, "_", ACTIVITY)) %>%
  select(VARIABLE, Location, date, obsValue) %>%
  spread(VARIABLE, obsValue) %>%
  mutate(obsValue = B1GA_VC / B1_GE_VTOT) %>%
  na.omit %>%
  left_join(colors, by = c("Location" = "country")) %>%
  ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) + 
  scale_color_identity() + add_3flags + theme_minimal() +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  theme(legend.position = c(0.1, 0.2),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(0, 40, 2),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Value Added in Manufacturing (% of GDP)") + xlab("")