Quarterly GDP and components - expenditure approach

Data - OECD

Author

François Geerolf

Info

source dataset .html .RData
oecd QNA_EXPENDITURE_CAPITA 2025-09-29 2025-09-28
oecd QNA_EXPENDITURE_USD 2025-08-25 2025-09-28

Last

obsTime Nobs
2025-Q2 336

REF_AREA

Code 
QNA_EXPENDITURE_USD %>%
  left_join(REF_AREA, by = "REF_AREA") %>%
  group_by(REF_AREA, Ref_area) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

UNIT_MEASURE

Code 
QNA_EXPENDITURE_USD %>%
  left_join(UNIT_MEASURE, by = "UNIT_MEASURE") %>%
  group_by(UNIT_MEASURE, Unit_measure) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
UNIT_MEASURE Unit_measure Nobs
USD_PPP US dollars, PPP converted 170511

SECTOR

Code 
QNA_EXPENDITURE_USD %>%
  left_join(SECTOR, by = "SECTOR") %>%
  group_by(SECTOR, Sector) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
SECTOR Sector Nobs
S1 Total economy 113832
S1M Households and non-profit institutions serving households (NPISH) 28362
S13 General government 28317

ADJUSTMENT

Code 
QNA_EXPENDITURE_USD %>%
  left_join(ADJUSTMENT, by = "ADJUSTMENT") %>%
  group_by(ADJUSTMENT, Adjustment) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
ADJUSTMENT Adjustment Nobs
Y Calendar and seasonally adjusted 170511

PRICE_BASE

Code 
QNA_EXPENDITURE_USD %>%
  left_join(PRICE_BASE, by = "PRICE_BASE") %>%
  group_by(PRICE_BASE, Price_base) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
PRICE_BASE Price_base Nobs
LR Chain linked volume (rebased) 85505
V Current prices 85006

FREQ

Code 
QNA_EXPENDITURE_USD %>%
  left_join(FREQ, by = "FREQ") %>%
  group_by(FREQ, Freq) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
FREQ Freq Nobs
Q Quarterly 136570
A Annual 33941

TRANSACTION

Code 
QNA_EXPENDITURE_USD %>%
  left_join(TRANSACTION, by = "TRANSACTION") %>%
  group_by(TRANSACTION, Transaction) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
TRANSACTION Transaction Nobs
P3 Final consumption expenditure 56679
B1GQ Gross domestic product 28801
P6 Exports of goods and services 28357
P7 Imports of goods and services 28357
P51G Gross fixed capital formation 28317

U.S., Europe, France, Germany

All

Code 
QNA_EXPENDITURE_USD %>%
  filter(REF_AREA %in% c("USA", "EA20", "FRA", "DEU"),
         FREQ == "Q",
         TRANSACTION == "B1GQ",
         PRICE_BASE == "LR",
         ADJUSTMENT == "Y",
         SECTOR == "S1") %>%
  quarter_to_date %>%
  arrange(desc(date)) %>%
  rename(LOCATION = REF_AREA) %>%
  left_join(QNA_var$LOCATION, by = "LOCATION") %>%
  mutate(Location = ifelse(LOCATION == "EA20", "Europe", Location)) %>%
  group_by(Location) %>%
  mutate(obsValue = 100 * obsValue / obsValue[date == as.Date("2007-04-01")]) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  mutate(color = ifelse(LOCATION != "DEU", color2, color)) %>%
  ggplot(.) + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = obsValue, color = color)) + add_4flags +
  scale_color_identity() +
  scale_x_date(breaks = c(seq(1900, 2100, 5)) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_log10(breaks = seq(5, 200, 5))

1995-

Code 
QNA_EXPENDITURE_USD %>%
  filter(REF_AREA %in% c("USA", "EA20", "FRA", "DEU"),
         FREQ == "Q",
         TRANSACTION == "B1GQ",
         PRICE_BASE == "LR",
         ADJUSTMENT == "Y",
         SECTOR == "S1") %>%
  quarter_to_date %>%
  arrange(desc(date)) %>%
  rename(LOCATION = REF_AREA) %>%
  left_join(QNA_var$LOCATION, by = "LOCATION") %>%
  filter(date >= as.Date("1995-01-01")) %>%
  mutate(Location = ifelse(LOCATION == "EA20", "Europe", Location)) %>%
  group_by(Location) %>%
  mutate(obsValue = 100 * obsValue / obsValue[date == as.Date("2007-04-01")]) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  mutate(color = ifelse(LOCATION != "DEU", color2, color)) %>%
  ggplot(.) + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = obsValue, color = color)) + add_4flags +
  scale_color_identity() +
  scale_x_date(breaks = c(seq(1995, 2100, 5)) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_log10(breaks = seq(50, 200, 5))

1999-

Tous

Code 
QNA_EXPENDITURE_USD %>%
  filter(REF_AREA %in% c("USA", "EA20", "FRA", "DEU"),
         FREQ == "Q",
         TRANSACTION == "B1GQ",
         PRICE_BASE == "LR",
         ADJUSTMENT == "Y",
         SECTOR == "S1") %>%
  quarter_to_date %>%
  rename(LOCATION = REF_AREA) %>%
  left_join(QNA_var$LOCATION, by = "LOCATION") %>%
  filter(date >= as.Date("1999-01-01")) %>%
  mutate(Location = ifelse(LOCATION == "EA20", "Europe", Location)) %>%
  group_by(Location) %>%
  mutate(obsValue = 100 * obsValue / obsValue[date == as.Date("2007-04-01")]) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  mutate(color = ifelse(LOCATION != "DEU", color2, color)) %>%
  ggplot(.) + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = obsValue, color = color)) + add_4flags +
  scale_color_identity() +
  scale_x_date(breaks = c(seq(1999, 2100, 5), seq(1997, 2100, 5)) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_log10(breaks = seq(50, 200, 5))

Base 100 = 1999

Code 
QNA_EXPENDITURE_USD %>%
  filter(REF_AREA %in% c("USA", "EA20", "FRA", "DEU"),
         FREQ == "Q",
         TRANSACTION == "B1GQ",
         PRICE_BASE == "LR",
         ADJUSTMENT == "Y",
         SECTOR == "S1") %>%
  quarter_to_date %>%
  rename(LOCATION = REF_AREA) %>%
  left_join(QNA_var$LOCATION, by = "LOCATION") %>%
  filter(date >= as.Date("1999-01-01")) %>%
  mutate(Location = ifelse(LOCATION == "EA20", "Europe", Location)) %>%
  group_by(Location) %>%
  mutate(obsValue = 100 * obsValue / obsValue[date == as.Date("1999-01-01")]) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  mutate(color = ifelse(LOCATION != "DEU", color2, color)) %>%
  ggplot(.) + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = obsValue, color = color)) + add_4flags +
  scale_color_identity() +
  scale_x_date(breaks = c(seq(1999, 2100, 5), seq(1997, 2100, 5)) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  theme(legend.position = "none") +
  scale_y_log10(breaks = seq(50, 200, 5))