| source | dataset | .html | .RData |
|---|---|---|---|
| oecd | QNA_EXPENDITURE_CAPITA | 2025-09-29 | 2025-09-28 |
| oecd | QNA_POP_EMPNC | 2025-08-25 | 2025-09-28 |
Quarterly compensation of employees by economic activity
Data - OECD
Info
Last
| obsTime | Nobs |
|---|---|
| 2025-Q3 | 3 |
FREQ
Code
QNA_POP_EMPNC %>%
left_join(FREQ, by = "FREQ") %>%
group_by(FREQ, Freq) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()| FREQ | Freq | Nobs |
|---|---|---|
| Q | Quarterly | 37255 |
| A | Annual | 9306 |
REF_AREA
Code
QNA_POP_EMPNC %>%
left_join(REF_AREA, by = "REF_AREA") %>%
group_by(REF_AREA, Ref_area) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()TRANSACTION
Code
QNA_POP_EMPNC %>%
left_join(TRANSACTION, by = "TRANSACTION") %>%
group_by(TRANSACTION, Transaction) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()| TRANSACTION | Transaction | Nobs |
|---|---|---|
| POP | Total population | 14829 |
| EMP | Total employment | 10704 |
| SAL | Employees | 10514 |
| SELF | Self employed | 10514 |
U.S., Europe, France, Germany
Population
1995-
Code
QNA_POP_EMPNC %>%
filter(REF_AREA %in% c("USA", "EA20", "FRA", "DEU"),
FREQ == "Q",
TRANSACTION == "POP",
ADJUSTMENT == "Y",
SECTOR == "S1") %>%
quarter_to_date %>%
arrange(desc(date)) %>%
rename(LOCATION = REF_AREA) %>%
left_join(QNA_var$LOCATION, by = "LOCATION") %>%
filter(date >= as.Date("1995-01-01")) %>%
mutate(Location = ifelse(LOCATION == "EA20", "Europe", Location)) %>%
group_by(Location) %>%
mutate(obsValue = 100 * obsValue / obsValue[date == as.Date("2007-04-01")]) %>%
left_join(colors, by = c("Location" = "country")) %>%
mutate(color = ifelse(LOCATION != "DEU", color2, color)) %>%
ggplot(.) + theme_minimal() + xlab("") + ylab("PIB par habitant (2007 = 100)") +
geom_line(aes(x = date, y = obsValue, color = color)) + add_4flags +
scale_color_identity() +
scale_x_date(breaks = c(seq(1995, 2100, 5)) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
theme(legend.position = "none") +
scale_y_log10(breaks = seq(50, 200, 5))
1999-
Tous
Code
QNA_POP_EMPNC %>%
filter(REF_AREA %in% c("USA", "EA20", "FRA", "DEU"),
FREQ == "Q",
TRANSACTION == "POP",
ADJUSTMENT == "Y",
SECTOR == "S1") %>%
quarter_to_date %>%
rename(LOCATION = REF_AREA) %>%
left_join(QNA_var$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("PIB par habitant (2007 = 100)") +
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_POP_EMPNC %>%
filter(REF_AREA %in% c("USA", "EA20", "FRA", "DEU"),
FREQ == "Q",
TRANSACTION == "POP",
ADJUSTMENT == "Y",
SECTOR == "S1") %>%
quarter_to_date %>%
rename(LOCATION = REF_AREA) %>%
left_join(QNA_var$LOCATION, by = "LOCATION") %>%
filter(date >= as.Date("1999-01-01")) %>%
mutate(Location = ifelse(LOCATION == "EA20", "Europe", Location)) %>%
group_by(Location) %>%
mutate(obsValue = 100 * obsValue / obsValue[date == as.Date("1999-01-01")]) %>%
left_join(colors, by = c("Location" = "country")) %>%
mutate(color = ifelse(LOCATION != "DEU", color2, color)) %>%
ggplot(.) + theme_minimal() + xlab("") + ylab("PIB par habitant (1999T1 = 100)") +
geom_line(aes(x = date, y = obsValue, color = color)) + add_4flags +
scale_color_identity() +
scale_x_date(breaks = c(seq(1999, 2100, 5), seq(1997, 2100, 5)) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
theme(legend.position = "none") +
scale_y_log10(breaks = seq(50, 200, 5)) +
geom_label(data = . %>% filter(date == max(date)), aes(x = date, y = obsValue, label = round(obsValue, 1), color = color))
Employment
1995-
Code
QNA_POP_EMPNC %>%
filter(REF_AREA %in% c("USA", "EA20", "FRA", "DEU"),
FREQ == "Q",
TRANSACTION == "EMP",
ADJUSTMENT == "Y",
SECTOR == "S1") %>%
quarter_to_date %>%
arrange(desc(date)) %>%
rename(LOCATION = REF_AREA) %>%
left_join(QNA_var$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("PIB par habitant (2007 = 100)") +
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_POP_EMPNC %>%
filter(REF_AREA %in% c("USA", "EA20", "FRA", "DEU"),
FREQ == "Q",
TRANSACTION == "EMP",
ADJUSTMENT == "Y",
SECTOR == "S1") %>%
quarter_to_date %>%
rename(LOCATION = REF_AREA) %>%
left_join(QNA_var$LOCATION, by = "LOCATION") %>%
filter(date >= as.Date("1999-01-01")) %>%
mutate(Location = ifelse(LOCATION == "EA20", "Europe", Location)) %>%
group_by(Location) %>%
mutate(obsValue = 100 * obsValue / obsValue[date == as.Date("2007-04-01")]) %>%
left_join(colors, by = c("Location" = "country")) %>%
mutate(color = ifelse(LOCATION != "DEU", color2, color)) %>%
ggplot(.) + theme_minimal() + xlab("") + ylab("PIB par habitant (2007 = 100)") +
geom_line(aes(x = date, y = obsValue, color = color)) + add_4flags +
scale_color_identity() +
scale_x_date(breaks = c(seq(1999, 2100, 5), seq(1997, 2100, 5)) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
theme(legend.position = "none") +
scale_y_log10(breaks = seq(50, 200, 5))
Base 100 = 1999
Code
QNA_POP_EMPNC %>%
filter(REF_AREA %in% c("USA", "EA20", "FRA", "DEU"),
FREQ == "Q",
TRANSACTION == "EMP",
ADJUSTMENT == "Y",
SECTOR == "S1") %>%
quarter_to_date %>%
rename(LOCATION = REF_AREA) %>%
left_join(QNA_var$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("PIB par habitant (1999T1 = 100)") +
geom_line(aes(x = date, y = obsValue, color = color)) + add_2flags +
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))