Composite Leading Indicators (MEI)
Data - OECD
François Geerolf
Info
LAST_COMPILE
| LAST_COMPILE |
|---|
| 2024-04-16 |
Last
| obsTime | FREQUENCY | Nobs |
|---|---|---|
| 2022 | A | 5 |
| 2023-08 | M | 118 |
| 2023-Q2 | Q | 32 |
SUBJECT
MEI_CLI %>%
left_join(MEI_CLI_var$SUBJECT, by = c("SUBJECT")) %>%
group_by(SUBJECT, Subject) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()| SUBJECT | Subject | Nobs |
|---|---|---|
| BSCICP03 | OECD Standardised BCI, Amplitude adjusted (Long term average=100), sa | 25369 |
| CSCICP03 | OECD Standardised CCI, Amplitude adjusted (Long term average=100), sa | 24791 |
| LORSGPNO | Normalised (GDP) | 15415 |
| LORSGPRT | Ratio to trend (GDP) | 15415 |
| LORSGPTD | Trend (GDP) | 14868 |
| LOLITOAA | Amplitude adjusted (CLI) | 13417 |
| LOLITONO | Normalised (CLI) | 13417 |
| LOLITOTR_STSA | Trend restored (CLI) | 13147 |
| LOLITOTR_GYSA | 12-month rate of change of the trend restored CLI | 12871 |
| LORSGPOR_IXOBSA | Original, seasonally adjusted (GDP) | 7850 |
| LORSGPOR_GYSA | 12-month rate of change of the reference series (GDP) | 7635 |
FREQUENCY
MEI_CLI %>%
left_join(MEI_CLI_var$FREQUENCY, by = c("FREQUENCY")) %>%
group_by(FREQUENCY, Frequency) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()| FREQUENCY | Frequency | Nobs |
|---|---|---|
| M | Monthly | 156100 |
| Q | Quarterly | 7884 |
| A | Annual | 211 |
LOCATION
MEI_CLI %>%
left_join(MEI_CLI_var$LOCATION, by = "LOCATION") %>%
group_by(LOCATION, Location) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Location))),
Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) %>%
select(Flag, everything()) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}Info
Documentation: http://www.oecd.org/sdd/leading-indicators/41629509.pdf
Leading Indicators Turning Point: http://www.oecd.org/sdd/leading-indicators/CLI-components-and-turning-points.pdf.
OECD Standardised Business Confidence Indicator (BCI)
France, Germany, Japan
All
MEI_CLI %>%
# OECD Standardised Business Confidence Indicator
filter(LOCATION %in% c("FRA", "DEU", "JPN"),
SUBJECT == "BSCICP03") %>%
month_to_date %>%
left_join(MEI_CLI_var$LOCATION, by = "LOCATION") %>%
group_by(LOCATION) %>%
left_join(colors, by = c("Location" = "country")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
scale_color_identity() + add_3flags +
theme_minimal() + xlab("") + ylab("OECD Standardised BCI") +
scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(-10, 200, 1),
labels = dollar_format(accuracy = 1, prefix = "")) +
theme(legend.position = c(0.2, 0.90),
legend.title = element_blank())
1995-
MEI_CLI %>%
# OECD Standardised Business Confidence Indicator
filter(LOCATION %in% c("FRA", "DEU", "JPN"),
SUBJECT == "BSCICP03") %>%
month_to_date %>%
filter(date >= as.Date("1995-01-01")) %>%
left_join(MEI_CLI_var$LOCATION, by = "LOCATION") %>%
group_by(LOCATION) %>%
left_join(colors, by = c("Location" = "country")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
scale_color_identity() + add_3flags +
theme_minimal() + xlab("") + ylab("OECD Standardised BCI") +
scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(-10, 200, 1),
labels = dollar_format(accuracy = 1, prefix = "")) +
theme(legend.position = c(0.2, 0.90),
legend.title = element_blank())
Italy, United States, United Kingdom
All
MEI_CLI %>%
# OECD Standardised Business Confidence Indicator
filter(LOCATION %in% c("ITA", "USA", "GBR"),
SUBJECT == "BSCICP03") %>%
month_to_date %>%
left_join(MEI_CLI_var$LOCATION, by = "LOCATION") %>%
group_by(LOCATION) %>%
left_join(colors, by = c("Location" = "country")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
scale_color_identity() + add_3flags +
theme_minimal() + xlab("") + ylab("OECD Standardised BCI") +
scale_x_date(breaks = seq(1940, 2030, 10) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(-10, 200, 1),
labels = dollar_format(accuracy = 1, prefix = "")) +
theme(legend.position = c(0.2, 0.90),
legend.title = element_blank())
1995-
MEI_CLI %>%
# OECD Standardised Business Confidence Indicator
filter(LOCATION %in% c("ITA", "USA", "GBR"),
SUBJECT == "BSCICP03") %>%
month_to_date %>%
filter(date >= as.Date("1995-01-01")) %>%
left_join(MEI_CLI_var$LOCATION, by = "LOCATION") %>%
group_by(LOCATION) %>%
left_join(colors, by = c("Location" = "country")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
scale_color_identity() + add_3flags +
theme_minimal() + xlab("") + ylab("OECD Standardised BCI") +
scale_x_date(breaks = seq(1940, 2030, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(-10, 200, 1),
labels = dollar_format(accuracy = 1, prefix = "")) +
theme(legend.position = c(0.2, 0.90),
legend.title = element_blank())
OECD Standardised Consumer Confidence Indicator (CCI), Amplitude adjusted (Long term average=100), sa (CCI)
Nobs
France, Germany, Japan
All
MEI_CLI %>%
# CSCICP03: Consumer Confidence Indicator (CCI)
filter(LOCATION %in% c("FRA", "DEU", "JPN"),
SUBJECT == "CSCICP03") %>%
month_to_date %>%
left_join(MEI_CLI_var$LOCATION, by = "LOCATION") %>%
group_by(LOCATION) %>%
left_join(colors, by = c("Location" = "country")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
scale_color_identity() + add_3flags +
theme_minimal() + xlab("") + ylab("OECD Standardised BCI") +
scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(-10, 200, 1),
labels = dollar_format(accuracy = 1, prefix = "")) +
theme(legend.position = c(0.2, 0.90),
legend.title = element_blank())
2010-
MEI_CLI %>%
# CSCICP03: Consumer Confidence Indicator (CCI)
filter(LOCATION %in% c("FRA", "DEU", "JPN"),
SUBJECT == "CSCICP03") %>%
month_to_date %>%
left_join(MEI_CLI_var$LOCATION, by = "LOCATION") %>%
group_by(LOCATION) %>%
left_join(colors, by = c("Location" = "country")) %>%
filter(date >= as.Date("2010-01-01")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
scale_color_identity() + add_3flags +
theme_minimal() + xlab("") + ylab("OECD Standardised BCI") +
scale_x_date(breaks = seq(1940, 2025, 2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(-10, 200, 1),
labels = dollar_format(accuracy = 1, prefix = "")) +
theme(legend.position = c(0.2, 0.90),
legend.title = element_blank())
France, Germany, Italy
All
MEI_CLI %>%
# CSCICP03: Consumer Confidence Indicator (CCI)
filter(LOCATION %in% c("FRA", "DEU", "ITA"),
SUBJECT == "CSCICP03") %>%
month_to_date %>%
left_join(MEI_CLI_var$LOCATION, by = "LOCATION") %>%
group_by(LOCATION) %>%
left_join(colors, by = c("Location" = "country")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
scale_color_identity() + add_3flags +
theme_minimal() + xlab("") + ylab("OECD Standardised BCI") +
scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(-10, 200, 1),
labels = dollar_format(accuracy = 1, prefix = "")) +
theme(legend.position = c(0.2, 0.90),
legend.title = element_blank())
2010-
MEI_CLI %>%
# CSCICP03: Consumer Confidence Indicator (CCI)
filter(LOCATION %in% c("FRA", "DEU", "ITA"),
SUBJECT == "CSCICP03") %>%
month_to_date %>%
left_join(MEI_CLI_var$LOCATION, by = "LOCATION") %>%
group_by(LOCATION) %>%
left_join(colors, by = c("Location" = "country")) %>%
filter(date >= as.Date("2010-01-01")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
scale_color_identity() + add_3flags +
theme_minimal() + xlab("") + ylab("OECD Standardised BCI") +
scale_x_date(breaks = seq(1940, 2030, 2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(-10, 200, 1),
labels = dollar_format(accuracy = 1, prefix = "")) +
theme(legend.position = c(0.2, 0.90),
legend.title = element_blank())
Italy, United States, United Kingdom
MEI_CLI %>%
# CSCICP03: Consumer Confidence Indicator (CCI)
filter(LOCATION %in% c("ITA", "USA", "GBR"),
SUBJECT == "CSCICP03") %>%
month_to_date %>%
left_join(MEI_CLI_var$LOCATION, by = "LOCATION") %>%
group_by(LOCATION) %>%
left_join(colors, by = c("Location" = "country")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
scale_color_identity() + add_3flags +
theme_minimal() + xlab("") + ylab("OECD Standardised BCI") +
scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(-10, 200, 1),
labels = dollar_format(accuracy = 1, prefix = "")) +
theme(legend.position = c(0.2, 0.90),
legend.title = element_blank())
Switzerland, Belgium, Netherlands
MEI_CLI %>%
# CSCICP03: Consumer Confidence Indicator (CCI)
filter(LOCATION %in% c("CHE", "BEL", "NLD"),
SUBJECT == "CSCICP03") %>%
month_to_date %>%
left_join(MEI_CLI_var$LOCATION, by = "LOCATION") %>%
group_by(LOCATION) %>%
left_join(colors, by = c("Location" = "country")) %>%
ggplot(.) + geom_line(aes(x = date, y = obsValue, color = color)) +
scale_color_identity() + add_3flags +
theme_minimal() + xlab("") + ylab("OECD Standardised BCI") +
scale_x_date(breaks = seq(1940, 2020, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(-10, 200, 1),
labels = dollar_format(accuracy = 1, prefix = "")) +
theme(legend.position = c(0.2, 0.90),
legend.title = element_blank())