QNA - Manufacturing

Data - OECD

~/data/oecd/QNA.html

Info

source	dataset	.html	.RData
oecd	QNA_manufacturing	2024-04-15	2023-10-04

Data on macro

source	dataset	.html	.RData
eurostat	nama_10_a10	2024-04-15	2024-04-09
eurostat	nama_10_a10_e	2024-04-15	2024-04-09
eurostat	nama_10_gdp	2024-04-15	2024-04-09
eurostat	nama_10_lp_ulc	2024-04-15	2024-04-15
eurostat	namq_10_a10	2024-04-15	2024-04-15
eurostat	namq_10_a10_e	2024-04-15	2024-04-15
eurostat	namq_10_gdp	2024-04-15	2024-04-09
eurostat	namq_10_lp_ulc	2024-04-15	2024-04-09
eurostat	namq_10_pc	2024-04-15	2024-04-09
eurostat	nasa_10_nf_tr	2024-04-15	2024-04-09
eurostat	nasq_10_nf_tr	2024-04-15	2024-04-15
fred	gdp	2024-04-15	2024-04-15
oecd	QNA	2024-04-15	2024-04-15
oecd	SNA_TABLE1	2024-04-15	2024-04-15
oecd	SNA_TABLE14A	2024-04-15	2024-04-15
oecd	SNA_TABLE2	2024-04-15	2024-04-11
oecd	SNA_TABLE6A	2024-04-15	2024-04-15
wdi	NE.RSB.GNFS.ZS	2024-04-14	2024-04-14
wdi	NY.GDP.MKTP.CD	2024-04-14	2024-04-14
wdi	NY.GDP.MKTP.PP.CD	2024-04-14	2024-04-14
wdi	NY.GDP.PCAP.CD	2024-04-14	2024-04-14
wdi	NY.GDP.PCAP.KD	2024-04-14	2024-04-14
wdi	NY.GDP.PCAP.PP.CD	2024-04-14	2024-04-14
wdi	NY.GDP.PCAP.PP.KD	2024-04-14	2024-04-14

Last

obsTime	Nobs
2023-Q2	1034

MEASURE

QNA %>%
  filter(FREQUENCY == "A") %>%
  left_join(QNA_var$MEASURE, by = "MEASURE") %>%
  group_by(MEASURE, Measure) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

Manufacturing VA

Number of observations

QNA %>%
  filter(SUBJECT %in% c("B1GVC"),
         FREQUENCY == "Q") %>%
  left_join(QNA_var$LOCATION, by = "LOCATION") %>%
  group_by(LOCATION, Location) %>%
  quarter_to_date() %>%
  summarise(first = first(date),
            last = last(date),
            Nobs = n()) %>%
  arrange(first) %>%
  mutate(Loc = gsub(" ", "-", str_to_lower(Location)),
         Loc = paste0('<img src="../../icon/flag/vsmall/', Loc, '.png" alt="Flag">')) %>%
  select(Loc, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

Number of observations - CQRSA

QNA %>%
  filter(SUBJECT %in% c("B1GVC"),
         MEASURE == "CQRSA",
         FREQUENCY == "Q") %>%
  left_join(QNA_var$LOCATION, by = "LOCATION") %>%
  group_by(LOCATION, Location) %>%
  quarter_to_date() %>%
  summarise(first = first(date),
            last = last(date),
            Nobs = n()) %>%
  arrange(first) %>%
  mutate(Loc = gsub(" ", "-", str_to_lower(Location)),
         Loc = paste0('<img src="../../icon/flag/vsmall/', Loc, '.png" alt="Flag">')) %>%
  select(Loc, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

France, Germany

QNA %>%
  filter(SUBJECT %in% c("B1GVC", "B1_GE"),
         MEASURE == "CQRSA",
         FREQUENCY == "Q",
         LOCATION %in% c("FRA", "DEU")) %>%
  left_join(QNA_var$LOCATION, by = "LOCATION") %>%
  quarter_to_date %>%
  select(Location, SUBJECT, date, obsValue) %>%
  spread(SUBJECT, obsValue) %>%
  mutate(obsValue = B1GVC / B1_GE) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = color)) +
  scale_color_identity() + theme_minimal() + add_2flags +
  scale_x_date(breaks = seq(1920, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Manufacturing Value Added (% of GDP)") + xlab("")

France, Germany, US, Japan, China, Britain, India

QNA %>%
  filter(SUBJECT %in% c("B1GVC", "B1_GE"),
         MEASURE == "CQRSA",
         FREQUENCY == "Q",
         LOCATION %in% c("FRA", "DEU", "JPN", "CHN", "GBR")) %>%
  left_join(QNA_var$LOCATION, by = "LOCATION") %>%
  quarter_to_date %>%
  filter(date >= as.Date("1995-01-01")) %>%
  select(LOCATION, Location, SUBJECT, date, obsValue) %>%
  spread(SUBJECT, obsValue) %>%
  mutate(obsValue = B1GVC / B1_GE) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  mutate(color = ifelse(LOCATION == "FRA", color2, color)) %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = color)) +
  scale_color_identity() + theme_minimal() + add_4flags +
  scale_x_date(breaks = seq(1920, 2030, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Manufacturing Value Added (% of GDP)") + xlab("")

France, Germany, US, Japan, China, Britain

QNA %>%
  filter(SUBJECT %in% c("B1GVC", "B1_GE"),
         MEASURE == "CQRSA",
         FREQUENCY == "Q",
         LOCATION %in% c("FRA", "DEU", "JPN", "CHN", "GBR")) %>%
  left_join(QNA_var$LOCATION, by = "LOCATION") %>%
  quarter_to_date %>%
  filter(date >= as.Date("1995-01-01")) %>%
  select(LOCATION, Location, SUBJECT, date, obsValue) %>%
  spread(SUBJECT, obsValue) %>%
  mutate(obsValue = B1GVC / B1_GE) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  mutate(color = ifelse(LOCATION == "FRA", color2, color)) %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = color)) +
  scale_color_identity() + theme_minimal() + add_4flags +
  scale_x_date(breaks = seq(1920, 2030, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Manufacturing Value Added (% of GDP)") + xlab("")

France, Italy, Germany

QNA %>%
  filter(SUBJECT %in% c("B1GVC", "B1_GE"),
         MEASURE == "CQRSA",
         FREQUENCY == "Q",
         LOCATION %in% c("ITA", "FRA", "DEU")) %>%
  left_join(QNA_var$LOCATION, by = "LOCATION") %>%
  quarter_to_date %>%
  select(Location, SUBJECT, date, obsValue) %>%
  spread(SUBJECT, obsValue) %>%
  mutate(obsValue = B1GVC / B1_GE) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  mutate(color = ifelse(Location == "Norway", color2, color)) %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = color)) +
  scale_color_identity() + theme_minimal() + add_3flags +
  scale_x_date(breaks = seq(1920, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Manufacturing Value Added (% of GDP)") + xlab("")

Norway, Switzerland, South Korea

QNA %>%
  filter(SUBJECT %in% c("B1GVC", "B1_GE"),
         MEASURE == "CQRSA",
         FREQUENCY == "Q",
         LOCATION %in% c("CHE", "KOR", "NOR")) %>%
  left_join(QNA_var$LOCATION, by = "LOCATION") %>%
  quarter_to_date %>%
  select(Location, SUBJECT, date, obsValue) %>%
  spread(SUBJECT, obsValue) %>%
  mutate(obsValue = B1GVC / B1_GE) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  mutate(color = ifelse(Location == "Norway", color2, color)) %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = color)) +
  scale_color_identity() + theme_minimal() + add_3flags +
  scale_x_date(breaks = seq(1920, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Manufacturing Value Added (% of GDP)") + xlab("")

Costa Rica, Finland, Sweden

QNA %>%
  filter(SUBJECT %in% c("B1GVC", "B1_GE"),
         MEASURE == "CQRSA",
         FREQUENCY == "Q",
         LOCATION %in% c("FIN", "CRI", "SWE")) %>%
  left_join(QNA_var$LOCATION, by = "LOCATION") %>%
  quarter_to_date %>%
  select(Location, SUBJECT, date, obsValue) %>%
  spread(SUBJECT, obsValue) %>%
  mutate(obsValue = B1GVC / B1_GE) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  mutate(color = ifelse(Location == "", color2, color)) %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = color)) +
  scale_color_identity() + theme_minimal() + add_3flags +
  scale_x_date(breaks = seq(1920, 2030, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Manufacturing Value Added (% of GDP)") + xlab("")

Real Manufacturing Value Added (% of Real GDP) - LNBQRSA - Chained Volume

France, Italy, Germany

QNA %>%
  filter(SUBJECT %in% c("B1GVC", "B1_GE"),
         MEASURE == "LNBQRSA",
         FREQUENCY == "Q",
         LOCATION %in% c("ITA", "FRA", "DEU")) %>%
  left_join(QNA_var$LOCATION, by = "LOCATION") %>%
  quarter_to_date %>%
  select(Location, SUBJECT, date, obsValue) %>%
  spread(SUBJECT, obsValue) %>%
  mutate(obsValue = B1GVC / B1_GE) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  mutate(color = ifelse(Location == "Norway", color2, color)) %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = color)) +
  scale_color_identity() + theme_minimal() + add_3flags +
  scale_x_date(breaks = seq(1920, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Manufacturing Value Added (% of GDP)") + xlab("")

France, Germany

All

QNA %>%
  filter(SUBJECT %in% c("B1GVC", "B1_GE"),
         MEASURE == "LNBQRSA",
         FREQUENCY == "Q",
         LOCATION %in% c("FRA", "DEU")) %>%
  left_join(QNA_var$LOCATION, by = "LOCATION") %>%
  quarter_to_date %>%
  select(Location, SUBJECT, date, obsValue) %>%
  spread(SUBJECT, obsValue) %>%
  mutate(obsValue = B1GVC / B1_GE) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = color)) +
  scale_color_identity() + theme_minimal() + add_2flags +
  scale_x_date(breaks = seq(1920, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Manufacturing Value Added (% of GDP)") + xlab("")

1995-

QNA %>%
  filter(SUBJECT %in% c("B1GVC", "B1_GE"),
         MEASURE == "LNBQRSA",
         FREQUENCY == "Q",
         LOCATION %in% c("FRA", "DEU")) %>%
  left_join(QNA_var$LOCATION, by = "LOCATION") %>%
  quarter_to_date %>%
  filter(date >= as.Date("1995-01-01")) %>%
  select(Location, SUBJECT, date, obsValue) %>%
  spread(SUBJECT, obsValue) %>%
  mutate(obsValue = B1GVC / B1_GE) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = color)) +
  scale_color_identity() + theme_minimal() + add_2flags +
  scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Manufacturing Value Added (% of GDP)") + xlab("")

Industry VA

Number of observations

QNA %>%
  filter(SUBJECT %in% c("B1GVB_E"),
         MEASURE == "CQRSA",
         FREQUENCY == "Q") %>%
  left_join(QNA_var$LOCATION, by = "LOCATION") %>%
  group_by(LOCATION, Location) %>%
  quarter_to_date() %>%
  summarise(first = first(date),
            last = last(date),
            Nobs = n()) %>%
  arrange(first) %>%
  mutate(Loc = gsub(" ", "-", str_to_lower(Location)),
         Loc = paste0('<img src="../../icon/flag/vsmall/', Loc, '.png" alt="Flag">')) %>%
  select(Loc, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

France, Germany

All

QNA %>%
  filter(SUBJECT %in% c("B1GVB_E", "B1_GE"),
         MEASURE == "CQRSA",
         FREQUENCY == "Q",
         LOCATION %in% c("FRA", "DEU")) %>%
  left_join(QNA_var$LOCATION, by = "LOCATION") %>%
  quarter_to_date %>%
  select(Location, SUBJECT, date, obsValue) %>%
  spread(SUBJECT, obsValue) %>%
  mutate(obsValue = B1GVB_E / B1_GE) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  mutate(color = ifelse(Location == "Norway", color2, color)) %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = color)) +
  scale_color_identity() + theme_minimal() + add_2flags +
  scale_x_date(breaks = seq(1920, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Industry Value Added (% of GDP)") + xlab("")

1995-

QNA %>%
  filter(SUBJECT %in% c("B1GVB_E", "B1_GE"),
         MEASURE == "CQRSA",
         FREQUENCY == "Q",
         LOCATION %in% c("FRA", "DEU")) %>%
  left_join(QNA_var$LOCATION, by = "LOCATION") %>%
  quarter_to_date %>%
  filter(date >= as.Date("1995-01-01")) %>%
  select(Location, SUBJECT, date, obsValue) %>%
  spread(SUBJECT, obsValue) %>%
  mutate(obsValue = B1GVB_E / B1_GE) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  mutate(color = ifelse(Location == "Norway", color2, color)) %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = color)) +
  scale_color_identity() + theme_minimal() + add_2flags +
  scale_x_date(breaks = seq(1920, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Industry Value Added (% of GDP)") + xlab("")

France, Italy, Germany (% of GDP)

All

QNA %>%
  filter(SUBJECT %in% c("B1GVB_E", "B1_GE"),
         MEASURE == "CQRSA",
         FREQUENCY == "Q",
         LOCATION %in% c("ITA", "FRA", "DEU")) %>%
  left_join(QNA_var$LOCATION, by = "LOCATION") %>%
  quarter_to_date %>%
  select(Location, SUBJECT, date, obsValue) %>%
  spread(SUBJECT, obsValue) %>%
  mutate(obsValue = B1GVB_E / B1_GE) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  mutate(color = ifelse(Location == "Norway", color2, color)) %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = color)) +
  scale_color_identity() + theme_minimal() + add_3flags +
  scale_x_date(breaks = seq(1920, 2030, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Industry Value Added (% of GDP)") + xlab("")

1995-

QNA %>%
  filter(SUBJECT %in% c("B1GVB_E", "B1_GE"),
         MEASURE == "CQRSA",
         FREQUENCY == "Q",
         LOCATION %in% c("ITA", "FRA", "DEU")) %>%
  left_join(QNA_var$LOCATION, by = "LOCATION") %>%
  quarter_to_date %>%
  filter(date >= as.Date("1995-01-01")) %>%
  select(Location, SUBJECT, date, obsValue) %>%
  spread(SUBJECT, obsValue) %>%
  mutate(obsValue = B1GVB_E / B1_GE) %>%
  left_join(colors, by = c("Location" = "country")) %>%
  mutate(color = ifelse(Location == "Norway", color2, color)) %>%
  ggplot() + geom_line(aes(x = date, y = obsValue, color = color)) +
  scale_color_identity() + theme_minimal() + add_3flags +
  scale_x_date(breaks = seq(1920, 2030, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-60, 60, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  ylab("Industry Value Added (% of GDP)") + xlab("")