Industry, value added (including construction) (% of GDP)
Data - WDI
François Geerolf
Info
| source | dataset | .html | .RData |
|---|---|---|---|
| wdi | NV.IND.TOTL.ZS | 2023-12-24 | 2023-09-20 |
Data on industry
| source | dataset | .html | .RData |
|---|---|---|---|
| ec | INDUSTRY | 2023-10-01 | 2023-10-01 |
| eurostat | ei_isin_m | 2023-12-31 | 2023-12-24 |
| eurostat | htec_trd_group4 | 2023-12-31 | 2023-12-24 |
| eurostat | nama_10_a64 | 2023-12-31 | 2023-12-24 |
| eurostat | nama_10_a64_e | 2023-12-24 | 2023-12-31 |
| eurostat | namq_10_a10_e | 2023-12-27 | 2023-12-31 |
| eurostat | road_eqr_carmot | 2023-12-31 | 2023-12-24 |
| eurostat | sts_inpp_m | 2024-01-02 | 2023-12-24 |
| eurostat | sts_inppd_m | 2023-12-24 | 2023-12-31 |
| eurostat | sts_inpr_m | 2023-12-31 | 2023-12-24 |
| eurostat | sts_intvnd_m | 2023-12-31 | 2023-12-24 |
| fred | industry | 2024-01-06 | 2024-01-06 |
| oecd | ALFS_EMP | 2024-01-05 | 2023-10-30 |
| oecd | BERD_MA_SOF | 2024-01-05 | 2023-09-09 |
| oecd | GBARD_NABS2007 | 2024-01-05 | 2023-11-22 |
| oecd | MEI_REAL | 2024-01-05 | 2023-12-27 |
| oecd | MSTI_PUB | 2024-01-05 | 2023-10-04 |
| oecd | SNA_TABLE4 | 2024-01-06 | 2024-01-06 |
| wdi | NV.IND.EMPL.KD | 2024-01-06 | 2023-06-18 |
| wdi | NV.IND.MANF.CD | 2024-01-06 | 2023-12-17 |
| wdi | NV.IND.MANF.ZS | 2024-01-06 | 2023-09-20 |
| wdi | NV.IND.TOTL.KD | 2024-01-06 | 2022-09-27 |
| wdi | NV.IND.TOTL.ZS | 2023-12-24 | 2023-09-20 |
| wdi | SL.IND.EMPL.ZS | 2023-12-24 | 2023-07-22 |
| wdi | TX.VAL.MRCH.CD.WT | 2023-12-24 | 2023-04-12 |
LAST_COMPILE
| LAST_COMPILE |
|---|
| 2024-01-06 |
Nobs - Javascript
NV.IND.TOTL.ZS %>%
left_join(iso2c, by = "iso2c") %>%
group_by(iso2c, Iso2c) %>%
rename(value = `NV.IND.TOTL.ZS`) %>%
mutate(value = round(value, 1)) %>%
summarise(Nobs = n(),
`Year 1` = first(year),
`Industry Share 1 (%)` = first(value),
`Year 2` = last(year),
`Industry Share 2 (%)` = last(value)) %>%
arrange(-Nobs) %>%
mutate(Flag = gsub(" ", "-", str_to_lower(Iso2c)),
Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) %>%
select(Flag, everything()) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}Crises in Emerging Markets (Source: Vegh (2013))
1982: Southern Cone - Argentina, Chile, Uruguay
NV.IND.TOTL.ZS %>%
year_to_date %>%
filter(iso2c %in% c("AR", "CL", "UY"),
date >= as.Date("1976-01-01"),
date <= as.Date("1986-01-01")) %>%
left_join(iso2c, by = "iso2c") %>%
left_join(colors, by = c("Iso2c" = "country")) %>%
mutate(value = NV.IND.TOTL.ZS/100) %>%
ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
xlab("") + ylab("Industry, value added (% of GDP)") +
theme_minimal() + scale_color_identity() + add_3flags +
scale_x_date(breaks = seq(1950, 2100, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
labels = scales::percent_format(accuracy = 1))
1994: Mexico
NV.IND.TOTL.ZS %>%
year_to_date %>%
filter(iso2c %in% c("MX"),
date <= as.Date("1999-01-01"),
date >= as.Date("1989-01-01")) %>%
left_join(iso2c, by = "iso2c") %>%
ggplot(.) +
geom_line(aes(x = date, y = NV.IND.TOTL.ZS/100)) +
theme_minimal() + scale_color_manual(values = viridis(5)[1:4]) +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.8)) +
scale_x_date(breaks = seq(1950, 2100, 1) %>% 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)) +
xlab("") + ylab("Industry, value added (% of GDP)")
1997: East Asia - Indonesia, Korea, Malaysia, Thailand
NV.IND.TOTL.ZS %>%
year_to_date %>%
filter(iso2c %in% c("ID", "KR", "MY", "TH"),
date <= as.Date("2002-01-01"),
date >= as.Date("1992-01-01")) %>%
left_join(iso2c, by = "iso2c") %>%
mutate(Iso2c = ifelse(iso2c == "KR", "South Korea", Iso2c)) %>%
left_join(colors, by = c("Iso2c" = "country")) %>%
mutate(value = NV.IND.TOTL.ZS/100) %>%
ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
xlab("") + ylab("Industry, value added (% of GDP)") +
theme_minimal() + scale_color_identity() + add_4flags +
scale_x_date(breaks = seq(1950, 2100, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
labels = scales::percent_format(accuracy = 1))
2001: Turkey
NV.IND.TOTL.ZS %>%
year_to_date %>%
filter(iso2c %in% c("TR"),
date <= as.Date("2006-01-01"),
date >= as.Date("1996-01-01")) %>%
left_join(iso2c, by = "iso2c") %>%
ggplot(.) +
geom_line(aes(x = date, y = NV.IND.TOTL.ZS/100)) +
theme_minimal() + scale_color_manual(values = viridis(5)[1:4]) +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.8)) +
scale_x_date(breaks = seq(1950, 2100, 1) %>% 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)) +
xlab("") + ylab("Industry, value added (% of GDP)")
2002: Uruguay
NV.IND.TOTL.ZS %>%
year_to_date %>%
filter(iso2c %in% c("UY"),
date <= as.Date("2008-01-01"),
date >= as.Date("1996-01-01")) %>%
left_join(iso2c, by = "iso2c") %>%
ggplot(.) +
geom_line(aes(x = date, y = NV.IND.TOTL.ZS/100)) +
theme_minimal() + scale_color_manual(values = viridis(5)[1:4]) +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.8)) +
scale_x_date(breaks = seq(1950, 2100, 1) %>% 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)) +
xlab("") + ylab("Industry, value added (% of GDP)")
Iceland
NV.IND.TOTL.ZS %>%
filter(iso2c %in% c("IS")) %>%
left_join(iso2c, by = "iso2c") %>%
year_to_date %>%
ggplot(.) + geom_line(aes(x = date, y = NV.IND.TOTL.ZS/100)) +
xlab("") + ylab("Industry, value added (% of GDP)") + theme_minimal() +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.2)) +
scale_x_date(breaks = seq(1950, 2100, 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))
Japan
NV.IND.TOTL.ZS %>%
filter(iso2c %in% c("JP")) %>%
left_join(iso2c, by = "iso2c") %>%
year_to_date %>%
ggplot(.) + geom_line(aes(x = date, y = NV.IND.TOTL.ZS/100)) +
xlab("") + ylab("Industry, value added (% of GDP)") + theme_minimal() +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.2)) +
scale_x_date(breaks = seq(1950, 2100, 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))
World, France, Germany
All
NV.IND.TOTL.ZS %>%
filter(iso2c %in% c("DE", "1W", "FR")) %>%
left_join(iso2c, by = "iso2c") %>%
year_to_date %>%
mutate(value = NV.IND.TOTL.ZS/100) %>%
ggplot(.) + xlab("") + ylab("Industry, value added (% of GDP)") +
geom_line(aes(x = date, y = value, color = Iso2c)) + add_3flags +
theme_minimal() + scale_color_manual(values = c("#002395", "#DD0000", "#000000")) +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.2)) +
scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = 0.01*seq(-60, 60, 2),
labels = scales::percent_format(accuracy = 1))
1990-
NV.IND.TOTL.ZS %>%
filter(iso2c %in% c("DE", "1W", "FR")) %>%
left_join(iso2c, by = "iso2c") %>%
year_to_date %>%
filter(date >= as.Date("1990-01-01")) %>%
mutate(value = NV.IND.TOTL.ZS/100) %>%
ggplot(.) + xlab("") + ylab("Industry, value added (% of GDP)") +
geom_line(aes(x = date, y = value, color = Iso2c)) + add_3flags +
theme_minimal() + scale_color_manual(values = c("#002395", "#DD0000", "#000000")) +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.2)) +
scale_x_date(breaks = seq(1950, 2100, 2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_log10(breaks = 0.01*seq(-60, 60, 2),
labels = scales::percent_format(accuracy = 1))
OECD, World, Advanced
NV.IND.TOTL.ZS %>%
filter(iso2c %in% c("OE", "1W", "EU")) %>%
left_join(iso2c, by = "iso2c") %>%
year_to_date %>%
mutate(Iso2c = ifelse(iso2c == "OE", "OECD Members", Iso2c)) %>%
left_join(colors, by = c("Iso2c" = "country")) %>%
mutate(value = NV.IND.TOTL.ZS/100) %>%
ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
xlab("") + ylab("Industry, value added (% of GDP)") +
theme_minimal() + scale_color_identity() + add_3flags +
scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
labels = scales::percent_format(accuracy = 1))
France, Germany, OECD
NV.IND.TOTL.ZS %>%
filter(iso2c %in% c("OE", "FR", "DE")) %>%
left_join(iso2c, by = "iso2c") %>%
year_to_date %>%
mutate(Iso2c = ifelse(iso2c == "OE", "OECD Members", Iso2c)) %>%
left_join(colors, by = c("Iso2c" = "country")) %>%
mutate(value = NV.IND.TOTL.ZS/100) %>%
ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
xlab("") + ylab("Industry, value added (% of GDP)") +
theme_minimal() + scale_color_identity() + add_3flags +
scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
labels = scales::percent_format(accuracy = 1))
China, France, Germany
NV.IND.TOTL.ZS %>%
filter(iso2c %in% c("CN", "FR", "DE")) %>%
left_join(iso2c, by = "iso2c") %>%
year_to_date %>%
left_join(colors, by = c("Iso2c" = "country")) %>%
mutate(value = NV.IND.TOTL.ZS/100) %>%
ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
xlab("") + ylab("Industry, value added (% of GDP)") +
theme_minimal() + scale_color_identity() + add_3flags +
scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
labels = scales::percent_format(accuracy = 1))
Japan, Iceland, South Korea
NV.IND.TOTL.ZS %>%
filter(iso2c %in% c("JP", "IS", "KR")) %>%
left_join(iso2c, by = "iso2c") %>%
mutate(Iso2c = ifelse(iso2c == "KR", "South Korea", Iso2c)) %>%
year_to_date %>%
left_join(colors, by = c("Iso2c" = "country")) %>%
mutate(value = NV.IND.TOTL.ZS/100) %>%
ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
xlab("") + ylab("Industry, value added (% of GDP)") +
theme_minimal() + scale_color_identity() + add_3flags +
scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
labels = scales::percent_format(accuracy = 1))
Italy, Portugal, Spain
NV.IND.TOTL.ZS %>%
filter(iso2c %in% c("ES", "IT", "PT")) %>%
left_join(iso2c, by = "iso2c") %>%
year_to_date %>%
left_join(colors, by = c("Iso2c" = "country")) %>%
mutate(value = NV.IND.TOTL.ZS/100) %>%
ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
xlab("") + ylab("Industry, value added (% of GDP)") +
theme_minimal() + scale_color_identity() + add_3flags +
scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
labels = scales::percent_format(accuracy = 1))
Spain, United Kingdom, United States
NV.IND.TOTL.ZS %>%
filter(iso2c %in% c("US", "GB", "ES")) %>%
left_join(iso2c, by = "iso2c") %>%
year_to_date %>%
left_join(colors, by = c("Iso2c" = "country")) %>%
mutate(value = NV.IND.TOTL.ZS/100) %>%
ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
xlab("") + ylab("Industry, value added (% of GDP)") +
theme_minimal() + scale_color_identity() + add_3flags +
scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
labels = scales::percent_format(accuracy = 1))
Argentina, Chile, Venezuela
NV.IND.TOTL.ZS %>%
filter(iso2c %in% c("AR", "CL", "VE")) %>%
left_join(iso2c, by = "iso2c") %>%
year_to_date %>%
mutate(Iso2c = ifelse(iso2c == "VE", "Venezuela", Iso2c)) %>%
left_join(colors, by = c("Iso2c" = "country")) %>%
mutate(value = NV.IND.TOTL.ZS/100) %>%
ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
xlab("") + ylab("Industry, value added (% of GDP)") +
theme_minimal() + scale_color_identity() + add_3flags +
scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
labels = scales::percent_format(accuracy = 1))
Greece, Hong Kong, Mexico
NV.IND.TOTL.ZS %>%
filter(iso2c %in% c("GR", "HK", "MX")) %>%
left_join(iso2c, by = "iso2c") %>%
mutate(Iso2c = ifelse(iso2c == "HK", "Hong Kong", Iso2c)) %>%
year_to_date %>%
left_join(colors, by = c("Iso2c" = "country")) %>%
mutate(value = NV.IND.TOTL.ZS/100) %>%
ggplot(.) + geom_line(aes(x = date, y = value, color = color)) +
xlab("") + ylab("Industry, value added (% of GDP)") +
theme_minimal() + scale_color_identity() + add_3flags +
scale_x_date(breaks = seq(1950, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-60, 60, 2),
labels = scales::percent_format(accuracy = 1))