source | dataset | .html | .RData |
---|---|---|---|
eurostat | bop_gdp6_q | 2024-11-01 | 2024-10-09 |
Main Balance of Payments and International Investment Position items as share of GDP (BPM6)
Data - Eurostat
Info
Data on europe
source | dataset | .html | .RData |
---|---|---|---|
eurostat | bop_gdp6_q | 2024-11-01 | 2024-10-09 |
eurostat | nama_10_a10 | 2024-11-01 | 2024-10-08 |
eurostat | nama_10_a10_e | 2024-11-01 | 2024-11-05 |
eurostat | nama_10_gdp | 2024-11-01 | 2024-10-08 |
eurostat | nama_10_lp_ulc | 2024-11-01 | 2024-10-08 |
eurostat | namq_10_a10 | 2024-11-01 | 2024-11-05 |
eurostat | namq_10_a10_e | 2024-11-01 | 2024-10-08 |
eurostat | namq_10_gdp | 2024-11-01 | 2024-10-08 |
eurostat | namq_10_lp_ulc | 2024-11-04 | 2024-11-04 |
eurostat | namq_10_pc | 2024-11-01 | 2024-10-08 |
eurostat | nasa_10_nf_tr | 2024-11-01 | 2024-10-08 |
eurostat | nasq_10_nf_tr | 2024-11-01 | 2024-10-09 |
eurostat | tipsii40 | 2024-11-01 | 2024-11-01 |
Data on macro
source | dataset | .html | .RData |
---|---|---|---|
eurostat | nama_10_a10 | 2024-11-01 | 2024-10-08 |
eurostat | nama_10_a10_e | 2024-11-01 | 2024-11-05 |
eurostat | nama_10_gdp | 2024-11-01 | 2024-10-08 |
eurostat | nama_10_lp_ulc | 2024-11-01 | 2024-10-08 |
eurostat | namq_10_a10 | 2024-11-01 | 2024-11-05 |
eurostat | namq_10_a10_e | 2024-11-01 | 2024-10-08 |
eurostat | namq_10_gdp | 2024-11-01 | 2024-10-08 |
eurostat | namq_10_lp_ulc | 2024-11-04 | 2024-11-04 |
eurostat | namq_10_pc | 2024-11-01 | 2024-10-08 |
eurostat | nasa_10_nf_tr | 2024-11-01 | 2024-10-08 |
eurostat | nasq_10_nf_tr | 2024-11-01 | 2024-10-09 |
fred | gdp | 2024-11-01 | 2024-11-01 |
oecd | QNA | 2024-06-06 | 2024-06-30 |
oecd | SNA_TABLE1 | 2024-09-15 | 2024-06-30 |
oecd | SNA_TABLE14A | 2024-09-15 | 2024-06-30 |
oecd | SNA_TABLE2 | 2024-07-01 | 2024-04-11 |
oecd | SNA_TABLE6A | 2024-07-01 | 2024-06-30 |
wdi | NE.RSB.GNFS.ZS | 2024-09-18 | 2024-09-18 |
wdi | NY.GDP.MKTP.CD | 2024-09-18 | 2024-09-26 |
wdi | NY.GDP.MKTP.PP.CD | 2024-09-18 | 2024-09-18 |
wdi | NY.GDP.PCAP.CD | 2024-10-15 | 2024-10-15 |
wdi | NY.GDP.PCAP.KD | 2024-09-18 | 2024-09-18 |
wdi | NY.GDP.PCAP.PP.CD | 2024-10-15 | 2024-10-15 |
wdi | NY.GDP.PCAP.PP.KD | 2024-09-18 | 2024-09-18 |
LAST_COMPILE
LAST_COMPILE |
---|
2024-11-05 |
Last
Code
%>%
bop_gdp6_q group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(desc(time)) %>%
head(1) %>%
print_table_conditional()
time | Nobs |
---|---|
2024Q2 | 3194 |
unit
Code
%>%
bop_gdp6_q left_join(unit, by = "unit") %>%
group_by(unit, Unit) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()
unit | Unit | Nobs |
---|---|---|
PC_GDP | Percentage of gross domestic product (GDP) | 520943 |
PC_GDP_3Y | Percentage of GDP - three-year average | 40702 |
s_adj
Code
%>%
bop_gdp6_q left_join(s_adj, by = "s_adj") %>%
group_by(s_adj, S_adj) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()
s_adj | S_adj | Nobs |
---|---|---|
NSA | Unadjusted data (i.e. neither seasonally adjusted nor calendar adjusted data) | 552066 |
SCA | Seasonally and calendar adjusted data | 9579 |
bop_item
Code
%>%
bop_gdp6_q left_join(bop_item, by = "bop_item") %>%
group_by(bop_item, Bop_item) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()
bop_item | Bop_item | Nobs |
---|---|---|
S | Services | 86141 |
G | Goods | 85443 |
GS | Goods and services | 82848 |
FA__D__F | Financial account; Direct Investment | 61149 |
IN2 | Secondary income | 49483 |
KA | Capital account | 49006 |
FA__P__F | Financial account; Portfolio Investment | 31318 |
FA | Financial account | 30663 |
CA | Current account | 21632 |
IN1 | Primary income | 21125 |
CKA | Current plus capital account (balance = Net lending (+) / net borrowing (-)) | 20583 |
S_X_CG | Services excluding Transport and Financial services | 14222 |
FA__FNED | Net external debt | 4277 |
FA__NENDI | Net international investment position excluding non-defaultable instruments | 3515 |
FA__TXR__F | Financial account excluding reserve assets | 240 |
stk_flow
Code
%>%
bop_gdp6_q left_join(stk_flow, by = "stk_flow") %>%
group_by(stk_flow, Stk_flow) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()
stk_flow | Stk_flow | Nobs |
---|---|---|
CRE | Credit | 111779 |
DEB | Debit | 102585 |
BAL | Balance | 102233 |
CRE_DEB_SUM | Sum of credits and debits | 62431 |
CRE_DEB_AVG | Average of credits and debits | 51576 |
ASS | Assets | 30412 |
NET | Net | 26218 |
LIAB | Liabilities | 25920 |
N_LE | Net positions at the end of period | 17374 |
A_LE | Assets - positions at the end of period | 14061 |
L_LE | Liabilities - positions at the end of period | 13469 |
NE_LE | Net liabilities (liabilities minus assets) | 3587 |
partner
Code
%>%
bop_gdp6_q left_join(partner, by = "partner") %>%
group_by(partner, Partner) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
mutate(Partner = ifelse(partner == "DE", "Germany", Partner)) %>%
mutate(Flag = gsub(" ", "-", str_to_lower(Partner)),
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 .} {
geo
Code
%>%
bop_gdp6_q left_join(geo, by = "geo") %>%
group_by(geo, Geo) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
time
Code
%>%
bop_gdp6_q group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(desc(time)) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
France, Germany, Italy
Last
Code
%>%
bop_gdp6_q filter(freq == "Q") %>%
%>%
quarter_to_date filter(geo %in% c("FR", "DE", "IT"),
== max(date, na.rm = T),
date !(stk_flow %in% c("CRE", "DEB"))) %>%
left_join(geo, by = "geo") %>%
left_join(bop_item, by = "bop_item") %>%
left_join(stk_flow, by = "stk_flow") %>%
select(-geo) %>%
spread(Geo, values) %>%
select_if(~ n_distinct(.) > 1) %>%
arrange(France) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
Germany, Spain, France, Italy, Netherlands, Europe
Current account Balance
All
Code
%>%
bop_gdp6_q filter(freq == "Q") %>%
filter(((geo %in% c("DE", "ES", "FR", "IT", "NL", "EA20")) & partner == "WRL_REST") |
== "EA20" & partner == "EXT_EA20"),
(geo == "PC_GDP",
unit == "CA",
bop_item == "NSA",
s_adj == "BAL") %>%
stk_flow left_join(geo, by = "geo") %>%
left_join(stk_flow, by = "stk_flow") %>%
select_if(~ n_distinct(.) > 1) %>%
%>%
quarter_to_date mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
left_join(colors, by = c("Geo" = "country")) %>%
mutate(values = values/100) %>%
+ geom_line(aes(x = date, y = values, color = color)) + theme_minimal() +
ggplot scale_color_identity() + add_6flags +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
labels = date_format("%Y")) +
xlab("") + ylab("Current account balance") +
scale_y_continuous(breaks = 0.01*seq(-100, 200, 2),
labels = scales::percent_format(accuracy = 1))
2006-
Code
%>%
bop_gdp6_q filter(freq == "Q") %>%
filter(((geo %in% c("DE", "ES", "FR", "IT", "NL", "EA20")) & partner == "WRL_REST") |
== "EA20" & partner == "EXT_EA20"),
(geo == "PC_GDP",
unit == "CA",
bop_item == "NSA",
s_adj == "BAL") %>%
stk_flow left_join(geo, by = "geo") %>%
left_join(stk_flow, by = "stk_flow") %>%
select_if(~ n_distinct(.) > 1) %>%
%>%
quarter_to_date filter(date >=as.Date("2006-01-01")) %>%
mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
left_join(colors, by = c("Geo" = "country")) %>%
mutate(values = values/100) %>%
+ geom_line(aes(x = date, y = values, color = color)) + theme_minimal() +
ggplot scale_color_identity() + add_6flags +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 2), "-01-01")),
labels = date_format("%Y")) +
xlab("") + ylab("Current account balance") +
scale_y_continuous(breaks = 0.01*seq(-100, 200, 2),
labels = scales::percent_format(accuracy = 1))
2012-
Code
%>%
bop_gdp6_q filter(freq == "Q") %>%
filter(((geo %in% c("DE", "ES", "FR", "IT", "NL", "EA20")) & partner == "WRL_REST") |
== "EA20" & partner == "EXT_EA20"),
(geo == "PC_GDP",
unit == "CA",
bop_item == "NSA",
s_adj == "BAL") %>%
stk_flow left_join(geo, by = "geo") %>%
left_join(stk_flow, by = "stk_flow") %>%
select_if(~ n_distinct(.) > 1) %>%
%>%
quarter_to_date filter(date >=as.Date("2012-01-01")) %>%
mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
left_join(colors, by = c("Geo" = "country")) %>%
mutate(values = values/100) %>%
+ geom_line(aes(x = date, y = values, color = color)) + theme_minimal() +
ggplot scale_color_identity() + add_6flags +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 1), "-01-01")),
labels = date_format("%Y")) +
xlab("") + ylab("Current account balance") +
scale_y_continuous(breaks = 0.01*seq(-100, 200, 2),
labels = scales::percent_format(accuracy = 1))
Net Investment Positions (FA__NENDI)
Code
%>%
bop_gdp6_q filter(freq == "Q") %>%
filter(((geo %in% c("DE", "ES", "FR", "IT", "NL", "EA20")) & partner == "WRL_REST") |
== "EA20" & partner == "EXT_EA20"),
(geo == "PC_GDP",
unit == "FA__NENDI",
bop_item == "NSA") %>%
s_adj left_join(geo, by = "geo") %>%
left_join(stk_flow, by = "stk_flow") %>%
select_if(~ n_distinct(.) > 1) %>%
%>%
quarter_to_date mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
left_join(colors, by = c("Geo" = "country")) %>%
mutate(values = values/100) %>%
+ geom_line(aes(x = date, y = values, color = color)) + theme_minimal() +
ggplot scale_color_identity() + add_5flags +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 5), "-01-01")),
labels = date_format("%Y")) +
xlab("") + ylab("Net international investment positions (% of GDP)") +
scale_y_continuous(breaks = 0.01*seq(-100, 200, 10),
labels = scales::percent_format(accuracy = 1))
Goods and Services
Code
%>%
bop_gdp6_q filter(freq == "Q") %>%
filter(((geo %in% c("DE", "ES", "FR", "IT", "NL", "EA20")) & partner == "WRL_REST") |
== "EA20" & partner == "EXT_EA20"),
(geo == "PC_GDP",
unit == "GS",
bop_item == "NSA",
s_adj == "BAL") %>%
stk_flow left_join(geo, by = "geo") %>%
left_join(stk_flow, by = "stk_flow") %>%
select_if(~ n_distinct(.) > 1) %>%
%>%
quarter_to_date mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
left_join(colors, by = c("Geo" = "country")) %>%
mutate(values = values/100) %>%
+ geom_line(aes(x = date, y = values, color = color)) + theme_minimal() +
ggplot scale_color_identity() + add_6flags +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 5), "-01-01")),
labels = date_format("%Y")) +
xlab("") + ylab("Goods and Services") +
scale_y_continuous(breaks = 0.01*seq(-100, 200, 2),
labels = scales::percent_format(accuracy = 1))
Goods
Code
%>%
bop_gdp6_q filter(freq == "Q") %>%
filter(((geo %in% c("DE", "ES", "FR", "IT", "NL", "EA20")) & partner == "WRL_REST") |
== "EA20" & partner == "EXT_EA20"),
(geo == "PC_GDP",
unit == "G",
bop_item == "NSA",
s_adj == "BAL") %>%
stk_flow left_join(geo, by = "geo") %>%
left_join(stk_flow, by = "stk_flow") %>%
select_if(~ n_distinct(.) > 1) %>%
%>%
quarter_to_date mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
left_join(colors, by = c("Geo" = "country")) %>%
mutate(values = values/100) %>%
+ geom_line(aes(x = date, y = values, color = color)) + theme_minimal() +
ggplot scale_color_identity() + add_6flags +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 5), "-01-01")),
labels = date_format("%Y")) +
xlab("") + ylab("Goods") +
scale_y_continuous(breaks = 0.01*seq(-100, 200, 2),
labels = scales::percent_format(accuracy = 1))
Services
Code
%>%
bop_gdp6_q filter(freq == "Q") %>%
filter(((geo %in% c("DE", "ES", "FR", "IT", "NL", "EA20")) & partner == "WRL_REST") |
== "EA20" & partner == "EXT_EA20"),
(geo == "PC_GDP",
unit == "S",
bop_item == "NSA",
s_adj == "BAL") %>%
stk_flow left_join(geo, by = "geo") %>%
left_join(stk_flow, by = "stk_flow") %>%
select_if(~ n_distinct(.) > 1) %>%
%>%
quarter_to_date mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
left_join(colors, by = c("Geo" = "country")) %>%
mutate(values = values/100) %>%
+ geom_line(aes(x = date, y = values, color = color)) + theme_minimal() +
ggplot scale_color_identity() + add_6flags +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2100, 5), "-01-01")),
labels = date_format("%Y")) +
xlab("") + ylab("Services") +
scale_y_continuous(breaks = 0.01*seq(-100, 200, 2),
labels = scales::percent_format(accuracy = 1))