| source | dataset | .html | .RData |
|---|---|---|---|
| eurostat | bop_iip6_q | 2024-11-21 | 2024-10-08 |
International investment position - quarterly and annual data (BPM6)
Data - Eurostat
Info
Data on europe
| source | dataset | .html | .RData |
|---|---|---|---|
| eurostat | bop_gdp6_q | 2024-11-23 | 2024-10-09 |
| eurostat | nama_10_a10 | 2024-11-22 | 2024-10-08 |
| eurostat | nama_10_a10_e | 2024-11-22 | 2024-11-23 |
| eurostat | nama_10_gdp | 2024-11-22 | 2024-11-22 |
| eurostat | nama_10_lp_ulc | 2024-11-22 | 2024-10-08 |
| eurostat | namq_10_a10 | 2024-11-22 | 2024-11-23 |
| eurostat | namq_10_a10_e | 2024-11-22 | 2024-11-22 |
| eurostat | namq_10_gdp | 2024-11-22 | 2024-11-22 |
| eurostat | namq_10_lp_ulc | 2024-11-22 | 2024-11-04 |
| eurostat | namq_10_pc | 2024-11-22 | 2024-11-21 |
| eurostat | nasa_10_nf_tr | 2024-11-22 | 2024-10-08 |
| eurostat | nasq_10_nf_tr | 2024-11-22 | 2024-10-09 |
| eurostat | tipsii40 | 2024-11-22 | 2024-11-23 |
Data on macro
| source | dataset | .html | .RData |
|---|---|---|---|
| eurostat | nama_10_a10 | 2024-11-22 | 2024-10-08 |
| eurostat | nama_10_a10_e | 2024-11-22 | 2024-11-23 |
| eurostat | nama_10_gdp | 2024-11-22 | 2024-11-22 |
| eurostat | nama_10_lp_ulc | 2024-11-22 | 2024-10-08 |
| eurostat | namq_10_a10 | 2024-11-22 | 2024-11-23 |
| eurostat | namq_10_a10_e | 2024-11-22 | 2024-11-22 |
| eurostat | namq_10_gdp | 2024-11-22 | 2024-11-22 |
| eurostat | namq_10_lp_ulc | 2024-11-22 | 2024-11-04 |
| eurostat | namq_10_pc | 2024-11-22 | 2024-11-21 |
| eurostat | nasa_10_nf_tr | 2024-11-22 | 2024-10-08 |
| eurostat | nasq_10_nf_tr | 2024-11-22 | 2024-10-09 |
| fred | gdp | 2024-11-21 | 2024-11-21 |
| oecd | QNA | 2024-06-06 | 2024-11-22 |
| oecd | SNA_TABLE1 | 2024-11-22 | 2024-11-22 |
| 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 | 2024-11-22 | 2024-11-21 |
| wdi | NY.GDP.PCAP.KD | 2024-09-18 | 2024-09-18 |
| wdi | NY.GDP.PCAP.PP.CD | 2024-11-21 | 2024-11-21 |
| wdi | NY.GDP.PCAP.PP.KD | 2024-11-21 | 2024-11-21 |
Last
Code
bop_iip6_q %>%
group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(desc(time)) %>%
head(3) %>%
print_table_conditional()| time | Nobs |
|---|---|
| 2024Q2 | 423090 |
| 2024Q1 | 471741 |
| 2023Q4 | 479160 |
Info
Code
include_graphics("https://ec.europa.eu/eurostat/statistics-explained/images/b/be/Net_international_investment_position%2C_surplus_and_deficit%2C_Top_10_economies%2C_2022_%28€_billion%29.png")
currency
Code
bop_iip6_q %>%
left_join(currency, by = "currency") %>%
group_by(currency, Currency) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()| currency | Currency | Nobs |
|---|---|---|
| MIO_EUR | Million euro | 27301917 |
| MIO_NAC | Million units of national currency | 27211477 |
bop_item
Code
bop_iip6_q %>%
left_join(bop_item, by = "bop_item") %>%
group_by(bop_item, Bop_item) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()sector10
Code
bop_iip6_q %>%
left_join(sector10, by = "sector10") %>%
group_by(sector10, Sector10) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()| sector10 | Sector10 | Nobs |
|---|---|---|
| S1 | Total economy | 14817121 |
| S13 | General Government | 4349616 |
| S121 | Central Bank | 4298223 |
| S123 | Money market funds | 4196286 |
| S122 | Deposit-taking corporations except the central bank | 4009318 |
| S12T | Monetary Financial Institutions (MFI) other than central bank | 3778406 |
| S1P | Other sectors than MFIs and general government | 3754605 |
| S12M | Financial corporations other than MFIs | 3740559 |
| S1V | Non-financial corporations, households and non-profit institutions serving households | 3697209 |
| S12O | Other financial institutions | 1518694 |
| S11 | Non-financial corporations | 1516724 |
| S12Q | Insurance corporations and pension funds | 1499842 |
| S1M | Households and non-profit institutions serving households | 1487682 |
| S124 | Non-MMF investment funds | 1392148 |
| S1Z | Sectors other than deposit-taking corporations and general government | 163282 |
| S12R | Other financial corporations | 130357 |
| S1X | Monetary authorities | 115802 |
| S12K | Monetary financial institutions (MFI) | 43650 |
| S1A | Affiliates | 1290 |
| S1N | Not sectorised | 1290 |
| S1W | Other sectors than General Government | 1290 |
sectpart
Code
bop_iip6_q %>%
left_join(sectpart, by = "sectpart") %>%
group_by(sectpart, Sectpart) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional()| sectpart | Sectpart | Nobs |
|---|---|---|
| S1 | Total economy | 51710642 |
| S12M | Financial corporations other than MFIs | 355231 |
| S123 | Money market funds | 347779 |
| S121 | Central Bank | 344922 |
| S122 | Deposit-taking corporations except the central bank | 334659 |
| S13 | General Government | 316990 |
| S1V | Non-financial corporations, households and non-profit institutions serving households | 308780 |
| S12T | Monetary Financial Institutions (MFI) other than central bank | 221185 |
| S12O | Other financial institutions | 104274 |
| S11 | Non-financial corporations | 104228 |
| S12Q | Insurance corporations and pension funds | 101962 |
| S1M | Households and non-profit institutions serving households | 101114 |
| S124 | Non-MMF investment funds | 71756 |
| S1N | Not sectorised | 64749 |
| S12K | Monetary financial institutions (MFI) | 25121 |
| S1X | Monetary authorities | 2 |
stk_flow
Code
bop_iip6_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 |
|---|---|---|
| A_LE | Assets - positions at the end of period | 21085675 |
| L_LE | Liabilities - positions at the end of period | 14017142 |
| N_LE | Net positions at the end of period | 13824363 |
| A_K7A | Assets - revaluations due to exchange rate changes | 911404 |
| A_K7B | Assets - revaluations due to other price changes | 857076 |
| A_KA | Assets - other changes in the volume of Assets/Liabilities | 798336 |
| L_K7A | Liabilities - revaluations due to exchange rate changes | 533607 |
| L_KA | Liabilities - other changes in the volume of Assets/Liabilities | 504284 |
| L_K7B | Liabilities - revaluations due to other price changes | 481470 |
| N_KA | Net other changes in the volume of Assets/Liabilities | 465504 |
| N_K7A | Net revaluations due to exchange rate changes | 453050 |
| N_K7B | Net revaluations due to other price changes | 446478 |
| NE_LE | Net liabilities (liabilities minus assets) | 134249 |
| NI_LE | Net FDI inward - positions at the end of period | 378 |
| NO_LE | Net FDI outward - positions at the end of period | 378 |
partner
Code
bop_iip6_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_iip6_q %>%
left_join(geo, by = "geo") %>%
group_by(geo, Geo) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
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 .}Net International Investment Position
Table
Code
bop_iip6_q %>%
filter(bop_item == "FA__NENDI",
currency == "MIO_EUR",
nchar(time) == 6) %>%
left_join(geo, by = "geo") %>%
group_by(geo, Geo) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
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 .}France, Germany, Spain, Netherlands, Italy
Code
bop_iip6_q %>%
filter(bop_item == "FA__NENDI",
currency == "MIO_EUR",
geo %in% c("FR", "DE", "EA19", "ES", "NL", "IT"),
nchar(time) == 6) %>%
quarter_to_date %>%
mutate(values = values/1000) %>%
left_join(geo, by = "geo") %>%
mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
left_join(colors, by = c("Geo" = "country")) %>%
ggplot + geom_line(aes(x = date, y = values, color = color)) + theme_minimal() +
scale_color_identity() + add_5flags +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2030, 2), "-01-01")),
labels = date_format("%Y")) +
xlab("") + ylab("Net international investment position") +
scale_y_continuous(breaks = seq(-3000, 3000, 250),
labels = dollar_format(suffix = " Bn€", prefix = "", accuracy = 1))
France, Germany, Europe
Code
bop_iip6_q %>%
filter(bop_item == "FA__NENDI",
currency == "MIO_EUR",
geo %in% c("FR", "DE", "EA20"),
nchar(time) == 6) %>%
quarter_to_date %>%
mutate(values = values/1000) %>%
left_join(geo, by = "geo") %>%
mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
left_join(colors, by = c("Geo" = "country")) %>%
ggplot + geom_line(aes(x = date, y = values, color = color)) + theme_minimal() +
scale_color_identity() + add_2flags +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2030, 2), "-01-01")),
labels = date_format("%Y")) +
xlab("") + ylab("Net international investment position") +
scale_y_continuous(breaks = seq(-3000, 3000, 250),
labels = dollar_format(suffix = " Bn€", prefix = "", accuracy = 1))
Spain, Netherlands, Italy
Code
bop_iip6_q %>%
filter(bop_item == "FA__NENDI",
currency == "MIO_EUR",
geo %in% c("ES", "NL", "IT"),
nchar(time) == 6) %>%
quarter_to_date %>%
mutate(values = values/1000) %>%
left_join(geo, by = "geo") %>%
left_join(colors, by = c("Geo" = "country")) %>%
ggplot + geom_line(aes(x = date, y = values, color = color)) + theme_minimal() +
scale_color_identity() + add_3flags +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2030, 2), "-01-01")),
labels = date_format("%Y")) +
xlab("") + ylab("Net international investment position") +
scale_y_continuous(breaks = seq(-3000, 3000, 250),
labels = dollar_format(suffix = " Bn€", prefix = "", accuracy = 1))