In MichaelGurkov/MiscImport:

df = import_bis_debt_sec(file_path = paste0(
  file.path(Sys.getenv("USERPROFILE")),
  "\\OneDrive - Bank Of Israel\\Data\\BIS\\",
  "WEBSTATS_DEBTSEC_DATAFLOW_csv_col.csv"),pivot_to_long = FALSE)

Intro

The debt dataset captures debt instruments (think bonds) that are issued in local (Domestic debt securities) or international (International debt securities) markets. For example an Israeli company issuing bonds in Israel will be designated to domestic market where as an Israeli company issuing bonds abroad will be classified to international market.

The location of the company is decided by two factors: Nationality - the place where parent company is headquartered. Residence - the place where the company is incorporated.

So for example a company that is headquartered in Israel but was incorporated in say Cyprus will be considered Cypriot company by residence but Israeli by nationality.

The following chart plot companies that were incorporated in Israel (Israeli residence) by the markets

temp_residence = df %>% 
  filter(issuer_residence == "Israel") %>% 
  filter(issuer_nationality == "All countries excluding residents") %>% 
  filter(issuer_sector_immediate_borrower == "Non-financial corporations") %>% 
  filter(original_maturity == "Total (all maturities)") %>% 
  filter(remaining_maturity == "Total (all maturities)") %>% 
  filter(measure == "Amounts outstanding") %>% 
  filter(issue_market %in% c("International markets",
                             "Domestic market")) %>% 
  filter(issue_currency_group == "All currencies") %>% 
  filter(issue_currency == "Total all currencies") %>% 
  filter(rate_type == "All rate types")


temp_residence %>% 
  select(matches("^[0-9]"),issue_market) %>% 
  pivot_longer(cols = - issue_market,names_to = "date") %>% 
  filter(complete.cases(.)) %>% 
  mutate(value = as.numeric(value),
         date = as.yearqtr(date, format = "%Y-Q%q")) %>% 
  filter(date >= as.yearqtr("2000 Q1")) %>% 
  ggplot(aes(x = date, y = value, color = issue_market)) + 
  geom_line() + 
  xlab(NULL) + ylab(NULL) + ggtitle("Israeli incorporatet comps issues") + 
  theme(legend.position = "bottom", legend.title = element_blank())

rm(temp_residence)

Bis has expanded its International statistics to include details about currency and interest rate type. We can look at currency composition of international issues

temp_currency = df %>% 
  filter(issuer_nationality == "All countries excluding residents") %>% 
  filter(issuer_sector_immediate_borrower == "Non-financial corporations") %>% 
  filter(original_maturity == "Total (all maturities)") %>% 
  filter(remaining_maturity == "Total (all maturities)") %>% 
  filter(measure == "Amounts outstanding") %>% 
  filter(issue_market == "International markets") %>% 
  filter(issue_currency_group == "Foreign currencies") %>% 
  filter(issue_currency == "Total all currencies") %>% 
  filter(rate_type == "All rate types")

MichaelGurkov/MiscImport documentation built on June 6, 2023, 10:53 p.m.