DBnomics’ API

Data - RDB

Author

François Geerolf 

Warning: le package 'lubriperiod' n'est pas disponible for this version of R

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Warning in library(package, lib.loc = lib.loc, character.only = TRUE,
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Info

source dataset Title .html .rData
rdb api NA NA NA

List of APIs

source dataset Title .html .rData
bdf api NA NA NA
bea api NA NA NA
bis api NA NA NA
bls api NA NA NA
dbnomics api NA NA NA
ecb api NA NA NA
eurostat api NA NA NA
imf api NA NA NA
insee api NA NA NA
oecd api OECD's API 2026-07-31 2026-07-31
wdi api NA NA NA

All

  • Use the JSON RESTful Web Service. html

  • List of providers. html

LAST_COMPILE

LAST_COMPILE
2026-08-01

Nominal GDP

Code 
rdb(ids = c("OECD/QNA/FRA.B1_GE.CARSA.Q",
            "OECD/QNA/USA.B1_GE.CARSA.Q",
            "OECD/QNA/ITA.B1_GE.CARSA.Q",
            "OECD/QNA/GBR.B1_GE.CARSA.Q",
            "OECD/QNA/ESP.B1_GE.CARSA.Q",
            "OECD/QNA/DEU.B1_GE.CARSA.Q")) |>
  filter(period >= as.Date("2019-10-01")) |>
  select(Country, period, value) |>
  group_by(Country) |>
  mutate(value = 100*value/value[1]) |>
  ggplot() + geom_line(aes(x = period, y = value, color = Country)) +
  theme_minimal() + xlab("") + ylab("Real GDP") +
  theme(legend.position = c(0.85, 0.3),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_x_date(breaks = "3 months",
               labels = date_format("%m-%Y")) +
  scale_y_continuous(breaks = seq(80, 200, 2))

Real GDP

Code 
rdb(ids = c("OECD/QNA/FRA.B1_GE.VOBARSA.Q",
            "OECD/QNA/USA.B1_GE.VOBARSA.Q",
            "OECD/QNA/ITA.B1_GE.VOBARSA.Q",
            "OECD/QNA/GBR.B1_GE.VOBARSA.Q",
            "OECD/QNA/ESP.B1_GE.VOBARSA.Q",
            "OECD/QNA/DEU.B1_GE.VOBARSA.Q")) |>
  filter(period >= as.Date("2019-10-01")) |>
  select(Country, period, value) |>
  group_by(Country) |>
  mutate(value = 100*value/value[1]) |>
  ggplot() + geom_line(aes(x = period, y = value, color = Country)) +
  theme_minimal() + xlab("") + ylab("Real GDP") +
  theme(legend.position = c(0.85, 0.3),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
  scale_x_date(breaks = "3 months",
               labels = date_format("%m-%Y")) +
  scale_y_continuous(breaks = seq(80, 120, 2))

U.S. Real GDP Cycle

Code 
rdb(ids = "BEA/NIPA-T10106/A191RX-A") |>
  select(date = period, `Real GDP` = value) |>
  mutate(year = lubridate::year(date)) |>
  mutate(`HP (1000) Cycle` = exp(hpfilter(log(`Real GDP`), freq = 1000, 
                                          type = "lambda", drift = FALSE)$cycle),
         `HP (10000) Cycle` = exp(hpfilter(log(`Real GDP`), freq = 10000, 
                                           type = "lambda", drift = FALSE)$cycle),
         `Log-Linear Cycle` = exp(residuals(lm(log(`Real GDP`) ~ year, 
                                               na.action = na.exclude)))) |>
  group_by(date) |>
  select(-year, - `Real GDP`) |>
  gather(variable, value, -date) |>
  ggplot() + geom_line(aes(x = date, y = value, linetype = variable)) + 
  theme_minimal() +
  theme(legend.title = element_blank(),
        legend.position = c(0.8, 0.8)) +
  geom_rect(data = nber_recessions |>
              filter(Peak > as.Date("1928-01-01")), 
            aes(xmin = Peak, xmax = Trough, ymin = -Inf, ymax = +Inf), 
            fill = 'grey', alpha = 0.5) + 
  scale_x_date(breaks = nber_recessions$Peak,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0.60, 1.40, 0.05),
                     labels = scales::percent_format(accuracy = 1)) + 
  xlab("") + ylab("GDP Cycle (% of Trend)")

U.S. Durable Goods

Code 
rdb(ids = c("BEA/NIPA-T10106/A191RX-A",
            "BEA/NIPA-T10105/DDURRC-A",
            "BEA/NIPA-T10105/A191RC-A")) |>
  select(series_code, date = period, value) |>
  spread(series_code, value) |>
  rename(GDP = `A191RC-A`,
         `Durable Goods` = `DDURRC-A`,
         `Real GDP` = `A191RX-A`) |>
  mutate(year = lubridate::year(date),
         `Real GDP HP (10000) Trend` = exp(hpfilter(log(`Real GDP`), freq = 10000, 
                                                    type = "lambda", drift = FALSE)$trend),
         `Real GDP Log-Linear Trend` = exp(fitted(lm(log(`Real GDP`) ~ year, 
                                                     na.action = na.exclude))),
         `Durable Goods (% of GDP)` = `Durable Goods` / GDP,
         `Durable Goods (% of Log-Linear GDP Trend)` = 
           (`Durable Goods` / GDP)*(`Real GDP` / `Real GDP Log-Linear Trend`),
         `Durable Goods (% of HP GDP Trend)` = 
           (`Durable Goods` / GDP)*(`Real GDP` / `Real GDP HP (10000) Trend`)) |>
  select(date, contains("Durable Goods (%")) |>
  gather(variable, value, -date) |>
  ggplot() +
  geom_line(aes(x = date, y = value, linetype = variable)) +
  theme_minimal() +
  theme(legend.title = element_blank(),
        legend.position = c(0.3, 0.85)) +
  geom_rect(data = nber_recessions |>
              filter(Peak >= as.Date("1928-01-01")),
            aes(xmin = Peak, xmax = Trough, ymin = -Inf, ymax = +Inf), 
            fill = 'grey', alpha = 0.5) +
  scale_x_date(breaks = nber_recessions$Peak,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(2, 16, 1),
                     limits = 0.01*c(2, 16),
                     labels = scales::percent_format(accuracy = 1)) + 
  xlab("") + ylab("Durable Goods (% of GDP)")