GDP by Industry - GDPbyIndustry

Data - BEA

Author

Last data update: 25 juil. 2026, 12:36

Last compile: 04 sept. 2026, 23:41

List of Parameters

Code

paste0("https://apps.bea.gov/api/data/?&",
       "UserID=", bea_key, "&",
       "method=GetParameterList&",
       "DataSetName=GDPbyIndustry&") |>
  fromJSON() |>
  pluck("BEAAPI", "Results", "Parameter") |> 
  select(ParameterName, ParameterDataType, ParameterDescription) %>%
  {if (is_html_output()) print_table(.) else .}

ParameterName	ParameterDataType	ParameterDescription
Frequency	string	A - Annual, Q-Quarterly
Industry	string	List of industries to retrieve (ALL for All)
TableID	integer	The unique GDP by Industry table identifier (ALL for All)
Year	integer	List of year(s) of data to retrieve (ALL for All)

List of Tables

Code

paste0("https://apps.bea.gov/api/data/?&",
       "UserID=", bea_key, "&",
       "method=GetParameterValues&",
       "datasetname=GDPbyIndustry&",
       "ParameterName=TableID&") |>
  fromJSON() |>
  pluck("BEAAPI", "Results", "ParamValue") |>
  select(Key, Desc) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Ex 1

Code

paste0("https://apps.bea.gov/api/data/?&",
       "UserID=", bea_key, "&",
       "method=GetData&",
       "DataSetName=GDPbyIndustry&",
       "TableID=15&",
       "Frequency=A&",
       "Industry=ALL&",
       "Year=ALL&",
       "ResultFormat=JSON") |>
  fromJSON() |> 
  pluck("BEAAPI", "Results", "Data") |> 
  nth(1) |>
  select(Industry, IndustrYDescription, Year, DataValue) %>%
  mutate_at(vars(DataValue), funs(gsub(",", "", .) |> as.numeric())) |>
  mutate(date = Year |> paste0("-01-01") |> as.Date()) |>
  select(Industry, IndustrYDescription, date, DataValue) |>
  arrange(date, Industry) |>
  filter(date == as.Date("2018-01-01")) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Ex 2

Code

paste0("https://apps.bea.gov/api/data/?&",
       "UserID=", bea_key, "&",
       "method=GetData&",
       "DataSetName=GDPbyIndustry&",
       "TableID=15&",
       "Frequency=A&",
       "Industry=ALL&",
       "Year=ALL&",
       "ResultFormat=JSON") |>
  fromJSON() |> 
  pluck("BEAAPI", "Results", "Data") |> 
  nth(1) |>
  select(TableID, Year, Industry, IndustrYDescription, DataValue) %>%
  mutate_at(vars(DataValue), funs(gsub(",", "", .) |> as.numeric())) |>
  mutate(date = Year |> paste0("-01-01") |> as.Date()) |>
  filter(Industry %in% c("11", "31G", "6", "7")) |>
  rename(variable = IndustrYDescription) |>
  left_join(gdp_adjustment, by = "date") |>
  mutate(value = 1000 * `Real GDP / Real GDP Trend (Log Linear)` * DataValue / GDP) |>
  ggplot() + geom_line(aes(x = date, y = value, color = variable)) + 
  ylab("% of GDP") + xlab("") + 
  theme_minimal()+
  geom_rect(data = nber_recessions |>
              filter(Peak > as.Date("1927-01-01")),
            aes(xmin = Peak, xmax = Trough, ymin = -Inf, ymax = +Inf), 
            fill = 'grey', alpha = 0.5) +
  scale_x_date(breaks = nber_recessions$Peak,
               minor_breaks = "5 years",
               labels = date_format("%Y"),
               limits = c(1997, Inf) |> paste0("-01-01") |> as.Date()) + 
  scale_y_continuous(breaks = 0.01*seq(0, 160, 2),
                     labels = scales::percent_format(accuracy = 1)) +
  scale_color_manual(values = viridis(5)[1:4]) +
  theme(legend.position = c(0.7, 0.9),
        legend.title = element_blank(),
        legend.text = element_text(size = 8),
        legend.key.size = unit(0.9, 'lines'))