Underlying GDP by Industry - UnderlyingGDPbyIndustry

Data - BEA

Author

Code

T10105 <- read_parquet("T10105.parquet")
UnderlyingGDPbyIndustry <- read_parquet("UnderlyingGDPbyIndustry.parquet")
nber_recessions <- read_parquet(here::here("data", "us", "nber_recessions.parquet"))

Info

Last observation: 2018-01-01 (N = 4002)

First observation: 1997-01-01 (N = 2482)

Last data update: 25 jul 2026, 12:36. Last compile: 17 aoû 2026, 22:54

List of Parameters

Code

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

ParameterName	ParameterDataType	ParameterDescription
Frequency	string	Q-Quarterly
Industry	string	List of industries to retrieve (ALL for All)
TableID	integer	The unique Underlying 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=UnderlyingGDPbyIndustry&",
       "ParameterName=TableID&") |>
  fromJSON() |>
  pluck("BEAAPI", "Results", "ParamValue") |>
  select(Key, Desc) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Tables

> 3%

Code

UnderlyingGDPbyIndustry |>
  filter(TableID == "211",
         DataValue >= 3,
         date == as.Date("2018-01-01")) |>
  select(Industry, IndustrYDescription, DataValue) |>
  mutate(DataValue = paste0(DataValue, " %")) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

> 1%

Code

UnderlyingGDPbyIndustry |>
  filter(TableID == "211",
         DataValue >= 1,
         date == as.Date("2018-01-01")) |>
  select(Industry, IndustrYDescription, DataValue) |>
  mutate(DataValue = paste0(DataValue, " %")) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Descending

Code

UnderlyingGDPbyIndustry |>
  filter(TableID == "211",
         date == as.Date("2018-01-01")) |>
  select(Industry, IndustrYDescription, DataValue) |>
  arrange(-DataValue) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Graphs

Big Items

Code

UnderlyingGDPbyIndustry |>
  filter(TableID == "211",
         Industry %in% c("FIRE", "PGOOD", "31G", "531")) |>
  ggplot() + ylab("% of GDP") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = DataValue/100, color = IndustrYDescription, linetype = IndustrYDescription)) + 
  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 = "2 years",
               minor_breaks = "1 years",
               labels = date_format("%Y"),
               limits = c(1997, 2019) |> 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'))

Housing, Owner, Tenant

Code

UnderlyingGDPbyIndustry |>
  filter(TableID == "211",
         Industry %in% c("HS", "HSO", "HST")) |>
  ggplot() + ylab("% of GDP") + xlab("") + theme_minimal() +
  geom_line(aes(x = date, y = DataValue/100, color = IndustrYDescription, linetype = IndustrYDescription)) + 
  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 = "2 years",
               minor_breaks = "1 years",
               labels = date_format("%Y"),
               limits = c(1997, 2019) |> paste0("-01-01") |> as.Date()) + 
  scale_y_continuous(breaks = 0.01*seq(0, 160, 2),
                     labels = scales::percent_format(accuracy = 1),
                     limits = c(0, 0.12)) +
  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'))