Table 5.10. Changes in Net Stock of Produced Assets (Fixed Assets and Inventories) (A) - T51000

Data - BEA

Last observation: 2021 (N = 75)

First observation: 1951 (N = 69)

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

Last compile: 05 sept. 2026, 22:43

Layout

• NIPA Website. html

Ex 1: Investment, Nominal changes in values (% of GDP)

T51000_A |>
  mutate(table = "T51000") |>
  bind_rows(T10105_A |>
              mutate(table = "T10105")) |>
  year_to_date() |>
  group_by(date) |>
  mutate(value = DataValue/DataValue[LineNumber == 1 & table == "T10105"]) |>
  filter(LineNumber %in% c(8, 54) & table == "T51000") |>
  ggplot() + theme_minimal() +
  geom_line(aes(x = date, y = value, color = LineDescription, linetype = LineDescription)) +
  theme(legend.title = element_blank(),
        legend.position = c(0.7, 0.9)) +
  geom_rect(data = nber_recessions |>
              filter(Peak > as.Date("1950-01-01")), 
            aes(xmin = Peak, xmax = Trough, ymin = -Inf, ymax = +Inf), 
            fill = 'grey', alpha = 0.5) + 
  scale_x_date(breaks = seq(1930, 2100, 5) |> paste0("-01-01") |> as.Date(),
               limits = c(1950, 2020) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  ylab("% of GDP") + xlab("") +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_y_continuous(breaks = 0.01*seq(-100, 600, 5),
                     labels = scales::percent_format(accuracy = 1))

Ex: Private, Government Produced Assets (% of GDP)

T51000_A |>
  mutate(table = "T51000") |>
  bind_rows(T10105_A |>
              mutate(table = "T10105")) |>
  year_to_date() |>
  group_by(date) |>
  mutate(value = DataValue/DataValue[LineNumber == 1 & table == "T10105"]) |>
  filter(LineNumber %in% c(1, 3, 6) & table == "T51000") |>
  ggplot() + theme_minimal() +
  geom_line(aes(x = date, y = value, color = LineDescription, linetype = LineDescription)) +
  theme(legend.title = element_blank(),
        legend.position = c(0.5, 0.3)) +
  geom_rect(data = nber_recessions |>
              filter(Peak > as.Date("1950-01-01")), 
            aes(xmin = Peak, xmax = Trough, ymin = -Inf, ymax = +Inf), 
            fill = 'grey', alpha = 0.5) + 
  scale_x_date(breaks = seq(1930, 2100, 5) |> paste0("-01-01") |> as.Date(),
               limits = c(1950, 2020) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  ylab("% of GDP") + xlab("") +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_y_continuous(breaks = 0.01*seq(-100, 600, 50),
                     labels = scales::percent_format(accuracy = 1))

Ex 2: 1938, 1958, 1978, 1998, 2018 Table

Percent of GDP

T51000_A |>
  mutate(table = "T51000") |>
  bind_rows(T10105_A |>
              mutate(table = "T10105")) |>
  year_to_date() |>
  group_by(date) |>
  mutate(year = year(date)) |>
  filter(year %in% c(1938, 1958, 1978, 1998, 2018)) |>
  group_by(year) |>
  mutate(value = round(100*DataValue/DataValue[LineNumber == 1 & table == "T10105"], 1)) |>
  filter(table == "T51000") |>
  ungroup() |>
  select(2, 3, 7, 8) |>
  spread(year, value) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Billions

T51000_A |>
  year_to_date() |>
  mutate(year = year(date)) |>
  filter(year %in% c(1938, 1958, 1978, 1998, 2018)) |>
  group_by(year) |>
  mutate(value = round(DataValue/1000)) |>
  ungroup() |>
  select(2, 3, 6, 7) |>
  spread(year, value) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}