Table 1.2.6. Real Gross Domestic Product by Major Type of Product, Chained Dollars (A) (Q) - T10206

Name: Table 1.2.6. Real Gross Domestic Product by Major Type of Product, Chained Dollars (A) (Q)
Creator: François Geerolf
License: https://www.usa.gov/government-works

Data - BEA

Author

François Geerolf

Last observation: Q2 2026 (N = 22) · 2025 (N = 22)

First observation: 1929 (N = 11) · Q1 1947 (N = 11)

Last data update: 04 sept. 2026, 23:39

Last compile: 05 sept. 2026, 22:42

Layout

NIPA Website. html

U.S. Real GDP (Quarterly)

Code

fit_Q <- T10206_Q |>
  quarter_to_date() |>
  filter(LineNumber == 1) |>
  select(date, `Real GDP` = DataValue) |>
  mutate(`Real GDP` = `Real GDP` / 1000000,
         datenum = year(date)+(month(date)-1)/12) |>
  filter(datenum <= 1971) %>%
  lm(log(`Real GDP`) ~ datenum, data = .) |>
  pluck("coefficients")

U.S. Real GDP Trends (1947-)

Log

1947-

Code

T10206_Q |>
  quarter_to_date() |>
  filter(LineNumber == 1) |>
  select(date, `Real GDP` = DataValue) |>
  mutate(`Real GDP` = `Real GDP` / 1000000,
         datenum = year(date)+(month(date)-1)/12) |>
  mutate(`Trend to Today` = lm(log(`Real GDP`) ~ datenum) |> fitted() |> exp(),
         `Trend to 1971, extrapolated` = ifelse(datenum >= 1971, (fit_Q[1] + fit_Q[2] * datenum) |> exp(), NA),
         `Trend to 1971` = ifelse(datenum <= 1971, (fit_Q[1] + fit_Q[2] * datenum) |> exp(), NA)) |>
  group_by(date) |>
  select(-datenum) |>
  gather(variable, value, -date) |>
  ggplot() + geom_line(aes(x = date, y = value, color = variable, linetype = variable)) + 
  theme_minimal() +
  scale_color_manual(values = c(viridis(4)[3], viridis(4)[1], viridis(4)[1], viridis(4)[2])) +
  scale_linetype_manual(values = c("solid", "solid", "dashed", "solid")) +
  theme(legend.title = element_blank(),
        legend.position = c(0.8, 0.2)) +
  scale_x_date(breaks = nber_recessions$Peak,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = 20*2^seq(-7, 1, 1),
                labels = scales::dollar_format(accuracy = 0.1, suffix = "Tn")) + 
  geom_rect(data = nber_recessions |>
              filter(Peak > as.Date("1947-01-01")), 
            aes(xmin = Peak, xmax = Trough, ymin = 0, ymax = +Inf), 
            fill = 'grey', alpha = 0.5) + 
  xlab("") + ylab("U.S. Real GDP, $2012")

1980-

Code

fit_Q_1980 <- T10206_Q |>
  quarter_to_date() |>
  filter(date >= as.Date("1980-01-01")) |>
  filter(LineNumber == 1) |>
  select(date, `Real GDP` = DataValue) |>
  mutate(`Real GDP` = `Real GDP` / 1000000,
         datenum = year(date)+(month(date)-1)/12) |>
  filter(datenum <= 2007) %>%
  lm(log(`Real GDP`) ~ datenum, data = .) |>
  pluck("coefficients")

T10206_Q |>
  quarter_to_date() |>
  filter(date >= as.Date("1980-01-01")) |>
  filter(LineNumber == 1) |>
  select(date, `Real GDP` = DataValue) |>
  mutate(`Real GDP` = `Real GDP` / 1000000,
         datenum = year(date)+(month(date)-1)/12) |>
  mutate(`Trend to Today` = lm(log(`Real GDP`) ~ datenum) |> fitted() |> exp(),
         `Trend to 2008, extrapolated` = ifelse(datenum >= 1971, (fit_Q_1980[1] + fit_Q_1980[2] * datenum) |> exp(), NA),
         `Trend to 2008` = ifelse(datenum <= 1971, (fit_Q_1980[1] + fit_Q_1980[2] * datenum) |> exp(), NA)) |>
  group_by(date) |>
  select(-datenum) |>
  gather(variable, value, -date) |>
  ggplot() + geom_line(aes(x = date, y = value, color = variable, linetype = variable)) + 
  theme_minimal() +
  scale_color_manual(values = c(viridis(4)[3], viridis(4)[1], viridis(4)[1], viridis(4)[2])) +
  scale_linetype_manual(values = c("solid", "solid", "dashed", "solid")) +
  theme(legend.title = element_blank(),
        legend.position = c(0.8, 0.2)) +
  scale_x_date(breaks = nber_recessions$Peak,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(1, 100, 1),
                labels = scales::dollar_format(accuracy = 1, suffix = "Tn")) + 
  geom_rect(data = nber_recessions |>
              filter(Peak > as.Date("1980-01-01")), 
            aes(xmin = Peak, xmax = Trough, ymin = 0, ymax = +Inf), 
            fill = 'grey', alpha = 0.5) + 
  xlab("") + ylab("U.S. Real GDP, $2012")

U.S. Real GDP (Annual)

Code

fit <- T10206_A |>
  year_to_date() |>
  filter(LineNumber == 1) |>
  select(date, `Real GDP` = DataValue) |>
  mutate(`Real GDP` = `Real GDP` / 1000000,
         year = year(date)) |>
  filter(year <= 1971) %>%
  lm(log(`Real GDP`) ~ year, data = .) |>
  pluck("coefficients")

U.S. Real GDP Trends (1929-)

Log

Code

T10206_A |>
  year_to_date() |>
  filter(LineNumber == 1) |>
  select(date, `Real GDP` = DataValue) |>
  mutate(`Real GDP` = `Real GDP` / 1000000,
         year = year(date)) |>
  mutate(`Trend to Today` = lm(log(`Real GDP`) ~ year) |> fitted() |> exp(),
         `Trend to 1971, extrapolated` = ifelse(year >= 1971, (fit[1] + fit[2] * year) |> exp(), NA),
         `Trend to 1971` = ifelse(year <= 1971, (fit[1] + fit[2] * year) |> exp(), NA)) |>
  group_by(date) |>
  select(-year) |>
  gather(variable, value, -date) |>
  ggplot() + geom_line(aes(x = date, y = value, color = variable, linetype = variable)) + 
  theme_minimal() +
  scale_color_manual(values = c(viridis(4)[3], viridis(4)[1], viridis(4)[1], viridis(4)[2])) +
  scale_linetype_manual(values = c("solid", "solid", "dashed", "solid")) +
  theme(legend.title = element_blank(),
        legend.position = c(0.8, 0.2)) +
  scale_x_date(breaks = nber_recessions$Peak,
               labels = date_format("%Y")) +
  scale_y_log10(breaks = 20*2^seq(-7, 1, 1),
                labels = scales::dollar_format(accuracy = 0.1, suffix = "Tn")) + 
  geom_rect(data = nber_recessions |>
              filter(Peak > as.Date("1928-01-01")), 
            aes(xmin = Peak, xmax = Trough, ymin = 0, ymax = +Inf), 
            fill = 'grey', alpha = 0.5) + 
  xlab("") + ylab("U.S. Real GDP, $2012")

Linear

Code

T10206_A |>
  year_to_date() |>
  filter(LineNumber == 1) |>
  select(date, `Real GDP` = DataValue) |>
  mutate(`Real GDP` = `Real GDP` / 1000000,
         year = year(date)) |>
  mutate(`Trend to 2019 (g = 3.5%)` = lm(log(`Real GDP`) ~ year) |> fitted() |> exp(),
         `Trend to 1971, extrapolated` = ifelse(year >= 1971, (fit[1] + fit[2] * year) |> exp(), NA),
         `Trend to 1971 (g = 4.1%)` = ifelse(year <= 1971, (fit[1] + fit[2] * year) |> exp(), NA)) |>
  group_by(date) |>
  select(-year) |>
  gather(variable, value, -date) |>
  ggplot() + geom_line(aes(x = date, y = value, color = variable, linetype = variable)) + 
  theme_minimal() +
  scale_color_manual(values = c(viridis(4)[3], viridis(4)[1], viridis(4)[1], viridis(4)[2])) +
  scale_linetype_manual(values = c("solid", "solid", "dashed", "solid")) +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.8)) +
  scale_x_date(breaks = nber_recessions$Peak,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 20*2^seq(-4, 1, 1),
                labels = scales::dollar_format(accuracy = 0.1, suffix = "Tn")) + 
  geom_rect(data = nber_recessions |>
              filter(Peak > as.Date("1928-01-01")), 
            aes(xmin = Peak, xmax = Trough, ymin = 0, ymax = +Inf), 
            fill = 'grey', alpha = 0.5) + 
  xlab("") + ylab("U.S. Real GDP, $2012")

U.S. Real GDP Cycles (1929-)

Code

T10206_A |>
  year_to_date() |>
  filter(LineNumber == 1) |>
  select(date, `Real GDP` = DataValue) |>
  mutate(`Real GDP` = `Real GDP` / 1000000,
         year = year(date)) |>
  mutate(`Cycle, Detrending to 2019 (g = 3.5%)` = lm(log(`Real GDP`) ~ year) |> residuals() |> exp(),
         `Cycle, Detrending to 1971, extrapolated` = ifelse(year >= 1971, exp(log(`Real GDP`) - fit[1] - fit[2] * year), NA),
         `Cycle, Detrending to 1971 (g = 4.1%)` = ifelse(year <= 1971, exp(log(`Real GDP`) - fit[1] - fit[2] * year), NA)) |>
  group_by(date) |>
  select(-year, -`Real GDP`) |>
  gather(variable, value, -date) |>
  ggplot() + geom_line(aes(x = date, y = value, color = variable, linetype = variable)) + 
  theme_minimal() +
  scale_color_manual(values = c(viridis(4)[1],viridis(4)[1], viridis(4)[2])) +
  scale_linetype_manual(values = c("solid", "dashed", "solid")) +
  theme(legend.title = element_blank(),
        legend.position = c(0.7, 0.8)) +
  scale_x_date(breaks = nber_recessions$Peak,
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 2.25, 0.10),
                labels = scales::percent_format(accuracy = 1),
                limits = c(0.4, 1.55)) + 
  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) + 
  xlab("") + ylab("U.S. Real GDP, $2012")

1938, 1958, 1978, 1998, 2018 Table

Percent

Code

T10206_A |>
  year_to_date() |>
  mutate(year = year(date)) |>
  filter(year %in% c(1938, 1958, 1978, 1998, 2018)) |>
  group_by(year) |>
  mutate(value = round(100*DataValue/DataValue[1], 1)) |>
  ungroup() |>
  select(2, 3, 6, 7) |>
  spread(year, value) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Billions

Code

T10206_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 .}

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