Table 2.1. Current-Cost Net Stock of Private Fixed Assets, Equipment, Structures, and Intellectual Property Products by Type (A) - FAAt201

Data - BEA

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bea FAAt201 Table 2.1. Current-Cost Net Stock of Private Fixed Assets, Equipment, Structures, and Intellectual Property Products by Type (A) - FAAt201 2024-02-11 2024-03-13

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  • Fixed Assets Website. html

Ex 1: Equipment

Decomposition of Equipment (% of GDP)

Code
FAAt201 %>%
  year_to_date %>%
  filter(LineNumber %in% c(4, 11, 18, 26)) %>%
  rename(variable = LineDescription) %>%
  left_join(gdp_adjustment, by = "date") %>%
  mutate(DataValue = `Real GDP / Real GDP Trend (Log Linear)` * DataValue / GDP) %>%
  ggplot + geom_line(aes(x = date, y = DataValue, 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")) + 
  scale_y_continuous(breaks = 0.01*seq(0, 160, 2),
                     labels = scales::percent_format(accuracy = 1)) + 
  theme(legend.position = c(0.25, 0.85),
        legend.title = element_blank(),
        legend.text = element_text(size = 8),
        legend.key.size = unit(0.9, 'lines'))

Decomposition of Structures

Code
FAAt201 %>%
  year_to_date %>%
  filter(LineNumber %in% c(36, 67, 68, 74)) %>%
  rename(variable = LineDescription) %>%
  left_join(gdp_adjustment, by = "date") %>%
  mutate(DataValue = `Real GDP / Real GDP Trend (Log Linear)` * DataValue / GDP) %>%
  ggplot + geom_line(aes(x = date, y = DataValue, 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")) + 
  scale_y_continuous(breaks = 0.01*seq(0, 160, 10),
                     labels = scales::percent_format(accuracy = 1)) + 
  theme(legend.position = c(0.25, 0.35),
        legend.title = element_blank(),
        legend.text = element_text(size = 8),
        legend.key.size = unit(0.9, 'lines'))