Table 5.1. Saving and Investment by Sector (A) (Q)
Data - BEA
Info
Data on US macro
LAST_COMPILE
LAST_COMPILE |
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2025-02-12 |
Last
date | Nobs |
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2024-12-31 | 35 |
Layout
- NIPA Website. html
Gross saving, Net saving, CCA
Code
%>%
T50100 filter(FREQ == "A") %>%
select(-FREQ) %>%
mutate(table = "T50100") %>%
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, 2, 13) & table == "T50100") %>%
ggplot(.) + theme_minimal() +
geom_line(aes(x = date, y = value, color = LineDescription)) +
theme(legend.title = element_blank(),
legend.position = c(0.5, 0.15)) +
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) +
scale_x_date(breaks = seq(1930, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
ylab("% of GDP") + xlab("") +
scale_y_continuous(breaks = 0.01*seq(-100, 100, 2),
labels = scales::percent_format(accuracy = 1))
Gross saving, Gross investment
Code
%>% filter(FREQ == "A") %>% select(-FREQ) %>%
T50100 mutate(table = "T50100") %>%
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, 21) & table == "T50100") %>%
ggplot(.) + theme_minimal() + ylab("% of GDP") + xlab("") +
geom_line(aes(x = date, y = value, color = LineDescription)) +
theme(legend.title = element_blank(),
legend.position = c(0.5, 0.15)) +
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) +
scale_x_date(breaks = seq(1930, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-100, 100, 2),
labels = scales::percent_format(accuracy = 1))
Corporate saving, government saving, personal saving
Annual
Code
%>% filter(FREQ == "A") %>% select(-FREQ) %>%
T50100 mutate(table = "T50100") %>%
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(9, 4, 10) & table == "T50100") %>%
ggplot(.) + theme_minimal() +
geom_line(aes(x = date, y = value, color = LineDescription)) +
theme(legend.title = element_blank(),
legend.position = c(0.5, 0.15)) +
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) +
scale_x_date(breaks = seq(1930, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
ylab("% of GDP") + xlab("") +
scale_y_continuous(breaks = 0.01*seq(-100, 100, 2),
labels = scales::percent_format(accuracy = 1))
Quarterly
Code
%>% filter(FREQ == "Q") %>% select(-FREQ) %>%
T50100 mutate(table = "T50100") %>%
bind_rows(T10105_Q %>%
mutate(table = "T10105")) %>%
%>%
quarter_to_date group_by(date) %>%
mutate(value = DataValue/DataValue[LineNumber == 1 & table == "T10105"]) %>%
filter(LineNumber %in% c(9, 4, 10) & table == "T50100") %>%
ggplot(.) + theme_minimal() +
geom_line(aes(x = date, y = value, color = LineDescription)) +
theme(legend.title = element_blank(),
legend.position = c(0.2, 0.15)) +
geom_rect(data = nber_recessions %>%
filter(Peak > as.Date("1947-01-01")),
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,
labels = date_format("%Y")) +
ylab("Net Saving (% of GDP)") + xlab("") +
scale_y_continuous(breaks = 0.01*seq(-100, 100, 2),
labels = scales::percent_format(accuracy = 1))
Undistributed profits, government saving, personal saving
Annual
Code
%>% filter(FREQ == "A") %>% select(-FREQ) %>%
T50100 mutate(table = "T50100") %>%
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(9, 5, 10) & table == "T50100") %>%
ggplot(.) + theme_minimal() +
geom_line(aes(x = date, y = value, color = LineDescription)) +
theme(legend.title = element_blank(),
legend.position = c(0.5, 0.15)) +
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) +
scale_x_date(breaks = seq(1930, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
ylab("% of GDP") + xlab("") +
scale_y_continuous(breaks = 0.01*seq(-100, 100, 2),
labels = scales::percent_format(accuracy = 1))
Quarterly
Code
%>% filter(FREQ == "Q") %>% select(-FREQ) %>%
T50100 mutate(table = "T50100") %>%
bind_rows(T10105_Q %>%
mutate(table = "T10105")) %>%
%>%
quarter_to_date group_by(date) %>%
mutate(value = DataValue/DataValue[LineNumber == 1 & table == "T10105"]) %>%
filter(LineNumber %in% c(9, 5, 10) & table == "T50100") %>%
ggplot(.) + theme_minimal() +
geom_line(aes(x = date, y = value, color = LineDescription)) +
theme(legend.title = element_blank(),
legend.position = c(0.5, 0.15)) +
geom_rect(data = nber_recessions %>%
filter(Peak > as.Date("1947-01-01")),
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,
labels = date_format("%Y")) +
ylab("% of GDP") + xlab("") +
scale_y_continuous(breaks = 0.01*seq(-100, 100, 2),
labels = scales::percent_format(accuracy = 1))
Main Items - 1938, 1958, 1978, 1998, 2018
Percent of GDP
Code
%>% filter(FREQ == "A") %>% select(-FREQ) %>%
T50100 mutate(table = "T50100") %>%
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, 2008, 2018)) %>%
group_by(year) %>%
mutate(value = round(100*DataValue/DataValue[LineNumber == 1 & table == "T10105"], 1)) %>%
filter(table == "T50100") %>%
%>%
ungroup select(2, 3, 7, 8) %>%
spread(year, value) %>%
slice(c(1, 2, 13, 21, 28, 35, 42)) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
1938, 1958, 1978, 1998, 2018 Full Table
Percent of GDP
Code
%>% filter(FREQ == "A") %>% select(-FREQ) %>%
T50100 mutate(table = "T50100") %>%
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 == "T50100") %>%
%>%
ungroup select(2, 3, 7, 8) %>%
spread(year, value) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
Billions
Code
%>% filter(FREQ == "A") %>% select(-FREQ) %>%
T50100 %>%
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 .} {