Table 2.1. Personal Income and Its Disposition (A) (Q) - T20100

Data - BEA

~/data/bea/NIPA.html

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LAST_DOWNLOAD

file	LAST_DOWNLOAD
T20100_Q	2022-10-09
T20100_A	2022-10-09

LAST_COMPILE

LAST_COMPILE
2024-02-11

Last

date	Nobs
2022-06-30	42

Layout

• NIPA Website. html

Comments

• Compensation of employees (70%) includes 56% of Wages and salaries:
  • Supplements to wages and salaries (14%)
  • Supplements include employer contributions (employee pension + insurance + government insurance)
• In Wages and salaries = 56.5%:
  • 8.9% = Government (acyclical)
  • 47.6% = Private (cyclical)

• Supplements to wages and salaries (14%) = acyclical.

• Dividends are only very mildly cyclical?

• Rental income (5% only):
  • Net of interest (not like in France?)
  • Net of depreciation
• Personal income receipts on assets:
  • Includes mortgage interest which was not included in rents.
  • Proof: Personal interest income and rental income of persons are NEGATIVELY CORRELATED.
• Disposable personal/household income:
  • 75% in USA.
  • Much higher in France?

Disposable personal income / Personal income as a % of GDP

T20100_A %>%
  mutate(table = "T20100") %>%
  bind_rows(T10105_A %>%
              mutate(table = "T10105")) %>%
  year_to_date %>%
  arrange(date, LineNumber) %>%
  group_by(date) %>%
  mutate(value = DataValue/DataValue[LineDescription == "Gross domestic product"]) %>%
  filter(LineNumber %in% c(27, 1),
         table == "T20100") %>%
  ggplot(.) + theme_minimal() + 
  geom_line(aes(x = date, y = value, color = LineDescription, linetype = LineDescription)) +
  theme(legend.title = element_blank(),
        legend.position = c(0.3, 0.9)) +
  geom_rect(data = nber_recessions %>%
              filter(Peak > as.Date("1929-01-01")), 
            aes(xmin = Peak, xmax = Trough, ymin = -Inf, ymax = +Inf), 
            fill = 'grey', alpha = 0.5) + 
  scale_x_date(breaks = seq(1930, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  ylab("% of GDP") + xlab("") +
  scale_color_manual(values = viridis(5)[1:4]) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 1),
                     labels = scales::percent_format(accuracy = 1))

Rental income of persons with capital consumption adjustment

T20100_A %>%
  year_to_date %>%
  arrange(date, LineNumber) %>%
  group_by(date) %>%
  mutate(value = DataValue/DataValue[LineNumber == 27]) %>%
  filter(LineNumber %in% c(12, 13, 14, 15)) %>%
  ggplot(.) + theme_minimal() + 
  geom_line(aes(x = date, y = value, color = LineDescription, linetype = LineDescription)) +
  theme(legend.title = element_blank(),
        legend.position = c(0.3, 0.9)) +
  geom_rect(data = nber_recessions %>%
              filter(Peak > as.Date("1929-01-01")), 
            aes(xmin = Peak, xmax = Trough, ymin = -Inf, ymax = +Inf), 
            fill = 'grey', alpha = 0.5) + 
  scale_x_date(breaks = seq(1930, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  ylab("% of Disposable personal income") + xlab("") +
  scale_color_manual(values = viridis(5)[1:4]) +
  scale_y_continuous(breaks = 0.01*seq(0, 25, 1),
                     labels = scales::percent_format(accuracy = 1))

Taxes

T20100_A %>%
  year_to_date %>%
  group_by(date) %>%
  mutate(value = DataValue/DataValue[LineNumber == 27]) %>%
  filter(LineNumber %in% c(26, 6)) %>%
  ggplot(.) + theme_minimal() + 
  geom_line(aes(x = date, y = value, color = LineDescription, linetype = LineDescription)) +
  theme(legend.title = element_blank(),
        legend.position = c(0.75, 0.2)) +
  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) + 
  scale_x_date(breaks = seq(1925, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  ylab("% of Disposable personal income") + xlab("") +
  scale_color_manual(values = viridis(5)[1:4]) +
  scale_y_continuous(breaks = 0.01*seq(0, 90, 2),
                     labels = scales::percent_format(accuracy = 1))

Wages and Salaries / Private VS Government

T20100_A %>%
  year_to_date %>%
  group_by(date) %>%
  mutate(value = DataValue/DataValue[LineNumber == 27]) %>%
  filter(LineNumber %in% c(3, 4, 5)) %>%
  ggplot(.) + theme_minimal() + 
  geom_line(aes(x = date, y = value, color = LineDescription, linetype = LineDescription)) +
  theme(legend.title = element_blank(),
        legend.position = c(0.45, 0.5)) +
  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) + 
  scale_x_date(breaks = seq(1925, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  ylab("% of Disposable personal income") + xlab("") +
  scale_color_manual(values = viridis(5)[1:4]) +
  scale_y_continuous(breaks = 0.01*seq(0, 90, 10),
                     labels = scales::percent_format(accuracy = 1))

Compensation of Employees

T20100_A %>%
  year_to_date %>%
  group_by(date) %>%
  mutate(value = DataValue/DataValue[LineNumber == 27]) %>%
  filter(LineNumber %in% c(2, 3, 6, 9)) %>%
  ggplot(.) + theme_minimal() + 
  geom_line(aes(x = date, y = value, color = LineDescription, linetype = LineDescription)) +
  theme(legend.title = element_blank(),
        legend.position = c(0.45, 0.5)) +
  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) + 
  scale_x_date(breaks = seq(1925, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  ylab("% of Disposable personal income") + xlab("") +
  scale_color_manual(values = viridis(5)[1:4]) +
  scale_y_continuous(breaks = 0.01*seq(0, 90, 10),
                     labels = scales::percent_format(accuracy = 1))

Government

T20100_A %>%
  year_to_date %>%
  group_by(date) %>%
  mutate(value = DataValue/DataValue[LineNumber == 27]) %>%
  filter(LineNumber %in% c(25, 17, 26)) %>%
  ggplot(.) + theme_minimal() + 
  geom_line(aes(x = date, y = value, color = LineDescription, linetype = LineDescription)) +
  theme(legend.title = element_blank(),
        legend.position = c(0.35, 0.9)) +
  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) + 
  scale_x_date(breaks = seq(1925, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  ylab("% of Disposable personal income") + xlab("") +
  scale_color_manual(values = viridis(5)[1:4]) +
  scale_y_continuous(breaks = 0.01*seq(0, 90, 2),
                     labels = scales::percent_format(accuracy = 1))

Government social benefits to persons

T20100_A %>%
  year_to_date %>%
  group_by(date) %>%
  mutate(value = DataValue/DataValue[LineNumber == 27]) %>%
  filter(LineNumber %in% c(18:23)) %>%
  ggplot(.) + theme_minimal() + 
  geom_line(aes(x = date, y = value, color = LineDescription, linetype = LineDescription)) +
  theme(legend.title = element_blank(),
        legend.position = c(0.15, 0.8)) +
  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) + 
  scale_x_date(breaks = seq(1925, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  ylab("% of Disposable personal income") + xlab("") +
  scale_color_manual(values = viridis(7)[1:6]) +
  scale_y_continuous(breaks = 0.01*seq(0, 90, 1),
                     labels = scales::percent_format(accuracy = 1))

1938, 1958, 1978, 1998, 2018 Table

% of Personal income

T20100_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[LineNumber == 1], 1)) %>%
  ungroup %>%
  select(2, 3, 6, 7) %>%
  spread(year, value) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

% of Personal Disposable income

T20100_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[LineNumber == 27], 1)) %>%
  ungroup %>%
  select(2, 3, 6, 7) %>%
  spread(year, value) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Billions

T20100_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 .}