source | dataset | Title | Download | Compile |
---|---|---|---|---|
fred | gdp | Gross Domestic Product | 2024-12-22 | [2024-11-21] |
eurostat | nama_10_a10 | Gross value added and income by A*10 industry breakdowns | 2024-10-08 | [2024-11-23] |
eurostat | nama_10_a10_e | Employment by A*10 industry breakdowns | 2024-11-23 | [2024-11-23] |
eurostat | nama_10_gdp | GDP and main components (output, expenditure and income) | 2024-12-21 | [2024-12-21] |
eurostat | nama_10_lp_ulc | Labour productivity and unit labour costs | 2024-10-08 | [2024-11-23] |
eurostat | namq_10_a10 | Gross value added and income A*10 industry breakdowns | 2024-12-21 | [2024-12-21] |
eurostat | namq_10_a10_e | Employment A*10 industry breakdowns | 2024-12-21 | [2024-12-21] |
eurostat | namq_10_gdp | GDP and main components (output, expenditure and income) | 2024-12-21 | [2024-12-21] |
eurostat | namq_10_lp_ulc | Labour productivity and unit labour costs | 2024-11-04 | [2024-11-23] |
eurostat | namq_10_pc | Main GDP aggregates per capita | 2024-11-21 | [2024-11-23] |
eurostat | nasa_10_nf_tr | Non-financial transactions | 2024-12-14 | [2024-12-14] |
eurostat | nasq_10_nf_tr | Non-financial transactions | 2024-10-09 | [2024-11-23] |
oecd | QNA | Quarterly National Accounts | 2024-12-21 | [2024-06-06] |
oecd | SNA_TABLE1 | Gross domestic product (GDP) | 2024-12-21 | [2024-12-21] |
oecd | SNA_TABLE14A | Non-financial accounts by sectors | 2024-06-30 | [2024-09-15] |
oecd | SNA_TABLE2 | Disposable income and net lending - net borrowing | 2024-04-11 | [2024-07-01] |
oecd | SNA_TABLE6A | Value added and its components by activity, ISIC rev4 | 2024-06-30 | [2024-07-01] |
wdi | NE.RSB.GNFS.ZS | External balance on goods and services (% of GDP) | 2024-09-18 | [2024-09-18] |
wdi | NY.GDP.MKTP.CD | GDP (current USD) | 2024-09-26 | [2024-09-18] |
wdi | NY.GDP.MKTP.PP.CD | GDP, PPP (current international D) | 2024-09-18 | [2024-09-18] |
wdi | NY.GDP.PCAP.CD | GDP per capita (current USD) | 2024-12-21 | [2024-12-16] |
wdi | NY.GDP.PCAP.KD | GDP per capita (constant 2015 USD) | 2024-09-18 | [2024-09-18] |
wdi | NY.GDP.PCAP.PP.CD | GDP per capita, PPP (current international D) | 2024-12-21 | [2024-12-21] |
wdi | NY.GDP.PCAP.PP.KD | GDP per capita, PPP (constant 2011 international D) | 2024-12-21 | [2024-12-21] |
Gross Domestic Product
Data - Fred
Info
LAST_COMPILE
LAST_COMPILE |
---|
2024-12-22 |
Last
date | Nobs |
---|---|
2034-10-01 | 1 |
variable
variable | Variable | Nobs |
---|---|---|
DSPI | Disposable Personal Income | 791 |
PCE | Personal Consumption Expenditures | 791 |
PCEDG | Personal Consumption Expenditures: Durable Goods | 791 |
TCU | Capacity Utilization: Total Index | 695 |
GDPPOT | Real Potential Gross Domestic Product | 344 |
PCESV | Personal Consumption Expenditures: Services | 315 |
PCND | Personal Consumption Expenditures: Nondurable Goods | 315 |
A939RX0Q048SBEA | Real gross domestic product per capita | 311 |
GDI | Gross Domestic Income | 311 |
GDPC1 | Real Gross Domestic Product | 311 |
DHSGRC0 | Personal Consumption Expenditures by Type of Product: Services: Household Consumption Expenditures: Housing | 263 |
GDINOS | Gross Domestic Income: Net Operating Surplus | 263 |
USSTHPI | All-Transactions House Price Index for the United States | 199 |
MDSP | Mortgage Debt Service Payments as a Percent of Disposable Personal Income | 179 |
FYFSD | Federal Surplus or Deficit [-] | 124 |
DCAFRC1A027NBEA | Personal consumption expenditures: Clothing, footwear, and related services | 95 |
DOWNRC1A027NBEA | Personal consumption expenditures: Services: Housing: Imputed rental of owner-occupied nonfarm housing | 95 |
GDPA | Gross Domestic Product | 95 |
GDPCA | Real Gross Domestic Product | 95 |
HDTGPDUSQ163N | Household Debt to GDP for United States | 77 |
USPCEHLTHCARE | Personal Consumption Expenditures: Services: Health Care for United States | 27 |
Real GDP
Annual
Linear
Code
<- gdp %>%
plot_linear filter(variable == "GDPCA") %>%
+ geom_line(aes(x = date, y = value)) +
ggplot scale_y_continuous(breaks = seq(0, 100000, 2000),
labels = dollar_format()) +
scale_x_date(breaks = seq(1900, 2100, 20) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
theme_minimal() + xlab("") + ylab("Real GDP")
plot_linear
Log
Code
<- plot_linear +
plot_log scale_y_log10(breaks = seq(0, 100000, 2000),
labels = dollar_format(acc = 1))
plot_log
Linear, Log
Code
ggarrange(plot_linear + ggtitle("Linear Scale"), plot_log + ylab("") + ggtitle("Log Scale"))
Quarterly
Linear
Code
<- gdp %>%
plot_linear filter(variable == "GDPC1") %>%
+ geom_line(aes(x = date, y = value)) +
ggplot scale_y_continuous(breaks = seq(0, 100000, 2000),
labels = dollar_format()) +
scale_x_date(breaks = seq(1950, 2100, 10) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
theme_minimal() + xlab("") + ylab("Real GDP")
plot_linear
Log
Code
<- plot_linear +
plot_log scale_y_log10(breaks = seq(0, 100000, 2000),
labels = dollar_format(acc = 1))
plot_log
Linear, Log
Code
ggarrange(plot_linear, plot_log + ylab(""))
Real GDP per capita
Linear
Code
<- gdp %>%
plot_linear filter(variable == "A939RX0Q048SBEA") %>%
+ geom_line(aes(x = date, y = value)) +
ggplot scale_y_continuous(breaks = seq(0, 100000, 10000),
labels = dollar_format()) +
scale_x_date(breaks = seq(1950, 2100, 10) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
theme_minimal() + xlab("") + ylab("Real GDP per capita")
plot_linear
Log
Code
<- plot_linear +
plot_log scale_y_log10(breaks = seq(0, 100000, 10000),
labels = dollar_format(acc = 1))
plot_log
Linear, Log
Code
ggarrange(plot_linear, plot_log + ylab(""))
Output Gap (%)
1945-2020
Code
%>%
gdp spread(variable, value) %>%
mutate(output_gap = (GDPC1 - GDPPOT)/GDPPOT) %>%
select(date, output_gap) %>%
%>%
na.omit ggplot(.) + xlab("") + ylab("Output Gap (% of Potential Output)") +
theme_minimal() +
geom_line(aes(x = date, y = output_gap)) +
geom_rect(data = nber_recessions %>%
filter(Peak > as.Date("1948-01-01")),
aes(xmin = Peak, xmax = Trough, ymin = -Inf, ymax = +Inf),
fill = 'grey', alpha = 0.5) +
theme(legend.title = element_blank(),
legend.position = c(0.4, 0.8)) +
scale_x_date(breaks = as.Date(paste0(seq(1920, 2020, 5), "-01-01")),
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-20, 20, 1),
labels = scales::percent_format(accuracy = 1))
1965-2020
Code
%>%
gdp filter(date >= as.Date("1965-01-01")) %>%
spread(variable, value) %>%
mutate(output_gap = (GDPC1 - GDPPOT)/GDPPOT) %>%
select(date, output_gap) %>%
%>%
na.omit ggplot(.) + xlab("") + ylab("Output Gap (% of Potential Output)") +
theme_minimal() +
geom_line(aes(x = date, y = output_gap)) +
geom_rect(data = nber_recessions %>%
filter(Peak > as.Date("1965-01-01")),
aes(xmin = Peak, xmax = Trough, ymin = -Inf, ymax = +Inf),
fill = 'grey', alpha = 0.5) +
theme(legend.title = element_blank(),
legend.position = c(0.4, 0.8)) +
scale_x_date(breaks = as.Date(paste0(seq(1920, 2025, 5), "-01-01")),
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(-20, 20, 1),
labels = scales::percent_format(accuracy = 1))
Deficits
All
(ref:surplus-gdp-1929-2019) Budget Surplus, 1929-2019 (% of GDP).
Code
<- US_presidents %>%
US_presidents_extract filter(start >= as.Date("1929-01-01"))
%>%
gdp filter(variable %in% c("FYFSD", "GDPA")) %>%
mutate(date = date %>% year,
date = as.Date(paste0(date, "-12-31"))) %>%
spread(variable, value) %>%
mutate(value = FYFSD / (GDPA*1000)) %>%
filter(date >= as.Date("1929-01-01")) %>%
ggplot(.) +
geom_line(aes(x = date, y = value)) + theme_minimal() +
theme(legend.title = element_blank(),
legend.position = c(0.3, 0.8)) +
scale_x_date(breaks = as.Date(US_presidents_extract$start),
labels = date_format("%Y")) +
geom_vline(aes(xintercept = as.numeric(start)),
data = US_presidents_extract,
colour = "grey50", alpha = 0.5) +
geom_rect(aes(xmin = start, xmax = end, fill = party),
ymin = -Inf, ymax = Inf, alpha = 0.1, data = US_presidents_extract) +
geom_text(aes(x = start, y = new, label = name),
data = US_presidents_extract %>% mutate(new = -0.27 + 0.01 * (1:n() %% 2)),
size = 2.5, vjust = 0, hjust = 0, nudge_x = 50) +
# scale_fill_manual(values = viridis(3)[2:1]) +
scale_fill_manual(values = c("white", "grey")) +
xlab("") + ylab("Budget Surplus (% of GDP)") +
guides(color = guide_legend("party"), fill = FALSE) +
scale_y_continuous(breaks = 0.01*seq(-30, 6, 2),
labels = scales::percent_format(accuracy = 1),
limits = c(-0.27, 0.05)) +
geom_hline(yintercept = 0, linetype = "dashed", color = viridis(3)[2])
1945-2021
Code
%>%
gdp filter(variable %in% c("FYFSD", "GDPA")) %>%
mutate(date = date %>% year,
date = as.Date(paste0(date, "-12-31"))) %>%
spread(variable, value) %>%
mutate(value = FYFSD / (GDPA*1000)) %>%
ggplot(.) +
geom_line(aes(x = date, y = value)) + theme_minimal() +
theme(legend.title = element_blank(),
legend.position = c(0.3, 0.8)) +
scale_x_date(breaks = as.Date(US_presidents$start),
labels = date_format("%Y"),
limits = c(as.Date("1929-01-01"), as.Date("2023-04-01"))) +
geom_vline(aes(xintercept = as.numeric(start)),
data = US_presidents,
colour = "grey50", alpha = 0.5) +
geom_rect(aes(xmin = start, xmax = end, fill = party),
ymin = -Inf, ymax = Inf, alpha = 0.1, data = US_presidents) +
geom_text(aes(x = start, y = new, label = name),
data = US_presidents %>% mutate(new = -0.27 + 0.01 * (1:n() %% 2)),
size = 2.5, vjust = 0, hjust = 0, nudge_x = 50) +
# scale_fill_manual(values = viridis(3)[2:1]) +
scale_fill_manual(values = c("white", "grey")) +
xlab("") + ylab("Budget Surplus (% of GDP)") +
guides(color = guide_legend("party"), fill = FALSE) +
scale_y_continuous(breaks = 0.01*seq(-30, 6, 2),
labels = scales::percent_format(accuracy = 1),
limits = c(-0.27, 0.05)) +
geom_hline(yintercept = 0, linetype = "dashed", color = viridis(3)[2])
Financial Crisis Macroeconomic Aggregates
Household Debt to GDP (% of GDP)
(ref:HDTGPDUSQ163N) Mortgage Debt Service Payments, in Billions (2000-2012)
Code
%>%
gdp filter(variable == "HDTGPDUSQ163N") %>%
spread(variable, value) %>%
%>%
na.omit mutate(value = HDTGPDUSQ163N / 100) %>%
select(date, value) %>%
filter(date >= as.Date("2000-01-01"),
<= as.Date("2012-01-01")) %>%
date ggplot(.) + geom_line(aes(x = date, y = value)) + theme_minimal() +
scale_x_date(breaks = seq(1870, 2020, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01* seq(10, 120, 1),
labels = percent_format(accuracy = 1)) +
xlab("") + ylab("Household Debt (% of GDP)") +
geom_vline(xintercept = as.Date("2008-09-15"), linetype = "dashed", color = viridis(3)[2]) +
geom_rect(data = data_frame(start = as.Date("2004-06-01"),
end = as.Date("2007-08-01")),
aes(xmin = start, xmax = end, ymin = -Inf, ymax = +Inf),
fill = viridis(4)[4], alpha = 0.2) +
geom_vline(xintercept = as.Date("2004-06-01"), linetype = "dashed", color = viridis(4)[4]) +
geom_vline(xintercept = as.Date("2007-08-01"), linetype = "dashed", color = viridis(4)[4])
Mortgage Debt Service Payments (in Billion Dollars)
(ref:MDSP-DSPI) Mortgage Debt Service Payments, in Billions (2000-2012)
Code
%>%
gdp filter(variable %in% c("DSPI", "MDSP")) %>%
spread(variable, value) %>%
%>%
na.omit mutate(value = MDSP * DSPI / 100) %>%
select(date, value) %>%
filter(date >= as.Date("2000-01-01"),
<= as.Date("2012-01-01")) %>%
date ggplot(.) + geom_line(aes(x = date, y = value)) + theme_minimal() +
scale_x_date(breaks = seq(1870, 2020, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(100, 16000, 50),
labels = dollar_format(suffix = "Bn", prefix = "$")) +
xlab("") + ylab("Mortgage Debt Service Payments") +
geom_vline(xintercept = as.Date("2008-09-15"), linetype = "dashed", color = viridis(3)[2]) +
geom_rect(data = data_frame(start = as.Date("2004-06-01"),
end = as.Date("2007-08-01")),
aes(xmin = start, xmax = end, ymin = -Inf, ymax = +Inf),
fill = viridis(4)[4], alpha = 0.2) +
geom_vline(xintercept = as.Date("2004-06-01"), linetype = "dashed", color = viridis(4)[4]) +
geom_vline(xintercept = as.Date("2007-08-01"), linetype = "dashed", color = viridis(4)[4])
Mortgage Debt Service Payments (% Disposable Personal Income)
(ref:MDSP) Mortgage Debt Service Payments (2000-2019)
Code
%>%
gdp filter(variable %in% c("MDSP")) %>%
filter(date >= as.Date("2000-01-01"),
<= as.Date("2012-01-01")) %>%
date mutate(value = value / 100) %>%
ggplot(.) + geom_line(aes(x = date, y = value)) + theme_minimal() +
scale_x_date(breaks = seq(1870, 2020, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = 0.01*seq(0, 15, 0.2),
labels = scales::percent_format(accuracy = 0.1)) +
xlab("") + ylab("% of Disposable Income") +
geom_vline(xintercept = as.Date("2008-09-15"), linetype = "dashed", color = viridis(3)[2]) +
geom_rect(data = data_frame(start = as.Date("2004-06-01"),
end = as.Date("2007-08-01")),
aes(xmin = start, xmax = end, ymin = -Inf, ymax = +Inf),
fill = viridis(4)[4], alpha = 0.2) +
geom_vline(xintercept = as.Date("2004-06-01"), linetype = "dashed", color = viridis(4)[4]) +
geom_vline(xintercept = as.Date("2007-08-01"), linetype = "dashed", color = viridis(4)[4])
House Prices
(ref:USSTHPI) House Prices (Index)
Code
%>%
gdp filter(variable %in% c("USSTHPI")) %>%
filter(date >= as.Date("2000-01-01"),
<= as.Date("2010-01-01")) %>%
date ggplot(.) + geom_line(aes(x = date, y = value)) + theme_minimal() +
scale_x_date(breaks = seq(1870, 2020, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(0, 600, 10)) +
xlab("") + ylab("House Price Index") +
geom_vline(xintercept = as.Date("2008-09-15"), linetype = "dashed", color = viridis(3)[2]) +
geom_rect(data = data_frame(start = as.Date("2004-06-01"),
end = as.Date("2007-08-01")),
aes(xmin = start, xmax = end, ymin = -Inf, ymax = +Inf),
fill = viridis(4)[4], alpha = 0.2) +
geom_vline(xintercept = as.Date("2004-06-01"), linetype = "dashed", color = viridis(4)[4]) +
geom_vline(xintercept = as.Date("2007-08-01"), linetype = "dashed", color = viridis(4)[4])
Disposable Income
(ref:DSPI-3) Disposable Income (2000-2019)
Code
%>%
gdp filter(variable %in% c("DSPI")) %>%
filter(date >= as.Date("2004-01-01"),
<= as.Date("2010-01-01")) %>%
date ggplot(.) + geom_line(aes(x = date, y = value)) + theme_minimal() +
scale_x_date(breaks = seq(1870, 2020, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(6000, 16000, 500),
labels = dollar_format(suffix = "Bn", prefix = "$")) +
xlab("") + ylab("Disposable Income") +
geom_vline(xintercept = as.Date("2008-09-15"), linetype = "dashed", color = viridis(3)[2]) +
geom_rect(data = data_frame(start = as.Date("2004-06-01"),
end = as.Date("2007-08-01")),
aes(xmin = start, xmax = end, ymin = -Inf, ymax = +Inf),
fill = viridis(4)[4], alpha = 0.2) +
geom_vline(xintercept = as.Date("2004-06-01"), linetype = "dashed", color = viridis(4)[4]) +
geom_vline(xintercept = as.Date("2007-08-01"), linetype = "dashed", color = viridis(4)[4])
Consumption
Code
%>%
gdp filter(variable %in% c("PCE")) %>%
filter(date >= as.Date("2006-01-01"),
<= as.Date("2020-01-01")) %>%
date ggplot(.) + geom_line(aes(x = date, y = value)) + theme_minimal() +
scale_x_date(breaks = seq(1870, 2020, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(8000, 20000, 500),
labels = dollar_format(suffix = "Bn", prefix = "$")) +
xlab("") + ylab("Consumption") +
geom_vline(xintercept = as.Date("2008-09-15"), linetype = "dashed", color = viridis(3)[2])
Durable, Non-Durable, Services
(ref:PCND-06-20) Non-durable Expenditures
Code
%>%
gdp filter(variable %in% c("PCND")) %>%
filter(date >= as.Date("2006-01-01"),
<= as.Date("2020-01-01")) %>%
date ggplot(.) + geom_line(aes(x = date, y = value)) + theme_minimal() +
scale_x_date(breaks = seq(1870, 2020, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(0, 20000, 100),
labels = dollar_format(suffix = "Bn", prefix = "$")) +
xlab("") + ylab("Non-durable Expenditures") +
geom_vline(xintercept = as.Date("2008-09-15"), linetype = "dashed", color = viridis(3)[2])
Durable Expenditures
(ref:PCEDG-06-20) Durable Expenditures
Code
%>%
gdp filter(variable %in% c("PCEDG")) %>%
filter(date >= as.Date("2001-01-01"),
<= as.Date("2015-01-01")) %>%
date ggplot(.) + geom_line(aes(x = date, y = value)) + theme_minimal() +
scale_x_date(breaks = seq(1870, 2020, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(0, 20000, 50),
labels = dollar_format(suffix = "Bn", prefix = "$")) +
xlab("") + ylab("Durable Expenditures") +
geom_vline(xintercept = as.Date("2008-09-15"), linetype = "dashed", color = viridis(3)[2])
Service Expenditures
(ref:PCESV-06-20) Service Expenditures
Code
%>%
gdp filter(variable %in% c("PCESV")) %>%
filter(date >= as.Date("2006-01-01"),
<= as.Date("2020-01-01")) %>%
date ggplot(.) + geom_line(aes(x = date, y = value)) + theme_minimal() +
scale_x_date(breaks = seq(1870, 2020, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = 1000*seq(0, 20, 0.5),
labels = dollar_format(suffix = "Bn", prefix = "$")) +
xlab("") + ylab("Service Expenditures") +
geom_vline(xintercept = as.Date("2008-09-15"), linetype = "dashed", color = viridis(3)[2])
Imputed rental
(ref:DOWNRC1A027NBEA) Imputed rental
Code
%>%
gdp filter(variable %in% c("DOWNRC1A027NBEA")) %>%
filter(date >= as.Date("2006-01-01"),
<= as.Date("2020-01-01")) %>%
date ggplot(.) + geom_line(aes(x = date, y = value)) + theme_minimal() +
scale_x_date(breaks = seq(1870, 2020, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(0, 20000, 100),
labels = dollar_format(suffix = "Bn", prefix = "$")) +
xlab("") + ylab("Imputed rental") +
geom_vline(xintercept = as.Date("2008-09-15"), linetype = "dashed", color = viridis(3)[2])
Health Care
(ref:USPCEHLTHCARE) Health Care
Code
%>%
gdp filter(variable %in% c("USPCEHLTHCARE")) %>%
filter(date >= as.Date("2006-01-01"),
<= as.Date("2020-01-01")) %>%
date mutate(value = value / 10^3) %>%
ggplot(.) + geom_line(aes(x = date, y = value)) + theme_minimal() +
scale_x_date(breaks = seq(1870, 2020, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(0, 20000, 100),
labels = dollar_format(suffix = "Bn", prefix = "$")) +
xlab("") + ylab("Imputed rental") +
geom_vline(xintercept = as.Date("2008-09-15"), linetype = "dashed", color = viridis(3)[2])
Housing
(ref:DHSGRC0-06-20) Housing
Code
%>%
gdp filter(variable %in% c("DHSGRC0")) %>%
filter(date >= as.Date("2006-01-01"),
<= as.Date("2020-01-01")) %>%
date mutate(value = value / 10^3) %>%
ggplot(.) + geom_line(aes(x = date, y = value)) + theme_minimal() +
scale_x_date(breaks = seq(1870, 2020, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(0, 20000, 100),
labels = dollar_format(suffix = "Bn", prefix = "$")) +
xlab("") + ylab("Housing") +
geom_vline(xintercept = as.Date("2008-09-15"), linetype = "dashed", color = viridis(3)[2])
Clothing
(ref:DCAFRC1A027NBEA-06-20) Clothing
Code
%>%
gdp filter(variable %in% c("DCAFRC1A027NBEA")) %>%
filter(date >= as.Date("2006-01-01"),
<= as.Date("2020-01-01")) %>%
date mutate(value = value) %>%
ggplot(.) + geom_line(aes(x = date, y = value)) + theme_minimal() +
scale_x_date(breaks = seq(1870, 2020, 1) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(0, 600, 10),
labels = dollar_format(suffix = "Bn", prefix = "$")) +
xlab("") + ylab("Clothing, footware, and related services") +
geom_vline(xintercept = as.Date("2008-09-15"), linetype = "dashed", color = viridis(3)[2])