Advanced Retail Trade
Joe Long, Data Analyst
2/17/2020
Advanced Retail Sale Survey
The U.S. Census Bureau conducts the Advance Monthly Retail Trade and Food Services Survey to provide an early estimate of monthly sales by kind of business for retail and food service firms located in the United States. Each month, questionnaires are mailed to a probability sample of approximately 4,700 employer firms selected from the larger Monthly Retail Trade Survey. Advance sales estimates are computed using a link relative estimator. For each detailed industry, we compute a ratio of current-to previous month weighted sales using data from units for which we have obtained usable responses for both the current and previous month. For each detailed industry, the advance total sales estimates for the current month is computed by multiplying this ratio by the preliminary sales estimate for the previous month (derived from the larger MRTS) at the appropriate industry level. Total estimates for broader industries are computed as the sum of the detailed industry estimates. The link relative estimate is used because imputation is not performed for most nonrespondents in MARTS. For a limited number of nonresponding companies that have influential effects on the estimates, sales may be estimated based on historical performance of that company. The monthly estimates are benchmarked to the annual survey estimates from the Annual Retail Trade Survey once available. The estimates are adjusted for seasonal variation and holiday and trading day differences. Additional information on MARTS and MRTS can be found on the Census Bureau website at: www.census.gov/retail.
Description of the survey as provided by the Census, https://census.gov/retail/marts/www/marts_current.pdf
Advance Retail Sales: Retail (Excluding Food Services) (RSXFS)
symbol <-fredr_series_observations(series_id = "RSXFS",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator,n=12) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2:3, T, color = "blue" ) | date | value | |
|---|---|---|
| 242 | 2020-02-01 | 461914 |
| 243 | 2020-03-01 | 438221 |
| 244 | 2020-04-01 | 382734 |
| 245 | 2020-05-01 | 448788 |
| 246 | 2020-06-01 | 479823 |
| 247 | 2020-07-01 | 483699 |
| 248 | 2020-08-01 | 488998 |
| 249 | 2020-09-01 | 497072 |
| 250 | 2020-10-01 | 496660 |
| 251 | 2020-11-01 | 491713 |
| 252 | 2020-12-01 | 488579 |
| 253 | 2021-01-01 | 513581 |
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-01-2021'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Monthly",
y = "Millions",
title = "Advance Retail Sales: Retail (Excluding Food Services) (RSXFS)",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
indicator2 <- filter(indicator,date >= "2019-01-01")
indicator2 %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-1-2021'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Monthly",
y = "Millions",
title = "Advance Retail Sales: Retail (Excluding Food Services) (RSXFS) _ Short Term Trend",
subtitle = str_glue("From {min(indicator2$date)} through {max(indicator2$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
Advance Retail Sales: Motor Vehicle and Parts Dealers (MARTSMPCSM441USN)
symbol <-fredr_series_observations(series_id = "MARTSMPCSM441USN",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator,n=12) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2:3, T, color = "blue" ) | date | value | |
|---|---|---|
| 242 | 2020-02-01 | 4.9 |
| 243 | 2020-03-01 | -15.5 |
| 244 | 2020-04-01 | -15.4 |
| 245 | 2020-05-01 | 54.8 |
| 246 | 2020-06-01 | 6.5 |
| 247 | 2020-07-01 | 1.5 |
| 248 | 2020-08-01 | -0.3 |
| 249 | 2020-09-01 | -2.6 |
| 250 | 2020-10-01 | 1.4 |
| 251 | 2020-11-01 | -10.0 |
| 252 | 2020-12-01 | 12.8 |
| 253 | 2021-01-01 | -11.9 |
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-1-2021'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
geom_hline(yintercept = 0,color="red")+
labs(
x = "Monthly",
y = "Percent Change from Preceding Period",
title = "Advance Retail Sales: Motor Vehicle and Parts Dealers (MARTSMPCSM441USN)",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
indicator2 <- filter(indicator,date >= "2019-01-01")
indicator2 %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-1-2021'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
geom_hline(yintercept = 0,color="red")+
labs(
x = "Monthly",
y = "Percent Change from Preceding Period",
title = "Advance Retail Sales: Motor Vehicle and Parts Dealers (MARTSMPCSM441USN)",
subtitle = str_glue("From {min(indicator2$date)} through {max(indicator2$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
Advance Retail Sales: Sporting Goods, Hobby, Book, and Music Stores (MARTSMPCSM451USN)
symbol <-fredr_series_observations(series_id = "MARTSMPCSM451USN",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator,n=12) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2:3, T, color = "blue" ) | date | value | |
|---|---|---|
| 242 | 2020-02-01 | -4.0 |
| 243 | 2020-03-01 | -6.9 |
| 244 | 2020-04-01 | -34.9 |
| 245 | 2020-05-01 | 81.7 |
| 246 | 2020-06-01 | 32.1 |
| 247 | 2020-07-01 | -4.4 |
| 248 | 2020-08-01 | 3.1 |
| 249 | 2020-09-01 | -5.0 |
| 250 | 2020-10-01 | -1.5 |
| 251 | 2020-11-01 | 9.2 |
| 252 | 2020-12-01 | 35.0 |
| 253 | 2021-01-01 | -35.8 |
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-1-2021'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
geom_hline(yintercept = 0,color="red")+
labs(
x = "Monthly",
y = "Percent Change from Preceding Period",
title = "Advance Retail Sales: Sporting Goods, Hobby, Book, and Music Stores",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
indicator2 <- filter(indicator,date >= "2019-01-01")
indicator2 %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-1-2021'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
geom_hline(yintercept = 0,color="red")+
labs(
x = "Monthly",
y = "Percent Change from Preceding Period",
title = "Advance Retail Sales: Sporting Goods, Hobby, Book,& Music Stores (MARTSMPCSM451USN)",
subtitle = str_glue("From {min(indicator2$date)} through {max(indicator2$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
Advance Retail Sales: Motor Vehicle and Parts Dealers (MARTSMPCSM441USN)
symbol <-fredr_series_observations(series_id = "MARTSMPCSM441USN",
observation_start = as.Date("2019-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator,n=12) %>% kable(caption = "Advance Retail Sales: Motor Vehicle and Parts Dealers (MARTSMPCSM441USN)") %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2:3, T, color = "blue" ) | date | value | |
|---|---|---|
| 14 | 2020-02-01 | 4.9 |
| 15 | 2020-03-01 | -15.5 |
| 16 | 2020-04-01 | -15.4 |
| 17 | 2020-05-01 | 54.8 |
| 18 | 2020-06-01 | 6.5 |
| 19 | 2020-07-01 | 1.5 |
| 20 | 2020-08-01 | -0.3 |
| 21 | 2020-09-01 | -2.6 |
| 22 | 2020-10-01 | 1.4 |
| 23 | 2020-11-01 | -10.0 |
| 24 | 2020-12-01 | 12.8 |
| 25 | 2021-01-01 | -11.9 |
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-1-2021'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
geom_hline(yintercept = 0,color="red")+
labs(
x = "Monthly",
y = "Percent Change ",
title = "Advance Retail Sales: Motor Vehicle and Parts Dealers (MARTSMPCSM441USN)",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
Advance Retail Sales: Auto and Other Motor Vehicles (MARTSMPCSM441XUSN)
symbol <-fredr_series_observations(series_id = "MARTSMPCSM441XUSN",
observation_start = as.Date("2019-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator,n=12) %>% kable(caption = "Advance Retail Sales: Auto and Other Motor Vehicles (MARTSMPCSM441XUSN)") %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2:3, T, color = "blue" ) | date | value | |
|---|---|---|
| 14 | 2020-02-01 | 5.7 |
| 15 | 2020-03-01 | -17.0 |
| 16 | 2020-04-01 | -16.3 |
| 17 | 2020-05-01 | 58.4 |
| 18 | 2020-06-01 | 6.3 |
| 19 | 2020-07-01 | 1.7 |
| 20 | 2020-08-01 | -0.2 |
| 21 | 2020-09-01 | -2.5 |
| 22 | 2020-10-01 | 1.4 |
| 23 | 2020-11-01 | -10.1 |
| 24 | 2020-12-01 | 13.9 |
| 25 | 2021-01-01 | -12.6 |
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-1-2021'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
geom_hline(yintercept = 0,color="red")+
labs(
x = "Monthly",
y = "Percent Change ",
title = "Advance Retail Sales: Auto and Other Motor Vehicles (MARTSMPCSM441XUSN)",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
Advance Retail Sales: Health and Personal Care Stores (MARTSMPCSM446USS)
symbol <-fredr_series_observations(series_id = "MARTSMPCSM446USS",
observation_start = as.Date("2019-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator,n=12) %>% kable(caption = "Advance Retail Sales: Health/Personal Care Stores (MARTSMPCSM446USS)") %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2:3, T, color = "blue" ) | date | value | |
|---|---|---|
| 14 | 2020-02-01 | 0.0 |
| 15 | 2020-03-01 | 5.2 |
| 16 | 2020-04-01 | -14.6 |
| 17 | 2020-05-01 | 3.1 |
| 18 | 2020-06-01 | 7.2 |
| 19 | 2020-07-01 | 4.3 |
| 20 | 2020-08-01 | -0.1 |
| 21 | 2020-09-01 | 1.1 |
| 22 | 2020-10-01 | -0.4 |
| 23 | 2020-11-01 | -0.3 |
| 24 | 2020-12-01 | 1.0 |
| 25 | 2021-01-01 | 1.3 |
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-1-2021'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
geom_hline(yintercept = 0,color="red")+
labs(
x = "Monthly",
y = "Percent Change ",
title = "Advance Retail Sales: Health/Personal Care Stores (MARTSMPCSM446USS)",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
Advance Retail Sales: Clothing and Clothing Accessory Stores (MARTSMPCSM448USN)
symbol <-fredr_series_observations(series_id = "MARTSMPCSM448USS",
observation_start = as.Date("2019-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator,n=12) %>% kable(caption = "Advance Retail Sales: Clothing & Accessory Stores (MARTSMPCSM448USN)") %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2:3, T, color = "blue" ) | date | value | |
|---|---|---|
| 14 | 2020-02-01 | -1.7 |
| 15 | 2020-03-01 | -48.7 |
| 16 | 2020-04-01 | -73.5 |
| 17 | 2020-05-01 | 180.1 |
| 18 | 2020-06-01 | 99.7 |
| 19 | 2020-07-01 | 2.7 |
| 20 | 2020-08-01 | 2.8 |
| 21 | 2020-09-01 | 15.4 |
| 22 | 2020-10-01 | -3.6 |
| 23 | 2020-11-01 | -6.1 |
| 24 | 2020-12-01 | 2.6 |
| 25 | 2021-01-01 | 5.0 |
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-1-2021'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Monthly",
y = "Percent Change ",
title = "Advance Retail Sales: Clothing & Assessory Stores (MARTSMPCSM448USN)",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
Advance Retail Sales: Gasoline Stations (RSGASS)
symbol <-fredr_series_observations(series_id = "RSGASS",
observation_start = as.Date("2000-01-01"))
indicator <-as.data.frame(symbol)[,c(1,3)]
tail(indicator) %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2, T, color = "red" ) | date | value | |
|---|---|---|
| 248 | 2020-08-01 | 35383 |
| 249 | 2020-09-01 | 36030 |
| 250 | 2020-10-01 | 36032 |
| 251 | 2020-11-01 | 35411 |
| 252 | 2020-12-01 | 37726 |
| 253 | 2021-01-01 | 39232 |
indicator %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-1-2021'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Monthly",
y = "Millions of Dollars",
title = " Advance Retail Sales: Gasoline Stations (RSGASS)",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()
indicator2 <- filter(indicator,date >= "2019-01-01")
indicator2 %>%
ggplot(aes(x = date, y = value)) +
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-1-2021'), ymin = -Inf, ymax = Inf),
fill = "white", alpha = 0.04)+
geom_line(color = "dodgerblue4",size=.8) +
labs(
x = "Quarterly",
y = "Millions of Dollars",
title = "Advance Retail Sales: Gasoline Stations (RSGASS) _ Short Term Trend",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
caption = "Data source: FRED St. Louis Federal Reserve \nIllustration by @JoeLongSanDiego") +
theme_economist()