FRED Financial Measures during COIVD19
Joe Long
9/04/2020
Total Nonrevolving Credit Owned and Securitized, Outstanding (NONREVSL)
Total revolving Credit Owned and Securitized, Outstanding (REVOLSL)
Total Consumer Credit Owned and Securitized, Outstanding (TOTALSL)
symbol1 <-fredr_series_observations(series_id = "NONREVSL",
observation_start = as.Date("2019-01-01"))
indicator1 <-as.data.frame(symbol1)[,c(1,3)]
symbol2 <-fredr_series_observations(series_id = "REVOLSL",
observation_start = as.Date("2019-01-01"))
indicator2 <-as.data.frame(symbol2)[,c(1,3)]
symbol3 <-fredr_series_observations(series_id = "TOTALSL",
observation_start = as.Date("2019-01-01"))
indicator3 <-as.data.frame(symbol3)[,c(1,3)]
indicator <-full_join(indicator1,indicator2, by="date")
indicator <-full_join(indicator,indicator3, by="date")
colnames(indicator) <- c("date","Non_revolving","Revolving","Total")
#------------------------
indicator %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2, T, color = "red" ) %>%
column_spec(3, T, color = "blue" ) %>%
column_spec(4, T, color = "green" ) | date | Non_revolving | Revolving | Total |
|---|---|---|---|
| 2019-01-01 | 2957 | 1058.4 | 4016 |
| 2019-02-01 | 2970 | 1062.2 | 4032 |
| 2019-03-01 | 2983 | 1061.1 | 4044 |
| 2019-04-01 | 2994 | 1067.8 | 4062 |
| 2019-05-01 | 3004 | 1072.2 | 4077 |
| 2019-06-01 | 3015 | 1073.4 | 4088 |
| 2019-07-01 | 3027 | 1084.7 | 4112 |
| 2019-08-01 | 3042 | 1084.7 | 4127 |
| 2019-09-01 | 3053 | 1084.9 | 4138 |
| 2019-10-01 | 3064 | 1088.0 | 4152 |
| 2019-11-01 | 3076 | 1082.7 | 4159 |
| 2019-12-01 | 3086 | 1094.2 | 4181 |
| 2020-01-01 | 3098 | 1092.7 | 4191 |
| 2020-02-01 | 3112 | 1098.7 | 4211 |
| 2020-03-01 | 3118 | 1078.1 | 4196 |
| 2020-04-01 | 3109 | 1020.5 | 4130 |
| 2020-05-01 | 3118 | 996.8 | 4115 |
| 2020-06-01 | 3132 | 995.0 | 4127 |
| 2020-07-01 | 3144 | 994.7 | 4139 |
chart <- indicator %>% ggplot() +
geom_line(mapping = aes(x=date,y=Non_revolving),color="red",size=1) +
geom_line(mapping = aes(x=date,y=Revolving),color="blue",size=1) +
geom_line(mapping = aes(x=date,y=Total),color="green",size=1) +
labs(title = "Consumer Credit Outstanding",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
x="", y="",
caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego")+
theme_economist()
chart + geom_text(aes(x = max(date),y=last(Non_revolving),label="Non_revolving"))+
geom_text(aes(x = max(date),y=last(Revolving),label="Revolving")) +
geom_text(aes(x = max(date),y=last(Total),label="Total")) 
*******************************************************************
Current Work Hours; Percent Reporting Decreases for Federal Reserve District 3 (AWCDNA156MNFRBPHI)
Current Work Hours; Percent Reporting Increases for Federal Reserve District 3 (AWCINA156MNFRBPHI)
- Current Workhours reports the change in workhours compared to the previous month for reporting manufacturing firms. For more information about this release from the Federal Reserve Bank of Philadelphia, visit: http://www.philadelphiafed.org/research-and-data/regional-economy/business-outlook-survey/ .
symbol1 <-fredr_series_observations(series_id = "AWCDNA156MNFRBPHI",
observation_start = as.Date("2019-01-01"))
indicator1 <-as.data.frame(symbol1)[,c(1,3)]
symbol2 <-fredr_series_observations(series_id = "AWCINA156MNFRBPHI",
observation_start = as.Date("2019-01-01"))
indicator2 <-as.data.frame(symbol2)[,c(1,3)]
indicator <-full_join(symbol1,symbol2, by="date")
indicator <- indicator[,c(1,3,5)]
colnames(indicator) <- c("date","Decrease","Increase")
#------------------------
indicator %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2, T, color = "red" ) %>%
column_spec(3, T, color = "blue" ) | date | Decrease | Increase |
|---|---|---|
| 2019-01-01 | 17.0 | 18.9 |
| 2019-02-01 | 8.5 | 11.9 |
| 2019-03-01 | 5.7 | 22.6 |
| 2019-04-01 | 8.8 | 24.6 |
| 2019-05-01 | 5.2 | 22.4 |
| 2019-06-01 | 10.0 | 20.0 |
| 2019-07-01 | 1.8 | 21.1 |
| 2019-08-01 | 19.7 | 23.0 |
| 2019-09-01 | 8.6 | 19.0 |
| 2019-10-01 | 12.3 | 22.8 |
| 2019-11-01 | 12.5 | 16.1 |
| 2019-12-01 | 13.3 | 18.3 |
| 2020-01-01 | 15.0 | 15.0 |
| 2020-02-01 | 7.1 | 16.1 |
| 2020-03-01 | 8.8 | 15.8 |
| 2020-04-01 | 52.4 | 3.2 |
| 2020-05-01 | 18.9 | 17.0 |
| 2020-06-01 | 17.4 | 13.0 |
| 2020-07-01 | 9.6 | 25.0 |
| 2020-08-01 | 10.5 | 19.3 |
indicator2 <- indicator %>%
dateCast() ## Warning: Unknown or uninitialised column: `period`.## Warning: Unknown or uninitialised column: `year`.## Please be sure to have columns named 'year' and 'period' in your dataframe as they are returned from the bls_api() function.chart <- indicator %>% ggplot() +
geom_line(mapping = aes(x=date,y=Decrease),color="red",size=1) +
geom_line(mapping = aes(x=date,y=Increase),color="blue",size=1) +
labs(title = "CURRENT Work Hour Changes: Increasing or Decreasing",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Percentage from previous month",
caption = "Data source: FRED Philadelphia Federal Reserve. Illustration by @JoeLongSanDiego")+
theme_economist()
chart + geom_text(aes(x = max(date),y=last(Increase),label="Increase"))+
geom_text(aes(x = max(date),y=last(Decrease),label="Decrease"))
Future Hours: Percent Reporting Decreases for Federal Reserve District 3 (AWFDNA156MNFRBPHI)
Future Hours; Percent Reporting Increases for Federal Reserve District 3 (AWFINA156MNFRBPHI)
Future Hours; Percent Reporting No Change for Federal Reserve District 3 (AWFNNA156MNFRBPHI)
symbol1 <-fredr_series_observations(series_id = "AWFDNA156MNFRBPHI",
observation_start = as.Date("2019-01-01"))
indicator1 <-as.data.frame(symbol1)[,c(1,3)]
symbol2 <-fredr_series_observations(series_id = "AWFINA156MNFRBPHI",
observation_start = as.Date("2019-01-01"))
indicator2 <-as.data.frame(symbol2)[,c(1,3)]
symbol3 <-fredr_series_observations(series_id = "AWFNNA156MNFRBPHI",
observation_start = as.Date("2019-01-01"))
indicator3 <-as.data.frame(symbol3)[,c(1,3)]
indicator <-full_join(indicator1,indicator2, by="date")
indicator <-full_join(indicator,indicator3, by="date")
colnames(indicator) <- c("date","Decrease","Increase","No_Change")
#------------------------
indicator %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
column_spec(2, T, color = "red" ) %>%
column_spec(3, T, color = "blue" ) %>%
column_spec(4, T, color = "green" ) | date | Decrease | Increase | No_Change |
|---|---|---|---|
| 2019-01-01 | 5.7 | 28.3 | 58.5 |
| 2019-02-01 | 5.1 | 20.3 | 71.2 |
| 2019-03-01 | 11.3 | 26.4 | 60.4 |
| 2019-04-01 | 7.0 | 14.0 | 75.4 |
| 2019-05-01 | 13.8 | 19.0 | 62.1 |
| 2019-06-01 | 18.3 | 23.3 | 53.3 |
| 2019-07-01 | 19.3 | 19.3 | 59.6 |
| 2019-08-01 | 11.5 | 14.8 | 68.9 |
| 2019-09-01 | 15.5 | 17.2 | 63.8 |
| 2019-10-01 | 10.5 | 21.1 | 64.9 |
| 2019-11-01 | 10.7 | 26.8 | 60.7 |
| 2019-12-01 | 10.0 | 33.3 | 55.0 |
| 2020-01-01 | 6.7 | 28.3 | 60.0 |
| 2020-02-01 | 5.4 | 39.3 | 51.8 |
| 2020-03-01 | 5.3 | 26.3 | 64.9 |
| 2020-04-01 | 9.5 | 38.1 | 42.9 |
| 2020-05-01 | 9.4 | 24.5 | 54.7 |
| 2020-06-01 | 10.9 | 30.4 | 50.0 |
| 2020-07-01 | 9.6 | 28.8 | 55.8 |
| 2020-08-01 | 14.0 | 26.3 | 52.6 |
chart <- indicator %>% ggplot() +
geom_line(mapping = aes(x=date,y=Decrease),color="red",size=1) +
geom_line(mapping = aes(x=date,y=Increase),color="blue",size=1) +
geom_line(mapping = aes(x=date,y=No_Change),color="green",size=1) +
labs(title = "FUTURE Work Hour Changes: Increase or Decrease or No Change",
subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Percentage from previous month",
caption = "Data source: FRED Philadelphia Federal Reserve. Illustration by @JoeLongSanDiego")+
theme_economist()
chart + geom_text(aes(x = max(date),y=last(Increase),label="Increase"))+
geom_text(aes(x = max(date),y=last(Decrease),label="Decrease")) +
geom_text(aes(x = max(date),y=last(No_Change),label="No Change")) 
Weekly Hours Worked: Manufacturing for the United States (HOHWMN02USM065N)
indicator <-fredr_series_observations(series_id = "HOHWMN02USM065N",
observation_start = as.Date("2019-01-01"))
indicator[,c(1,3)] %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"))| date | value |
|---|---|
| 2019-01-01 | 41.7 |
| 2019-02-01 | 41.5 |
| 2019-03-01 | 41.6 |
| 2019-04-01 | 41.6 |
| 2019-05-01 | 41.5 |
| 2019-06-01 | 41.8 |
| 2019-07-01 | 41.2 |
| 2019-08-01 | 41.7 |
| 2019-09-01 | 41.7 |
| 2019-10-01 | 41.5 |
| 2019-11-01 | 41.7 |
| 2019-12-01 | 41.9 |
| 2020-01-01 | 41.2 |
| 2020-02-01 | 41.2 |
| 2020-03-01 | 41.1 |
| 2020-04-01 | 38.3 |
| 2020-05-01 | 39.3 |
| 2020-06-01 | 39.9 |
| 2020-07-01 | 40.3 |
# plotting data
indicator %>% ggplot() + geom_line(mapping = aes(x=date,y=value),
color = "blue4",size=1) +
labs(title = "Weekly Hours Worked: Manufacturing for the United States",
subtitle = str_glue("from {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Thousands of People",
caption = "Data source: FRED Federal Reserve. Illustration by @JoeLongSanDiego")+
theme_economist()+
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-08-2020'), ymin = -Inf, ymax = Inf),
fill = "grey", alpha = 0.03)
Employment Level - Persons At Work 1-34 Hours, Economic Reasons, All Industries (LNU02032194)
indicator <-fredr_series_observations(series_id = "LNU02032194",
observation_start = as.Date("2019-01-01"))
indicator[,c(1,3)] %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"))| date | value |
|---|---|
| 2019-01-01 | 5640 |
| 2019-02-01 | 4561 |
| 2019-03-01 | 4621 |
| 2019-04-01 | 4483 |
| 2019-05-01 | 4160 |
| 2019-06-01 | 4602 |
| 2019-07-01 | 4102 |
| 2019-08-01 | 4316 |
| 2019-09-01 | 3992 |
| 2019-10-01 | 4046 |
| 2019-11-01 | 4110 |
| 2019-12-01 | 4247 |
| 2020-01-01 | 4732 |
| 2020-02-01 | 4600 |
| 2020-03-01 | 5879 |
| 2020-04-01 | 10684 |
| 2020-05-01 | 10429 |
| 2020-06-01 | 9306 |
| 2020-07-01 | 8572 |
| 2020-08-01 | 7488 |
# plotting data
indicator %>% ggplot() + geom_line(mapping = aes(x=date,y=value),
color = "blue4",size=1) +
labs(title = "Part-time employment: All Industries",
subtitle = str_glue("At work from 1 to 34 hours \nfrom {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Thousands of People",
caption = "Data source: FRED Federal Reserve. Illustration by @JoeLongSanDiego")+
theme_economist()+
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-08-2020'), ymin = -Inf, ymax = Inf),
fill = "grey", alpha = 0.03)
KC Fed Labor Market Conditions Index, Level of Activity Indicator (FRBKCLMCILA)
A positive value indicates that labor market conditions are above their long-run average, while a negative value signifies that labor market conditions are below their long-run average.
For more information regarding this series visit the release website at http://www.kc.frb.org/research/indicatorsdata/lmci/index.cfm .
indicator <-fredr_series_observations(series_id = "FRBKCLMCILA",
observation_start = as.Date("2019-01-01"))
indicator[,c(1,3)] %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"))| date | value |
|---|---|
| 2019-01-01 | 0.8944 |
| 2019-02-01 | 0.9844 |
| 2019-03-01 | 0.9477 |
| 2019-04-01 | 1.0006 |
| 2019-05-01 | 1.0397 |
| 2019-06-01 | 1.0122 |
| 2019-07-01 | 1.1909 |
| 2019-08-01 | 1.0251 |
| 2019-09-01 | 1.0398 |
| 2019-10-01 | 0.9657 |
| 2019-11-01 | 1.0187 |
| 2019-12-01 | 1.0942 |
| 2020-01-01 | 1.1598 |
| 2020-02-01 | 1.0731 |
| 2020-03-01 | 0.1852 |
| 2020-04-01 | -2.0233 |
| 2020-05-01 | -1.0691 |
| 2020-06-01 | -0.5602 |
| 2020-07-01 | -1.1835 |
# plotting data
indicator %>% ggplot() + geom_line(mapping = aes(x=date,y=value),
color = "blue4",size=1) +
labs(title = "Labor Market Conditions Index",
subtitle = str_glue("Zero Index: the long-run average\nfrom {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Index",
caption = "Data source: Kansas City Federal Reserve.\nIllustration by @JoeLongSanDiego")+
theme_economist()+
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-07-2020'), ymin = -Inf, ymax = Inf),
fill = "grey", alpha = 0.03)+
geom_hline(yintercept = 0,color="red")
Employment Level - Part-Time for Economic Reasons, Slack Work or Business Conditions, All Industries (LNS12032195)
indicator <-fredr_series_observations(series_id = "LNS12032195",
observation_start = as.Date("2019-01-01"))
indicator[,c(1,3)] %>% kable() %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"))| date | value |
|---|---|
| 2019-01-01 | 3402 |
| 2019-02-01 | 2779 |
| 2019-03-01 | 2887 |
| 2019-04-01 | 2868 |
| 2019-05-01 | 2647 |
| 2019-06-01 | 2704 |
| 2019-07-01 | 2392 |
| 2019-08-01 | 2683 |
| 2019-09-01 | 2600 |
| 2019-10-01 | 2747 |
| 2019-11-01 | 2634 |
| 2019-12-01 | 2657 |
| 2020-01-01 | 2655 |
| 2020-02-01 | 2776 |
| 2020-03-01 | 4043 |
| 2020-04-01 | 9939 |
| 2020-05-01 | 9543 |
| 2020-06-01 | 7939 |
| 2020-07-01 | 7281 |
| 2020-08-01 | 6214 |
# plotting data
indicator %>% ggplot() + geom_line(mapping = aes(x=date,y=value),
color = "blue4",size=1) +
labs(title = "Under-employment: Part-Time Employment due to Business Condition ",
subtitle = str_glue("Zero Index: the long-run average\nfrom {min(indicator$date)} through {max(indicator$date)}"),
x="Monthly", y="Thousands of Persons",
caption = "Data source: U.S. Bureau of Labor Statistics (LNS12032195).\nIllustration by @JoeLongSanDiego")+
theme_economist()+
geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-07-2020'), ymin = -Inf, ymax = Inf),
fill = "grey", alpha = 0.03)
# geom_hline(yintercept = 0,color="red")