Unemployment Indicators during COVID19

Initial Claims (ICNSA)

usa_claims <- 
  "ICNSA" %>% 
  tq_get(get = "economic.data", 
         from = "2019-01-01") %>% 
  rename(claims = price) 


  usa_claims %>% 
    ggplot(aes(x = date, y = claims)) +
     geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('20-10-2020'), ymin = -Inf, ymax = Inf),
                   fill = "white", alpha = 0.02)+
    geom_line(color = "blue",size=1) + 
    labs(
      x = "Weekly",
      y = "Number of Persons",
      title = "New Initial Unemployment (Insured) Claims _ National",
      caption = "Data source: FRED Philadelphia Federal Reserve\nIllustration by @JoeLongSanDiego",
      subtitle = str_glue("From {min(usa_claims$date)} through {max(usa_claims$date)}")
    ) +
    theme_economist() +
    scale_y_continuous(labels = scales::comma)

Continued Claims (Insured Unemployment) (CCNSA)

indicator <- 
  "CCNSA" %>% 
  tq_get(get = "economic.data", 
         from = "2019-01-01") %>% 
  rename(claims = price) 


  indicator %>% 
    ggplot(aes(x = date, y = claims)) +
     geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-11-2020'), ymin = -Inf, ymax = Inf),
                   fill = "white", alpha = 0.02)+
    geom_line(color = "blue",size=1) + 
    labs(
      x = "Weekly",
      y = "Number of Persons",
      title = "Continued Unemployment Claims _ Insured only",
      caption = "Data source: FRED Philadelphia Federal Reserve\nIllustration by @JoeLongSanDiego",
      subtitle = str_glue("From {min(usa_claims$date)} through {max(usa_claims$date)}\nNot counting exhausted claims")
    ) +
    theme_economist() +
    scale_y_continuous(labels = scales::comma)

National Unemployment Rate (UNRATE)

usa_claims <- 
  "UNRATE" %>% 
  tq_get(get = "economic.data", 
         from = "2019-01-01") %>% 
  rename(claims = price) 


  usa_claims %>% 
    ggplot(aes(x = date, y = claims)) +
     geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
                   fill = "white", alpha = 0.02)+
    geom_line(color = "blue",size=1) + 
    labs(
      x = "Monthly",
      y = "Percent",
      title = "New Unemployment Claims _ National ",
      caption = "Data source: FRED Philadelphia Federal Reserve\nIllustration by @JoeLongSanDiego",
      subtitle = str_glue("From {min(usa_claims$date)} through {max(usa_claims$date)}")
    ) +
    theme_economist() +
    scale_y_continuous(labels = scales::comma)

Labor Force Participation Rate (LNU01300000)

indicator <- 
  "LNU01300000" %>% 
  tq_get(get = "economic.data", 
         from = "2019-01-01") 
   


  indicator %>% 
    ggplot(aes(x = date, y = price)) +
     geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
                   fill = "grey", alpha = 0.02)+
    geom_line(color = "blue",size=1) + 
    labs(
      x = "Monthly",
      y = "Percent",
      title = "Labor Force Participation Rate (LNU01300000)",
      caption = "Data source: FRED Philadelphia Federal Reserve\nIllustration by @JoeLongSanDiego",
      subtitle = str_glue("From {min(usa_claims$date)} through {max(usa_claims$date)}")
    ) +
    theme_economist() +
    scale_y_continuous(labels = scales::comma)

Labor Force Participation Rate (LNU01300000)

indicator <- 
  "LNU01300000" %>% 
  tq_get(get = "economic.data", 
         from = "1980-01-01") 
   


  indicator %>% 
    ggplot(aes(x = date, y = price)) +
     geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
                   fill = "grey", alpha = 0.02)+
    geom_line(color = "blue",size=1) + 
    labs(
      x = "Monthly",
      y = "Percent",
      title = "Labor Force Participation Rate (LNU01300000)",
      caption = "Data source: FRED Philadelphia Federal Reserve\nIllustration by @JoeLongSanDiego",
      subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}")
    ) +
    theme_economist() +
    scale_y_continuous(labels = scales::comma)

Labor Force Participation Rate - Women (LNU01300002)

indicator <- 
  "LNU01300002" %>% 
  tq_get(get = "economic.data", 
         from = "1980-01-01") 
   


  indicator %>% 
    ggplot(aes(x = date, y = price)) +
     geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
                   fill = "grey", alpha = 0.02)+
    geom_line(color = "blue",size=1) + 
    labs(
      x = "Monthly",
      y = "Percent",
      title = "Women _ Labor Force Participation Rate (LNU01300002)",
      caption = "Data source: FRED Philadelphia Federal Reserve\nIllustration by @JoeLongSanDiego",
      subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}")
    ) +
    theme_economist() +
    scale_y_continuous(labels = scales::comma)

Labor Force Participation Rate - Men (LNU01300001)

indicator <- 
  "LNU01300002" %>% 
  tq_get(get = "economic.data", 
         from = "1980-01-01") 
   


  indicator %>% 
    ggplot(aes(x = date, y = price)) +
     geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
                   fill = "grey", alpha = 0.02)+
    geom_line(color = "blue",size=1) + 
    labs(
      x = "Monthly",
      y = "Percent",
      title = "Men _ Labor Force Participation Rate (LNU01300001)",
      caption = "Data source: FRED Philadelphia Federal Reserve\nIllustration by @JoeLongSanDiego",
      subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}")
    ) +
    theme_economist() +
    scale_y_continuous(labels = scales::comma)

All Employees, Leisure and Hospitality (CEU7000000001)

indicator <-fredr_series_observations(series_id = "CEU7000000001",
        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	15739
2019-02-01	15841
2019-03-01	16090
2019-04-01	16406
2019-05-01	16788
2019-06-01	17219
2019-07-01	17289
2019-08-01	17244
2019-09-01	16759
2019-10-01	16648
2019-11-01	16439
2019-12-01	16450
2020-01-01	16092
2020-02-01	16264
2020-03-01	15714
2020-04-01	8485
2020-05-01	10109
2020-06-01	12437
2020-07-01	13152
2020-08-01	13231
2020-09-01	13124

# plotting data
indicator %>% ggplot() +
  geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('10-10-2020'), ymin = -Inf, ymax = Inf),
                   fill = "grey", alpha = 0.02)+
  geom_line(mapping = aes(x=date,y=value), 
                              color = "blue4",size=1) +
  labs(title = "All Employees, Leisure and Hospitality Industries", 
       subtitle = str_glue("from {min(indicator$date)} through {max(indicator$date)}"),
       x="Monthly", y="Thousands of Persons",
       caption = "Data source:  FRED Federal Reserve\nIllustration by @JoeLongSanDiego")+
    theme_economist()

All Employees, Accommodation and Food Services (CEU7072000001)

indicator <-fredr_series_observations(series_id = "CEU7072000001",
        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	13576
2019-02-01	13649
2019-03-01	13826
2019-04-01	14036
2019-05-01	14289
2019-06-01	14505
2019-07-01	14507
2019-08-01	14533
2019-09-01	14275
2019-10-01	14237
2019-11-01	14141
2019-12-01	14138
2020-01-01	13855
2020-02-01	14003
2020-03-01	13480
2020-04-01	7371
2020-05-01	8877
2020-06-01	10773
2020-07-01	11326
2020-08-01	11433
2020-09-01	11421

# plotting data
indicator %>% ggplot() +
  geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
                   fill = "grey", alpha = 0.03)+
  geom_line(mapping = aes(x=date,y=value), 
                              color = "blue4",size=1) +
  labs(title = "All Employees, Hospitality Accommodation and Food Services", 
       subtitle = str_glue("from {min(indicator$date)} through {max(indicator$date)}"),
       x="Monthly", y="Thousands of Persons",
       caption = "Data source:  FRED Federal Reserve\nIllustration by @JoeLongSanDiego")+
    theme_economist()

All Employees, Amusements, Gambling, and Recreation (CEU7071300001)

indicator <-fredr_series_observations(series_id = "CEU7071300001",
        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	1556.9
2019-02-01	1564.2
2019-03-01	1608.5
2019-04-01	1663.6
2019-05-01	1768.6
2019-06-01	1974.1
2019-07-01	2050.1
2019-08-01	1989.1
2019-09-01	1771.7
2019-10-01	1713.2
2019-11-01	1622.9
2019-12-01	1646.9
2020-01-01	1618.4
2020-02-01	1625.5
2020-03-01	1607.9
2020-04-01	717.3
2020-05-01	831.9
2020-06-01	1242.8
2020-07-01	1414.6
2020-08-01	1375.0
2020-09-01	1293.6

# plotting data
indicator %>% ggplot() +
  geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
                   fill = "grey", alpha = 0.03)+
  geom_line(mapping = aes(x=date,y=value), 
                              color = "blue4",size=1) +
  labs(title = "All Employees, Amusements, Gambling, and Recreation", 
       subtitle = str_glue("from {min(indicator$date)} through {max(indicator$date)}"),
       x="Monthly", y="Thousands of Persons",
       caption = "Data source:  U.S. Bureau of Labor Statistics (CEU7071300001)\nIllustration by @JoeLongSanDiego")+
    theme_economist()

All Employees, Construction of Buildings (CEU2023600001)

indicator <-fredr_series_observations(series_id = "CEU2023600001",
        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	1603
2019-02-01	1602
2019-03-01	1616
2019-04-01	1629
2019-05-01	1647
2019-06-01	1686
2019-07-01	1701
2019-08-01	1708
2019-09-01	1686
2019-10-01	1696
2019-11-01	1680
2019-12-01	1666
2020-01-01	1632
2020-02-01	1636
2020-03-01	1636
2020-04-01	1434
2020-05-01	1556
2020-06-01	1616
2020-07-01	1638
2020-08-01	1648
2020-09-01	1640

# plotting data
indicator %>% ggplot() +
  geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
                   fill = "grey", alpha = 0.03)+
  geom_line(mapping = aes(x=date,y=value), 
                              color = "blue4",size=1) +
  labs(title = "All Employees, Construction of Buildings", 
       subtitle = str_glue("from {min(indicator$date)} through {max(indicator$date)}"),
       x="Monthly", y="Thousands of Persons",
       caption = "Data source:  U.S. Bureau of Labor Statistics (CEU2023600001)\nIllustration by @JoeLongSanDiego")+
    theme_economist()

All Employees, Clothing and Clothing Accessories Stores (CEU4244800001)

indicator <-fredr_series_observations(series_id = "CEU4244800001",
        observation_start = as.Date("2019-01-01")) 

# plotting data
ggplot(indicator) + 
   geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
                   fill = "lightyellow", alpha = 0.02)+
  geom_line(mapping = aes(x=date,y=value),  color = "red4") +
  
  labs(title = "All Employees, Clothing and Clothing Accessories Stores", 
       subtitle = str_glue("from {min(indicator$date)} through {max(indicator$date)}\nNot Seasonally Adjusted"),
       x="Monthly", y="Thousand of Persons",
       caption = "Data source: FRED Federal Reserve.\nIllustration by @JoeLongSanDiego")+
    theme_economist()

All Employees, Automobile Dealers (CEU4244110001)

indicator <-fredr_series_observations(series_id = "CEU4244100001",
        observation_start = as.Date("2019-01-01")) 

# plotting data
ggplot(indicator) + 
   geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
                   fill = "lightyellow", alpha = 0.02)+
  geom_line(mapping = aes(x=date,y=value),  color = "red4") +
  
  labs(title = "All Employees, Automobile Dealers", 
       subtitle = str_glue("from {min(indicator$date)} through {max(indicator$date)}\nNot Seasonally Adjusted"),
       x="Monthly", y="Thousand of Persons",
       caption = "Data source: FRED Federal Reserve.\nIllustration by @JoeLongSanDiego")+
    theme_economist()

All Employees, General Merchandise Stores (CEU4245200001)

indicator <-fredr_series_observations(series_id = "CEU4245200001",
        observation_start = as.Date("2019-01-01")) 

# plotting data
ggplot(indicator) + 
   geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
                   fill = "lightyellow", alpha = 0.02)+
  geom_line(mapping = aes(x=date,y=value),  color = "red4") +
  
  labs(title = "All Employees, General Merchandise Stores", 
       subtitle = str_glue("from {min(indicator$date)} through {max(indicator$date)}\nNot Seasonally Adjusted"),
       x="Monthly", y="Thousand of Persons",
       caption = "Data source: FRED Federal Reserve.\nIllustration by @JoeLongSanDiego")+
    theme_economist()

All Employees, Motor Vehicle and Parts Dealers (CEU4244100001)

indicator <-fredr_series_observations(series_id = "CEU4244100001",
        observation_start = as.Date("2019-01-01")) 

# plotting data
ggplot(indicator) + 
   geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
                   fill = "lightyellow", alpha = 0.02)+
  geom_line(mapping = aes(x=date,y=value),  color = "red4") +
  
  labs(title = "All Employees, Motor Vehicle and Parts Dealers", 
       subtitle = str_glue("from {min(indicator$date)} through {max(indicator$date)}\nNot Seasonally Adjusted"),
       x="Monthly", y="Thousand of Persons",
       caption = "Data source: FRED Federal Reserve.\nIllustration by @JoeLongSanDiego")+
    theme_economist()

All Employees, Building Material and Garden Supply Stores (CEU4244400001)

indicator <-fredr_series_observations(series_id = "CEU4244400001",
        observation_start = as.Date("2019-01-01")) 

# plotting data
ggplot(indicator) + 
   geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
                   fill = "lightyellow", alpha = 0.02)+
  geom_line(mapping = aes(x=date,y=value),  color = "red4") +
  
  labs(title = "All Employees, Building Material and Garden Supply Stores", 
       subtitle = str_glue("from {min(indicator$date)} through {max(indicator$date)}\nNot Seasonally Adjusted"),
       x="Monthly", y="Thousand of Persons",
       caption = "Data source: FRED Federal Reserve.\nIllustration by @JoeLongSanDiego")+
    theme_economist()

All Employees, Health and Personal Care Stores (CEU4244600001)

indicator <-fredr_series_observations(series_id = "CEU4244600001",
        observation_start = as.Date("2019-01-01")) 

# plotting data
ggplot(indicator) + 
   geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
                   fill = "lightyellow", alpha = 0.02)+
  geom_line(mapping = aes(x=date,y=value),  color = "red4") +
  
  labs(title = "All Employees, Health and Personal Care Stores", 
       subtitle = str_glue("from {min(indicator$date)} through {max(indicator$date)}\nNot Seasonally Adjusted"),
       x="Monthly", y="Thousand of Persons",
       caption = "Data source: FRED Federal Reserve.\nIllustration by @JoeLongSanDiego")+
    theme_economist()

All Employees, Food and Beverage Stores (CEU4244500001)

indicator <-fredr_series_observations(series_id = "CEU4244500001",
        observation_start = as.Date("2019-01-01")) 

# plotting data
ggplot(indicator) + 
   geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
                   fill = "lightyellow", alpha = 0.02)+
  geom_line(mapping = aes(x=date,y=value),  color = "red4") +
  
  labs(title = "All Employees, Food and Beverage Stores", 
       subtitle = str_glue("from {min(indicator$date)} through {max(indicator$date)}\nNot Seasonally Adjusted"),
       x="Monthly", y="Thousand of Persons",
       caption = "Data source: FRED Federal Reserve.\nIllustration by @JoeLongSanDiego")+
    theme_economist()

* All Employees, Retail Trade (USTRADE)

indicator <-fredr_series_observations(series_id = "USTRADE",
        observation_start = as.Date("2019-01-01")) 

# plotting data
ggplot(indicator) + 
   geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
                   fill = "lightyellow", alpha = 0.02)+
  geom_line(mapping = aes(x=date,y=value),  color = "red4") +
  
  labs(title = "All Employees, Retail Trade", 
       subtitle = str_glue("from {min(indicator$date)} through {max(indicator$date)}\nSeasonally Adjusted"),
       x="Monthly", y="Thousand of Persons",
       caption = "Data source: FRED Federal Reserve.\nIllustration by @JoeLongSanDiego")+
    theme_economist()

All Employees, Manufacturing (CEU3000000001)

indicator <- 
  "CEU3000000001" %>% 
  tq_get(get = "economic.data", 
         from = "2019-01-01") %>% 
  rename(claims = price) 


  indicator %>% 
    ggplot(aes(x = date, y = claims)) +
     geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
                   fill = "grey", alpha = 0.03)+
    geom_line(color = "blue",size=1) + 
    labs(
      x = "Monthly",
      y = "Thousands",
      title = "All Employees, Manufacturing (CEU3000000001)",
      caption = "Data source: FRED Philadelphia Federal Reserve\nIllustration by @JoeLongSanDiego",
      subtitle = str_glue("From {min(usa_claims$date)} through {max(usa_claims$date)}")
    ) +
    theme_economist() +
    scale_y_continuous(labels = scales::comma)

Unemployment Rate - Women (LNU04000002)

Unemployment Rate - Men (LNS14000001)

symbol1 <-fredr_series_observations(series_id = "LNS14000001", 
      observation_start = as.Date("2019-01-01"))
indicator1 <-as.data.frame(symbol1)[,c(1,3)]
symbol2 <-fredr_series_observations(series_id = "LNS14000002", 
      observation_start = as.Date("2019-01-01"))
indicator2 <-as.data.frame(symbol2)[,c(1,3)]


indicator <-full_join(indicator1,indicator2, by="date")


colnames(indicator) <- c("date","Male","Female")

#------------------------
indicator %>% kable() %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>%
   column_spec(2, T, color = "red" ) %>%
   column_spec(3, T, color = "blue" ) 

date	Male	Female
2019-01-01	4.1	3.9
2019-02-01	3.9	3.7
2019-03-01	3.9	3.7
2019-04-01	3.8	3.4
2019-05-01	3.7	3.6
2019-06-01	3.7	3.6
2019-07-01	3.7	3.7
2019-08-01	3.7	3.6
2019-09-01	3.6	3.4
2019-10-01	3.6	3.5
2019-11-01	3.5	3.5
2019-12-01	3.5	3.5
2020-01-01	3.6	3.5
2020-02-01	3.6	3.4
2020-03-01	4.4	4.4
2020-04-01	13.5	16.2
2020-05-01	12.2	14.5
2020-06-01	10.6	11.7
2020-07-01	9.8	10.6
2020-08-01	8.3	8.6
2020-09-01	7.7	8.0

chart <- indicator %>% ggplot() + 
    geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-10-2020'), ymin = -Inf, ymax = Inf),
                   fill = "grey", alpha = 0.03)+
  geom_line(mapping = aes(x=date,y=Male),color="red",size=1)  +
  geom_line(mapping = aes(x=date,y=Female),color="blue",size=1)  +
  
     labs(title = "Unemployment Rate By Gender", 
          subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}\nMale = Red - Female = Blue"),
       x="Monthly", y="Percentage",
       caption = "Data source: FRED Philadelphia Federal Reserve\nIllustration by @JoeLongSanDiego")+
    theme_economist()

chart + geom_text(aes(x = max(date),y=last(Male),label="Male"))+
        geom_text(aes(x = max(date),y=last(Female),label="Female"))