Manufacturing Outlook _ Philadelphia Federal Reserve District

Future Capital Expenditures; Diffusion Index (CEFDFNA066MNFRBPHI)

Federal Reserve District 3: Philadelphia

• Future Capital Expenditures forecasts the change in capital expenditures over the next six months for reporting manufacturing firms. The diffusion index is calculated by taking the percent reporting increases and subtracting the percentage reporting decreases.

• 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/

• Data source : Federal Reserve Bank of Philadelphia, Future Capital Expenditures; Diffusion Index for Federal Reserve District 3: Philadelphia [CEFDFNA066MNFRBPHI], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/CEFDFNA066MNFRBPHI.

indicator <- fredr(series_id = "CEFDFNA066MNFRBPHI", observation_start = as.Date("2015-01-01"))


ggplot(data = indicator, mapping = aes(x = date, y = value)) +
   geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('05-01-2021'), ymin = -Inf, ymax = Inf),
                   fill = "lightyellow", alpha = 0.02)+
   geom_line(mapping = aes(x=date,y=value), 
                              color = "blue4") +
    labs(title = "Future Capital Expenditures _ Diffusion Index", 
       subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}\nFED District 3 only"),
       x="Monthly", y="Index",
       caption = "Capital expenditures over the next six months\nData source: Federal Reserve Bank of Philadelphia.   Illustration by @JoeLongSanDiego")+
    theme_economist()

tail(indicator,n=12) %>%
  ggplot(mapping = aes(x = date, y = value)) +
   
   geom_line(mapping = aes(x=date,y=value), 
                              color = "blue4") +
    labs(title = "Future Capital Expenditures _ Diffusion Index", 
       subtitle = "Past 12 months\nFED District 3 only",
       x="Monthly", y="Index",
       caption = "Net Change _ Capital expenditures over the next six months\nData source: Federal Reserve Bank of Philadelphia\nIllustration by @JoeLongSanDiego")+
    theme_economist()

highchart() %>% 
    hc_chart(type = "column") %>%
    hc_xAxis(categories = indicator$date) %>%
    hc_add_series(name="All Employment",data = indicator$value) %>% 
    #hc_add_series(name="Female _ Software Developers",data = indicator$female) %>%
  hc_subtitle(text=str_glue("From {min(indicator$date)} through {max(indicator$date)} \nFED District 3 only"), align = "center") %>%
     hc_title(text = "Future Capital Expenditures _ Diffusion Index ",
             style = list(fontWeight = "bold", fontSize = "20px"),
             align = "center")  %>%
  hc_credits(enabled = TRUE,text = "Data Source: FRED Philadelphia Federal Reserve _ Illustration by @JoeLongSanDiego") %>%
   hc_yAxis(title = list(text = "Index")) %>%
    hc_add_theme(hc_theme_economist())

Current Employment; Diffusion Index (NECDFSA066MSFRBPHI)

Federal Reserve District 3: Philadelphia

indicator <- fredr(series_id = "NECDFSA066MSFRBPHI", observation_start = as.Date("2010-01-01"))


ggplot(data = indicator, mapping = aes(x = date, y = value)) +
   geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('05-01-2021'), ymin = -Inf, ymax = Inf),
                   fill = "lightyellow", alpha = 0.02)+
   geom_line(mapping = aes(x=date,y=value), 
                              color = "blue4") +
    labs(title = "Current Employment _ Diffusion Index", 
       subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}\nFED District 3 only"),
       x="Monthly", y="Index",
       caption = " Changes in employment compared to the previous month\nData source: Federal Reserve Bank of Philadelphia.   Illustration by @JoeLongSanDiego")+
    theme_economist()

tail(indicator,n=12) %>%
  ggplot(mapping = aes(x = date, y = value)) +
  
   geom_line(mapping = aes(x=date,y=value), 
                              color = "blue4") +
    labs(title = "Current Employment _ Diffusion Index", 
       subtitle = "Past 12 months\nFED District 3 only",
       x="Monthly", y="Index",
       caption = "Current Employment _ Diffusion Index\nData source: Federal Reserve Bank of Philadelphia\nIllustration by @JoeLongSanDiego")+
    theme_economist()

highchart() %>% 
    hc_chart(type = "column") %>%
    hc_xAxis(categories = indicator$date) %>%
    hc_add_series(name="Index",data = indicator$value) %>% 
    #hc_add_series(name="Female _ Software Developers",data = indicator$female) %>%
  hc_subtitle(text=str_glue("From {min(indicator$date)} through {max(indicator$date)} \nFED District 3 only"), align = "center") %>%
     hc_title(text = "Current Employment _ Diffusion Index ",
             style = list(fontWeight = "bold", fontSize = "20px"),
             align = "center")  %>%
  hc_credits(enabled = TRUE,text = "Data Source: FRED Philadelphia Federal Reserve _ Illustration by @JoeLongSanDiego") %>%
   hc_yAxis(title = list(text = "Index")) %>%
    hc_add_theme(hc_theme_economist())

Current New Orders; Diffusion Index (NOCDFNA066MNFRBPHI)

Federal Reserve District 3: Philadelphia

• Current New Orders reports the change in new orders compared to the previous month for reporting manufacturing firms.
• The diffusion index is calculated by taking the percent reporting increases and subtracting the percentage reporting decreases

indicator <- fredr(series_id = "NOCDFNA066MNFRBPHI", observation_start = as.Date("2010-01-01"))


ggplot(data = indicator, mapping = aes(x = date, y = value)) +
   geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-05-2021'), ymin = -Inf, ymax = Inf),
                   fill = "lightyellow", alpha = 0.02)+
   geom_line(mapping = aes(x=date,y=value), 
                              color = "blue4") +
    labs(title = "New Orders _ Diffusion Index", 
       subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}\nFED District 3 only"),
       x="Monthly", y="Index",
       caption = "Data source: Federal Reserve Bank of Philadelphia.   Illustration by @JoeLongSanDiego\nrpubs.com/Data_Panoramic")+
    theme_economist()

tail(indicator,n=12) %>%
  ggplot(mapping = aes(x = date, y = value)) +
   
   geom_line(mapping = aes(x=date,y=value), 
                              color = "blue4") +
    labs(title = "Future Capital Expenditures _ Diffusion Index", 
       subtitle = "Past 12 months\nFED District 3 only",
       x="Monthly", y="Index",
       caption = "Data source: Federal Reserve Bank of Philadelphia\nIllustration by @JoeLongSanDiego\nrpubs.com/Data_Panoramic")+
    theme_economist()

highchart() %>% 
    hc_chart(type = "column") %>%
    hc_xAxis(categories = indicator$date) %>%
    hc_add_series(name="All Employment",data = indicator$value) %>% 
    #hc_add_series(name="Female _ Software Developers",data = indicator$female) %>%
  hc_subtitle(text=str_glue("From {min(indicator$date)} through {max(indicator$date)} \nFED District 3 only"), align = "center") %>%
     hc_title(text = "Future Capital Expenditures _ Diffusion Index ",
             style = list(fontWeight = "bold", fontSize = "20px"),
             align = "center")  %>%
  hc_credits(enabled = TRUE,text = "Data Source: FRED Philadelphia Federal Reserve _ Illustration by @JoeLongSanDiego") %>%
   hc_yAxis(title = list(text = "Index")) %>%
    hc_add_theme(hc_theme_economist())

Current Delivery Time; Diffusion Index (DTCDFNA066MNFRBPHI)

Federal Reserve District 3: Philadelphia

• Current Delivery Time reports the change in delivery time compared to the previous month for reporting manufacturing firms.
• The diffusion index is calculated by taking the percent reporting increases and subtracting the percentage reporting decreases.

indicator <- fredr(series_id = "DTCDFNA066MNFRBPHI", observation_start = as.Date("2010-01-01"))


ggplot(data = indicator, mapping = aes(x = date, y = value)) +
   geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-05-2021'), ymin = -Inf, ymax = Inf),
                   fill = "lightyellow", alpha = 0.02)+
   geom_line(mapping = aes(x=date,y=value), 
                              color = "blue4") +
    labs(title = "Current Delivery Time; Diffusion Index", 
       subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}\nFED District 3 only"),
       x="Monthly", y="Index",
       caption = "Data source: Federal Reserve Bank of Philadelphia.   Illustration by @JoeLongSanDiego\nrpubs.com/Data_Panoramic")+
    theme_economist()

tail(indicator,n=12) %>%
  ggplot(mapping = aes(x = date, y = value)) +
   
   geom_line(mapping = aes(x=date,y=value), 
                              color = "blue4") +
    labs(title = "Current Delivery Time; Diffusion Index", 
       subtitle = "Past 12 months\nFED District 3 only",
       x="Monthly", y="Index",
       caption = "Data source: Federal Reserve Bank of Philadelphia\nIllustration by @JoeLongSanDiego\nrpubs.com/Data_Panoramic")+
    theme_economist()

highchart() %>% 
    hc_chart(type = "column") %>%
    hc_xAxis(categories = indicator$date) %>%
    hc_add_series(name="All Employment",data = indicator$value) %>% 
    #hc_add_series(name="Female _ Software Developers",data = indicator$female) %>%
  hc_subtitle(text=str_glue("From {min(indicator$date)} through {max(indicator$date)} \nFED District 3 only"), align = "center") %>%
     hc_title(text = "Current Delivery Time; Diffusion Index for Federal Reserve District 3 ",
             style = list(fontWeight = "bold", fontSize = "20px"),
             align = "center")  %>%
  hc_credits(enabled = TRUE,text = "Data Source: FRED Philadelphia Federal Reserve _ Illustration by @JoeLongSanDiego") %>%
   hc_yAxis(title = list(text = "Index")) %>%
    hc_add_theme(hc_theme_economist())

Current Employment; Diffusion Index (NECDFNA066MNFRBPHI)

Federal Reserve District 3: Philadelphia

• Current Employment reports the change in employment compared to the previous month for reporting manufacturing firms.
• The diffusion index is calculated by taking the percent reporting increases and subtracting the percentage reporting decreases.

indicator <- fredr(series_id = "NECDFNA066MNFRBPHI", observation_start = as.Date("2010-01-01"))


ggplot(data = indicator, mapping = aes(x = date, y = value)) +
   geom_rect(aes(xmin= dmy('01-01-2020'), xmax=dmy('01-05-2021'), ymin = -Inf, ymax = Inf),
                   fill = "lightyellow", alpha = 0.02)+
   geom_line(mapping = aes(x=date,y=value), 
                              color = "blue4") +
    labs(title = "Current Employment; Diffusion Index ", 
       subtitle = str_glue("From {min(indicator$date)} through {max(indicator$date)}\nFED District 3 only"),
       x="Monthly", y="Index",
       caption = "Data source: Federal Reserve Bank of Philadelphia.   Illustration by @JoeLongSanDiego\nrpubs.com/Data_Panoramic")+
    theme_economist()

tail(indicator,n=12) %>%
  ggplot(mapping = aes(x = date, y = value)) +
   
   geom_line(mapping = aes(x=date,y=value), 
                              color = "blue4") +
    labs(title = "Current Employment; Diffusion Index ", 
       subtitle = "Past 12 months\nFED District 3 only",
       x="Monthly", y="Index",
       caption = "Data source: Federal Reserve Bank of Philadelphia\nIllustration by @JoeLongSanDiego\nrpubs.com/Data_Panoramic")+
    theme_economist()

highchart() %>% 
    hc_chart(type = "column") %>%
    hc_xAxis(categories = indicator$date) %>%
    hc_add_series(name="All Employment",data = indicator$value) %>% 
    #hc_add_series(name="Female _ Software Developers",data = indicator$female) %>%
  hc_subtitle(text=str_glue("From {min(indicator$date)} through {max(indicator$date)} \nFED District 3 only"), align = "center") %>%
     hc_title(text = "Current Employment; Diffusion Index for Federal Reserve District 3 ",
             style = list(fontWeight = "bold", fontSize = "20px"),
             align = "center")  %>%
  hc_credits(enabled = TRUE,text = "Data Source: FRED Philadelphia Federal Reserve _ Illustration by @JoeLongSanDiego") %>%
   hc_yAxis(title = list(text = "Index")) %>%
    hc_add_theme(hc_theme_economist())