GDP Nowcast v. 10-yrs

gistfile1.txt

# Inspired by the work of Rich Falk-Wallace

library(tidyverse)
library(tidyquant)
library(timetk)
library(readxl)
library(plotly)
library(scales)
library(formattable)


url <- 
  "https://www.atlantafed.org/-/media/documents/cqer/researchcq/gdpnow/GDPTrackingModelDataAndForecasts.xlsx"
destfile <- "GDPTrackingModelDataAndForecasts.xlsx"
curl::curl_download(url, destfile)

treasury_fred_symbols <- 
  tibble(
    symbol = c("DGS1MO","DGS3MO", 
               "DGS1", "DGS2", 
               "DGS5", "DGS10", 
               "DGS30" ),
    name = c("one_month","three_month", 
             "one_year", "two_year", 
             "five_year", "ten_year", 
             "thirty_year") %>% 
      as_factor()
  )

treasury_data <- 
treasury_fred_symbols %>% 
  tq_get(get = "economic.data", from = "1979-01-01") %>% 
  rename(yield = price) %>% 
  mutate(yield = yield/100)


read_excel(destfile, sheet = "Contributions",
    skip = 1)  %>% 
  clean_names() %>% 
select(date, `GDP Nowcast`=  gdp_forecast) %>% 
  mutate(`GDP Nowcast` = `GDP Nowcast`/100, 
         date = ymd(date)) %>% 
  left_join(
    treasury_data %>% 
    filter(str_detect(name, "ten")) %>% 
  select(date, `10-YR Yield` = yield) 
  ) %>% 
  fill(`10-YR Yield`, .direction = c("down")) %>% 
  pivot_longer(-date) %>% 
  filter(date >= "2013-01-01") %>% 
  mutate(value = case_when(date <= "2022-02-01" & date >= "2020-01-01" ~ NA_real_, 
                           TRUE ~ value)
         ) %>% 
ggplot(aes(x = date, y = value, color = name)) +
  geom_line() +
  scale_color_manual(values = c("orange", "steelblue")) +
  theme_minimal() +
  scale_y_continuous(labels = percent_format(accuracy = 1),
                     breaks = pretty_breaks(n = 10)) +
  scale_x_date(date_labels = "%b %Y",
               date_breaks = "13 months") +
  labs(x = "", y = "", title = "GDP Now v. 10-yr (2014-Present)",
       color = "", caption = "Source: Rich Falk-Wallace") +
  theme(plot.title = element_text(hjust = .5), 
        legend.position = c(.68, .88))