R Econ Visual Library

# Install and load packages ---------------
packages <- c(
  "tidyverse",
  "haven",
  "latex2exp",
  "gridExtra",
  "lemon",
  "sciplot"
)

# Change to install = TRUE to install the required packages
pacman::p_load(packages, character.only = TRUE, install = FALSE)

# Load an example dataset ---------------
data <- read_dta("https://github.com/worldbank/r-econ-visual-library/raw/master/Library/Data/ScatterPolynomial.dta")

subdata <- data %>%
  filter(cons_pae_m_sine < quantile(.$cons_pae_m_sine, 0.99) & cons_pae_m_sine > quantile(.$cons_pae_m_sine, 0.01))

p1 <- ggplot(subdata, aes(x = cons_pae_m_sine, y = cons_pae_sd_sine)) +
      geom_point(alpha = 0.2, size = 0.5) +
      geom_smooth(aes(colour = "red"), show.legend = TRUE) +
      theme_classic() +
      scale_colour_manual(name = "", values = "red", labels = "Local Poly. & 95% CI") +
      xlab(TeX("$\\widehat{m}$")) +
      ylab(TeX("$\\widehat{s}$"))

p2 <- ggplot(subdata, aes(x = cons_pae_m_sine, y = cv)) +
      geom_point(alpha = 0.2, size = 0.5) +
      geom_smooth(aes(colour = "red"), show.legend = TRUE) +
      theme_classic() +
      scale_colour_manual(name = "", values = "red", labels = "Local Poly. % 95% CI") +
      xlab(TeX("$\\widehat{m}$")) +
      ylab(TeX("$\\widehat{s} / \\widehat{m}$"))

grid_arrange_shared_legend(p1, p2, position = "bottom")

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'