The goal of this supervision is to learn to use R to analyse the relationship between economic growth and various factors.

Using the data set called ‘USMacroG’, prepare plots to analyse the relationship between macroeconomic variables.

An example code is displayed below.

# Set CRAN mirror
options(repos = "https://cloud.r-project.org")

# Install and load the AER and tidyverse packages without displaying the output
install.packages(c("AER", "tidyverse")) 
library(AER)
library(tidyverse)


# Load the USMacroG data

data("USMacroG")

# Convert data to a data frame and calculate economic growth using the data

data <- as.data.frame(USMacroG) %>% mutate(growth = gdp / lag(gdp) - 1)

data = data %>% dplyr::select(growth, inflation, interest, unemp)
# Code to make a plot

plot(data$inflation, data$growth, xlab = "Inflation", ylab = "Growth", main = "Relationship between Inflation and Growth")

# Add a line of best fit
fit <- lm(growth ~ inflation, data = data) 
abline(fit, col = "red")

Adapt the code above to analyse the empirical relationship between interest rates, unemployment, inflation and GDP growth.

Save your plots and export them into a text document. Write down an analysis of each graph.

Bonus question: use the ‘GrowthSW’ data set to analyse the relationship between economic growth and the other variables in the data set. As well as using plots, use a regression incorporating all of the variables. This will allow you to see what variables are associated with growth after accounting for the other variables. (Hint: use the lm() function)