Introduction to Econometrics: Exercises
5. Real log returns. You are given a data frame, data, which contains the variables, log_real_returns
and log_inflation_rate for the period between 2011 and 2021.
The real log return is computed as follows:
\[ real\_log\_return_{t} = log\_return_{t} - log\_inflation_{t}\]
dates <- c("2012-01-01","2013-01-01","2014-01-01","2015-01-01","2016-01-01",
"2017-01-01","2018-01-01","2019-01-01","2020-01-01","2021-01-01")
log_return <- c(-0.031904211,0.028994207,-0.264031081,-0.15822276,0.160653519,
0.051089674,-0.126810388,0.13166768,-0.101928956,0.192571489)
log_inflation <- c(0.007574986,0.006520971,0.002827248,0.002765125,0.008816409,
0.009153037,0.008239028,0.009713099,0.005515779,0.02977545)
data <- data.frame(
dates <- dates,
log_return = log_return,
log_inflation = log_inflation
)
# Calculate the real log return.
real_log_return <- data$___ - ___
# Add real log return to data frame.
___$real_log_return <- ___
# Plot histogram of real log returns.
___(data$real_log_return)
# Calculate the real log return.
real_log_return <- data$log_return - data$log_inflation
# Add real log return to data frame.
data$real_log_return <- real_log_return
# Plot histogram of real log returns.
hist(data$real_log_return)
test_error()
test_object("real_log_return", incorrect_msg="Did you the correct variables to compute `real_log_return`?")
test_function("hist", incorrect_msg="Recall that you can create a histogram with the `hist()` function.")
success_msg("Well done! Notice that you can compute the real log return exactly from the log return and log inflation.")
Did you the correct variables to compute
real_log_return?Previous Exercise Next Exercise