The goal of epuR
is to provide a simple and consistent framework to
collect Economic Policy Uncertainty and related index data from their
official web locations in real time.
The official websites are listed here:
Economic Policy Uncertainty:https://www.policyuncertainty.com/china_monthly.html.
Trade Policy Uncertainty: https://www.matteoiacoviello.com/tpu.htm#data
Oxford-Man Institute Realized Volatility: https://realized.oxford-man.ox.ac.uk/
Geopolitical Risk Index: https://www.matteoiacoviello.com/gpr.htm
You can install the released version of epuR
from
CRAN with:
install.packages("epuR")
And the development version from GitHub with:
# install.packages("devtools")
devtools::install_github("Lingbing/epuR")
epuR
functions adopts a get_XXX() style to collect the index
data, where ‘XXX’ refers to the index name. For example, to get the
Economic Policy Uncertainty (EPU) index, use function get_EPU()
:
library(epuR)
## get EPU data
epu_data <- get_EPU()
class(epu_data)
#> [1] "xts" "zoo"
Every get
function returns an xts
time series object so that further
data manipulation and visualization is very straightforward if you are
familiar with operations on xts
. To plot all regions in the EPU data:
plot(epu_data)
To plot some specific region:
plot(epu_data$Australia)
dygraphs
can be directly employed to make the time series plot
interactive:
library(dygraphs)
dygraph(epu_data$China)
Currently, the following indexes are supported:
Function | Index Data | Default arguments |
---|---|---|
get_EPU |
Economic Policy Uncertainty | region = “all” |
get_EMV |
Equity Market Volatility | all = T |
get_FSI |
Financial Stress Indicator | freq = “monthly” |
get_GPR |
Geopolitical Risk Index | type = 1 |
get_IRI |
Immigration Related Index | region = “all” |
get_TPU |
Trade Policy Uncertainty | region = “China” |
get_WUI |
World Uncertainty Index | type = “F1” |
get_OMI |
Oxford-Man Institute RV | index = “AEX” |
For example, to get the FSI data:
fsi_data <- get_FSI()
dygraph(fsi_data)