pesaranData {BGVAR} | R Documentation |
pesaranData
Description
This data set contains quarterly observations by country, spanning the period from 1979Q2 to 2019Q4. It can be downloaded from https://www.mohaddes.org/gvar. The country coverage is 28 countries.
Usage
pesaranData
Format
The data loads pesaranData
, which is a list object of length N
(i.e, the number of countries) and contains the country-level data as described in Mohaddes and Raissi (2020). The countries are abbreviated using ISO-2 codes. Furthermore, we also provide two datasets with first differences of some variables in pesaranDiff
. dominant
contains data that is considered global. tA
is a three-dimensional array that contains N
times N
annual trade flow matrices over the period from 1980 to 2016. This array can be used to construct weight matrices. For more details, see below:
W.8016
Weight matrix for the
pesaran.level
andpesaran.diff
data sets, based on averaged trade flows covering the period 1980 to 2016 (based ontA
).tA
Three-dimensional array that contains the yearly, bilateral trade flows, which were used to construct
W.8016
.peseranData
List object of length
N
containingy
Real GDP.
Dp
Consumer price inflation.
r
Short-term interest rate, typically 3-months money market rate.
lr
Long-term interest rate.
eq
Equity prices.
ep
Exchange rate vis a vis the US dollar, deflated by the domestic CPI.
pesaranDiff
List object of length
N
containingy
Growth rate of real GDP.
Dp
First differences of consumer price inflation.
r
First differences of short-term interest rate, typically 3-months money market rate.
lr
Long-term interest rate.
eq
Equity prices.
ep
Exchange rate vis a vis the US dollar, deflated by the domestic CPI.
dominant
Data set containing global variables:
poil
Oil prices.
pmetal
Metal price index.
pmat
Agricultural price index.
References
Mohaddes, K. and M. Raissi (2018). Compilation, Revision and Updating of the Global VAR (GVAR) Database, 1979Q2-2016Q4. University of Cambridge: Faculty of Economics (mimeo).