pesaranData {BGVAR}

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 and pesaran.diff data sets, based on averaged trade flows covering the period 1980 to 2016 (based on tA).

tA

Three-dimensional array that contains the yearly, bilateral trade flows, which were used to construct W.8016.

peseranData

List object of length N containing

y

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 containing

y

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).