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`

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).

*BGVAR*version 2.5.5 Index]