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# Euribor data

`euribor.Rd`

Data used in example 1 of Salmerón, García and García (2024) (subsection 4.1) on Euribor data.

## Usage

    data("euribor")

## Format

A data frame with 47 observations on the following 5 variables:

`E`

  Euribor (dependent variable, in percentage).

`cte`

  Intercept.

`HIPC`

  Harmonized index of consumer prices (in percentage).

`BC`

  Balance of payments to net current account (millions of euros).

`GD`

  Goverment deficit to net nonfinancial accounts (millions of euros).

## Details

This dataset is originally used by Salmerón, Rodríguez and García (2020).

## References

Salmerón, R., Rodríguez, A. and García, C.B. (2020). Diagnosis and quantification of the non-essential collinearity. Computational Statistics, 35(2), 647-666, doi: doi:10.1007/s00180-019-00922-x .

Salmerón, R., García, C.B. and García, J. (2025). A redefined Variance Inflation Factor: overcoming the limitations of the Variance Inflation Factor. Computational Economics, 65, 337-363, doi: doi:10.1007/s10614-024-10575-8 .

## Examples

      head(euribor, n=5)
    #>      E cte  HIPC    BC       GD
    #> 1 3.63   1 92.92 17211 -51384.0
    #> 2 3.90   1 93.85  2724 -49567.1
    #> 3 3.45   1 93.93 17232 -52128.4
    #> 4 3.01   1 94.41  9577 -53593.3
    #> 5 2.54   1 95.08  4117 -65480.0
      y = euribor[,1]
      x = euribor[,2:5]
      multicollinearity(y, x)
    #>          RVIFs           c0           c3 Scenario Affects
    #> 1 5.325408e+00 1.575871e+01 2.166907e-02      a.1      No
    #> 2 5.357830e-04 3.219456e-06 4.249359e-05      b.1     Yes
    #> 3 5.109564e-11 1.098649e-09 2.586237e-12      a.1      No
    #> 4 1.631439e-11 3.216522e-10 8.274760e-13      a.1      No