Skip to contents

Wissel data on outstanding mortgage debt.

Usage

data("Wissel")

Format

A data frame with 17 observations on the following 6 variables:

t

Year.

D

Outstanding mortgage debt (dependent variable).

cte

Intercept.

C

Personal consumption (trillions of dollars).

I

Personal income (trillions of dollars).

CP

Outstanding consumer credit (trillions of dollars).

References

Wissel, J. (2009). A new biased estimator for multivariate regression models with highly collinear variables. Ph.D. thesis, Erlangung des naturwissenschaftlichen Doktorgrades der Bayerischen Julius-Maximilians-Universität Würzburg, url: https://opus.bibliothek.uni-wuerzburg.de/opus4-wuerzburg/frontdoor/deliver/index/docId/2949/file/wissel.pdf.

Examples

  head(Wissel, n=5)
#>      t      D cte      C      I     CP
#> 1 1996 3.8051   1 4.7703 4.8786 808.23
#> 2 1997 3.9458   1 4.7784 5.0510 798.03
#> 3 1998 4.0579   1 4.9348 5.3620 806.12
#> 4 1999 4.1913   1 5.0998 5.5585 865.65
#> 5 2000 4.3585   1 5.2907 5.8425 997.30
  y = Wissel[,2]
  x = Wissel[,3:6]
  multicollinearity(y, x)
#>          RVIFs           c0           c3 Scenario Affects
#> 1 1.948661e+02 7.371069e+00 1.017198e+00      b.1     Yes
#> 2 3.032628e+01 4.456018e+00 9.157898e-01      b.1     Yes
#> 3 4.765888e+00 2.399341e+00 1.053598e+01      b.2      No
#> 4 3.821626e-05 2.042640e-06 7.149977e-04      b.2      No