<abstract xmlns="http://www.w3.org/1999/xhtml"><p> We introduce a method that eliminates the specification error and spurious relationships in regression. In addition, we introduce a test of strong causality. Furthermore, hypothesis testing (inference) becomes almost unneeded. Moreover, this method virtually resolves error problems such as heteroscedasticity, autocorrelation, non-stationarity and endogeneity.</p></abstract>

We introduce a method that eliminates the specification error and spurious relationships in regression. In addition, we introduce a test of strong causality. Furthermore, hypothesis testing (inference) becomes almost unneeded. Moreover, this method virtually resolves error problems such as heteroscedasticity, autocorrelation, non-stationarity and endogeneity.

The perfect regression and causality test: A solution to regression problems

Biometrical Letters

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"The perfect regression and causality test: A solution to regression problems"}

We introduce a method that eliminates the specification error and spurious relationships in regression. In addition, we introduce a test of strong causality....

The perfect regression and causality test: A solution to regression problems

Online veröffentlicht: 22. Juni 2018

Seitenbereich: 45 - 48

DOI: https://doi.org/10.2478/bile-2018-0004

Schlüsselwörter
spurious regression, strong causality, specification error

© 2018 Moawia Alghalith, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

The perfect regression and causality test: A solution to regression problems

Online veröffentlicht: 22. Juni 2018

Seitenbereich: 45 - 48

DOI: https://doi.org/10.2478/bile-2018-0004

Schlüsselwörterspurious regression, strong causality, specification error

© 2018 Moawia Alghalith, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
spurious regression, strong causality, specification error