A new accurate regression: Overcoming the specification error

Alghalith, Moawia

doi:10.2478/bile-2025-0009

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A new accurate regression: Overcoming the specification error

Biometrical Letters

Volume 62 (2025): Issue 2 (December 2025)

By: Moawia Alghalith

Open Access

|Dec 2025

Abstract

We develop a simple method that virtually eliminates the regression specification error and spurious relationships. Furthermore, we introduce a strong (real) causality test.

References

Alghalith M. (2018): The perfect regression and causality test: A solution to regression problems. Biometrical Letters 55: 45–48.
Search in Google Scholar Back to article
Alghalith M. (2019): A simple solution to the specification error. Biometrical Letters 56: 13–16. doi:10.2478/bile-2019-0002
Search in Google Scholar Back to article
Asteriou D., Hall S.G. (2011): Applied Econometrics. Palgrave MacMillan, London.
Search in Google Scholar Back to article
Golden R., Henley S., White H., Kashner T. (2016): Generalized information matrix tests for detecting model misspecification. Econometrics 4: 1–24.
Search in Google Scholar Back to article
Granger C.W.J. (1969): Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37: 424–438.
Search in Google Scholar Back to article
Maddala G.S., Lahiri K. (2009): Diagnostic checking, model selection, and specification testing. In: *Introduction to Econometrics* (4th ed.). Wiley, Chichester.
Search in Google Scholar Back to article
Phillips P.C.B. (1986): Understanding spurious regressions in econometrics. Journal of Econometrics 33: 311–340.
Search in Google Scholar Back to article
Shiffrin R.M. (2016): Drawing causal inference from big data. Proc Natl Acad Sci USA 113: 7308–7309.
Search in Google Scholar Back to article
Varian H.R. (2016): Causal inference in economics and marketing. Proc Natl Acad Sci USA 113: 7307–7315.
Search in Google Scholar Back to article