A Critical Examination of Orthogonal Regression

40 Pages Posted: 16 Jul 2003

See all articles by Gishan Dissanaike

Gishan Dissanaike

University of Cambridge - Judge Business School

Shiyun Wang

University of Sheffield - School of Management

Abstract

The method of orthogonal regression has a long and distinguished history in statistics and economics. It has been viewed as superior to ordinary least squares in certain situations. However, our theoretical and empirical study shows that this method is flawed in that it implicitly assumes equations without the error term. A direct result is that it over-optimistically estimates the slope coefficient. It also cannot be applied to testing if there is an equal proportionate relationship between two variables, a case where orthogonal regression has been frequently used in previous research. We offer an alternative adjusted orthogonal estimator and show that it performs better than all the previous orthogonal regression models and, in most cases, better than ordinary least squares.

Keywords: Orthogonal Regression, Errors-in-Variables, OLS

JEL Classification: C20, C52

Suggested Citation

Dissanaike, Gishan and Wang, Shiyun, A Critical Examination of Orthogonal Regression. Available at SSRN: https://ssrn.com/abstract=407560 or http://dx.doi.org/10.2139/ssrn.407560

Gishan Dissanaike

University of Cambridge - Judge Business School ( email )

Trumpington Street
Cambridge, CB2 1AG
United Kingdom
+441 223 339626 (Phone)
+441 223 339701 (Fax)

Shiyun Wang (Contact Author)

University of Sheffield - School of Management ( email )

9 Mappin Street
Sheffield, S1 4DT
United Kingdom

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