Ramsey RESET test

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In statistics, the Ramsey Regression Equation Specification Error Test (RESET) test (Ramsey, 1969) is a general specification test for the linear regression model. More specifically, it tests whether non-linear combinations of the fitted values help explain the response variable. The intuition behind the test is that if non-linear combinations of the explanatory variables have any power in explaining the response variable, the model is mis-specified.

Technical summary[edit]

Consider the model

\hat{y}=E\{y|x\}=\beta x.

The Ramsey test then tests whether (\beta x)^2, (\beta x)^3...,(\beta x)^k has any power in explaining y. This is executed by estimating the following linear regression

y=\alpha x + \gamma_1\hat{y}^2+...+\gamma_{k-1}\hat{y}^k+\epsilon,

and then testing, by a means of a F-test whether \gamma_1~ through ~\gamma_{k-1} are zero. If the null-hypothesis that all \gamma~ coefficients are zero is rejected, then the model suffers from mis-specification.

References[edit]

  • Murteira, Bento. (2008) Introdução à Estatística, McGraw Hill.
  • Wooldridge, Jeffrey M. (2006) Introductory Econometrics - A Modern Approach, Thomson South-Western, International Student Edition.