Misspecification Tests in Econometrics

Abstract

Misspecification tests play an important role in detecting unreliable and inadequate economic models. This book brings together many results from the growing literature in econometrics on misspecification testing. It provides theoretical analyses and convenient methods for application. The main emphasis is on the Lagrange multiplier principle, which provides considerable unification, although several other approaches are also considered. The author also examines general checks for model adequacy that do not involve formulation of an alternative hypothesis. General and specific tests are discussed in the context of multiple regression models, systems of simultaneous equations, and models with qualitative or limited dependent variables.

Do Anger Control and Social Problem-Solving Mediate Relationships Between Difficulties in Emotion Regulation and Aggression in Adolescents?

“…Autocorrelation occurs when the residuals are not independent from each other and not linearly auto-correlated (Cohen et al, 2013). If this assumption does not occur, there is a correlation between the error terms of independent variables, and it can weaken the estimates (Godfrey, 1988). The Durbin-Watson and Breusch-Godfrey LM tests are usually the preferred tests to examine this assumption.…”

Macroeconomics and agriculture in Tunisia

“…Both subsystems are estimated including two lags 5 and a constant restricted to the cointegration space 6 . Multivariate tests for autocorrelation (Godfrey, 1988) and normality (Doornik and Hansen, 1994) have been carried out to check for model statistical adequacy before applying the reduced rank tests. Results indicated that both subsystems could be considered correctly specified 7 .…”

Externalities in Rural Development: Evidence for China

“…The test described in Jalan and Ravallion (2002) (following Godfrey, 1988) is used to test the null hypothesis that 1 = t r for all t. In estimating equation (4) The essential condition to justify this choice of instruments is that the error term in (4) is second-order serially independent, as implied by serial independence of it µ . The Arellano and Bond (1991) second-order serial correlation test is performed, given that the consistency of the estimator for the quasi-differenced model depends on the assumption that the composite error term is second-order serially independent.…”