Article2000

Residual-Based Tests for Normality in Autoregressions: Asymptotic Theory and Simulation Evidence

74 citations0/0 files storedJournal of Business and Economic Statistics

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Monetary Policy and Economic Impact Statistical Distribution Estimation and Applications Financial Risk and Volatility Modeling

Abstract

Existing results for the asymptotic validity of the Jarque–Bera test in vector autoregressive (VAR) models assume stationarity. In applied work, however, researchers often work with possibly integrated and cointegrated process. We prove the asymptotic validity of the Jarque–Bera test for vector error-correction (VEC) models and for unrestricted VAR models with possibly integrated or cointegrated variables. We also propose the use of bootstrap critical values in stationary VAR models and in VEC models. We show that the bootstrap version of the Jarque–Bera test is considerably more accurate in small samples than the asymptotic test, even for processes with roots close to unity.

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References

1987Co-Integration and Error Correction: Representation, Estimation, and Testing 1986Generalized autoregressive conditional heteroskedasticity 1988Statistical analysis of cointegration vectors 1990MAXIMUM LIKELIHOOD ESTIMATION AND INFERENCE ON COINTEGRATION — WITH APPLICATIONS TO THE DEMAND FOR MONEY 1991Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models 2002Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis 1995Likelihood-Based Inference in Cointegrated Vector Autoregressive Models 1995Inside the Black Box: The Credit Channel of Monetary Policy Transmission

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