Abstract #301888

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JSM 2003 Abstract #301888
Activity Number: 55
Type: Contributed
Date/Time: Sunday, August 3, 2003 : 4:00 PM to 5:50 PM
Sponsor: Business & Economics Statistics Section
Abstract - #301888
Title: Finite Sample Simulation-Based Inference in Vector Autoregressive Models
Author(s): Jouini Tarek*+ and Jean-Marie Dufour
Companies: University of Montreal and Universite De Montreal
Address: C.P. 6128 Succursale Centre-ville, Montreal, PQ, H3C 3J7, Canada
Keywords: time series ; maximized Monte Carlo test ; VAR ; exact test ; bootstrap ; Monte Carlo test
Abstract:

Statistical inference in vector autoregressive (VAR) models is typically based on large-sample approximations, involving the use of asymptotic distributions or bootstrap techniques. After documenting that such methods can be very misleading even with realistic sample sizes, especially when the number of lags or the number of equations is not small, we propose a general simulation-based technique that allows one to control completely the level of tests in parametric VAR models. In particular, we show that maximized Monte Carlo tests (Dufour 2001) can provide provably exact tests for such models, whether they are stationary or integrated. Tests of noncausality and cointegration hypotheses are considered as special cases. The technique developed is applied to a VAR model of the U.S. economy.

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