On the Limiting Distribution of Sieve VAR(∞) Estimators in Small Samples
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When a finite order vector autoregressive model is fitted to VAR(∞) data the asymptotic distribution of statistics obtained via smooth functions of least-squares estimates requires care. Lütkepohl and Poskitt (1991) provide a closed-form expression for the limiting distribution of (structural) impulse responses for sieve VAR models based on the Delta method. Yet, numerical simulations have shown that confidence intervals built in such way appear overly conservative. In this note I argue that these results stem naturally from the limit arguments used in Lütkepohl and Poskitt (1991), that they manifest when sieve inference is improperly applied, and that they can be "remedied" by either using bootstrap resampling or, simply, by using standard (non-sieve) asymptotics.
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