Sieve inference on possibly misspecified semi-nonparametric time series models

A-Tier
Journal: Journal of Econometrics
Year: 2014
Volume: 178
Issue: P3
Pages: 639-658

Score contribution per author:

1.341 = (α=2.01 / 3 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

This paper establishes the asymptotic normality of plug-in sieve M estimators of possibly irregular functionals of semi-nonparametric time series models. We show that, even when the sieve score process is not a martingale difference sequence, the asymptotic variance in the case of irregular functionals is the same as those for independent data. Using an orthonormal series long run variance estimator, we construct a “pre-asymptotic” Wald statistic and show that it is asymptotically F distributed. Simulations indicate that our “pre-asymptotic” Wald test with F critical values has more accurate size in finite samples than the conventional Wald test with chi-square critical values.

Technical Details

RePEc Handle
repec:eee:econom:v:178:y:2014:i:p3:p:639-658
Journal Field
Econometrics
Author Count
3
Added to Database
2026-01-25