Double robust inference for continuous updating GMM

B-Tier
Journal: Quantitative Economics
Year: 2025
Volume: 16
Issue: 1
Pages: 295-327

Authors (2)

Frank Kleibergen (not in RePEc) Zhaoguo Zhan (Kennesaw State University)

Score contribution per author:

1.005 = (α=2.01 / 2 authors) × 1.0x B-tier

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

Abstract

We propose the double robust Lagrange multiplier (DRLM) statistic for testing hypotheses specified on the minimizer of the population continuous updating objective function. The (bounding) χ2 limiting distribution of the DRLM statistic is robust to both misspecification and weak identification, hence its name. The minimizer is the so‐called pseudo‐true value, which equals the true value of the structural parameter under correct specification. To emphasize its importance for applied work where misspecification and weak identification are common, we use the DRLM test to analyze: the risk premia in Adrian et al. (2014) and He et al. (2017); the structural parameters in a nonlinear asset pricing model with constant relative risk aversion.

Technical Details

RePEc Handle
repec:wly:quante:v:16:y:2025:i:1:p:295-327
Journal Field
General
Author Count
2
Added to Database
2026-01-29