Jackknife bias reduction for simulated maximum likelihood estimator of discrete choice models

C-Tier
Journal: Economics Letters
Year: 2022
Volume: 219
Issue: C

Authors (2)

Score contribution per author:

0.503 = (α=2.01 / 2 authors) × 0.5x C-tier

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

Abstract

We propose to reduce asymptotic biases of simulated maximum likelihood estimators (SMLE) by using a jackknife method similar to Dhaene and Jochmans (2015). Because the jackknife method does not require an explicit characterization of the bias, it may be a practically attractive alternative to Lee’s (1995) estimator.

Technical Details

RePEc Handle
repec:eee:ecolet:v:219:y:2022:i:c:s0165176522002841
Journal Field
General
Author Count
2
Added to Database
2026-01-25