Modified-likelihood estimation of fixed-effect models for dyadic data

Koen Jochmans

No 24-1502, TSE Working Papers from Toulouse School of Economics (TSE)

Abstract: We consider point estimation and inference based on modifications of the profile likelihood in models for dyadic interactions between n agents featuring agent-specific parameters. The maximum-likelihood estimator of such models has bias and standard deviation of order n-1 and so is asymptotically biased. Estimation based on modified likelihoods leads to estimators that are asymptotically unbiased and likelihood ratio tests that exhibit correct size.

Keywords: Asymptotic bias; Dyadic data; Fixed effects; Undirected random graph (search for similar items in EconPapers)
JEL-codes: C23 (search for similar items in EconPapers)
Date: 2024-01-24
New Economics Papers: this item is included in nep-dcm and nep-ecm
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Related works:
Journal Article: Modified-likelihood estimation of fixed-effect models for dyadic data (2023)
Working Paper: Modified-Likelihood Estimation of Fixed-Effect Models for Dyadic Data (2019)
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Persistent link: https://EconPapers.repec.org/RePEc:tse:wpaper:129030

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