Modified-Likelihood Estimation of Fixed-Effect Models for Dyadic Data

Koen Jochmans

Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge

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. This setup covers the ß-model of network formation and generalizations thereof. The maximum-likelihood estimator of such models has bias and standard deviation of O(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. We apply the modifications to versions of the ß-model for network formation and of the Bradley-Terry model for paired comparisons.

Keywords: asymptotic bias; ß-model; Bradley-Terry model; dyadic data; fixed effects; modified profile likelihood; paired comparisons; matching; network formation; undirected random graph (search for similar items in EconPapers)
Date: 2019-06-25
New Economics Papers: this item is included in nep-ecm and nep-net
Note: kj345
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Citations: View citations in EconPapers (1)

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Related works:
Working Paper: Modified-likelihood estimation of fixed-effect models for dyadic data (2024)
Journal Article: Modified-likelihood estimation of fixed-effect models for dyadic data (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:cam:camdae:1958

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