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

Author

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  • Jochmans, K.

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.

Suggested Citation

  • Jochmans, K., 2019. "Modified-Likelihood Estimation of Fixed-Effect Models for Dyadic Data," Cambridge Working Papers in Economics 1958, Faculty of Economics, University of Cambridge.
    • Handle: RePEc:cam:camdae:1958
    Note: kj345
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    Cited by:

    1. Shujie Ma & Liangjun Su & Yichong Zhang, 2020. "Detecting Latent Communities in Network Formation Models," Economics and Statistics Working Papers 12-2020, Singapore Management University, School of Economics.

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    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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