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Subgraph Network Random Effects Error Components Models: Specification and Testing

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  • Gabriel Montes Rojas

    (Instituto Interdisciplinario de Economía Política de Buenos Aires - UBA - CONICET)

Abstract

This paper develops a subgraph network random effects error components for network data regression models. In particular, it allows for edge and triangle specific components, which serve as a basal model for modeling network effects. It then evaluates the potential effects of ignoring network effects in the estimation of the variance-covariance matrix. It also proposes consistent estimator of the variance components and Lagrange Multiplier tests for evaluating the appropriate model of random components in networks. Monte Carlo simulations show that the tests have good performance in finite samples. It applies the proposed tests to the Call interbank market in Argentina.

Suggested Citation

  • Gabriel Montes Rojas, 2019. "Subgraph Network Random Effects Error Components Models: Specification and Testing," Documentos de trabajo del Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET) 2019-44, Universidad de Buenos Aires, Facultad de Ciencias Económicas, Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET).
    • Handle: RePEc:ake:iiepdt:201944
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    More about this item

    Keywords

    Networks; Clusters; Moulton Factor;
    All these keywords.

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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    This paper has been announced in the following NEP Reports:

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