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Testing for Correlation in Error-Component Models

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  • Jochmans, K.

Abstract

This paper concerns linear models for grouped data with group-specific effects. We construct a test for the null of no within-group correlation beyond that induced by the group-specific effect. The approach tests against correlation of arbitrary form while allowing for (conditional) heteroskedasticity. Our setup covers models with exogenous, predetermined, or endogenous regressors. We provide theoretical results on size and power under asymptotics where the number of groups grows but their size is held fixed. In simulation experiments we find good size control and high power in a wide range of designs. We also find that our test is more powerful than the popular test developed by Arellano and Bond (1991), which uses only a subset of the information used by our procedure.

Suggested Citation

  • Jochmans, K., 2019. "Testing for Correlation in Error-Component Models," Cambridge Working Papers in Economics 1910, Faculty of Economics, University of Cambridge.
  • Handle: RePEc:cam:camdae:1910
    Note: kj345
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    Cited by:

    1. Jochmans, Koen, 2023. "Many (Weak) Judges in Judge-Leniency Designs," TSE Working Papers 23-1481, Toulouse School of Economics (TSE).

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    More about this item

    Keywords

    analysis of variance; clustered standard errors; error components; fixed; heteroskedasticity; within-group correlation; Portmanteau test; short panel data;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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