Paper
Variance Estimation with Dependence and Heterogeneous Means
Authors
Luther Yap
Abstract
This paper considers the problem of estimating the variance of a sum of a triangular array of random vectors with heterogeneous means. When random vectors exhibit two-way cluster dependence or weak dependence, standard variance estimators designed under homogeneous means can underestimate the true variance, which results in subsequent tests being oversized. To restore validity, this paper proposes a simple conservative variance estimator robust to heterogeneous means and shows its asymptotic validity.
Metadata
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Raw Data (Debug)
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"raw_xml": "<entry>\n <id>http://arxiv.org/abs/2603.11497v1</id>\n <title>Variance Estimation with Dependence and Heterogeneous Means</title>\n <updated>2026-03-12T03:34:57Z</updated>\n <link href='https://arxiv.org/abs/2603.11497v1' rel='alternate' type='text/html'/>\n <link href='https://arxiv.org/pdf/2603.11497v1' rel='related' title='pdf' type='application/pdf'/>\n <summary>This paper considers the problem of estimating the variance of a sum of a triangular array of random vectors with heterogeneous means. When random vectors exhibit two-way cluster dependence or weak dependence, standard variance estimators designed under homogeneous means can underestimate the true variance, which results in subsequent tests being oversized. To restore validity, this paper proposes a simple conservative variance estimator robust to heterogeneous means and shows its asymptotic validity.</summary>\n <category scheme='http://arxiv.org/schemas/atom' term='econ.EM'/>\n <category scheme='http://arxiv.org/schemas/atom' term='stat.ME'/>\n <published>2026-03-12T03:34:57Z</published>\n <arxiv:primary_category term='econ.EM'/>\n <author>\n <name>Luther Yap</name>\n </author>\n </entry>"
}