AN ALTERNATIVE ASYMPTOTIC ANALYSIS OF RESIDUAL-BASED STATISTICS

• 成果类型: Article
• 署名作者: Andreou, Elena; Werker, Bas J. M.
• 署名单位: University of Cyprus; Tilburg University
• 刊物名称: REVIEW OF ECONOMICS AND STATISTICS
• ISSN/ISSBN: 0034-6535
• DOI: 10.1162/REST_a_00151
• 发表日期: 2012-02
• 页码: 88-99
• 关键词: Adaptive Estimation; estimators; likelihood; parameters; inference; normality; tests

摘要

This paper presents an alternative method to derive the limiting distribution of residual-based statistics. Our method does not impose an explicit assumption of (asymptotic) smoothness of the statistic of interest with respect to the model's parameters and thus is especially useful in cases where such smoothness is difficult to establish. Instead, we use a locally uniform convergence in distribution condition, which is automatically satisfied by residual-based specification test statistics. To illustrate, we derive the limiting distribution of a new functional form specification test for discrete choice models, as well as a runs-based tests for conditional symmetry in dynamic volatility models.