How useful is yet another data-driven bandwidth in long-run variance estimation?:A simulation study on cointegrating regressions

Masayuki Hirukawa

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How useful is yet another data-driven bandwidth in long-run variance estimation?:A simulation study on cointegrating regressions

机译：长期方差估计中另一种数据驱动的带宽有多有用？：关于协整回归的模拟研究

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摘要

This paper investigates how bandwidth choice rules in long-run variance estimation affect finite-sample performance of efficient estimators for cointegrating regression models. Monte Carlo results indicate that Hirukawa's (2010) bandwidth choice rule contributes bias reduction in the estimators.

机译：本文研究了长期方差估计中的带宽选择规则如何影响用于协整回归模型的有效估计器的有限样本性能。蒙特卡洛的结果表明，Hirukawa（2010）的带宽选择规则有助于降低估计量的偏差。

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来源
《Economics letters》 |2011年第2期|p.170-172|共3页
作者
Masayuki Hirukawa;
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作者单位

Faculty of Economics, Setsunan University, 17-8 Ikeda Nakamachi, Neyagawa, Osaka, 572-8508, Japan;

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原文格式 PDF
正文语种 eng
中图分类
关键词
bandwidth; cointegration; kernel; long-run variance; simulation;

机译：带宽;协整核心;长期差异;模拟;

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How useful is yet another data-driven bandwidth in long-run variance estimation?:A simulation study on cointegrating regressions

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