Spurious regressions with high-order models: A reconsideration

Lingxiang Zhang

doi:10.1016/j.econlet.2018.04.007

Spurious regressions with high-order models: A reconsideration

Lingxiang Zhang

科研成果: 期刊稿件 › 文章 › 同行评审

1 引用（Scopus）

摘要

This paper reconsiders spurious regressions with high-order processes by using a balanced regression approach. Results show that if the balanced orders adopted in a regression model are greater than the truly largest lag of regressand and regressor data generation processes, then spurious regressions can be eliminated.

源语言	英语
页（从-至）	70-72
页数	3
期刊	Economics Letters
卷	168
DOI	https://doi.org/10.1016/j.econlet.2018.04.007
出版状态	已出版 - 7月 2018

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title = "Spurious regressions with high-order models: A reconsideration",

abstract = "This paper reconsiders spurious regressions with high-order processes by using a balanced regression approach. Results show that if the balanced orders adopted in a regression model are greater than the truly largest lag of regressand and regressor data generation processes, then spurious regressions can be eliminated.",

keywords = "Balanced regression, High-order models, Spurious regression",

author = "Lingxiang Zhang",

note = "Publisher Copyright: {\textcopyright} 2018",

year = "2018",

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doi = "10.1016/j.econlet.2018.04.007",

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AB - This paper reconsiders spurious regressions with high-order processes by using a balanced regression approach. Results show that if the balanced orders adopted in a regression model are greater than the truly largest lag of regressand and regressor data generation processes, then spurious regressions can be eliminated.

KW - Balanced regression

KW - High-order models

KW - Spurious regression

UR - https://www.scopus.com/pages/publications/85045626011

U2 - 10.1016/j.econlet.2018.04.007

DO - 10.1016/j.econlet.2018.04.007

M3 - Article

AN - SCOPUS:85045626011

SN - 0165-1765

VL - 168

SP - 70

EP - 72

JO - Economics Letters

JF - Economics Letters

ER -

Spurious regressions with high-order models: A reconsideration

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