Scholarlink

<p>This paper provides a detailed, step-by-step guide for implementing the Augmented Autoregressive Distributed Lag (A-ARDL) method, focusing on the aging-income inequality nexus in South Korea. The A-ARDL method has gained popularity in fields such as energy, development, and population economics due to its enhanced robustness in testing long-run relationships. The vital contribution of the A-ARDL model is that it complements the existing two tests in the ARDL model by incorporating an extra F-test on the lagged-level of the independent variable(s), significantly reducing the risk of spurious cointegration. Despite its advantages, a common challenge in applying the A-ARDL model is the lack of easily accessible program code. Consequently, many researchers rely on automated ARDL procedures in EViews, which often omit the additional test. To that effect, this paper offers a structured, stepwise approach to applying the A-ARDL model, enabling researchers to correctly replicate, apply, and interpret their findings for more effective policy analysis.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Methodological guide to the augmented ARDL model: step-by-step application with South Korean data

  • 期刊论文

  • 发表日期：

    2025年5月19日

查看全文
  • Muhammad Raees Shaik Saffarudin,
  • Soo Khoon Goh,
  • Robert McNown

摘要

This paper provides a detailed, step-by-step guide for implementing the Augmented Autoregressive Distributed Lag (A-ARDL) method, focusing on the aging-income inequality nexus in South Korea. The A-ARDL method has gained popularity in fields such as energy, development, and population economics due to its enhanced robustness in testing long-run relationships. The vital contribution of the A-ARDL model is that it complements the existing two tests in the ARDL model by incorporating an extra F-test on the lagged-level of the independent variable(s), significantly reducing the risk of spurious cointegration. Despite its advantages, a common challenge in applying the A-ARDL model is the lack of easily accessible program code. Consequently, many researchers rely on automated ARDL procedures in EViews, which often omit the additional test. To that effect, this paper offers a structured, stepwise approach to applying the A-ARDL model, enabling researchers to correctly replicate, apply, and interpret their findings for more effective policy analysis.