ScholarGate
助手

方法对比

并排查看您选择的方法;存在差异的行会高亮显示。

非线性ARDL (NARDL) 边界检验×ARDL 边界检验(Pesaran 边界检验)×
领域计量经济学计量经济学
方法族Regression modelRegression model
起源年份20142001
提出者Shin, Yu, and Greenwood-NimmoPesaran, Shin & Smith
类型Asymmetric cointegration testCointegration test / Autoregressive distributed lag model
开创性文献Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In W. C. Horrace & R. C. Sickles (Eds.), Festschrift in Honor of Peter Schmidt (pp. 281-314). Springer. DOI ↗Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds Testing Approaches to the Analysis of Level Relationships. Journal of Applied Econometrics, 16(3), 289–326. DOI ↗
别名NARDL, asymmetric ARDL, nonlinear bounds testing approach, NARDL bounds testingPesaran bounds test, bounds testing approach, ARDL cointegration test, ARDL Sınır Testi (Pesaran Bounds Test)
相关14
摘要The Nonlinear ARDL bounds test, developed by Shin, Yu, and Greenwood-Nimmo (2014), extends the linear ARDL framework to detect asymmetric long-run relationships in time series. By decomposing a regressor into positive and negative partial sums, NARDL simultaneously tests for cointegration and estimates separate long-run effects for increases and decreases — without requiring all variables to be integrated of the same order.The ARDL bounds test is an autoregressive distributed lag method that tests for a cointegrating (long-run level) relationship between time series, introduced by Pesaran, Shin and Smith in 2001. Unlike the Johansen procedure, it remains valid whether the variables are I(0), I(1) or a mix of the two, and it is more reliable than Johansen in small samples of roughly 30 to 80 observations.
ScholarGate数据集
  1. v1
  2. 2 来源
  3. PUBLISHED
  1. v1
  2. 2 来源
  3. PUBLISHED

前往搜索 下载幻灯片

ScholarGate方法对比: Nonlinear ARDL bounds test · ARDL Bounds Test. 于 2026-06-18 检索自 https://scholargate.app/zh/compare