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Panel nemlineáris autoregresszív elosztott késleltetésű (Panel NARDL) modell×ARDL Határvizsgálat (Pesaran Határvizsgálat)×
TudományterületÖkonometriaÖkonometria
MódszercsaládRegression modelRegression model
Keletkezés éve2014–20182001
MegalkotóShin, Yu & Greenwood-Nimmo (2014), extended to panel settings by subsequent authorsPesaran, Shin & Smith
TípusNonlinear dynamic panel modelCointegration test / Autoregressive distributed lag model
AlapműShin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In R. C. Sickles & W. C. Horrace (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 ↗
Alternatív nevekPanel Nonlinear ARDL, panel asymmetric ARDL, panel NARDL bounds test, nonlinear panel cointegration modelPesaran bounds test, bounds testing approach, ARDL cointegration test, ARDL Sınır Testi (Pesaran Bounds Test)
Kapcsolódó44
ÖsszefoglalóPanel NARDL extends the time-series NARDL framework of Shin, Yu and Greenwood-Nimmo (2014) to a panel data setting, allowing researchers to detect asymmetric long-run and short-run relationships between variables across multiple cross-sections simultaneously. By decomposing the regressor into positive and negative partial sums, the model tests whether increases and decreases in an explanatory variable have different effects on the outcome.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.
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ScholarGateMódszerek összehasonlítása: Panel NARDL · ARDL Bounds Test. Letöltve 2026-06-17, forrás: https://scholargate.app/hu/compare