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Test KSS sur données de panel×ARDL Cross-Sectionnel×Test de cointégration de Maki×DF-GLS pour données de panel×
DomaineÉconométrieÉconométrieÉconométrieÉconométrie
FamilleRegression modelRegression modelRegression modelRegression model
Année d'origine1992200620121996
Auteur d'origineKwiatkowski, Phillips, Schmidt, and Shin (panel version by Hadri)Pesaran and colleaguesDarshana MakiElliott, Rothenberg, and Stock (adapted to panels)
TypeUnit-root testDynamic panel modelStructural-break testStationarity test
Source fondatriceKwiatkowski, D., Phillips, P. C., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root. Journal of Econometrics, 54(1-3), 159-178. DOI ↗Pesaran, M. H., & Smith, R. (2016). Testing weak cross-sectional dependence in large panels. Econometric Reviews, 34(6-10), 1089-1117. link ↗Maki, D. (2012). Tests for cointegration allowing for an unknown number of breaks. Economic Modelling, 29(5), 2011-2015. DOI ↗Elliott, G., Rothenberg, T. J., & Stock, J. H. (1996). Efficient tests for an autoregressive unit root. Econometric Reviews, 13(4), 469-497. DOI ↗
AliasPanel stationarity testPanel ARDL with cross-sectional dependenceStructural-break cointegration testPanel unit-root test
Apparentées3333
RésuméThe Panel KSS test reverses the null hypothesis of unit-root tests: it tests whether variables are stationary (stationarity is the null) versus nonstationary (unit root is the alternative). Introduced by Kwiatkowski et al. (1992) and extended to panels by Hadri (2000), this complementary approach provides robustness when combined with unit-root tests like Panel DF-GLS. Using both tests together reduces the risk of erroneous conclusions about variable persistence.CS-ARDL (Cross-Sectional ARDL) applies the ARDL framework to panel data while explicitly accounting for cross-sectional dependence—correlation of shocks and relationships across units (countries, firms, regions). Introduced by Pesaran and colleagues (2016), it extends panel ARDL methods to handle common factors or global shocks affecting all units simultaneously. This is crucial for realistic modeling of internationally integrated economies and firm networks.The Maki cointegration test extends cointegration testing to allow for an unknown number of endogenously-determined structural breaks in the cointegrating relationship. Introduced by Maki (2012), it builds on Gregory and Hansen (1996), enabling detection of cointegration even when relationships shift due to policy changes, institutional reforms, or fundamental regime shifts. This is essential for applied time-series work where structural change is common.Panel DF-GLS extends the Elliott, Rothenberg, and Stock (1996) GLS unit-root test to panel data, combining cross-sectional and time-series information to test whether variables contain unit roots. Introduced by Hadri and colleagues (2005), it is more powerful than standard panel unit-root tests (IPS, LLC) due to its GLS detrending approach. This test is essential for establishing stationarity before fitting cointegration or dynamic panel models.
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ScholarGateComparer des méthodes: Panel KSS · CS-ARDL · Maki Cointegration Test · Panel DF-GLS. Consulté le 2026-06-19 sur https://scholargate.app/fr/compare