Testing for PPP: Should we use panel methods?

By Anindya Banerjee, Massimiliano Marcellino, C. Osbat. 2005

366 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/9477e13644ab902185746fd93ff6e0425445ec7b

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Citations in the corpus

A Simple Panel-CADF Test for Unit Roots (2013, unknown): “However, the power gain motivation has probably been the dominating one in the majority of theoretical and applied papers and it has been questioned only recently (see e.g. Banerjee et al., 2004, 2005).”
In search of FDI-led growth in developing countries (2008, background): “Banerjee et al. (2004; 2005) show that this restriction is very likely to be violated in many macroeconomic time series because of economic links across countries.”
Panel Unit Root Tests in the Presence of Cross-Sectional Dependencies: Comparison and Implications for Modelling (2009, unknown): “δ∗ pooled = ∑T t=2 Y ′ t−1QΛ̂KYt −NTφ̂e ∑T t=2 Y ′ t−1QΛ̂KYt−1 , (9)”
Are fluctuations in energy consumption per capita transitory? Evidence from a panel of Pacific Island countries (2009, methodology): “If the data contains cross-sectional dependence across countries, it is well-recognised that these conventional panel unit root tests will show large size distortions (see O’Connell, 1998; Maddala & Wu, 1999; Strauss & Yigit, 2003; Banerjee et al., 2005).”
Panel data stochastic convergence analysis of the Mexican regions (2009, unknown): “The lack of consideration of the crosssection dependence might bias the analysis to conclude in favour of the stationarity of the panel data even in the case where it is non-stationary (O’Connell 1998; Banerjee et al. 2004,2005 ).”
Unit Root Testing in Heteroscedastic Panels Using the Cauchy Estimator (2012, unknown): “In a final set of experiments, we study the size properties of the tests under cross-unit cointegration, a dependence structure which has been shown to be challenging for many existing second-generation panel unit root tests (Banerjee et al., 2005).”
Testing for Panel Cointegration Using Common Correlated Effects Estimators (2017, methodology): “Finally, I.1/ common factors will also help to capture the existence of cross-cointegration relationship among the same variable for the different units of the panel data – see Banerjee et al. (2005).”
Une synthèse des tests de racine unitaire sur données de panel (2005, unknown): “[10] Banerjee, A.”