Testing For A Unit Root In Panels With Dynamic Factors

By H. R. Moon, B. Perron. 2004

1,082 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/e1316d6d99adff382c7f3650c8d74c6452aeb3a2

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Citations in the corpus

Testing for Convergence in Carbon Dioxide Emissions Using a Century of Panel Data (2008, methodology): “By contrast, Moon and Perron (2004) take the alternative approach and assume a common autoregressive parameter φ for all countries, so that a rejection should be interpreted as evidence of convergence for the panel as a whole. This difference in interpretation makes both approaches interesting. Moon”
Unit Roots and Cointegration in Panels (2005, methodology): “The simulations carried out by Gengenbach, Palm and Urbain (2004) show that in general, the mean CADF test has better size properties than the test of Moon and Perron (2004), which tends to be conservative in small samples.”
PANEL UNIT ROOT TESTS WITH CROSS-SECTION DEPENDENCE: A FURTHER INVESTIGATION (2009, methodology): “By Lemma 4, the result continues to hold when ẽit is replaced by êit and (σ̄ 2N , ω̄ 2 N ) is replaced by (σ̂ 2ε , ω̂ 2 ε ) because √ N (σ̂ 2ε − σ̄ 2N ) = op(1) and √ N (ω̂2ε − ω̄2N ) = op(1); see Moon and Perron (2004).”
Estimation of fractionally integrated panels with fixed effects and cross-section dependence (2015, neutral): “Similarly, Moon and Perron (2004) propose the use of dynamic factors for unit-root testing for panels with cross-section dependence.”
A Simple Panel Unit‐Root Test with Smooth Breaks in the Presence of a Multifactor Error Structure (2016, neutral): “(Chang, 2002; Phillips and Sul, 2003; Bai and Ng, 2004; Moon and Perron, 2004; Smith et al., 2004; Breitung and Das, 2003; Choi and Chue, 2007; Pesaran, 2007; Pesaran et al., 2009, 2012, 2013).”
Unit Root Testing in Heteroscedastic Panels Using the Cauchy Estimator (2012, background): “We demonstrate in the following that many popular secondgeneration panel unit root tests (e.g., Moon and Perron 2004; Breitung and Das 2005; Demetrescu, Hassler, and Tarcolea 2006; Pesaran 2007) do not control size under unconditional heteroscedasticity in the time dimension.”
The Stochastic Convergence of CO2 Emissions: A Long Memory Approach (2010, background): “Our results tell a story that is also different from Westerlund and Basher (2008 )( WB hereafter) who using the panel based tests byPhillips and Sul(2003),Bai and Ng(2004), and Moon and Perron (2004) , conclude that they have strong evidence of convergence for all the units of their two panels of 1”
The Performance of Panel Unit Root and Stationarity Tests: Results from a Large Scale Simulation Study (2006, background): “These include Bai and Ng ( 2004 ), Chang ( 2002 ), Choi ( 2002 ), Moon and Perron ( 2004 ), and Pesaran ( 2003 ).”
Large Dimensional Factor Analysis (2008, methodology): “The statistics Pa,b are the analog of ta,b of Moon and Perron (2004), except that (i) the tests are based on PANIC residuals and (ii) the method of “defactoring” of the data is different from MP. Improved versions of the tests can also be obtained by iteration. As discussed in Bai and Ng (2006d), it”
Panel Unit Root Tests and Spatial Dependence (2006, neutral): “factor models, see Bai and Ng (2004), Moon and Perron (2004) and Phillips and Sul (2003).”
Financial markets, innovations and cleaner energy production in OECD countries (2018, neutral): “The recent econometrics literature developed second-generation unit root tests (Bai and Ng, 2004; Moon and Perron, 2004; Pesaran, 2007) to overcome the problem of cross-sectional dependence across the units.”