2012
DOI: 10.1111/j.1467-9957.2012.02270.x
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Testing for Unit Roots in Panel Time‐series Models With Multiple Level Breaks*

Abstract: This paper proposes two new unit root tests that are appropriate in the presence of an unknown number of structural breaks in the level of the data. One is based on a single time series and the other is based on a panel of multiple series. For the estimation of the number of breaks and their locations, a simple procedure based on outlier detection is proposed. The limiting distributions of the tests are derived and evaluated in small samples using simulation experiments. The implementation of the tests is illu… Show more

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Cited by 11 publications
(5 citation statements)
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“…Testing for unit roots is essential for determining if and how frequently time series data should be differentiated [167]. The unit-roots test is essential for determining the stationarity of the data in time series analysis [168][169][170].…”
Section: Unit Root Testmentioning
confidence: 99%
“…Testing for unit roots is essential for determining if and how frequently time series data should be differentiated [167]. The unit-roots test is essential for determining the stationarity of the data in time series analysis [168][169][170].…”
Section: Unit Root Testmentioning
confidence: 99%
“…Denklemi elde edilir. Burada; 𝜉(κ) ve 𝜁(κ), κ. Frekanstaki bireysel istatistiklerin sırasıyla ortalama ve varyansların ortalamasını ifade etmektedir ve bu değerler, kapalı form ifadesi mevcut değilse, test istatistiğinin sınırlayıcı dağılımına ilişkin Monte Carlo simülasyonu gerçekleştirilerek elde edilebilir (Westerlund, 2012).…”
Section: Metodolojiunclassified
“…denklemi elde edilmektedir. Burada; (κ) ve (κ), κ. frekanstaki bireysel istatistiklerin sırasıyla ortalama ve varyansların ortalamasını ifade etmektedir ve bu değerler, kapalı form ifadesi mevcut değilse, test istatistiğinin sınırlayıcı dağılımına ilişkin Monte Carlo simülasyonu gerçekleştirilerek elde edilmektedir (Westerlund, 2012).…”
Section: Veri Setiunclassified