Dealing with Structural Breaks

By Pierre Perron. 2005

888 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/9c292f7bf3cc2f3796b58a5a9ea6563aabf28bbb

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Citations in the corpus

SHRINKAGE ESTIMATION OF REGRESSION MODELS WITH MULTIPLE STRUCTURAL CHANGES (2015, methodology): “Bai, J. & P. Perron (2006) Multiple structural change models: a simulation analysis.”
Estimating Structural Changes in Regression Quantiles (2011, unknown): “Keywords: structural change, quantile regression, conditional distribution.”
A simple test of changes in mean in the possible presence of long‐range dependence (2011, background): “See Banerjee and Urga (2005) and Perron (2006) for excellent reviews of long memory and structural break from an econometric standpoint.”
Ecological thresholds and regime shifts: approaches to identification. (2009, methodology): “Econometricians have developed a range of tools for detecting step changes in linear time series models, typically called structural changes or breaks in the econometric literature (see [63] for a recent review).”
The impact of economic growth on CO2 emissions in Azerbaijan (2018, background): “Interested readers can refer to the above given references as well as Enders (2010), Perron (2006), Zivot and Andrews (1992), and Banerjee et al. (1992).”
A Non-local Perspective on the Power Properties of the CUSUM and CUSUM of Squares Tests for Structural Change (2005, methodology): “[19] Perron, P.”
Testing for Change Points in Time Series (2010, methodology): “…Statistical Association Journal of the American Statistical Association September 2010, Vol. 105, No. 491, Theory and Methods DOI: 10.1198/jasa.2010.tm10103 1228 refer the interested readers to the excellent review articles by Kokoszka and Leipus (2002) and Perron (2006) for more references.”
Selective review of offline change point detection methods (2020, background): “Historically, Opt 653 was introduced for a non-related problem [109] and later applied to change point 654 detection, in many different contexts, such as EEG recordings [65, 110], DNA 655 sequences [100, 111], tree growth monitoring [20], financial time-series [49, 76], 656 radar waveforms [112], et”
Two-Step LM Unit Root Tests with Trend-Breaks (2012, background): “A recent survey paper by Perron (2006) also recognizes this critical drawback of assuming the absence of breaks under the null and provides a warning in this regard.”
Another Pass-Through Bites the Dust?: Oil Prices and Inflation (2007, background): “…that have data throughout the 40 years of our sample, this corresponds to 23 of the 34 countries.8 We take the 23 pass-throughs 6Hansen (2001) and Perron (2005) provide a review of the literature on structural breaks and we will only briefly discuss the main intuition that sustains the method…”
Testing the structural stability of temporally dependent functional observations and application to climate projections (2011, background): “There is a large literature and long history on change point testing in scalar or vector time series (see Csörgő and Horváth [9], Perron [18] and references therein), but research on change point testing for functional data is very recent.”
Trends and random walks in macroeconomic time series: A reappraisal (2012, background): “3 Nunes et al. (1997) provide evidence that assuming no break under the null in endogenous break unit root test leads to significant rejection of the unit root null when the data generating process is a unit root with break (see Perron, 2006).”