Computation and Analysis of Multiple Structural-Change Models

By Jushan Bai, Pierre Perron. 1998

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Citations in the corpus

Differentially Private Change-Point Detection (2018, background): “ted work The change-point detection problem originally arose from industrial quality control, and has since been applied in a wide variety of other contexts including climatology [LR02], econometrics [BP03], and DNA analysis [ZS12]. The problem is studied both in the oine setting, in which the algor”
The New Keynesian Phillips Curve: From Sticky Inflation to Sticky Prices (2008, methodology): “…the dates of potential change points in the NKPC are therefore unknown, we perform break tests using the methodology developed by Andrews (1993) and Andrews and Ploberger (1994), taking into account the possibility of multiple breaks through the Bai and Perron (1998, 2003) repartition procedure.”
Model selection when there are multiple breaks (2012, background): “2 Illustration of the U.S. ex-postreal interest rate Bai and Perron (2003) (hereafter BP) reconsider an application from Garcia and Perron (1996) who examine the evidence for structural change in the U.S. real interest rate (three-month treasury bill rate deflated by the CPI inflation rate).”
Another Pass-Through Bites the Dust?: Oil Prices and Inflation (2007, methodology): “We therefore test the regressions for multiple structural breaks on all parameters following Bai and Perron (1998, 2003) .”
Detecting multiple breaks in financial market volatility dynamics (2002, methodology): “The Lavielle and Moulines is a least squares type test and in order to detect multiple breaks one may apply a grid search approach or a more efficient algorithm based on dynamic programming suggested in Bellman and Roth (1969) and reintroduced in Bai and Perron (1998, 2002).”
Unit‐root testing against the alternative hypothesis of up to m structural breaks (2005, unknown): “An alternative procedure to estimate multiple breaks with reduced computational burden has recently been suggested by Bai and Perron (2000).”
Does twitter predict Bitcoin? (2019, methodology): “Therefore we split our sample into two subsamples, where the breakpoint is determined by the Bai and Perron (2003) test.”
The limit distribution of the estimates in cointegrated regression models with multiple structural changes (2008, methodology): “The estimates of the parameters can be obtained using the algorithm of Bai and Perron (2003) with no modification since the algorithm itself is valid irrespective of the nature of the regressors and errors given that it is designed to obtain estimates of the break dates that minimize the global sum…”
Market timing and return prediction under model instability (2002, background): “Bai and Perron (1998, 2001) proposed a method for estimating linear regression models subject to multiple breaks.”