Optimally Testing General Breaking Processes in Linear Time Series Models

By Graham Elliott, Ulrich K. Mueller. 2003

50 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/66a45fe9b9ba6f553f3db21e30460d2dec1c1abd

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

In Finance

In Management Science and Operations Research

Citations in the corpus

Efficient Estimation of the Parameter Path in Unstable Time Series Models (2010, unknown): “From Lemma (1) in Elliott and Müller (2003),”
Forecasting and Estimating Multiple Change-Point Models with an Unknown Number of Change Points (2004, unknown): “If the number of break points is even moderately large, then computational costs can become overwhelming [see, for instance, the discussion in Elliott and Muller (2003) of the approach developed in Bai and Perron (1998)].”
Dealing with Structural Breaks (2005, background): “Elliott and Müller (2003) consider optimal tests for a class of models involving nonconstant coefficients which, however, rule out one-time abrupt changes.”
Confidence Sets for the Date of a Single Break in Linear Time Series Regressions (2004, background): “…Fubini’s Theorem and the likelihood structure in Condition 2, an efficient invariant test for b2 > 0 of (3) maximizing (5) can hence be based on (see Elliott and Müller (2003) for development) LRT = X t=1,··· ,τ−1,τ+1,··· ,T wt Z exp £ σ−2y0MQΞ(t)d− 12σ −2d0Ξ(t)0MQΞ(t)d ¤ dνt(d) where Ξ(t) is a T…”
Efficient Bayesian Inference for Multiple Change-Point and Mixture Innovation Models (2008, unknown): “Draw the discrete latent variables Kμ of the conditional mean part as in Gerlach et al. (2000) or with the adaptive Metropolis– Hastings sampler described in Section 6.”
Instability of Return Prediction Models (2006, methodology): “As a final test for instability we apply the J-test suggested by Elliott and Muller (2003) .”
Structural Breaks and Predictive Regression Models of Aggregate U.S. Stock Returns (2006, methodology): “…(1993) SupF statistic in concert with the Hansen (2000) heteroskedastic fixed-regressor bootstrap, as well as the recently developed Ĵ statistic of Elliott and Müller (2003), to test for a structural break at an unknown date in the parameters of 16 bivariate predictive regression models of…”
How Costly is it to Ignore Breaks When Forecasting the Direction of a Time Series? (2004, background): “Elliott and Mueller (2002) consider optimal tests for models with either many or relatively few breaks.”
How Stable is the Forecasting Performance of the Yield Curve for Output Growth (2006, methodology): “In addition, Elliott and Müller (2003) showed that traditional tests for structural breaks have power against ‘large’ breaks, but may lack power against slowly time-varying coefficients.”