The power of tests of predictive ability in the presence of structural breaks

By Todd E. Clark, Michael W. McCracken. 2005

106 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/18264b685cf3823ae559724de91128e9016d56b5

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Citations in the corpus

Out-of-Sample Forecast Tests Robust to the Choice of Window Size (2011, unknown): “Therefore, given the proofs of Clark and McCracken (2000), it is straightforward to extend their proofs to show that lemmas A2, A5, and A6 hold uniformly in µ ∈ [µ,µ].”
Evaluating Direct Multistep Forecasts (2005, background): “2 Clark and McCracken ( 2005a ) consider how these out-of-sample tests behave under a broad range of alternatives that include breaks in the causal relationships.”
Advances in Forecast Evaluation (2011, unknown): “To illustrate essential features, we present selected results, for the distributions of the MSE-t and MSE-F tests when the recursive sampling scheme is used, developed in Clark and McCracken (2005a).”
How Stable is the Forecasting Performance of the Yield Curve for Output Growth (2006, methodology): “…of two models, one that uses the information in the yield curve, and one that does not (i.e. according to which GDP growth is unpredictable, which has been the standard alternative used in out-of-sample forecast comparisons – see, among others, Stock and Watson, 2003; Clark and McCracken, 2005).”
Forecasting the Price of Oil (2010, unknown): “Clark and McCracken (2010) for the first time proposed a correctly specified test of the null of equal out-of-sample MSPEs.”
ARE EXCHANGE RATES REALLY RANDOM WALKS? SOME EVIDENCE ROBUST TO PARAMETER INSTABILITY (2005, background): “Even if out-of-sample tests can potentially detect both model mis-specification and parameter instability, their asymptotic local power is not the highest for the joint null hypothesis of interest.”
Advances in Forecasting Under Instability (2012, unknown): “Clark and McCracken (2005) have compared the performance of the GCT and DMWP tests with Rossi s (2005) Exp W T test and shown that the latter is always more powerful when instabilities take the form of a one-time break.”
Change-Point Monitoring in Linear Models (2006, unknown): “The second procedure is motivated by the recent work of Clark and McCracken (2005).”
FORECAST EVALUATION (methodology): “…distributions that are asymptotically free of nuisance parameters under certain additional conditions: (6.2c) one step ahead predictions and conditionally homoskedastic prediction errors, or (6.2d) the number of additional regressors in the larger model is exactly 1 [Clark and McCracken (2005a)].”
Comparing forecast accuracy: A Monte Carlo investigation (2013, methodology): “In fact, Clark and McCracken (2005b, 2009) show that breaks significantly affect the properties of tests of predictive ability and thus they may render harder the task of discriminating between competing models, and they also argue that the choice of estimation window in rolling regressions becomes…”
Selection of estimation window in the presence of breaks (2007, methodology): “Our ndings are closely related to the work by Clark and McCracken (2005) on how the power of tests of predictive ability are aaected by structural breaks.”
Testing for Smooth Structural Changes in Time Series Models via Nonparametric Regression (2012, methodology): “Examples include Chow’s (1960) single break model, Hall and Hart’s (1990) deterministic trend model, Lin and Ter .”