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Predictive Regressions

Jesus Gonzalo () and Jean-Yves Pitarakis ()

UC3M Working papers. Economics from Universidad Carlos III de Madrid. Departamento de Economía

Abstract: Predictive regressions are a widely used econometric environment for assessing the predictability of economic and financial variables using past values of one or more predictors. The nature of the applications considered by practitioners often involve the use of predictors that have highly persistent smoothly varying dynamics as opposed to the much noisier nature of the variable being predicted. This imbalance tends to affect the accuracy of the estimates of the model parameters and the validity of inferences about them when one uses standard methods that do not explicitly recognise this and related complications. A growing literature that aimed at introducing novel techniques specifically designed to produce accurate inferences in such environments ensued. The frequent use of these predictive regressions in applied work has also led practitioners to question the validity of viewing predictability within a linear setting that ignores the possibility that predictability may occasionally be switched off. This in turn has generated a new stream of research aiming at introducing regime specific behaviour within predictive regressions in order to explicitly capture phenomena such as episodic predictability.

Keywords: Cusum; Structural; Breaks; Thresholds; Economic; Regime; Shifts; Nonlinear; Predictability; Nuisance; Parameters; Instrumental; Variables; Local; To; Unit; Root; Persistence; Predictability (search for similar items in EconPapers)
Date: 2019-07
New Economics Papers: this item is included in nep-ecm
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