Local block bootstrap inference for trending time series

Arif Dowla, Efstathios Paparoditis and Dimitris Politis ()
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Arif Dowla: http://www.stochasticlogic.com

Metrika: International Journal for Theoretical and Applied Statistics, 2013, vol. 76, issue 6, 733-764

Abstract: Resampling for stationary sequences has been well studied in the last couple of decades. In the paper at hand, we focus on nonstationary time series data where the nonstationarity is due to a slowly-changing deterministic trend. We show that the local block bootstrap methodology is appropriate for inference under this locally stationary setting without the need of detrending the data. We prove the asymptotic consistency of the local block bootstrap in the smooth trend model, and complement the theoretical results by a finite-sample simulation. Copyright Springer-Verlag Berlin Heidelberg 2013

Keywords: Bootstrap; Dependent data; Kernel smoothing; Local stationarity; Regression (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s00184-012-0413-9

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