Subsampling intervals in autoregressive models with linear time trend

Joseph P. Romano and Michael Wolf

DES - Working Papers. Statistics and Econometrics. WS from Universidad Carlos III de Madrid. Departamento de Estadística

Abstract: A new method is proposed for constructing confidence intervals in autoregressive models with linear time trend. Interest focuses on the sum of the autoregressive coefficients because this parameter provides a useful scalar measure of the long-run persistence properties of an economic time series. Since the type of the limiting distribution of the corresponding OLS estimator, as well as the rate of its convergence, depend in a discontinuous fashion upon whether the true parameter is less than one or equal to one (that is, trend-stationary case or unit root case), the construction of confidence intervals is notoriously difficult. The crux of our method is to recompute the OLS estimator on smaller blocks of the observed data, according to the general subsampling idea of Politis and Romano (1994a), although some extensions of the standard theory are needed. The method is more general than previous approaches in that it works for arbitrary parameter values, but also because it allows the innovations to be'-a martingale difference sequence rather than i.i.d .. Some simulation studies examine the finite sample performance.

Keywords: Autoregressive; time; series; Local-to-unity; asymptotics; Subsampling; Trend-Stationarity; Unit; roots (search for similar items in EconPapers)
Date: 1999-12
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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Journal Article: Subsampling Intervals in Autoregressive Models with Linear Time Trend (2001)
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Persistent link: https://EconPapers.repec.org/RePEc:cte:wsrepe:6400

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