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Bootstrapping time series models
Authors:G S Hongyi Li  Maddala
Institution:Department of Economics , The Ohio State University , Columbus, OH, 43210
Abstract:This paper surveys recent development in bootstrap methods and the modifications needed for their applicability in time series models. The paper discusses some guidelines for empirical researchers in econometric analysis of time series. Different sampling schemes for bootstrap data generation and different forms of bootstrap test statistics are discussed. The paper also discusses the applicability of direct bootstrapping of data in dynamic models and cointegrating regression models. It is argued that bootstrapping residuals is the preferable approach. The bootstrap procedures covered include the recursive bootstrap, the moving block bootstrap and the stationary bootstrap.
Keywords:Least median of squares  Reweighted least squares  Partially adaptive estimation
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