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Bootstrap estimation of long-run variance under strong dependence
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 Title & Authors
Bootstrap estimation of long-run variance under strong dependence
Baek, Changryong; Kwon, Yong;
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 Abstract
This paper considers a long-run variance estimation using a block bootstrap method under strong dependence also known as long range dependence. We extend currently available methods in two ways. First, it extends bootstrap methods under short range dependence to long range dependence. Second, to accommodate the observation that strong dependence may come from deterministic trend plus noise models, we propose to utilize residuals obtained from the nonparametric kernel estimation with the bimodal kernel. The simulation study shows that our method works well; in addition, a data illustration is presented for practitioners.
 Keywords
long-run variance;long range dependence;block bootstrap;
 Language
Korean
 Cited by
 References
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