Abstract

Most proposed subsampling and resampling methods in the literature assume stationary data. In many empirical applications, however, the hypothesis of stationarity can easily be rejected. In this talk, it is demonstrated that variance estimators based on the subsampling methodology can be employed for different types of nonstationarity data, and the estimators are shown to be consistent under mild moment and mixing conditions. Results from a small simulation study on finite sample properties are provided, and an example with applications to forestry, using satellite data, is discussed

Published in

Conference

Exploring Stochastics

SLU Authors

• Ekström, Magnus

  • Department of Forest Economics, Swedish University of Agricultural Sciences
    

Permanent link to this page (URI)

https://res.slu.se/id/publ/21578