Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/87550 
Year of Publication: 
2012
Series/Report no.: 
Tinbergen Institute Discussion Paper No. 12-133/III
Publisher: 
Tinbergen Institute, Amsterdam and Rotterdam
Abstract: 
This paper proposes a new set of transformed polynomial functions that provide a flexible setting for nonlinear autoregressive modeling of the conditional mean while at the same time ensuring the strict stationarity, ergodicity, fading memory and existence of moments of the implied stochastic sequence. The great flexibility of the transformed polynomial functions makes them interesting for both parametric and semi-nonparametric autoregressive modeling. This flexibility is established by showing that transformed polynomial sieves are sup-norm-dense on the space of continuous functions and offer appropriate convergence speeds on Holder function spaces.
Subjects: 
time-series
nonlinear autoregressive models
semi-nonparametric models
method of sieves.
JEL: 
C01
C13
C14
C22
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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