Arbeitspapier

Adaptative LASSO estimation for ARDL models with GARCH innovations

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In this paper we show the validity of the adaptive LASSO procedure in estimating stationary ARDL(p,q) models with GARCH innovations. We show that, given a set of initial weights, the adaptive Lasso selects the relevant variables with probability converging to one. Afterwards, we show that the estimator is oracle, meaning that its distribution converges to the same distribution of the oracle assisted least squares, i.e., the least squares estimator calculated as if we knew the set of relevant variables beforehand. Finally, we show that the LASSO estimator can be used to construct the initial weights. The performance of the method in finite samples is illustrated using Monte Carlo simulation

Sprache
Englisch

Erschienen in
Series: Texto para discussão ; No. 637

Klassifikation
Wirtschaft
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Thema
ARDL
GARCH
sparse models
shrinkage
LASSO
adaLASSO
time series

Ereignis
Geistige Schöpfung
(wer)
Medeiros, Marcelo C.
Mendes, Eduardo F.
Ereignis
Veröffentlichung
(wer)
Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio), Departamento de Economia
(wo)
Rio de Janeiro
(wann)
2015

Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
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Objekttyp

  • Arbeitspapier

Beteiligte

  • Medeiros, Marcelo C.
  • Mendes, Eduardo F.
  • Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio), Departamento de Economia

Entstanden

  • 2015

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