Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/173440
Title: Nearly unbiased estimation of autoregressive models for bounded near‐integrated stochastic processes
Author: Carrión i Silvestre, Josep Lluís
Gadea Rivas, María Dolores
Montañés, Antonio
Keywords: Econometria
Anàlisi de regressió
Anàlisi estocàstica
Mètode de Montecarlo
Econometrics
Regression analysis
Analyse stochastique
Monte Carlo method
Issue Date: 1-Feb-2021
Publisher: John Wiley & Sons
Abstract: The paper investigates the estimation bias of autoregressive models for bounded near‐integrated stochastic processes and the performance of the standard procedures in the literature that aim to correct the estimation bias. In some cases, the bounded nature of the stochastic processes worsens the estimation bias effect. The paper extends two popular autoregressive estimation bias correction procedures to cover bounded stochastic processes. Monte Carlo simulations reveal that accounting for the bounded nature of the stochastic processes leads to improvements in the estimation of autoregressive models. Finally, an illustration is given using the unemployment rate of the G7 countries.
Note: Versió postprint del document publicat a: https://doi.org/10.1111/obes.12399
It is part of: Oxford Bulletin of Economics and Statistics, 2021, vol. 83, num. 1, p. 273-297
URI: http://hdl.handle.net/2445/173440
Related resource: https://doi.org/10.1111/obes.12399
ISSN: 0305-9049
Appears in Collections:Articles publicats en revistes (Econometria, Estadística i Economia Aplicada)

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