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“Unbiased estimation of autoregressive models for bounded stochastic processes”

Author

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  • Josep Lluís Carrion-i-Silvestre

    (AQR-IREA Research Group, Department of Econometrics, Statistics, and Spanish Economy, University of Barcelona. Av. Diagonal, 690. 08034 Barcelona.)

  • María Dolores Gadea

    (Department of Applied Economics, University of Zaragoza. Gran Vía, 4, 50005 Zaragoza (Spain).)

  • Antonio Montañés

    (Department of Applied Economics, University of Zaragoza. Gran Vía, 4, 50005 Zaragoza (Spain).)

Abstract

The paper investigates the estimation bias of autoregressive models for bounded stochastic processes and the performance of the standard procedures in the literature that aim to correcting the estimation bias. It is shown that, in some cases, the bounded nature of the stochastic processes worsen the estimation bias effect, which suggests the design of bound-specific bias correction methods. The paper focuses on two popular autoregressive estimation bias correction procedures which are extended to cover bounded stochastic processes. Finite sample performance analysis of the new proposal is carried out using Monte Carlo simulations which 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 current account balance of some developed countries, whose shocks persistence measures are computed.

Suggested Citation

  • Josep Lluís Carrion-i-Silvestre & María Dolores Gadea & Antonio Montañés, 2017. "“Unbiased estimation of autoregressive models for bounded stochastic processes”," IREA Working Papers 201719, University of Barcelona, Research Institute of Applied Economics, revised Nov 2017.
    • Handle: RePEc:ira:wpaper:201719
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    References listed on IDEAS

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    More about this item

    Keywords

    Bounded stochastic processes; estimation bias; unit root tests; current account balance. JEL classification: C22; C32; E32; Q43.;
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