Mostrando recursos 121 - 140 de 310

  1. Unit root inference for non-stationary linear processes driven by infinite variance innovations

    Cavaliere, Giuseppe; Georgiev, Iliyan; Taylor, Robert
    The contribution of this paper is two-fold. First, we derive the asymptotic null distribution of the familiar augmented Dickey-Fuller [ADF] statistics in the case where the shocks follow a linear process driven by in…nite variance innovations. We show that these distributions are free of serial correlation nuisance parameters but depend on the tail index of the in…nite variance process. These distributions are shown to coincide with the corresponding results for the case where the shocks follow a …nite autoregression, provided the lag length in the ADF regression satis…es the same o(T1=3) rate condition as is required in the …nite variance...

  2. Unit root inference for non-stationary linear processes driven by infinite variance innovations

    Cavaliere, Giuseppe; Georgiev, Iliyan; Taylor, Robert
    The contribution of this paper is two-fold. First, we derive the asymptotic null distribution of the familiar augmented Dickey-Fuller [ADF] statistics in the case where the shocks follow a linear process driven by in…nite variance innovations. We show that these distributions are free of serial correlation nuisance parameters but depend on the tail index of the in…nite variance process. These distributions are shown to coincide with the corresponding results for the case where the shocks follow a …nite autoregression, provided the lag length in the ADF regression satis…es the same o(T1=3) rate condition as is required in the …nite variance...

  3. Unit root inference for non-stationary linear processes driven by infinite variance innovations

    Cavaliere, Giuseppe; Georgiev, Iliyan; Taylor, Robert
    The contribution of this paper is two-fold. First, we derive the asymptotic null distribution of the familiar augmented Dickey-Fuller [ADF] statistics in the case where the shocks follow a linear process driven by in…nite variance innovations. We show that these distributions are free of serial correlation nuisance parameters but depend on the tail index of the in…nite variance process. These distributions are shown to coincide with the corresponding results for the case where the shocks follow a …nite autoregression, provided the lag length in the ADF regression satis…es the same o(T1=3) rate condition as is required in the …nite variance...

  4. Unit root inference for non-stationary linear processes driven by infinite variance innovations

    Cavaliere, Giuseppe; Georgiev, Iliyan; Taylor, Robert
    The contribution of this paper is two-fold. First, we derive the asymptotic null distribution of the familiar augmented Dickey-Fuller [ADF] statistics in the case where the shocks follow a linear process driven by in…nite variance innovations. We show that these distributions are free of serial correlation nuisance parameters but depend on the tail index of the in…nite variance process. These distributions are shown to coincide with the corresponding results for the case where the shocks follow a …nite autoregression, provided the lag length in the ADF regression satis…es the same o(T1=3) rate condition as is required in the …nite variance...

  5. Unit root inference for non-stationary linear processes driven by infinite variance innovations

    Cavaliere, Giuseppe; Georgiev, Iliyan; Taylor, Robert
    The contribution of this paper is two-fold. First, we derive the asymptotic null distribution of the familiar augmented Dickey-Fuller [ADF] statistics in the case where the shocks follow a linear process driven by in…nite variance innovations. We show that these distributions are free of serial correlation nuisance parameters but depend on the tail index of the in…nite variance process. These distributions are shown to coincide with the corresponding results for the case where the shocks follow a …nite autoregression, provided the lag length in the ADF regression satis…es the same o(T1=3) rate condition as is required in the …nite variance...

  6. Unit root inference for non-stationary linear processes driven by infinite variance innovations

    Cavaliere, Giuseppe; Georgiev, Iliyan; Taylor, Robert
    The contribution of this paper is two-fold. First, we derive the asymptotic null distribution of the familiar augmented Dickey-Fuller [ADF] statistics in the case where the shocks follow a linear process driven by in…nite variance innovations. We show that these distributions are free of serial correlation nuisance parameters but depend on the tail index of the in…nite variance process. These distributions are shown to coincide with the corresponding results for the case where the shocks follow a …nite autoregression, provided the lag length in the ADF regression satis…es the same o(T1=3) rate condition as is required in the …nite variance...

  7. Unit root inference for non-stationary linear processes driven by infinite variance innovations

    Cavaliere, Giuseppe; Georgiev, Iliyan; Taylor, Robert
    The contribution of this paper is two-fold. First, we derive the asymptotic null distribution of the familiar augmented Dickey-Fuller [ADF] statistics in the case where the shocks follow a linear process driven by in…nite variance innovations. We show that these distributions are free of serial correlation nuisance parameters but depend on the tail index of the in…nite variance process. These distributions are shown to coincide with the corresponding results for the case where the shocks follow a …nite autoregression, provided the lag length in the ADF regression satis…es the same o(T1=3) rate condition as is required in the …nite variance...

  8. Unit root inference for non-stationary linear processes driven by infinite variance innovations

    Cavaliere, Giuseppe; Georgiev, Iliyan; Taylor, Robert
    The contribution of this paper is two-fold. First, we derive the asymptotic null distribution of the familiar augmented Dickey-Fuller [ADF] statistics in the case where the shocks follow a linear process driven by in…nite variance innovations. We show that these distributions are free of serial correlation nuisance parameters but depend on the tail index of the in…nite variance process. These distributions are shown to coincide with the corresponding results for the case where the shocks follow a …nite autoregression, provided the lag length in the ADF regression satis…es the same o(T1=3) rate condition as is required in the …nite variance...

  9. Unit root inference for non-stationary linear processes driven by infinite variance innovations

    Cavaliere, Giuseppe; Georgiev, Iliyan; Taylor, Robert
    The contribution of this paper is two-fold. First, we derive the asymptotic null distribution of the familiar augmented Dickey-Fuller [ADF] statistics in the case where the shocks follow a linear process driven by in…nite variance innovations. We show that these distributions are free of serial correlation nuisance parameters but depend on the tail index of the in…nite variance process. These distributions are shown to coincide with the corresponding results for the case where the shocks follow a …nite autoregression, provided the lag length in the ADF regression satis…es the same o(T1=3) rate condition as is required in the …nite variance...

  10. Unit root inference for non-stationary linear processes driven by infinite variance innovations

    Cavaliere, Giuseppe; Georgiev, Iliyan; Taylor, Robert
    The contribution of this paper is two-fold. First, we derive the asymptotic null distribution of the familiar augmented Dickey-Fuller [ADF] statistics in the case where the shocks follow a linear process driven by in…nite variance innovations. We show that these distributions are free of serial correlation nuisance parameters but depend on the tail index of the in…nite variance process. These distributions are shown to coincide with the corresponding results for the case where the shocks follow a …nite autoregression, provided the lag length in the ADF regression satis…es the same o(T1=3) rate condition as is required in the …nite variance...

  11. Unit root inference for non-stationary linear processes driven by infinite variance innovations

    Cavaliere, Giuseppe; Georgiev, Iliyan; Taylor, Robert
    The contribution of this paper is two-fold. First, we derive the asymptotic null distribution of the familiar augmented Dickey-Fuller [ADF] statistics in the case where the shocks follow a linear process driven by in…nite variance innovations. We show that these distributions are free of serial correlation nuisance parameters but depend on the tail index of the in…nite variance process. These distributions are shown to coincide with the corresponding results for the case where the shocks follow a …nite autoregression, provided the lag length in the ADF regression satis…es the same o(T1=3) rate condition as is required in the …nite variance...

  12. Unit root inference for non-stationary linear processes driven by infinite variance innovations

    Cavaliere, Giuseppe; Georgiev, Iliyan; Taylor, Robert
    The contribution of this paper is two-fold. First, we derive the asymptotic null distribution of the familiar augmented Dickey-Fuller [ADF] statistics in the case where the shocks follow a linear process driven by in…nite variance innovations. We show that these distributions are free of serial correlation nuisance parameters but depend on the tail index of the in…nite variance process. These distributions are shown to coincide with the corresponding results for the case where the shocks follow a …nite autoregression, provided the lag length in the ADF regression satis…es the same o(T1=3) rate condition as is required in the …nite variance...

  13. Unit root inference for non-stationary linear processes driven by infinite variance innovations

    Cavaliere, Giuseppe; Georgiev, Iliyan; Taylor, Robert
    The contribution of this paper is two-fold. First, we derive the asymptotic null distribution of the familiar augmented Dickey-Fuller [ADF] statistics in the case where the shocks follow a linear process driven by in…nite variance innovations. We show that these distributions are free of serial correlation nuisance parameters but depend on the tail index of the in…nite variance process. These distributions are shown to coincide with the corresponding results for the case where the shocks follow a …nite autoregression, provided the lag length in the ADF regression satis…es the same o(T1=3) rate condition as is required in the …nite variance...

  14. Unit root inference for non-stationary linear processes driven by infinite variance innovations

    Cavaliere, Giuseppe; Georgiev, Iliyan; Taylor, Robert
    The contribution of this paper is two-fold. First, we derive the asymptotic null distribution of the familiar augmented Dickey-Fuller [ADF] statistics in the case where the shocks follow a linear process driven by in…nite variance innovations. We show that these distributions are free of serial correlation nuisance parameters but depend on the tail index of the in…nite variance process. These distributions are shown to coincide with the corresponding results for the case where the shocks follow a …nite autoregression, provided the lag length in the ADF regression satis…es the same o(T1=3) rate condition as is required in the …nite variance...

  15. Unit root inference for non-stationary linear processes driven by infinite variance innovations

    Cavaliere, Giuseppe; Georgiev, Iliyan; Taylor, Robert
    The contribution of this paper is two-fold. First, we derive the asymptotic null distribution of the familiar augmented Dickey-Fuller [ADF] statistics in the case where the shocks follow a linear process driven by in…nite variance innovations. We show that these distributions are free of serial correlation nuisance parameters but depend on the tail index of the in…nite variance process. These distributions are shown to coincide with the corresponding results for the case where the shocks follow a …nite autoregression, provided the lag length in the ADF regression satis…es the same o(T1=3) rate condition as is required in the …nite variance...

  16. Unit root inference for non-stationary linear processes driven by infinite variance innovations

    Cavaliere, Giuseppe; Georgiev, Iliyan; Taylor, Robert
    The contribution of this paper is two-fold. First, we derive the asymptotic null distribution of the familiar augmented Dickey-Fuller [ADF] statistics in the case where the shocks follow a linear process driven by in…nite variance innovations. We show that these distributions are free of serial correlation nuisance parameters but depend on the tail index of the in…nite variance process. These distributions are shown to coincide with the corresponding results for the case where the shocks follow a …nite autoregression, provided the lag length in the ADF regression satis…es the same o(T1=3) rate condition as is required in the …nite variance...

  17. Unit root inference for non-stationary linear processes driven by infinite variance innovations

    Cavaliere, Giuseppe; Georgiev, Iliyan; Taylor, Robert
    The contribution of this paper is two-fold. First, we derive the asymptotic null distribution of the familiar augmented Dickey-Fuller [ADF] statistics in the case where the shocks follow a linear process driven by in…nite variance innovations. We show that these distributions are free of serial correlation nuisance parameters but depend on the tail index of the in…nite variance process. These distributions are shown to coincide with the corresponding results for the case where the shocks follow a …nite autoregression, provided the lag length in the ADF regression satis…es the same o(T1=3) rate condition as is required in the …nite variance...

  18. Unit root inference for non-stationary linear processes driven by infinite variance innovations

    Cavaliere, Giuseppe; Georgiev, Iliyan; Taylor, Robert
    The contribution of this paper is two-fold. First, we derive the asymptotic null distribution of the familiar augmented Dickey-Fuller [ADF] statistics in the case where the shocks follow a linear process driven by in…nite variance innovations. We show that these distributions are free of serial correlation nuisance parameters but depend on the tail index of the in…nite variance process. These distributions are shown to coincide with the corresponding results for the case where the shocks follow a …nite autoregression, provided the lag length in the ADF regression satis…es the same o(T1=3) rate condition as is required in the …nite variance...

  19. Unit root inference for non-stationary linear processes driven by infinite variance innovations

    Cavaliere, Giuseppe; Georgiev, Iliyan; Taylor, Robert
    The contribution of this paper is two-fold. First, we derive the asymptotic null distribution of the familiar augmented Dickey-Fuller [ADF] statistics in the case where the shocks follow a linear process driven by in…nite variance innovations. We show that these distributions are free of serial correlation nuisance parameters but depend on the tail index of the in…nite variance process. These distributions are shown to coincide with the corresponding results for the case where the shocks follow a …nite autoregression, provided the lag length in the ADF regression satis…es the same o(T1=3) rate condition as is required in the …nite variance...

  20. Unit root inference for non-stationary linear processes driven by infinite variance innovations

    Cavaliere, Giuseppe; Georgiev, Iliyan; Taylor, Robert
    The contribution of this paper is two-fold. First, we derive the asymptotic null distribution of the familiar augmented Dickey-Fuller [ADF] statistics in the case where the shocks follow a linear process driven by in…nite variance innovations. We show that these distributions are free of serial correlation nuisance parameters but depend on the tail index of the in…nite variance process. These distributions are shown to coincide with the corresponding results for the case where the shocks follow a …nite autoregression, provided the lag length in the ADF regression satis…es the same o(T1=3) rate condition as is required in the …nite variance...

Aviso de cookies: Usamos cookies propias y de terceros para mejorar nuestros servicios, para análisis estadístico y para mostrarle publicidad. Si continua navegando consideramos que acepta su uso en los términos establecidos en la Política de cookies.