Generating univariate fractional integration within a large VAR(1)

Guillaume Chevillon; Alain Hecq; Sebastien Laurent

doi:10.1016/j.jeconom.2018.01.002

Generating univariate fractional integration within a large VAR(1)

Guillaume Chevillon^*
, Alain Hecq
, Sebastien Laurent

^*Corresponding author for this work

QE Econometrics

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

This paper shows that a large dimensional vector autoregressive model (var) of finite order can generate fractional integration in the marginalized univariate series. We derive high-level assumptions under which the final equation representation of a var(1) leads to univariate fractional white noises and verify the validity of these assumptions for two specific models.

Original language	English
Pages (from-to)	54-65
Number of pages	12
Journal	Journal of Econometrics
Volume	204
Issue number	1
DOIs	https://doi.org/10.1016/j.jeconom.2018.01.002
Publication status	Published - May 2018

Keywords

Long memory
Vector autoregressive model
Marginalization
Final equation representation
GAUSSIAN SEMIPARAMETRIC ESTIMATION
LONG MEMORY PROCESSES
DYNAMIC-MODELS
AGGREGATION
VOLATILITY

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10.1016/j.jeconom.2018.01.002

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title = "Generating univariate fractional integration within a large VAR(1)",

abstract = "This paper shows that a large dimensional vector autoregressive model (var) of finite order can generate fractional integration in the marginalized univariate series. We derive high-level assumptions under which the final equation representation of a var(1) leads to univariate fractional white noises and verify the validity of these assumptions for two specific models.",

keywords = "Long memory, Vector autoregressive model, Marginalization, Final equation representation, GAUSSIAN SEMIPARAMETRIC ESTIMATION, LONG MEMORY PROCESSES, DYNAMIC-MODELS, AGGREGATION, VOLATILITY",

author = "Guillaume Chevillon and Alain Hecq and Sebastien Laurent",

note = "data source: no data used",

year = "2018",

month = may,

doi = "10.1016/j.jeconom.2018.01.002",

language = "English",

volume = "204",

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AU - Chevillon, Guillaume

AU - Hecq, Alain

AU - Laurent, Sebastien

N1 - data source: no data used

PY - 2018/5

Y1 - 2018/5

N2 - This paper shows that a large dimensional vector autoregressive model (var) of finite order can generate fractional integration in the marginalized univariate series. We derive high-level assumptions under which the final equation representation of a var(1) leads to univariate fractional white noises and verify the validity of these assumptions for two specific models.

AB - This paper shows that a large dimensional vector autoregressive model (var) of finite order can generate fractional integration in the marginalized univariate series. We derive high-level assumptions under which the final equation representation of a var(1) leads to univariate fractional white noises and verify the validity of these assumptions for two specific models.

KW - Long memory

KW - Vector autoregressive model

KW - Marginalization

KW - Final equation representation

KW - GAUSSIAN SEMIPARAMETRIC ESTIMATION

KW - LONG MEMORY PROCESSES

KW - DYNAMIC-MODELS

KW - AGGREGATION

KW - VOLATILITY

U2 - 10.1016/j.jeconom.2018.01.002

DO - 10.1016/j.jeconom.2018.01.002

M3 - Article

SN - 0304-4076

VL - 204

SP - 54

EP - 65

JO - Journal of Econometrics

JF - Journal of Econometrics

IS - 1

ER -

Generating univariate fractional integration within a large VAR(1)

Abstract

Keywords

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