Nonfractional Long-Range Dependence: Long Memory, Antipersistence, and Aggregation

This paper used cross-sectional aggregation as the inspiration for a model with long-range dependence that arises in actual data. One of the advantages of our model is that it is less brittle than fractionally integrated processes. In particular, we showed that the antipersistent phenomenon is not p...

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Main Author: J. Eduardo Vera-Valdés
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Econometrics
Subjects:
Online Access:https://www.mdpi.com/2225-1146/9/4/39
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author J. Eduardo Vera-Valdés
author_facet J. Eduardo Vera-Valdés
author_sort J. Eduardo Vera-Valdés
collection DOAJ
description This paper used cross-sectional aggregation as the inspiration for a model with long-range dependence that arises in actual data. One of the advantages of our model is that it is less brittle than fractionally integrated processes. In particular, we showed that the antipersistent phenomenon is not present for the cross-sectionally aggregated process. We proved that this has implications for estimators of long-range dependence in the frequency domain, which will be misspecified for nonfractional long-range-dependent processes with negative degrees of persistence. As an application, we showed how we can approximate a fractionally differenced process using theoretically-motivated cross-sectional aggregated long-range-dependent processes. An example with temperature data showed that our framework provides a better fit to the data than the fractional difference operator.
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spelling doaj.art-5fae9bafef9d4b6297f230dc2894a7792023-11-23T07:58:17ZengMDPI AGEconometrics2225-11462021-10-01943910.3390/econometrics9040039Nonfractional Long-Range Dependence: Long Memory, Antipersistence, and AggregationJ. Eduardo Vera-Valdés0Department of Mathematical Sciences, Aalborg University, Skjernvej 4A, DK-9220 Aalborg, DenmarkThis paper used cross-sectional aggregation as the inspiration for a model with long-range dependence that arises in actual data. One of the advantages of our model is that it is less brittle than fractionally integrated processes. In particular, we showed that the antipersistent phenomenon is not present for the cross-sectionally aggregated process. We proved that this has implications for estimators of long-range dependence in the frequency domain, which will be misspecified for nonfractional long-range-dependent processes with negative degrees of persistence. As an application, we showed how we can approximate a fractionally differenced process using theoretically-motivated cross-sectional aggregated long-range-dependent processes. An example with temperature data showed that our framework provides a better fit to the data than the fractional difference operator.https://www.mdpi.com/2225-1146/9/4/39long memoryantipersistencefractional differencingaggregationstrong persistence
spellingShingle J. Eduardo Vera-Valdés
Nonfractional Long-Range Dependence: Long Memory, Antipersistence, and Aggregation
Econometrics
long memory
antipersistence
fractional differencing
aggregation
strong persistence
title Nonfractional Long-Range Dependence: Long Memory, Antipersistence, and Aggregation
title_full Nonfractional Long-Range Dependence: Long Memory, Antipersistence, and Aggregation
title_fullStr Nonfractional Long-Range Dependence: Long Memory, Antipersistence, and Aggregation
title_full_unstemmed Nonfractional Long-Range Dependence: Long Memory, Antipersistence, and Aggregation
title_short Nonfractional Long-Range Dependence: Long Memory, Antipersistence, and Aggregation
title_sort nonfractional long range dependence long memory antipersistence and aggregation
topic long memory
antipersistence
fractional differencing
aggregation
strong persistence
url https://www.mdpi.com/2225-1146/9/4/39
work_keys_str_mv AT jeduardoveravaldes nonfractionallongrangedependencelongmemoryantipersistenceandaggregation