Seasonal Long Memory in Retail Sales in the G7 Countries

This article examines the seasonal patterns of retail sales in the G7 nations, a key component of private consumption. Using seasonal fractional integration, we assess whether shocks present a lasting or temporary effect on retail sales trends, considering the high seasonal component. We observe mean reversion in France, Germany, Italy, Japan, and the UK, and permanent effects in the cases of Canada and USA. However, these outcomes vary based on the error term model applied. These results offer valuable information for policymakers seeking to boost consumption depending on the seasonal long memory property of the G7 countries.

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Publication Details

Journal
Fractal and Fractional
Published
2024-11-07
DOI
https://doi.org/10.3390/fractalfract8110650
Citations
1
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
1.13
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article

Seasonal Long Memory in Retail Sales in the G7 Countries

Luis A. Gil-Alaña, Carlos Poza
1 citations
Fractal and Fractional
Market Dynamics and Volatility
1.13
article

Seasonal Long Memory in Retail Sales in the G7 Countries

Luis A. Gil-Alaña, Carlos Poza
article en
1 citations

Abstract

This article examines the seasonal patterns of retail sales in the G7 nations, a key component of private consumption. Using seasonal fractional integration, we assess whether shocks present a lasting or temporary effect on retail sales trends, considering the high seasonal component. We observe mean reversion in France, Germany, Italy, Japan, and the UK, and permanent effects in the cases of Canada and USA. However, these outcomes vary based on the error term model applied. These results offer valuable information for policymakers seeking to boost consumption depending on the seasonal long memory property of the G7 countries.

Fractal and FractionalVol. 8(11)
Universidad Francisco de Vitoria (ES), Universidad de Navarra (ES)
Partnerships for the goals
Openalex Percentile: Top 11%
Market Dynamics and Volatility
1.13
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