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Temperature Anomalies, Long Memory, and Aggregation

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  • J. Eduardo Vera-Valdés

    (Aalborg University and CREATES)

Abstract

Econometric studies for global heating have typically used regional or global temperature averages to show that they exhibit long memory properties. One typical explanation behind the long memory properties of temperature averages is cross-sectional aggregation. Nonetheless, the formal analysis regarding the effect that aggregation has on the long memory dynamics of temperature data has been missing. Thus, this paper studies the long memory properties of individual grid temperatures and compares them against the long memory dynamics of global and regional averages. Our results show that the long memory parameters in individual grid observations are smaller than the ones from regional averages. Global and regional long memory estimates are found to be greatly affected by temperature measurements at the Tropics, where the data is less reliable. Thus, this paper supports the notion that aggregation may be exacerbating the long memory estimated in regional and global temperature data. The results are robust to the bandwidth parameter, limit for station radius of influence, and sampling frequency.

Suggested Citation

  • J. Eduardo Vera-Valdés, 2020. "Temperature Anomalies, Long Memory, and Aggregation," CREATES Research Papers 2020-16, Department of Economics and Business Economics, Aarhus University.
    • Handle: RePEc:aah:create:2020-16
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    References listed on IDEAS

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    Cited by:

    1. J. Eduardo Vera-Valdés, 2021. "Nonfractional Long-Range Dependence: Long Memory, Antipersistence, and Aggregation," Econometrics, MDPI, vol. 9(4), pages 1-18, October.
    2. Klöcker, J.A. & Daumann, F., 2023. "What drives migration to Germany? A panel data analysis," Research in Economics, Elsevier, vol. 77(2), pages 251-264.

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    More about this item

    Keywords

    Global Heating; Temperature Anomalies; Climate Econometrics; Long Memory; Aggregation;
    All these keywords.

    JEL classification:

    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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