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Temperature Anomalies, Long Memory, and Aggregation

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Temperature Anomalies, Long Memory, and Aggregation. / Vera-Valdés, J. Eduardo.

Aarhus : Institut for Økonomi, Aarhus Universitet, 2020.

Research output: Working paperResearch

Harvard

Vera-Valdés, JE 2020 'Temperature Anomalies, Long Memory, and Aggregation' Institut for Økonomi, Aarhus Universitet, Aarhus.

APA

Vera-Valdés, J. E. (2020). Temperature Anomalies, Long Memory, and Aggregation. Institut for Økonomi, Aarhus Universitet. CREATES Research Papers No. 2020-16

CBE

Vera-Valdés JE. 2020. Temperature Anomalies, Long Memory, and Aggregation. Aarhus: Institut for Økonomi, Aarhus Universitet.

MLA

Vera-Valdés, J. Eduardo Temperature Anomalies, Long Memory, and Aggregation. Aarhus: Institut for Økonomi, Aarhus Universitet. (CREATES Research Papers; Journal number 2020-16). 2020., 14 p.

Vancouver

Vera-Valdés JE. Temperature Anomalies, Long Memory, and Aggregation. Aarhus: Institut for Økonomi, Aarhus Universitet. 2020 Dec.

Author

Vera-Valdés, J. Eduardo. / Temperature Anomalies, Long Memory, and Aggregation. Aarhus : Institut for Økonomi, Aarhus Universitet, 2020. (CREATES Research Papers; No. 2020-16).

Bibtex

@techreport{39182e686e5d4dcc89d0b8491cf4c2c2,
title = "Temperature Anomalies, Long Memory, and Aggregation",
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.",
keywords = "Global Heating, Regional Temperature, Climate Econometrics, Long Memory, Aggregation",
author = "Vera-Vald{\'e}s, {J. Eduardo}",
year = "2020",
month = dec,
language = "English",
series = "CREATES Research Papers",
publisher = "Institut for {\O}konomi, Aarhus Universitet",
number = "2020-16",
type = "WorkingPaper",
institution = "Institut for {\O}konomi, Aarhus Universitet",

}

RIS

TY - UNPB

T1 - Temperature Anomalies, Long Memory, and Aggregation

AU - Vera-Valdés, J. Eduardo

PY - 2020/12

Y1 - 2020/12

N2 - 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.

AB - 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.

KW - Global Heating

KW - Regional Temperature

KW - Climate Econometrics

KW - Long Memory

KW - Aggregation

M3 - Working paper

T3 - CREATES Research Papers

BT - Temperature Anomalies, Long Memory, and Aggregation

PB - Institut for Økonomi, Aarhus Universitet

CY - Aarhus

ER -