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Detecting and Quantifying Structural Breaks in Climate.
- Source :
- Econometrics (2225-1146); Dec2022, Vol. 10 Issue 4, p33, 27p
- Publication Year :
- 2022
-
Abstract
- Structural breaks have attracted considerable attention recently, especially in light of the financial crisis, Great Recession, the COVID-19 pandemic, and war. While structural breaks pose significant econometric challenges, machine learning provides an incisive tool for detecting and quantifying breaks. The current paper presents a unified framework for analyzing breaks; and it implements that framework to test for and quantify changes in precipitation in Mauritania over 1919–1997. These tests detect a decline of one third in mean rainfall, starting around 1970. Because water is a scarce resource in Mauritania, this decline—with adverse consequences on food production—has potential economic and policy consequences. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 22251146
- Volume :
- 10
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- Econometrics (2225-1146)
- Publication Type :
- Academic Journal
- Accession number :
- 160988050
- Full Text :
- https://doi.org/10.3390/econometrics10040033