Comparing deep neural network and econometric approaches to predicting the impact of climate change on agricultural yield
Michael Keane and Timothy Neal
| Year of publication: |
2020
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|---|---|
| Authors: | Keane, Michael P. ; Neal, Timothy |
| Published in: |
The econometrics journal. - Oxford : Oxford University Press, ISSN 1368-423X, ZDB-ID 1475536-1. - Vol. 23.2020, 3, p. S59-S80
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| Subject: | Climate change | crop yield | panel data | machine learning | deep learning | Klimawandel | Ernteertrag | Crop yield | Prognoseverfahren | Forecasting model | Neuronale Netze | Neural networks | Künstliche Intelligenz | Artificial intelligence | Agrarproduktion | Agricultural production | Panel | Panel study | Prognose | Forecast |
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1093/ectj/utaa012 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10012385263