Forecasting crop yields through climate variables using mixed frequency data. The case of Argentine soybeans

Magdalena Cornejo

Económica, 2021, vol. 67, 93-106

Abstract: This article evaluates the value of information on climate variables published in advance and at a higher frequency than the target variable of interest—crop yields—in order to get short term forecasts. Aggregate and disaggregate climate data, alternative weighting schemes and different updating schemes are used to evaluate forecasting performance. This study focuses on the case of soybean yields in Argentina. Results show that models including high frequency weather data outperformed particularly during the three consecutive campaigns after 2008/09 when soybean yield decreased almost by 50%. Furthermore, forecast combinations showed a better forecasting performance than individual forecasting models.

Keywords: yields; forecasting; climate; mixed-frequency; soybeans (search for similar items in EconPapers)
JEL-codes: C53 Q10 (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
https://revistas.unlp.edu.ar/Economica/article/view/10621/12171 (application/pdf)

Related works:
Journal Article: Forecasting crop yields through climate variables using mixed frequency data. The case of Argentine soybeans (2021)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:lap:journl:632

Access Statistics for this article

More articles in Económica from Departamento de Economía, Facultad de Ciencias Económicas, Universidad Nacional de La Plata Contact information at EDIRC.
Bibliographic data for series maintained by Milagros Cejas ().