Forecasting crop yields through climate variables using mixed frequency data: the case of Argentine soybeans

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 sch...

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Detalles Bibliográficos
Autor principal: Cornejo, Magdalena
Formato: Articulo
Lenguaje:Inglés
Publicado: 2021
Materias:
Ciencias Económicas
Yields
Forecasting
Climate
Mixed-frequency
Soybeans
Rendimientos
Predicciones
Clima
Frecuencia mixta
Soja
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/145346
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-145346
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Económicas
Yields
Forecasting
Climate
Mixed-frequency
Soybeans
Rendimientos
Predicciones
Clima
Frecuencia mixta
Soja
spellingShingle Ciencias Económicas
Yields
Forecasting
Climate
Mixed-frequency
Soybeans
Rendimientos
Predicciones
Clima
Frecuencia mixta
Soja
Cornejo, Magdalena
Forecasting crop yields through climate variables using mixed frequency data: the case of Argentine soybeans
topic_facet Ciencias Económicas
Yields
Forecasting
Climate
Mixed-frequency
Soybeans
Rendimientos
Predicciones
Clima
Frecuencia mixta
Soja
description 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.
format Articulo
Articulo
author Cornejo, Magdalena
author_facet Cornejo, Magdalena
author_sort Cornejo, Magdalena
title Forecasting crop yields through climate variables using mixed frequency data: the case of Argentine soybeans
title_short Forecasting crop yields through climate variables using mixed frequency data: the case of Argentine soybeans
title_full Forecasting crop yields through climate variables using mixed frequency data: the case of Argentine soybeans
title_fullStr Forecasting crop yields through climate variables using mixed frequency data: the case of Argentine soybeans
title_full_unstemmed Forecasting crop yields through climate variables using mixed frequency data: the case of Argentine soybeans
title_sort forecasting crop yields through climate variables using mixed frequency data: the case of argentine soybeans
publishDate 2021
url http://sedici.unlp.edu.ar/handle/10915/145346
work_keys_str_mv AT cornejomagdalena forecastingcropyieldsthroughclimatevariablesusingmixedfrequencydatathecaseofargentinesoybeans
AT cornejomagdalena pronosticosdelrendimientodeloscultivosatravesdevariablesclimaticasusandodatosenfrecuenciasmixtaselcasoargentino
bdutipo_str Repositorios
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