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 target variable interest -crop yields- order to get short-term forecasts. Aggregate disaggregate data, alternative weighting schemes di erent updating are used evaluate forecasting performance. study focuses case soybean yields Argentina. Results show that models including high weather data outperformed particularly during three consecutive compaigns after 2008/09 when yield decreased almost by 50%. Furthermore, forecast combinations showed better performance individual models.