Abstract
Forecasting food production is important to identify possible shortages in supply and, thus, food security risks. Such forecasts may improve input allocation decisions that affect agribusiness and the input supply industry. This paper explains methods and data used to forecast acreage of four crops that are particularly important staple commodities in the world, namely wheat, corn, rice, and soybeans for major global producer countries. It focuses on forecasting acreage—one of the two major determinants of grain production—3 months before planting starts with publicly available data. To this end, we use data from the period 1991 to 2013 and perform an out-of-sample forecast for the year 2014. A particular characteristic of this study is that the respective acreage determinants for each country and each crop are identified and used for forecasting separately. This allows accounting for the heterogeneity in the countries’ agricultural, political, and economic systems through a country-specific model specification. The performance of the resulting forecasting tool is validated with ex-post prediction of acreage against historical data.
Highlights
Food insecurity remains to be a critical challenge to the world’s poor today
In order to minimize the risk of a pre-test bias, we considered the Bayesian information criterion (BIC) for our model selection
The results show that rainfall is the most important driver of Indian rice area
Summary
Food insecurity remains to be a critical challenge to the world’s poor today. The focus of this study is not food insecurity and hunger per se. It instead addresses one major component of food security, that is, food production. Our focus is on production of the world’s principal staple crops, namely wheat, rice, maize, and corn. These crops are crucial for the fight against global food insecurity since they are major sources of food in several parts of the world, comprising three quarters of the food calories in global food production.
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