Measuring and Modeling Food Losses

Mingione Marco (), Fabi Carola () and Lasinio Giovanna Jona ()
Additional contact information
Mingione Marco: University of Rome La Sapienza, Department of Statistical Sciences, Piazzale Aldo Moro 5, Rome, 00185, Italy.
Fabi Carola: Food and Agriculture Organization of the United Nations, Statistics Division, Rome, Italy.
Lasinio Giovanna Jona: University of Rome La Sapienza, Department of Statistical Sciences, Piazzale Aldo Moro 5, Rome, 00185, Italy.

Journal of Official Statistics, 2021, vol. 37, issue 1, 171-211

Abstract: Within the context of Sustainable Development Goals, progress towards Target 12.3 can be measured and monitored with the Food Loss Index. A major challenge is the lack of data, which dictated many methodology decisions. Therefore, the objective of this work is to present a possible improvement to the modeling approach used by the Food and Agricultural Organization in estimating the annual percentage of food losses by country and commodity. Our proposal combines robust statistical techniques with the strict adherence to the rules of the official statistics. In particular, the case study focuses on cereal crops, which currently have the highest (yet incomplete) data coverage and allow for more ambitious modeling choices. Cereal data is available in 66 countries and 14 different cereal commodities from 1991 to 2014. We use the annual food loss as response variable, expressed as percentage over production, by country and cereal commodity. The estimation work is twofold: it aims at selecting the most important factors explaining losses worldwide, comparing two Bayesian model selection approaches, and then at predicting losses with a Beta regression model in a fully Bayesian framework.

Keywords: Bayesian variable selection; Beta mixed model; SDG 12.3 (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.2478/jos-2021-0008 (text/html)

Related works:
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:vrs:offsta:v:37:y:2021:i:1:p:171-211:n:5

DOI: 10.2478/jos-2021-0008

Access Statistics for this article

Journal of Official Statistics is currently edited by Annica Isaksson and Ingegerd Jansson

More articles in Journal of Official Statistics from Sciendo
Bibliographic data for series maintained by Peter Golla ().