Replication Data for: Nutrition Transition and the Structure of Global Food Demand

DOI

Estimating future demand for food is a critical aspect of global food security analyses. The process linking dietary changes to wealth is known as the nutrition transition and presents well-identified features that help to predict consumption changes in poor countries. This study proposes to represent the nutrition transition with a nonhomothetic, flexible-in-income, demand system. The resulting model is estimated statistically based on cross-sectional information from FAOSTAT. It captures the main features of the nutrition transition: rise in demand for calories associated with income growth; diversification of diets away from starchy staples; and a large increase in caloric demand for animal-based products, fats, and sweeteners. The estimated model is used to project food demand between 2010 and 2050 based on a set of plausible futures (trend projections and Shared Socioeconomic Pathways scenarios). The main results of these projections are: (1) global food demand will increase by 47%, less than half the growth in the previous four decades; (2) this growth will be attributable mainly to lower-middle-income and low-income countries; (3) the structure of global food demand will change over the period, with a doubling of demand for animal-based calories and a much smaller 19% increase in demand for starchy staples; and (4) the analysis of a range of population and income projections reveals important uncertainties: depending on the scenario, the projected increases in demand for animal-based and vegetal-based calories range from 74 to 114% and from 20 to 42%, respectively.

Identifier
DOI https://doi.org/10.15454/9DZLRA
Related Identifier IsCitedBy https://doi.org/10.1093/ajae/aay030
Metadata Access https://entrepot.recherche.data.gouv.fr/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.15454/9DZLRA
Provenance
Creator Gouel, Christophe ORCID logo; Guimbard, Houssein ORCID logo
Publisher Recherche Data Gouv
Contributor Gouel, Christophe
Publication Year 2018
Rights info:eu-repo/semantics/openAccess
OpenAccess true
Contact Gouel, Christophe (INRA - Institut National de la Recherche Agronomique)
Representation
Resource Type Dataset
Format application/zip; application/vnd.ms-excel.sheet.macroEnabled.12
Size 268083083; 97706
Version 4.1
Discipline Agriculture, Forestry, Horticulture; Social Sciences; Nutritional Sciences; Economics