Food Security Simulator – Papua New Guinea

cg.authorship.typesCGIAR single centre
cg.contributor.donorAustralian Department of Foreign Affairs and Trade
cg.contributor.donorAustralian Centre for International Agricultural Research
cg.coverage.countryPapua New Guinea
cg.coverage.regionOceania
cg.coverage.regionMelanesia
cg.coverage.regionAsia
cg.identifier.dataurlhttps://doi.org/10.7910/DVN/LVOLEP
cg.identifier.dataurlhttps://doi.org/10.7910/DVN/NS1A7V
cg.identifier.dataurlhttps://doi.org/10.7910/DVN/WWMN6H
cg.identifier.dataurlhttps://doi.org/10.7910/DVN/OXZ0H6
cg.identifier.doihttps://doi.org/10.7910/dvn/b7in6l
cg.identifier.projectIFPRI - Foresight and Policy Modeling Unit
cg.identifier.projectIFPRI - Development Strategies and Governance Unit
cg.identifier.publicationRankNot ranked
cg.placeWashington, DC
cg.reviewStatusInternal Review
cg.subject.impactAreaPoverty reduction, livelihoods and jobs
cg.subject.impactAreaNutrition, health and food security
cg.subject.sdgSDG 1 - No poverty
cg.subject.sdgSDG 3 - Good health and well-being
dc.contributor.authorInternational Food Policy Research Institute
dc.date.accessioned2025-06-05T14:58:26Z
dc.date.available2025-06-05T14:58:26Z
dc.identifier.urihttps://hdl.handle.net/10568/174997
dc.titleFood Security Simulator – Papua New Guineaen
dcterms.abstractThe Food Security Simulator Papua New Guinea (FSS-PNG) is an innovative and easy-to-use, MS-Excel-based tool for assessing the potential short-term impacts of food price or household income shocks, along with changes in preferences, on food security and people’s diets. The Simulator is an ideal tool for first-cut forward-looking evaluations of direct, household-level outcomes of economic crises and policy responses in a timely manner. The tool allows users to enter positive and negative price or income changes in percentage terms and provides simulated changes for a diverse set of food-consumption- and diet-quality-related indicators. In addition to detailed tabular presentations of all simulation results by household income quintile and residential area, key indicator results are summarized in concise overview tables and visualized in graphs for easy export and use in reports. The underlying data include estimates from representative household survey data and rigorous, sophisticated food demand models to capture consumer behavior.en
dcterms.accessRightsOpen Access
dcterms.audienceAcademics
dcterms.audienceGeneral Public
dcterms.audiencePolicy Makers
dcterms.bibliographicCitationInternational Food Policy Research Institute (IFPRI). 2025. Food Security Simulator – Papua New Guinea. Washington, DC: IFPRI [dataset]. https://doi.org/10.7910/DVN/B7IN6L. Harvard Dataverse. Version 1.
dcterms.isPartOfCountry Level
dcterms.issued2025-06-04
dcterms.languageen
dcterms.licenseCC-BY-4.0
dcterms.publisherInternational Food Policy Research Institute
dcterms.relationhttps://doi.org/10.2499/p15738coll2.134675
dcterms.relationhttps://doi.org/10.1016/j.foodpol.2023.102471
dcterms.subjectfood security
dcterms.subjectconsumer behavior
dcterms.subjectdiet quality
dcterms.subjectfood consumption
dcterms.subjecthousehold surveys
dcterms.subjectsimulation models
dcterms.typeDataset

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