Probabilistic Decision Tools for Determining Impacts of Agricultural Development Policy on Household Nutrition

Governments around the world have agreed to end hunger and food insecurity and to improve global nutrition, largely through changes to agriculture and food systems. However, they are faced with a lot of uncertainty when making policy decisions, since any agricultural changes will influence social an...

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Main Authors: Whitney, Cory W., Lanzanova, D., Muchiri, C., Shepherd, Keith D., Rosenstock, Todd S., Krawinkel, M., Tabuti, J. R. S., Luedeling, Eike
Format: Journal Article
Language:Inglés
Published: Wiley 2018
Online Access:https://hdl.handle.net/10568/91685
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author Whitney, Cory W.
Lanzanova, D.
Muchiri, C.
Shepherd, Keith D.
Rosenstock, Todd S.
Krawinkel, M.
Tabuti, J. R. S.
Luedeling, Eike
author_browse Krawinkel, M.
Lanzanova, D.
Luedeling, Eike
Muchiri, C.
Rosenstock, Todd S.
Shepherd, Keith D.
Tabuti, J. R. S.
Whitney, Cory W.
author_facet Whitney, Cory W.
Lanzanova, D.
Muchiri, C.
Shepherd, Keith D.
Rosenstock, Todd S.
Krawinkel, M.
Tabuti, J. R. S.
Luedeling, Eike
author_sort Whitney, Cory W.
collection Repository of Agricultural Research Outputs (CGSpace)
description Governments around the world have agreed to end hunger and food insecurity and to improve global nutrition, largely through changes to agriculture and food systems. However, they are faced with a lot of uncertainty when making policy decisions, since any agricultural changes will influence social and biophysical systems, which could yield either positive or negative nutrition outcomes. We outline a holistic probability modeling approach with Bayesian Network (BN) models for nutritional impacts resulting from agricultural development policy. The approach includes the elicitation of expert knowledge for impact model development, including sensitivity analysis and value of information calculations. It aims at a generalizable methodology that can be applied in a wide range of contexts. To showcase this approach, we develop an impact model of Vision 2040, Uganda's development strategy, which, among other objectives, seeks to transform the country's agricultural landscape from traditional systems to large-scale commercial agriculture. Model results suggest that Vision 2040 is likely to have negative outcomes for the rural livelihoods it intends to support; it may have no appreciable influence on household hunger but, by influencing preferences for and access to quality nutritional foods, may increase the prevalence of micronutrient deficiency. The results highlight the trade-offs that must be negotiated when making decisions regarding agriculture for nutrition, and the capacity of BNs to make these trade-offs explicit. The work illustrates the value of BNs for supporting evidence-based agricultural development decisions.
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spelling CGSpace916852024-08-27T10:37:17Z Probabilistic Decision Tools for Determining Impacts of Agricultural Development Policy on Household Nutrition Whitney, Cory W. Lanzanova, D. Muchiri, C. Shepherd, Keith D. Rosenstock, Todd S. Krawinkel, M. Tabuti, J. R. S. Luedeling, Eike Governments around the world have agreed to end hunger and food insecurity and to improve global nutrition, largely through changes to agriculture and food systems. However, they are faced with a lot of uncertainty when making policy decisions, since any agricultural changes will influence social and biophysical systems, which could yield either positive or negative nutrition outcomes. We outline a holistic probability modeling approach with Bayesian Network (BN) models for nutritional impacts resulting from agricultural development policy. The approach includes the elicitation of expert knowledge for impact model development, including sensitivity analysis and value of information calculations. It aims at a generalizable methodology that can be applied in a wide range of contexts. To showcase this approach, we develop an impact model of Vision 2040, Uganda's development strategy, which, among other objectives, seeks to transform the country's agricultural landscape from traditional systems to large-scale commercial agriculture. Model results suggest that Vision 2040 is likely to have negative outcomes for the rural livelihoods it intends to support; it may have no appreciable influence on household hunger but, by influencing preferences for and access to quality nutritional foods, may increase the prevalence of micronutrient deficiency. The results highlight the trade-offs that must be negotiated when making decisions regarding agriculture for nutrition, and the capacity of BNs to make these trade-offs explicit. The work illustrates the value of BNs for supporting evidence-based agricultural development decisions. 2018-03 2018-03-15T08:56:58Z 2018-03-15T08:56:58Z Journal Article https://hdl.handle.net/10568/91685 en Open Access application/pdf Wiley Whitney, C.W.; Lanzanova, D.; Muchiri, C.; Shepherd, K. D.; Rosenstock, T. S.; Krawinkel, M.; Tabuti, J. R. S.; Luedeling, E. 2018. Probabilistic decision tools for determining impacts of agricultural development policy on household nutrition. Earth's Future. doi:10.1002/2017EF000765
spellingShingle Whitney, Cory W.
Lanzanova, D.
Muchiri, C.
Shepherd, Keith D.
Rosenstock, Todd S.
Krawinkel, M.
Tabuti, J. R. S.
Luedeling, Eike
Probabilistic Decision Tools for Determining Impacts of Agricultural Development Policy on Household Nutrition
title Probabilistic Decision Tools for Determining Impacts of Agricultural Development Policy on Household Nutrition
title_full Probabilistic Decision Tools for Determining Impacts of Agricultural Development Policy on Household Nutrition
title_fullStr Probabilistic Decision Tools for Determining Impacts of Agricultural Development Policy on Household Nutrition
title_full_unstemmed Probabilistic Decision Tools for Determining Impacts of Agricultural Development Policy on Household Nutrition
title_short Probabilistic Decision Tools for Determining Impacts of Agricultural Development Policy on Household Nutrition
title_sort probabilistic decision tools for determining impacts of agricultural development policy on household nutrition
url https://hdl.handle.net/10568/91685
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