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Measuring postharvest loss inequality: Method and applications

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  • Miljkovic, Dragan
  • Winter-Nelson, Alex

Abstract

Sustainably meeting future food demand requires increases in food production and reductions in the amount of food that is lost and wasted. This paper examines inequality in postharvest losses to reveal patterns and opportunities for intervention. We present a measure that provides information on the distribution of postharvest losses in a single graph, the postharvest loss inequality curve, or an index number, the postharvest loss inequality index. Inequality measurement can help direct policy measures to units generating the greatest postharvest losses and thereby support more favorable policy outcomes and cost/benefit relationships. Concepts and methods introduced here are empirically analyzed based on the African Postharvest Losses Information System data for maize losses in Sub-Saharan Africa. Empirical results indicate the presence of a great deal of variability and inequality in postharvest losses as measured by the postharvest loss inequality index. In the data analyzed, the postharvest loss inequality index better captures anomalies in data distribution such as outliers, skewness and kurtosis than the more direct measure of postharvest losses as a share of total maize production.

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  • Miljkovic, Dragan & Winter-Nelson, Alex, 2021. "Measuring postharvest loss inequality: Method and applications," Agricultural Systems, Elsevier, vol. 186(C).
    • Handle: RePEc:eee:agisys:v:186:y:2021:i:c:s0308521x20308453
    DOI: 10.1016/j.agsy.2020.102984
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    References listed on IDEAS

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    1. Schneider, Uwe A. & Havlík, Petr & Schmid, Erwin & Valin, Hugo & Mosnier, Aline & Obersteiner, Michael & Böttcher, Hannes & Skalský, Rastislav & Balkovic, Juraj & Sauer, Timm & Fritz, Steffen, 2011. "Impacts of population growth, economic development, and technical change on global food production and consumption," Agricultural Systems, Elsevier, vol. 104(2), pages 204-215, February.
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    3. Gastwirth, Joseph L, 1972. "The Estimation of the Lorenz Curve and Gini Index," The Review of Economics and Statistics, MIT Press, vol. 54(3), pages 306-316, August.
    4. Gastwirth, Joseph L, 1971. "A General Definition of the Lorenz Curve," Econometrica, Econometric Society, vol. 39(6), pages 1037-1039, November.
    5. Miljkovic, Dragan & Rimal, Arbindra, 2008. "The impact of socio-economic factors on political instability: A cross-country analysis," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 37(6), pages 2454-2463, December.
    6. Dragan Miljkovic, 2005. "Measuring and causes of inequality in farm sizes in the United States," Agricultural Economics, International Association of Agricultural Economists, vol. 33(1), pages 21-27, July.
    7. Affognon, Hippolyte & Mutungi, Christopher & Sanginga, Pascal & Borgemeister, Christian, 2015. "Unpacking Postharvest Losses in Sub-Saharan Africa: A Meta-Analysis," World Development, Elsevier, vol. 66(C), pages 49-68.
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    1. Barrera, Emiliano Lopez & Miljkovic, Dragan, 2022. "The link between the two epidemics provides an opportunity to remedy obesity while dealing with Covid-19," Journal of Policy Modeling, Elsevier, vol. 44(2), pages 280-297.
    2. Barnor, Kodjo & Caton, James & Miljkovic, Dragan, 2023. "The role of funding on research and science: The impact of glyphosate herbicides on health and the environment," Journal of Policy Modeling, Elsevier, vol. 45(1), pages 103-120.

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