IDEAS home Printed from https://ideas.repec.org/a/vrs/seejeb/v12y2017i1p104-113n4.html
   My bibliography  Save this article

A Nutritional Analysis of the Food Basket in BIH: A Linear Programming Approach

Author

Listed:
  • Arnaut-Berilo Almira

    (Assistant Professor, School of Economics and Business, University of Sarajevo)

  • Delalic Adela

    (Assistant Professor, School of Economics and Business, University of Sarajevo)

  • Huseinbasic Adisa

    (School of Economics and Business, University of Sarajevo)

Abstract

This paper presents linear and goal programming optimization models for determining and analyzing the food basket in Bosnia and Herzegovina (BiH) in terms of adequate nutritional needs according to World Health Organization (WHO) standards and World Bank (WB) recommendations. A linear programming (LP) model and goal linear programming model (GLP) are adequate since price and nutrient contents are linearly related to food weight. The LP model provides information about the minimal value and the structure of the food basket for an average person in BiH based on nutrient needs. GLP models are designed to give us information on minimal deviations from nutrient needs if the budget is fixed. Based on these results, poverty analysis can be performed. The data used for the models consisted of 158 food items from the general consumption of the population of BiH according to COICOP classifications, with average prices in 2015 for these products.

Suggested Citation

  • Arnaut-Berilo Almira & Delalic Adela & Huseinbasic Adisa, 2017. "A Nutritional Analysis of the Food Basket in BIH: A Linear Programming Approach," South East European Journal of Economics and Business, Sciendo, vol. 12(1), pages 104-113, April.
  • Handle: RePEc:vrs:seejeb:v:12:y:2017:i:1:p:104-113:n:4
    DOI: 10.1515/jeb-2017-0004
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/jeb-2017-0004
    Download Restriction: no

    File URL: https://libkey.io/10.1515/jeb-2017-0004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Kyereme, Stephen S. & Thorbecke, Erik, 1987. "Food poverty profile and decomposition applied to Ghana," World Development, Elsevier, vol. 15(9), pages 1189-1199, September.
    2. Greer, Joel & Thorbecke, Erik, 1986. "A methodology for measuring food poverty applied to Kenya," Journal of Development Economics, Elsevier, vol. 24(1), pages 59-74, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Uche Ozughalu, 2016. "Relationship Between Household Food Poverty and Vulnerability to Food Poverty: Evidence from Nigeria," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 125(2), pages 567-587, January.
    2. Russell Davidson & Jean-Yves Duclos, 2000. "Statistical Inference for Stochastic Dominance and for the Measurement of Poverty and Inequality," Econometrica, Econometric Society, vol. 68(6), pages 1435-1464, November.
    3. Ye, Yuxiang & Koch, Steven F., 2021. "Measuring energy poverty in South Africa based on household required energy consumption," Energy Economics, Elsevier, vol. 103(C).
    4. Emily Schmidt & Rachel Gilbert & Brian Holtemeyer & Kristi Mahrt, 2021. "Poverty analysis in the lowlands of Papua New Guinea underscores climate vulnerability and need for income flexibility," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 65(1), pages 171-191, January.
    5. Ravallion, Martin & Lokshin, Michael, 2003. "On the utility consistency of poverty lines," Policy Research Working Paper Series 3157, The World Bank.
    6. Okushima, Shinichiro, 2016. "Measuring energy poverty in Japan, 2004–2013," Energy Policy, Elsevier, vol. 98(C), pages 557-564.
    7. Ravallion, Martin & Bidani, Benu, 1994. "How Robust Is a Poverty Profile?," The World Bank Economic Review, World Bank, vol. 8(1), pages 75-102, January.
    8. Sayema Haque Bidisha & Tanveer Mahmood & Md. Biplob Hossain, 2021. "Assessing Food Poverty, Vulnerability and Food Consumption Inequality in the Context of COVID-19: A Case of Bangladesh," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 155(1), pages 187-210, May.
    9. Geda, A. & de Jong, N. & Mwabu, G. & Kimenyi, M.S., 2001. "Determinants of poverty in Kenya : a household level analysis," ISS Working Papers - General Series 19095, International Institute of Social Studies of Erasmus University Rotterdam (ISS), The Hague.
    10. Ravallion, Martin & Sen, Binayak, 1994. "When method matters : toward a resolution of the debate about Bangladesh's poverty measures," Policy Research Working Paper Series 1359, The World Bank.
    11. Balisacan, Arsenio M., 1994. "Agricultural Growth and Rural Incomes: Rural Performance Indicators and Consumption Patterns," Discussion Papers DP 1994-12, Philippine Institute for Development Studies.
    12. Peter Svedberg, 1987. "Undernutrition in Sub-Saharan Africa: A Critical Assessment of the Evidence," WIDER Working Paper Series wp-1987-015, World Institute for Development Economic Research (UNU-WIDER).
    13. repec:agg:journl:1288 is not listed on IDEAS
    14. Folbre N., 1993. "Women and social security in Latin America, the Caribbean and sub- saharan Africa," ILO Working Papers 992932813402676, International Labour Organization.
    15. Korir, Lilian & Rizov, Marian & Ruto, Eric, 2020. "Food security in Kenya: Insights from a household food demand model," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 92, pages 99-108.
    16. Valerie Rhoe & Suresh Babu & William Reidhead, 2008. "An analysis of food security and poverty in Central Asia-case study from Kazakhstan," Journal of International Development, John Wiley & Sons, Ltd., vol. 20(4), pages 452-465.
    17. World Bank, 2008. "Mozambique - Beating the Odds : Sustaining Inclusion in a Growing Economy - A Mozambique Poverty, Gender, and Social Assessment, Volume 1. Main Report," World Bank Publications - Reports 7981, The World Bank Group.
    18. Aditi Dimri & François Maniquet, 2020. "Income poverty measurement in India: defining group-specific poverty lines or taking preferences into account?," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 18(2), pages 137-156, June.
    19. Besma Belhadj & Firas Kaabi, 2020. "New membership function for poverty measure," Metroeconomica, Wiley Blackwell, vol. 71(4), pages 676-688, November.
    20. Apata, T.G. & Apata, O.M. & Kehinde, A.L., 2015. "Explaining the ‘hungry farmer paradox’: Through dynamics of Nutritional Scarcity and Its Determinants among Farming Households in Southwestern, Nigeria," 2015 Conference, August 9-14, 2015, Milan, Italy 210955, International Association of Agricultural Economists.

    More about this item

    Keywords

    linear programming; goal programming; optimization; cost; nutrition; budget;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vrs:seejeb:v:12:y:2017:i:1:p:104-113:n:4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.