IDEAS home Printed from https://ideas.repec.org/p/ecm/ausm04/170.html
   My bibliography  Save this paper

Derivation of Nutrient Prices from Household level Food Expenditure Data: Methodology and Applications

Author

Listed:
  • Ranjan Ray
  • Amita Majumder
  • Dipankor Coondoo
  • Geoffrey Lancaster

Abstract

In cross-country/cross-region multilateral consumer price level comparisons, differences in the mix of food items consumed in individual countries pose a major problem. Comparison of the level of prices of food items in two countries will be difficult, if the sets of food items consumed in the two countries are very different. However, if the data on average level of intake of major nutrients and some measure of the corresponding nutrient prices is available, a comparison of the level of nutrient prices is possible. At the household level, given the prices of food items actually paid and the corresponding levels of actual intake of different nutrients (from the consumption of various food items), it is possible, in principle, to work out a set of shadow prices of individual nutrients. In this context, it may be mentioned that the shadow prices of nutrients thus derived, being based on households' actual consumption information, would be influenced by the prices of food items consumed, nominal income, household attributes and other preference factors characterizing the individual households. Given such sets of household level nutrient prices and corresponding nutrient intakes for individual countries, a set of multilateral nutrient price index numbers may be worked out and a cross-country comparison of the nutrient price level performed. In this paper a regression analysis-based procedure has been proposed for estimation of household-level unit values of carbohydrates, protein and fat, using a cross-sectional household level data set on food expenditure, total consumer expenditure, quantities of nutrients consumed and related variables. The proposed procedure has been applied to the Indian household level data for the year 1999-2000 using the 55th round Consumer Expenditure Survey of the National Sample Survey Organisation, Govt. of India and subsequently analysed separately for the rural and urban sector of some selected major Indian States.

Suggested Citation

  • Ranjan Ray & Amita Majumder & Dipankor Coondoo & Geoffrey Lancaster, 2004. "Derivation of Nutrient Prices from Household level Food Expenditure Data: Methodology and Applications," Econometric Society 2004 Australasian Meetings 170, Econometric Society.
    • Handle: RePEc:ecm:ausm04:170
    as

    Download full text from publisher

    File URL: http://repec.org/esAUSM04/up.16025.1077757461.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. John Strauss & Duncan Thomas, 1998. "Health, Nutrition, and Economic Development," Journal of Economic Literature, American Economic Association, vol. 36(2), pages 766-817, June.
    2. D. Coondoo & A. Majumder & R. Ray, 2004. "A Method of Calculating Regional Consumer Price Differentials with Illustrative Evidence from India," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 50(1), pages 51-68, March.
    3. Stiglitz, Joseph E, 1976. "The Efficiency Wage Hypothesis, Surplus Labour, and the Distribution of Income in L.D.C.s," Oxford Economic Papers, Oxford University Press, vol. 28(2), pages 185-207, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Schneider, Kate R., 2022. "Nationally representative estimates of the cost of adequate diets, nutrient level drivers, and policy options for households in rural Malawi," Food Policy, Elsevier, vol. 113(C).

    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. Paula Carvalho Pereda & Denisard Cneio de Oliveira Alves, 2008. "Demand for Nutrients in Brazil," Anais do XXXVI Encontro Nacional de Economia [Proceedings of the 36th Brazilian Economics Meeting] 200807211136590, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    2. Aysit Tansel & Ceyhan Ozturk & Erkan Erdil, 2021. "The Impact of Body Mass Index on Growth, Schooling, Productivity, and Savings: A Cross-Country Study," Koç University-TUSIAD Economic Research Forum Working Papers 2118, Koc University-TUSIAD Economic Research Forum.
    3. Pinna Pintor, Matteo & Fumagalli, Elena & Suhrcke, Marc, 2024. "The impact of health on labour market outcomes: A rapid systematic review," Health Policy, Elsevier, vol. 143(C).
    4. Geoffrey Lancaster & Pushkar Maitra & Ranjan Ray, 2006. "Gender Bias in Nutrient Intake," South Asia Economic Journal, Institute of Policy Studies of Sri Lanka, vol. 7(2), pages 255-299, September.
    5. Angus Deaton, 2003. "Health, Inequality, and Economic Development," Journal of Economic Literature, American Economic Association, vol. 41(1), pages 113-158, March.
    6. Ferda HALICIOGLU, 2012. "The Demand for Calories in Turkey," Iktisat Isletme ve Finans, Bilgesel Yayincilik, vol. 27(316), pages 93-108.
    7. Renuka Mahadevan & Vincent Hoang, 2016. "Is There a Link Between Poverty and Food Security?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 128(1), pages 179-199, August.
    8. Raghbendra Jha & Raghav Gaiha & Anurag Sharma, 2005. "Poverty Nutrition Trap in Rural India," Departmental Working Papers 2005-02, The Australian National University, Arndt-Corden Department of Economics.
    9. Garance Genicot, 2005. "Malnutrition and Child Labor," Scandinavian Journal of Economics, Wiley Blackwell, vol. 107(1), pages 83-102, March.
    10. Ali, Mubarik & Farooq, Umar, 2004. "Dietary Diversity And Rural Labor Productivity: Evidence From Pakistan," 2004 Annual meeting, August 1-4, Denver, CO 20310, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    11. Marcos Vera-Hernández & Aida Galiano Martínez, 2008. "Health shocks, household consumption, and child nutrition," Working Papers. Serie EC 2008-14, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    12. Chakraborty, Shankha & Papageorgiou, Chris & Pérez Sebastián, Fidel, 2010. "Diseases, infection dynamics, and development," Journal of Monetary Economics, Elsevier, vol. 57(7), pages 859-872, October.
    13. Kota Ogasawara & Mizuki Komura, 2022. "Consequences of war: Japan’s demographic transition and the marriage market," Journal of Population Economics, Springer;European Society for Population Economics, vol. 35(3), pages 1037-1069, July.
    14. Banerji, Sanjay & Gupta, Manas Ranjan, 1997. "The efficiency wage given long-run employment and concave labor constraint," Journal of Development Economics, Elsevier, vol. 53(1), pages 185-195, June.
    15. Lee, Yoonjung, 2024. "Impacts of School Meals with Fortified Rice on Children's Health Outcomes and Cognitive Performance in Cambodia," 2024 Annual Meeting, July 28-30, New Orleans, LA 344061, Agricultural and Applied Economics Association.
    16. Cristiano Codagnone & Fabienne Abadie, 2010. "Strategic Intelligence Monitor on Personal Health Systems (SIMPHS): Structure of Available Data and New Measurement Framework with Selected Indicators," JRC Research Reports JRC62167, Joint Research Centre.
    17. Das, Jishnu & Hammer, Jeffrey & Sánchez-Paramo, Carolina, 2012. "The impact of recall periods on reported morbidity and health seeking behavior," Journal of Development Economics, Elsevier, vol. 98(1), pages 76-88.
    18. Karen Clay & Werner Troesken & Michael Haines, 2014. "Lead and Mortality," The Review of Economics and Statistics, MIT Press, vol. 96(3), pages 458-470, July.
    19. Haddad, Lawrence & Kanbur, Ravi, 1992. "Is There an Intrahousehold Kuznets Curve? Some Evidence from the Philippines," Public Finance = Finances publiques, , vol. 47(Supplemen), pages 77-93.
    20. Mohammed SHARIF, 2000. "Inverted “S”—The complete neoclassical labour-supply function," International Labour Review, International Labour Organization, vol. 139(4), pages 409-435, December.

    More about this item

    Keywords

    Nutrients; prices; multilateral; comparisons;
    All these keywords.

    JEL classification:

    • 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
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

    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:ecm:ausm04:170. 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: Christopher F. Baum (email available below). General contact details of provider: https://edirc.repec.org/data/essssea.html .

    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.