IDEAS home Printed from https://ideas.repec.org/p/ags/iaae09/51538.html
   My bibliography  Save this paper

Fat Chance: Modelling the Socio-Economic Determinants of Dietary Fat Intake in China

Author

Listed:
  • Shankar, Bhavani

Abstract

Quantile Regression methods have much to offer the investigation of the determinants of dietary intake. Dietary inadequacy or excess occurs at the tails of nutrient and food intakes, and it seems intuitive that intake responses in these areas will differ from elsewhere along the intake distribution. We apply quantile regression to examine the drivers of a key aspect of dietary health, fat density of energy intake in China. The sample of 2612 individuals between the ages of 20 and 45 is derived from the China Health and Nutrition Survey. The following insights emerge: (i) Fat density increases with income, but worryingly the income effect is more pronounced at the upper conditional tail of fat intake (ii) While it is confirmed that an urban location contributes to higher fat density for the most part, this effect disappears at the upper conditional quantiles, suggesting that, at the most unhealthy levels of fat density conditional on covariates, the problem is as much a rural one as it is urban.

Suggested Citation

  • Shankar, Bhavani, 2009. "Fat Chance: Modelling the Socio-Economic Determinants of Dietary Fat Intake in China," 2009 Conference, August 16-22, 2009, Beijing, China 51538, International Association of Agricultural Economists.
  • Handle: RePEc:ags:iaae09:51538
    DOI: 10.22004/ag.econ.51538
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/51538/files/IAAE%202009%20submission%20-%20Shankar1.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.51538?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. Behrman, Jere R & Deolalikar, Anil B, 1987. "Will Developing Country Nutrition Improve with Income? A Case Study for Rural South India," Journal of Political Economy, University of Chicago Press, vol. 95(3), pages 492-507, June.
    2. Abdulai, Awudu & Aubert, Dominique, 2004. "Nonparametric and parametric analysis of calorie consumption in Tanzania," Food Policy, Elsevier, vol. 29(2), pages 113-129, April.
    3. Fang, Cheng & Beghin, John C., 2002. "Urban Demand for Edible Oils and Fats in China: Evidence from Household Survey Data," Journal of Comparative Economics, Elsevier, vol. 30(4), pages 732-753, December.
    4. J. Gibson & S. Rozelle, 2002. "How Elastic is Calorie Demand? Parametric, Nonparametric, and Semiparametric Results for Urban Papua New Guinea," Journal of Development Studies, Taylor & Francis Journals, vol. 38(6), pages 23-46.
    5. Du, Shufa & Mroz, Tom A. & Zhai, Fengying & Popkin, Barry M., 2004. "Rapid income growth adversely affects diet quality in China--particularly for the poor!," Social Science & Medicine, Elsevier, vol. 59(7), pages 1505-1515, October.
    6. Yen, Steven T. & Fang, Cheng & Su, Shew-Jiuan, 2004. "Household food demand in urban China: a censored system approach," Journal of Comparative Economics, Elsevier, vol. 32(3), pages 564-585, September.
    7. Behrman, Jere R. & Wolfe, Barbara L., 1984. "More evidence on nutrition demand : Income seems overrated and women's schooling underemphasized," Journal of Development Economics, Elsevier, vol. 14(1), pages 105-128.
    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. Zhen Miao & John C. Beghin & Helen H. Jensen, 2013. "Accounting For Product Substitution In The Analysis Of Food Taxes Targeting Obesity," Health Economics, John Wiley & Sons, Ltd., vol. 22(11), pages 1318-1343, November.

    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. Bhavani Shankar & Yi Liu, 2007. "Will rising household incomes solve China's micronutrient deficiency problems?," Economics Bulletin, AccessEcon, vol. 15(10), pages 1-14.
    2. repec:ebl:ecbull:v:15:y:2007:i:10:p:1-14 is not listed on IDEAS
    3. Tankari, Mahamadou R., 2014. "L’élasticité calorie-revenu est-elle faible au Niger ?," Revue d'Etudes en Agriculture et Environnement, Editions NecPlus, vol. 95(04), pages 473-491, December.
    4. Santeramo, Fabio Gaetano & Shabnam, Nadia, 2015. "The income-elasticity of calories, macro and micro nutrients: What is the literature telling us?," MPRA Paper 63754, University Library of Munich, Germany.
    5. Biswabhusan Bhuyan & Bimal Kishore Sahoo & Damodar Suar, 2020. "Quantile Regression Analysis of Predictors of Calorie Demand in India: An Implication for Sustainable Development Goals," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(4), pages 825-859, December.
    6. Mohammad Ali & Kira M. Villa & Janak Joshi, 2018. "Health and hunger: nutrient response to income depending on caloric availability in Nepal," Agricultural Economics, International Association of Agricultural Economists, vol. 49(5), pages 611-621, September.
    7. Ogundari, Kolawole & Abdulai, Awudu, 2013. "Examining the heterogeneity in calorie–income elasticities: A meta-analysis," Food Policy, Elsevier, vol. 40(C), pages 119-128.
    8. Chandana Maitra & Sriram Shankar & D.S. Prasada Rao, 2016. "Income Poor or Calorie Poor? Who should get the Subsidy?," Discussion Papers Series 564, School of Economics, University of Queensland, Australia.
    9. Emmanuel Skoufias & Vincenzo Di Maro & Teresa González‐Cossío & Sonia Rodríguez Ramírez, 2009. "Nutrient consumption and household income in rural Mexico," Agricultural Economics, International Association of Agricultural Economists, vol. 40(6), pages 657-675, November.
    10. Indunil De Silva & Sudarno Sumarto, 2018. "Child Malnutrition in Indonesia: Can Education, Sanitation and Healthcare Augment the Role of Income?," Journal of International Development, John Wiley & Sons, Ltd., vol. 30(5), pages 837-864, July.
    11. De Zhou & Xiaohua Yu, 2015. "Calorie Elasticities with Income Dynamics: Evidence from the Literature," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 37(4), pages 575-601.
    12. Jing You, 2014. "Dietary change, nutrient transition and food security in fast-growing China," Chapters, in: Raghbendra Jha & Raghav Gaiha & Anil B. Deolalikar (ed.), Handbook on Food, chapter 9, pages 204-245, Edward Elgar Publishing.
    13. Jumrani, Jaya, 2023. "How responsive are nutrients in India? Some recent evidence," Food Policy, Elsevier, vol. 114(C).
    14. Ecker, Olivier & Qaim, Matin, 2011. "Analyzing Nutritional Impacts of Policies: An Empirical Study for Malawi," World Development, Elsevier, vol. 39(3), pages 412-428, March.
    15. Hamidou Jawara & Rainer Thiele, 2021. "The Nutrient-Income Elasticity in Ultra-Poor Households: Evidence from Kenya," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 33(6), pages 1795-1819, December.
    16. Salois, Matthew & Tiffin, Richard & Balcombe, Kelvin, 2010. "Calorie and Nutrient Consumption as a Function of Income: A Cross-Country Analysis," MPRA Paper 24726, University Library of Munich, Germany.
    17. Ogundari, Kolawole & Abdulai, Awudu, 2012. "A meta-analysis of the response of calorie demand to income changes," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 123287, International Association of Agricultural Economists.
    18. Emmanuel Skoufias & Vincenzo Di Maro & Teresa Gonzalez-Cossio & Sonia Rodriguez Ramirez, 2011. "Food quality, calories and household income," Applied Economics, Taylor & Francis Journals, vol. 43(28), pages 4331-4342.
    19. Tian, Xu & Yu, Xiaohua, 2015. "Using semiparametric models to study nutrition improvement and dietary change with different indices: The case of China," Food Policy, Elsevier, vol. 53(C), pages 67-81.
    20. P. J. Dawson & A. I. Sanjuan, 2011. "Calorie consumption and income: panel cointegration and causality evidence in developing countries," Applied Economics Letters, Taylor & Francis Journals, vol. 18(15), pages 1455-1461.
    21. Jing You & Katsushi S. Imai & Raghav Gaiha, 2014. "Decoding the Growth-Nutrition Nexus in China: Inequality, Uncertainty and Food Insecurity," Discussion Paper Series DP2014-28, Research Institute for Economics & Business Administration, Kobe University, revised Dec 2014.

    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:ags:iaae09:51538. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/iaaeeea.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.