IDEAS home Printed from https://ideas.repec.org/p/tse/wpaper/31804.html
   My bibliography  Save this paper

Calorie intake and income in China: New evidence using semiparametric modelling with generalized additive models

Author

Listed:
  • Simioni, Michel
  • Thomas-Agnan, Christine
  • Trinh, Thi-Huong

Abstract

Recent research on calorie intake and income relationship abounds with parametric models but usually gives inconclusive results. Our paper aims at contributing to this literature by using recent advances in the estimation of generalized additive models with penalized spline regression smoothing (GAM). These semi-parametric models enable mixing parametric and nonparametric functions of explanatory variables and enlarge the distribution of the response variable. The revealed performance test (Racine and Parmeter, 2014), supported by simulation data, shows that GAM models outperform the parametric models. Using data from CHNS in 2006, 2009 and 2011, we find a positive and statistically significant relationship between household calorie intake and household income for the poor. Then the impact of increasing income on calorie consumption slows down for the middle class and the rich. In addition, we find that income-calorie elasticities are generally small, ranging from 0.07 to 0.12.

Suggested Citation

  • Simioni, Michel & Thomas-Agnan, Christine & Trinh, Thi-Huong, 2017. "Calorie intake and income in China: New evidence using semiparametric modelling with generalized additive models," TSE Working Papers 17-826, Toulouse School of Economics (TSE).
    • Handle: RePEc:tse:wpaper:31804
    as

    Download full text from publisher

    File URL: https://www.tse-fr.eu/sites/default/files/TSE/documents/doc/wp/2017/wp_tse_826.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ogundari, Kolawole & Abdulai, Awudu, 2013. "Examining the heterogeneity in calorie–income elasticities: A meta-analysis," Food Policy, Elsevier, vol. 40(C), pages 119-128.
    2. Simon N. Wood, 2003. "Thin plate regression splines," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 95-114, February.
    3. Bhargava, Alok, 2012. "Food, Economics, and Health," OUP Catalogue, Oxford University Press, number 9780199663910.
    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. Marra, Giampiero & Wood, Simon N., 2011. "Practical variable selection for generalized additive models," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2372-2387, July.
    6. Barry M. Popkin, 2003. "The Nutrition Transition in the Developing World," Development Policy Review, Overseas Development Institute, vol. 21(5-6), pages 581-597, December.
    7. 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.
    8. Linh Vu Hoang, 2009. "Analysis of Calorie and Micronutrient Consumption in Vietnam," Working Papers 14, Development and Policies Research Center (DEPOCEN), Vietnam.
    9. Peng Nie & Alfonso Sousa-Poza, 2016. "A fresh look at calorie-income elasticities in China," China Agricultural Economic Review, Emerald Group Publishing Limited, vol. 8(1), pages 55-80, February.
    10. Racine, Jeffrey & Su, Liangjun & Ullah, Aman, 2014. "The Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics," OUP Catalogue, Oxford University Press, number 9780199857944.
    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. Simioni, Michel & Thomas-Agnan, Christine & Trinh, Thi-Huong, 2017. "A Fresh Look at the Nutrition Transition in Vietnam using Semiparametric Modeling," TSE Working Papers 17-842, Toulouse School of Economics (TSE).
    2. Trinh Thi, Huong & Simioni, Michel & Thomas-Agnan, Christine, 2018. "Assessing the nonlinearity of the calorie-income relationship: An estimation strategy – With new insights on nutritional transition in Vietnam," World Development, Elsevier, vol. 110(C), pages 192-204.
    3. Jumrani, Jaya, 2023. "How responsive are nutrients in India? Some recent evidence," Food Policy, Elsevier, vol. 114(C).
    4. 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.
    5. 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.
    6. Smith, Lisa C., 2015. "The great Indian calorie debate: Explaining rising undernourishment during India’s rapid economic growth," Food Policy, Elsevier, vol. 50(C), pages 53-67.
    7. 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.
    8. 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.
    9. Hui Wang & Yingjie Yu & Xu Tian, 2019. "Does Eating-Away-from-Home Increase the Risk of a Metabolic Syndrome Diagnosis?," IJERPH, MDPI, vol. 16(4), pages 1-14, February.
    10. Gressani, Oswaldo & Lambert, Philippe, 2021. "Laplace approximations for fast Bayesian inference in generalized additive models based on P-splines," Computational Statistics & Data Analysis, Elsevier, vol. 154(C).
    11. 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.
    12. Théo Michelot & Richard Glennie & Catriona Harris & Len Thomas, 2021. "Varying-Coefficient Stochastic Differential Equations with Applications in Ecology," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(3), pages 446-463, September.
    13. Ren, Yanjun & Castro Campos, Bente & Loy, Jens-Peter & Brosig, Stephan, 2019. "Low-income and overweight in China: Evidence from a life-course utility model," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 18(8), pages 1753-1767.
    14. David C. Broadstock & Shunsuke Managi & Roman Matousek & Nickolaos G. Tzeremes, 2019. "Does doing “good” always translate into doing “well”? An eco‐efficiency perspective," Business Strategy and the Environment, Wiley Blackwell, vol. 28(6), pages 1199-1217, September.
    15. Ren, Yanjun & Li, Hui & Wang, Xiaobing, 2019. "Family income and nutrition-related health: Evidence from food consumption in China," Social Science & Medicine, Elsevier, vol. 232(C), pages 58-76.
    16. Kuhlgatz, Christian H. & Huang, Jiaqi & Antonides, Gerrit & Nie, Fengying, 2018. "The Effect of Food Prices and Own-produced Food on Food Security of Chinese Rural Households," 2018 Annual Meeting, August 5-7, Washington, D.C. 273988, Agricultural and Applied Economics Association.
    17. Li Zhou & Xiaohong Chen & Lei Lei, 2018. "Intra-Household Allocation of Nutrients in an Opening China," IJERPH, MDPI, vol. 15(4), pages 1-24, April.
    18. Vijay A. Murik, 2013. "Bond pricing with a surface of zero coupon yields," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 53(2), pages 497-512, June.
    19. Francesco Brizzi & Paul J. Birrell & Martyn T. Plummer & Peter Kirwan & Alison E. Brown & Valerie C. Delpech & O. Noel Gill & Daniela Angelis, 2019. "Extending Bayesian back-calculation to estimate age and time specific HIV incidence," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(4), pages 757-780, October.
    20. M.L. Nores & M.P. Díaz, 2016. "Bootstrap hypothesis testing in generalized additive models for comparing curves of treatments in longitudinal studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(5), pages 810-826, April.

    More about this item

    Keywords

    Calorie intake and income; generalized additive models; CHNS data; revealed performance test; cross validation procedure;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:tse:wpaper:31804. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/tsetofr.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.