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

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  • 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
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    References listed on IDEAS

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    1. 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.
    2. Linh Vu Hoang, 2009. "Analysis of Calorie and Micronutrient Consumption in Vietnam," Working Papers 14, Development and Policies Research Center (DEPOCEN), Vietnam.
    3. 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.
    4. 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.
    5. 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.
    6. Bhargava, Alok, 2012. "Food, Economics, and Health," OUP Catalogue, Oxford University Press, number 9780199663910.
    7. repec:bla:devpol:v:21:y:2003:i:5-6:p:581-597 is not listed on IDEAS
    8. 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.
    9. Ogundari, Kolawole & Abdulai, Awudu, 2013. "Examining the heterogeneity in calorie–income elasticities: A meta-analysis," Food Policy, Elsevier, vol. 40(C), pages 119-128.
    10. 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.
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    Keywords

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