Determinants of the Socioeconomic and Spatial Pattern of Undernutrition by Sex in India: A Geoadditive Semi-parametric Regression Approach

  • Christiane Belitz
  • Judith Hübner
  • Stephan Klasen
  • Stefan Lang


In this paper, we use geoadditive semiparametric regression models to study the determinants of chronic undernutrition of boys and girls in India in 1998/99. A particular focus of our paper is to explain the strong regional pattern in undernutrition and sex differences in determinants of undernutrition. We find that determinants associated with competition for household resources and cultural factors are more important for the nutrition of girls than boys, while boys’ nutrition reactsmore sensitively to nutrition and medical care access. With our models we are able to explain a large portion of the spatial pattern of undernutrition of boys and girls, but significant spatial patterns remain. We are also able to fully explain the spatial pattern of sex differences in undernutrition with our empirical model.


Spatial Effect Semiparametric Regression National Family Health Survey Linear Index Uttar Pradesh 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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We would like to thank Monica Das Gupta, Davic Sahn, Paul Schultz, Amartya Sen, and Lisa Smitz as well as participants at workshops in Munich, Tübingen, IFPRI, and Göttingen for helpful comments and discussion. Funding from the German Research Foundation is gratefully acknowledged. We also thank the IIPS for giving us access to the district location of households.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Christiane Belitz
    • 1
  • Judith Hübner
    • 2
  • Stephan Klasen
    • 3
  • Stefan Lang
    • 4
  1. 1.Institut für StatistikLudwig-Maximilians-Universität MünchenMünchenGermany
  2. 2.Institut für MathematikTechnische Universität MünchenMünchenGermany
  3. 3.Department of EconomicsUniversity of GöttingenGöttingenGermany
  4. 4.Department of StatisticsUniversity of InnsbruckInnsbruckAustria

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