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Does the Rotten Child Spoil His Companion? Spatial Peer Effects Among Children in Rural India

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  • Helmers, Christian
  • Patnam, Manasa

Abstract

This paper identifies the effect of neighborhood peer groups on childhood skill acquisition using observational data. We incorporate spatial peer interaction, defined as a child's nearest geographical neighbors, into a production function of child cognitive development in Andhra Pradesh, India. Our peer group definition takes the form of networks, whose structure allows us to separately identify endogenous peer effects and contextual effects. We exploit variation over time to avoid confounding correlated with social effects. Our results suggest that spatial peer and neighborhood effects are strongly positively associated with a child's cognitive skill formation. Further, we find that the presence of peer groups helps provide insurance against the negative impact of idiosyncratic shocks to child learning. We show that peer effects are robust to different specifications of peer interactions and investigate the sensitivity of our estimates to potential mis-specification of the network structure using Monte Carlo experiments.

Suggested Citation

  • Helmers, Christian & Patnam, Manasa, 2011. "Does the Rotten Child Spoil His Companion? Spatial Peer Effects Among Children in Rural India," Proceedings of the German Development Economics Conference, Berlin 2011 40, Verein für Socialpolitik, Research Committee Development Economics.
  • Handle: RePEc:zbw:gdec11:40
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    Cited by:

    1. Patacchini, Eleonora & Venanzoni, Giuseppe, 2014. "Peer effects in the demand for housing quality," Journal of Urban Economics, Elsevier, vol. 83(C), pages 6-17.
    2. Gibbons, Steve & Overman, Henry G. & Patacchini, Eleonora, 2015. "Spatial Methods," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 115-168, Elsevier.
    3. Jose-Alberto Guerra & Myra Mohnen, 2022. "Multinomial Choice with Social Interactions: Occupations in Victorian London," The Review of Economics and Statistics, MIT Press, vol. 104(4), pages 736-747, October.
    4. Tapsuwan, Sorada & Polyakov, Maksym & Bark, Rosalind & Nolan, Martin, 2015. "Valuing the Barmah–Millewa Forest and in stream river flows: A spatial heteroskedasticity and autocorrelation consistent (SHAC) approach," Ecological Economics, Elsevier, vol. 110(C), pages 98-105.
    5. Hatem Jemmali & Mohamed Amara, 2018. "On Measuring and Decomposing Inequality of Opportunity among Children: Evidence from Tunisia," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 13(1), pages 137-155, March.
    6. Topa, Giorgio & Zenou, Yves, 2015. "Neighborhood and Network Effects," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 561-624, Elsevier.
    7. Bet Caeyers, 2014. "Peer effects in development programme awareness of vulnerable groups in rural Tanzania," CSAE Working Paper Series 2014-11, Centre for the Study of African Economies, University of Oxford.
    8. Tisorn Songsermsawas & Kathy Baylis & Ashwini Chhatre & Hope Michelson, 2014. "Can Peers Improve Agricultural Productivity?," CESifo Working Paper Series 4958, CESifo.
    9. Roman Horvath, 2020. "Peer Effects in Central Banking," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 68(4), pages 764-814, December.
    10. Sintayehu Hailu Alemu & Luuk Kempen & Ruerd Ruben, 2018. "The Long Shadow of Faith-based Social Networks on Agricultural Performance: Evidence from Ethiopian Apple Growers," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 30(2), pages 297-319, April.
    11. Songsermsawas, Tisorn & Baylis, Kathy & Chhatre, Ashwini & Michelson, Hope, 2016. "Can Peers Improve Agricultural Revenue?," World Development, Elsevier, vol. 83(C), pages 163-178.
    12. Kelchtermans, Stijn & Neicu, Daniel & Teirlinck, Peter, 2020. "The role of peer effects in firms’ usage of R&D tax exemptions," Journal of Business Research, Elsevier, vol. 108(C), pages 74-91.
    13. Bet Caeyers, 2014. "Exclusion bias in empirical social interaction models: causes, consequences and solutions," CSAE Working Paper Series 2014-05, Centre for the Study of African Economies, University of Oxford.
    14. Songsermsawas, Tisorn & Baylis, Kathy & Chhatre, Ashwini & Michelson, Hope & Prasanna, Satya, 2015. "Friends or traders? Do social networks explain the use of market mechanisms by farmers in India," 2015 Conference, August 9-14, 2015, Milan, Italy 211206, International Association of Agricultural Economists.
    15. Gupta, Abhimanyu, 2023. "Efficient closed-form estimation of large spatial autoregressions," Journal of Econometrics, Elsevier, vol. 232(1), pages 148-167.
    16. repec:oxf:wpaper:wps/2014-05 is not listed on IDEAS
    17. Liangjun Su & Xi Qu, 2017. "Specification Test for Spatial Autoregressive Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 572-584, October.
    18. Baylis, Katherine R. & Paulson, Nicholas D. & Piras, Gianfranco, 2011. "Spatial Approaches to Panel Data in Agricultural Economics: A Climate Change Application," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 43(3), pages 1-14, August.
    19. repec:oxf:wpaper:wps/2014-11 is not listed on IDEAS
    20. Roychowdhury, Punarjit, 2019. "Peer effects in consumption in India: An instrumental variables approach using negative idiosyncratic shocks," World Development, Elsevier, vol. 114(C), pages 122-137.

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    More about this item

    Keywords

    Children; peer effects; cognitive skills; India;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population

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