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Does the rotten child spoil his companion? Spatial peer effects among children in rural India

Author

Listed:
  • Christian Helmers
  • Manasa Patnam

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 identify endogenous peer effects and contextual effects separately. 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 explore the effect of peer groups in helping to provide insurance against the negative impact of idiosyncratic shocks to child learning. We find that the data reject full risk‐sharing, but cannot rule out the existence of partial risk‐sharing on behalf of peers. We show that peer effects are robust to different specifications of peer interactions and investigate the sensitivity of our estimates to potential misspecification of the network structure using Monte Carlo experiments.

Suggested Citation

  • Christian Helmers & Manasa Patnam, 2014. "Does the rotten child spoil his companion? Spatial peer effects among children in rural India," Quantitative Economics, Econometric Society, vol. 5, pages 67-121, March.
  • Handle: RePEc:wly:quante:v:5:y:2014:i::p:67-121
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    File URL: http://hdl.handle.net/10.1111/quan.2014.5.issue-1.x
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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. 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.
    4. 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.
    5. Manon Garrouste & Camille Hémet, 2024. "Neighbor Effects and Early Track Choices," Working Papers halshs-04655509, HAL.
    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. Gupta, Abhimanyu & Kokas, Sotirios & Michaelides, Alexander & Minetti, Raoul, 2025. "Networks and information in credit markets," Journal of Corporate Finance, Elsevier, vol. 94(C).
    9. Tisorn Songsermsawas & Kathy Baylis & Ashwini Chhatre & Hope Michelson, 2014. "Can Peers Improve Agricultural Productivity?," CESifo Working Paper Series 4958, CESifo.
    10. Roman Horvath, 2020. "Peer Effects in Central Banking," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 68(4), pages 764-814, December.
    11. 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.
    12. Songsermsawas, Tisorn & Baylis, Kathy & Chhatre, Ashwini & Michelson, Hope, 2016. "Can Peers Improve Agricultural Revenue?," World Development, Elsevier, vol. 83(C), pages 163-178.
    13. 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.
    14. 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.
    15. Jing Li & Huan Deng & Jun Li, 2025. "The impact of village heads’ educational levels on adolescent academic performance: Evidence from rural China," PLOS ONE, Public Library of Science, vol. 20(1), pages 1-15, January.
    16. 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.
    17. Gupta, Abhimanyu, 2023. "Efficient closed-form estimation of large spatial autoregressions," Journal of Econometrics, Elsevier, vol. 232(1), pages 148-167.
    18. repec:oxf:wpaper:wps/2014-05 is not listed on IDEAS
    19. 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.
    20. 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.
    21. Baylis, Kathy & Paulson, Nicholas D. & Piras, Gianfranco, 2011. "Spatial Approaches to Panel Data in Agricultural Economics: A Climate Change Application," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 43(3), pages 325-338, August.
    22. repec:oxf:wpaper:wps/2014-11 is not listed on IDEAS
    23. 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.

    More about this item

    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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