Nothing Special   »   [go: up one dir, main page]

IDEAS home Printed from https://ideas.repec.org/p/cpr/ceprdp/13707.html
   My bibliography  Save this paper

Demand and Welfare Analysis in Discrete Choice Models with Social Interactions

Author

Listed:
  • Dupas, Pascaline
  • Bhattacharya, Debopam
  • ,
Abstract
Many real-life settings of consumer choice involve social interactions, causing targeted policies to have spillover effects. This paper develops novel empirical tools for analyzing demand and welfare effects of policy interventions in binary choice settings with social interactions. Examples include subsidies for health product adoption and vouchers for attending a high-achieving school. We establish the connection between econometrics of large games and Brock-Durlauf-type interaction models, under both I.I.D. and spatially correlated unobservables. We develop new convergence results for associated beliefs and estimates of preference parameters under increasing domain spatial asymptotics. Next, we show that even with fully parametric specifications and unique equilibrium, choice data, that are sufficient for counterfactual demand prediction under interactions, are insufficient for welfare calculations. This is because distinct underlying mechanisms producing the same interaction coefficient can imply different welfare effects and deadweight-loss from a policy intervention. Standard index-restrictions imply distribution-free bounds on welfare. We illustrate our results using experimental data on mosquito-net adoption in rural Kenya.

Suggested Citation

  • Dupas, Pascaline & Bhattacharya, Debopam & ,, 2019. "Demand and Welfare Analysis in Discrete Choice Models with Social Interactions," CEPR Discussion Papers 13707, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:13707
    as

    Download full text from publisher

    File URL: https://cepr.org/publications/DP13707
    Download Restriction: CEPR Discussion Papers are free to download for our researchers, subscribers and members. If you fall into one of these categories but have trouble downloading our papers, please contact us at subscribers@cepr.org
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Rust, John, 1987. "Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher," Econometrica, Econometric Society, vol. 55(5), pages 999-1033, September.
    2. Brock, William A. & Durlauf, Steven N., 2001. "Interactions-based models," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 54, pages 3297-3380, Elsevier.
    3. Small, Kenneth A & Rosen, Harvey S, 1981. "Applied Welfare Economics with Discrete Choice Models," Econometrica, Econometric Society, vol. 49(1), pages 105-130, January.
    4. Donald W. K. Andrews, 2005. "Cross-Section Regression with Common Shocks," Econometrica, Econometric Society, vol. 73(5), pages 1551-1585, September.
    5. Jerry A. Hausman & Whitney K. Newey, 2016. "Individual Heterogeneity and Average Welfare," Econometrica, Econometric Society, vol. 84, pages 1225-1248, May.
    6. William A. Brock & Steven N. Durlauf, 2001. "Discrete Choice with Social Interactions," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 68(2), pages 235-260.
    7. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, April.
    8. Giuseppe De Luca, 2008. "SNP and SML estimation of univariate and bivariate binary-choice models," Stata Journal, StataCorp LP, vol. 8(2), pages 190-220, June.
    9. Pascaline Dupas, 2014. "Short‐Run Subsidies and Long‐Run Adoption of New Health Products: Evidence From a Field Experiment," Econometrica, Econometric Society, vol. 82(1), pages 197-228, January.
    10. Brock, William A. & Durlauf, Steven N., 2007. "Identification of binary choice models with social interactions," Journal of Econometrics, Elsevier, vol. 140(1), pages 52-75, September.
    11. Áureo de Paula, 2015. "Econometrics of network models," CeMMAP working papers 52/15, Institute for Fiscal Studies.
    12. Bhattacharya, Debopam, 2008. "A Permutation-Based Estimator For Monotone Index Models," Econometric Theory, Cambridge University Press, vol. 24(3), pages 795-807, June.
    13. Charles F. Manski, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(3), pages 531-542.
    14. Debopam Bhattacharya, 2015. "Nonparametric Welfare Analysis for Discrete Choice," Econometrica, Econometric Society, vol. 83, pages 617-649, March.
    15. Han, Aaron K., 1987. "Non-parametric analysis of a generalized regression model : The maximum rank correlation estimator," Journal of Econometrics, Elsevier, vol. 35(2-3), pages 303-316, July.
    16. Debopam Bhattacharya, 2018. "Empirical welfare analysis for discrete choice: Some general results," Quantitative Economics, Econometric Society, vol. 9(2), pages 571-615, July.
    17. Konrad Menzel, 2016. "Inference for Games with Many Players," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 83(1), pages 306-337.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Davide Viviano & Jess Rudder, 2020. "Policy design in experiments with unknown interference," Papers 2011.08174, arXiv.org, revised May 2024.
    2. Michael P. Leung, 2020. "Equilibrium computation in discrete network games," Quantitative Economics, Econometric Society, vol. 11(4), pages 1325-1347, November.
    3. Davide Viviano, 2019. "Policy Targeting under Network Interference," Papers 1906.10258, arXiv.org, revised Apr 2024.
    4. Wilfried Youmbi, 2024. "Nonparametric Analysis of Random Utility Models Robust to Nontransitive Preferences," Papers 2406.13969, arXiv.org.

    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. Lin, Zhongjian & Hu, Yingyao, 2024. "Binary choice with misclassification and social interactions, with an application to peer effects in attitude," Journal of Econometrics, Elsevier, vol. 238(1).
    2. Bhattacharya, D. & Dupas, P. & Kanaya, S., 2018. "Demand and Welfare Analysis in Discrete Choice Models under Social Interactions," Cambridge Working Papers in Economics 1885, Faculty of Economics, University of Cambridge.
    3. Lin, Zhongjian & Tang, Xun & Yu, Ning Neil, 2021. "Uncovering heterogeneous social effects in binary choices," Journal of Econometrics, Elsevier, vol. 222(2), pages 959-973.
    4. Debopam Bhattacharya, 2021. "The Empirical Content of Binary Choice Models," Econometrica, Econometric Society, vol. 89(1), pages 457-474, January.
    5. Chen, Liang & Luo, Yao, 2023. "Empirical analysis of network effects in nonlinear pricing data," International Journal of Industrial Organization, Elsevier, vol. 91(C).
    6. Giulio Zanella, 2004. "Discrete Choice with Social Interactions and Endogenous Memberships," Department of Economics University of Siena 442, Department of Economics, University of Siena.
    7. Xi Chen & Ralf van der Lans & Michael Trusov, 2021. "Efficient Estimation of Network Games of Incomplete Information: Application to Large Online Social Networks," Management Science, INFORMS, vol. 67(12), pages 7575-7598, December.
    8. William A. Brock & Steven N. Durlauf, 2010. "Adoption Curves and Social Interactions," Journal of the European Economic Association, MIT Press, vol. 8(1), pages 232-251, March.
    9. Qingyan Shang & Lung-fei Lee, 2011. "Two-Step Estimation of Endogenous and Exogenous Group Effects," Econometric Reviews, Taylor & Francis Journals, vol. 30(2), pages 173-207.
    10. Vincent Boucher & Yann Bramoullé, 2020. "Binary Outcomes and Linear Interactions," AMSE Working Papers 2038, Aix-Marseille School of Economics, France.
    11. Chen, Denghui & Kiefer, Hua & Liu, Xiaodong, 2022. "Estimation of discrete choice network models with missing outcome data," Regional Science and Urban Economics, Elsevier, vol. 97(C).
    12. Zhao, Chuanmin & Qu, Xi, 2021. "Peer effects in pension decision-making: evidence from China's new rural pension scheme," Labour Economics, Elsevier, vol. 69(C).
    13. Crudu, Federico & Neri, Laura & Tiezzi, Silvia, 2018. "Family Ties and Children Obesity in Italy," MPRA Paper 90360, University Library of Munich, Germany, revised 15 Oct 2018.
    14. ÖZGÜR, Onur & BISIN, Alberto, 2011. "Dynamic Linear Economies with Social Interactions," Cahiers de recherche 04-2011, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    15. Yang, Chao & Lee, Lung-fei, 2017. "Social interactions under incomplete information with heterogeneous expectations," Journal of Econometrics, Elsevier, vol. 198(1), pages 65-83.
    16. Semih Tumen & Tugba Zeydanli, 2015. "Is Happiness Contagious? Separating Spillover Externalities from the Group-Level Social Context," Journal of Happiness Studies, Springer, vol. 16(3), pages 719-744, June.
    17. Liang Chen & Yao Luo, 2023. "Empirical Analysis of Network Effects in Nonlinear Pricing Data," Working Papers tecipa-758, University of Toronto, Department of Economics.
    18. Liu, Xiaodong & Zhou, Jiannan, 2017. "A social interaction model with ordered choices," Economics Letters, Elsevier, vol. 161(C), pages 86-89.
    19. Kourtellos, Andros & Petrou, Kyriakos, 2022. "The role of social interactions in preferences for redistribution," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 716-737.
    20. Steven N. Durlauf & Yannis M. Ioannides, 2010. "Social Interactions," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 451-478, September.

    More about this item

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • H4 - Public Economics - - Publicly Provided Goods
    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs
    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development

    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:cpr:ceprdp:13707. 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://www.cepr.org .

    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.