[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2009.09614.html
   My bibliography  Save this paper

Spillovers of Program Benefits with Missing Network Links

Author

Listed:
  • Lina Zhang
Abstract
The issue of missing network links in partially observed networks is frequently neglected in empirical studies. This paper addresses this issue when investigating the spillovers of program benefits in the presence of network interactions. Our method is flexible enough to account for non-i.i.d. missing links. It relies on two network measures that can be easily constructed based on the incoming and outgoing links of the same observed network. The treatment and spillover effects can be point identified and consistently estimated if network degrees are bounded for all units. We also demonstrate the bias reduction property of our method if network degrees of some units are unbounded. Monte Carlo experiments and a naturalistic simulation on real-world network data are implemented to verify the finite-sample performance of our method. We also re-examine the spillover effects of home computer use on children's self-empowered learning.

Suggested Citation

  • Lina Zhang, 2020. "Spillovers of Program Benefits with Missing Network Links," Papers 2009.09614, arXiv.org, revised Aug 2024.
    • Handle: RePEc:arx:papers:2009.09614
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2009.09614
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kremer, Michael Robert & Miguel, Edward A., 2004. "The Illusion of Sustainability," Department of Economics, Working Paper Series qt94p8w1d7, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    2. Charles F. Manski, 2001. "Designing Programs for Heterogeneous Populations: The Value of Covariate Information," American Economic Review, American Economic Association, vol. 91(2), pages 103-106, May.
    3. Aaron Sojourner, 2013. "Identification of Peer Effects with Missing Peer Data: Evidence from Project STAR," Economic Journal, Royal Economic Society, vol. 123(569), pages 574-605, June.
    4. Margherita Comola & Marcel Fafchamps, 2017. "The Missing Transfers: Estimating Misreporting in Dyadic Data," Economic Development and Cultural Change, University of Chicago Press, vol. 65(3), pages 549-582.
    5. Rossella Calvi & Arthur Lewbel & Denni Tommasi, 2022. "LATE With Missing or Mismeasured Treatment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(4), pages 1701-1717, October.
    6. Angelucci, Manuela & De Giorgi, Giacomo & Rangel, Marcos A. & Rasul, Imran, 2010. "Family networks and school enrolment: Evidence from a randomized social experiment," Journal of Public Economics, Elsevier, vol. 94(3-4), pages 197-221, April.
    7. Liu, Xiaodong, 2013. "Estimation of a local-aggregate network model with sampled networks," Economics Letters, Elsevier, vol. 118(1), pages 243-246.
    8. Michael Kremer & Edward Miguel, 2007. "The Illusion of Sustainability," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(3), pages 1007-1065.
    9. Susan Athey & Dean Eckles & Guido W. Imbens, 2018. "Exact p-Values for Network Interference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(521), pages 230-240, January.
    10. M. Angelucci & V. Di Maro, 2016. "Programme evaluation and spillover effects," Journal of Development Effectiveness, Taylor & Francis Journals, vol. 8(1), pages 22-43, March.
    11. Sobel, Michael E., 2006. "What Do Randomized Studies of Housing Mobility Demonstrate?: Causal Inference in the Face of Interference," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1398-1407, December.
    12. Paul Goldsmith-Pinkham & Guido W. Imbens, 2013. "Social Networks and the Identification of Peer Effects," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(3), pages 253-264, July.
    13. Timothy G. Conley & Christopher R. Udry, 2010. "Learning about a New Technology: Pineapple in Ghana," American Economic Review, American Economic Association, vol. 100(1), pages 35-69, March.
    14. Áureo de Paula & Imran Rasul & Pedro CL Souza, 2018. "Recovering social networks from panel data: identification, simulations and an application," CeMMAP working papers CWP17/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    15. Qu, Xi & Lee, Lung-fei, 2015. "Estimating a spatial autoregressive model with an endogenous spatial weight matrix," Journal of Econometrics, Elsevier, vol. 184(2), pages 209-232.
    16. Erich Battistin & Barbara Sianesi, 2011. "Misclassified Treatment Status and Treatment Effects: An Application to Returns to Education in the United Kingdom," The Review of Economics and Statistics, MIT Press, vol. 93(2), pages 495-509, May.
    17. Yosef Rinott & Vladimir Rotar, 2000. "Normal approximations by Stein's method," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 23(1), pages 15-29.
    18. Antoni Calvó-Armengol & Eleonora Patacchini & Yves Zenou, 2009. "Peer Effects and Social Networks in Education," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(4), pages 1239-1267.
    19. Bound, John & Brown, Charles & Mathiowetz, Nancy, 2001. "Measurement error in survey data," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 59, pages 3705-3843, Elsevier.
    20. Battistin, Erich & De Nadai, Michele & Sianesi, Barbara, 2014. "Misreported schooling, multiple measures and returns to educational qualifications," Journal of Econometrics, Elsevier, vol. 181(2), pages 136-150.
    21. Arthur Lewbel, 2007. "Estimation of Average Treatment Effects with Misclassification," Econometrica, Econometric Society, vol. 75(2), pages 537-551, March.
    22. Edward Miguel & Michael Kremer, 2004. "Worms: Identifying Impacts on Education and Health in the Presence of Treatment Externalities," Econometrica, Econometric Society, vol. 72(1), pages 159-217, January.
    23. Guillaume Basse & Avi Feller, 2018. "Analyzing Two-Stage Experiments in the Presence of Interference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(521), pages 41-55, January.
    24. Sergio Currarini & Matthew O. Jackson & Paolo Pin, 2009. "An Economic Model of Friendship: Homophily, Minorities, and Segregation," Econometrica, Econometric Society, vol. 77(4), pages 1003-1045, July.
    25. Yingyao Hu & Susanne M. Schennach, 2008. "Instrumental Variable Treatment of Nonclassical Measurement Error Models," Econometrica, Econometric Society, vol. 76(1), pages 195-216, January.
    26. Patacchini, Eleonora & Rainone, Edoardo & Zenou, Yves, 2017. "Heterogeneous peer effects in education," Journal of Economic Behavior & Organization, Elsevier, vol. 134(C), pages 190-227.
    27. Aprajit Mahajan, 2006. "Identification and Estimation of Regression Models with Misclassification," Econometrica, Econometric Society, vol. 74(3), pages 631-665, May.
    28. Emily Oster & Rebecca Thornton, 2012. "Determinants Of Technology Adoption: Peer Effects In Menstrual Cup Take-Up," Journal of the European Economic Association, European Economic Association, vol. 10(6), pages 1263-1293, December.
    29. Tauchen, George, 1985. "Diagnostic testing and evaluation of maximum likelihood models," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 415-443.
    30. Kyungchul Song, 2018. "Measuring the Graph Concordance of Locally Dependent Observations," The Review of Economics and Statistics, MIT Press, vol. 100(3), pages 535-549, July.
    31. Newey, Whitney K., 1994. "Kernel Estimation of Partial Means and a General Variance Estimator," Econometric Theory, Cambridge University Press, vol. 10(2), pages 1-21, June.
    32. Fafchamps, Marcel & Lund, Susan, 2003. "Risk-sharing networks in rural Philippines," Journal of Development Economics, Elsevier, vol. 71(2), pages 261-287, August.
    33. Isaac M. Opper, 2019. "Does Helping John Help Sue? Evidence of Spillovers in Education," American Economic Review, American Economic Association, vol. 109(3), pages 1080-1115, March.
    34. Emily Breza & Arun G. Chandrasekhar & Tyler H. McCormick & Mengjie Pan, 2020. "Using Aggregated Relational Data to Feasibly Identify Network Structure without Network Data," American Economic Review, American Economic Association, vol. 110(8), pages 2454-2484, August.
    35. Lan Liu & Michael G. Hudgens, 2014. "Large Sample Randomization Inference of Causal Effects in the Presence of Interference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(505), pages 288-301, March.
    36. Felipe Barrera-Osorio & Marianne Bertrand & Leigh L. Linden & Francisco Perez-Calle, 2011. "Improving the Design of Conditional Transfer Programs: Evidence from a Randomized Education Experiment in Colombia," American Economic Journal: Applied Economics, American Economic Association, vol. 3(2), pages 167-195, April.
    37. Hudgens, Michael G. & Halloran, M. Elizabeth, 2008. "Toward Causal Inference With Interference," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 832-842, June.
    38. Elias Masry, 1996. "Multivariate Local Polynomial Regression For Time Series:Uniform Strong Consistency And Rates," Journal of Time Series Analysis, Wiley Blackwell, vol. 17(6), pages 571-599, November.
    39. Candelaria, Luis E. & Ura, Takuya, 2020. "Identification and Inference of Network Formation Games with Misclassified Links," The Warwick Economics Research Paper Series (TWERPS) 1258, University of Warwick, Department of Economics.
    40. Hu, Yingyao, 2008. "Identification and estimation of nonlinear models with misclassification error using instrumental variables: A general solution," Journal of Econometrics, Elsevier, vol. 144(1), pages 27-61, May.
    41. Xiaohong Chen & Han Hong & Denis Nekipelov, 2011. "Nonlinear Models of Measurement Errors," Journal of Economic Literature, American Economic Association, vol. 49(4), pages 901-937, December.
    42. Arun Advani & Bansi Malde, 2018. "Credibly Identifying Social Effects: Accounting For Network Formation And Measurement Error," Journal of Economic Surveys, Wiley Blackwell, vol. 32(4), pages 1016-1044, September.
    Full references (including those not matched with items on IDEAS)

    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. Yann Bramoullé & Habiba Djebbari & Bernard Fortin, 2020. "Peer Effects in Networks: A Survey," Annual Review of Economics, Annual Reviews, vol. 12(1), pages 603-629, August.
    2. Takahide Yanagi, 2019. "Inference on local average treatment effects for misclassified treatment," Econometric Reviews, Taylor & Francis Journals, vol. 38(8), pages 938-960, September.
    3. Arun Advani & Bansi Malde, 2018. "Credibly Identifying Social Effects: Accounting For Network Formation And Measurement Error," Journal of Economic Surveys, Wiley Blackwell, vol. 32(4), pages 1016-1044, September.
    4. Akanksha Negi & Digvijay Singh Negi, 2022. "Difference-in-Differences with a Misclassified Treatment," Papers 2208.02412, arXiv.org.
    5. 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).
    6. Chih-Sheng Hsieh & Stanley I. M. Ko & Jaromír Kovářík & Trevon Logan, 2018. "Non-Randomly Sampled Networks: Biases and Corrections," NBER Working Papers 25270, National Bureau of Economic Research, Inc.
    7. Arun Advani & Bansi Malde, 2014. "Empirical methods for networks data: social effects, network formation and measurement error," IFS Working Papers W14/34, Institute for Fiscal Studies.
    8. Michael P. Leung, 2020. "Treatment and Spillover Effects Under Network Interference," The Review of Economics and Statistics, MIT Press, vol. 102(2), pages 368-380, May.
    9. Gonzalo Vazquez-Bare, 2017. "Identification and Estimation of Spillover Effects in Randomized Experiments," Papers 1711.02745, arXiv.org, revised Jan 2022.
    10. Sarah Baird & Aislinn Bohren & Craig McIntosh & Berk Ozler, 2017. "Optimal Design of Experiments in the Presence of Interference*, Second Version," PIER Working Paper Archive 16-025, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 30 Nov 2017.
    11. DiTraglia, Francis J. & García-Jimeno, Camilo, 2019. "Identifying the effect of a mis-classified, binary, endogenous regressor," Journal of Econometrics, Elsevier, vol. 209(2), pages 376-390.
    12. Battistin, Erich & Chesher, Andrew, 2014. "Treatment effect estimation with covariate measurement error," Journal of Econometrics, Elsevier, vol. 178(2), pages 707-715.
    13. Yann Algan & Quoc-Anh Do & Nicolò Dalvit & Alexis Le Chapelain & Yves Zenou, 2015. "How Social Networks Shape Our Beliefs: A Natural Experiment among Future French Politicians," Working Papers hal-03459820, HAL.
    14. repec:spo:wpmain:info:hdl:2441/78vacv4udu92eq3fec89svm9uv is not listed on IDEAS
    15. Francis J. DiTraglia & Camilo García-Jimeno, 2017. "Mis-classified, Binary, Endogenous Regressors: Identification and Inference," NBER Working Papers 23814, National Bureau of Economic Research, Inc.
    16. Battistin, Erich & De Nadai, Michele & Sianesi, Barbara, 2014. "Misreported schooling, multiple measures and returns to educational qualifications," Journal of Econometrics, Elsevier, vol. 181(2), pages 136-150.
    17. repec:hal:spmain:info:hdl:2441/78vacv4udu92eq3fec89svm9uv is not listed on IDEAS
    18. Zhaonan Qu & Ruoxuan Xiong & Jizhou Liu & Guido Imbens, 2021. "Semiparametric Estimation of Treatment Effects in Observational Studies with Heterogeneous Partial Interference," Papers 2107.12420, arXiv.org, revised Jun 2024.
    19. Sarah Baird & Aislinn Bohren & Craig McIntosh & Berk Ozler, 2014. "Designing Experiments to Measure Spillover Effects," PIER Working Paper Archive 14-032, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    20. Hu, Yingyao, 2017. "The econometrics of unobservables: Applications of measurement error models in empirical industrial organization and labor economics," Journal of Econometrics, Elsevier, vol. 200(2), pages 154-168.
    21. Braun, Martin & Verdier, Valentin, 2023. "Estimation of spillover effects with matched data or longitudinal network data," Journal of Econometrics, Elsevier, vol. 233(2), pages 689-714.
    22. Acerenza, Santiago & Ban, Kyunghoon & Kedagni, Desire, 2021. "Marginal Treatment Effects with Misclassified Treatment," ISU General Staff Papers 202106180700001132, Iowa State University, Department of Economics.

    More about this item

    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:arx:papers:2009.09614. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.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.