IDEAS home Printed from https://ideas.repec.org/p/ifs/ifsewp/21-16.html
   My bibliography  Save this paper

Coordination and the poor maintenance trap: an experiment on public infrastructure in India

Author

Listed:
  • Alex Armand

    (Institute for Fiscal Studies and Nova School of Business and Economics)

  • Britta Augsburg

    (Institute for Fiscal Studies and Institute for Fiscal Studies)

  • Antonella Bancalari

    (Institute for Fiscal Studies and University of St. Andrews)

Abstract

Poorly maintained public infrastructure is common in low- and middle-income countries, with consequences for service delivery and public health. By experimentally identifying the impact of incentives for local maintenance for both providers and potential users, this paper provides one of the ?rst economic analyses of provider–user dynamics in the presence of local coordination failure. Focusing on shared sanitation facilities for slum residents in two major Indian cities, we randomly allocate facilities to either a control or two treatments. The ?rst treatment incentivizes maintenance of the facility among providers, while the second treatment adds a sensitization campaign about the returns of a well-maintained facility among potential users. Using surveys, behavioral and objective measurements for both providers and potential users, we show that incentivizing maintenance does not favor collective action. The treatments raise the quality of facilities and reduce free riding, but at the cost of user selection. Providers improve routine maintenance, but also respond strategically to the newly-introduced incentives. While slum residents’ private willingness to pay and cooperation are unaffected, their demand for public intervention increases. The second treatment raises aware-ness, but does not affect behavior.

Suggested Citation

  • Alex Armand & Britta Augsburg & Antonella Bancalari, 2021. "Coordination and the poor maintenance trap: an experiment on public infrastructure in India," IFS Working Papers W21/16, Institute for Fiscal Studies.
  • Handle: RePEc:ifs:ifsewp:21/16
    as

    Download full text from publisher

    File URL: https://ifs.org.uk/uploads/WP2116-Coordination-and-the-Poor-Maintenance-Trap.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Karlan, Dean S. & Zinman, Jonathan, 2012. "List randomization for sensitive behavior: An application for measuring use of loan proceeds," Journal of Development Economics, Elsevier, vol. 98(1), pages 71-75.
    2. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2011. "Inference on Treatment Effects After Selection Amongst High-Dimensional Controls," Papers 1201.0224, arXiv.org, revised May 2012.
    3. Jonah B. Gelbach, 2016. "When Do Covariates Matter? And Which Ones, and How Much?," Journal of Labor Economics, University of Chicago Press, vol. 34(2), pages 509-543.
    4. Carole Treibich & Aurélia Lépine, 2019. "Estimating misreporting in condom use and its determinants among sex workers: Evidence from the list randomisation method," Health Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 144-160, January.
    5. Stefan Wager & Susan Athey, 2018. "Estimation and Inference of Heterogeneous Treatment Effects using Random Forests," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(523), pages 1228-1242, July.
    6. Ashraf, Nava & Bandiera, Oriana & Lee, Scott S., 2014. "Awards unbundled: Evidence from a natural field experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 100(C), pages 44-63.
    7. Steffen Andersen & Glenn Harrison & Morten Lau & E. Rutström, 2009. "Elicitation using multiple price list formats," Experimental Economics, Springer;Economic Science Association, vol. 12(3), pages 365-366, September.
    8. Augsburg, Britta & Rodríguez-Lesmes, Paul Andrés, 2018. "Sanitation and child health in India," World Development, Elsevier, vol. 107(C), pages 22-39.
    9. Stopnitzky, Yaniv, 2017. "No toilet no bride? Intrahousehold bargaining in male-skewed marriage markets in India," Journal of Development Economics, Elsevier, vol. 127(C), pages 269-282.
    10. Victor Chernozhukov & Mert Demirer & Esther Duflo & Ivan Fernandez-Val, 2017. "Generic machine learning inference on heterogenous treatment effects in randomized experiments," CeMMAP working papers CWP61/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Yeatman, S. & Trinitapoli, J., 2011. "Best-friend reports: A tool for measuring the prevalence of sensitive behaviors," American Journal of Public Health, American Public Health Association, vol. 101(9), pages 1666-1667.
    12. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2013. "Supplementary Appendix for "Inference on Treatment Effects After Selection Amongst High-Dimensional Controls"," Papers 1305.6099, arXiv.org, revised Jun 2013.
    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. Michael C. Knaus & Michael Lechner & Anthony Strittmatter, 2022. "Heterogeneous Employment Effects of Job Search Programs: A Machine Learning Approach," Journal of Human Resources, University of Wisconsin Press, vol. 57(2), pages 597-636.
    2. Gabriel Okasa, 2022. "Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance," Papers 2201.12692, arXiv.org.
    3. Teck-Hua Ho & Noah Lim & Sadat Reza & Xiaoyu Xia, 2017. "OM Forum—Causal Inference Models in Operations Management," Manufacturing & Service Operations Management, INFORMS, vol. 19(4), pages 509-525, October.
    4. Chakravorty, Bhaskar & Arulampalam, Wiji & Bhatiya, Apurav Yash & Imbert, Clément & Rathelot, Roland, 2024. "Can information about jobs improve the effectiveness of vocational training? Experimental evidence from India," Journal of Development Economics, Elsevier, vol. 169(C).
    5. Saraswat, Deepak, 2024. "Gender composition of children and sanitation behavior in India," Journal of Environmental Economics and Management, Elsevier, vol. 125(C).
    6. Ian W. McKeague & Min Qian, 2015. "An Adaptive Resampling Test for Detecting the Presence of Significant Predictors," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1422-1433, December.
    7. Alexandre Belloni & Victor Chernozhukov, 2015. "Comment," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1449-1451, December.
    8. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2014. "High-Dimensional Methods and Inference on Structural and Treatment Effects," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 29-50, Spring.
    9. David Cheng & Abhishek Chakrabortty & Ashwin N. Ananthakrishnan & Tianxi Cai, 2020. "Estimating average treatment effects with a double‐index propensity score," Biometrics, The International Biometric Society, vol. 76(3), pages 767-777, September.
    10. Michael C Knaus, 2022. "Double machine learning-based programme evaluation under unconfoundedness [Econometric methods for program evaluation]," The Econometrics Journal, Royal Economic Society, vol. 25(3), pages 602-627.
    11. Strittmatter, Anthony & Wunsch, Conny, 2021. "The Gender Pay Gap Revisited with Big Data: Do Methodological Choices Matter?," Working papers 2021/05, Faculty of Business and Economics - University of Basel.
    12. Michael J. Weir & Thomas W. Sproul, 2019. "Identifying Drivers of Genetically Modified Seafood Demand: Evidence from a Choice Experiment," Sustainability, MDPI, vol. 11(14), pages 1-21, July.
    13. Clarke, Damian, 2023. "The Economics of Abortion Policy," IZA Discussion Papers 16395, Institute of Labor Economics (IZA).
    14. Michela Carlana & Eliana La Ferrara & Paolo Pinotti, 2022. "Goals and Gaps: Educational Careers of Immigrant Children," Econometrica, Econometric Society, vol. 90(1), pages 1-29, January.
    15. Augsburg, Britta & Malde, Bansi & Olorenshaw, Harriet & Wahhaj, Zaki, 2023. "To invest or not to invest in sanitation: The role of intra-household gender differences in perceptions and bargaining power," Journal of Development Economics, Elsevier, vol. 162(C).
    16. Chakravorty, Bhaskar & Bhatiya, Apurav Yash & Imbert, Clément & Lohnert, Maximilian & Panda, Poonam & Rathelot, Roland, 2023. "Impact of the COVID-19 crisis on India’s rural youth: Evidence from a panel survey and an experiment," World Development, Elsevier, vol. 168(C).
    17. Bütikofer, Aline & Ginja, Rita & Landaud, Fanny & Løken, Katrine V., 2020. "School Selectivity, Peers, and Mental Health," Working Papers in Economics 5/20, University of Bergen, Department of Economics.
    18. Olivia Bertelli & Thomas Calvo & Massa Coulibaly & Moussa Coulibaly & Emmanuelle Lavallée & Marion Mercier & Sandrine Mesplé-Somps & O. Z. Traoré, 2023. "Collecter des données sur des expériences et attitudes sensibles : le cas du Mali," Post-Print hal-04442342, HAL.
    19. Helmut Wasserbacher & Martin Spindler, 2024. "Credit Ratings: Heterogeneous Effect on Capital Structure," Papers 2406.18936, arXiv.org.
    20. González, Felipe & Muñoz, Pablo & Prem, Mounu, 2021. "Lost in transition? The persistence of dictatorship mayors," Journal of Development Economics, Elsevier, vol. 151(C).

    More about this item

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • C39 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Other
    • I15 - Health, Education, and Welfare - - Health - - - Health and Economic Development
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling

    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:ifs:ifsewp:21/16. 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: Emma Hyman (email available below). General contact details of provider: https://edirc.repec.org/data/ifsssuk.html .

    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.