IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp18259.html

Using the MVPF to Allocate Treatment Under Imperfect Compliance and Supply-Side Constraints

Author

Listed:
  • Dalla-Zuanna, Antonio

    (Bank of Italy)

  • Liu, Kai

    (University of Cambridge)

Abstract

This paper shows how the Marginal Value of Public Funds (MVPF) can guide treatment allocation to improve social welfare. Under budget constraints, the optimal treatment targets individuals with MVPFs above a threshold that minimizes the opportunity cost of treatment. Using experimental data, we show that prioritizing high-MVPF groups under tight budgets can double Head Start’s social benefits compared to random assignment. Analyzing joint allocation across early (Head Start) and late (Job Corps) skill investment programs, we find that exclusive investment in early interventions is not optimal unless substantially higher welfare weights are placed on young children.

Suggested Citation

  • Dalla-Zuanna, Antonio & Liu, Kai, 2025. "Using the MVPF to Allocate Treatment Under Imperfect Compliance and Supply-Side Constraints," IZA Discussion Papers 18259, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp18259
    as

    Download full text from publisher

    File URL: https://docs.iza.org/dp18259.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. García, Jorge Luis & Heckman, James Joseph, 2022. "Three Criteria for Evaluating Social Programs," Journal of Benefit-Cost Analysis, Cambridge University Press, vol. 13(3), pages 281-286, October.
    2. García, Jorge Luis & Heckman, James J., 2022. "On Criteria for Evaluating Social Programs," IZA Discussion Papers 15188, Institute of Labor Economics (IZA).
    3. Flavio Cunha & James J. Heckman & Susanne M. Schennach, 2010. "Estimating the Technology of Cognitive and Noncognitive Skill Formation," Econometrica, Econometric Society, vol. 78(3), pages 883-931, May.
    4. Marianne P. Bitler & Hilary W. Hoynes & Thurston Domina, 2014. "Experimental Evidence on Distributional Effects of Head Start," NBER Working Papers 20434, National Bureau of Economic Research, Inc.
    5. Lechner, Michael & Smith, Jeffrey, 2007. "What is the value added by caseworkers?," Labour Economics, Elsevier, vol. 14(2), pages 135-151, April.
    6. Raj Chetty & John N. Friedman & Nathaniel Hilger & Emmanuel Saez & Diane Whitmore Schanzenbach & Danny Yagan, 2011. "How Does Your Kindergarten Classroom Affect Your Earnings? Evidence from Project Star," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 126(4), pages 1593-1660.
    7. Kleven, Henrik Jacobsen & Kreiner, Claus Thustrup, 2006. "The marginal cost of public funds: Hours of work versus labor force participation," Journal of Public Economics, Elsevier, vol. 90(10-11), pages 1955-1973, November.
    8. Jason B. Cook & Chloe N. East, 2023. "The Effect of Means-Tested Transfers on Work: Evidence from Quasi-Randomly Assigned SNAP Caseworkers," NBER Working Papers 31307, National Bureau of Economic Research, Inc.
    9. Mayshar, Joram, 1990. "On measures of excess burden and their application," Journal of Public Economics, Elsevier, vol. 43(3), pages 263-289, December.
    10. Frolich, Markus, 2008. "Statistical Treatment Choice: An Application to Active Labor Market Programs," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 547-558, June.
    11. Robert W. Hahn & Nathaniel Hendren & Robert D. Metcalfe & Ben Sprung-Keyser, 2024. "A Welfare Analysis of Policies Impacting Climate Change," NBER Working Papers 32728, National Bureau of Economic Research, Inc.
    12. Peter Z. Schochet & John Burghardt & Sheena McConnell, 2008. "Does Job Corps Work? Impact Findings from the National Job Corps Study," American Economic Review, American Economic Association, vol. 98(5), pages 1864-1886, December.
    13. Toru Kitagawa & Aleksey Tetenov, 2018. "Who Should Be Treated? Empirical Welfare Maximization Methods for Treatment Choice," Econometrica, Econometric Society, vol. 86(2), pages 591-616, March.
    14. repec:mpr:mprres:6097 is not listed on IDEAS
    15. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    16. Chan, M. & Dalla-Zuanna, A., 2023. "Understanding Program Complementarities: Estimating the Dynamic Effects of Head Start with Multiple Alternatives," Cambridge Working Papers in Economics 2330, Faculty of Economics, University of Cambridge.
    17. Dehejia, Rajeev H., 2005. "Program evaluation as a decision problem," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 141-173.
    18. Charles F. Manski, 2004. "Statistical Treatment Rules for Heterogeneous Populations," Econometrica, Econometric Society, vol. 72(4), pages 1221-1246, July.
    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. Patrick Kline & Christopher R. Walters, 2016. "Evaluating Public Programs with Close Substitutes: The Case of HeadStart," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1795-1848.
    2. Garbero, Alessandra & Sakos, Grayson & Cerulli, Giovanni, 2023. "Towards data-driven project design: Providing optimal treatment rules for development projects," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    3. Bhattacharya, Debopam & Dupas, Pascaline, 2012. "Inferring welfare maximizing treatment assignment under budget constraints," Journal of Econometrics, Elsevier, vol. 167(1), pages 168-196.
    4. Susan Athey & Stefan Wager, 2021. "Policy Learning With Observational Data," Econometrica, Econometric Society, vol. 89(1), pages 133-161, January.
    5. Neil Christy & Amanda Ellen Kowalski, 2024. "Counting Defiers: A Design-Based Model of an Experiment Can Reveal Evidence Beyond the Average Effect," Papers 2412.16352, arXiv.org, revised Dec 2025.
    6. Stefanie Behncke & Markus Frölich & Michael Lechner, 2009. "Targeting Labour Market Programmes - Results from a Randomized Experiment," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 145(III), pages 221-268, September.
    7. Yu-Chang Chen & Haitian Xie, 2022. "Personalized Subsidy Rules," Papers 2202.13545, arXiv.org, revised Mar 2022.
    8. Takanori Ida & Takunori Ishihara & Koichiro Ito & Daido Kido & Toru Kitagawa & Shosei Sakaguchi & Shusaku Sasaki, 2021. "Paternalism, Autonomy, or Both? Experimental Evidence from Energy Saving Programs," Papers 2112.09850, arXiv.org.
    9. Achim Ahrens & Alessandra Stampi‐Bombelli & Selina Kurer & Dominik Hangartner, 2024. "Optimal multi‐action treatment allocation: A two‐phase field experiment to boost immigrant naturalization," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(7), pages 1379-1395, November.
    10. Augustine Denteh & Helge Liebert, 2022. "Who Increases Emergency Department Use? New Insights from the Oregon Health Insurance Experiment," CESifo Working Paper Series 9664, CESifo.
    11. Yuehao Bai & Azeem M. Shaikh & Max Tabord-Meehan, 2024. "A Primer on the Analysis of Randomized Experiments and a Survey of some Recent Advances," Papers 2405.03910, arXiv.org, revised Apr 2025.
    12. Hirano, Keisuke & Porter, Jack R., 2020. "Asymptotic analysis of statistical decision rules in econometrics," Handbook of Econometrics, in: Steven N. Durlauf & Lars Peter Hansen & James J. Heckman & Rosa L. Matzkin (ed.), Handbook of Econometrics, edition 1, volume 7, chapter 0, pages 283-354, Elsevier.
    13. Takanori Ida & Takunori Ishihara & Koichiro Ito & Daido Kido & Toru Kitagawa & Shosei Sakaguchi & Shusaku Sasaki, 2022. "Choosing Who Chooses: Selection-Driven Targeting in Energy Rebate Programs," NBER Working Papers 30469, National Bureau of Economic Research, Inc.
    14. Bastani, Spencer, 2023. "The marginal cost of public funds: A brief guide," Working Paper Series 2023:14, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    15. Spencer Bastani, 2025. "The marginal value of public funds: a brief guide and application to tax policy," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 32(4), pages 919-956, August.
    16. Holla,Alaka & Bendini,Maria Magdalena & Dinarte Diaz,Lelys Ileana & Trako,Iva, 2021. "Is Investment in Preprimary Education Too Low ? Lessons from (Quasi) ExperimentalEvidence across Countries," Policy Research Working Paper Series 9723, The World Bank.
    17. Giovanni Cerulli & Francesco Caracciolo, 2025. "Risk-Adjusted Policy Learning and the Social Cost of Uncertainty: Theory and Evidence from CAP evaluation," Papers 2510.05007, arXiv.org.
    18. Eric Mbakop & Max Tabord‐Meehan, 2021. "Model Selection for Treatment Choice: Penalized Welfare Maximization," Econometrica, Econometric Society, vol. 89(2), pages 825-848, March.
    19. Anders Bredahl Kock & Martin Thyrsgaard, 2017. "Optimal sequential treatment allocation," Papers 1705.09952, arXiv.org, revised Aug 2018.
    20. Firpo, Sergio & Galvao, Antonio F. & Kobus, Martyna & Parker, Thomas & Rosa-Dias, Pedro, 2025. "Loss aversion and the welfare ranking of policy interventions," Journal of Econometrics, Elsevier, vol. 252(PB).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • H43 - Public Economics - - Publicly Provided Goods - - - Project Evaluation; Social Discount Rate
    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs
    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • J68 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Public Policy
    • I26 - Health, Education, and Welfare - - Education - - - Returns to Education

    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:iza:izadps:dp18259. 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: Holger Hinte (email available below). General contact details of provider: https://edirc.repec.org/data/izaaade.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.