IDEAS home Printed from https://ideas.repec.org/p/ehl/lserod/126829.html
   My bibliography  Save this paper

Talking therapy: impacts of a nationwide mental health service in England

Author

Listed:
  • Oparina, Ekaterina
  • Krekel, Christian
  • Srisuma, Sorawoot

Abstract

Mental health problems impose significant costs, yet healthcare systems of-ten overlook them. We provide the first causal evidence on the effectiveness of a nationwide-scaled mental health service in England for treating depression and anxiety using non-experimental data and methods. We exploit over-subscription and resulting exogenous variation in waiting times across areas and time for identification, based on a novel dataset of over one million patients. We find that treatment improves mental health and reduces impairment in work and social life. We provide suggestive evidence that it enhances employment. Impacts vary across patients and services. Nevertheless, the programme is highly cost-effective.

Suggested Citation

  • Oparina, Ekaterina & Krekel, Christian & Srisuma, Sorawoot, 2024. "Talking therapy: impacts of a nationwide mental health service in England," LSE Research Online Documents on Economics 126829, London School of Economics and Political Science, LSE Library.
  • Handle: RePEc:ehl:lserod:126829
    as

    Download full text from publisher

    File URL: http://eprints.lse.ac.uk/126829/
    File Function: Open access version.
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2018. "Double/debiased machine learning for treatment and structural parameters," Econometrics Journal, Royal Economic Society, vol. 21(1), pages 1-68, February.
    2. Christopher Blattman & Julian C. Jamison & Margaret Sheridan, 2017. "Reducing Crime and Violence: Experimental Evidence from Cognitive Behavioral Therapy in Liberia," American Economic Review, American Economic Association, vol. 107(4), pages 1165-1206, April.
    3. Jens Ludwig & Greg J. Duncan & Lisa A. Gennetian & Lawrence F. Katz & Ronald C. Kessler & Jeffrey R. Kling & Lisa Sanbonmatsu, 2013. "Long-Term Neighborhood Effects on Low-Income Families: Evidence from Moving to Opportunity," American Economic Review, American Economic Association, vol. 103(3), pages 226-231, May.
    4. 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.
    5. Emily A. Beam & Stella Quimbo, 2023. "The Impact of Short-Term Employment for Low-Income Youth: Experimental Evidence from the Philippines," The Review of Economics and Statistics, MIT Press, vol. 105(6), pages 1379-1393, November.
    6. Berger, Mark C & Black, Dan A, 1992. "Child Care Subsidies, Quality of Care, and the Labor Supply of Low-Income, Single Mothers," The Review of Economics and Statistics, MIT Press, vol. 74(4), pages 635-642, November.
    7. Stillman, Steven & McKenzie, David & Gibson, John, 2009. "Migration and mental health: Evidence from a natural experiment," Journal of Health Economics, Elsevier, vol. 28(3), pages 677-687, May.
    8. Laura Dague & Thomas DeLeire & Lindsey Leininger, 2017. "The Effect of Public Insurance Coverage for Childless Adults on Labor Supply," American Economic Journal: Economic Policy, American Economic Association, vol. 9(2), pages 124-154, May.
    9. Matthew Lang, 2013. "The Impact Of Mental Health Insurance Laws On State Suicide Rates," Health Economics, John Wiley & Sons, Ltd., vol. 22(1), pages 73-88, January.
    10. Roland G. Fryer & Lawrence F. Katz, 2013. "Achieving Escape Velocity: Neighborhood and School Interventions to Reduce Persistent Inequality," American Economic Review, American Economic Association, vol. 103(3), pages 232-237, May.
    11. Sara B. Heller & Anuj K. Shah & Jonathan Guryan & Jens Ludwig & Sendhil Mullainathan & Harold A. Pollack, 2017. "Thinking, Fast and Slow? Some Field Experiments to Reduce Crime and Dropout in Chicago," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(1), pages 1-54.
    12. Barnay, Thomas & Juin, Sandrine, 2016. "Does home care for dependent elderly people improve their mental health?," Journal of Health Economics, Elsevier, vol. 45(C), pages 149-160.
    13. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    14. Brian A. Jacob & Jens Ludwig, 2012. "The Effects of Housing Assistance on Labor Supply: Evidence from a Voucher Lottery," American Economic Review, American Economic Association, vol. 102(1), pages 272-304, February.
    15. Thomas Bossuroy & Markus Goldstein & Bassirou Karimou & Dean Karlan & Harounan Kazianga & William Parienté & Patrick Premand & Catherine C. Thomas & Christopher Udry & Julia Vaillant & Kelsey A. Wrigh, 2022. "Tackling psychosocial and capital constraints to alleviate poverty," Nature, Nature, vol. 605(7909), pages 291-297, May.
    16. Robles, Silvia & Gross, Max & Fairlie, Robert W., 2021. "The effect of course shutouts on community college students: Evidence from waitlist cutoffs," Journal of Public Economics, Elsevier, vol. 199(C).
    17. Gruber, Jonathan & Lordan, Grace & Pilling, Stephen & Propper, Carol & Saunders, Rob, 2022. "The impact of mental health support for the chronically ill on hospital utilisation: Evidence from the UK," Social Science & Medicine, Elsevier, vol. 294(C).
    18. Amy Finkelstein & Nathaniel Hendren & Erzo F. P. Luttmer, 2019. "The Value of Medicaid: Interpreting Results from the Oregon Health Insurance Experiment," Journal of Political Economy, University of Chicago Press, vol. 127(6), pages 2836-2874.
    19. Brian A. Jacob & Max Kapustin & Jens Ludwig, 2015. "The Impact of Housing Assistance on Child Outcomes: Evidence from a Randomized Housing Lottery," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(1), pages 465-506.
    20. Richard Layard, 2016. "The economics of mental health," IZA World of Labor, Institute of Labor Economics (IZA), pages 321-321, December.
    21. Chuard, Caroline, 2023. "Negative effects of long parental leave on maternal health: Evidence from a substantial policy change in Austria," Journal of Health Economics, Elsevier, vol. 88(C).
    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. Emma Sharland & Marta Rossa & Ted Dolby & Ekaterina Oparina & Rob Saunders & Daniel Ayoubkhani & Vahe Nifilyan & Klaudia Rzepnicka, 2025. "The effect of adult psychological therapies on employment and earnings: Evidence from England," CEP Discussion Papers dp2070, Centre for Economic Performance, LSE.

    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. Arbour, William & Lacroix, Guy & Marchand, Steeve, 2021. "Prison Rehabilitation Programs: Efficiency and Targeting," IZA Discussion Papers 14022, Institute of Labor Economics (IZA).
    2. Palmer, Caroline & Phillips, David C. & Sullivan, James X., 2019. "Does emergency financial assistance reduce crime?," Journal of Public Economics, Elsevier, vol. 169(C), pages 34-51.
    3. Cassidy, Michael T., 2020. "A Closer Look: Proximity Boosts Homeless Student Performance in New York City," IZA Discussion Papers 13558, Institute of Labor Economics (IZA).
    4. Nicolaj N. Mühlbach, 2020. "Tree-based Synthetic Control Methods: Consequences of moving the US Embassy," CREATES Research Papers 2020-04, Department of Economics and Business Economics, Aarhus University.
    5. Michael C. Knaus, 2021. "A double machine learning approach to estimate the effects of musical practice on student’s skills," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(1), pages 282-300, January.
    6. Michael C Knaus & Michael Lechner & Anthony Strittmatter, 2021. "Machine learning estimation of heterogeneous causal effects: Empirical Monte Carlo evidence," The Econometrics Journal, Royal Economic Society, vol. 24(1), pages 134-161.
    7. Hugo Bodory & Martin Huber & Michael Lechner, 2024. "The Finite Sample Performance of Instrumental Variable-Based Estimators of the Local Average Treatment Effect When Controlling for Covariates," Computational Economics, Springer;Society for Computational Economics, vol. 64(4), pages 2053-2078, October.
    8. Guido W. Imbens, 2020. "Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics," Journal of Economic Literature, American Economic Association, vol. 58(4), pages 1129-1179, December.
    9. Martin Huber & Jannis Kueck, 2022. "Testing the identification of causal effects in observational data," Papers 2203.15890, arXiv.org, revised Jun 2023.
    10. Nathan Kallus, 2023. "Treatment Effect Risk: Bounds and Inference," Management Science, INFORMS, vol. 69(8), pages 4579-4590, August.
    11. Andre Luis Squarize Chagas & Guilherme Malvezzi Rocha, 2019. "Housing program and social conditions impact: Evidences from Minha Casa Minha Vida program lotteries in Brazil," Working Papers, Department of Economics 2019_40, University of São Paulo (FEA-USP), revised 05 Nov 2019.
    12. Fredrik Andersson & John C. Haltiwanger & Mark J. Kutzbach & Giordano Palloni & Henry O. Pollakowski & Daniel H. Weinberg, 2013. "Childhood Housing and Adult Earnings: A Between-Siblings Analysis of Housing Vouchers and Public Housing," Working Papers 13-48, Center for Economic Studies, U.S. Census Bureau.
    13. Goller, Daniel & Harrer, Tamara & Lechner, Michael & Wolff, Joachim, 2021. "Active labour market policies for the long-term unemployed: New evidence from causal machine learning," Economics Working Paper Series 2108, University of St. Gallen, School of Economics and Political Science.
    14. Anna Baiardi & Andrea A. Naghi, 2021. "The Value Added of Machine Learning to Causal Inference: Evidence from Revisited Studies," Papers 2101.00878, arXiv.org.
    15. Nathan Kallus, 2022. "Treatment Effect Risk: Bounds and Inference," Papers 2201.05893, arXiv.org, revised Jul 2022.
    16. Brett R. Gordon & Robert Moakler & Florian Zettelmeyer, 2022. "Close Enough? A Large-Scale Exploration of Non-Experimental Approaches to Advertising Measurement," Papers 2201.07055, arXiv.org, revised Oct 2022.
    17. Anna Baiardi & Andrea A. Naghi, 2021. "The Value Added of Machine Learning to Causal Inference: Evidence from Revisited Studies," Tinbergen Institute Discussion Papers 21-001/V, Tinbergen Institute.
    18. Joshua B. Gilbert & Zachary Himmelsbach & James Soland & Mridul Joshi & Benjamin W. Domingue, 2024. "Estimating Heterogeneous Treatment Effects with Item-Level Outcome Data: Insights from Item Response Theory," Papers 2405.00161, arXiv.org, revised Jan 2025.
    19. Max H. Farrell & Tengyuan Liang & Sanjog Misra, 2021. "Deep Neural Networks for Estimation and Inference," Econometrica, Econometric Society, vol. 89(1), pages 181-213, January.
    20. Strittmatter, Anthony, 2023. "What is the value added by using causal machine learning methods in a welfare experiment evaluation?," Labour Economics, Elsevier, vol. 84(C).

    More about this item

    Keywords

    mental health; psychological therapies; quasi-natural experiment; policy evaluation; machine learning; cost-benefit analysis; wellbeing;
    All these keywords.

    JEL classification:

    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • D00 - Microeconomics - - General - - - General

    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:ehl:lserod:126829. 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: LSERO Manager (email available below). General contact details of provider: https://edirc.repec.org/data/lsepsuk.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.