IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/28413.html
   My bibliography  Save this paper

Selection on Welfare Gains: Experimental Evidence from Electricity Plan Choice

Author

Listed:
  • Koichiro Ito
  • Takanori Ida
  • Makoto Tanaka

Abstract

We study a problem in which policymakers need to screen self-selected individuals by unobserved heterogeneity in social welfare gains from a policy intervention. In our framework, the marginal treatment effects and marginal treatment responses arise as key statistics to characterize social welfare. We apply this framework to a randomized field experiment on electricity plan choice. Consumers were offered welfare-improving dynamic pricing with randomly assigned take-up incentives. We find that price-elastic consumers—who generate larger welfare gains—are more likely to self-select. Our counterfactual simulations quantify the optimal take-up incentives that exploit observed and unobserved heterogeneity in selection and welfare gains.

Suggested Citation

  • Koichiro Ito & Takanori Ida & Makoto Tanaka, 2021. "Selection on Welfare Gains: Experimental Evidence from Electricity Plan Choice," NBER Working Papers 28413, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:28413
    Note: EEE IO PE
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w28413.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. LaLonde, Robert J, 1986. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," American Economic Review, American Economic Association, vol. 76(4), pages 604-620, September.
    2. James J. Heckman, 2010. "Building Bridges between Structural and Program Evaluation Approaches to Evaluating Policy," Journal of Economic Literature, American Economic Association, vol. 48(2), pages 356-398, June.
    3. Liran Einav & Amy Finkelstein & Yunan Ji & Neale Mahoney, 2022. "Voluntary Regulation: Evidence from Medicare Payment Reform," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 137(1), pages 565-618.
    4. Robinson, Peter M, 1988. "Root- N-Consistent Semiparametric Regression," Econometrica, Econometric Society, vol. 56(4), pages 931-954, July.
    5. James J. Heckman & Edward Vytlacil, 2005. "Structural Equations, Treatment Effects, and Econometric Policy Evaluation," Econometrica, Econometric Society, vol. 73(3), pages 669-738, May.
    6. Ahmad Faruqui & Sanem Sergici, 2011. "Dynamic pricing of electricity in the mid-Atlantic region: econometric results from the Baltimore gas and electric company experiment," Journal of Regulatory Economics, Springer, vol. 40(1), pages 82-109, August.
    7. Liran Einav & Amy Finkelstein & Paul Schrimpf, 2010. "Optimal Mandates and the Welfare Cost of Asymmetric Information: Evidence From the U.K. Annuity Market," Econometrica, Econometric Society, vol. 78(3), pages 1031-1092, May.
    8. Manasi Deshpande & Yue Li, 2019. "Who Is Screened Out? Application Costs and the Targeting of Disability Programs," American Economic Journal: Economic Policy, American Economic Association, vol. 11(4), pages 213-248, November.
    9. Kline, Patrick & Walters, Christopher, 2014. "Evaluating Public Programs with Close Substitutes: The Case of Head Start," Institute for Research on Labor and Employment, Working Paper Series qt43s9211b, Institute of Industrial Relations, UC Berkeley.
    10. 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.
    11. Severin Borenstein & Lucas W. Davis, 2016. "The Distributional Effects of US Clean Energy Tax Credits," Tax Policy and the Economy, University of Chicago Press, vol. 30(1), pages 191-234.
    12. Callen, Mike & Isaqzadeh, Mohammad & Long, James D. & Sprenger, Charles, 2014. "Violence and risk preference: experimental evidence from Afghanistan," LSE Research Online Documents on Economics 102932, London School of Economics and Political Science, LSE Library.
    13. Raj Chetty, 2009. "Sufficient Statistics for Welfare Analysis: A Bridge Between Structural and Reduced-Form Methods," Annual Review of Economics, Annual Reviews, vol. 1(1), pages 451-488, May.
    14. Magne Mogstad & Andres Santos & Alexander Torgovitsky, 2018. "Using Instrumental Variables for Inference About Policy Relevant Treatment Parameters," Econometrica, Econometric Society, vol. 86(5), pages 1589-1619, September.
    15. Gallant, A Ronald & Nychka, Douglas W, 1987. "Semi-nonparametric Maximum Likelihood Estimation," Econometrica, Econometric Society, vol. 55(2), pages 363-390, March.
    16. Michael Callen & Mohammad Isaqzadeh & James D. Long & Charles Sprenger, 2014. "Violence and Risk Preference: Experimental Evidence from Afghanistan," American Economic Review, American Economic Association, vol. 104(1), pages 123-148, January.
    17. Meredith Fowlie & Catherine Wolfram & C. Anna Spurlock & Annika Todd & Patrick Baylis & Peter Cappers, 2017. "Default Effects and Follow-On Behavior: Evidence from an Electricity Pricing Program," NBER Working Papers 23553, National Bureau of Economic Research, Inc.
    18. Hunt Allcott & Michael Greenstone, 2017. "Measuring the Welfare Effects of Residential Energy Efficiency Programs," NBER Working Papers 23386, National Bureau of Economic Research, Inc.
    19. Amy Finkelstein & Matthew J Notowidigdo, 2019. "Take-Up and Targeting: Experimental Evidence from SNAP," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 134(3), pages 1505-1556.
    20. 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.
    21. Kline, Patrick & Walters, Christopher, 2014. "Evaluating Public Programs with Close Substitutes: The Case of Head Start," Department of Economics, Working Paper Series qt43s9211b, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    22. Philipp Eisenhauer & James J. Heckman & Edward Vytlacil, 2015. "The Generalized Roy Model and the Cost-Benefit Analysis of Social Programs," Journal of Political Economy, University of Chicago Press, vol. 123(2), pages 413-443.
    23. Ali Hortaçsu & Seyed Ali Madanizadeh & Steven L. Puller, 2017. "Power to Choose? An Analysis of Consumer Inertia in the Residential Electricity Market," American Economic Journal: Economic Policy, American Economic Association, vol. 9(4), pages 192-226, November.
    24. Frank A. Wolak, 2011. "Do Residential Customers Respond to Hourly Prices? Evidence from a Dynamic Pricing Experiment," American Economic Review, American Economic Association, vol. 101(3), pages 83-87, May.
    25. S. Borenstein, 2013. "Effective and Equitable Adoption of Opt-In Residential Dynamic Electricity Pricing," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 42(2), pages 127-160, March.
    26. Severin Borenstein, 2002. "The Trouble With Electricity Markets: Understanding California's Restructuring Disaster," Journal of Economic Perspectives, American Economic Association, vol. 16(1), pages 191-211, Winter.
    27. Koichiro Ito & Takanori Ida & Makoto Tanaka, 2018. "Moral Suasion and Economic Incentives: Field Experimental Evidence from Energy Demand," American Economic Journal: Economic Policy, American Economic Association, vol. 10(1), pages 240-267, February.
    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. Lang, Corey & Qiu, Yueming (Lucy) & Dong, Luran, 2023. "Increasing voluntary enrollment in time-of-use electricity rates: Findings from a survey experiment," Energy Policy, Elsevier, vol. 173(C).
    2. Luther Yap, 2022. "Sensitivity of Policy Relevant Treatment Parameters to Violations of Monotonicity," Working Papers 655, Princeton University, Department of Economics, Industrial Relations Section..
    3. 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.
    4. Luis E. GONZALES & ITO Koichiro & Mar REGUANT, 2022. "The Dynamic Impact of Market Integration: Evidence from renewable energy expansion in Chile," Discussion papers 22050, Research Institute of Economy, Trade and Industry (RIETI).
    5. Capitán, Tabaré & Alpízar, Francisco & Madrigal-Ballestero, Róger & Pattanayak, Subhrendu K., 2021. "Time-varying pricing may increase total electricity consumption: Evidence from Costa Rica," Resource and Energy Economics, Elsevier, vol. 66(C).
    6. Hirofumi Kurokawa & Shusaku Sasaki, 2023. "How Does Opt-in Work? A Field Experiment on Financial Incentives for Physical Activity," Discussion Papers in Economics and Business 23-01, Osaka University, Graduate School of Economics.
    7. Pébereau, Charles & Remmy, Kevin, 2023. "Barriers to real-time electricity pricing: Evidence from New Zealand," International Journal of Industrial Organization, Elsevier, vol. 89(C).

    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. Wang, Wenjie & Ida, Takanori & Shimada, Hideki, 2020. "Default effect versus active decision: Evidence from a field experiment in Los Alamos," European Economic Review, Elsevier, vol. 128(C).
    2. Jeffrey Smith & Arthur Sweetman, 2016. "Viewpoint: Estimating the causal effects of policies and programs," Canadian Journal of Economics, Canadian Economics Association, vol. 49(3), pages 871-905, August.
    3. Rothstein, Jesse & Von Wachter, Till, 2016. "Social Experiments in the Labor Market," Department of Economics, Working Paper Series qt7957p9g6, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    4. Rothstein, Jesse & von Wachter, Till, 2016. "Social Experiments in the Labor Market," Institute for Research on Labor and Employment, Working Paper Series qt6605k20b, Institute of Industrial Relations, UC Berkeley.
    5. Jesse Rothstein & Till von Wachter, 2016. "Social Experiments in the Labor Market," NBER Working Papers 22585, National Bureau of Economic Research, Inc.
    6. Rothstein, Jesse & von Wachter, Till, 2016. "Social Experiments in the Labor Market," Department of Economics, Working Paper Series qt6605k20b, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    7. Cornelissen, Thomas & Dustmann, Christian & Raute, Anna & Schönberg, Uta, 2016. "From LATE to MTE: Alternative methods for the evaluation of policy interventions," Labour Economics, Elsevier, vol. 41(C), pages 47-60.
    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. Gerten, Elisa & Beckmann, Michael & Kräkel, Matthias, 2022. "Information and Communication Technology, Hierarchy, and Job Design," IZA Discussion Papers 15491, Institute of Labor Economics (IZA).
    10. Patrick Kline & Christopher R. Walters, 2019. "On Heckits, LATE, and Numerical Equivalence," Econometrica, Econometric Society, vol. 87(2), pages 677-696, March.
    11. Robert W. Hahn & Robert D. Metcalfe, 2021. "Efficiency and Equity Impacts of Energy Subsidies," American Economic Review, American Economic Association, vol. 111(5), pages 1658-1688, May.
    12. Manu Navjeevan & Rodrigo Pinto & Andres Santos, 2023. "Identification and Estimation in a Class of Potential Outcomes Models," Papers 2310.05311, arXiv.org.
    13. Bartalotti, Otávio & Kédagni, Désiré & Possebom, Vitor, 2023. "Identifying marginal treatment effects in the presence of sample selection," Journal of Econometrics, Elsevier, vol. 234(2), pages 565-584.
    14. Gathmann, Christina & Vonnahme, Christina & Kim, Jongoh & Busse, Anna, 2021. "Marginal Returns to Citizenship and Educational Performance," CEPR Discussion Papers 16636, C.E.P.R. Discussion Papers.
    15. Vishal Kamat & Samuel Norris & Matthew Pecenco, 2023. "Identification in Multiple Treatment Models under Discrete Variation," Papers 2307.06174, arXiv.org.
    16. Jorge Rodríguez & Fernando Saltiel & Sergio Urzúa, 2022. "Dynamic treatment effects of job training," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 242-269, March.
    17. Zhewen Pan & Zhengxin Wang & Junsen Zhang & Yahong Zhou, 2024. "Marginal treatment effects in the absence of instrumental variables," Papers 2401.17595, arXiv.org.
    18. 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.
    19. Giesecke, Matthias & Schuß, Eric, 2019. "Heterogeneity in marginal returns to language training of immigrants," IAB-Discussion Paper 201919, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    20. James J. Heckman, 1991. "Randomization and Social Policy Evaluation Revisited," NBER Technical Working Papers 0107, National Bureau of Economic Research, Inc.

    More about this item

    JEL classification:

    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

    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:nbr:nberwo:28413. 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://edirc.repec.org/data/nberrus.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.