IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp10057.html
   My bibliography  Save this paper

Proxy Variables and Nonparametric Identification of Causal Effects

Author

Listed:
  • de Luna, Xavier

    (Umeå University)

  • Fowler, Philip

    (Umeå University)

  • Johansson, Per

    (Uppsala University)

Abstract

Proxy variables are often used in linear regression models with the aim of removing potential confounding bias. In this paper we formalise proxy variables within the potential outcome framework, giving conditions under which it can be shown that causal effects are nonparametrically identified. We characterise two types of proxy variables and give concrete examples where the proxy conditions introduced may hold by design.

Suggested Citation

  • de Luna, Xavier & Fowler, Philip & Johansson, Per, 2016. "Proxy Variables and Nonparametric Identification of Causal Effects," IZA Discussion Papers 10057, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp10057
    as

    Download full text from publisher

    File URL: https://docs.iza.org/dp10057.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, April.
    3. Frost, Peter A, 1979. "Proxy Variables and Specification Bias," The Review of Economics and Statistics, MIT Press, vol. 61(2), pages 323-325, May.
    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. Sènakpon Fidèle A. Dedehouanou & Luca Tiberti & Hilaire G. Houeninvo & Djohodo Inès Monwanou, 2019. "Working while studying: Employment premium or penalty for youth in Benin?," Working Papers PMMA 2019-03, PEP-PMMA.
    2. N'dri, Lasme Mathieu & Kakinaka, Makoto, 2020. "Financial inclusion, mobile money, and individual welfare: The case of Burkina Faso," Telecommunications Policy, Elsevier, vol. 44(3).
    3. Stacy, Brian, 2014. "Ranking Teachers when Teacher Value-Added is Heterogeneous Across Students," EconStor Preprints 104743, ZBW - Leibniz Information Centre for Economics.
    4. Dennis Shen & Peng Ding & Jasjeet Sekhon & Bin Yu, 2022. "Same Root Different Leaves: Time Series and Cross-Sectional Methods in Panel Data," Papers 2207.14481, arXiv.org, revised Oct 2022.
    5. Stefan Boes & Michael Gerfin, 2016. "Does Full Insurance Increase the Demand for Health Care?," Health Economics, John Wiley & Sons, Ltd., vol. 25(11), pages 1483-1496, November.
    6. Mullahy, John, 2024. "Analyzing health outcomes measured as bounded counts," Journal of Health Economics, Elsevier, vol. 95(C).
    7. Del Prete, Davide & Ghins, Léopold & Magrini, Emiliano & Pauw, Karl, 2019. "Land consolidation, specialization and household diets: Evidence from Rwanda," Food Policy, Elsevier, vol. 83(C), pages 139-149.
    8. Tymon Słoczyński, 2022. "Interpreting OLS Estimands When Treatment Effects Are Heterogeneous: Smaller Groups Get Larger Weights," The Review of Economics and Statistics, MIT Press, vol. 104(3), pages 501-509, May.
    9. Rita A. Balaban & Donna B. Gilleskie & Uyen Tran, 2016. "A quantitative evaluation of the flipped classroom in a large lecture principles of economics course," The Journal of Economic Education, Taylor & Francis Journals, vol. 47(4), pages 269-287, October.
    10. Mirella Damiani & Fabrizio Pompei & Andrea Ricci, 2020. "Opting Out, Collective Contracts and Labour Flexibility: Firm‐Level Evidence for The Italian Case," British Journal of Industrial Relations, London School of Economics, vol. 58(3), pages 558-586, September.
    11. Faruque As Sunny & Linlin Fu & Md Sadique Rahman & Zuhui Huang, 2022. "Determinants and Impact of Solar Irrigation Facility (SIF) Adoption: A Case Study in Northern Bangladesh," Energies, MDPI, vol. 15(7), pages 1-17, March.
    12. Annette Schminke & Johannes Van Biesebroeck, 2013. "Using export market performance to evaluate regional preferential policies in China," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 149(2), pages 343-367, June.
    13. Müller, Isabella & Nguyen, Huyen & Nguyen, Trang, 2024. "Carbon transition risk and corporate loan securitization," IWH Discussion Papers 22/2022, Halle Institute for Economic Research (IWH), revised 2024.
    14. Hao Dong & Daniel L. Millimet, 2020. "Propensity Score Weighting with Mismeasured Covariates: An Application to Two Financial Literacy Interventions," JRFM, MDPI, vol. 13(11), pages 1-24, November.
    15. Backson Mwangi & Ibrahim Macharia & Eric Bett, 2021. "Ex-post Impact Evaluation of Improved Sorghum Varieties on Poverty Reduction in Kenya: A Counterfactual Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 154(2), pages 447-467, April.
    16. Castells-Quintana, David & Lopez-Uribe, Maria del Pilar & McDermott, Thomas K.J., 2022. "Population displacement and urban conflict: Global evidence from more than 3300 flood events," Journal of Development Economics, Elsevier, vol. 158(C).
    17. Tea Petrin & Dragana Radicic, 2023. "Instrument policy mix and firm size: is there complementarity between R&D subsidies and R&D tax credits?," The Journal of Technology Transfer, Springer, vol. 48(1), pages 181-215, February.
    18. Crespo Cuaresma, Jesus & Oberhofer, Harald & Vincelette, Gallina Andronova, 2014. "Firm growth and productivity in Belarus: New empirical evidence from the machine building industry," Journal of Comparative Economics, Elsevier, vol. 42(3), pages 726-738.
    19. Jonathan Kropko & Robert Kubinec, 2020. "Interpretation and identification of within-unit and cross-sectional variation in panel data models," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-22, April.
    20. Siddhartha Bandyopadhyay & Sanjukta Sarkar & Rudra Sensarma, 2021. "Does Access to Key Household Resources Help in Reducing Violence against Women?," Discussion Papers 21-09, Department of Economics, University of Birmingham.

    More about this item

    Keywords

    potential outcomes; observational studies; average treatment effect; unobserved confounders;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: 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:iza:izadps:dp10057. 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.