IDEAS home Printed from https://ideas.repec.org/p/cen/wpaper/17-45.html
   My bibliography  Save this paper

File Matching with Faulty Continuous Matching Variables

Author

Listed:
  • Nicole M. Dalzell
  • Jerome P. Reiter
  • Gale Boyd

Abstract

We present LFCMV, a Bayesian file linking methodology designed to link records using continuous matching variables in situations where we do not expect values of these matching variables to agree exactly across matched pairs. The method involves a linking model for the distance between the matching variables of records in one file and the matching variables of their linked records in the second. This linking model is conditional on a vector indicating the links. We specify a mixture model for the distance component of the linking model, as this latent structure allows the distance between matching variables in linked pairs to vary across types of linked pairs. Finally, we specify a model for the linking vector. We describe the Gibbs sampling algorithm for sampling from the posterior distribution of this linkage model and use artificial data to illustrate model performance. We also introduce a linking application using public survey information and data from the U.S. Census of Manufactures and use LFCMV to link the records.

Suggested Citation

  • Nicole M. Dalzell & Jerome P. Reiter & Gale Boyd, 2017. "File Matching with Faulty Continuous Matching Variables," Working Papers 17-45, Center for Economic Studies, U.S. Census Bureau.
    • Handle: RePEc:cen:wpaper:17-45
    as

    Download full text from publisher

    File URL: https://www2.census.gov/ces/wp/2017/CES-WP-17-45.pdf
    File Function: First version, 2017
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hang J. Kim & Jerome P. Reiter & Quanli Wang & Lawrence H. Cox & Alan F. Karr, 2014. "Multiple Imputation of Missing or Faulty Values Under Linear Constraints," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(3), pages 375-386, July.
    2. Todd D. Gerarden & Richard G. Newell & Robert N. Stavins, 2017. "Assessing the Energy-Efficiency Gap," Journal of Economic Literature, American Economic Association, vol. 55(4), pages 1486-1525, December.
    3. Ishwaran H. & James L. F, 2001. "Gibbs Sampling Methods for Stick Breaking Priors," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 161-173, March.
    4. Hunt Allcott & Michael Greenstone, 2012. "Is There an Energy Efficiency Gap?," Journal of Economic Perspectives, American Economic Association, vol. 26(1), pages 3-28, Winter.
    5. Roee Gutman & Christopher C. Afendulis & Alan M. Zaslavsky, 2013. "A Bayesian Procedure for File Linking to Analyze End-of-Life Medical Costs," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(501), pages 34-47, March.
    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. Louis-Gaëtan Giraudet & Anna Petronevich & Laurent Faucheux, 2018. "How do lenders price energy efficiency? Evidence from posted interest rates for unsecured credit in France [Comment les créditeurs valorisent-ils l'efficacité énergétique? Une analyse des taux d'in," Working Papers hal-01890636, HAL.
    2. Kube, Roland & von Graevenitz, Kathrine & Löschel, Andreas & Massier, Philipp, 2019. "Do voluntary environmental programs reduce emissions? EMAS in the German manufacturing sector," Energy Economics, Elsevier, vol. 84(S1).
    3. Gale A. Boyd and Jonathan M. Lee, 2020. "Relative Effectiveness of Energy Efficiency Programs versus Market Based Climate Policies in the Chemical Industry," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 39-62.
    4. Joshua Blonz, 2019. "The Welfare Costs of Misaligned Incentives: Energy Inefficiency and the Principal-Agent Problem," Finance and Economics Discussion Series 2019-071, Board of Governors of the Federal Reserve System (U.S.).
    5. Laura Abrardi, 2019. "Behavioral barriers and the energy efficiency gap: a survey of the literature," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 46(1), pages 25-43, March.
    6. Dimitris Damigos & Christina Kaliampakou & Anastasios Balaskas & Lefkothea Papada, 2021. "Does Energy Poverty Affect Energy Efficiency Investment Decisions? First Evidence from a Stated Choice Experiment," Energies, MDPI, vol. 14(6), pages 1-17, March.
    7. Olivier De Groote & Frank Verboven, 2019. "Subsidies and Time Discounting in New Technology Adoption: Evidence from Solar Photovoltaic Systems," American Economic Review, American Economic Association, vol. 109(6), pages 2137-2172, June.
    8. Cohen, François & Glachant, Matthieu & Söderberg, Magnus, 2017. "Consumer myopia, imperfect competition and the energy efficiency gap: Evidence from the UK refrigerator market," European Economic Review, Elsevier, vol. 93(C), pages 1-23.
    9. Kent D. Daniel & Robert B. Litterman & Gernot Wagner, 2016. "Applying Asset Pricing Theory to Calibrate the Price of Climate Risk," NBER Working Papers 22795, National Bureau of Economic Research, Inc.
    10. Moreno-Cruz, Juan B. & Wagner, Gernot & Keith, David w., 2017. "An Economic Anatomy of Optimal Climate Policy," Working Paper Series rwp17-028, Harvard University, John F. Kennedy School of Government.
    11. Stadelmann, Marcel & Schubert, Renate, 2018. "How Do Different Designs of Energy Labels Influence Purchases of Household Appliances? A Field Study in Switzerland," Ecological Economics, Elsevier, vol. 144(C), pages 112-123.
    12. Das, Narasingha & Gangopadhyay, Partha & Alghamdi, Thamer & Sarwar, Suleman & Haseeb, Mohammad & Barut, Abdulkadir & Dey, Labani, 2023. "Understanding the role of efficiency in the electricity generation process for promoting human development in India: Findings from the novel multiple threshold nonlinear ARDL modelling," Utilities Policy, Elsevier, vol. 82(C).
    13. Lu Zhang & Lennart Stangenberg & Sjors van Wickeren, 2020. "The information value of energy labels: Evidence from the Dutch residential housing market," CPB Discussion Paper 413.rdf, CPB Netherlands Bureau for Economic Policy Analysis.
    14. Trotta, Gianluca, 2018. "Factors affecting energy-saving behaviours and energy efficiency investments in British households," Energy Policy, Elsevier, vol. 114(C), pages 529-539.
    15. Bruno Lanz and Evert Reins, 2021. "Asymmetric Information on the Market for Energy Efficiency: Insights from the Credence Goods Literature," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    16. Rockstuhl, Sebastian & Wenninger, Simon & Wiethe, Christian & Häckel, Björn, 2021. "Understanding the risk perception of energy efficiency investments: Investment perspective vs. energy bill perspective," Energy Policy, Elsevier, vol. 159(C).
    17. Lang, Ghislaine & Lanz, Bruno, 2022. "Climate policy without a price signal: Evidence on the implicit carbon price of energy efficiency in buildings," Journal of Environmental Economics and Management, Elsevier, vol. 111(C).
    18. Andersen, Kristoffer Steen & Wiese, Catharina & Petrovic, Stefan & McKenna, Russell, 2020. "Exploring the role of households’ hurdle rates and demand elasticities in meeting Danish energy-savings target," Energy Policy, Elsevier, vol. 146(C).
    19. Chersoni, Giulia & DellaValle, Nives & Fontana, Magda, 2022. "Modelling thermal insulation investment choice in the EU via a behaviourally informed agent-based model," Energy Policy, Elsevier, vol. 163(C).
    20. Anne Kesselring, 2023. "Willingness-to-Pay for Energy Efficiency: Evidence from the European Common Market," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 86(4), pages 893-945, December.

    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:cen:wpaper:17-45. 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: Dawn Anderson (email available below). General contact details of provider: https://edirc.repec.org/data/cesgvus.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.