IDEAS home Printed from https://ideas.repec.org/p/cen/wpaper/11-28.html
   My bibliography  Save this paper

Modeling Single Establishment Firm Returns to the 2007 Economic Census

Author

Listed:
  • Emin Dinlersoz
  • Shawn Klimek

Abstract

The Economic Census is one of the most important activities that the U.S. Census Bureau performs. It is critical for updating firm ownership/structure and industry information for a large number of businesses in the Census Bureau’s Business Register, impacting most other economic programs. Also, it feeds into Bureau of Economic Analysis products, such as benchmark inputoutput accounts and Gross Domestic Product. The overall check-in rate for the 2007 Economic Census was just over 86%. Establishments owned by multi-location companies returned over 90% of their forms, as compared to the roughly two million single-establishment firms sampled in the Census that returned just over 80%. We model the check-in rate for single-establishment firms by using a large number of variables that might be correlated with whether or not a firm returns a form in the Economic Census. These variables are broadly categorized as the characteristics of firms, measures of external factors, and features of the survey design. We use the model for two purposes. First, by including many of the factors that may be correlated with returns we aim to focus limited advertising and outreach resources to low-return segments of the population. Second, we use the model to investigate the efficacy of an unplanned intervention expected to increase return rates: using certified mailing for one of the form follow-ups.

Suggested Citation

  • Emin Dinlersoz & Shawn Klimek, 2011. "Modeling Single Establishment Firm Returns to the 2007 Economic Census," Working Papers 11-28, Center for Economic Studies, U.S. Census Bureau.
    • Handle: RePEc:cen:wpaper:11-28
    as

    Download full text from publisher

    File URL: https://www2.census.gov/ces/wp/2011/CES-WP-11-28.pdf
    File Function: First version, 2011
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. A. Smith, Jeffrey & E. Todd, Petra, 2005. "Does matching overcome LaLonde's critique of nonexperimental estimators?," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 305-353.
    2. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," Econometrica, Econometric Society, vol. 66(5), pages 1017-1098, September.
    3. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    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. Dettmann, E. & Becker, C. & Schmeißer, C., 2011. "Distance functions for matching in small samples," Computational Statistics & Data Analysis, Elsevier, vol. 55(5), pages 1942-1960, May.
    2. Sant’Anna, Pedro H.C. & Zhao, Jun, 2020. "Doubly robust difference-in-differences estimators," Journal of Econometrics, Elsevier, vol. 219(1), pages 101-122.
    3. Iacus, Stefano M. & Porro, Giuseppe, 2007. "Missing data imputation, matching and other applications of random recursive partitioning," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 773-789, October.
    4. Islam, Asadul & Nguyen, Chau & Smyth, Russell, 2015. "Does microfinance change informal lending in village economies? Evidence from Bangladesh," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 141-156.
    5. Aki Kangasharju, 2007. "Do Wage Subsidies Increase Employment in Subsidized Firms?," Economica, London School of Economics and Political Science, vol. 74(293), pages 51-67, February.
    6. Frölich, Markus & Michaelowa, Katharina, 2004. "Peer effects and textbooks in primary education: Evidence from francophone sub-Saharan Africa," HWWA Discussion Papers 311, Hamburg Institute of International Economics (HWWA).
    7. Polyakov, Maksym & Iftekhar, Md Sayed & Fogarty, James & Buurman, Joost, 2022. "Renewal of waterways in a dense city creates value for residents," Ecological Economics, Elsevier, vol. 199(C).
    8. Juan Díaz & Miguel Jaramillo, 2006. "An Evaluation of the Peruvian "Youth Labor Training Program"-PROJOVEN," OVE Working Papers 1006, Inter-American Development Bank, Office of Evaluation and Oversight (OVE).
    9. Ravallion, Martin & Galasso, Emanuela & Lazo, Teodoro & Philipp, Ernesto, 2001. "Do workfare participants recover quickly from retrenchment?," Policy Research Working Paper Series 2672, The World Bank.
    10. Aydemir, Abdurrahman B. & Kırdar, Murat G., 2017. "Quasi-experimental impact estimates of immigrant labor supply shocks: The role of treatment and comparison group matching and relative skill composition," European Economic Review, Elsevier, vol. 98(C), pages 282-315.
    11. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2006. "Moving the Goalposts: Addressing Limited Overlap in the Estimation of Average Treatment Effects by Changing the Estimand," NBER Technical Working Papers 0330, National Bureau of Economic Research, Inc.
    12. Paweł Strawiński, 2013. "Controlling for overlap in matching," Working Papers 2013-10, Faculty of Economic Sciences, University of Warsaw.
    13. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2009. "Dealing with limited overlap in estimation of average treatment effects," Biometrika, Biometrika Trust, vol. 96(1), pages 187-199.
    14. Myriã Tatiany Neves Bast & Sergio Naruhiko Sakurai, 2016. "Uma Avaliação Empírica Dos Efeitos Dos Empréstimos Do Bndes Aos Governos Municipais Brasileiros," Anais do XLIII Encontro Nacional de Economia [Proceedings of the 43rd Brazilian Economics Meeting] 064, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    15. Spermann, Alexander & Strotmann, Harald, 2005. "The Targeted Negative Income Tax (TNIT) in Germany: Evidence from a Quasi Experiment," ZEW Discussion Papers 05-68, ZEW - Leibniz Centre for European Economic Research.
    16. Bernhard Boockmann & Tobias Brändle, 2019. "Coaching, Counseling, Case‐Working: Do They Help the Older Unemployed Out of Benefit Receipt and Back Into the Labor Market?," German Economic Review, Verein für Socialpolitik, vol. 20(4), pages 436-468, November.
    17. Kamdem, Cyrille Bergaly, 2016. "Impact of cocoa farmer field schools on cocoa yield: empirical evidence of cocoa farmers in Cameroon," 2016 Fifth International Conference, September 23-26, 2016, Addis Ababa, Ethiopia 246388, African Association of Agricultural Economists (AAAE).
    18. Guo, Yuchen Mo & Falck, Oliver & Langer, Christina & Lindlacher, Valentin & Wiederhold, Simon, 2024. "Training, Automation, and Wages: Worker-Level Evidence," VfS Annual Conference 2024 (Berlin): Upcoming Labor Market Challenges 302366, Verein für Socialpolitik / German Economic Association.
    19. Kent Eliasson & Pär Hansson, 2016. "Are workers more vulnerable in tradable industries?," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 152(2), pages 283-320, May.
    20. Marco Caliendo & Reinhard Hujer & Stephan L. Thomsen, 2008. "The employment effects of job-creation schemes in Germany: A microeconometric evaluation," Advances in Econometrics, in: Modelling and Evaluating Treatment Effects in Econometrics, pages 381-428, Emerald Group Publishing Limited.

    More about this item

    Keywords

    Economic Census; multivariate analysis; paradata; responsive design;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

    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:cen:wpaper:11-28. 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.