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Modeling Single Establishment Firm Returns to the 2007 Economic Census


  • Emin Dinlersoz
  • Shawn Klimek


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

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    References listed on IDEAS

    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 J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," Review of Economic Studies, Oxford University Press, vol. 64(4), pages 605-654.
    3. 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.
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    More about this item


    Economic Census; multivariate analysis; paradata; responsive design;

    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

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