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What’s Up with Unit Non-Response in the Bank of Canada’s Business Outlook Survey? The Effect of Staff Tenure

Author

Listed:
  • Sarah Miller
  • David Amirault
  • Laurent Martin

Abstract

Since 1997, the Bank of Canada’s regional offices have been conducting the Business Outlook Survey (BOS), a quarterly survey of business conditions. Survey responses are gathered through face-to-face, confidential consultations with a sample of private sector firms representative of the various sectors, firm sizes and regions across Canada. Participation is voluntary and although efforts are made to encourage participation, some firms either do not respond to the Bank’s contact attempts or refuse to or cannot participate for various reasons, resulting in unit non-response. Using data for all firms contacted between 2009 and 2016, this paper analyzes the determinants of unit non-response including the impact of the tenure of the Bank’s survey booking teams. Difference-in-differences estimates suggest that new survey booking teams increase the probability of unit non-response. Building on previous findings, regression results also provide further support that some firm characteristics are associated with non-response, including firm size, ownership status, sector and participation history. There is little evidence to conclude that the effect linked to new booking teams differs significantly for new versus repeat firms. Finally, we find no statistically significant relationship between firms’ credit scores and unit non-response, and no obvious upward trend in the BOS non-response rate once other relevant factors have been taken into account.

Suggested Citation

  • Sarah Miller & David Amirault & Laurent Martin, 2017. "What’s Up with Unit Non-Response in the Bank of Canada’s Business Outlook Survey? The Effect of Staff Tenure," Discussion Papers 17-11, Bank of Canada.
    • Handle: RePEc:bca:bocadp:17-11
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    References listed on IDEAS

    as
    1. Christian Seiler, 2014. "The determinants of unit non-response in the Ifo Business Survey," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 8(3), pages 161-177, September.
    2. Chernis, Tony & Cheung, Calista & Velasco, Gabriella, 2020. "A three-frequency dynamic factor model for nowcasting Canadian provincial GDP growth," International Journal of Forecasting, Elsevier, vol. 36(3), pages 851-872.
    3. Daniel de Munnik & Mark Illing & David Dupuis, 2013. "Assessing the accuracy of non-random business conditions surveys: a novel approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(2), pages 371-388, February.
    4. Annelies G. Blom & Edith D. de Leeuw & Joop J. Hox, 2010. "Interviewer Effects on Nonresponse," MEA discussion paper series 10202, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    5. Florian Janik & Susanne Kohaut, 2012. "Why don’t they answer? Unit non-response in the IAB establishment panel," Quality & Quantity: International Journal of Methodology, Springer, vol. 46(3), pages 917-934, April.
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    More about this item

    Keywords

    Econometric and statistical methods; Firm dynamics; Regional economic developments;
    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
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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