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Constructing Sampling Weights for the Quarterly Financial Report

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  • N. Aaron Pancost

Abstract

Although sampling weights are necessary inputs to any statistical analysis using the QFR microdata, they are unavailable in many years. I compute sampling weights for QFR firms in Census years by merging them with the Economic Census and the LBD. I use the LBD to aggregate data to the firm level; the Economic Census allows me to include conditioning variables (beyond employment) from which I estimate the probability of inclusion in the QFR using logit regressions. First, I find that a substantial number of QFR respondents belong to the same firm. Second, the estimated logit weights are reasonable and lead to sensible estimates of aggregate employment for most years and broad industry categories: manufacturing, mining, retail trade, and wholesale trade, but only after restricting the minimum firm size for non-QFR firms in the EC.

Suggested Citation

  • N. Aaron Pancost, 2022. "Constructing Sampling Weights for the Quarterly Financial Report," CES Technical Notes Series 22-12, Center for Economic Studies, U.S. Census Bureau.
    • Handle: RePEc:cen:tnotes:22-12
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    Keywords

    QFR; LBD; CMF; CMI; CRT; CWT;
    All these keywords.

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