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Alternative Methods of Unit Nonresponse Weighting Adjustments: An Application from the 2003 Survey of Small Business Fin

Alternative Methods of Unit Nonresponse Weighting Adjustments: An Application from the 2003 Survey of Small Business Finances *. Lieu N. Hazelwood, Traci L. Mach, and John D. Wolken ICES 2007 June 20, 2007

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Alternative Methods of Unit Nonresponse Weighting Adjustments: An Application from the 2003 Survey of Small Business Fin

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  1. Alternative Methods of Unit Nonresponse Weighting Adjustments: An Application from the 2003 Survey of Small Business Finances * Lieu N. Hazelwood, Traci L. Mach, and John D. Wolken ICES 2007 June 20, 2007 * Published as a Federal Reserve Board Working Paper 2007-10. The views expressed herein are those of the authors. They do not necessarily reflect the opinions of the Federal Reserve Board or its staff.

  2. Reasons for applying a Nonresponse Adjustment (NRADJ) • Biased estimates (both relative and absolute) • Inappropriate variances in the weights • Invalid confidence statements

  3. Nonresponse Adjustment Methods • Traditional Weighting Class • Direct Propensity Scoring • Propensity Stratification • 2003 SSBF Hybrid Method

  4. Talk Overview • Survey overview • NRADJ methods overview • Application using the 2003 SSBF • Results

  5. Survey of Small Business Finances (SSBF) • Survey conducted every five years • Data from the 2003 Survey released in October 2006 • Three previous surveys – 1987, 1993, and 1998

  6. 2003 Overview • Short telephone screening interview to determine main eligibility Screener response rate: 62% • 4,240 completed main interviews Main response rate: 52% • Overall response rate: 32%

  7. Current Analysis • Used only the screener interview • Focuses solely on unit nonresponse • Future study may deal with the main interview

  8. Traditional Weighting Class Adjustment • Widely used • Partitioned into homogenous cells • NRADJ=inverse of cell response rate • Cell counts maintained • Population count maintained

  9. Propensity Weighting • Estimate a propensity score using a probit or a logit model • Propensity scores are used to form the NRADJ cell

  10. Traditional versus Propensity • Traditional Cell Weighting Preserves cell counts Preserves population counts Limited number of variables • Propensity Weighting May not preserve cell counts May not preserve population counts Allows large number of variables

  11. Direct Propensity versus Propensity Stratification • Direct Propensity NRADJ=mean propensity score NRADJ=inverse of the propensity score • Propensity Stratification Stratify sample using propensity scores NRADJ=inverse of cell response rate

  12. 2003 SSBF Hybrid Method • Size class (“super strata”) • Propensity strata: propensity scores • NRADJ=inverse of cell response rate • Cell and population counts maintained within super strata

  13. Implementation • Traditional cell weighting used 98 strata variables for stratification • Propensity Methods estimated a logit model that incorporated most frame variables • Direct Propensity divided the sample into 5 cells and used the inverse of the mean propensity score within each cell • Propensity Stratification divided the sample into 5 cells and used the inverse of the cell response rate • Hybrid method used the inverse of the response rate w/in propensity strata w/in super strata

  14. Super Strata Selection • Size class important to maintain • Size Classes: 0-19 employees 20-49 employees 50-99 employees 100-499 employees • Smallest size class had 25 NRADJ cells and the rest had 5

  15. Results: Hybrid versus Traditional Cell Weighting • Similar to Traditional method • Mixed results within subcategories Different weight variances Different point estimates • But differences are small

  16. Results: Hybrid versus Direct Propensity Method • Small differences in point estimates • Smaller weight variances • Difference in population counts by 7.5%

  17. Results: Hybrid versus Propensity Stratification • Slightly higher weight variances • Slightly different point estimates • Preserves population count but not size class counts

  18. Total Firms and Variance of Screener NRADJ Weight

  19. Variance of the NRADJ Screener weight by Business Type

  20. Conclusion • Similar weight variances and point estimates • Easier implementation • More homogenous NRADJ cells

  21. Contact Information • Lieu.N.Hazelwood@frb.gov • Traci.L.Mach@frb.gov • John.D.Wolken@frb.gov • www.federalreserve.gov/pubs/oss/ oss3/nssbftoc.htm

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