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Nonresponse and Measurement Error in Employment Research Gerrit Müller (IAB)

Nonresponse and Measurement Error in Employment Research Gerrit Müller (IAB) joint with: Frauke Kreuter (JPSM – U Maryland), Mark Trappmann (IAB). Research Questions. Do survey respondents recruited with extra effort, provide answers of lower quality?

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Nonresponse and Measurement Error in Employment Research Gerrit Müller (IAB)

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  1. Nonresponse and Measurement Error in Employment Research Gerrit Müller (IAB) joint with: Frauke Kreuter (JPSM – U Maryland), Mark Trappmann (IAB)

  2. Research Questions • Do survey respondents recruited with extra effort, provide answers of lower quality? • Are cooperators more motivated to provide accurate data? • Or, are late respondents hampered by recall deficits? • How does extra effort affect total bias?

  3. Survey Data • Panel Study “Labor Market and Social Security” (PASS) • Dual frame survey (benefit recipients / residential population) • Wave1: 12,000 HH 20,000 P • RR1: 30.5% (within HH: 85%) • Mixed mode survey (sequential CATI -> CAPI)

  4. Record Linkage I • Individual survey data linked with individual administrative data (80% of all Rs agreed; 72% successfully matched) • Administrative records on: employment, earnings, unemployment, labor market programs , • Contact data on HH-level only

  5. Record Linkage II • Administrative data linked with paradata for the gross sample of recipients (from unemployment register) • Contact data on HH-level only • Indicator for Respondents / Nonrespondents on HH-level only ,

  6. Hypotheses about Measurement Error(response process model, Tourangeau ’84) • Unemployment benefit (UBII) • July 2006 • Nov 2006 • at time of interview • Income in month prior to interview • Occupation • Educational degree Relationship between ME and response propensity (number of contact attempts)

  7. Contact Quintiles and Follow-Up Efforts • Transfer CATI to CAPI • CATI NR follow-up of “soft refusals”

  8. Measurement Error (in percent) by Contact Quintiles and Follow-up Efforts

  9. Measurement Error by Contact Quintiles and Follow-up Efforts

  10. 5. NR-ME Bias Decomposition • for Recipient sample only • HH-level variables only (!) • UBII in Jul06 not feasible for bias decomposition • UBII in Nov • UBII at date of interview

  11. “Pick your brains” • ME-Model for UBII in July06 (handout) Puzzle: high ME for the young? HH-interview by target head? • Administrative data not always „Gold Standard“ (error-free) Assumption: ME in register data unrelated to ME in survey reports and response propensity

  12. “Pick your brains” • Decomposition findings statistic-specific • Extend analyses to P-level variables (e.g. employment, income) • Problem: unknown on individual level • How to go ahead?

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