Redesign Dutch LFS 2021 Sample of persons with a panel of households Martijn Souren Reykjavik, April 2018

6 domains 1. Sampling 2. Collection 3. Sub-sampling 4. Questionnaire 5. Processing 6. Output

1. Sampling

Sampling Person sampling: No proxy Shorter questionnaire -> mobile devices -> higher response and panel reqruitement rates -> Future proof More costs per response:

Sampling Make it as efficiënt as possible: Stratification targeted at meaurement of unemployment for 15- tot 75-years old: “Maximizing” design effect

Sampling Age = 15-24 25-44 45-64 65+ Reg. Unempl = 0 West = 1 3/8 1/4 1/8 West = 0 5/8 Reg. Unempl= 1 7/8 1

Sampling

1. Sampling 2. Collection 6. Output

Output Simulating person sample out of current household sample Applying the design effect Response wave 1 based on experiment Using same budget Assumptions on panel response -> Appr. 10 percent increase in SE MUR

6 stappen 1. Sampling 2. Collection 3. Sub-sampling 6. Output

Subsampling Type of variable Waves Q: Quarterly All H: Household One Y: Yearly M: Ad-hoc module T: Third party module L: Longitudinal 2-5

Subsampling Q Q,L From P1: Q: Quarterly From P2: Q: Quarterly, partly dependent int. L: Longitudinal Only P2 Y: Yearly M: Ad-hoc Only P3 T: Third Party Only P5 H: Household

Subsampling Q Q,L From P1: Q: Quarterly From P2: Q: Quarterly, partly dependent int. L: Longitudinal Only P2 Y: Yearly M: Ad-hoc H: Household Only P3 T: Third Party H: Household

Subsampling Q Q,L,H Q,L,h From P1: Q: Quarterly From P2: Q: Quarterly, partly dependent int. L: Longitudinal H: Household Q,L,h Only P2 Y: Yearly M: Ad-hoc Only P3 T: Third Party

1. Sampling 2. Collection 3. Sub-sampling 6. Output

Output Extending Structural Time series with household data Important: first wave estimate is the benchmark! Household data does not affect level of estimates but improves precision -> Appr. 10 percent decrease in SE MUR

Output Extending Structural Time series to more variables: - STAPRO/TEMP - Potential additional labour force - Duration of unemployment

1. Sampling 2. Collection 3. Subsampling 4. Questionnaire 5. Processing 6. Output

Questionnaire As short and respondent-friendly as possible for other Household members E.g.: Instead of model questionnaire: Does partner have a paid job? Is partner self-employed If no: did partner look for a job Could partner start working within 2 weeks.

Questionnaire and output For model-based estimates: Level is based on proxy-free person sample interviews For household/yearly variables a more general labour market position suffices

Conclusion Questions? First wave minimizes bias Panel maximizes precision Questions?