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Re-weighting to reduce unit non-response bias in household wealth surveys

Re-weighting to reduce unit non-response bias in household wealth surveys. Q2010 Conference, Helsinki, May 2010 S. Pérez-Duarte & C. Sanchez-Muñoz & V-M Törmälehto European Central Bank. The views expressed are our own and do not necessarily reflect those of the ECB or the Eurosystem.

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Re-weighting to reduce unit non-response bias in household wealth surveys

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  1. Re-weighting to reduce unit non-response bias in household wealth surveys Q2010 Conference, Helsinki, May 2010 S. Pérez-Duarte & C. Sanchez-Muñoz & V-M Törmälehto European Central Bank The views expressed are our own and do not necessarily reflect those of the ECB or the Eurosystem.

  2. Outline • Background: Euro area Household Finance and Consumption Survey (HFCS) • Unit non-response levels in wealth surveys and other household surveys • Case study with the Finnish Wealth Survey 2004: non-response bias and alternative re-weighting scenarios

  3. Background: Euro area Household Finance and Consumption Survey • Motivation for this paper: unit non-response in the forthcoming euro area Household Finance and Consumption Survey (HFCS) • The HFCS is a decentralized effort. Each country finances and conducts its own wealth survey, in most cases through the National Central Bank alone, occasionally with the support of the National Statistical Institute. • Eight countries are adapting an existing survey, eight are launching a new survey. • Data collected around 2009/2010, total sample size should be around 52 000 households

  4. Response rates in existing wealth surveys

  5. Response rates in existing wealth surveys and other household surveys

  6. Findings • Among wealth surveys, there is substantial variationbetween countries in response rates 2. Wealth surveys have a certain tendency to register higher unit non-response rates compared to other household surveys - Also substantial country variation in this respect

  7. Findings Potential factors explaining these findings: • cultural and social differences • sensitivity of the topic • respondent burden: length, level of effort required, survey exhaustiveness (e.g. exclusion of financial wealth in Austria) • who collects the data (NSIs seem to achieve higher response rates) • sample design and contact strategies, e.g. stratification to over-sample wealthier households (who generally have lower than average response rates)

  8. Re-weighting in the euro area HFCS Non-response adjustments in the euro area survey envisaged to follow two-step re-weighting procedure: (1) Adjustment of the design weights for non-response using sample level information • What is known about non-respondents in the euro area HFCS? • centrally: contact attempt information, interviewer observations (paradata) • at country level : frame variables and possibly panel data, micro-geographical information, record linked data from registers (2) Calibration to externalpopulation information • Calibration to population levels seems to have a set of “euro area” variables: age and gender, region, household size

  9. Non-response in the Finnish household wealth survey 2004 • Case study with the Finnish Wealth Survey 2004: 1. What explains non-response and is there bias due to unit non-response? 2. Does re-weighting reduce non-response bias? 3. Would the amount of information used for calibration matter in a cross-country context? Abundance of register variables available both for respondents and non-respondents (e.g. income, debt, taxable wealth)

  10. A. Modeling non-response: Distribution of propensity scores in the Finnish Wealth Survey

  11. B. Three re-weighting scenarios

  12. Relative non-response bias of mean debt per household by age groups

  13. Relative non-response bias of mean debt per household by age groups

  14. Conclusions From the case study: • In contrast with many other wealth surveys, unit non-response did not increase with wealth in this survey • Non-response bias in the sample means of income, debt and taxable wealth was in general smaller than expected • Standard weight adjustment procedure (naïve adjustment at sample level and then calibration to external information) did not do much to reduce bias observed in certain age categories • Different calibration approaches using different levels of auxiliary information did not bring forward sizable differences  Consequently, different country approaches as to the number of variables used for calibration may not have substantial effects on cross-country comparability

  15. Conclusions More in general: • Good interviewing practices can positively influence participation  However, availability of external micro-level information on wealth would be essential for - supporting sample design and ex-post adjustments - assessing relevance and precision of survey data.

  16. Thank you for your attention!

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