1 / 16

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.

blake
Download Presentation

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

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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!

More Related