Eurostat Repeated surveys

Presented by Eva Elvers Statistics Sweden

Outline Definition and related concepts Why treat in a separate module? Some typical issues –Frames, sampling, and estimation –Data collection and data processing –Time series issues –Tests, experiments, and evaluation Design issues

A repeated survey A repeated survey is –carried out more than once –mostly/often with a regular frequency. Most surveys in a statistical office are repeated, e.g. STS and SBS.

A few related concepts Some concepts and terms: ‒ Longitudinal survey; longitudinal data ‒ Panel survey; panel, rotation panel ‒ Survey with overlap over time ‒ Coordinated samples; independent samples Why such data and surveys/studies? ‒ Study on unit level ‒ Accuracy reasons

Why a separate Memobust module?  Discuss possible reasons to consider and describe Repeated surveys separately

Why enhance in a separate module Some major reasons: Possibilities to make improvements over time. Possibilities to utilise previous data if a unit is included repeatedly. Issues related to time series breaks. ?

Note Many issues are mentioned here. For most of them there will be more information in other topics and parts of the course (later today or tomorrow). Some issues are considered here only.

Accuracy (and response burden) Normally Measures of change are important. Higher accuracy requested for estimators of change than for estimators of level. Accuracy, in general: ‒ considerable overlap between samples over time ‒ include and handle population changes: births, deaths, splits, change of industry, …

(Accuracy and) response burden Few surveys and few times! Not jump in and out of a survey. Be selected for a survey during a period and then not at all for a period.

Frames and sampling Sample design with overlap Participation over a time period for each business (statistical unit: enterprise, …) Frame construction: up-to-date information, as far as possible Draw the sample Reality is a bit different due to deaths, splits, …

Some issues for frames & sampling 1.How often do you construct a new frame and draw a new sample? 2.Advantages of frequent updates? 3.Disadvantages of frequent updates? 4.Do you feed back information about changes to the Business Register? 5.Do you update the frame? When? 6.Are there risks/disadvantages of updates?

Sampling and estimation (1) Sample, consider e.g. industry and size Changes are due to ‒ Population changes (births, deaths, …) ‒ Variable values change Estimation methods ‒ Changes, organisational ‒ Coverage ‒ Auxiliary information, calibration

Sampling and estimation (2) Point estimation Interval estimation, e.g. confidence intervals Outliers ‒ True value ‒ Highly influential ‒ Bias and variance Learn

Data collection & processing (1) Providing previous values –Assistance to respondent. –May discover previous error. –Previous error may remain.

Data collection & processing (2) Corrections of previous micro-data Possibly effects on macro-data ‒ Size? ‒ Correction of statistics needed? ‒ Revisions are planned

Data collection & processing (3) Using previous values in imputation Model Similarity? ‒ Group average for level ‒ Own value and group change

Time series issues (1) Comparability over time ‒ Definitions ‒ Methodology Reality and user needs change

Time series issues (2) Reasons for breaks, e.g. ‒ New definitions due to new needs ‒ Align with other statistics ‒ Better methodology

Time series issues (3) Methods to overcome breaks ‒ Double period ‒ Planned, study ‒ Model, e.g. when NA change a source

Time series issues (4) Revision of a classification, e.g. a new version of NACE Two major approaches ‒ Micro ‒ Macro Time series, back-casting ‒ Assumption about relationships

Tests and experiments Pilot study ‒ qualitative; ‒ quantitative. Tests and experiments ‒ Embedded experiment ‒ Would … mean an improvement? E.g. contact strategy ‒ Can … be changed without effects on the estimates? E.g. data collection mode

Evaluation For this repeated survey and possibly others Teamwork to summarise and suggest actions for future rounds Quality indicators, e.g. ‒ Accuracy planned and achieved. ‒ Response rates, over time, on item level etc. ‒ Signals in editing and debriefing with staff ‒ Revision sizes

Design issues New repeated survey (groups 1, 4) Frame, sampling, estimation (groups 2, 5) Improvements of repeated surveys (groups 3, 6)

Conclusions Many surveys are repeated Design from the beginning, as repeated Utilise the advantages, with data, … Evaluate and feed back Improve in a controlled way; consider time series, effects