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Internet Surveys & Future Works In Official Statistics

Yeonok Choi

The 4th International Workshop on Internet Survey Methods, 12-13 Sept.Statistical Center, Statistics Korea, Daejeon

Statistical Research Institute, Statistics Korea, Daejeon, Korea

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The Rise of Internet Surveys

The optimum properties of a survey– High response rates– Low costs– Quick response and return– High quality data

F to F interview can not be a predominant method – People are busier– Privacy is highly valued and sensitive

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The Rise of Internet Surveys (cont.)

With the advancement of science and tech-nology– Internet emerged as a data collection option

Needs for innovation of data collection modes in Official Statistics(OS)– Budgetary pressures– Growing difficulty in access to respondents

Internet == good solution candidate

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Expectations from the Workshop

The 1st workshop was held in 2009– To promote Internet surveys(IS)– To discuss latest research on web survey methods – To explore its potential in official statistics

The past three workshops dealt with major issues relating to Internet surveys- E-census experiences, Estimation for Volunteer Panel, Re-

sponse Rate problem- The use of mixed mode data collection, Propensity score

weighting, the statistical use of the administrative data

The focus of this workshop– How to ensure data quality from Internet Surveys

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Expectations from the Workshop

Key Questions

- Does IS mode contribute to the improvement of data quality?

- How to effectively implement Internet surveys in OS to ensure data quality?

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Summary of Sessions

Internet only surveys are rare, especially in OS Mixed mode(MM) design is widely used - It is not evident that sequential design starting with the internet is best  The benefit of sequential MM design lies in cost, speed of response, data quality - rather than response rates - Yet, measurement differences exist between survey modes

[Session 1]Advantages and disadvantages of utilizing IS methods for OS

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Summary of Sessions

Incentives can improve Response Rates for Internet Surveys - Improved response rates do not necessarily indicate better quality survey data, and better quality is difficult to determine - Incentives can have different effects on different groups

Importance of recognizing participant characteristics

[Session 2]Design and implementation issues in web surveys

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Summary of Sessions

Cases in Official Statistics

- Redesigning French Internet Business data collection at INSEE

- Optimization of operations and systems for statistical work – administrative reform in Japanese

Cases in Public Opinion Surveys

- Online surveys can be limited by respondent conditions such as computer skill, online usage, concern etc.

[Session 3]Cases of statistics utilizing Internet survey meth-ods

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Summary of Sessions

Case of Netherlands : focusing on decreasing budgets and increasing accuracy in MM design - MM surveys including IS are cheaper but mode effects are large - How to stabilize statistics in MM surveys including web is an issue

Case of European Social Survey - Using MM design shows measurement differences among modes - However, there in no simple adjustment method for these mode effects

Case Study of Internet surveys: Abu Dhabi

[Session 4] Data Quality issues in web surveys

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Lessons Learned - using IS in OS

1. Does IS mode contribute to the improvement data quality?

IS mode is not so promising in RR- However, RR can vary on the survey content,

disposition of the persons, and process of survey i.g) The survey on Private Education Expenses in Korea: high RR in IS

Potential to improve data quality by appropriate web survey design was found

- There seems no common criterion for measuring the data quality

MM becomes more appropriate for OS as survey circum-stances are changing

– Strength in survey cost, response speed, and access to hard-to-con-tact group

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2. How to effectively implement Internet sur-veys in OS to ensure data quality?

Sequential MM design with the Internet mode as the first step

Analyzing the dispositions of respondents by modeConsidering enumerator and incentive effects in MM Trying to minimize the measurement error differ-

ences

Lessons Learned - using IS in OS

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Review of Internet Surveysin Statistics Korea

Utilizing the internet survey as MM design– Total of 43 Survey – Uses of 26 survey : 16 on establishment, 10 on households– About 48% internet uptake rate in 2010 census Offering convenience to respondents hard to reach

The matter of data quality remains i.g) The duplication of responses among household

members from census

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Our current researches for MM surveys

- MM design for 2015 census including IS question-naire design to increase data quality

- Estimation methods considering response differ-ences by survey mode

Research projects in Statistics Korea

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Future works

Research on questionnaire design in MM design

- Question may differ on paper vs. internet questionnaire- Need to explore method to handle these differences

Research on statistical methodologies for differentmode effects

- Selection bias, nonresponse bias, measurement error etc.- Understanding the respondent propensities by modes

Research for extended adoption of IS to establish-ment surveys

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Thank you and Good bye