1. 0/40

2. 1/40 Contents Outline of the Korean Census 1 Environment of Census-taking 2 Internet Survey 3 e-Census System 4 Data Capture and Editing 5

3. 2/40 Outline of the Korean Census 1 1  Historical Background ◈ The Population Census has been conducted on every five years since 1925 and the Housing Census since 1960 - 2010 Population Census : 18th Census - 2010 Housing Census : 10th Census  Legal Basis ◈ Statistics Law and its Enforcement Decree - Designated statistics : Population Census No. 10101 Housing Census No. 10102 ◈ Population and Housing Census regulations

4. 3/40  Census Day : As of 0:00, November. 1  Census-taking Period ◈ Preparatory work : October 29-31 ◈ Enumeration : November 1-15  Coverage - All Koreans and foreigners, - and their housing units - within the scope of the administrative jurisdiction of the Korea - as of the Census day

5. 4/40  Census questions ( ) : No. of questions which were made by each Province  Enumeration Methods ◈ Face to face interviews ◈ Self-enumeration ◈ Internet Survey (introduced on 2005 census) ’80’85’90’95’00’05 Total453045285044(3) Short form263033172021 Long Form19-12113023(3)

6. 5/40  Budget ◈ The cost of Census is over the total budget of KNSO  Release of the Results (based on 2005) ◈ Preliminary results : December 2005 ◈ Final results : May 2006 ~ December 2006 199520002005 Total Budget of KNSO (A)91.4148.2238.8 Cost of Census (B)53.983.4129.0 B/A (%)58%56%54%

7. 6/40  The System of the Census-Taking (based on 2005) National Statistical Office Metropolitan city, Province (16) City, County (250) Eup, Myeon, Dong (3,573) Supervisor (8,000) Enumerator (90,000) Census Data Users’ and Experts’ Committee Technical Advisory Committee 4

8. 7/40 Environment of Census-taking 2 2   Social Environment ◈ Growing awareness of privacy ◈ Increasing unwillingness to cooperate with government among people  Financial  Financial Environment ◈ Burden of requiring a huge budget and large-scale human resources 199520002005 The ratio of omission1.4%2.1%1.9% 1995200020052010 The cost of Census (billion won) 53.983.4129.0 210.7 (estimated)

9. 8/40   Statistical Environment ◈ More likely to use the administrative Sources - Computerization of administrative records : Building registers, foreigner registration, etc. ◈ Increasing number of daytime absent households ◈ Difficult to collect data because of the increase of ageing people and one-person household ◈ Possible to use “Internet” for the-data collection - Internet access rate : 79.8% (2007.12) 199520002005 The ratio of over 655.9%7.3%9.3%

10. 9/40 Internet Survey of 2005 Census  Objectives ◈ Decrease in coverage error - Provide a way for hard-to-enumerate households ◈ Low-cost data collection method ◈ Introduced on the 2005 Census for the first time :  Periods : 2005.10.29~11.12 :  Participation : 141,000 HHs (0.9% of total HHs) Internet Survey 3 3

11. 10/40  Characteristics of Respondents Internet Respondents Total Population Age 30~3940.5%17.5% 20~2923.9%15.6% Education College and over 51.6%34.3% High School21.4%41.2% Type of Housing Apartment66.7%52.7% Detached dwelling 14.8%32.2%

12. 11/40 Input of questionnaire Input of questionnaire Ordinary citizens Ordinary citizens Credit rating agency Credit rating agency Confirmation of real name Internet Data encryption Internet application Confirmation of real name and address Confirmation of real name and address Input period Input of questionnaire Confirmation of result Confirmation of result Procedure of proceedings SMS, Mail  Process of Internet survey

13. 12/40 ◈ Internet Questionnaire Form

14. 13/40  Lessons from Internet Survey ◈ Advantages - Provide a way for hard-to-enumerate households et coverage error : Post-enumeration net coverage error : ※ 1.6% (2000 census) ※ 1.6% (2000 census)  0.9% (2005 census) - Cost reduction in survey management and enumerator’s employment

15. 14/40 ◈ Advantages - Improved data quality: interactive user guidance, automatic filtering of irrelevant survey items - Correspondence rates in the post-enumeration survey InterviewInternet survey Age98.7%99.0% Relationship to the Head of Households 99.3%99.1% Marital Status98.9%99.9%

16. 15/40 ◈ Challenges and problems for future census - Automatic address matching rate: 62.1%  37.9% respondents waited to receive the number of census tract - Difficulty in estimating appropriate system capacity Difficulty in estimating peak time user frequencies

17. 16/40 ◈ Increase the participation ratio of Internet survey - 2005 (0.9%) → 2010 (20~30%) ◈ Introduce Internet survey participation number (ISPN) - ISPN(12digits) : □□□ □□□ □□ □□ □□ ◈ Intensify publicity campaign for Internet survey ◈ Improve the Internet survey system ◈ Provide incentive to the Internet survey respondents ※ Internet survey participation rates (1 st pre-test in 2007) : 13.3% Plan for the Internet Survey of 2010 Census

18. 17/40  Objectives ◈ Economic census with low cost, high efficiency ◈ Improvement of data quality - Provide a way for hard-to-enumerate households - Decrease in coverage error ◈ Shortening data release time e-Census System 4 4

19. 18/40 Analysis / Publication Estimate No.of Enumerators Field Survey Management Census Tract Management Recruit Management Education Management Web Based Data Input Data Editing/Tabulation Supply Management Payroll Management Compiling a List of Households Compiling a List of Households Internet Survey, Housing DB  Flow Chart of the e-Census System Cyber Education Preliminary Count of Census

20. 19/40  Function of e-Census System ◈ Survey Management - Census tract management - Supply management - Education management, Cyber education - Short messaging system - Survey result management

21. 20/40 ◈ Enumerator Management - Recruitment - Assignment of census tracts to enumerators - Payroll - Information of local officers (Name, Phone numbers, e-mail, etc) ◈ Internet Survey ◈ Web Based Data Input ◈ Data Editing and Tabulation ⇒ The e-Census system will be used in 2010 census with a little changes

22. 21/40 Data Capture and Editing 5 5   Punch card system : 1935~1970  Key-board data entry : 1975~1985  Optical marking reading : 1990~1995  Key-board data entry : 2000  Web-based data input system / ICR : 2005

23. 22/40  Web-based data input system ◈ Data capture for short form and long form ◈ Decentralized to 256 cities/counties  ICR system ◈ For special enumeration areas such as military camps  Internet system ◈ For households participated on Internet survey Data Capture System of 2005 Census 5-1

24. 23/40 Web-Based Data Input System 5-2  Principle of 2005 data capture ◈ Accurate and rapid data capture using e-Census system ◈ e-Census : Unified system combined input, editing, tabulation, and administration functions  Data input period ◈ 2005. 11. 28. ~ 12. 22. (19 days)  No. of persons for data input and editing ◈ 13,372 persons (including 614 managers)

25. 24/40  Data entry form

26. 25/40  Process of data input and editing ◈ Data input and editing through on-line system ◈ Data input and editing by an enumeration district. - Able to generate error messages following data input by enumeration districts ◈ Integrated editing of Internet survey and key-board entry data ◈ Input error rates : 0.19%

27. 26/40 ICR System 5.3  Data capture for special EDs ◈ No. of questionnaires : 130 thousand  ICR system ◈ 3 scanners, 1 storage, 12 servers, 40 pcs for correction of errors and editing ◈ 1 scanner per 2 persons : 2005.11.21~12.2 (10 days)  Scanning periods : 2005.11.21~12.2 (10 days)

28. 27/40  ICR system Server PC for recognition of images Scanner PC for scanner Correction of recognition errors

29. 28/40 Tota l0123456789 99.6899.8799.6699.4899.7299.7899.4299.7199.5499.7899.91  Recognition rates of numbers (%)  Recognition rates of characters : 76.73% ◈ Recognition rates lower than pre-test’s rates (86~90%) - Lower rates were a results of using unsuitable pen

30. 29/40 Data Capture for Non-response HHs 5.4  No. of non-response HHs (2005) : 75,000 HHs ◈ 0.47% of total Households (HHs) ◈ Collect basic information of HHs - EX. : No. of HH members, sex, age, type of housing  Imputation for non-response HHs ◈ Hierarchical Hot-deck Method ◈ Probability Hot-deck Method ◈ Deductive methods

31. 30/40  Imputation for missing data ◈ Hierarchical Hot-deck Method - Used data mining technique to make Hot-deck tables - Ex. : Hot-deck table for total floor space * Column of table : No. of households * Low of table : Type of housing, No. of room ◈ Deductive methods - Ex. : Education of children under 5 → No schooling

32. 31/40 Auto-coding for Industry/Occupation 5.5  Process of auto-coding ◈ Coding according to the code from industrial census ◈ Coding by matching with coding case dictionary ◈ Selection of code by coders among 3 suggested codes by auto-coding system   Periods of auto-coding (2005) ◈ Coding for industry : 2,030,000 cases - Auto coding (63.0%) : 2005.12.28~12.30 - Selection of codes (36.7%) : 2006.1.4~2.10 - Unable to code (0.3%)