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Practical exercises on analysis methods of TLS census micro data using REDATAM

Training Course on Analysis and Dissemination of Population and Housing Census Data with Gender Concern 3 - 7 October 2011, Dili, Timor-Leste. Practical exercises on analysis methods of TLS census micro data using REDATAM. H. Furuta Lecturer/Statistician UNSIAP. Contents. What is REDATAM

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Practical exercises on analysis methods of TLS census micro data using REDATAM

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  1. Training Course on Analysis and Dissemination of Population and Housing Census Data with Gender Concern 3 - 7 October 2011, Dili, Timor-Leste Practical exercises on analysis methods of TLS census micro data using REDATAM H. Furuta Lecturer/Statistician UNSIAP

  2. Contents • What is REDATAM • Getting started with Process R+SP • Data dictionary and data structure • Basic commands • Exercises

  3. What is REDATAM? • REtrieval of DATa for small Areas by Microcomputer • Developed by CELADE-Population Division of ECLAC (Economic Commission for Latin America and the Caribbean ) • Free software for tabulation, analysis and dissemination of census data • Use of the software has expanded

  4. Process of census and role of REDATAM Planning Data collection Data capture Data check Editing Coding Tabulation Analysis Dissemination Raw data Micro data Error-free Macro data Aggregated data DevInfo CensusInfo REDATAM Household / person level info.

  5. Typical usage of REDATAM • Type A: Internal use within NSO • Type B: Dissemination for the public

  6. Type A: Internal use within NSO Main purpose is tabulation and analysis conducted by NSO staff Accessible even to household/person level data Programmable using command sets Able to develop new indicators Command sets applicable for other data sets, such as different regions, different population groups Such as, children not attending school, Households with female household heads,

  7. Type B: Dissemination for the public Purpose is dissemination on the web or CD for the public, especially at regional and municipality level. Household/person’s information is protected. Encrypted database Access is controlled only higher level of area, such as province, region, village. Ready-made aggregated data is available like CensusInfo/DevInfo. Customized tables and creation of new indicators are also possible

  8. Getting Started with REDATAM • Run ‘R+SP Process’ • Change default language (Spanish) to English (only once at the first time) • Click on REDATAM icon on top left • Select ‘Preference’ → ‘General’ → ‘Select language’

  9. Getting Started with REDATAM (cont.) • Specify the directory in which your outputs will be stored: • Create a folder “Redatam” in “D” driver. • Open REDATAM data dictionary • Serve as a bridge between user and data files • File → Open dictionary → Select TLS census data dictionary

  10. R+SP Process Module Click new command set

  11. Data dictionary and data structure • Hierarchical level (entity) • For example • Whole country • District • … • EA (Enumeration area) • Household • Person

  12. Data dictionary and data structure • List of all variables for each entity • HOUSEHOLD, for example; • Ownership • Roof • Drinking water • PERSON, for example; • Sex, age, relationship, marital status • School attendance, highest education • Main economic activity

  13. Data dictionary and data structure • Codes (values or categories) for each variable, for example; • Sex • 1: Male • 2: Female • Age • Integer from 00 to 98

  14. Basic Three Commandsof REDATAM Process R+SP • RUNDEF • DEFINE (if necessary) • TABLE • Comments /* …… */

  15. RUNDEF command • RUNDEF jobname[FOR ….] • FOR allows definition of logical filter to be used in all processed

  16. TABLE command • TABLE tabname AS • FREQUENCY • CROSSTABS • AVERAGE • AREALIST OF variable(s) [BY variable] [FOR … ] [AREABREAK … ]

  17. DEFINE command • Create new variable • DEFINE new_varnameAS • COUNT • RECORD • SUM • Arithmetic/logical expression [FOR …] [TYPE INTEGER/REAL] [RANGE …] [DECIMALS …]

  18. Exercise!!!

  19. Part 1: Basics of commands and functions, and how to make indicators 1. Population by single-year age and sex –RUNDEF, TABLE, CROSSTABS 2. Sex ratio by district –DEFINE, COUNT, AREALIST 3. Dependency ratio by district –RECORD, SWITCH 4. Number of households by sex and age group of household head 5. Number of female household heads by marital status - FOR 6. Proportion of women with age 15-19 that have had children by district While conducting following hands-on exercises using TLS 2010 CHP dataset, with support of Mr. Silvino Lopes, participants will learn how to use commands and functions of REDATAM Process P+SP as well as how to develop indicators used for analysis.

  20. Past and future of population of Japan

  21. Population Pyramids of Japan • Towards ‘super’ aged society • Composition ratio of aged65 and more • 7.1%: aging society • 14.5%: aged society • 2005 21.0% • Only 25 years from 7% to 14% Baby boomers born during 1947-49 Source:’Population Census’, MIC and ‘Future Projection of Population’, MHLW

  22. Part 2: Employment 1. Define economically active (EA) person 2. Labour force participation rate (LFPR) by sex and 5-year age group 3. Comparison of LFPR by sex and age group between 2010 and 2004 CHP 4. Number of unemployed and unemployment rate by sex, age group and district 5. Occupation of employed person by sex 6. Industry of employed person by sex 7. Number of (unpaid) family workers by sex and age group International definition of “economically active” will be applied for TLS census data for analysis of the level of labour force participation rate and gender disparity.

  23. Male LFPR by age Labour force participation rate by age (Male) (%) 100 1970 80 Almost 100% 1990 60 Old-age pension 40 University advancement 2005 20 0 15～19 25～29 35～39 45～49 55～59 65～ 20～24 30～34 40～44 50～54 60～64 Source:’Labour Force Survey’, MIC, Japan

  24. Labour force participation rate by age (Female) (%) 80 2000 2005 60 1990 40 1980 1970 20 0 25～29 35～39 45～49 55～59 15～19 65～ 20～24 30～34 40～44 50～54 60～64 Female LFPR by age: M-shaped curve • The bottom goes up towards flat curve. • Bottom rise • Peak age shift from 20-24 to 25-29 Source:’Labour Force Survey’, MIC, Japan

  25. Unemployment Rate of Japan

  26. Ternary Diagram on Industrial Composition • Tree sector hypothesisby Colin Clark • the main focus of an economy's activity shifts from the primary, through the secondary and finally to the tertiary sector. Source:’Statistical Yearbook of Japan’, MIC

  27. Part 3: Education 1. School attendance rate of children aged 5-14 by sex, single-year age by urban/rural 2. Percentage of children with age of primary education not attending school by district 3. Education level by sex and age group 4. Relationship between education level and housing/household amenities Net enrolment ratios of primary school in TLS 2010 CHP don’t show much difference between male(66.6%) and female(68.2%), while big difference between urban(80.2%) and rural(67.4%).

  28. Part 4: Disability ? Disability statistics is an emerging issue which countries have to focus on.

  29. Part 4: Disability 1. International comparison of prevalence rate of persons with disability (PWD) 2. Number of PWD with any form of disability among walking, seeing, hearing and intellectual/mental) by sex and age group 3. Number of PWD with any form of disability by level of difficulty 4. Define household with PWD in the household 5. Proportion of household with PWD by district 6. School attendance of PWD children by sex 7. Education level of PWD by sex 8. Employment of PWD by sex

  30. Part 5: Housing/household haracteristics 1. Define number of UBN among selected facilities, such as light, cooking fuel, safe water, toilet, etc. 2. Frequency of households by number of UBN by urban/rural 3. Define threshold between poor and non-poor in the context of UBN 4. Number of households with NBS more than the threshold by district Above is a trial to distinguish between poor and non-poor in line with UBN (unmet basic need).

  31. References • R+SP 2 basic process ENG.pdf • As a Tool for the creation of indicators • R+SP 3 process indicators ENG.pdf • Samples for the creation of indicators • Example of Command Sets.pdf • Practical exercises on analysis methods of census micro data using REDATAM online of Cambodia Census 2008 and 1998 THANKS

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