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

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Practical exercises on Practical exercises on analysis methods of analysis methods of

TLS census micro data TLS census micro data using REDATAMusing REDATAM

H. FurutaH. FurutaLecturer/StatisticianLecturer/Statistician

UNSIAPUNSIAP

Training Course on Analysis and Dissemination of Population and Housing Census Data with Gender Concern

3 - 7 October 2011, Dili, Timor-Leste

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

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What is REDATAM?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

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Process of census and Process of census and role of REDATAMrole of REDATAM

Planning Data collectionData capture

Data checkEditingCoding

TabulationAnalysis

Dissemination

Raw dataMicro dataError-free

Macro dataAggregated data

Household / person level info.

DevInfoCensusInfo

REDATAM

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Typical usage of REDATAMTypical usage of REDATAM

• Type A: Internal use within NSO

• Type B: Dissemination for the public

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Type A: Internal use within NSOType 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,

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Type B: Dissemination for the publicType 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

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Getting Started with REDATAMGetting 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’

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Getting Started with REDATAM Getting Started with REDATAM (cont.)(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

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R+SP Process ModuleR+SP Process ModuleClick new command set

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Data dictionary and data structureData dictionary and data structure

• Hierarchical level (entity)• For example

– Whole country– District– …– EA (Enumeration area)– Household– Person

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• 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

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• Codes (values or categories) for each variable, for example;

• Sex– 1: Male– 2: Female

• Age– Integer from 00 to 98

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Basic Three CommandsBasic Three Commandsof REDATAM Process R+SPof REDATAM Process R+SP

• RUNDEF• DEFINE (if necessary)• TABLE

• Comments/* …… */

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RUNDEF commandRUNDEF command

• RUNDEF jobname[FOR ….]

• FOR allows definition of logical filter to be used in all processed

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TABLE commandTABLE command

• TABLE tabname AS – FREQUENCY – CROSSTABS – AVERAGE – AREALISTOF variable(s) [BY variable][FOR … ][AREABREAK … ]

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DEFINE commandDEFINE command

• Create new variable• DEFINE new_varname

AS – COUNT– RECORD– SUM– Arithmetic/logical expression[FOR …][TYPE INTEGER/REAL][RANGE …][DECIMALS …]

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Exercise!!!Exercise!!!

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Part 1: Basics of commands and Part 1: Basics of commands and functions, and how to make indicatorsfunctions, and how to make indicators

1. Population by single-year age and sex – RUNDEF, TABLE, CROSSTABS

2. Sex ratio by district – DEFINE, COUNT, AREALIST3. Dependency ratio by district – RECORD, SWITCH4. Number of households by sex and age group of

household head5. Number of female household heads by marital

status - FOR6. 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.

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Past and future of population of Past and future of population of JapanJapan

Long-term trends and future projections of population, Japan

Source: 1) Edo peri od: based on Mr. Ki to' s est i mati on2) From 1872 to 2005: ' Hi stori cal Stat i st i cs of J apan' , MI C3) From 2010 to 2050: ' Future Proj ect i on of Popul at i on' , MHLWNote: Duri ng Edo peri od, J apan cl osed i tsel f off f rom the outsi de worl d.I n 1968, J apan opened i tsel f agai n.

0

2000

4000

6000

8000

10000

12000

14000

1600 1700 1800 1900 2000 2100

(Ten housand)

Edo Period

FutureProj ect i ons

Resul ts ofPopul at i onCensuses

1945 End ofWorl d War Ⅱ

1868 Mei j i Restorat i on

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Population Population Pyramids of Japan Pyramids of Japan

1975 1990

2005 2020

-5 -4 -3 -2 -1 0 1 2 3 4 5

0 4～ 5 9～

10 14～ 15 19～ 20 24～ 25 29～ 30 34～ 35 39～ 40 44～ 45 49～ 50 54～ 55 59～ 60 64～ 65 69～ 70 74～ 75 79～ 80 84～

85歳～Male Female

(%)-5 -4 -3 -2 -1 0 1 2 3 4 5

-5 -4 -3 -2 -1 0 1 2 3 4 5

0 4～ 5 9～

10 14～ 15 19～ 20 24～ 25 29～ 30 34～ 35 39～ 40 44～ 45 49～ 50 54～ 55 59～ 60 64～ 65 69～ 70 74～ 75 79～ 80 84～ 85 89～ 90 94～

95歳～

-5 -4 -3 -2 -1 0 1 2 3 4 5

Towards ‘super’ aged society

Composition ratio of aged65 and more

1970 7.1%: aging society

1995 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

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Part 2: EmploymentPart 2: Employment1. Define economically active (EA) person2. Labour force participation rate (LFPR) by sex and

5-year age group3. Comparison of LFPR by sex and age group

between 2010 and 2004 CHP4. Number of unemployed and unemployment rate

by sex, age group and district5. Occupation of employed person by sex6. Industry of employed person by sex7. 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.

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Male LFPR by ageMale LFPR by age

Labour force participation rate by age (Male)

0

20

40

60

80

100

15～ 1920～ 24

25～ 2930～ 34

35～ 3940～ 44

45～ 4950～ 54

55～ 5960～ 64

65～

(%)1970

1990

2005

Almost 100%

Source:’Labour Force Survey’, MIC, Japan

Old-agepensionUniversity

advancement

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Female LFPR by age: M-shaped curveFemale LFPR by age: M-shaped curve The bottom goes up towards flat curve.

Labour force participation rate by age (Female)

0

20

40

60

80

15～ 1920～ 24

25～ 2930～ 34

35～ 3940～ 44

45～ 4950～ 54

55～ 5960～ 64

65～

(%)

1970 1980

1990

2000 2005

Source:’Labour Force Survey’, MIC, Japan

1) Bottom rise2) Peak age shift from 20-24 to 25-29

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Unemployment Rate of JapanUnemployment Rate of Japan

Unemployment Rate by Sex and Age (2005)

Source: 'Labour Force Survey', MIC

0

2

4

6

8

10

12

14

15-1920-24

25-2930-34

35-3940-44

45-4950-54

55-5960-64

65+

(%)

Male

Female

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Ternary Diagram on Industrial CompositionTernary 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.

Composition of employed person by industorial sector

Note: Red l i ne shows j apan' s trends f rom 1950 to 2000.Bl ue dots show the l atest posi t i on of each country.

020406080100%0

20

40

60

80

100% 0

20

40

60

100%

J apan

PhilippinesUS

Brazil UK

GermanyPoland

Egypt

NZ

IndonesiaChina

Primary industry

Secondary Tertiary industry

J apan 1950 2000～

Source:’Statistical Yearbook of Japan’, MIC

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Part 3: EducationPart 3: Education1.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 group4.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%).

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Part 4: DisabilityPart 4: Disability

Disability statistics is an emerging issue which countries have to focus on.

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Part 4: DisabilityPart 4: Disability1. 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 household5. Proportion of household with PWD by district6. School attendance of PWD children by sex7. Education level of PWD by sex8. Employment of PWD by sex

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Part 5: Housing/household haracteristicsPart 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).

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ReferencesReferences• 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

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

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