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
1
Contents
• What is REDATAM
• Getting started with Process R+SP
• Data dictionary and data structure
• Basic commands
• Exercises
2
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
3
Process of census and
role of REDATAM
Planning
Data collection
Data capture
Data check
Editing
Coding
Raw data
Tabulation
Analysis
Micro data
Error-free
Household / person level info.
Dissemination
Macro data
Aggregated data
DevInfo
CensusInfo
REDATAM
4
Typical usage of REDATAM
• Type A: Internal use within NSO
• Type B: Dissemination for the public
5
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,
6
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
7
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’
8
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
9
R+SP Process Module
Click new command set
10
Data dictionary and data structure
• Hierarchical level (entity)
• For example
– Whole country
– District
–…
– EA (Enumeration area)
– Household
– Person
11
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
12
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
13
Basic Three Commands
of REDATAM Process R+SP
• RUNDEF
• DEFINE (if necessary)
• TABLE
• Comments
/* …… */
14
RUNDEF command
• RUNDEF jobname
[FOR ….]
• FOR allows definition of logical filter
to be used in all processed
15
TABLE command
• TABLE tabname
AS
– FREQUENCY
– CROSSTABS
– AVERAGE
– AREALIST
OF variable(s) [BY variable]
[FOR … ]
[AREABREAK … ]
16
DEFINE command
• Create new variable
• DEFINE new_varname
AS
– COUNT
– RECORD
– SUM
– Arithmetic/logical expression
[FOR …]
[TYPE INTEGER/REAL]
[RANGE …]
[DECIMALS …]
17
Exercise!!!
18
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.
19
Past and future of population of Japan
Long-term trends and future projections of population, Japan
14000
(Ten housand)
Results of
Population
Censuses
12000
10000
Future
Projections
8000
6000
Edo P eriod
1945 End of
World War Ⅱ
4000
2000
0
1600
1868 Meiji Restoration
1700
1800
1900
2000
2100
Source: 1) Edo period: based on Mr. Kito's estimation
2) From 1872 to 2005: 'Historical Statistics of Japan', MIC
3) From 2010 to 2050: 'Future Projection of Population', MHLW
Note: During Edo period, Japan closed itself off from the outside world.
In 1968, Japan opened itself again.
20
Population
Pyramids of Japan
Towards ‘super’ aged society
Composition ratio of aged
65 and more
1970 7.1%: aging society
1975
85歳～
80～84
75～79
70～74
65～69
60～64
55～59
50～54
45～49
40～44
35～39
30～34
25～29
20～24
15～19
10～14
5～ 9
0～ 4
M ale
-5 -4 -3 -2 -1
1995 14.5%: aged society
1990
2005 21.0%
Fem ale
0
1
2
3
4
5 -5 -4 -3 -2 -1
(%)
2005
Only 25 years from 7% to 14%
Baby boomers born
during 1947-49
Source:’Population Census’, MIC and
‘Future Projection of Population’, MHLW
0
1
2
3
4
5
2
3
4
5
2020
95歳～
90～94
85～89
80～84
75～79
70～74
65～69
60～64
55～59
50～54
45～49
40～44
35～39
30～34
25～29
20～24
15～19
10～14
5～ 9
0～ 4
-5 -4 -3 -2 -1
0
1
2
3
4
5 -5 -4 -3 -2 -1
0
1
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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.
22
Male LFPR by age
Labour force participation rate by age (Male)
100 (%)
1970
80
Almost 100%
1990
60
40
Old-age
pension
University
advancement
2005
20
0
15～19
25～29
20～24
35～39
30～34
45～49
40～44
55～59
50～54
65～
60～64
Source:’Labour Force Survey’, MIC, Japan
23
Female LFPR by age: M-shaped curve
 The bottom goes up towards flat curve.
Labour force participation rate by age (Female)
80
(%)
2000
2005
60
1990
40
1970
1980
1) Bottom rise
2) Peak age shift from 20-24 to 25-29
20
0
25～29
15～19
20～24
35～39
30～34
45～49
40～44
Source:’Labour Force Survey’, MIC, Japan
55～59
50～54
65～
60～64
24
Unemployment Rate of Japan
Unemployment Rate by Sex and Age (2005)
14
(%)
12
M ale
10
8
6
Fem ale
4
2
0
15-19
25-29
20-24
35-39
30-34
45-49
40-44
55-59
50-54
65+
60-64
Source:'Labour Force Survey',M IC
25
Ternary Diagram on Industrial Composition
Composition of employed person by industorial sector
 Tree sector
hypothesis
by Colin Clark
- the main focus of
an economy's
activity shifts from
the primary,
through the
secondary and
finally to the
tertiary sector.
100%
0
80
20
S econdary
Tertiary industry
60
40
40
60
Japan 1950～2000
G erm any
P oland
B razil
20
0
100%
Indonesia
C hina
NZ
Egypt
P hilippines
Japan
UK
US
100%
80
60
40
20
0
P rim ary industry
Source:’Statistical Yearbook of Japan’,
MIC
Note: Red line shows japan's trends from 1950 to 2000.
Blue dots show the latest position of each country.
26
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%).
27
Part 4: Disability
Disability statistics is an emerging issue which countries have to
focus on.
28
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
29
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).
30
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
31