Transcript Initiates file download

SCOPE OF COLLECTION OF
VILLAGE –LEVEL DATA VIA
2003 AGRICULTURE CENSUS
IN INDONESIA
PRESENTED BY
PIETOJO *
*) DEPUTY FOR DIRECTOR GENERAL
FOR ECONOMIC STATISTICS, BPS-STATISTICS INDONESIA
1
Indonesia’ experience
• BPS-Statistics Indonesia (BPS) always
collect village-level data (PODES=Potensi
Desa) in line with any censuses
• Podes data collection is carried out 3X
within one decade
• Data collection of Podes is important
because some data are not able to be
collected from household = infrastructure
& socio economic condition in village
2
Indonesia’ experience
•
Data from Podes is important need in order to
create appropriate policy in village-level
• The uses of Podes :
1. To identify poor villages for Presidential Aid For
Poor Programme
2. To identify the level of conversion of agriculture
land to non agriculture purpose
3. To provide data used to identify urban & rural
3
Scope
•
Podes was collected completely in
August 2002 :
1. 68,816 villages
2. Including Transmigration Resettlement
Units and Remote Ethnic Resettlement
4
Methodology
• The enumerators conduct interviewing
directly to Village Head or Staff Member of
village Office entrusted to answer
• The questionnaire used basically can be
divided by two parts :
1. core data, which collected in every
census
2. module data, which collected only in the
implementation of a particular census
5
Type of Data Collected (1)
1.
2.
3.
4.
5.
6.
7.
Identification of village
Population and Labor Force
Housing and Environment
Education
Health, Nutrition, Family Planning
Socio-culture
Recreation, Entertainment, Art and Sport
Facilities
8. Communication and Information
6
Type of Data Collected (2)
09. Transportation
10. Land area and Land Use
11. Agriculture
12-. Agriculture Machineries
13. Trade and Industry
14. Village Income
15. Politic and Security
16. Village Officer Information
7
Problems
• Sometimes respondent does not give correct
answer, mostly political rreason
• There is pressure from the Head of District to the
Village Head to give false answers so that the
performance of the village condition looks better
• Respondent is afraid that the answer will be
used to evaluate the development performance
• Data collected in household-level should not be
collected in village-level because it can give
totally different picture that confuses data
consumers
8
Comments on FAO Data Items
(1)
Geography :
- The distance from village office to subdistrict office
- Pollution (water, land,air, noise)
- Conversion of agriculture land to non
agriculture purposes during the last three
years
9
Comments on FAO Data Items
(2)
Socio-economic Conditions
- Existence of agriculture skill training
- Village Officers Information
Community Infrastructure & Services
- Number of agriculture establishment by
type of activity
10
Analysis
• Village –level data is used to identify poor
villages by using 17 variables for urban and 18
variables for rural areas. Each variable is giving
a score. In 2003 there were 22,094 villages are
categorized poor
• Data from village-level data is also used to
compare the level of conversion of agriculture
land to non-agriculture purposes for district level.
Using simple method such as average, standard
deviation, and range, districts are classified into
3 groups = high, medium, and low-level
conversions
11
Thank You Very Much
For Your Kind Attention
12
13