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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

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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

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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

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Scope

• Podes was collected completely in August 2002 :

1. 68,816 villages

2. Including Transmigration Resettlement Units and Remote Ethnic Resettlement

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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

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Type of Data Collected (1)

1. Identification of village2. Population and Labor Force3. Housing and Environment4. Education5. Health, Nutrition, Family Planning6. Socio-culture7. Recreation, Entertainment, Art and Sport

Facilities8. Communication and Information

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Type of Data Collected (2)

09. Transportation10. Land area and Land Use11. Agriculture12-. Agriculture Machineries13. Trade and Industry14. Village Income15. Politic and Security16. Village Officer Information

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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

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Comments on FAO Data Items (1)

Geography :

- The distance from village office to sub-district office

- Pollution (water, land,air, noise)

- Conversion of agriculture land to non agriculture purposes during the last three years

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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

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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

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Thank You Very Much

For Your Kind Attention

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