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Household Socio-Economic Survey 2008

Indonesia, 2008
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Reference ID
IDN_2008_SUSETI-BASELINE_v01_M
Producer(s)
Survey Meter
Metadata
DDI/XML JSON
Created on
Feb 19, 2014
Last modified
Mar 29, 2019
Page views
39941
Downloads
17010
  • Study Description
  • Data Description
  • Downloads
  • Related Publications
  • Identification
  • Version
  • Scope
  • Coverage
  • Producers and sponsors
  • Sampling
  • Data Collection
  • Access policy
  • Disclaimer and copyrights
  • Metadata production

Identification

Survey ID Number
IDN_2008_SUSETI-BASELINE_v01_M
Title
Household Socio-Economic Survey 2008
Subtitle
Baseline
Translated Title
Survei Sosial Ekonomi Rumah Tangga, Baseline 2008
Country
Name Country code
Indonesia IDN
Study type
Living Standards Measurement Study [hh/lsms]
Series Information
This research project is made up of two stages. The first stage that will be conducted earlier is an end-line survey regarding households expenditure toward the random household samples in the same area as in the second stage. This survay will inquire about household consumption and various characteristics as well as household participations in social activities.

End-line survey will be conducted in three province, they are Central Java, North Sumatra, and South Sulawesi. They aproximately include 640 villages spread all over 12 regencies that randomly selected of 50% urban areas and 50% rural areas. There will be one Rukun Tetangga (RT) in every village and for every chosen RT will be taken 9 households to be interviewed, including the head of the RT. Thereby, there will be 5760 households all together that are going to be interviewed.

In the second stage of the research, BPS and the society facilitators will test a number of different methods to determine eligible households for anti-poverty programs. The methods are Proxy Means that using serial of indicators to predict per capita expenditure and using per capita income as the basis of target assigning, elegibility rules decentralization, and social participation for household eligibility assessment. Every method will generate poor household lists in RT/RW.
Abstract
The alteration of social targetting toward poor society has become the main priority in many countries for the last two decades as the answer for financial constraint and changing policy to increase program efectivness in fighting against poverty. Indonesian government has implemented a number of anti-poberty programs in large scale during the last couple years which have helped reduce poverty. Such programs are Direct Cash Aid (BLT), Conditional Cash Aid (BTB) and Health Insurance (Askeskin). Targetting improvement on those programs which is intended to guarantee the limited resources to be delivered to the right households, the poor households, instead of the have ones, becomes a continuous challange to guarantee the eficiency of those programs.
Meeting the needs to increase the targetting result, National Planning Buro (BAPPENAS) has requested a technical fund to gain better system in targetting the poor households to the World Bank. The findings of this research will lead to new methods to identify poor households who deserve to receive any aid programs established by the government. This research is a colaboration between World Bank Of Jakarta (WBOJ), Bureau of Statistic Centre (BPS), and academic researchers of Jameel Poverty Action Lab (J-PAL) in Massachusettes Institute of Technology (MIT)
Kind of Data
Sample survey data
Unit of Analysis
The unit of analysis are every household member, from every selected household collected general information regarding name, relationship with Head of household, sex and age.

This survey will also ask a number of questions regarding household consumption, as well as a wide range of household characteristics and participation in community activities. In each village will be selected one RT (RT) and in each selected RT will be interviewed 9 household, which one of it is the Head of RT household.

Version

Version Description
v01: Basic raw data. Obtained from Survey Meter
Version Notes
Data Household Socioeconomic Survey of Indonesia - Baseline 2008 (Idn) also known as SUSETI (Survai Sosial Ekonomi Rumah Tangga Indonesia)

Scope

Notes
From each selected household collected information about the general state of each member of the household including name, relationship to head of household, sex, and age. There will also be asked a number of questions about household consumption, as well as a wide range of household characteristics and participation in community activities. In each village will be selected the Neighborhood (RT) and RT in each selected household is interviewed 9, where one of them is the head of the household RT
Keywords
Keyword
Head of household
Household member
Groups
Consumption
Household property

Coverage

Geographic Coverage
Coverage provincial representative to the level of the village / district
Universe
Household

Producers and sponsors

Primary investigators
Name
Survey Meter

Sampling

Sampling Procedure
This research project is made up of two stages. The first stage that will be conducted earlier is an end-line survey regarding households expenditure toward the random household samples in the same area as in the second stage. This survay will inquire about household consumption and various characteristics as well as household participations in social activities.

End-line survey will be conducted in three province, they are Central Java, North Sumatra, and South Sulawesi. They aproximately include 640 villages spread all over 12 regencies that randomly selected of 50% urban areas and 50% rural areas. There will be one Rukun Tetangga (RT) in every village and for every chosen RT will be taken 9 households to be interviewed, including the head of the RT. Thereby, there will be 5760 households all together that are going to be interviewed.

In the second stage of the research, BPS and the society facilitators will test a number of different methods to determine eligible households for anti-poverty programs. The methods are Proxy Means that using serial of indicators to predict per capita expenditure and using per capita income as the basis of target assigning, elegibility rules decentralization, and social participation for household eligibility assessment. Every method will generate poor household lists in RT/RW.

In this survey pilot, we will visit Rukun Tetangga (RT)/Rukun Warga (RW)/Lingkungan/Dusun/Lorong of the chosen village and we will only interview 9 households for every village. In order to have sample of households that are going to be interviewed, we must find out the whole number of household in that neighbors/Rukun Warga/Lingkungan/Dusun/Lorong. Thus, there must be preliminary listing of the household first

Data Collection

Dates of Data Collection
Start End Cycle
2008-11-13 2008-12-12 1
Data Collection Mode
Face-to-face [f2f]
Data Collectors
Name
Survey Meter

Access policy

Contacts
Name Email
Survey Meter sm@surveymeter.org
Access conditions
This data is available in external resource. Please contact Survey Meter for data request and further iformation
Citation requirements
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Access authority
Name Email URL
Survey Meter sm@surveymeter.org www.surveymeter.org

Disclaimer and copyrights

Disclaimer
Data users claim that data producer, the official distributor of the data, and the relevant funding agencies are not responsible for the use of data, interpretation, or conclusion based on the use of data.

Metadata production

DDI Document ID
DDI_IDN_2008_SUSETI-BASELINE_v02_M
Producers
Name Abbreviation Affiliation Role
Ayu Harlinah AH World Bank Data Cataloging Staff
Date of Metadata Production
2012-12-19
DDI Document version
Version 02 (December 2013). Edited version based on Version 01 (Initial version of DDI documentation - December 2012) DDI (DDI_IDN_2008_SUSETI_v01_M) that was done by Ayu Harlinah (The World Bank).
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