Young Lives: An International Study of Childhood Poverty 2002-2009
Rounds 1-3 Constructed Files
Young Lives: An International Study of Childhood Poverty is a collaborative project investigating the changing nature of childhood poverty in selected developing countries. The UK’s Department for International Development (DFID) is funding the first three-year phase of the project.
Young Lives involves collaboration between Non Governmental Organisations (NGOs) and the academic sector. In the UK, the project is being run by Save the Children-UK together with an academic consortium that comprises the University of Reading, London School of Hygiene and Tropical Medicine, South Bank University, the Institute of Development Studies at Sussex University and the South African Medical Research Council.
The study is being conducted in Ethiopia, India (in Andhra Pradesh), Peru and Vietnam. These countries were selected because they reflect a range of cultural, geographical and social contexts and experience differing issues facing the developing world; high debt burden, emergence from conflict, and vulnerability to environmental conditions such as drought and flood.
Objectives of the study
The Young Lives study has three broad objectives:
• producing good quality panel data about the changing nature of the lives of children in poverty.
• trace linkages between key policy changes and child poverty
• informing and responding to the needs of policy makers, planners and other stakeholders
There will also be a strong education and media element, both in the countries where the project takes place, and in the UK.
The study takes a broad approach to child poverty, exploring not only household economic indicators such as assets and wealth, but also child centred poverty measures such as the child’s physical and mental health, growth, development and education. These child centred measures are age specific so the information collected by the study will change as the children get older.
Further information about the survey, including publications, can be downloaded from the <a href='http://www.younglives.org.uk/'>Young Lives</a> website.
The Rounds 1-3 Constructed Files, 2002-2009 are combined sub-sets of selected variables from Round 1, 2 and 3 of the Young Lives survey. One main constructed data file is available for each of the four countries. These are presented in a panel format and contain approximately 200 original and constructed variables, with the majority comparable across all three rounds.
Kind of data
Sample survey data [ssd]
Date of First Release: 24 April 2014
File last updated: 19 May 2014
Social indicators and quality of life - Society and culture
Time use - Society and culture
Youth - Social stratification and groupings
Child development and child rearing - Social stratification and groupings
Young Lives is an international study of childhood poverty, involving 12,000 children in 4 countries.
- Ethiopia (20 communities in Addis Ababa, Amhara, Oromia, and Southern National, Nationalities and People's Regions)
- India (20 sites across Andhra Pradesh and Telangana)
- Peru (74 communities across Peru)
- Vietnam (20 communities in the communes of Lao Cai in the north-west, Hung Yen province in the Red River Delta, the city of Danang on the coast, Phu Yen province from the South Central Coast and Ben Tre province on the Mekong River Delta)
No spatial unit
Unit of analysis
Location of Units of Observation: Cross-national; Subnational
Population: Young Lives children and their households, in Ethiopia, India (Andhra Pradesh), Peru and Vietnam, in 2002-2009.
Producers and sponsors
University of Oxford
Department for International Development
Funded the study
Sampling Procedures: Purposive selection/case studies
Number of Units: Ethiopia: 8,997 children; India: 9,057 children; Peru: 8,298 children; Vietnam: 9,000 children
No weighting used.
Dates of collection
Mode of data collection
The constructed files are combined sub-sets of selected variables from Round 1, 2 and 3 of the Young Lives survey. The files contain about 200 original and constructed variables, most of them comparable across the three rounds, presented in a panel format and classified in four broad groups: panel information, general characteristics, household characteristics, and child characteristics.
Data Archive Processing Standards
The data were processed to the UK Data Archive's A standard. A rigorous and comprehensive series of checks was carried out to ensure the quality of the data and documentation.ï¿½Firstly, checks were made that the number of cases and variables matched the depositor's records. Secondly, checks were made that all variables had variable labels and all nominal (categorical) variables had value labels. Where possible, either with reference to the documentation and/or in communication with the depositor, absent labels were created. Thirdly, logical checks were performed to ensure that nominal (categorical) variables had values within the range defined (either by value labels or in the depositor's documentation). Lastly, any data or documentation that breached confidentiality rules were altered or suppressed to preserve anonymity.
All notable and/or outstanding problems discovered are detailed under the 'Data and documentation problems' heading below.
Data and documentation problems
Data conversion information
From January 2003 onwards, almost all data conversions have been performed using software developed by the UK Data Archive. This enables standardisation of the conversion methods and ensures optimal data quality. In addition to its own data processing/conversion code, this software uses the SPSS and StatTransfer command processors to perform certain format translations. Although data conversion is automated, all data files are also subject to visual inspection by a member of the Archiveï¿½s Data Services team.
With some format conversions, data, and more especially internal metadata (i.e. variable labels, value labels, missing value definitions, data type information), will inevitably be lost or truncated owing to the differential limits of the proprietary formats. A UK Data Archive Data Dictionary file (generally in Rich Text Format (RTF)) is usually provided for each data file, enabling viewing and searching of the internal metadata as it existed in the originating format. These files are called: [data file name]_UKDA_Data_Dictionary.rtf
Important information about the data format supplied
The links below provide important information about the Archive's data supply formats. Some of this information is specific to the ingest format of the data, i.e. the format in which the Archive received the data from the depositor. The ingest format for this study was STATA
Please follow the appropriate link below to see information on your chosen supply (download) format.
SPSS files (*.sav files)
If SPSS was not the ingest format, this format will generally either have been created via the SPSS command processor (e.g. if the ingest format is STATA, SAS, Excel, or dBase). If the ingest format was non-delimited or fixed-width text, SPSS files will have been created using SPSS command syntax.
Issues: There is very seldom any loss of data or internal metadata when importing data files into SPSS. Any problems will have been listed above in the Data and Documentation Problems section of this file.
STATA (*.dta files)
If STATA was not the ingest format, STATA files will generally have been created from SPSS via the StatTransfer command processor. Importantly, StatTransfer's optimisation routine is run so that variables with SPSS write formats narrower than the data (e.g. numeric variables with 10 decimal places of data formatted to FX.2) are not rounded upon conversion to STATA because they are converted to 'doubles ' rather than floats. Discrete user missing values are copied across into STATA (as opposed to being collapsed into a single system missing code).
Issues: There are a number of data and metadata handling mismatches between SPSS and STATA. Where any data or internal metadata has been lost or truncated, it will be logged in the study's SPSS_to_STATA_conversion RTF file. Note that the complete internal metadata has been supplied in the UKDA Data Dictionary file(s): [data file name]_UKDA_Data_Dictionary.rtf
Tab-delimited text (*.tab files)
If tab-delimited text was not the ingest format, tab-delimited files will have been created from via the SPSS command processor, and also from Excel and MS Access files. When exporting from Access data tables to tab-delimited text, the potentially problematic special characters (tabs, carriage returns, line feeds, etc.) allowed by Access memo and text fields may have been removed by the Archive if necessary.
Issues: Date formats in SPSS are always exported to mm/dd/yyyy in tab-delimited text format. There may be a mismatch with the documentation on such variables. Variables that include both date and time such as dd-mm-yyyy hh:mm:ss (e.g. 18-JUN-2011 13:28:00), will lose the time information and become mm/dd/yyyy. All users of the data in tab-delimited format should consult the UK Data Archive Data Dictionary RTF file(s).
If the data was exported from MS Access, more limited 'data documenter' information is generally available in the RTF variable information files. These files may also contain SQL setup information.
MS Excel (*.xls/*xslx files)
If MS Excel was not the ingest format, Excel files may have been created via StatTransfer. The date and time issues noted under tab-delimited format may also apply here.
SAS (*.sas7bdat and *sas files)
If SAS was not the ingest format, SAS files will usually have been created via StatTransfer or SPSS. SAS is not one of the Archive's standard supply formats, and the files are likely to have been created in response to a user request. The usual format is *.sas7bdat files plus a .sas proc formats file. Note that the complete internal metadata has been supplied in the accompanying UK Data Archive Data Dictionary file(s).
Issues: The main loss of information when converting from SPSS to SAS is user-missing value definitions. By editing the .sas file, the user can choose whether to collapse all user-missing values into system missing or preserve theï¿½value and lose the user-missing definition. To achieve the latterï¿½the following section of the .sas file should be removed before running it:
/* User Missing Value Specifications */
Note that the complete internal metadata has been suppliedï¿½in the UKDA Data Dictionary file(s): [data file name]_UKDA_Data_Dictionary.rtf
MS Access (*.mdb/*.mdbx files)
Due to substantial incompatibilities between versions of MS Access, the Archive will only make data available in MS Access format if this is the ingest format and/or the database contains important information in addition to the data tables (coding information, forms, queries, etc.).may have been created from scanned paper documents. Occasionally, some documentation cannot be usefully converted to PDF (e.g. MS Excel files with wide worksheets) and this is usually supplied in the original or a more appropriate format.
Access conditions: The depositor has specified that registration is required and standard conditions of use apply. The depositor may be informed about usage. See <a href=http://ukdataservice.ac.uk/get-data/how-to-access/conditions.aspx>terms and conditions of access</a> for further information.
All works which use or refer to these materials should acknowledge these sources by means of bibliographic citation. To ensure that such source attributions are captured for bibliographic indexes, citations must appear in footnotes or in the reference section of publications. The bibliographic citation for this data collection is:
Boyden, J., Young Lives: an International Study of Childhood Poverty: Rounds 1-3 Constructed Files, 2002-2009 [computer file]. Colchester, Essex: UK Data Archive [distributor], April 2014. SN: 7483 , http://dx.doi.org/10.5255/UKDA-SN-7483-1
Any publication, whether printed, electronic or broadcast, based wholly or in part on these materials, should acknowledge the original data creators, depositors or copyright holders, the funders of the Data Collections (if different) and the UK Data Archive, and to acknowledge Crown Copyright where appropriate.
Any publication, whether printed, electronic or broadcast, based wholly or in part on these materials should carry a statement that the original data creators, depositors or copyright holders, the funders of the Data Collections (if different) and the UK Data Archive bear no responsibility for their further analysis or interpretation.
Data collection locations
UK Data Service
Disclaimer and copyrights
Although all efforts are made to ensure the quality of the materials, neither the original data creators, depositors or copyright holders, the funders of the Data Collections, nor the UK Data Archive bear any responsibility for the accuracy or comprehensiveness of these materials.
All rights reserved. No part of these materials may be reproduced, stored in, or introduced into a retrieval system, or transmitted, in any form, or by any means (electronic, mechanical, photocopying, recording or otherwise) without the prior written permission of the UK Data Archive.
UK Data Archive
University of Essex
Essex C04 3SQ
Crown copyright material is reproduced with the permission of the Controller of HMSO and the Queens Printer for Scotland
Anne Solon, Data and Survey Manager
University of Oxford
Young Lives, Oxford Department of International Development (ODID)