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Editing Census Data: Mexico’s Experience

Editing Census Data: Mexico’s Experience. Oswaldo Palma INEGI, Mexico September 2012. About INEGI. National Institute for Statistics and Geography (INEGI) is, from 2008, an autonomous institute in Technical and Managing matters.

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Editing Census Data: Mexico’s Experience

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  1. EditingCensus Data:Mexico’sExperience Oswaldo Palma INEGI,Mexico September 2012

  2. About INEGI • National Institute for Statistics and Geography (INEGI) is, from 2008, an autonomous institute in Technical and Managing matters. • According to Mexican Statistical and Geographical Information Act, INEGI it is the responsible for making the Population and Housing Census every decade • Being the responsible for the Statistics-Geography couple, it gives institute significant technical, operational and statistical data dissemination advantages.

  3. Characteristics of Census 2010 • Traditional census, de facto. • Field working to visit around 32 million of dwellings and enumerate 112.3 million of inhabitants. • Field work in the Mexican 2010 Population and Housing Census was undertaken from May 31st to June 30th, 2010. • Interviews were held using printed forms.

  4. Formsused • Sixkind of formswereused: • Buildinglist • Short form • Long form • Selfenumerationform • Urbanenvironmentform (CEU) • Localityform

  5. Information’sTreatment • Deliveringresults in eightmonths • Parallelprocesses • Sixstages • Form’sstorage • Data Entry • Coding • Editing • Mappingupdate • Figures validation • Disseminating

  6. Editing Short formand Long form

  7. Data Editing characteristics • Assure the logic congruence and integrity of questions and sections • Correcting errors made during the interview or data entry • Respect as much as possible the respondent answers • Practically null stochastic imputation

  8. Methodologyimplemented • Vector’smethodolgywasused • Tocreateanequivalencebetween cases (a partition) • Advantages • Comprehensive information analysis • System programming simplified • Analysis simplified • Follow-up simplified on changes made

  9. Vector’sMethodologysteps • Variables intervening in editing criteria and values taken for each variable are identified. • A vector is built which components represent values that every variable can take. • All combinations between values that vectors take are generated, which are obtained by varying every value of each vector component, this is made starting from last to first component up to obtain the total group of combinations. • To have control on combinations generated, the known addressing function is built, which allows the assignment of an only value also known as image to each combination according to the order in the one they are generated. • For each particular combination an specific treatment is stated.

  10. Number of criteriadesigned • 232 criteriawereprogrammedusing JAVA supportedby PL/SQL insidedatabase • Eachcriteriawastestedusing a “EditingCriteria Simulator”

  11. Computing infrastructure • Robust architecture • Supporting multi-processing • Possibility to add Apps & DB servers according to requirements • Time to process 165.6 hours

  12. EditingUrbanEnviromentform

  13. UrbanEnvironmentform (CEU) • CEU wascarriedoutforfirst time in 2010 • Allows the collection of information about urban characteristics of streets delimiting each block in localities of 5,000 inhabitants or over • Inclusion of CEU in the 2010 Census forms allows link information on population and housing with urban characteristics.

  14. Characteristiccollected • Kind of road of characteristic (street, avenue, etc.) • Persons access (free, restricted, prohibited) • Cars access (free, restricted, prohibited) • Type of recovering (concrete, stone, ground) • Availability of street identifier • Availability of: • Public light. • Public telephone. • Sewage. • Sidewalk. • Sidewalk margin. • Ornamental trees or plants. • Collective transport. • Semi-fix trade workstations. • Petty trade workstations.

  15. New Challenges • A need to generate vector mapping for new geographic levels (block side). • Generate and maintain a new conceptual framework consistent to prior traditionally taken into account. • Develop new methodologies to: coding, editing, validating, and imputing to ensure information consistency when this is represented on a map.

  16. Example of inconsistencies

  17. Problemsolvingadvance • Information association to its respective block side • Standarization of streets names • Identification of irregular patterns in mapping

  18. Association and Standardization • 100 analysts hired during four months

  19. Mainproblemsfound • Methodologies and concepts to unify language and strategies are required. • Training staff in conceptual model (long time process) • Hiring or training of human resources in handling geographic information apps. (It could be an issue specially when the NSO don't conjugates the statistical & geographical expertise) • Development of expert systems which allows automatic and assisted identification of patterns and data infrastructure needed for these activities. • Computers with proper capacity and performance • Sometimes bandwidth can also be an issue

  20. Administrativeregisters • Nowadays, the first essay to associate the administrative registers of electricity supplier with the cartographic frame is being undertaken. In this process the information and methods derived from the standardization process of street names is used as key information. (72% of the essay information has been associated). • However; these tests, are oriented to define a proper conceptual framework incorporating linguistic computing elements and pattern recognition in texts.

  21. Concludingremarks • Data editing of the Census 2010 was successfully carried out. • Significant improvement compared to prior census were obtained. • Improvements are mainly identified in the changes control on information and treatments comprehensiveness. • The time to carry out census data editing was almost a year (lesser than the previous censuses)

  22. Concludingremarks • Editing CEU had no problems when considering it as the traditional editing registers process in a data table. • The development of criteria considering data consistency when these are presented on a map still is a challenge. • Latter imply interesting technical challenges and can force to the NSO to review planning and evaluate available resources.

  23. Concludingremarks • Finally, for the case of Mexico, which has no administrative registers with the quality needed for use as statistical registers, work for solving the problem of data editing can be reused to convert the available registers in statistical registers.

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