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Statistical Coherence: Census Hub Hypercubes and IPUMS Microdata UNECE Expert Group on Population and Housing Censuses Geneva, 23-26 September 2014 Lara.

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Presentation on theme: "Statistical Coherence: Census Hub Hypercubes and IPUMS Microdata UNECE Expert Group on Population and Housing Censuses Geneva, 23-26 September 2014 Lara."— Presentation transcript:

1 Statistical Coherence: Census Hub Hypercubes and IPUMS Microdata UNECE Expert Group on Population and Housing Censuses Geneva, 23-26 September 2014 Lara Cleveland University of Minnesota, USA clevelan@umn.edu with Robert McCaa 1, Matt Sobek 1, Albert Esteve 2, and Antonio Lopez 2 1 University of Minnesota, USA 2 Autonomous University of Barcelona, Spain

2 79 countries -- 258 censuses -- 560 million person records

3 CED Barcelona: IECM DWB: Jan 2015 Workshop for microdata researchers INGRID: June 2015 Workshop for IPUMS partners after Conference of European Statisticians Albert Esteve: aesteve@ced.uab.es

4 IECM – IPUMS Partnership CED Barcelona

5 Complementary means of dissemination Serve different constituencies Census Hub open access, counts, descriptive statistics IPUMS Microdata research or policy access, multivariate analysis Census Hub and IPUMS Microdata

6 Census Hub

7 Census Hub: Summary Data

8 Census Hub: Cross-National

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10 Relation to head Marital status Education Occupation Microdata

11 Microdata vs. Hub Data Both: harmonize data internationally; pooled output; provide metadata IPUMS/IECM Download data for analysis Multivariate modelling Samples Global, with historical depth Household-level samples: individual behavior in context

12 Microdata vs. Hub Data Both: harmonize data internationally; pooled output; provide metadata Microdata samples = flexibility (IPUMS/IECM) Download data for analysis Multivariate modelling Denominator Household-level samples: individual behavior in context

13 Household Microdata Example: Foreign-born persons in union with native-born (ca. 2000)

14 79 countries -- 258 censuses -- 560 million person records

15 69 Samples Entrusted to IPUMS

16 2015 IPUMS Sample Processing

17 Coherence Hub and IPUMS/IECM sample data  Between sources  Across census years Method: cohort analysis  By birth year  Proportion completed secondary education Expected Results: Results should match for each year of birth  Between sources from the Hub and IPUMS/IECM  Across censuses from different years  Net of some effect of migration and mortality Statistical Coherence Comparison of Hub and IPUMS Data

18 Secondary Education Completed: Austria 40% of people born in 1922 completed secondary 83% of people born in 1986 completed secondary

19 Secondary Education Completed: Austria

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24 Secondary Education Completed: Ireland

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26 Secondary Education Completed: France

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28 Preservation Researchers Time trend analysis Analysis of policy outcomes or treatment effects Interrelationships among social phenomena Historical study IPUMS Archive data and documentation Current technology Secure technology and facilities Data management “best practices” Data recovery

29 Harmonization NSOs balance  Standards (ISO, UN Principles and Recommendations, Regional and Global meetings)  National context and temporal change Researchers want  Consistent codes and concepts across all datasets  Warnings about potential pitfalls IPUMS  Finishes the harmonization process  Coding rationale transparent and reversible

30 Harmonization

31 Dissemination NSOs Unique systems and formats Different request/retrieval procedures Researchers Formats are overwhelming Request processes burdensome

32 Dissemination Data – IPUMS Consistent format Customizable microdata file Pooled across time and or place Only relevant variables (question items) Choice of data format Free to registered and verified users for scholarly research and policy purposes

33 Dissemination Metadata For each variable (census item or question) Coding structure (original and harmonized) Discuss comparison issues Question and enumerator instruction text or register source For each sample Sample and census characteristics

34 High degree of correspondence with official totals Census microdata dissemination benefits High quality documentation Persistent data quality assessment Large research and policy impact Excellent user support Results and Reflections IPUMS/IECM census microdata

35 Researchers and the IPUMS goals Preservation NSO: Current and future Res: Change over time – empirically Harmonization NSO: Standards in National Context Res: Cross-country and cross-temporal Dissemination NSO: Specific format Res: Single format across all data sources Serves small specialty audience

36 Variables Included in Extracts

37 Top Institutional Users

38 Thank you! ipums.org clevelan@umn.edu


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