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As mobile and wireless technologies continually improve and become more affordable, reliable, powerful and user-friendly, Computer Assisted Personal Interviewing (CAPI) is expected to become the one of the effective approaches in field-based census data collection even in those countries where access to infrastructure for information and communication technologies is limited. African countries are at such a case. The introduction of electronic data capture into the business cycle of the census provides cost and time savings, and also allows users to take advantage of added features that can be programmed into mobile devices or linked to the data collection process. These features include, among others, integrated maps and Global Positioning System (GPS) and real time monitoring of fieldwork. This paper shows how the Italian National Institute of Statistics (Istat) has supported the Ethiopia Central Statistics Agency (CSA) in designing and implementing such a monitoring system, which has been fully integrated with the census data collection process managed by CSPro, the public domain software package developed by the U.S. Census Bureau (USCB). The proposed architecture is generalised and provides a simple solution for monitoring electronic data collection operations, particularly in cases where the technical and financial resources to implement such a system from the ground up are lacking. [ABSTRACT FROM AUTHOR]

The Dutch 2011 Census tables were produced by combining existing register and sample survey data. Since the last census based on a complete enumeration was held in 1971, the willingness of the population to participate has fallen sharply. Statistics Netherlands no longer uses census questionnaires and has found an alternative in the register-based census, using only existing data. The register-based census is cheaper and more socially acceptable. The table results of the Netherlands are not only comparable with earlier Dutch censuses, but also with those of the other countries in the 2011 European Census Round, although most other countries do not yet have register-based censuses. The Dutch Census 2011 cannot be considered in isolation from its predecessors. This most recent census builds on a rich tradition of traditional population and housing censuses carried out in the period 1829–1971. For the European Union censuses of 1981 and 1991, Statistics Netherlands provided alternative census data consisting of a combination of register and survey data, but without complete numerical consistency between census tables and without detailed information about regions and specific categories. This combined data provision was continued for the censuses of 2001 and 2011, by which time it was possible to compile completely consistent data at a very detailed level. The 2011 Census data are more detailed than those of 2001, and include the hypercubes (high dimensional tables) that are mandatory for all EU countries under the 2008 European Census Act. The challenge for the future is to keep comparability, but to improve the timeliness of the European census results. [ABSTRACT FROM AUTHOR]

Monitoring and addressing racial and ethnic disparities in health and health care require the collection and analysis of reliable demographic information. With the intention of improving the measurement and monitoring of disparities, certain provisions of the Patient Protection and Affordable Care Act (ACA) of 2010 require states to collect, report, and analyze data on demographic characteristics of applicants and participants in Medicaid and other federally supported programs. In this large-scale study we link Medicaid records to the Census 2000, the 2010 Census, and the American Community Survey for years 2001–2009 to explore the extent to which pre-ACA Medicaid administrative records matched self-reported race and Hispanic origin in Census Bureau data. Record linkage allows comparison of demographic, socioeconomic and neighborhood characteristics between Medicaid participants with matching and non-matching race and Hispanic origin in census. Identification of the groups most likely to have non-matching and missing race and Hispanic origin data in Medicaid relative to census can inform strategies to improve the quality of demographic data collected from the Medicaid population. [ABSTRACT FROM AUTHOR]

The aim of this paper is to show a Palestinian Central Bureau of Statistics (PCBS) [1] experiment in administrative data records linkage. We focused in this paper on PCBS experiment in matching different data sources from different ministries, municipalities and other partners with PCBS Establishments Census 2012. Different matching algorithms and tools were used in the experiment. We started our experiment by using the Fuzzy Lookup [2]. It is an add-in for Excel developed by Microsoft Research. It performs fuzzy matching of textual data in Microsoft Excel. The tool uses the Jaccard Index of Similarity and Levenshtein distance; a statistical way to measure similarities between sample sets. In order to compare data and try to find out matching data, we also used Duke, see Lars [3] which is an existing and flexible deduplication (or entity resolution, or record linkage) engine written in Java. By using Duke Engine, we wrote our matching algorithm and comparators to increase the matching results and matching accuracy. We also wrote some data-cleaning functions for matching variables (Commercial Name, Owner Name and Telephone) in order to standardize each matching variable to get improved results. Different matching algorithms were used in the experiment such as Hamming Distance, e.g. Mohammad [4], Levenshtein distance, Mark [5], Jaccard Similarity, e.g. Suphakit et al. [6], exact match and multiple match. The results showed that after cleaning the identification variables, the number of matches rises significantly. We also noted that there is an improvement in matching rates when going from the matching based only on phone numbers to the matching based on Telephone, Commercial Name and Owner Name. [ABSTRACT FROM AUTHOR]