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Census of Population and Housing 2005

Palau, 2005
Reference ID
PLW_2005_PHC_v01_M
Producer(s)
Office of Planning and Statistics
Metadata
DDI/XML JSON
Created on
Feb 19, 2014
Last modified
Mar 29, 2019
Page views
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  • Study Description
  • Data Dictionary
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  • Related Publications
  • Identification
  • Scope
  • Coverage
  • Producers and sponsors
  • Sampling
  • Data collection
  • Data processing
  • Data appraisal
  • Data Access
  • Disclaimer and copyrights
  • Contacts
  • Metadata production
  • Identification

    Survey ID number

    PLW_2005_PHC_v01_M

    Title

    Census of Population and Housing 2005

    Country
    Name Country code
    Palau PLW
    Study type

    Population and Housing Census [hh/popcen]

    Series Information

    This volume presents population and housing statistics from the 2005 Census of Population and Housing for the Republic of Palau. The 2005 census is the third one undertaken and fully funded by the government of the Republic of Palau, following the 1995 and 2000 Censuses. OPS played the key role in collection and processing the 2005 Census information and was also the lead agency analyzing the data.

    Abstract

    The 2005 Census of Population and Housing was the third comprehensive data collection of population and housing characteristics taken by the Republic since Compact Implementation in October 1994. The 2005 Census of Palau had two volumes. This first volume contained the basic tables, which can be used instantly for planning and policy determination. A second volume, the Census monograph, contained analyses of trends and comparisons of the States.

    Kind of Data

    Census/enumeration data [cen]

    Unit of Analysis

    Individuals
    Families
    Households
    General Population

    Scope

    Notes

    The scope of the 2005 Palau Census of Population and Housing includes collecting, compiling, evaluating, analysing and releasing demographic and housing, economic and social data pertaining to all persons and their living quarters.

    The fundamental purpose of a census is to provide information on the size, distribution and characteristics of a country’s population. The census data are used for policymaking, planning and administration, as well as in management and evaluation of programmes in education, labour force, family planning, housing, health, transportation and rural development. A basic administrative use is in the demarcation of constituencies and allocation of representation to governing bodies. The census is also an invaluable resource for research, providing data for scientific analysis of the composition and distribution of the population and for statistical models to forecast its future growth. The census provides business and industry with the basic data they need to appraise the demand for housing, schools, furnishings, food, clothing, recreational facilities, medical supplies and other goods and services.

    Coverage

    Geographic Coverage

    National

    Universe

    The Census covered all the households and respective residents in the entire country.

    Producers and sponsors

    Primary investigators
    Name Affiliation
    Office of Planning and Statistics Ministry of Finance
    Producers
    Name Affiliation Role
    U.S. Department of Interior US Government Technical Assistance Grant
    U.S. Bureau of Census US Government Technical Assistance in census entirety
    Funding Agency/Sponsor
    Name Role
    Republic of Palau Financing
    United States of America Technical Expertise Financier
    Other Identifications/Acknowledgments
    Name Affiliation Role
    Student Volunteers Midszenty High School Coding
    Student Workers Workforce Investment Act Coding and Keying

    Sampling

    Sampling Procedure

    Not applicable to a full enumeration census.
    For details please refer to the attached Basic Tables and Monograph.

    Response Rate

    In any large-scale statistical operation, such as the 2005 Census of the Republic of Palau, human- and machine-related errors do occur. These errors are commonly referred to as nonsampling errors. Such errors include not enumerating every household or every person in the population, not obtaining all required information form the respondents, obtaining incorrect or inconsistent information, and recording information incorrectly. In addition, errors can occur during the field review of the enumerators' work, during clerical handling of the census questionnaires, or during the electronic processing of the questionnaires.

    To reduce various types of nonsampling errors, a number of techniques were implemented during the planning, data collection, and data processing activities. Quality assurance methods were used throughout the data collection and processing phases of the census to improve the quality of the data.

    Data collection

    Dates of Data Collection
    Start End Cycle
    2005-04-01 2005-05-15 Enumeraton
    Data Collectors
    Name Affiliation
    Office of Planning and Statistics Ministry of Finance

    Data processing

    Data Editing

    Full scale processing and editing activiities comprised eight separate sessions either with or separately but with remote guidance of the U.S. Census Bureau experts to finalize all datasets for publishing stage.

    Data appraisal

    Estimates of Sampling Error

    Sampling Error is not applicable to censuses; however, a processing operation was handled with care to produce a set of data that describes the population as clearly and accurately as possible. To meet this objective, questionnaires were reviewed and edited during field data collection operations by crew leaders for consistency, completeness, and acceptability. Questionnaires were also reviewed by census clerks in the census office for omissions, certain inconsistencies, and population coverage. For example, write-in entries such as “Don't know” or “NA” were considered unacceptable in certain quantities and/or in conjunction with other data omissions.

    As a result of this review operation, a telephone or personal visit follow-up was made to obtain missing information. Potential coverage errors were included in the follow-up, as well as questionnaires with omissions or inconsistencies beyond the completeness and quality tolerances specified in the review procedures.

    Subsequent to field operations, remaining incomplete or inconsistent information on the questionnaires was assigned using imputation procedures during the final automated edit of the collected data. Allocations, or computer assignments of acceptable data in place of unacceptable entries or blanks, were needed most often when an entry for a given item was lacking or when the information reported for a person or housing unit on that item was inconsistent with other information for that same person or housing unit. As in previous censuses, the general procedure for changing unacceptable entries was to assign an entry for a person or housing unit that was consistent with entries for persons or housing units with similar characteristics. The assignment of acceptable data in lace of blanks or unacceptable entries enhanced the usefulness of the data.

    Another way to make corrections during the computer editing process is substitution. Substitution is the assignment of a full set of characteristics for a person or housing unit. Because of the detailed field operations, substitution was not needed for the 2005 Census.

    Data Appraisal

    In any large-scale statistical operation, such as the 2005 Census of the Republic of Palau, human- and machine-related errors were anticipated. These errors are commonly referred to as nonsampling errors. Such errors include not enumerating every household or every person in the population, not obtaining all required information form the respondents, obtaining incorrect or inconsistent information, and recording information incorrectly. In addition, errors can occur during the field review of the enumerators' work, during clerical handling of the census questionnaires, or during the electronic processing of the questionnaires.

    To reduce various types of nonsampling errors, a number of techniques were implemented during the planning, data collection, and data processing activities. Quality assurance methods were used throughout the data collection and processing phases of the census to improve the quality of the data.

    Data Access

    Access authority
    Name Affiliation URL Email
    Director, Bureau of Budget and Planning Ministry of Finance http://www.palaugov.net/stats ropbudget@palaugov.net
    Statistics Coordinator Office of Planning and Statistics http://www.palaugov.net/stats ops@palaugov.net
    Confidentiality
    Is signing of a confidentiality declaration required? Confidentiality declaration text
    yes Confidentiality of respondents and their information is guarded under a confidentiality oath required of all enumerators and OPS staff involved in the undertaking of Census 2005. Further protection is guaranteed under the Statistics Act of 2011. While public acces to aggregate Census data is permissible, the identity of respondents (persons and establishments) cannot be revealed at any time. The Statistics Act 2011 specifically inhibits any means by which the identity and privacy of respondents could be compromised with corresponding penalties.
    Access conditions

    While the dataset has been anonymized and is available as a Public Use Dataset, it is accessible to all for statistical and research purposes only, under the following terms and conditions:

    1. The data and other materials will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of the Director of Budget and Planning, Ministry of Finance.
    2. The data will be used for statistical and scientific research purposes only. They will be used solely for reporting of aggregated informationand not for investigation of specific individuals or organizations.
    3. No attempt will be made to re-identify respondents, and no use will be made of the identity of any person or establishment discovered inadvertently. Any such discovery would immediately be reported to the Director of the Bureau of Budget and Planning.
    4. No attempt will be made to produce links among datasets provided by the Office of Planning and Statistics (OPS), or among data from the OPS and other datasets that could identify individuals or organizations.
    5. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from the Office of Planning and Statistics will cite the source of data in accordance with the generally accepted research and data reference standards.
    6. An electronic copy of all reports and publications based on the requested data should be sent to the OPS or the Bureau of Budget and Planning at the following email addresses: ops@palaugov.net or ropbudget@palaugov.net.

    The original collector of the data, the OPS, and the relevant funding and technical agencies bear no responsibility for use of the data or for interpretations or inferences based upon such uses.

    Disclaimer and copyrights

    Disclaimer

    The user of the data acknowledges that the Office of Planning and Statistics, Republic of Palau, original collector of the data, the authorized distributor of the data, and the relevant funding and technical agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.

    Copyright

    (c) 2005, Office of Planning and Statistics, MoF, Republic of Palau Government

    Contacts

    Contacts
    Name Affiliation Email URL
    Statistics Coordinator Office of Planning and Statistics ops@palaugov.net http://www.palaugov.net/stats

    Metadata production

    DDI Document ID

    DDI_PLW_2005_PHC_v01_M

    Producers
    Name Affiliation Role
    Rhinehart Silas Office of Planning and Statistics Census Documentation
    Date of Metadata Production

    2012-07-16

    Metadata version

    DDI Document version

    Version 01 (September 2012) - Adapted version of the DDI "DDI-PLW-OPS-CPH-2005-v1.1." documented by Office of Planning and Statistics in July 2012

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