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    Home / Central Data Catalog / TON / SPC_TON_2023_HFPS-Q2_V01_M_V01_A_PUF
TON

High Frequency Phone Survey, Continuous Data Collection 2023
Quarter 2 2023 to Quarter 4 2024

Tonga, 2023 - 2024
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Reference ID
SPC_TON_2023_HFPS-Q2_v01_M_v01_A_PUF
Producer(s)
Shohei Nakamura, William Seitz
Collections
Tonga
Metadata
Documentation in PDF DDI/XML JSON
Created on
Apr 14, 2025
Last modified
Apr 15, 2025
Page views
24816
Downloads
139
  • Study Description
  • Data Dictionary
  • Downloads
  • Get Microdata
  • Identification
  • Version
  • Scope
  • Coverage
  • Producers and sponsors
  • Sampling
  • Survey instrument
  • Data collection
  • Data processing
  • Data Access
  • Disclaimer and copyrights
  • Contacts
  • Metadata production
  • Identification

    Survey ID number

    SPC_TON_2023_HFPS-Q2_v01_M_v01_A_PUF

    Title

    High Frequency Phone Survey, Continuous Data Collection 2023

    Subtitle

    Quarter 2 2023 to Quarter 4 2024

    Abbreviation or Acronym

    HFPS 2023

    Country
    Name Country code
    Tonga TON
    Study type

    Other Household Survey [hh/oth]

    Series Information

    After two rounds of data collection in 2022, monthly High Frequency Phone Survey (HFPS) data collection commenced in April 2023 and continued until November 2024 (but with some gaps in the months of collection).

    Abstract

    Access to up-to-date socio-economic data is a widespread challenge in Tonga and other Pacific Island Countries. To increase data availability and promote evidence-based policymaking, the Pacific Observatory provides innovative solutions and data sources to complement existing survey data and analysis. One of these data sources is a series of High Frequency Phone Surveys (HFPS), which began in 2020 as a way to monitor the socio-economic impacts of the COVID-19 Pandemic, and since 2023 has grown into a series of continuous surveys for socio-economic monitoring. See <https> for further details.
    For Tonga, after two rounds of data collection from in 2022, monthly HFPS data collection commenced in April 2023 and continued until November 2024 (but with some gaps in the months of collection). The survey collected socio-economic data on topics including employment, income, food security, health, food prices, assets and well-being. Each month of collection has approximately 415 households in the sample and is representative of urban and rural areas. This dataset contains combined monthly survey data for all months of the continuous HFPS in Tonga.

    Kind of Data

    Sample survey data [ssd]

    Unit of Analysis

    Individual and household.

    Version

    Version Description

    Cleaned, labelled and anonymized version of the master file provided by the World Bank.

    Version Date

    2025-04-11

    Scope

    Notes

    -HOUSEHOLD: Interview information and Basic information (S1); Household roster (S2); Food security and food prices (S4); Household income (S5); Agriculture (S6); Social protection (S7); Access to services (S8); Assets (S9); Follow up (S11)
    -INDIVIDUAL: Interview information (S1); Labor (S3); Education (S10).

    Coverage

    Geographic Coverage

    National urban and rural areas (5 islands): Tongatapu, Vava'u, Ha'apai, Eua, Ongo Niua

    Producers and sponsors

    Primary investigators
    Name Affiliation
    Shohei Nakamura World Bank
    William Seitz World Bank
    Producers
    Name Affiliation
    Pacific Observatory
    International Bank for Reconstruction and Development World Bank Group
    Sistemas Integrales Consulting Ltda World Bank Group
    Funding Agency/Sponsor
    Name Abbreviation Role
    World Bank Group WBG Funding
    Australian Department of Foreign Affairs and Trade DFAT Funding

    Sampling

    Sampling Procedure

    The Tonga High Frequency Phone Survey (HFPS) monthly sample was generated in three ways. The first method is Random Digit Dialing (RDD) process covering all cell telephone numbers active at the time of the sample selection. The RDD methodology generates virtually all possible telephone numbers in the country under the national telephone numbering plan and then draws a random sample of numbers. This method guarantees full coverage of the population with a phone.

    First, a large first-phase sample of cell phone numbers was selected and screened through an automated process to identify the active numbers. Then, a smaller second-phase sample was selected from the active residential numbers identified in the first-phase sample and was delivered to the data collection team to be called by the interviewers. When a cell phone was called, the call answerer was interviewed as long as he or she was 18 years of age or above and knowledgeable about the household activities.

    It was initially planned to stratify the sample by island group based on the phone number prefixes. However, this was not feasible given the high internal migration across islands and the atypical assignment of phone number prefixes across islands in Tonga. The raw sample is overrepresenting urban areas and the population of Tongatapu.

    Weighting

    Tonga High Frequency Phone Survey (HFPS) monthly data collection includes only household-level data. The household weighting process involves the following five steps:

    1. Calculation of the inclusion probabilities of cell phone numbers.
    2. Computation of household design weights.
    3. Nonresponse weighting adjustment.
    4. Weight calibration.
    5. Weight trimming and recalibration.

    Adjusted weights of respondent households were calibrated to reflect the country distribution of households by island group, sex, age and educational attainment of the household head, the average household size and the average household's wealth status according to the 2016 Tonga Population Census and the 2019 Tonga Multiple Indicator Cluster Survey (MICS).
    Survey methodology literature and experience show that cell phone survey results tend to be biased towards male, younger and more educated individuals than the overall population, and towards poorer households. This is due to both cell phone ownership patterns (coverage bias) and differential response rates (nonresponse bias). Such overrepresentation of male, younger and more educated individuals and better-off households can be compensated via weight calibration adjustment. Among the existing calibration techniques, the monthly data collection applied the raking method using the logit distance function. The raking margins were based on 2016 Census household counts by island groups and MICS relative distribution of households by household heads' sex, age, education level, household size, and wealth index based on MICS data.

    Survey instrument

    Questionnaires

    The questionnaire was developed in both English and Tongan and can be found in this documentation in Excel format. Sections of the Questionnaire are provided below:

    1. Interview information and Basic information
    2. Household roster
    3. Labor
    4. Food security and food prices
    5. Household income
    6. Agriculture
    7. Social protection
    8. Access to services
    9. Assets
    10. Education
    11. Follow up
    Methodology notes

    For consistency purposes, all categorical levels were labeled identically across variables, where applicable.

    The data is then analyzed and published on a Dashboard. Link: https://dataviz.worldbank.org/views/Dashboard_v19/Labor?:embed=y&:iid=1&:isGuestRedirectFromVizportal=y#3 <https Labor?:embed=y&:iid isGuestRedirectFromVizportal=y>

    Data collection

    Dates of Data Collection
    Start End Cycle
    2023-04-01 2024-11-30 Data collection
    Mode of data collection
    • Computer Assisted Telephone Interview [cati]
    Data Collectors
    Name
    Sistemas Integrales Consulting
    Data Collection Notes

    The survey management team of Sistemas Integrales included a Project Manager, a Data Manager, two survey statisticians, one quality control officer, and one data analyst. The data collection was carried out every other week for five working days and resting a week in between. It was conducted by 10 interviewers, 2 supervisors and one local coordinator provided by 3SMT, a local survey firm hired by Sistemas Integrales Consulting (SIC). The local team also included one auditor hired by SIC and external to 3SMT.

    Data processing

    Data Editing

    At the end of data collection, the raw dataset was cleaned by the survey firm and the World Bank team. Data cleaning mainly included formatting, relabeling, and excluding survey monitoring variables (e.g., interview start and end times). Data was edited using the software Stata.

    Data Access

    Access authority
    Name Affiliation Email
    Shohei Nakamura World Bank snakamura2@worldbank.org
    Confidentiality
    Is signing of a confidentiality declaration required? Confidentiality declaration text
    yes Before being granted access to the dataset, all users must formally agree: 1. To make no copies of any files or portions of files to which s/he is granted access except those authorized by the data depositor. 2. Not to use any technique in an attempt to learn the identity of any person, establishment, or sampling unit not identified on public use data files. 3. To hold in strictest confidence the identification of any establishment or individual that may be inadvertently revealed in any document, discussion, or analysis. Such inadvertent identification revealed in her/his analysis needs to be immediately brought to the attention of the data depositor.
    Access conditions

    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 related survey materials, including survey instruments, documentation and reports, will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of the World Bank Microdata Library.
    2. The data will be used for statistical and scientific research purposes only. They will be used solely for reporting of aggregated information, and not for investigation of specific individual(s) or organization(s).
    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 World Bank Microdata Library.
    4. No attempt will be made to produce links among datasets provided by the World Bank Microdata Library, or among data from the World Bank Microdata Library and other datasets that could identify any individual(s) or organization(s).
    5. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from the World Bank Microdata Library will cite the source of data in accordance with the Citation Requirement provided with each dataset.
    Citation requirements

    "Tonga, High Frequency Phone Survey Q2 2023 to Q4 2024, Continuous Data Collection 2023 (HFPS 2023-Q2), Version 01 of the licensed dataset (April 2025), provided by the Pacific Data Hub - Microdata Library. https://microdata.pacificdata.org/index.php/home"

    Disclaimer and copyrights

    Disclaimer

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

    Contacts

    Contacts
    Name Affiliation Email
    Shohei Nakamura World Bank snakamura2@worldbank.org

    Metadata production

    DDI Document ID

    DDI_SPC_TON_2023_HFPS-Q2_v01_M_v01_A_PUF

    Producers
    Name Abbreviation Affiliation Role
    Statistics for Development Division SDD Pacific Community (SPC) Documentation of the survey
    Date of Metadata Production

    2025-04-14

    Metadata version

    DDI Document version

    Version 01 (April 2025): This is the first attempt at documenting the first continuous data collection of Quarter 2 2023 to Quarter 4 2024 of Tonga. Done by Statistics for Development Division at Noumea, New Caledonia.

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