High Frequency Phone Survey, Continuous Data Collection 2023
Quarter 2 2023 to Quarter 1 2025
Papua New Guinea, 2023 - 2025
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SPC_PNG_2023_HFPS-Q2_v01_M_v01_A_PUF
High Frequency Phone Survey, Continuous Data Collection 2023
Quarter 2 2023 to Quarter 1 2025
HFPS 2023
| Name | Country code |
|---|---|
| Papua New Guinea | PNG |
Other Household Survey [hh/oth]
A series of High Frequency Phone Surveys (HFPS) 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.
For Papua New Guinea, after five rounds of data collection from 2020-2022, in April 2023 a monthly HFPS data collection commenced and continued for 18 months (ending September 2024) –on topics including employment, income, food security, health, food prices, assets and well-being.
Access to up-to-date socio-economic data is a widespread challenge in Papua New Guinea 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://www.worldbank.org/en/country/pacificislands/brief/the-pacific-observatory for further details.
For PNG, after five rounds of data collection from 2020-2022, in April 2023 a monthly HFPS data collection commenced and continued for 18 months (ending September 2024) –on topics including employment, income, food security, health, food prices, assets and well-being. This followed an initial pilot of the data collection from January 2023-March 2023. Data for April 2023-September 2023 were a repeated cross section, while October 2023 established the first month of a panel, which is ongoing as of March 2025. For each month, approximately 550-1000 households were interviewed. The sample is representative of urban and rural areas but is not representative at the province level. This dataset contains combined monthly survey data for all months of the continuous HFPS in PNG. There is one date file for household level data with a unique household ID, and separate files for individual level data within each household data, and household food price data, that can be matched to the household file using the household ID. A unique individual ID within the household data which can be used to track individuals over time within households.
Sample survey data [ssd]
Household, Individual
Version
Cleaned, labelled and anonymized version of the master file.
2025-03-21
Scope
-HOUSEHOLD: Interview information and Basic information (S1); Household roster (S2); Food security; and food prices (S4); Household income (S5); Agriculture (S6); Access to services (S8); Assets (S9); Wellbeing and shocks (S10); Water and Sanitation (S10a)
-INDIVIDUAL: Basic information (S1); Labor (S3).
Coverage
Urban and rural areas of Papua New Guinea
Producers and sponsors
| Name | Affiliation |
|---|---|
| Darian Naidoo | World Bank |
| William Seitz | World Bank |
| Name | Role |
|---|---|
| Pacific Observatory | Technical assistance |
| International Bank for Reconstruction and Development | Technical assistance |
| Name | Abbreviation | Role |
|---|---|---|
| Australian Department of Foreign Affairs and Trade | DFAT | Funding |
Sampling
The initial sample was drawn through Random Digit Dialing (RDD) with geographic stratification from a large random sample of Digicel’s subscribers. As an objective of the survey was to measure changes in household economic wellbeing over time, the HFPS sought to contact a consistent number of households across each province month to month. This was initially a repeated cross section from April 2023-Dec 2023. The resulting overall sample has a probability-based weighted design, with a proportionate stratification to achieve a proper geographical representation. More information on sampling for the cross-sectional monthly sample can be found in previous documentation for the PNG HFPS data.
A monthly panel was established in October 2023, that is ongoing as of March 2025. In each subsequent round of data collection after October 2024, the survey firm would first attempt to contact all households from the previous month, and then attempt to contact households from earlier months that had dropped out. After previous numbers were exhausted, RDD with geographic stratification was used for replacement households.
Sampling weights were calculated in a series of steps, applied consistently for April 2023 – February 2025 for the repeated cross-sectional sample. The sampling weighting procedure applied consistently for the period October 2023 - February 2025, was slightly different to make comparisons across the panel nature of the data across this period. These differences are explained after some description of the basic elements of the weighting approach and data used.
General Approach
A shortcoming of using random digit dialing in a phone survey is that the resulting data is representative of mobile phone owners, who tend to be of higher income groups and more concentrated in urban areas, rather than being representative of the whole population. Mobile cellular subscription in PNG is estimated to be around 71% percent of households, according to the socio-demographic and economic survey (SDES, 2022). In addition, non-random non-responses can exacerbate these differences. To make statistically meaningful inferences about the overall population instead of the country’s mobile phone holders, it was necessary to reweight the survey data.
Auxiliary data to serve as inputs to the weighting exercise is severely limited as there are few recent nationally representative sources. In previous HFPS rounds for PNG (from 2020-2022), data from the Demographic and Health Survey 2016 (DHS) was used as the reference for the characteristics of households, and for population estimates by province. The DHS sample was based on the 2011 Census frame, with oversampling of smaller provinces. The provincial distribution of World Bank is very similar to that of the Census 2011 frame.
The most recent nationally representative survey that includes some measures of socio-economic welfare was the 2022 Socio-demographic and Economic Survey (SDES). Although there are no provincial estimates in the SDES (and hence the need to continue to use population estimates from the DHS/Census 2011 for that), there are household demographic, asset, ad dwelling characteristics, that can be used for weighting. A set of common variables between the SDES and the HFPS data set were identified and made to be comparable through re-coding and aggregation of response options, where response options were different. While a census of population was conducted in PNG in 2024, it did not collect data on household characteristics beyond age and gender, so cannot be suitable for weighting purposes.
Cross Sectional Weights for April 2023-October 2023
The household weight variable in the household dataset is named “weight_hh” and represents household cross-sectional weights. The individual data set contains individual weights for individual analysis that sum to the population of the 2019 Census; it is named as ‘weight_ind.’
The base month of the monthly HFPS, October 2023, was weighted to make the sample as representative of SDES 2022 common variables, and then each month the procedure was repeated and independent, i.e. without regard to the weights of the previous month.
Cross-sectional Weights for December 2023- February 2025
The weights were calculated similarly to the approach for April 2023- December 2024, except only the base month of January 2024 was weighted to the 2019 Census. All subsequent months were then weighted to match as closely as possible to January 2024 to enhance comparability of monthly statistics across 2024. If there was zero attrition from month to month, this would mean that the weights would be exactly the same in each month, but with attrition, there is change in the average demographic, dwelling, and asset characteristics of households that means that the household weights for each households are at least slightly different, even for “returning” households. Further to this, panel data weights could be generated specifically for panel data analysis.
Survey instrument
he questionnaire, which can be found in the External Resources of this documentation, is in English with a Pidgin translation.
The survey instrument for Q1 2025 consists of the following modules:
-1. Basic Household information,
-2. Household Roster,
-3. Labor,
-4a Food security,
-4b Food prices
-5. Household income,
-6. Agriculture,
-8. Access to services,
-9. Assets
-10. Wellbeing and shocks
-10a. WASH
Open-ended response “Other, specify” in various questions in the questionnaire was recorded as a separate variable in the raw dataset. These were recoded and incorporated as a response option of the corresponding multiple-choice question. These “other, specify” variables were then dropped from the household and individual data sets.
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
Data collection
| Start | End | Cycle |
|---|---|---|
| 2023-04-01 | 2025-03-01 | Data collection |
- Computer Assisted Telephone Interview [cati]
| Name |
|---|
| Digicel Pacific |
The monthly High Frequency Phone Survey was conducted between April, 2023, and is ongoing as of March 2025, with periodic updates to this online version of the data planned quarterly. Digicel Pacific conducts the data collection from a call center in Port Moresby, using local enumerators.
Data processing
The raw data were cleaned by the World Bank team using STATA. This included formatting and correcting errors identified through the survey’s monitoring and quality control process. The data are presented in two datasets: a household dataset and an individual dataset. The individual dataset contains information on individual demographics and labor market outcomes of all household members aged 15 and above, and the household data set contains information about household demographics, education, food security, food prices, household income, agriculture activities, social protection, access to services, and durable asset ownership. The household identifier (hhid) is available in both the household dataset and the individual dataset. The individual identifier (id_member) can be found in the individual dataset.
Data Access
| 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. |
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:
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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.
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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).
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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.
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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).
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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.
"Papua New Guinea, High Frequency Phone Survey Q2 2023 to Q1 2025, Continuous Data Collection 2023 (HFPS 2023-Q2), Version 01 of the licensed dataset (March 2025), provided by the Pacific Data Hub - Microdata Library. https://microdata.pacificdata.org/index.php/home"
Disclaimer and copyrights
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
| Name | Affiliation | |
|---|---|---|
| Darian Naidoo | World Bank | dnaidoo@worldbank.org |
Metadata production
DDI_SPC_PNG_2023_HFPS-Q2_v01_M_v01_A_PUF
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Statistics for Development Division | SDD | Pacific Community | Documentation of study |
2025-03-21
Metadata version
-Version 01 (March 2025): This is the first attempt at documenting the first continuous data collection of Quarter 2 2023 to Quarter 1 2025 of Papua New Guinea. Done by Statistics for Development Division at Noumea, New Caledonia.