High Frequency Phone Survey, Continuous Data Collection 2023
Quarter 2 2023 to Quarter 3 2024
Solomon Islands, 2023 - 2024
Get MicrodataIdentification
SPC_SLB_2023_HFPS-Q2_v01_M_v01_A_PUF
High Frequency Phone Survey, Continuous Data Collection 2023
Quarter 2 2023 to Quarter 3 2024
HFPS 2023
| Name | Country code |
|---|---|
| Solomon Islands | SLB |
Other Household Survey [hh/oth]
After five rounds of data collection from 2020-2020, in April 2023 a monthly High Frequency Phone Survey 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 Solomon Islands 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 Solmon Islands, after five rounds of data collection from 2020-2020, 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. Fieldwork took place in two non-consecutive weeks of each month. Data for April 2023-December 2023 were a repeated cross section, while January 2024 established the first month of a panel, the was continued to September 2024. Each month has approximately 550 households in the sample and 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 Solomon Islands. There is one date file for household level data with a unique household ID. and a separate file for individual level data within each household data, that can be matched to the household file using the household ID, and which also has a unique individual ID within the household data which can be used to track individuals over time within households, where the data is panel data.
Sample survey data [ssd]
Household, individual.
Version
Cleaned, labelled and anonymized version of the master file provided by the World Bank.
2025-03-01
Scope
-HOUSEHOLD: Interview information and Basic information (S1); Household roster (S2); Food security (S4A),Food prices (S4B); Household income (S5); Agriculture (S6); Social protection (S7); Access to services (S8); Assets (S9); Energy (S12).
-INDIVIDUAL: Basic information (S1); Employment and income information (S3).
Coverage
Urban and rural areas of Solomon Islands.
Producers and sponsors
| Name | Affiliation |
|---|---|
| Darian Naidoo and William Seitz | World Bank Group |
| Name | Affiliation | Role |
|---|---|---|
| The Pacific Observatory | Technical assistance | |
| International Bank for Reconstruction and Development | World Bank | Technical assistance |
| Name | Abbreviation | Role |
|---|---|---|
| World Bank | Funding | |
| Australian Department of Foreign Affairs and Trade | DFAT | Funding |
Sampling
The initial sample was drawn through Random Digit Dialing (RDD) with geographic stratification. 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 initial sample was drawn from information provided by a major phone service provider in Solomon Islands, covering all the provinces in the country. It had a probability-based weighted design, with a proportionate stratification to achieve geographical representation. The geographical distribution compared to the 2019 Census is listed below for the first month of the HFPS monthly survey:
Choiseul : Census: 4.3%, HFPS: 5.2%
Western : Census: 14.4%, HFPS: 13.7%
Isabel : Census: 4.8%, HFPS: Census: 3.6%, HFPS: 5.2%
Ren Bell : Census: 0.6%, HFPS: 1.4%
Guadalcanal: Census: 19.8%, HFPS: 21.1%
Malaita : Census: 23.1%, HFPS: 18.7%
Makira : Census: 5.6%, HFPS: 5.6%
Temotu: Census: 3.0%, HFPS: 3%
Honiara: Census: 20.7%, HFPS: 21.3%
Source: Census of Population and Housing 2019
Note: The values in the HFPS column represent the proportion of survey participants residing in each province, based on the raw HFPS data from April.
In April 2023, the geographic distribution of World Bank HFPS participants was generally similar to that of the census data at the province level, though within provinces, areas with less mobile phone connectivity are likely to be underrepresented. One indication of this is that urban areas constituted 38.2 percent of the survey sample, which is a slight overrepresentation, compared to 32.5 percent in the Census 2019.
A monthly panel was established in January 2024, that is ongoing as of March 2025. In each subsequent month after January 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. Across all months of the survey a total of, 9,926 interviews were completed.
Sampling weights were calculated in a series of steps, applied consistently for April 2023- December 2024 for the repeated cross-sectional sample. The sampling weighting procedure applied consistently for the period January 2024- September 2024 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 Solomon Islands is estimated to be about only 67 percent of the population in 2021, according to the International Telecommunication Union (ITU) World Telecommunication/ICT Indicators Database. 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. The last Household Income and Expenditure Survey (HIES) was from 2012/2013, the only survey that can be used to measure differences in consumption and income across the population and hence, differentiate the poor from the non-poor. The most recent nationally representative dataset that includes some measures of socio-economic welfare was the 2019 Census of Population and Housing (2019 Census). Although there is no measure of consumption of households in the 2019 Census, there are household demographic and dwelling characteristics, and household assets, that can be used for weighting. A set of common variables between the 2019 Census 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.
-Cross Sectional Weights for April 2023-December 2024
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, January 2023, was weighted to make the sample as representative of the 2019 Census common variables, and then each month the procedure was repeated and independent, ie. without regard to the weights of the previous month. One limitation of this approach that is not possible to mitigate without an updated source of nationally representative data, is the time elapsed between the HFPS data and the reference survey (2019 Census) increases, the weighting procedure may become a less accurate way of achieving representativeness if the population characteristics are also changing. For example, if the proportion of households with electricity has increased between 2019 and 2023, the raw HFPS data may be more representative than the differences in the means of the HFPS data and 2019 Census data would suggest, and the weights may potentially “overcorrect” the bias in the HFPS data. For this reason, weights were trimmed for outliers above the 95th percentile and below the 5th percentile. Specifically, values above the 95th percentile were adjusted to match the 95th percentile value, while values below the 5th percentile were adjusted to match the 5th percentile value.
-Cross-sectional Weights for January 2024- September 2024
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
The questionnaire, which can be found in the External Resources of this documentation, is available in English, with Solomons Pijin translation. There were few changes to the questionnaire across the survey months, but some sections were only introduced in 2024, namely energy access questions and questions to inform the baseline data of the Solomon Islands Government Integrated Economic Development and Climate Resilience (IEDCR) project.
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 urban/rural status of each household was established based on both the household’s self-reported status and the urban/rural population at the ward level from the 2009 Solomon Islands Census of Population and Housing. If a household reported that they lived in urban area yet the ward where they lived in did not have an urban population according to the 2009 Census, the status of that household was adjusted to be rural instead; and vice versa.
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 | 2024-09-30 | Data collection |
- Computer Assisted Telephone Interview [cati]
| Name |
|---|
| Sistemas Integrals Consulting |
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 total number of observations is 9,926 in the household dataset and 62,054 in the 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.
"Solomon Islands, High Frequency Phone Survey Q2 2023 to Q3 2024, 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 Group | dnaidoo@worldbank.org |
Metadata production
DDI_SPC_SLB_2023_HFPS-Q2_v01_M_v01_A_PUF
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Statistics for Development Division | SDD | Pacific Community | Documentation of the study |
2025-03-19
Metadata version
Version 01 (March 2025): This is the first attempt at documenting the first continuous data collection of Quarter 2 2023 to Quarter 3 2024 of Solomon Islands. Done by Statistics for Development Division at Noumea, New Caledonia.