This is the second Household Income and Expenditure Survey conducted by Fiji Islands Bureau of Statistics (FIBoS), the first HIES was conducted in 2002-03. In 2002-03 and 2008-09 surveys similar sampling methodology was used.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
The 2008 Fiji Household Income and Expenditure Survey covered the following topic:
- Demographic particulars and economic activity status
- Housing particulars
- Household and other bills
- Expenditure on household utilities
- Expenditure on education, health, religion culture and holidays, etc
- Housing tenure rents and other maintenance costs
- Land purchase for residential or farming purposes
- Outright purchase of durable
- Installment agreement or hire purchase on consumer durables
- Outright purchase of consumer semi-durables
- Installment agreement or hire purchase on consumer semi-durables
- Household cash expenditure
- Consumption of home produced commodities
- Goods and services taken from your business
- Good and services obtained from your employer
- Gifts of cash or goods and services received
- Gifts of cash or good and services given
- Household income, primary income
- Non-primary income
Producers and sponsors
Fiji Islands Bureau of Statistics (FIBoS)
Government of Fiji
Government of Fiji
Funding the study
A two-stage sampling strategy was used. In the first stage, the frame was divided into 7 strata and representative samples of Urban and Rural Enumeration Areas were then selected from these strata.
Within each stratum Enumeration Areas (EAs) or Primary Sampling Unit (PSU) from the frame were selected with probability proportional to size, measured in terms of the total households in the frame. Within each EA a fixed number of households (hh) were then selected by systematic random sampling. The final HIES sample then selected 10 households from each selected EA.
The household weight for all the households in each selected EA was calculated as:
((Population of Stratum i) * (Listing number of households in EA)) / ((Frame population of EA) * (No of hh in sample) * (Number of EAs selected in stratum))
Dates of Data Collection
Data Collection Mode
Data Collection Notes
The Bureau conducted training programmes for enumerators and supervisors at its four centres, followed by examinations to select those qualified. The training covered conduct of interviews, as well as the content of the questionnaires.
Data collection was continuous over a 1-year period. For each survey, a sixth of the sample households was covered in a 2-month sub-round. In effect, there were six independent sub-samples for each survey. Each sub-round sample was distributed into lots to ensure data was collected continuously for the whole 1-year period.
Fieldwork arrangements were delegated to 4 field superintendents who put together their work plans, assigned the supervisors and enumerators, and ensured the regular accountable financing of their required activities, including travel, subsistence and fees.
The arrangements for the interview depended on the availability of the householder. For the diary the enumerators were required to visit the household daily for two weeks, to try to minimise omissions due to weaknesses in the recall.
The Enumerators were instructed to complete work in a selected EA within a time frame of 3 weeks. The first week was spent on listing all households in the EA and the following two weeks for gathering information on Schedule 2 (recurrent expenditure) Schedule 3 (2 week expenditure diary) and Schedule 4 (income).
While supervisors are normally required to check on enumerators on a daily basis by selecting households at random to confirm that the data recorded was actually reported by the householder, this was not generally possible for the 2008-09 survey, because of budgetary constraints. It should be emphasised for future surveys that such checks improve the data collection practice of the enumerators, and of the quality of the survey results in general.
With expenditure usually being better reported than incomes, where the former exceeded the latter, enumerators were required to re-question the relevant households for possible omissions of incomes. Enumerators were also trained to probe further where they observed that households had income-earning assets but were not reporting any related incomes. Enumerators and Supervisors were also required to check the validity of any large incomes and expenditures reported.
Fiji Islands Bureau of Statistics
Government of Fiji
The 2008 Fiji Household Income and Expenditure Survey collected using 4 questionnaires (schedules).
Coding and data entry work was centralised to the 4 regional offices. Data was captured using CSPro and processed using SAS. Manually calculated subtotals and totals were used as control totals to check against data entry errors and consistency of the computer programmes.
Data Adjustments: Imputed Rents
In keeping with internationally accepted HIES methodology, the 2008-09 HIES estimated "imputed rents" - the estimated net value of owner-occupied dwellings which need to be added to the incomes (and expenditures) of all households which do not pay rents on the dwellings occupied.
Net Imputed Rent = Gross Imputed Values (estimated from the regressions) less the Imputed Cost of Owned Houses.
The "Imputed Cost of Owned Houses" was estimated as an aggregate percentage (21.9%) of Gross Imputed Values, representing Actual Repairs and Maintenance plus Interest Component of Installment payments plus Property Rates on owner-occupied houses.
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Fiji Islands Bureau of Statistics (FIBoS). Household Income and Expenditure Survey 2008-2009 (HIES). Ref. FJI_2008_HIES_v01_M. Dataset downloaded from [source] on [date].
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.