Abstract

This is the fourth Labor Force Survey of Tonga. The first one was conducted in 1990. Earlier surveys were conducted in 1990, 1993/94, and 2003 and the results of those surveys were published by the Statistics Department.

The objective of the LFS survey is providing information on not only well-known employment and unemployment as well as providing comprehensive information on other standard indicators characterizing the country labour market. It covers those age 10 and over in the whole Kingdom. Information includes age, sex, activity, current and usual employment status, hours worked and wages and in addition included a seperate Food Insecurity Experiences Survey (FIES) questionniare module at the Household Level.

The conceptual framework used in this labour force survey in Tonga aligns closely with the standards and guidelines set out in Resolutions of International Conferences of Labour Statistician.

Geographic coverage

National coverage.

There are six statistical regions known as Division's in Tonga namely Tongatapu urban area, Tongatapu rural area, Vava'u, Ha'pai, Eua and the Niuas.Tongatapu Urban refers to the capital Nuku'alofa is the urban area while the other five divisions are rural areas. Each Division is subdivided into political districts, each district into villages and each village into census enumeration areas known as Census Blocks. The sample for the 2018 Labour Force Survey (LFS) was designed to cover at least 2500 employed population aged 10 years and over from all the regions. This was made mainly to have sufficient cases to provide information on the employed population.

Analysis unit

• Households (for food insecurity module questionnaire)
• Individuals.

Universe

Population living in private households in Tonga. The labour force questionnaire is directed to the population aged 10 and above. Disability short set of questions is directed to all individuals age 2 and above and the food insecurity experience scale is directed to the head of household.

Kind of data

Sample survey data [ssd]

Sampling procedure

2018 Tonga Labour force survey aimed at estimating all the main ILO indicators at the island group level (geographical stratas). The sampling strategy is based on a two stages stratified random survey.

1. Computation of the survey parameters: Total sample size per strata, number of households to interview in each Primary Sampling Unit (PSU = census block) and number of PSUs to select The stratification of the survey is the geographical breakdown by island group (6 stratas Tongatapu urban, Tongatapu rural, Vava'u, Ha'apai, 'Eua, Niuas)
2. The selection strategy is a 2 stages random survey where: Random selection of census blocks within each
3. Census blocks are randomly selected in first place, using probability proportional to size

4. 15 households per block are randomly selected using uniform probability

5. The sampling frame used to select PSUs (census blocks) and household is the 2016 Tonga population census.

The computation of sample size required the use of: - Tonga 2015 HIES dataset (labour force section) - Tonga 2016 population census (distribution of households across the stratas) The resource variable used to compute the sample size is the labour force participation rate from the 2015 HIES. The use of the 2015 labour force section of the Tonga HIES allows the computation of the design effect of the labour force participation rate within each strata. The design effect and sampling errors of the labour force participation rate estimated from the 2015 HIES in combination with the 2016 household population distribution allow to predict the minimum sample size required (per strata) to get a robust estimate from the 2018 LFS.

Total sample size: 2685 households Geographical stratification: 6 island groups Selection process: 2 stages random survey where census blocks are selected using Probability Proportional to Size (Primary Sampling Unit) in the first place and households are randomly selected within each selected blocks (15 households per block) Non response: a 10% increase of the sample happened in all stratas to account for non-response Sampling frame: the household listing from the 2016 population census was used as a sampling frame and the 2015 labour force section of the HIES was used to compute the sample size (using labour force participation rate.

Sampling deviation

No major deviation from the original sample has taken place.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The 2018 Tonga Labour Force Survey questionnaire included 15 sections:

IDENTIFICATION SECTION B: INDIVIDUAL CHARACTERISTICS SECTION C: EDUCATION (AGE 3+) SECTIONS B & C: EMPLOYMENT IDENTIFICATION AND TEMPORARY ABSENCE (AGE 10+) SECTION D: AGRICULTURE WORK AND MARKET DESTINATION SECTION E1: MAIN EMPLOYMENT CHARACTERISTICS SECTION E2: SECOND PAID JOB/ BUSINESS ACTIVITY CHARACTERISTICS SECTION F: INCOME FROM EMPLOYMENT SECTION G: WORKING TIME SECTION H: JOB SEARCH SECTION I: PREVIOUS WORK EXPERIENCE SECTION J: MAIN ACTIVITY SECTION K: OWN USE PRODUCTION WORK FOOD INSECURITY EXPERIENCES GPS + PHOTO

The questionniares were developed and administered in English and were translated into Tongan language. The questionnaire is provided as external resources.

The draft questionnaire was pre-tested during the supervisors training and during the enumerators training and it was finally tested during the pilot test. The pilot testing was undertaken on the 27th of May to the 1st of June 2018 in Tongatapu Urban and Rural areas. The questionnaire was revised rigorously in accordance to the feedback received from each test. At the same time, a field operations manual for supervisors and enumerators was prepared and modified accordingly for field operators to use as a reference during the field work.

Cleaning operations

The World Bank Survey Solutions software was used for Data Processing, STATA software was used for data cleaning, tabulation tabulation and analysis.

Editing and tabulation of the data will be undertaken in February/March 2019 in collaboration with SPC and ILO.

Response rate

A total, 2,685 households were selected for the sample. Of these existing households, 2,584 were successfully interviewed, giving a household response rate of 96.2%.

Response rates were higher in urban areas than in the rural area of Tongatapu.

-1 Tongatapu urban: 97.30%
-2 Tongatapu rural: 93.00%
-3 Vava'u: 100.00% -4 Ha'pai: 100.00% -5 Eua: 95.20% -6 Niuas: 80.00% -Total: 96.20%.

Sampling error estimates

Sampling errors were computed and are presented in the final report.

The sampling error were computed using the survey set package in Stata. The Finite Population Correction was included in the sample design (optional in svy set Stata command) as follow: - Fpc 1: total number of census blocks within the strata (variable toteas) - Fpc 2: Here is a list of some LF indicators presented with sampling error

-RSE: Labour force population: 2.2% Employment - population in employment: 2.2% Labour force participation rate (%): 1.7% Unemployment rate (%): 13.5% Composite rate of labour underutilization (%): 7.3% Youth unemployment rate (%): 18.2% Informal employment rate (%): 2.7% Average monthly wages - employees (TOP): 12%.

-95% Interval: Labour force population: 28,203 => 30,804 Employment - population in employment: 27,341 => 29,855 Labour force participation rate (%): 45.2% => 48.2% Unemployment rate (%): 2.2% => 3.9% Composite rate of labour underutilization (%): 16% => 21.4% Youth unemployment rate (%): 5.7% => 12.1% Informal employment rate (%): 44.3% => 49.4% Average monthly wages - employees (TOP): 1,174 => 1,904.

Tonga TO: Labour Force data was reported at 41,220.000 Person in 2017. This records an increase from the previous number of 40,582.000 Person for 2016. Tonga TO: Labour Force data is updated yearly, averaging 37,049.500 Person from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 41,220.000 Person in 2017 and a record low of 32,066.000 Person in 1990. Tonga TO: Labour Force data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tonga – Table TO.World Bank.WDI: Labour Force. Labor force comprises people ages 15 and older who supply labor for the production of goods and services during a specified period. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.; ; Derived using data from International Labour Organization, ILOSTAT database and World Bank population estimates. Labor data retrieved in September 2018.; Sum; Data up to 2016 are estimates while data from 2017 are projections.

This is the fourth Labor Force Survey of Tonga. The first one was conducted in 1990. Earlier surveys were conducted in 1990, 1993/94, and 2003 and the results of those surveys were published by the Statistics Department.

The objective of the LFS survey is providing information on not only well-known employment and unemployment as well as providing comprehensive information on other standard indicators characterizing the country labour market. It covers those age 10 and over in the whole Kingdom. Information includes age, sex, activity, current and usual employment status, hours worked and wages and in addition included a seperate Food Insecurity Experiences Survey (FIES) questionniare module at the Household Level.

The conceptual framework used in this labour force survey in Tonga aligns closely with the standards and guidelines set out in Resolutions of International Conferences of Labour Statistician.

Version 01: Clean, labelled and de-identified version of the Master file.

The scope of the study includes:

-Household composition and individual characteristics of household members
-Literacy and education (age 3+)
-Training within the last 12 months (outside of the general eucation system)
-Employment main characteristics (10 years and older)
-Agriculture work
-Temporary absence
-Market activity
-Characteristics of the main paid job/business activity
-Characteristics of the second paid job/business activity
-Working time
-Job search
-Previous work experience
-Occupational injuries within the last 12 months
-Main activity
-Own use production work
-Food insecurity experiences (FIES) for Households only module

• Collection start: 2018
• Collection end: 2018

Tonga TO: Labour Force Participation Rate: Modeled ILO Estimate: % of Total Population Aged 15+ data was reported at 59.468 % in 2017. This records an increase from the previous number of 59.455 % for 2016. Tonga TO: Labour Force Participation Rate: Modeled ILO Estimate: % of Total Population Aged 15+ data is updated yearly, averaging 59.666 % from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 60.383 % in 2007 and a record low of 55.606 % in 1990. Tonga TO: Labour Force Participation Rate: Modeled ILO Estimate: % of Total Population Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tonga – Table TO.World Bank.WDI: Labour Force. Labor force participation rate is the proportion of the population ages 15 and older that is economically active: all people who supply labor for the production of goods and services during a specified period.; ; International Labour Organization, ILOSTAT database. Data retrieved in September 2018.; Weighted average; Data up to 2016 are estimates while data from 2017 are projections. National estimates are also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

Tonga TO: Labour Force Participation Rate: Modeled ILO Estimate: % of Total Population Aged 15-64 data was reported at 61.376 % in 2017. This records a decrease from the previous number of 61.378 % for 2016. Tonga TO: Labour Force Participation Rate: Modeled ILO Estimate: % of Total Population Aged 15-64 data is updated yearly, averaging 61.575 % from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 62.486 % in 2007 and a record low of 57.277 % in 1990. Tonga TO: Labour Force Participation Rate: Modeled ILO Estimate: % of Total Population Aged 15-64 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tonga – Table TO.World Bank.WDI: Labour Force. Labor force participation rate is the proportion of the population ages 15-64 that is economically active: all people who supply labor for the production of goods and services during a specified period.; ; International Labour Organization, ILOSTAT database. Data retrieved in September 2018.; Weighted average; Data up to 2016 are estimates while data from 2017 are projections. National estimates are also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

Tonga TO: Labour Force Participation Rate: Modeled ILO Estimate: Ratio of Female to Male data was reported at 60.881 % in 2017. This records an increase from the previous number of 60.858 % for 2016. Tonga TO: Labour Force Participation Rate: Modeled ILO Estimate: Ratio of Female to Male data is updated yearly, averaging 60.394 % from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 60.881 % in 2017 and a record low of 47.585 % in 1990. Tonga TO: Labour Force Participation Rate: Modeled ILO Estimate: Ratio of Female to Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tonga – Table TO.World Bank: Labour Force. Labor force participation rate is the proportion of the population ages 15 and older that is economically active: all people who supply labor for the production of goods and services during a specified period. Ratio of female to male labor force participation rate is calculated by dividing female labor force participation rate by male labor force participation rate and multiplying by 100.; ; Derived using data from International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; Weighted Average; Data up to 2016 are estimates while data from 2017 are projections. National estimates are also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

Tonga TO: Labour Force Participation Rate: Modeled ILO Estimate: Aged 15-24 data was reported at 37.302 % in 2017. This records an increase from the previous number of 37.282 % for 2016. Tonga TO: Labour Force Participation Rate: Modeled ILO Estimate: Aged 15-24 data is updated yearly, averaging 38.208 % from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 43.685 % in 1990 and a record low of 36.212 % in 2011. Tonga TO: Labour Force Participation Rate: Modeled ILO Estimate: Aged 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tonga – Table TO.World Bank.WDI: Labour Force. Labor force participation rate for ages 15-24 is the proportion of the population ages 15-24 that is economically active: all people who supply labor for the production of goods and services during a specified period.; ; International Labour Organization, ILOSTAT database. Data retrieved in September 2018.; Weighted average; Data up to 2016 are estimates while data from 2017 are projections. National estimates are also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

Labour Force Participation Rate: Female: 5-Year Bands: Aged 30-34 data was reported at 61.421 % in 2023. This records a decrease from the previous number of 66.908 % for 2021. Labour Force Participation Rate: Female: 5-Year Bands: Aged 30-34 data is updated yearly, averaging 55.350 % from Dec 1966 (Median) to 2023, with 7 observations. The data reached an all-time high of 66.908 % in 2021 and a record low of 4.920 % in 1966. Labour Force Participation Rate: Female: 5-Year Bands: Aged 30-34 data remains active status in CEIC and is reported by International Labour Organization. The data is categorized under Global Database’s Tonga – Table TO.ILO.LFS: Labour Force Participation Rate: By Sex and Age: Annual.

Tonga Labour Force Participation Rate: Aggregate Bands: Aged 15-24 data was reported at 34.227 % in 2021. This records an increase from the previous number of 28.305 % for 2018. Tonga Labour Force Participation Rate: Aggregate Bands: Aged 15-24 data is updated yearly, averaging 36.395 % from Dec 1966 (Median) to 2021, with 8 observations. The data reached an all-time high of 42.970 % in 1990 and a record low of 28.305 % in 2018. Tonga Labour Force Participation Rate: Aggregate Bands: Aged 15-24 data remains active status in CEIC and is reported by International Labour Organization. The data is categorized under Global Database’s Tonga – Table TO.ILO.LFS: Labour Force Participation Rate: By Sex and Age: Annual.

Abstract

This research is an Indicator Survey conducted in Tonga from April 27 to Sept. 30, 2009, as part of the Enterprise Survey initiative. An Indicator Survey, which is similar to an Enterprise Survey, is implemented for smaller economies where the sampling strategies inherent in an Enterprise Survey are often not applicable due to the limited universe of firms.

The objective of the survey is to obtain feedback from enterprises on the state of the private sector as well as to help in building a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms. Through interviews with firms in the manufacturing and services sectors, the survey assesses the constraints to private sector growth and creates statistically significant business environment indicators that are comparable across countries.

Questionnaire topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, land and permits, taxation, business-government relations, and performance measures.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The whole population, or the universe, covered in the Enterprise Surveys is the non-agricultural economy. It comprises: all manufacturing sectors according to the ISIC Revision 3.1 group classification (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this population definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities-sectors.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for Tonga was selected using stratified random sampling. Two levels of stratification were used in this country: industry and establishment size.

Industry stratification was designed in the way that follows: the universe was stratified into manufacturing industries, and one services sector.

Size stratification was defined following the standardized definition for the rollout: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees). For stratification purposes, the number of employees was defined on the basis of reported permanent full-time workers. This seems to be an appropriate definition of the labor force since seasonal/casual/part-time employment is not a common practice, except in the sectors of construction and agriculture.

Regional stratification did not take place as only the main island of Tongatapu where the capital of Nuku'alofa is located. Tongatapu is also the largest island of Tonga's three island groups and is the home of the majority of the formal business community for the country.

Due to limited data sources available in Tonga on registered businesses, the final sample frame was obtained from a combined dataset obtained from the Tonga National Statistics Office. The list provided by the NSO was limited to including information on the sector and location of enterprises, with no details on the number of employees. Therefore, original sample counts were not able to be stratified by enterprise size. The modified sample frame was used to select the sample of establishments for the full survey. This database contained the following information: -Name of the firm -Contact details -Location -ISIC code.

Given the impact that non-eligible units included in the sample universe may have on the results, adjustments may be needed when computing the appropriate weights for individual observations. The percentage of confirmed non-eligible units as a proportion of the total number of sampled establishments contacted for the survey was 42% (139 out of 333 establishments). Breaking down by industry, the following numbers of establishments were surveyed: Manufacturing - 78, Services - 72.

Mode of data collection

Face-to-face [f2f]

Research instrument

The current survey instruments are available: - Services Questionnaire - Manufacturing Questionnaire - Screener Questionnaire.

The Services Questionnaire is administered to the establishments in the services sector. The Manufacturing Questionnaire is built upon the Services Questionnaire and adds specific questions relevant to manufacturing.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance.

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

Response rate

Complete information regarding the sampling methodology, sample frame, weights, response rates, and implementation can be found in "Description of Tonga Implementation 2009" in "Technical Documents" folder.

Abstract

Tonga Household Income and Expenditure Survey 2009 (HIES), undertaken by the Tonga Statistics Department during the period from 1 January 2009 to 31 December 2009. This is the second survey of its kind in Tonga. The last one was carried out in 2000/01, and the results were used in November 2002 to rebase the Consumer Price Index (CPI). A report from that survey was produced in December 2002, and where possible, results from this report will be made to be comparable to the previous report.

• To provide updated information for the expenditure item weights for the CPI;

• To provide some data for the components of National Accounts; and

• To provide information on the nature and distribution of household income and expenditure for planners, policy makers, and the general public.

Geographic coverage

National Coverage and Island Division.

Analysis unit

Private Households, individuals, Income and expenditure items.

Universe

The survey covered all members of the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample design was done in such a way that promoted estimates primarily at the national level, but also at the island division level. For that reason a higher sample fraction was selected in the smaller island divisions.

Rural Tongatapu received the smallest sample fraction (8.3%) as it had the highest population. On the other hand the Ongo Niua received the largest sample fraction (21.5%) as their population was the smallest. Overall a sample of roughly 10 per cent was selected for Tonga.

The sample was selected independently within each of the 6 target areas. Firstly, extremely remote areas were removed from the frame (and thus not given a chance of selection) as it was considered too expensive to cover these areas. These areas only represented about 3.5 per cent of the total population for Tonga, so the impact of their removal was considered very minimal.

The sampling in each area was then undertaken using a two-stage process. The first stage involved the selection of census blocks using Probability Proportional to Size (PPS) sampling, where the size measure was the expected number of households in that block. For the second stage, a fixed number (twelve) of households were selected from each selected census block using systematic sampling. The household lists for all selected blocks were updated just prior to the second stage of selection.

Given the sample was spread out over four quarters during the 2009 calendar year, every 4th selected census block was allocated to a respective quarter. To ensure an equally distribution of sample to each quarter, the number of census blocks selected for each of the six target group was made divisible by four. This therefore meant the sample size for each target group was adjusted so that it was divisible by (4*12)=48, as can be seen in Table 1 of Section 1 of the survey report.

Mode of data collection

Face-to-face [f2f]

Research instrument

There were 4 main survey schedules used to collect the information for the survey were published in English: 1) Household Questionnaire 2) Individual Questionnaire - Part 1 3) Individual Questionnaire - Part 2 4) Individual Diary (x2)

Household Questionnaire

This questionnaire is primarily used to collect information on large expenditure items, but also collects information about the dwelling characteristics. In total there are 14 sections to this uestionnaire which cover: 1 Dwelling Characteristics 2 Household Possessions 3 Dwelling Tenure 4 Construction of Dwellings 5 Household Bills 6 Transport Expenses 7 Major Consumer Durables 8 Education/Recreation 9 Medical & Health 10 Overseas Travel 11 Special Events 12 Subsistence Activity Sales 13 Remittances 14 Contributions to Church/Village/School As stated above, the first section is devoted to collecting information about key dwelling characteristics, whereas the second section collects information on household possessions. Sections 3-11, and Section 14, focus on expenses the household incurs, whereas Section 13 focuses on remittances both paid by and received by the household. Finally, Section 12 collects information from households about the income they generate from subsistence activities. This section is the main question collecting income from the household questionnaire, as was included here as it was considered more appropriate to collect this data at the household level. The front page of this Questionnaire is also used for collecting the Roster of Household Members.

Individual Questionnaire - Part 1

This questionnaire collects basic demographic information about each individual in the household, including: • Relationship to Household Head • Sex • Age • Ethnicity • Marital Status

Also collected in this form is information about health problems each individual may have encountered in the last 3 months, followed by education information. For the education section, if a person is currently attending an education institution, then current level is asked, whereas if the person attended an education institution but no longer attends, then the highest level completed is collected. The last main section of this form collects information about labour force and is only asked of individuals aged 10 years and above. These questions aim to classify each person in scope for this section as either: • In the Labour Force - Employed • In the Labour Force - Unemployed • Not in the Labour Force

Individual Questionnaire - Part 2

This questionnaire is focused on collecting information from individuals regarding their income. There are eight sections to this questionnaire of which six are devoted to income. They include: 1 Wages and Salary 2 Self-Employment
3 Previous Jobs
4 Ad-hoc Jobs 5 Pensions/Welfare Benefits 6 Other Income 7 Loan Information 8 Contributions to Benefit Schemes

As stated above, the first six sections of this questionnaire focus on income. Section 7 collects information pertaining to loans for i) households, ii) cars, iii) special events and iv) other, and finally the last question is an expense related question covering contributions to benefit schemes which was considered best covered at an individual level.

Individual Diary

The last form used for the survey was the Individual Diary which each individual aged 10 years and over was required to fill in for two weeks (two one-week diaries).

Each diary had 4 sections covering the following: 1) Items Purchased: This section had a separate page for each day and was for recording all items bought in a store, street vendors, market or any other place (including credit) 2) Home Grown/Produced Items: This section was for recording home grown/produced items consisting of items such as food grown at home or at the family plantation, self caught or gathered fish and homemade handicrafts and other goods grown and produced at home. Information is recorded for these items consumed by the household which they produced themselves, these items they gave away as a gift, and these items they received as a gift. 3) Gifts Given and Received: This section of the diary is for recording gifts given and received including both cash and purchased goods (but not home produced). If any member of the household receives a gift that meets this criteria during the diary keeping period from someone who is not a member of their household it is recorded here. 4) Winnings from Gambling: The last section of the Diary is for recording all winnings from gambling during the diary keeping period.

Cleaning operations

Batch edits in CSPro were performed on the data after data entry was completed. The batch edits were aimed at identifying any values falling outside acceptable ranges, as well as other inconsistencies in the data. As this process was done at the batch level, questionnaires were often referred to and manual changes to the data were performed to amend identified errors.

One significant problem which was identified during this process was the incorrect coding of phone card purchase to the purchase of actual phones. As there were many such cases, an automatic code change was applied to any purchase of phones which was less than $40 - recoding them to purchase of phone cards.

Response rate

The final Response Rates for the survey was high, which will assist in yielding statistically significant estimates. Across all six target groups the response rate was in excess of 95 per cent, with the exception of Ongo Niua who only reported 50 per cent. The reason the number was so low in the Ongo Niua was because this target area was only visited in the 2nd quarter, where half the total sample were enumerated (to make up for the sample loss in the first quarter), and was not visited again in quarter 3 and 4.

The reason behind the high response rates in other areas was due to the updated lists for selected census blocks excluding vacant dwellings. As such, it was mostly refusals that impacted on the final response rates.

Sampling error estimates

Sampling errors refer to those errors that are implicit in any sample survey, where only a portion of the population is covered. Non-sampling errors refer to all other types of error. These can arise at any stage of the survey process. Examples of activities that are likely to increase the level of non-sampling error are: failing to select a proper sample, poor questionnaire design, weak field supervision, inaccurate data entry, insufficient data editing, or failure to analyze or report on the data

The 2021 Tonga HIES is the new update of this kind, after the 2015/2016, 2009 & 2001 versions. This survey aims to provide indicators on Household Living Standard using monetary aspect (amount of income and expenditure), non-monetary aspect (calory consumed, assets own, imputed rents…) and more social approach (education, health, food security status…). Survey outputs have multiple uses in various domains such as public health (food nutrition analysis), economic development (poverty), system of National Account (consumption aggregates), and they represent a key source of information to populate many National SDGs.

Version 01: Cleaned, labelled and anonymized version of the Master file.

-HOUSEHOLD: Dwelling characteristics; Assets; Home maintenance; Vehicles; International trips; Domestic trips; Household services; Financial support; Other household expenditure; Ceremonies; Remittances; Food insecurity; Livestock and aquaculture; Agriculture; Legal services.
-INDIVIDUAL: Individual characteristics; Education; Health; Disability; Communication; Alcohol; Other individual expenses; Labour force; Fisheries and hunting; Handicraft.

• Collection start: 2021
• Collection end: 2021

Tonga TO: Labour Force: Female: % of Total Labour Force data was reported at 38.447 % in 2017. This records a decrease from the previous number of 38.515 % for 2016. Tonga TO: Labour Force: Female: % of Total Labour Force data is updated yearly, averaging 38.185 % from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 38.737 % in 2011 and a record low of 32.271 % in 1990. Tonga TO: Labour Force: Female: % of Total Labour Force data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tonga – Table TO.World Bank.WDI: Labour Force. Female labor force as a percentage of the total show the extent to which women are active in the labor force. Labor force comprises people ages 15 and older who supply labor for the production of goods and services during a specified period.; ; Derived using data from International Labour Organization, ILOSTAT database and World Bank population estimates. Labor data retrieved in September 2018.; Weighted average; Data up to 2016 are estimates while data from 2017 are projections.

Tonga TO: Unemployment with Basic Education: Male: % of Male Labour Force data was reported at 1.853 % in 2021. This records a decrease from the previous number of 2.046 % for 2018. Tonga TO: Unemployment with Basic Education: Male: % of Male Labour Force data is updated yearly, averaging 1.853 % from Dec 2016 (Median) to 2021, with 3 observations. The data reached an all-time high of 2.046 % in 2018 and a record low of 1.142 % in 2016. Tonga TO: Unemployment with Basic Education: Male: % of Male Labour Force data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tonga – Table TO.World Bank.WDI: Employment and Unemployment. The percentage of the labor force with a basic level of education who are unemployed. Basic education comprises primary education or lower secondary education according to the International Standard Classification of Education 2011 (ISCED 2011).;International Labour Organization. “Education and Mismatch Indicators database (EMI)” ILOSTAT. Accessed January 07, 2025. https://ilostat.ilo.org/data/.;Weighted average;

Abstract

Household Income and Expenditure Survey (HIES) collects a wealth of information on household income and expenditure, such as source of income by industry, HH expenditure on goods and services, and income and expenditure associated with subsistence production and consumption. In addition to this, HIES collects information on sectoral and thematic areas, such as education, health, labour force, primary activities, transport, information and communication, transfers and remittances, food expenditure (acquisition) and gender.

The Pacific Islands regionally standardized HIES instruments and procedures were adopted by Tonga Statistics Department (TSD) for the 2015/2016 HIES. These standards, were designed to feed high-quality data to HIES data end users for: deriving expenditure weights and other useful data for the revision of the CPI, supplementing the data available for use in compiling official estimates of various components in the System of NA, supplementing the data available for production of the balance of payments; and gathering information on poverty lines and the incidence of poverty in Tonga.

The 2015/2016 HIES was conducted to update the 2009 HIES data and aimed to estimate the total amount HH spent and earnt over the past 12 months at the national and island group level (total expenditure and income).

Geographic coverage

National coverage.

Analysis unit

Individuals and Households.

Universe

Household Income and Expenditure Survey (HIES) covered all persons who were considered to be usual residents of private dwellings (must have been living in Tonga for a period of 12-months, or have intention to live in Tonga for a period of 12-months in order to be included in the survey).

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2 stages sample method used in the 2015 Household Income and Expenditure Survey (HIES) aims to select randomly: Census blocks (with probability proportional to size - each blocks will have a different probability of selection) - based on the 2011 population census; and households (HHs) (within each selected blocks all the HHs have the same probability of selection) - based on a update of the HH listing conducted by the HIES field team.

To make the probability of selection more even, some small census blocks were merged and some large census blocks split. There's more detail in the methodological report on this process. Before each round, the field teams updated the HH listing in each randomly selected block (stage 1 sample selection) and, after the listing was updated, the team randomly selected 18 HHs, which were 12 HHs as primary target HHs to interview; and 6 HHs in case that a primary selected HH cannot participate and a replacement is needed (e.g., refusal, absence, etc.) - this is done in order to achieve a high response rate.

Sampling deviation

Two-stage selection is used in Tongatapu (urban and rural), Vava’u, Ha’apai and ‘Eua, with the selection of census blocks (merged and split) in the first stage and the selection of households (HHs) in the second stage. HHs in Ongo Niua were selected directly from the updated HH listing (one-stage).

Mode of data collection

Face-to-face [f2f]

Research instrument

The use of a common questionnaire developed by the Statistics for Development Division (SDD) of the Pacific Community (SPC) was adopted by Tonga Statistics Department (TSD) to conduct Household Income and Expenditure Survey (HIES) 2015. Addition to the 4 Modules was a section on Deprivation.

4 modules to collect socio-demographic information, and expenditure and income; and o a two-week diary to collect daily expenditure, gifts received and home produced items Four modules are completed by paper-based personal interview, including: 1. Demographic information – characteristics of household (HH) members, including activity and education profile; 2. Household characteristics and expenditure (Housing characteristics, Housing tenure expenditure, Utilities and communication...etc); 3. Individual expenditure (Education, Health, Clothing, Communication...etc); 4. Individual and HH income (Wages and salaries, Agricultural and Forestry activities, Fishing, gatehring and hunting activities...etc).

Depending on the information being collected, a recall period (ranging from the last 7 days to the last 12 months) is applied to various sections of the questionnaire.
The forms were completed by face-to-face interview, usually with the Household (HH) head providing most of the information, with other HH members being interviewed when necessary. The interviews took place over a 2-week period such that the HH diary, which is completed by the HH on a daily basis for 2 weeks, can be monitored while the module interviews take place.

The HH diary collects information on the HH’s daily expenditure on goods and services; and the harvest, capture, collection or slaughter of primary produce (fruit, vegetables and animals) by intended purpose (home consumption, sale or to give away).

The 4 Modules were published in English but with a Tongan version that was made available to enumerators to help them with the interview. For the diaries they were published in both Tongan and English which ever version that the household find easy to fill in.

Cleaning operations

A first set of edits was done on the raw data via questionnaire checks, which was the first set of corrections. A summary of findings includes: 1820 questionnaires retrieved from the field in which 17 households with no diaries were removed. The process for the manual cleaning included checking the following information in the questionnaire: Labour force section (waged job) declared in module 1 and salaries declared in module 4 (income section). Imputation of wages in households: 30011, 40176, 40190, 40097. Electricity connection and payment of electric bill (module 2). Imputation of electricity bill in households: 20290, 20302, 20304, 30051. Households who are using butane for cooking and payment for butane.Ages and relationship to the household head.Check all the government pension in the salary section. Check the remittances sent by household members who are currently picking fruits overseas (that have to be transferred in wages & salary section).Check if the household members who are in Australia/NZ for fruit picking have declared their resident status in the household accordingly (option 4). After the first clean of the raw data, 1803 valid questionnaires were kept.

Further edits that was done to the raw data set was done using the software STATA.

Response rate

The table below shows the response rates by strata: -Tongatapu - urban: 99.8% -Tongatapu - rura: 99.8% -Vava'u: 100.0% -Ha'apai: 94.3% -Eua: 96.4% -Ongo Niua: 99.0% -Total: 99%

Sampling error estimates

Standard error, the relative sampling errors (RSE) and 95 percentage confidence interval were calculated for the total household expenditure, total household consumption expenditure, total household non consumption expenditure, total household cash expenditure, total household subsistence expenditure, total household expenditure on COICOP division 1, total household net income, total household net cash income, total net wages and salary cash income and total net primary cash income by strata. At the national level the RSE calculated was of good quality however caution should be made at the strata level.

Details of the sampling errors are presented in the sampling errors appendix 2 of the report presented in the external resources.

Non-sampling errors cannot be readily measured, however it is worth noting the issues associated with non-sampling errors, including: both respondents and interviewers may not entirely understand the information required from the survey, which can result in misinterpretation of the question being asked and the incorrect response; enumerator and respondent fatigue, resulting in underreporting, especially in completion of the household (HH) diary; unwillingness to fully disclose information – especially in a small-island context - such as income and expenditure on some items (e.g., alcohol, tobacco and cash donations); the questionnaire being in English, which could be a second language for both the interviewers and respondents, and the need to complete a written diary (noting that: three-quarters of diaries were in Tongan; HHs were given the opportunity to complete a Tongan written diary; and enumerators could mostly converse in Tongan when required); and the inability to interview HHs members living abroad but remain dependent on the HH (e.g., students living in school dormitories) or are working to support the HH (e.g., seamen living on a ship), but who have not formed another HH outside of Tonga.

Tonga TO: Unemployment: Modeled ILO Estimate: Female: % of Female Labour Force data was reported at 1.594 % in 2017. This records an increase from the previous number of 1.556 % for 2016. Tonga TO: Unemployment: Modeled ILO Estimate: Female: % of Female Labour Force data is updated yearly, averaging 1.975 % from Dec 1991 (Median) to 2017, with 27 observations. The data reached an all-time high of 7.427 % in 2003 and a record low of 1.509 % in 2012. Tonga TO: Unemployment: Modeled ILO Estimate: Female: % of Female Labour Force data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tonga – Table TO.World Bank.WDI: Employment and Unemployment. Unemployment refers to the share of the labor force that is without work but available for and seeking employment.; ; International Labour Organization, ILOSTAT database. Data retrieved in September 2018.; Weighted average; Data up to 2016 are estimates while data from 2017 are projections. National estimates are also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

Tonga TO: Labour Force With Basic Education: % of Total Working-age Population data was reported at 56.016 % in 2021. This records an increase from the previous number of 50.059 % for 2018. Tonga TO: Labour Force With Basic Education: % of Total Working-age Population data is updated yearly, averaging 52.839 % from Dec 2016 (Median) to 2021, with 3 observations. The data reached an all-time high of 56.016 % in 2021 and a record low of 50.059 % in 2018. Tonga TO: Labour Force With Basic Education: % of Total Working-age Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tonga – Table TO.World Bank.WDI: Labour Force. The ratio of the labor force with basic education to the working-age population with basic education. Basic education comprises primary education or lower secondary education according to the International Standard Classification of Education 2011 (ISCED 2011).;International Labour Organization. “Education and Mismatch Indicators database (EMI)” ILOSTAT. Accessed January 07, 2025. https://ilostat.ilo.org/data/.;Weighted average;

Tonga TO: Labour Force With Intermediate Education: Male: % of Male Working-age Population data was reported at 70.061 % in 2021. This records an increase from the previous number of 66.939 % for 2018. Tonga TO: Labour Force With Intermediate Education: Male: % of Male Working-age Population data is updated yearly, averaging 70.061 % from Dec 2016 (Median) to 2021, with 3 observations. The data reached an all-time high of 83.943 % in 2016 and a record low of 66.939 % in 2018. Tonga TO: Labour Force With Intermediate Education: Male: % of Male Working-age Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tonga – Table TO.World Bank.WDI: Labour Force. The ratio of the labor force with intermediate education to the working-age population with intermediate education. Intermediate education comprises upper secondary or post-secondary non tertiary education according to the International Standard Classification of Education 2011 (ISCED 2011).;International Labour Organization. “Education and Mismatch Indicators database (EMI)” ILOSTAT. Accessed January 07, 2025. https://ilostat.ilo.org/data/.;Weighted average;

Tonga TO: Unemployment with Advance Education: Female: % of Female Labour Force data was reported at 3.372 % in 2021. This records a decrease from the previous number of 3.737 % for 2018. Tonga TO: Unemployment with Advance Education: Female: % of Female Labour Force data is updated yearly, averaging 3.554 % from Dec 2018 (Median) to 2021, with 2 observations. The data reached an all-time high of 3.737 % in 2018 and a record low of 3.372 % in 2021. Tonga TO: Unemployment with Advance Education: Female: % of Female Labour Force data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tonga – Table TO.World Bank.WDI: Employment and Unemployment. The percentage of the labor force with an advanced level of education who are unemployed. Advanced education comprises short-cycle tertiary education, a bachelor’s degree or equivalent education level, a master’s degree or equivalent education level, or doctoral degree or equivalent education level according to the International Standard Classification of Education 2011 (ISCED 2011).;International Labour Organization. “Education and Mismatch Indicators database (EMI)” ILOSTAT. Accessed January 07, 2025. https://ilostat.ilo.org/data/.;Weighted average;

Tonga TO: Labour Force Participation Rate: Modeled ILO Estimate: Female: Aged 15-24 data was reported at 25.845 % in 2017. This records a decrease from the previous number of 25.891 % for 2016. Tonga TO: Labour Force Participation Rate: Modeled ILO Estimate: Female: Aged 15-24 data is updated yearly, averaging 27.109 % from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 29.936 % in 1991 and a record low of 25.248 % in 2011. Tonga TO: Labour Force Participation Rate: Modeled ILO Estimate: Female: Aged 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tonga – Table TO.World Bank.WDI: Labour Force. Labor force participation rate for ages 15-24 is the proportion of the population ages 15-24 that is economically active: all people who supply labor for the production of goods and services during a specified period.; ; International Labour Organization, ILOSTAT database. Data retrieved in September 2018.; Weighted average; Data up to 2016 are estimates while data from 2017 are projections. National estimates are also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.