Quality Statement
Hours worked in employment per week is the total number of hours usually worked in employment each week by a person aged 15 years and over who:
- worked one hour or more for pay, profit, or payment in kind, in a job, business, farm, professional practice
- worked one hour or more without pay in work that contributed directly to the operation of a business, farm, or professional practice operated by a relative
- had a job or business they were temporarily absent from.
Hours worked in employment per week is derived using the sum of the hours worked in the main job and in all other jobs. It is one of the variables used to derive work and labour force status.
Moderate quality
Data quality processes section below has more detail on the rating.
Priority level 2
A priority level is assigned to all census concepts: priority 1, 2, or 3 (with 1 being highest and 3 being the lowest priority).
Hours worked in employment per week is a priority 2 concept. Priority 2 concepts cover key subject populations that are important for policy development, evaluation, or monitoring. These concepts are given second priority in terms of quality, time, and resources across all phases of a census.
The census priority level for hours worked in employment per week remains the same as 2018.
The 2023 Census: Final content report has more information on priority ratings for census concepts.
Employed census usually resident population count aged 15 years and over
‘Subject population’ means the people, families, households, or dwellings that the variable applies to.
Hours worked in employment per week is classified into the following categories:
Hours worked in employment per week – standard classification (3 numeric) V2.0.0 – level 1 of 2
Code | Category |
---|---|
0001 | 1 hour worked |
0002 | 2 hours worked |
0003 | 3 hours worked |
… | … |
0166 | 166 hours worked |
0167 | 167 hours worked |
0168 | 168 hours worked |
9999 | Not elsewhere included |
Hours worked in employment per week uses a 2-level hierarchical classification with level 1 categories presented in the above table. The level 1 category ‘Not elsewhere included’ contains the residual categories ‘Response unidentifiable’ and ‘Not stated’. Follow the link above the table to examine the classification in more detail.
This classification is used for hours worked at main job, hours worked in all other jobs, and total hours worked.
Hours worked in employment per week is primarily output in ranges using the classifications which are listed below:
The 2023 Census classification for hours worked in employment per week is consistent with that used in the 2018 Census.
Standards and classifications has more information on what classifications are, how they are reviewed, where they are stored, and how to provide feedback on them.
Hours worked in employment per week is derived from the individual form (question 40 on the paper form). The question includes the following two fields:
- hours usually worked in main job
- hours usually worked in all other jobs for pay, profit or income.
The wording directs respondents to provide a number to the nearest hour. Hours worked in main and other jobs are summed to derive a weekly total of usual hours worked.
There were differences in the way a person could respond between the modes of collection (online and paper forms).
On the online form:
- built-in routing functionality directed individuals to the appropriate questions. If a respondent indicated that they worked for pay or profit in the last 7 days, or that they usually work but were not working in the last 7 days, they were routed to the ‘hours worked’ question
- respondents could only enter whole numbers
- respondents could only enter values for hours worked in main job and all other jobs that sum to less than or equal to 168.
On the paper form:
- respondents outside the subject population could answer the question. These are filtered out by using the correct subject population
- respondents could enter decimal numbers which were then rounded
- respondents could enter values out of range which were resolved by using edits.
Data from the online forms may therefore be of higher overall quality than data from paper forms. However, processing checks and edits were in place to improve the quality of the paper form data.
Stats NZ Store House has samples for both the individual and dwelling paper forms.
Data-use outside Stats NZ:
- by organisations involved in policy making, such as government departments, research institutes, and local government
- to examine trends in employment and employment insecurity across different groups.
Data-use by Stats NZ:
- in official productivity statistics.
Alternative data sources were used for missing and residual census responses and responses that could not be classified or did not provide the type of information asked for. The table below shows the distribution of data sources for hours worked in employment per week.
Data sources for hours worked in employment per week, as a percentage of the employed census usually resident population count aged 15 years and over, 2023 Census | ||
---|---|---|
Source of hours worked in employment per week data | Percent | |
2023 Census response | 84.4 | |
Historical census | 0.0 | |
Admin data | 0.0 | |
Deterministic derivation | 0.0 | |
Statistical imputation | 15.6 | |
CANCEIS donor's response sourced from 2023 Census form | 15.6 | |
No information | 0.0 | |
Total | 100.0 | |
1. CANCEIS = imputation based on CANadian Census Edit and Imputation System
Note: Due to rounding, individual figures may not always sum to the stated total(s) or score contributions. |
Statistical imputation was used for records with missing or residual responses.
Editing, data sources, and imputation in the 2023 Census describes how data quality is improved by editing, and how missing and residual responses are filled with alternative data sources (admin data and historical census responses) or statistical imputation. The paper also describes the use of CANCEIS (the CANadian Census Editing and Imputation System), which is used to perform imputation.
Missing and residual responses represent data gaps where respondents either did not provide answers (missing responses) or provided answers that were not valid (residual responses).
Where possible, alternative data sources have been used to fill missing and residual responses in the 2023 and 2018 Censuses.
Percentage of ‘Not stated’ for the employed census usually resident population count aged 15 years and over:
- 2023: 0.0 percent
- 2018: 0.0 percent
- 2013: 4.1 percent
For output purposes, the residual category responses are grouped with ‘Not stated’ and are classified as ‘Not elsewhere included’.
Percentage of ‘Not elsewhere included’ for the employed census usually resident population count aged 15 years and over:
- 2023: 0.0 percent
- 2018: 0.0 percent
- 2013: 4.5 percent
Overall quality rating: Moderate
Data has been evaluated to assess whether it meets quality standards and is suitable for use.
Three quality metrics contribute to the overall quality rating:
- data sources and coverage
- consistency and coherence
- accuracy of responses.
The lowest rated metric determines the overall quality rating.
Data quality assurance in the 2023 Census provides more information on the quality rating scale.
Data sources and coverage: Moderate quality
The quality of all the data sources that contribute to the output for the variable were assessed. To calculate the data sources and coverage quality score for a variable, each data source is rated and multiplied by the proportion it contributes to the total output.
The rating for a valid census response is defined as 1.00. Ratings for other sources are the best estimates available of their quality relative to a census response. Each source that contributes to the output for that variable is then multiplied by the proportion it contributes to the total output. The total score then determines the metric rating according to the following range:
- 0.98–1.00 = very high
- 0.95–<0.98 = high
- 0.90–<0.95 = moderate
- 0.75–<0.90 = poor
- <0.75 = very poor.
While the level of census response was high for hours worked in employment per week data, the lack of other alternative sources, apart from statistical imputation, resulted in a score of 0.94, leading to a quality rating of moderate.
Data sources and coverage rating calculation for hours worked in employment per week data, employed census usually resident population count aged 15 years and over, 2023 Census | |||
---|---|---|---|
Source of hours worked in employment per week | Rating | Percent | Score contribution |
2023 Census response | 1.00 | 84.40 | 0.84 |
CANCEIS nearest neighbour imputation | 0.60 | 15.60 | 0.09 |
No information | 0.00 | 0.00 | 0.00 |
Total | 100.00 | 0.94 | |
1. CANCEIS = imputation based on CANadian Census Edit and Imputation System Note: Due to rounding, individual figures may not always sum to stated total(s) or score contributions. |
Consistency and coherence: High quality
Hours worked in employment per week data is consistent with expectations across nearly all consistency checks, with some minor variation from expectations or benchmarks which makes sense due to real-world change, incorporation of other sources of data, or a change in how the variable has been collected.
Trends are consistent with expected real-world change with some minor variation in ‘hours worked in all other jobs’ due to the small subject population of those who have two or more jobs.
Accuracy of responses: High quality
Hours worked in employment per week data has only minor data quality issues. The quality of coding and responses within classification categories is high. Any issues with the variable appear in a low number of cases (typically in the low hundreds).
Data shows high levels of accuracy of responses collected from both paper and online forms. The following factors had a minor impact on data accuracy:
- an edit removes ‘hours worked in all other jobs’ if both this question and ‘hours worked in main job’ are equal to or greater than 40 hours. However, it was not possible to determine if respondents had misunderstood the question as total hours, or if the number of hours listed in other jobs was correct. A second edit ensured hours worked in main job was greater than hours worked in all other jobs. The hours were switched if a respondent had listed that they worked more hours in other jobs than in their main job.
- a small level of respondent error, particularly among age groups 65+ years, was caused by respondents providing multiple answers, and people who were unemployed or not in the labour force answering questions about employment. While these types of responses were largely resolved through edits, in some cases accuracy can be less certain.
Hours worked in employment per week data can be used in a comparable manner to the 2018 and 2013 Censuses.
When using this data, users should be aware:
- 2023 Census hours worked in employment per week data shows very high consistency with the 2018 Census, and slightly less consistency with the 2013 Census due to the introduction of statistical imputation for missing information since the 2018 Census.
- a small level of respondent error remains in the data after consistency edits have been applied where some people aged 85 years and over who are not in the labour force responded to work questions and had a response or imputed value for hours worked in employment per week.
Comparison to other data sources
Although surveys and sources other than the census collect hours worked in employment per week data, data users are advised to become familiar with the strengths and limitations of the sources before use.
Key considerations when comparing hours worked in employment per week information from the 2023 Census with other sources include:
- census is a key source of information on hours worked in employment per week for small areas and small populations. Many other sources do not provide detail at this level.
- census aims to be a national count of all individuals in a population while other surveys (such as the Household Labour Force Survey, the Household Economic Survey, and the General Social Survey) measuring this variable are only based on a sample of the population.
To assess how this concept aligns with the variables from the previous census, use the links below:
- Hours worked in employment per week – 2018 Information by variable
- Hours worked in employment per week – 2013 Information by variable
Contact our Information centre for further information about using this concept.
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