Hours worked in employment per week (information about this variable and its quality)

Description

Hours worked in employment 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, or professional practice, or
  • 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, or
  • had a job or business they were temporarily absent from.

Hours worked is derived by summing the number of hours worked in a main job, and number of hours worked in all other jobs for pay, profit or income.

The key variable derived from hours worked in employment per week is:

  • work and labour force status.

Statistics

Representation

Variable Details

Other Variable Information

Priority level

Priority level 2

We assign a priority level to all census variables: 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 variable. Priority 2 variables cover key subject populations that are important for policy development, evaluation, or monitoring. These variables are given second priority in terms of quality, time, and resources across all phases of a census.

The priority level for hours worked in employment per week remains the same as 2013.

Quality Management Strategy and the Information by variable for hours worked in employment per week (2013) have more information on the priority rating.

Overall quality rating for 2018 Census

Moderate quality

Data quality processes section below has more detail on the rating for this variable.

The External Data Quality Panel has provided an independent assessment of the quality of this variable and has rated it as moderate/poor quality. 2018 Census External Data Quality Panel: Assessment of Variables has more information.

Subject population

Employed census usually resident population aged 15 years and over.

‘Subject population’ means the people, families, households, or dwellings to whom the variable applies.

How this data is classified

Hours worked in employment per week - standard classification (3 numeric)V2.0.0

Hours worked is a flat classification with single hour categories ranging from 1 to 168 hours.

0001 1 Hour Worked

0002 2 Hours Worked

::

:: 0167 167 Hours Worked

0168 168 Hours Worked

9999 Not elsewhere included

The not elsewhere included category contains the residual categories ‘Response unidentifiable’ and ‘Not stated’.

This classification is used for hours worked at main job, hours worked in all other jobs, and total hours worked.

The classification of hours worked in employment per week in the 2018 Census is consistent with the classification used in the 2013 and 2006 Censuses.

The Standards and Classifications page provides background information on classifications and standards.

Question format

Hours worked per week is derived from:

  • hours worked in main job
  • hours worked in all other jobs for pay, profit or income.

Both are found on the individual form (question 37 on the paper form). The hours from each source are summed to produce a weekly total.

Stats NZ Store House has samples for both the individual and dwelling paper forms.

There were no differences between the wording or question format in the online and paper versions of this question. However, there were differences between the modes of collection (paper and online form).

On the online individual 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.

On the paper individual form:

  • respondents outside the subject population could answer the question. These will be filtered out by using the correct subject population.

How this data is used

Outside Stats NZ

  • Used by organisations in policy formation such as government departments, research institutes, and local government.

Within Stats NZ

  • Used in official productivity statistics.

2018 data sources

We used alternative data sources for missing census responses and responses that could not be classified or did not provide the type of information asked for. Where possible, we used responses from the 2013 Census, administrative data from the Integrated Data Infrastructure (IDI), or imputation. The table below shows the breakdown of the various data sources used for this variable.

2018 Hours worked in employment per week – employed census usually resident population aged 15 years and over
Source Percent
Response from 2018 Census 81.3 percent
2013 Census data 0.0 percent
Administrative data 0.0 percent
Statistical imputation 18.7 percent
No information 0.0 percent
Total 100 percent
Due to rounding, individual figures may not always sum to the stated total(s)  

The ‘no information’ percentage is where we had evidence a person in the subject population exists (through either census forms or admin enumeration) but were not able to source hours worked in employment per week data for them.

Please note that when examining hours worked in employment per week data for specific population groups within the subject population, the percentage that is from statistical imputation may differ from that for the overall subject population.

Missing and residual responses

‘No information’ in the data sources table is the percentage of the subject population coded to ‘not stated’. In previous censuses, non-response was the percentage of the subject population coded to ‘not stated.’

In 2018, the percentage of ‘not stated’ is zero due to the use of the additional data source described above.

Percentage of ‘not stated’ for the employed census usually resident population aged 15 years and over:

  • 2018: 0.0 percent
  • 2013: 4.1 percent
  • 2006: 5.1 percent.

In 2018, there were no other residual responses remaining in the data. In output for previous censuses, responses that could not be classified or did not provide the type of information asked for were grouped with ‘not stated’ and classified as ‘not elsewhere included’.

Percentage of ‘not elsewhere included’ for the employed census usually resident population aged 15 years and over:

  • 2018: 0.0 percent
  • 2013: 4.5 percent
  • 2006: 7.7 percent.

2013 Census data user guide provides more information about non-response in the 2013 Census.

Data quality processes

Overall quality rating: Moderate quality

Data was evaluated to assess whether it meets quality standards and is suitable for use.

Three quality metrics contributed to the overall quality rating:

  • data sources and coverage
  • consistency and coherence
  • data quality.

The lowest rated metric determines the overall quality rating.

Data quality assurance for 2018 Census provides more information on the quality rating scale.

Data sources and coverage: Moderate quality

We have assessed the quality of all the data sources that contribute to the output for the variable. To calculate a 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:

  • 98–100 = very high
  • 95–<98 = high
  • 90–<95 = moderate
  • 75–<90 = poor
  • <75 = very poor.

The only alternative data source used for hours worked was statistical imputation, which was mostly comparable to 2018 Census responses. The proportions of responses from received forms and statistical imputation contributed to the score of 0.94, determining the moderate quality rating.

Quality rating calculation table for the sources of hours worked in employment per week data –
employed census usually resident population aged 15 years and over
Source Rating Percent of total Score contribution
2018 Census form 1.00 81.31 0.81
Imputation
Donor’s 2018 Census form 0.70 18.69 0.13
No Information 0.00 0.00 0.00
Total 100.00 0.94
Due to rounding, individual figures may not always sum to the stated total(s) or score contributions.      

Data sources, editing, and imputation in the 2018 Census has more information on the Canadian census edit and imputation system (CANCEIS) that was used to derive donor responses.

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 that makes sense due to real-world change or incorporation of other sources of data.

Checks against 2013 and 2006 data showed only minor inconsistencies with the 2018 data at the territorial authority level, mainly for ‘hours worked in other jobs’ above 50 hours a week. These inconsistencies are largely due to improvements to the 2018 Census data through the increased use of online responses, and the introduction of new quality edits. Some care therefore needs to be taken when directly comparing ‘hours worked in other jobs’ with previous census data. However, even with these minor inconsistencies, data can still be compared with previous censuses.

Data quality: High quality

The data quality checks for hours worked in employment per week included edits for consistency within the dataset and cross-tabulations to the regional council level of geography.

Census tests showed some respondents interpreted ‘hours worked in all other jobs’ as asking for total hours worked across their main job and other jobs. A new 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 was introduced to ensure hours worked in main job was greater than hours worked in other jobs. The hours were switched if a respondent had listed that they worked more hours in other jobs than in their main job.

Recommendations for use and further information

While new imputation methods have been used to produce the 2018 Census data, the overall quality of the data is moderate and comparable with 2006 and 2013 data.

However, when using this data you should be aware that:

  • data has been assessed to be consistent at the regional council and territorial authority level of geography. Some variation is possible at geographies below this level.
  • when examining data at geographies below the national level, the proportion of imputed CANCEIS data may differ from that of the overall subject population
  • there are some inconsistencies with time series for hours worked above 50 hours a week. This is likely due to the implementation of new edits aimed at reducing respondent error and improving quality of the data, although there may be an element of real-world change.
  • while the data collected from the individual forms is high quality, there is a large percentage of data imputed from CANCEIS resulting in an overall quality rating of moderate.

Comparisons with other data sources

Although surveys and sources other than the census collect hours worked data, data users are advised to familiarise themselves with the strengths and limitations of the sources before use.

Key considerations when comparing hours worked information from the 2018 Census with other sources include:

  • census is a key source of information on hours worked 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 sources Household Labour Force Survey (HLFS), Household Economic Survey (HES), and General Social Survey (GSS) measuring this variable are only based upon a sample of the population.

Contact our Information Centre for further information about using this variable.

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