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Information about the Quarterly Employment Survey |
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Availability
| Valid From: .. | 02/20/1989 |
| To: .. | Ongoing |
| Frequency: .. | Quarterly |
Design
Purpose: The purpose of the Quarterly Employment Survey (QES) is to measure quarterly estimates of the changes in and levels of average hourly and average weekly (pre-tax) earnings, average weekly paid hours, and the number of filled jobs.
General Information ..Target Population
All business locations belonging to economically significant enterprises in surveyed industries with employees.
An economically significant enterprise is one which meets at least one of the following criteria:
- has greater than $30,000 annual GST expenses or sales;
- has at least three for its rolling mean employment (rolling mean employment is the average employee count over the past 12 months);
- is in a GST-exempt industry except residential property leasing and rental;
- is part of a group of enterprises;
- is a new GST registration that is compulsory, special or forced;
- is registered for GST and is involved in agriculture or forestry.
Surveyed industries exclude the following...
| Industries excluded from the QES are: | ANZSIC |
| Agriculture | A01 |
| Services to agricultural | A02 |
| Commercial fishing | A04 |
| International sea transport | I6301 |
| Residential property owners | L7711 |
| Foreign government representation | M813 |
| Private households employing staff | Q97 |
| |
The population is broken into single and multi-geographical unit enterprises, with the eligible population being all geographical units with any full-time equivalent employees. ( a full-time equivalent employee is either one full-time employee or two part-time employees)
Statistical Unit
The statistical unit is the geographical unit or individual business location.
Selection Unit
Enterprise units on the Business Frame (BF) are the selection units. All in-scope geographic units attached to selected enterprises are included in the sample.
Collection Unit
The geographic unit is the reporting unit.
Sample Size
The February, May, August and November quarterly surveys, which are based on stratified random samples, cover approximately 18,000 geographic units.
Prior to 2004, each February, a larger sample was surveyed with approximately 47,500 geographic units.
Key Firms
Key firms are currently defined as those that contribute at least 0.03% of total male (female) FTEs, or that if removed from the data would cause at least 0.015% relative change in any of the following:
- * average ordinary time weekly paid hours for males
* average ordinary time hourly earnings for males
* average ordinary time weekly earnings for males
* average ordinary time weekly paid hours for females
* average ordinary time hourly earnings for females
* average ordinary time weekly earnings for females
* average ordinary time weekly paid hours for the public sector
* average ordinary time hourly earnings for the public sector
* average ordinary time weekly earnings for the public sector
* average ordinary time weekly paid hours for the private sector
* average ordinary time hourly earnings for the private sector
* average ordinary time weekly earnings for the private sector
Output Variables
Output variables are pieces of individual information that can be extracted from the survey/output data. Often output variables can be cross tabulated with other output variables, for example sales by industry classification. The list below contains all current and past output variables which have been released for this survey/output.
| Variable Name | Description |
| Average ordinary time hourly earnings | Ordinary time payout divided by ordinary time hours. |
| Average ordinary time weekly earnings | Ordinary time payout divided by full-time equivalent employees. |
| Average overtime hourly earnings Average overtime weekly earnings | Overtime payout divided by overtime hours. Overtime payout divided by full-time equivalent employees. |
| Average total weekly earnings | Total earnings (ordinary time plus overtime payout) divided by full-time equivalent employees. |
| Average total hourly earnings | Total earnings (ordinary time plus overtime payout) divided by total hours (ordinary time plus overtime hours). |
| Total surveyed employment | Estimated number of full-time and part-time employees in business locations which employ more than two full-time equivalent employees. As an FTE measure, surveyed employment is published as the “earnings data population”; as an actual number, surveyed employment is also known as “in-scope employment”. |
| Filled jobs | The number of full-time employees + part-time employees + working proprietors as measured by the QES. Note that working proprietors in businesses with no employees are outside the scope of the survey and so are not included in the estimate of filled jobs. |
| Average ordinary time weekly hours paid for | Ordinary time hours divided by full-time equivalent employees. |
| Average overtime weekly hours paid for | Overtime hours divided by full-time equivalent employees. |
| Average total weekly hours paid for | Total hours (ordinary time hours plus overtime hours) divided by full-time equivalent employees |
In addition to totals by all industries, Statistics New Zealand produces these variables by male and female individually, and by industry (using both NZSIC and ANZSIC industrial classifications), region and sector categories:
Note for the average weekly earnings and average weekly paid hours variables, Statistics New Zealand also produces a full set of series using total employees, rather than full-time equivalent employees, as the denominator.
Changes in Output Variables over time
Guide to Interpreting Data
Summary of Changes to Survey/Output ..1957-1979 Employment Information Survey
From 1946 to 1979, the Department of Labour conducted a half-yearly full coverage Employment Information Survey. This was conducted twice yearly with a reference to a pay week in April and October. The survey covered all establishments with a minimum of two full-time equivalent persons.
A number of changes have occurred over this period which brought the survey closer to the current QES. They included:
- Hours and earnings data by sex became available in 1973;
- The definition of working proprietors was changed in 1973 to include surveyable professional practitioners (e.g. accountants, dentists) and female working proprietors in the construction industry;
- Before 1973, ordinary time hours referred to actual hours worked, while overtime hours referred to the actual number of overtime hours worked. Since 1973, ordinary time hours have been defined as the number of hours represented by the ordinary wage payments;
- Before October 1979, average total weekly earnings were calculated using the divisor “full-timers plus part-timers”, in contrast to the current divisor “full-timers plus half of part-timers”.
- The division line between part-time and full-time employees was changed in February 1980; before 1980, a part-time employee was one who worked fewer than three-quarters of the scheduled ordinary time hours for that industry; A part time employee is now someone who is employed for less than thirty hours each week.
- Several modifications were made to the classification of the organisations constituting the Government sector, and to the methods of capturing computer payroll information for public servants and teachers;
1980-1988 Introduction of the Quarterly Employment Survey
In 1980, the Department of Labour introduced the Quarterly Employment Survey. The data was collected for a pay week in February, May, August and November. The February survey in each year was a full coverage survey, while the remaining three were sample surveys.
This survey covered businesses with two or more persons (part-timers, full-timers and/or working proprietor) engaged. The Department of Labour's sampling frame was its own Central Register of Businesses, considered to be less comprehensive than the Business Frame (the SNZ's sampling frame). In addition to those industries excluded from the current survey, waterfront work and the police force were excluded from the Department of Labour survey.
The Department of Labour conducted the survey until the results of the November 1988 survey were published.
1989 Statistics New Zealand Responsibility
In February 1989, the survey became the responsibility of Statistics New Zealand. The survey has been conducted on a quarterly basis, collecting data referring to the pay-weeks ending on, or immediately before, the 20th of the month in February, May, August and November, and according to the present methodology. In order to have provided a consistent long-term historical series, some of the Department of Labour data back to 1982 was revised according to the new survey coverage. Some adjusted estimates were published for 1987 and 1988.
1999 SNZ makes further changes to the QES
Several changes were made to the QES from the November 1999 release onward. These changes had become necessary because of the age of the current sample, and because of a desire to ensure the survey's statistics are more representative of the New Zealand economy. The changes included:
- Re-designing and re-weighting sample.
- Reducing the size of the quarterly (monitor) samples and the annual (analytical) census. While the sample sizes reduced slightly, accuracy at the aggregate level was not compromised due to improved sample design techniques.
- No longer having a census in February. This was replaced by a large (analytical) sample. The names of the new samples (ie monitor and analytical) give a clue as to their intended use - the quarterly monitor samples is intended for quarterly monitoring of national-level aggregates, while the annual analytical database is intended for more in-depth analysis.
- Extending the coverage to include small businesses (i.e. those with fewer than 2.5 full-time equivalent employees).
- More accurate and timely estimates of filled jobs (employees plus working proprietors), since they are produced directly from the quarterly monitor. Previously they were produced as provisional results subject to revision annually after the February census.
- The survey no longer produces estimates based on the New Zealand Standard Industrial Classification (NZSIC). Instead, the survey has moved to Australian New Zealand Standard Industrial Classification(ANZSIC) based estimates. (Note that ANZSIC based estimates are available from 1994 onwards).
2001 Introduction of modelled component
From the May 2001 quarter (inclusive), the QES results contain a modelled component that improves the coverage of existing businesses that start employing staff, and accounts for the impact of annual frame updates. The results from May 1999 to February 2001 were revised to incorporate this improvement.
The survey population is comprised of businesses on the BF that have a nonzero employee indicator. Businesses on the BF that have started employing staff can only be represented by the survey sample if their employee indicator changes to a nonzero value. This indicator is only updated once a year from data collected in AFUS in February. However, it can be more than a year between the time a business on the BF begins employing staff, and the updating of its employee indicator. The contribution from these businesses is modelled before their AFUS updates takes effect on the BF.
2003 Changes in reference quarters
At the start of September 2003, the reference quarters for the QES were renamed to bring them into line with other Statistics New Zealand surveys. The February, May, August, and November quarters became March, June, September, and December quarters. The survey reference periods did not change; it remains the pay week ending on or immediately before the 20th of the middle month of the quarter.
2003 New business size indicator
In October 2003, employee count replaced FTE as the business size indicator in the sample design. The size indicator is used to identify businesses on the BF with paid employees. An employee count size indicator enables the survey to operate under the new BF maintenance environment.
Prior to October 2003, a business was included in the QES population if it had at least one paid FTE. From October 2003 onwards, it must have an employee count of at least one. The resulting operational change necessitated an update of the sample which improved its representativeness. Consequently there was no need to retain the modelled component. It also meant revising previously published results from quarters December 1999 to June 2003 (inclusive). The revisions were released on 22 October 2003.
The September 2003 quarterly release will be the first based on employee count as the size indicator.
2004 Sample size reduction
The use of EC in the sample design resulted in a significant sample size increase. In the June 2004 quarter, the sample was reduced by about 1,700 business locations. This had a negligible effect on the accuracy of the key published estimates.
Usage and Limitations of the Data ..Usage
Statistics from the QES are currently used in a number of significant ways:
- Private sector hourly earnings data are used by the Reserve Bank in their economic models to indicate wage inflation variable.
- Ordinary time weekly earnings are used as the benchmark in setting the floor for National Superannuation levels, and for setting stand-down periods for unemployment benefits.
- Total paid hours are used to monitor economic activity and used to calculate labour productivity.
- Gross payout figures are used as the measure of compensation of employees in GDP measurement.
- Changes in average earnings, hours and jobs are all used as economic indicators, i.e. they indicate the health of the economy.
- Gender pay differences are used to monitor the gender pay gap.
Limitations
For some large organisations, data is only obtained for all geographic units belonging to an enterprise. To put it in a form that is compatible with the requirements of the QES, it is then apportioned over all the eligible geographic units of the organisation. Apportionment primarily affects the quality of regional estimates. Apportionment assumes that people in different regional locations receive the same payout, whereas this may not be true in reality.
Estimates based on smaller strata, for example estimates at the territorial local authority level, are generally subject to higher sample errors.
Related Data Sources ..Annual Business Frame Update Survey
Household Labour Force Survey
NZ Income Survey
Sampling Errors ..Sampling error is a measure of variablility that occurs by chance because a sample of eligible businesses, rather than the entire population, is surveyed. The magnitude of the sampling error is controlled by the size of the sample and the use of statistically sound selection techniques.The accuracy levels ( sampling error) at the 95% confidence level of publishing variables can be obtained by contacting QES team.
Non-sampling errors Non-sample error includes possible errors in reporting by respondents, and errors in processing data. For example, if a respondent fails to note that they have supplied fortnightly data instead of weekly data, or the non-response imputation system has been incorrectly programmed, or the data is supplied correctly but is mis-punched at data entry. Input and output editing and sample monitoring procedures attempt to correct these types of error.
Caveats on Release ..The above confidentiality rules must be applied to all data to be publicly released. Regional data has an added complication in relation to quality, due to apportionment.
Customised Output
Available on request from information Consultancy services.
Catalogue & Reference Numbers
Classifications | Classification Versions | Classification Type |
ANZSIC96 - Australian and New Zealand Standard Industrial Classification - NZ Version 1996 | V4.1 | NZ Standard |
NZISC96 - New Zealand Standard Institutional Sector Classification 1996 | V1.0 | NZ Standard |
REGC06 - Regional Council 2006 | V1.0 | NZ Standard |
MB06 - Meshblock 2006 | V1.0 | NZ Standard |
TA06 - Territorial Authority 2006 | V2.0 | NZ Standard |
SEX - Sex - New Zealand Standard Classification | V1.0 | NZ Standard |
Glossary of Terms
| Term | Description |
| Working proprietor | a) A sole proprietor or partner who is actively engaged in the business. b) A shareholder in a limited liability company actively engaged in its management and classified by the respondent as a working proprietor consistently across survey periods. |
| Employee | Paid workers in a business who are not working proprietors. Respondents are asked to include employees temporarily absent from work (e.g. sick, on leave, on strike, temporarily laid-off), whether paid or not. Employees working for commission are included, as are managers and executives (where they are not working proprietors). |
| Full-time/part-time | Full-time employees are those who regularly work 30 hours or more per week, while part-time employees regularly work fewer than 30 hours per week. |
| Ordinary time payout | The gross total payout to all employees, less any overtime payments. All shift, penal and other allowances are included, as are bonuses, paid leave, and commissions if they are earned in the payweek. Payments not earned in the payweek (e.g. back-pay, redundancy, severance pay) and non-taxable payments, such as tool money, are excluded. Where a payment is for a period of longer than the survey payweek, only the proportion that relates to the survey reference payweek is counted. |
| Overtime payout | The gross total payout for overtime hours worked by employees in the survey payweek. |
| Ordinary time hours | The number of paid hours to which the ordinary time payout relates. Paid travelling time and hours of sick pay, holiday pay and other temporary absences are included. |
| Overtime hours | The number of paid hours to which the overtime payout relates. |
| Full- Time Equivalent Employee (FTE) | The number of full-time employees plus half the part time employees. |
Contact Details
| Customer Service E-mail Contact: | info@stats.govt.nz |
| |
| Survey Enquiries E-mail Contact: | fiona.edmonds@stats.govt.nz |
Liability
Statistics New Zealand gives no warranty that the information or data supplied contains no errors. However, all care and diligence has been used in processing, analysing and extracting the information. Statistics New Zealand shall not be liable for any loss or damage suffered by the customer consequent upon the use directly, or indirectly, of the information supplied in this product.