The case study focuses on the development of the tourism monthly employment indicator series by Statistics New Zealand, which provides early insights into changes in the labour market, specifically in terms of filled jobs and gross earnings. The series was developed as part of Statistics New Zealand’s response to the COVID-19 pandemic to understand the impact of closed international borders on employment in tourism-related industries. The data covers various employment categories, including full-time and part-time employees, international residents, and self-employed individuals. The case study highlights the critical success factors and challenges faced in producing the tourism series monthly employment indicator series.
Using tax data to develop a monthly employment indicator in New Zealand
Abstract
The monthly employment indicator (MEI) series produced by Stats NZ was developed to provide an early indication of changes in the labour market in terms of filled jobs and gross earnings. The indicator series was first published in November 2019 just prior to the COVID-19 pandemic and was designed to complement New Zealand’s suite of labour market statistics. The key user demand for its development came from the Reserve Bank and the Ministry of Business, Innovation and Employment.
The MEI-tourism series was developed as part of Stats NZ’s response to the COVID-19 pandemic to understand the impact of closed international borders on employment in tourism-related industries. Customers have valued this early employment indicator to identify shifts in the labour market at such a detailed industry level. This sort of request would have historically been unable to be answered using the traditional labour market surveys of households in New Zealand.
The MEI series is created from pay as you earn (PAYE) data supplied by Inland Revenue within four weeks after the end of the reference month. All firms or enterprises in New Zealand with paid employees must submit PAYE data on a payday basis for each of their employees to Inland Revenue. This case study focuses on the MEI and the MEI-tourism series. This work formed part of a broader package of indicators brought together as part of the Stats NZ COVID-19 response.
At the core of the MEI is the PAYE payday record for an employee. This data are collected from Inland Revenue and includes the start and end date of the pay period, and the corresponding gross earnings, PAYE deductions and paid hours. Enterprises in the PAYE data are linked to enterprises on the Statistical Business Register to obtain industry coding.
The MEI series covers filled jobs and gross earnings belonging to:
Full-time and part-time employees
International residents
Self-employed people who pay themselves a wage or salary.
Excluded are jobs and gross earnings associated with employees on unpaid leave and unpaid employees, as well as self-employment income not taxed at the source.
A filled job is a continuing employer-employee relationship. An employer is defined as a ‘kind of activity unit’. In most cases employers have only one kind of activity unit and one PAYE record and are easily linked. A small number of large businesses in New Zealand have multiple kind of activity units and require more complex modelling of their PAYE data based on other available data sources.
The MEI-tourism series reflects employment in select tourism industries, not overall tourism employment. The industries used in the MEI-tourism series are sourced from the Tourism Satellite Account (TSA) also produced by Stats NZ. The industries selected were designed to have a high overlap, but not be an exact match with the tourism sector groupings presented in the TSA.
The TSA provides definitive annual tourism employment earnings and employee counts on a "number of people employed” basis and the TSA data are sourced from annual Linked Employer Employee Data produced by Stats NZ. Whilst the TSA is the definitive measure, it lacked the timeliness that the tourism cut of MEI information offered the users.
As part of Stats NZ’s COVID-19 response, a new portal was developed to highlight and bring together the timeliest statistical series available in New Zealand. Figure 1 shows the user interface highlighting the MEI-tourism series.
Source: Statistics New Zealand
To get to a stage where both the MEI and the MEI-tourism series was able to be produced every month by Stats NZ required significant effort by a wide number of people. This section focuses on the key factors for success as well as the challenges faced.
Critical success factors
Significant changes to reporting and technology introduced by Inland Revenue as part of their transformation program enabled Stats NZ access to high quality and timely PAYE data. This regular data supply continued throughout the most challenging times of the COVID-19 pandemic in New Zealand.
Flexible working from home arrangements allowed Stats NZ employees to be able to produce the ongoing series as well as develop new series like the new tourism splits.
Extensive R&D work on the characteristics of the PAYE data before the MEI was published allowed suitable methods to be developed, such as those for the filled job measure. Continuous improvement of these methods has also occurred since the series inception as more is learnt about the PAYE data.
A good relationship and data sharing agreement between Stats NZ and Inland Revenue was critical in enabling the production of timely monthly outputs based on PAYE data. Inland Revenue and Stats NZ have relationship managers that allow issues to related to the supply of data be resolved as well as offering a key point of contact when needing to understand technical queries about the data.
There is almost complete coverage of payday records for the reference month when the MEI and the MEI-tourism series are produced.
Stats NZ has a comprehensive Statistical Business Register which includes updates to employers, birthing and ceasing of employers, and the attributes of kind of activity units and enterprises for use in statistical processing and output Statistical Business Register.
A good monitoring and analysis system that detects unusual movements at macro and micro levels.
Challenges producing the MEI and MEI-tourism series
To get to a point where the MEI and the MEI-tourism series were produced was challenging. This first section focuses on broader challenges with the development of the series before then narrowing in on specific challenges with the data and methods used.
There are a wide variety of labour market statistics available in New Zealand, each with its own purpose, strengths, and weaknesses. This can be challenging for inexperienced users of the labour market data.
Releases of information like the MEI-tourism series often generated more requests from policy agencies and other customers for more detailed information or to explore what else was possible. Stats NZ had to carefully prioritise where resources and development time was spent.
Stats NZ needed to understand the impacts of the changes in systems at Inland Revenue because of the transformation program to ensure that Stats NZ’s systems would continue to receive and ingest data correctly.
The production of the MEI statistics requires knowledge of different software tools (R, SAS, and SQL) and it is rare to find people with skills across all these tools.
Due to some of the reasons listed in the challenges with data and methods section below, Stats NZ decided to allow a three-month provisional status on the series from when Stats NZ produce the first monthly release. This was something new for the labour market statistics unit.
Challenges with the data and methods
Choosing a suitable filled job measure for the MEI was challenging. Average weekly filled jobs in the month (based on Monday to Sunday weeks) was chosen because it is based on all jobs in the month and is more representative of the monthly employment. The approach is also like that of the Household Labour Force Survey which is the data source for official statistics about New Zealand’s labour force.
There is partial and completely missing data at the enterprise level in the MEI series. Partial or missing data are due to partial or incomplete processing of payroll records by enterprises when the data are supplied by Inland Revenue. Median imputation and aggregate adjustments based on historical data are applied to the initial totals to account for partial and completely missing enterprise data.
PAYE data includes self-employed people who pay themselves a wage or salary. They are not removed from monthly estimates of filled jobs and earnings because their identification requires information from annual tax returns.
There can be updates made to the PAYE data. To ensure these are reflected in the output dataset, estimates for the previous 3 months in each MEI release are revised.
Gross earnings reported in the payday records cover earnings for work in the pay period and lump sum payments which include redundancy and bonus payments. Redundancy payments are identified and excluded from the gross earnings outputs where possible. Bonus payments are included because they are difficult to identify.
Tax data are the sole source of employee demographic data. Date of birth, gender, and region of residential address are obtained from Inland Revenue’s client register which covers businesses and individual taxpayers. Imputation is used if the data are not available or incorrectly reported. There are other administrative sources of demographic data, but these are currently not used by the MEI.
Customers often want information about occupation. However, the employee's occupation is not available in the tax data because it is not required for taxation purposes.
PAYE groups occur when an enterprise reports on behalf of a group of enterprises linked by ownership. The MEI production system includes a process that automatically maintains the list of known PAYE groups and apportions data to kind of activity units within the group. It also identifies new groups, and groups that are no longer operating.
Concluding remarks
When the MEI was produced just prior to the COVID-19 pandemic, it was with the knowledge that Stats NZ wanted to be able to respond to more granular requests for information. The MEI-tourism series highlights the ability to produce more detailed insights from administrative data produced by the tax system. Particularly when comparing this series against what the traditional sample surveys had ever been able to produce before.
Further details about the data sources, definitions, methodology and comparisons with the labour market statistics is available on the statistical agency’s website.
For further information please contact:
Nicholas Cox, Senior Analyst, Statistics New Zealand, nicholas.cox@stats.govt.nz;
Sue Chapman, Manager – Business Employment Insights, Statistics New Zealand, sue.chapman@stats.govt.nz
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