Understanding the impact of COVID-19 on Stats NZ's data and statistics
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Understanding the impact of COVID-19
on Stats NZ’s data and statistics
Acknowledgement of our data providers and collaboration partners
We gratefully acknowledge our survey respondents and other data suppliers, our stakeholders,
customers, and collaboration partners across government, the private sector, the New Zealand
public, and overseas. Without their cooperation, Stats NZ would not be able to deliver the suite of
data products and services. Their support is even more important in the COVID-19 situation.
Nāu te rourou, nāku te rourou, ka ora ai te iwi
With your food basket and my food basket the people will thrive
Whakatauki / Māori proverb
Crown copyright ©
See Copyright and terms of use for our copyright, attribution, and liability statements.
Citation
Stats NZ (2020). Understanding the impact of COVID-19 on Stats NZ’s data and statistics. Retrieved from
www.stats.govt.nz.
ISBN 978-1-98-858389-1 (online)
Published in June 2020 by
Stats NZ Tatauranga Aotearoa
Wellington, New Zealand
Contact
Stats NZ Information Centre: info@stats.govt.nz
Phone toll-free 0508 525 525
Phone international +64 4 931 4600
www.stats.govt.nzUnderstanding the impact of COVID-19 on Stats NZ’s data and statistics
Contents
Purpose and summary ...................................................................................................... 4
Purpose .................................................................................................................................. 4
Summary of key points .......................................................................................................... 4
Challenges, opportunities, and priorities for Stats NZ ......................................................... 6
Importance of data and statistics in challenging times ......................................................... 6
Measurement challenges ...................................................................................................... 6
Impact on data quality ......................................................................................................... 12
Opportunities ....................................................................................................................... 14
Stats NZ’s priorities .............................................................................................................. 15
Impact of COVID-19 on Stats NZ’s data and statistics ....................................................... 17
Labour market statistics....................................................................................................... 17
Business and economic indicators and surveys ................................................................... 21
Price statistics ...................................................................................................................... 27
Macroeconomic accounts .................................................................................................... 29
Population statistics ............................................................................................................. 34
Household surveys ............................................................................................................... 37
Environmental statistics....................................................................................................... 39
Stats NZ release schedule ................................................................................................ 42
Stats NZ’s release calendar .................................................................................................. 42
Timeliness of Stats NZ’s regular monthly and quarterly releases ....................................... 42
Release schedule by topic and frequency ........................................................................... 43
Appendix: COVID-19 timeline .......................................................................................... 47
List of figures
1 Main phases in the Generic Statistical Business Process Model ............................................. 14
2 Data sources for labour market statistics ................................................................................ 18
3 Timeliness of regular Stats NZ monthly and quartley outputs ................................................ 42
3Understanding the impact of COVID-19 on Stats NZ’s data and statistics
Purpose and summary
Purpose
The purpose of this paper is to help Stats NZ’s customers understand the impact of COVID-19
on our data and statistics. The paper discusses the data collection, methodological, and
measurement challenges being experienced by Stats NZ, how we are addressing the
challenges, and their impact on some of our key statistical releases. It also discusses Stats NZ’s
response to customer needs for more timely data and some new data sourcing opportunities
that have emerged.
The paper has three parts:
• Challenges, opportunities, and priorites for Stats NZ – a general overview of our
measurement challenges, the impact on data quality, and opportunities and priorities
for Stats NZ.
• Impact of COVID-19 on Stats NZ’s data and statistics –the challenges on Stats NZ’s
economic, social, and environmental data, and how we deal with this.
• Stats NZ release schedule – an overview of our release schedule to indicate when
customers can expect COVID-19 impacts to come through in Stats NZ’s statistical
releases.
The paper is intended as an overview of what is happening across the wide range of Stats NZ’s
data and statistics as a result of COVID-19. It includes links to other information and
methodological papers which provide more detail about specific topic areas, such as Impacts
of the COVID-19 lockdown on the March 2020 quarter CPI and March 2020 FPI, and COVID-19
lockdown and labour market statistics for March and June 2020 quarters.
We will continue to provide more information as our understanding grows about measuring
the unprecedented impact of COVID-19 on New Zealand’s society, economy, and
environment. This will include detail about changes in sources and methods, the conceptual
underpinning of (policy) changes due to COVID-19, and an indication of the specific impact on
data quality, to be provided in information papers ahead of key releases, and in releases
themselves.
Summary of key points
The key points are:
• COVID-19 is impacting almost all aspects of daily life and it is one of the most
significant impacts on data and statistics we have seen in many decades.
• The pandemic is causing people’s behaviour to change, economic shocks, and
structural changes world-wide. COVID-19 has brought a new set of challenges to the
global statistical community as to how to understand and measure its impact in both
the short and longer term and that of government interventions.
• There are also opportunities. These include new data sources, innovations in data
collection and statistical methods, and greater national and international
collaboration. Stats NZ, for example, has worked with customers and a number of
public and private sector agencies to develop the COVID-19 data portal. We are also
working closely with other national statistical offices and international statistical
agencies to find solutions to common problems and to peer-review work.
• The highest priorities for Stats NZ are to support the all-of-government COVID-19
response, to continue to provide key statistics, and to strengthen engagement with
4Understanding the impact of COVID-19 on Stats NZ’s data and statistics
our customers and stakeholders, particularly iwi and Māori. Stats NZ will also continue
to plan and prepare for the 2023 Census and complete long-term planning to support
our broader suite of products and to understand future data needs.
• Now more than ever, it is critical that the statistics provided by Stats NZ are credible,
coherent, and relevant, so our customers can make decisions to support the wellbeing
of New Zealanders. Stats NZ is committed to this and to being transparent about the
quality of the statistics we produce and of the methodological changes and
uncertainties. As part of this, we are providing information about changes in sources
and methods ahead of our major releases and will be noting estimates that may be
subject to higher than usual uncertainty.
• Stats NZ is facing many challenges in collecting data, applying statistical methods,
measuring COVID-19 impacts, and meeting new data needs. Our staff are also working
remotely from their homes and our survey interviewers are temporarily not doing
face-to-face interviewing.
• Stats NZ will continue to provide key information to show how New Zealand is faring
across a range of statistics – including trade, travel, spending, inflation, employment,
and many other aspects of our economy, society, and environment. We will also
continue to provide new and timelier data to inform and monitor the response to
COVID-19 and the strategies for economic recovery – for example, provisional weekly
international travel data and weekly trade data.
• Stats NZ aims to publish statistics according to the regular release calendar, but
changes may occur depending on data supply and methodological issues, and re-
prioritisation of resources. We will let customers know as soon as possible if data is
not going to be delivered on schedule and will provide regular updates by email and
on our website.
• We gratefully acknowledge our survey respondents and other data suppliers, our
customers, stakeholders, and collaboration partners across government, the private
sector, the New Zealand public, and overseas. Without their cooperation, Stats NZ
would not be able to deliver its suite of data products and services, especially in the
challenging circumstances we now face.
5Understanding the impact of COVID-19 on Stats NZ’s data and statistics
Challenges, opportunities, and priorities for Stats
NZ
The COVID-19 pandemic is creating major challenges for Stats NZ. This chapter outlines the
importance of data, our measurement challenges and how we are addressing these, the
impact on data quality, opportunities arising from the issues we are facing, and our main
priorities.
Importance of data and statistics in challenging times
The COVID-19 pandemic has profound impacts on our society and economy.1 Now more than
ever, it is important that the data and statistics provided by Stats NZ are credible, coherent,
and relevant, so our customers can make informed decisions to support the wellbeing of New
Zealanders. However, the impact of COVID-19 is is affecting our ability to produce new and
existing statistics and measure COVID-19 impacts. More quality data is needed for policy and
decision-making, and at the same time, capacity constraints for national statistical
organisations like Stats NZ are intensified.
“During any crisis citizens, governments and businesses need “the facts” quickly so that they
can make critical decisions. The way that we collectively manage the COVID-19 crisis that now
grips the planet is highly dependent on having a steady stream of timely, high quality data that
allow governments and citizens to make life-saving and livelihood saving decisions. National
Statistical Systems are facing unprecedented challenges in delivering these data. Innovation,
resiliency and international cooperation are ensuring that official statistics not only continue
to flow but that they are enhanced to address the specific COVID-19 information needs”.2
We acknowledge that data gaps exist in the information we need right now and that some of
Stats NZ’s traditional statistics are not published with sufficient frequency or timeliness. The
new COVID-19 data portal for high-frequency data may address some of these issues. We
focus here on the measurement challenges and data quality impacts for our regular releases,
and how we deal with these. In response to the challenges imposed by COVID-19, we are using
new data sources and providing more frequent and timely data where possible.
Measurement challenges
We can distinguish four types of measurement challenges, which are often inter-related:
• data collection issues
• methodological issues
• conceptual challenges
• new data needs.
1The appendix of this paper contains a COVID-19 timeline, covering the spread of the virus, travel restrictions put in
place, and the COVID-19 alert level system in New Zealand.
2 Source: Committee for the Coordination of Statistical Activities (2020). How COVID-19 is changing the world: a
statistical perspective. Retrieved 28 May 2020 from https://unstats.un.org/unsd/ccsa/documents/covid19-report-
ccsa.pdf.
6Understanding the impact of COVID-19 on Stats NZ’s data and statistics
Data collection issues
COVID-19 impacts are causing major issues for the collection of data for household and
business surveys and for price index statistics. Administrative data used in our statistics could
be affected as well, although we have no indication of that yet.
Face-to-face survey collection stopped until further notice
On 22 March 2020, following advice from the Ministry of Health and the Government Chief
Science Advisor, an all-of-government decision was made to suspend all face-to-face survey
interviews until further notice.3 This was not a decision taken lightly, but was made to protect
the health and wellbeing of frontline staff and respondents and to ensure this work does not
contribute to the spread of COVID-19. As the response continues to evolve, the Ministry of
Health will monitor the situation and advise agencies on when it is safe to resume face-to-face
survey interviewing. Stats NZ is working with other agencies to ensure a coordinated and
consistent approach is taken to resuming data collection via face-to-face interviews across
government.
Impact on household surveys and price statistics
The decision to stop all face-to-face survey collection until further notice has significant
impacts on Stats NZ’s data collection and the statistics used to make decisions for New
Zealanders. Face-to-face survey interviewing is normally used for household surveys, such as
the household economic survey (HES), the general social survey (GSS), and for a part of the
household labour force survey (HLFS) from which official employment and unemployment
measures are derived. An important part of the price data collected for the consumers price
index (CPI) and the food price index (FPI) is also collected by survey interviewers.
Some of these surveys require face-to-face data collection, and in many cases it is not
straightforward to shift to another method of collection (like phone, email, or online). Where
we can use another form of surveying, we do. For example, our survey interviewers are now
collecting data by phone, focusing on the HLFS. Despite data collection continuing, lower
response rates are to be expected, especially for respondents who are in the survey for the
first time and those who are hard-to-reach (for example, young people and those living in
lower socio-economic areas). This is likely to cause some collection bias; that is, a distortion
that results in the information not being fully representative of the population.
For missing price data for CPI and FPI, we are increasing our use of web-scraping as well as
collecting prices manually from the internet, and contacting retailers directly to acquire price
data.
Collection issues for business surveys
Postal surveys sent to businesses may also be affected by lower-than-usual response rates,
depending on the extent to which businesses continue to operate (for example, those
businesses in the tourism and hospitality sectors).
Due to the closure of non-essential businesses and employees working from home,
respondents were unlikely to receive business surveys for the March 2020 quarter. We applied
the following mitigations:
3Media release COVID-19 update: Surveys by email and phone continue, although face-to-face survey interviews
have stopped.
7Understanding the impact of COVID-19 on Stats NZ’s data and statistics
• Digital response options were implemented for all March 2020 quarter business
surveys, including supplying editable PDF and Microsoft Excel questionnaires to
respondents via email.
• Digital response options were dispatched on or shortly after 25 March 2020. Only pre-
scheduled print and post jobs in progress were completed by a Stats NZ’s service
provider.
• In cases where businesses were new to a survey or Stats NZ did not have an email
address, we undertook pre-contact calling to establish respondents and obtain their
email address.
• Stats NZ’s field staff were redeployed to contact calling businesses and we increased
the use of digital reminders.
Stats NZ successfully made contact with the majority of businesses selected for surveying and
worked with them to obtain their response. We also made increased use of digital channels,
including email and text messages, to remind businesses to respond.
Potential impact on administrative data
Administrative data is data that has not been collected primarily for statistical purposes. It is
used as a data source for economic, social, and environmental statistics.
Over the years, Stats NZ has been increasing the use of administrative data, in particular tax
data, in place of survey data where possible to reduce respondent burden and improve
coverage in economic and social statistics. At this stage, there is no indication that COVID-19
impacts will disrupt administrative data sourcing. However, risks exist that COVID-19 impacts
could result in some delays and data quality issues.
Another type of administrative data is data collected in environmental reporting systems.
Environmental data is largely collected by regional councils and Crown research institutes for
environmental monitoring, and repurposed for national environmental reporting. While some
collections are done via remote sensors (such as air quality and the hydrometric network –
flood warnings, minimum flows, rainfall), others are done manually (such as water quality
monitoring). Manual collection was suspended during the COVID-19 alert level 4 lockdown,
but we do not yet know the impact on these manual collections, or any data quality issues
arising from missed calibration during the lockdown.
Uncertainty in the short term about collection modes and data coverage
All the impacts on data collection are not yet known. They depend on how long we are unable
to carry out face-to-face survey interviewing and how households and businesses are able to
respond to other forms of data collection. We expect some loss of data coverage, where there
is no practical alternative to collect data or business respondents are struggling to respond.
Methodological issues
To ensure we can capture the impact of COVID-19 on the New Zealand economy and society in
our data, we are reviewing and modifying the methodology to produce our statistics. Below,
we briefly cover the potential effects of changing collection, imputation methods, estimation
models, time series, and revisions.
8Understanding the impact of COVID-19 on Stats NZ’s data and statistics
Potential effects of changing collection methods
If we change the way we collect data, potential effects need to be considered. This can relate
to the sampling frame, coverage, and measurement quality (for example, differing types of
responses).
For example, for a face-to-face household survey, the sampling frame uses addresses. We do
not necessarily have the respondent contact details, which would enable us to switch to a
phone or email collection, unless they have previously been surveyed. Without the option of
face-to-face contact, recruiting new households into a sample may also be challenging (for
example in the HLFS). To mitigate this, we sent out pre-notification and reminder letters to
request households for which we do not have phone numbers to call Stats NZ for interviewing.
When changing the collection method, the respondent coverage is likely to be different. For
example, people who do not have internet access would not be able to participate in an online
collection, affecting the coverage of the survey.
The collection method can also affect aspects of measurement quality, like data completeness
and responses that may be influenced by perceptions of what is socially desirable. Different
methods can result in different types of answers. For example, the answers relating to
questions about labour force status can be different for face-to-face and phone interviews,
even when both are conducted by a survey interviewer.
The impact of changing collection methods is difficult to measure, so we need to apply good
judgement to moderate it.
Imputation methods
Although we have put considerable effort into collecting data, some of the data we would
normally collect may be missing, incomplete, or incorrect. This will require imputation (filling
data gaps) to produce accurate and relevant statistics. Various imputation methods are in
place to handle missing or incomplete data. These methods can be based on historical data,
data from similar responding people or businesses (such as mean, nearest neighbour, or
random donor imputation), or modelled data.
Due to the COVID-19 impacts, some of these methods may not be appropriate anymore. For
example, historical data may not be representative or there may not be enough responses
available to use for filling data gaps. In addition, we cannot rely on the assumption that the
data is missing at random, as there may be certain patterns of non-response.
For some datasets, imputation was previously not required, but the COVID-19 situation has
changed this. An example could be environmental datasets, if daily manual monitoring could
not take place during the COVID-19 alert level 4 lockdown.
We are reviewing where interventions or method changes for imputation are required.
Estimation models
We use many models across economic, social, population, and environmental statistics to
provide estimates for specific components of our published statistics. Some of these models
may not reflect the real-world impacts of COVID-19, and may require modifications or a
replacement. In other instances, we need to develop new data sources and methods to be
able to measure the short-term and long-term impacts of COVID-19.
9Understanding the impact of COVID-19 on Stats NZ’s data and statistics
An example of rapid change undermining the validity of modelling parameters is the model
used to estimate the value of construction work being put in place. The model parameters are
based on historical relationships that have broken down due to the COVID-19 lockdown. This,
and some other examples, are further discussed in the next part about impacts on specific
Stats NZ statistics.
Dealing with abrupt changes in seasonally adjusted and trend series
COVID-19 will cause abrupt changes to many time series. This is a challenge for decomposing
time series into their trend, seasonal, and irregular components.4
The default trend produced by Stats NZ’s seasonal adjustment system (X-13) estimates what is
happening in the time series in the medium- to long-term. For the trend estimates produced in
the seasonal adjustment system, medium to long term changes are occurring over more than
15 months (five quarters), though this is an approximate cut-off. This results in a trend
estimate that is a smooth time series through the original or seasonally adjusted series.
With most of the abrupt changes due to COVID-19 happening in the June 2020 quarter, the
default trend series are not going to realistically measure the effects. We are estimating these
abrupt changes separately to get a better understanding of the underlying trends in our time
series. Stats NZ is preparing intervention strategies for the seasonal adjustment system it is
using.
With only one data point (April 2020 month or June 2020 quarter) to estimate the effect,
estimation of the COVID-19 affected time series would lead to major uncertainty and possibly
large revisions when subsequent data becomes available.
With one data point, there is no substantive quantitative difference in terms of modelling for
an outlier or a level shift. The current seasonal adjustment system will treat the April 2020
month or June 2020 quarter figures as outliers and seasonally adjust accordingly. This means
the unusual value will appear in the seasonally adjusted series but will be ignored for the trend
series estimate. The trend will be assumed to be similar to the trend for previous quarters or
months, and therefore would, if published, tell a story that would not reflect the reality of the
situation.
In summary, we expect the seasonally adjusted series to be informative for the April 2020
month and the June 2020 quarter, but not the trend series. For example, the release of
international travel data and international migration data for the month April 2020, both
scheduled for publication on 15 June 2020, will not contain trend estimates due to the impact
of the COVID-19 pandemic on international travel.
Revisions to time series may be larger than usual
Maintaining consistent long time series across a range of statistics is important, as this can
contextualise the present and illuminate the future. As we adjust sources and methods to be
able to capture real-world changes following the COVID-19 pandemic, revisions to time series
may be larger than usual.
Revisions to previously published data are often necessary to maintain the best possible
estimates and are part of our regular production cycles. They are not to be confused with
corrections of errors in releases. Our goal across all revisions is to increase the quality of
4Calendar effects like number of trading days in a month, for example due to holidays, can be accounted for as
well.
10Understanding the impact of COVID-19 on Stats NZ’s data and statistics
previously published data. It is international best practice to revise statistics to ensure these
continue to reflect the realities of a changing world. Our revisions policy is governed by three
guiding principles, which recognise the importance of our customers’ needs. These principles
are:
• All statistical outputs we produce should be internally consistent and present the
same (or a similar) story of underlying activity.
• Revisions to statistical outputs should be applied consistently, with knowledge of the
time lag inherent in different data sources and the effect that revisions to one data
source may have on ancillary or other outputs.
• The revision process must be transparent and open.
Conceptual challenges
The response to the COVID-19 pandemic by the government, households, businesses, and
other organisations creates many conceptual measurement challenges for Stats NZ. Each
challenge needs to be addressed separately, and the conceptual treatment for each challenge
needs to be consistent across the system of statistics.
Some examples of those conceptual challenges we are working on, and which are further
discussed in the next part of this paper, are:
• How do we treat the COVID-19 wage subsidy scheme in labour market and business
surveys, and in the national accounts?
• How do we measure the price of goods and services that are not available?
International collaboration
Since national statistical offices around the world are facing similar challenges, we have
increased our collaboration over the last couple of months with colleagues overseas, such as
the Australian Bureau of Statistics and Office of National Statistics (United Kingdom).
International frameworks and standards (like the System of National Accounts and the
Consumer Price Index Manual) are the references for deciding on conceptual treatments.
Organisations like the United Nations Statistical Commission (UNSC), the International Labour
Organization (ILO), the International Monetary Fund (IMF), and the Organisation for Economic
Cooperation and Development (OECD) are providing guidance on how to deal with statistical
challenges due to COVID-19, as data and statistics from different countries need to be
comparable.
New data needs
COVID-19 continues to create new data needs for the response, recovery, and rebuild phases.
New questions are to be answered. Stats NZ receives external requests for data, but internally
new data is required as well.
COVID-19 data portal for high-frequency and timely data
Decision making in the response phase has required new high-frequency and timely data; for
example, to measure the impact of the COVID-19 alert system. We have developed and are
maintaining a new COVID-19 data portal on our website. It reports on the changing state of
aspects of New Zealand’s economy since the COVID-19 outbreak, and includes health data and
social indicators as well. The data has been sourced from Stats NZ; other government
organisations, including the Reserve Bank of New Zealand, The Treasury, Ministry of Social
Development, banks; and international sources.
11Understanding the impact of COVID-19 on Stats NZ’s data and statistics
Structural changes in the recovery and rebuild phases
COVID-19 will almost certainly lead to structural changes in New Zealand’s economy and
society; for example, more businesses operating predominantly online, a decrease in
international tourism, and the potential increase of people working from home on a
permanent basis. These changes will give rise to new data needs, as new questions need to be
answered. For example, how is the resilience of some businesses different from others? What
new data do we need, in order to assess the situation for particularly vulnerable people in our
society, such as single parents, or grandparents looking after their mokopuna?
External data requests
Stats NZ has received many external data requests. Often, they involve more than the usual
data granularity (for example, to assess the impact on specific industries, regions, age groups,
or vulnerable communities). We have prioritised external data requests, for example, requests
for COVID-19-related research using Stats NZ’s Integrated Data Infrastructure (IDI).
Data Ventures is the commercial arm of Stats NZ. They bring datasets across government and
private sector together in a trusted environment, and turn these into useful products.5
Following the COVID-19 outbreak, Data Ventures has been tasked with supplying critical data
sets such as Population Density and Spend Density to the National Crisis Management Centre
(NCMC), along with brokering Stats NZ expertise and insights where needed at speed.
New data needs at Stats NZ
Stats NZ also needs new data to be able to capture COVID-19 impacts in our key releases. We
need alternative data sources to fill data gaps and for alternative or new estimation methods.
An example is wage subsidy data from the Ministry of Social Development, which can be used
as an input for economic accounts, the Stats NZ Business Register etc. As the COVID-19
impacts could result in large movements in our data, we need additional data sources to
validate the story the data is telling.
Data stewardship
Data stewardship is the careful, responsible, and ethical management and use of data. Even
when data needs are urgent and COVID-19 developments are fast-paced, Stats NZ is still
following procedures to ensure the security, privacy, and confidentiality of the data it sources,
holds, and releases.
A trusted, credible data system is also essential for a well-functioning government. We are
continuing our focus on our data stewardship role to ensure the development and production
of high-quality data across government.
Impact on data quality
The measurement challenges we are facing will have a significant impact on data quality in our
statistical releases in the short and medium term.
Existing data sources and traditional methods of measurement and strategies for collection
(such as face-to-face survey interviewing) may not be possible or may become limited in their
ability to accurately capture and represent the shifts in in the economy and societal behaviour,
5 Data Ventures does not sell Stats NZ data.
12Understanding the impact of COVID-19 on Stats NZ’s data and statistics
and provide insights at the level of granularity needed (for example, regional, age groups, and
sub-populations).
We are committed to producing fit-for-purpose data and statistics, but some estimates may
have a higher-than-usual level of uncertainty following the COVID-19 pandemic.
Considering data quality dimensions and data value
We can explore what fit-for-purpose means by looking at various dimensions of data quality:
• Relevance – the degree to which data meets the changing needs of customers.
• Reliability – data is published on time and is accurate, coherent, and produced
efficiently:
o timeliness – data is released within a time period that permits the information
to be of value to users
o frequency – the data is available often enough to be useful (for example,
weekly, monthly, quarterly)
o accuracy – source data and statistical methods are sound, and outputs
sufficiently portray the reality they are designed to represent
o coherence – data is coherent and consistent within a dataset, and it can be
successfully brought together with other information within a broad analytical
framework and in time series.
• Accessibility – data is available, understandable, and usable:
o availability – data is provided in suitable mediums for access, and users are
aware of this
o interpretability -- supplementary information and metadata necessary to
interpret and use the data is provided.
Fit-for-purpose means finding a balance between various dimensions of data quality, while
also considering the public value that releasing data can generate. Timely and frequent data
products are important to support immediate decisions, but this often means lower accuracy
and less granularity. More accurate and detailed statistics will be more important when
making long-term decisions, assessing long-term impacts, and monitoring progress.
The fit-for-purpose and data-value consideration does apply to both headline statistics and
more granular breakdowns of the data. For example, a headline figure from a survey may be
robust, but skewed responses could have a serious impact on the accuracy of breakdowns.
If there are urgent needs, and where we can, we will release timely indicators that are
important for decision making, even when this data may not be as accurate as usual, and may
not be consistent with other data we have released before.
Managing change due to measurement and data quality challenges
The measurement and data quality challenges described above will require many changes to
our existing regular statistical production processes, which need to be managed. The focus on
change can be illustrated with the Generic Statistical Business Process Model (GSBPM) in
figure 1.
13Understanding the impact of COVID-19 on Stats NZ’s data and statistics
Figure 1: Main phases in the Generic Statistical Business Process Model (GSBPM)6
1 Main phases in the Generic Statistical Business Process Model
In our regular production cycles, the work
phases – data collection, processing,
analysing, and disseminating – are in many
ways affected by the COVID-19 pandemic.
This requires us to put substantial effort into
the change phases of specifying new
customer needs (including determining
priorities), (re)designing and reviewing
methodology and processes, and building
and testing changes in production systems.
Stats NZ will engage with key customers and
stakeholders, and inform users ahead of
major releases on decisions and progress we
make with changes resulting from
measurement challenges.
Opportunities
With challenges come opportunities. These could be in the form of new data sources,
innovations in statistical methods and processes, and more collaboration with other
organisations in New Zealand and overseas. With these opportunities, New Zealand’s data
system could come stronger out of the COVID-19 pandemic.
New data sources
New data sources may become available that could help answer new questions. They could
also be useful beyond the COVID-19 response phase. Data could be used for multiple
purposes. For example, wage subsidy data from the Ministry of Social Development could be
used as supplementary information for labour market statistics, household, and business
surveys.
Inland Revenue (IR) is administering a number of business support initiatives around COVID-
19. Stats NZ will continue to work with IR to explore the availability of potential new data
sources to assess the impact of COVID-19 on the New Zealand economy.
Innovations in methods and processes
The COVID-19 crisis is an opportunity to push innovation in methods and processes.
Implementation of some development work on collection methods and estimation models can
be accelerated. Recent improvements in processing systems are re-used to develop new
products to respond to COVID-19 information needs. Innovative solutions developed for the
short-term COVID-19 response will also be beneficial in the longer term.
6Source: High-Level Group for the Modernisation of Official Statistics (nd). Generic Statistical Business Process
Model. Retrieved 28 May 2020 from https://statswiki.unece.org/display/GSBPM.
14Understanding the impact of COVID-19 on Stats NZ’s data and statistics
Making the most of collaboration opportunities
In the COVID-19 crisis, Stats NZ has been collaborating with many government and private
sector organisations. This could provide opportunities for more collaboration in the future.
Stronger collaboration with other national statistics organisations (for example in Australia,
the UK, and Canada) and other international organisations could continue in the future.
Stats NZ’s priorities
We cannot take up all our challenges and opportunities at once, so Stats NZ is setting
priorities. In the COVID-19 context, the highest priorities for Stats NZ are to support the all-of-
government COVID-19 response, to continue to provide key statistics, and to strengthen
engagement with our customers and stakeholders, particularly iwi and Māori.
Supporting the all-of-government COVID-19 response
As part of supporting the all-of-government COVID-19 response, some Stats NZ staff have
been redeployed to other organisations to support COVID-19 modelling, data analysis, and the
COVID-19 website. In April 2020, approximately 100 Stats NZ contact centre staff were
redeployed to support Healthline website enquiries. As a replacement, survey interviewers
across New Zealand formed a virtual Stats NZ contact centre. This way, the data collection for
thehousehold labour force survey could continue via phone.
Continuing to provide key statistics
Another high priority is to continue to provide key economic and social statistics to show how
New Zealand is faring across a range of statistics, such as trade, travel, spending, inflation, and
employment. We are also providing new high-frequency and timely data to help decisions
around COVID-19. Key data products, such as quarterly GDP, measures of international
performance, labour market measures, and environmental statistics, will play a vital role in
New Zealand’s COVID-19 recovery. The planning and design work for the 2023 Census is also
continuing, and we are completing long-term planning to support our broader suite of
products and to understand future data needs.
Although we aim to meet our scheduled release dates, we may decide to delay or reschedule
some of our statistical releases due to measurement challenges or other priorities.
Engaging with our customers and stakeholders
Our intention is to create value by providing services and products in conjunction with strong
and trusting relationships. Products are most likely to meet the needs of customers if the
actual customers have been involved in developing the products. Ongoing working
relationships with stakeholders ensures commonality of understanding and transparency of
priorities. This will continue to be of importance in the COVID-19 context.
Responding to iwi and Māori data needs
We are committed to strengthening relationships with iwi and Māori to make sure they can
take part in decisions about their data. The Mana Ōrite Relationship Agreement was signed
between Stats NZ and the Data Iwi Leaders Group of the National Iwi Chairs Forum in October
2019. The purpose of the relationship is to work together with iwi and Māori to realise the
15Understanding the impact of COVID-19 on Stats NZ’s data and statistics
potential of data to make a sustainable, positive difference to outcomes for iwi, hapū, and
whānau. This work continues in the COVID-19 crisis.
Māori are a vulnerable population group in the COVID-19 crisis. The economic impacts may be
very strong. Māori tend to be particularly hard hit by recessions, given that they are over-
represented in lower-skilled and less secure jobs. Some regions with large Māori populations
have high levels of unemployment, underutilisation, and underemployment. Many Māori
individuals and businesses are involved in potentially vulnerable industries, such as primary
production (including forestry), manufacturing, hospitality, and the tourism industry (which is
severely affected by COVID-19 travel restrictions). Cultural wellbeing has also been affected by
the ban of tangihanga (mourning and funeral ceremonies) under COVID-19 alert system levels
3 and 4.
We are working with Māori communities to improve the quality of their data, so that these
communities are more fully represented in the data. Data improvements will enable improved
planning that directly supports the wellbeing of Māori.
For example, we responded to a request from the National Iwi Chairs Forum Pandemic
Response Group for iwi affiliation data. While we could not provide iwi affiliation data, we
were able to prepare data by ethnicity. The data is from the 2018 Census, including
demographic information and information about activity limitations, cigarette smoking
behaviour, and unpaid household activities, such as care work.
We acknowledge that ethnicity data is not sufficient to be able to link people with iwi. In the
COVID-19 situation, iwi and Māori are trying to understand what is happening in relation to
their iwi, including iwi members both within and outside their tribal boundaries. They want to
understand the impacts and demands on their communities during the crisis and then will
want to know how they can best respond to help their people and communities. However,
bespoke data about iwi is missing.
We have not released official counts of iwi recently, due to the level of missing iwi affiliation
data in the 2018 Census dataset. We have not been able to use administrative data to fill in
missing information as there are no reliable government data sources for iwi affiliation data
other than the census. We are working with iwi to address this challenge and meet data
needs.
Crucial to ensuring equitable data access is that Māori and iwi are deeply involved in the
design and development of statistical products and data collection. As the lead agency in the
government data system, Stats NZ is responding to growing concerns raised by Māori about
the amount of data activity (including a large number of surveys and development of new data
sets) occurring in the context of COVID-19. We are undertaking initiatives to improve
coordination across the government data system and ensure data and quality standards are
maintained. COVID-19 has shown the lack of iwi affiliation data and the importance of it to iwi.
Collaborative work is happening across the system to improve administrative data to ensure a
sustainable and diversified flow of relevant iwi affiliation data for Māori in the data system.
The COVID-19 crisis offers opportunities for the Māori-Crown relationship, for being more
responsive to Māori and iwi data needs, and for engaging Māori in decision-making at a
governance level. Stats NZ can help by actively encouraging a Te Ao Māori lens (a Māori world
view) is embedded in the way in which decisions are taken across the government data
system.
16Understanding the impact of COVID-19 on Stats NZ’s data and statistics
Impact of COVID-19 on Stats NZ’s data and statistics
The COVID-19 pandemic and response has impacts across all of Stats NZ’s economic, social,
and environmental data and statistics. In this part of the paper, we look at the key
measurement challenges for specific data and statistics, and how we are dealing with these.
We cover the impacts on the following broad topics:
• Labour market statistics
• Business and economic indicators and surveys
• Price statistics
• Macroeconomic accounts
• Population statistics
• Household surveys
• Environmental statistics
We also highlight some of the links between these statistical areas, and how we keep
consistency across the official statistics system. As an example, we show how the COVID-19
wage subsidy is being treated consistently across various statistical areas.
Labour market statistics
This section describes what we have seen in Labour market statistics: March 2020 quarter,
measurement challenges for the June 2020 quarter, and the action we are taking to address
these. We expect lower-than-usual response rates, with cascading effects on imputation and
estimation methodology. To capture COVID-19 impacts accurately, we provide guidance to
survey interviewers to help respondents provide accurate data and have added a couple of
additional questions in the core part of the HLFS.
Summary of the quarterly labour market statistics release content
The quarterly labour market statistics release combines data from three surveys to present a
broad picture of New Zealand’s labour market. It is published about five weeks after the
reference quarter.
The HLFS provides a picture of New Zealand's labour force from a household perspective (as
the labour supplier). These statistics relate to employment, unemployment, underutilisation,
and people not in the labour force. The article Working-class heroes: Understanding labour
market data explains how we define and measure this labour market information.
The quarterly employment survey (QES) estimates the demand for labour by New Zealand
businesses. These statistics relate to the number of filled jobs at established businesses, total
weekly gross earnings, total weekly paid hours, average hourly and average weekly earnings,
and average weekly paid hours in the industries surveyed.
The labour cost index (LCI) measures changes in salary and wage rates for a fixed quantity and
quality of labour input. It is a measure of wage inflation, reflecting changes in the rates that
employers pay to have the same job done to the same standard.
Figure 2 shows the role of HLFS, QES, LCI in labour market statistics. Linked employer-
employee data (LEED) is discussed later.
17Understanding the impact of COVID-19 on Stats NZ’s data and statistics
Figure 2: Data sources for labour market statistics
2 Data sources for labour market statistics
March 2020 quarter reflected the labour market before the
lockdown
Labour Market Statistics: March 2020 quarter, published 6 May 2020, largely reflected the
state of the labour market before the five-week alert level 4 lockdown. This was partly due to
the timing of collecting data, and the slowing of the data collection towards the end of March
2020 for the HLFS.
• The HLFS data is collected over 13 weeks, each quarter. This means estimates are
designed to reflect the state of the labour market over the full quarter, not at a single
point in time. The information obtained from respondents relates to the week before
their interview.
• The QES reference period is the pay week ending on or immediately before the 20th of
the middle month of the quarter (20 February for the March 2020 quarter).
• LCI wage and salary rates for the March 2020 quarter were captured as at 15 February
2020.
Based on the survey periods for QES and LCI, and no HLFS face-to-face survey interviews taking
place at the end of March 2020,7 these labour market statistics may indicate early impacts (on
particular industries) as COVID-19 spread internationally, but they do not reflect the lockdown
period at the end of March 2020.
For the March 2020 quarter, much of the quarter had passed prior to the introduction of steps
to slow the spread of COVID-19. The interrupted data collection means we will not have fully
captured activities during the period in which New Zealand shifted from alert level 2 to alert
levels 3 and 4. The article COVID-19 lockdown and labour market statistics for March and June
2020 quarters explains in more detail how the data collection was slowed by COVID-19.
7 We continued telephone-based interviews where possible for the HLFS.
18Understanding the impact of COVID-19 on Stats NZ’s data and statistics
June 2020 quarter responses likely to reflect the lockdown
restrictions
We expect Labour market statistics: June 2020 quarter (due to be published on 5 August 2020)
to show more clearly how the COVID-19 lockdown has changed New Zealand’s labour market.
Alongside the unemployment rate, a wide range of indicators, such as underutilisation,
underemployment, hours actually worked, and hours usually worked, will provide a clearer
picture of how restrictions to stem the spread of COVID-19 are affecting New Zealand’s
workplaces and workforce.
However, it will likely take some time to measure the full effects of the lockdown and
restrictions at other COVID-19 alert system levels. Some people may be getting a wage subsidy
but have not been actually working because firms have been forced to shut temporarily. When
the wage subsidy expires, some businesses may have to lay off staff. People who are very
recently laid off may not initially be recorded as unemployed in the HLFS, but rather as not in
the labour force, if they do not meet the criteria of having been actively seeking and available
for work. The consistent treatment of the COVID-19 wage subsidy scheme in labour market
and other statistics is discussed in the section on national accounts.
Measurement challenges for the June 2020 quarter
We expect to see the impact of COVID-19 lockdown actions reflected in a lower number of
responses to our surveys in the June 2020 quarter. For the HLFS, face-to-face interviewing
remains suspended until further notice. For QES and LCI, some of the businesses we select to
survey in April 2020 may close, temporarily or indefinitely, before the survey reference periods
in mid-May 2020. Additionally, many businesses that are operating will be doing so differently
from usual, so it may be more difficult to contact them, or for them to respond.
Addressing challenges presented by COVID-19
We have and will take the following actions to mitigate potential impacts on data quality for
the June 2020 quarter caused by the COVID-19 lockdown restrictions.
Changes to the HLFS survey sample
The HLFS has eight rotation groups, meaning selected households participate in the survey for
eight quarters. To maintain a sufficient sample size for the HLFS, we have retained
respondents who were scheduled to exit the survey after the March 2020 quarter. This will
help to compensate for the difficulty of recruiting new households for the first rotation panel
without face-to-face interviewing. On balance, the sample size for the June 2020 quarter is
likely to be smaller than usual. If face-to-face interviewing for the HLFS cannot restart for the
September 2020 quarter, this problem could become exacerbated. As a mitigation, Stats NZ is
sending pre-notification and reminder letters to request households for which we do not have
phone numbers to call in for interviewing.
Changes to HLFS core survey content
We are asking employed people a couple of new questions about perceived job security and
working from home in the core questions for the HLFS from the June 2020 quarter.
19Understanding the impact of COVID-19 on Stats NZ’s data and statistics
Perceived job security
This question asks all employed people what they think the chance is that they could lose their
main job or business in the next 12 months for reasons beyond their control. A five-point scale
is used to answer this question:
• almost certain
• a high chance
• a medium chance
• a low chance, or
• almost no chance.
Work from home
Respondents who worked during the reference week are asked whether any of the hours
worked were at home and, if so, about how many hours (to the nearest hour). People are also
asked whether they have always worked some hours from home, which will give us an
indication whether people worked from home for the first time.
Guidance for answering HLFS questions
We acknowledge that under the current circumstances respondents may find it difficult to
answer some labour market survey questions. For example, questions about their availability
to work, working fewer hours, being away from work, being on paid leave, and reporting of
wages and salaries.
If a respondent is unsure how to report their usual hours, our survey interviewer will guide
them to answer based on the hours they worked prior to lockdown, and record their actual
hours, which are the hours they worked in the reference week.
As another example, if a respondent is not working any hours and is receiving the wage
subsidy from their employer, then they have a paid job. The survey interviewer will record
them as employed but away from work during the reference week. Respondents’ reason(s) for
being away from work will also be captured.
Ensuring reliable data
We are preparing for a decrease in responses from households and businesses, especially from
the industries that are heavily affected by COVID-19, such as hospitality and tourism. As with
any quarter, we will ensure the statistics are as reliable as possible and be transparent about
response rates and the ways we may need to fill any data gaps.
Other useful statistics about the labour market
For further insight into the labour market during this period of uncertainty due to the COVID-
19 lockdown, some statistics based on administrative data are available.
Stats NZ’s monthly employment indicators for filled jobs and gross earnings use a combination
of data from two different IR sources, the employer monthly schedule (EMS) and payday filing.
These indicator series are published four-to-five weeks after the end of the reference month.
We are working on releasing more detailed industry information.
The Ministry of Social Development publishes statistics on benefits and the wage subsidy
assistance. These statistics are not directly comparable with Stats NZ’s labour market statistics.
The Guide to unemployment statistics (third edition) shows the differences between HLFS
unemployment measures and people included in Jobseeker support.
20Understanding the impact of COVID-19 on Stats NZ’s data and statistics
Linked employer-employee data (LEED) measures labour market dynamics with much detail
and coverage. LEED is not very timely, but would be useful for providing detailed insights of
the situation before and after COVID-19.
• LEED uses existing administrative data from IR, together with business data from Stats
NZ’s longitudinal business frame (LBF).
• The LEED dataset is created by linking an employer series from the LBF to a
longitudinal series of (EMS) payroll data from IR.
• LEED provides quarterly statistics on filled jobs, job flows, worker flows, mean and
median earnings for continuing jobs and new hires, and total earnings.
• The statistics are grouped by sex, industry, and region.
• LEED uses counts of jobs at the 15th of the middle month of the reference quarter.
• LEED statistics are published about 12 months after the reference quarter. They are
provisional for two quarters (that is they will be revised for an additional two
quarters). The statistics are final 18 months after the reference quarter. The data
covers almost 100 percent of all jobs in the reference period.
Business and economic indicators and surveys
This section covers Stats NZ’s business and economic indicators and surveys which are on a
monthly, quarterly, or annual frequency. Most of these statistics use administrative data (for
example, tax data) to collect information about small and medium-sized businesses and
organisations. Only key enterprises are directly surveyed.
Electronic card transactions
We produce monthly statistics on electronic card transactions (ECT) from aggregated
administrative data generated in the process of administering New Zealand-based electronic
transactions. ECT covers all debit, credit, and charge card transactions with New Zealand-
based merchants. It can be used to indicate changes in consumer spending and economic
activity. The data is supplied monthly in aggregated form. There are no issues with data supply
due to COVID-19.
The seasonal adjustment methodology required interventions due to extreme movements in
the series. One example is a negative value appearing in the actual data in a series that had
never had a negative value before. This related to travel agencies refunding more money than
they were receiving in a month.
We have been releasing lower-level card transaction data than usual, as part of the response
to COVID-19. Early indications of the economic impacts of COVID-19 are visible in the ECT
series. In March 2020, COVID-19 measures knocked retail spending, and Electronic card
transactions: April 2020 showed that spending halved during the lockdown, and hospitality
was hit hard.
International trade in goods
Overseas merchandise trade statistics provide information on imports and exports of
merchandise goods between New Zealand and other countries. These statistics are derived
from data we receive daily from the New Zealand Customs Service (NZCS) for imports and
exports over $1,000.
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