Agnes Tassy, Statistics Denmark, ata@dst.dk

Everyday life including cultural activities has changed dramatically due to COVID-19. The past 22 months have been characterised by more or less extended lockdowns. These lockdowns and an in-creased need for social distancing have drastically changed the way we consume cultural products and services. Statistic Denmark’s new quarterly cultural consumption statistics covers this development in cultural consumption. Data are collected quarterly and results are available 15 days after the last day of the quarter covered. The survey is thus one of the fastest official statistics in Denmark, providing updated information on cultural consumption in the rapidly changing context of partial or full lock-downs, which have also affected the cultural sector dramatically.

By combining demand and supply side statistics about cultural activities, the paper addresses the fol-lowing questions:

- Which cultural activities and sectors have been affected most by COVID-19?

- Is there a difference between the characteristics of pre- and post-pandemic cultural consum-ers?

- How can we characterise the groups of people who returned to the museums, concerts, etc. after the lockdowns? Are there groups that did not return?

- What influence has the pandemic had on the average number of visits per visitor in selected groups of consumers?

- Has cultural consumption become more digital between 2018 and 2021? If yes, how? Which cultural domains are most affected?

Results from the quarterly cultural consumption statistics indicate that there is a need to think digital ways of consumption when we collect information about cultural activities. The last part of the paper focuses on suggestions as to how questionnaires can be improved to cover both physical, digital or ’on the couch’ consumption.

Keywords: cultural habits, cultural consumption, COVID-19, digitalization, lockdown

Session 4.1. The effects of COVID: Revulsion, recession and recovery

When: Tuesday, August 23 at 13:00 - 13:55

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Lars Werke, Sweden Statistics, Lars.Werke@scb.se

Sini Liukkonen, Statistics Finland, sini.liukkonen@stat.fi

Ólafur Már Sigurðsson, Statistics Iceland, olafur.m.sigurdsson@hagstofa.is

Geir Hjemås, Statistics Norway, Geir.Hjemas@ssb.no

Peter Bøegh Nielsen, Statistics Denmark, PBN@dst.dk

Søren Schiønning Andersen, Statistics Denmark, SSA@dst.dk

Fenja Søndergaard Møller, Statistics Denmark, FSM@dst.dk

Since the beginning of 2020, Covid-19 has caused major impact on public health and economies around the world. A number of analyses have looked into socio-economic effects of Covid-19 in individual countries. However, there is need for evaluating the effects and strategies in a comparative perspective. Mandated by the Nordic chief statisticians at their meeting in Torshavn in August 2021, this analysis describes the socio-economic effects of Covid-19 in five Nordic countries: Denmark, Finland, Iceland, Norway and Sweden. The analysis is divided into five sections with selected key variables concerning 1) macro-level indicators 2) health indicators, 3) government support schemes, 4) business indicators, and 5) labour market indicators. Focus is on the development from the first quarter of 2019 until the third quarter of 2021.

The analysis identifies several similar patterns in the five countries. In general, all five countries have recovered economically. For instance, the GDP levels are back to pre Covid-19 after a drop in the beginning of the pandemic. Moreover, none of the countries has experienced markedly more bankruptcies or higher unemployment rates in the third quarter of 2021 than in the pre-pandemic period.

Nonetheless, the five countries also differ significantly in various aspects. Firstly, the countries varies in relation to confirmed Covid-19 cases, number of deaths, and test strategies. Secondly, the government support strategies across the five countries are considerably diverse.

These identified similarities and differences are conceivably relevant for users when comparing across countries. A solid foundation of comparative statistics may help to guide policy-makers and contribute to fact-based decision-making in the context of a pandemic. Likewise, the analysis could encourage and inspire other national statistics institutes and scientists to make similar comparative analyses, e.g. of downstream structural effects. The plan is to update this analysis with new data on the recent development from the post-vaccine period. Since the beginning of 2020, Covid-19 has caused major impact on public health and economies around the world. A number of analyses have looked into socio-economic effects of Covid-19 in individual countries. However, there is need for evaluating the effects in a comparative perspective. Mandated by the Nordic chief statisticians at their meeting in Torshavn in August 2021, the Nordics (Denmark, Finland, Iceland, Norway and Sweden) published a joint report in May 2022 concerning the socio-economic effects of Covid-19. This paper is a shortened version of the report. The paper is divided into four main sections concerning i) health ii) macro economy, iii) businesses, and iiii) labour market. Focus is on the development from the first quarter of 2019 until the third quarter of 2021.

The comparison identifies several similar patterns in the five countries. In general, all five countries have recovered economically. For instance, the GDP levels are back to pre Covid-19 after a drop in the beginning of the pandemic. Moreover, employment rates increased in 2021 in all five countries, and except for Iceland, the employment rate was even higher in Q3 2021 than at the beginning of the pandemic in 2020. Nonetheless, the five countries also differ significantly in various aspects such as confirmed Covid-19 cases, number of deaths, and test strategies.

These identified similarities and differences are conceivably relevant for users when comparing across countries. A solid foundation of comparative statistics may help to guide policy-makers and contribute to fact-based decision-making in the context of a pandemic. Likewise, the analysis could encourage and inspire other national statistics institutes and scientists to make similar comparative analyses, e.g. of downstream structural effects.

Keywords: Covid-19, Nordic countries, economy, health, businesses

Session 4.1. The effects of COVID: Revulsion, recession and recovery

When: Tuesday, August 23 at 13:00 - 13:55

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Alina Grecu, Statistics Denmark, agc@dst.dk

Michael Elgaard Nielsen, Statistics Denmark, men@dst.dk

Merja Myllymäki, Statistics Finland, merja.myllymaki@stat.fi

Andreas Poldahl, Statistics Sweden, andreas.poldahl@scb.se

Thomas Moen, Statistics Norway, thomas.moen@ssb.no

Evaluating the impact of COVID-19 on companies’ activities is a topic of major interest to politicians, researchers and the public. However, COVID-19 has also impacted NSIs and how official statistics data is collected and presented. Using the most recent Global Value Chains and International Sourcing survey data collected in Denmark, Finland, Sweden and Norway, we investigate the impact of COVID19 on Nordic companies’ activities. The purpose of studying this topic in a Nordic collaboration is to present the data findings, but also to discuss challenges in collecting this type of data. The first part of the paper introduces the similarities and differences across the national surveys on international sourcing decisions. Next, we discuss the cross-country results of the survey by looking at whether companies report disruptions in international organization of activities. This includes challenges related to raw materials and intermediate products, logistical challenges, and order cancellations/declining sales. The paper also discusses experiences from the survey related to data collection challenges, data limitations and quality issues, as well as challenges involved in producing timely and dynamic structural business statistics. Finally, the paper will also point to opportunities for the future of the questionnaire and opportunities for future analysis (e.g., through micro-data linking).

Keywords: Cross-Nordic, COVID-19, global value chains, international sourcing, structural business statistics

Session 4.1. The effects of COVID: Revulsion, recession and recovery

When: Tuesday, August 23 at 13:00 - 13:55

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Knut Linnerud, Statistics Norway, knl@ssb.no

Kristin Egge-Hoveid, Statistics Norway, keg@ssb.no

The strategy for Statistics Norway (SSB) states that “Statistics Norway shall collect, use and share data for the benefit of society. We shall contribute to the quality and continuity of source data and exploit the growth of new data sources. We shall ensure the effective collection, use and sharing of data”.

Exploring and exploiting new data sources is crucial for national statistical offices (NSO) to innovate and stay relevant. To improve the quality of the upcoming household budget survey (HBS) SSB has started collecting non-survey big data from multiple commercial companies. The data contains receipt transactions from Norway’s four largest grocery chains and debit card transaction data from NETS Branch Norway.

In this paper we present the recent years processes of gaining access to, receiving and exploring these new data sources. After several years of dialogue with private data owners SSB started streaming grocery receipts in real time January 1st, 2022.

New data sources often have wider areas of utilization, in both social- and business statistics. Some structural changes in the statistical office thus would be necessary. A new unit, “Team new sources” has been established, with the role of coordinating different statistical needs for new data in the office. This unit produces cross-disciplinary work: Data collection and dialogue with data owners, subject area, methods, legal expertise and IT.

We discuss challenges regarding communication and collaboration with private data owners. Scepticism and slow processes are key words. Legal issues: In challenging private companies’ commercial interests. Confidentiality issues: When linking such data to persons pushes the limit of what is tolerable in the society. New data comes with a cost. And calls for a refreshed discussion of necessity and proportionality in the context of applying new data sources for the purpose of official statistics.

Keywords: Big data, Household budget survey, transaction data

Session 4.2. New data sources and experimental statistics

When: Tuesday, August 23 at 14:00 - 14:55

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Simon B. Halifax, Statistics Denmark, sbh@dst.dk

Measuring activity in the construction sector is an important indicator for use as short-term business statistics. We have good registry data on permitted and completed projects, but data about when the construction actually begins are usually not available before completion. A model to correct for the delay is our current setup allowing for a quarterly statistic on the number of started construction projects for every month. The accuracy of the model is limited and the data published 5 weeks after the end of a quarter.

Therefore, there is a potential for faster and more accurate statistics. With our new access to smart-meters with high frequent data on electricity consumption for every address in Denmark this potential can be released. We receive information on electricity consumption agreements once every month only 8 days after the end of the reference month. So if we can connect the advent of a new agreement and consumption on an address with information on permitted construction projects we are able to make a fast indicator of construction activity.

A pilot study was conducted identifying a single construction using consumption data and it proved to be much more reliable than the registry data. The registry data that had an incorrect date of construction start and was not available before construction end 4 months late. Going forward the idea is now to identify whether this can be extended to all construction projects and compare the results with our current quarterly statistic.

Initially, data will be made available as an experimental indicator. If it proves to be stable and reliable, the hope is to support or replace the current official statistic with a faster and potentially better one.

Keywords: constriction activity, smart-meters, electricity consumption, fast indicators, experimental statistics.

Session 4.2. New data sources and experimental statistics

When: Tuesday, August 23 at 14:00 - 14:55

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Pieter Vlag, Ulf Durnell, Jens Malmros, all at: SCB, pieter.vlag@scb.se

Anonymized and aggregated mobile phone position data from mobile network operators can be a very suitable data-source for producing official statistics about dynamic populations, commuting, tourism and long distance travelling. Having this in mind, Statistics Sweden (SCB) and one of the biggest telecom operators in the Nordics (Telia) started a collaboration in 2020, one month before the outbreak of COVID-19. The aim of the project was to analyze the quality of aggregated mobile phone data.

Because the data clearly showed changes in population movements in relation to the pandemic, public interest and interest from authorities grew considerably after the outbreak of the pandemic. At the same time, it appeared that creating stable time-series out of mobile phone position data is not straightforward in periods of sudden change, hampering an exact quantification of differences in population movements before and after the pandemic. Transparent and well-described processes were needed to tackle this issue. In this context, the collaboration gradually changed into a partnership in which the operator delivered 1) data and process descriptions and 2) SCB developed quality reports and benchmark tables to improve the data. At the same time SCB managed to receive data from another operator. After having resolved the most important quality issues, SCB started with the next and still on-going phase of the partnership: the development of dynamic population statistics which estimate variations in the actual number of people in a pre-defined area.

Some issues, which will be addressed, are: Why do we need partnerships with mobile network operators? In the collaboration, what went relatively easy and what could have been done better? Why do dynamic populations estimates meet society´s demand for up-to-date statistical information? How do these statistics fit in the system of official statistics?

Keywords: mobile phone position data, partnerships, quality, dynamic populations

Session 4.2. New data sources and experimental statistics

When: Tuesday, August 23 at 14:00 - 14:55

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Kristian Taskinen, Statistics Finland, kristian.taskinen@stat.fi

At the beginning of the Covid-19 crisis, a lot of concerns on e.g. teleworking and the data collection of statistics aroused. Fortunately, the threats of the initial phase did not materialize, and retrospectively it can be said that the pandemic accelerated renewal process of statistics significantly.

The main driver for change was the emphasis on society's information needs during the exceptional circumstances. New, faster, and more in-depth information was urgently needed to deal with the crisis and to understand its consequences for the people, economy and society. In addition, aim of avoiding social contacts encouraged innovations in new data collection methods like web scraping.

To provide relevant information for society, statistical agencies were forced to seek new data sources and collaborate with external stakeholders with potential data sources. Cooperation with researchers also took some new forms which might continue in the future.

New communication channels and tools for disseminating statistics have also been created across the countries. New era for experimental statistics has come and all kind of visualisations and dashboards are expected by users from now on.

This article describes consequences of pandemic for statistics production. Experiences are based on Statistics Finland’s internal Covid-19 group activities and European collaboration. All countries have probably some special features related to statistics production and innovations during the pandemic era. Aim of this article is to present some interesting experiences from Finland and to analyze common development trends of statistics across the Europe. Most of the observed trends were already underneath, but pandemic bring them clearly visible.

Keywords: Covid-19, information needs, innovations, timeliness, experimental statistics

Session 4.3. Innovation and timeliness in times of crisis

When: Tuesday, August 23 at 15:30 - 16:25

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Þorsteinn Aðalsteinsson, Statistics Iceland, thorsteinn.adalsteinsson@hagstofa.is

The ratio of import to native production of food is a measure of an economy’s food independence. This, along with food waste and food quality measures, is a key indicator for how well an economy allocates resources drawn from nature. The Economy-Wide Material Flow Account (EW-MFA) measures material consumption and resource productivity, but the module has limitations when users try to extract in-depth information on issues such as food independence. The limitations come from the macroscopic approach of the module, as it only considers flow of material into the economy but not within it. For example, domestic extraction only includes wild catch and harvest. The production of food from domestic animals and crops is not considered in the final compiling. This means that, although users may think the EW-MFA will help in understanding food independence, it does not. Here, I will present a method to generate a set of supply and use tables for an extended EW-MFA framework where food production within the economy is estimated. This method leverages registry data from agriculture, fishing and trade statistics that are used to compile the EW-MFA. The data is further enriched using productivity factors from literature and from outside experts, thus using a minimal modeling approach. The resulting tables give an interesting view of how food matter flows into the economy and yields food available for consumption. This provides a measure for food independence within the economy as well as food availability. By extending the EW-MFA in this way, we expand the value of the Eurostat module and use the framework’s design. The use of registry data reduces the need for surveys and other costly data collection.

Keywords: food production, Economy-Wide Material Flow Account (EW-MFA)

Session 4.3. Innovation and timeliness in times of crisis

When: Tuesday, August 23 at 15:30 - 16:25

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Søren Dalbro, Statistics Denmark, sda@dst.dk

Erik Fjærli, Statistics Norway, Erik.Fjaerli@ssb.no

As the economies turn into alert in March 2020 it emerged that the traditional statistics on bankruptcies were inadequate to measure the actual economic temperature in the enterprises. The demand on faster and more actual indicators was immense – more nowcasting, please.

This paper presents the inventions and developments of the statistics on bankruptcies which took place in the statistical offices in Norway and Denmark to meet the new requirements. We do furthermore reflect on theories on how public and private inventions and developments take place.

We’ll do that in five steps:

- First we take a short walk along the memory lane to establish the context – what happened in the economy, which changes experienced the enterprises, what was the challenges for the decision makers?

- Secondly we ask if our statistics could answer the many questions about the life of the enterprises in an abruptly changing economy – and why not.

- As the third step we present the Norwegian and Danish initiatives respectively as well as an evaluation of the degree of success.

- In the fourth step we take a broad view on how innovation and development can be stimulated in public and private organizations.

- Finally we ask about the outcome; what have we learned and can we inspire each other?

Keywords: Bankruptcies, COVID-19, economic temperature indicator, fast indicator, innovation, web-scraping, experimental statistics

Session 4.3. Innovation and timeliness in times of crisis

When: Tuesday, August 23 at 15:30 - 16:25

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Peter Bøegh Nielsen, Statistics Denmark, pbn@dst.dk

Kalle Emil Holst Hansen, Statistics Denmark, khs@dst.dk

Sini Liukkonen, Statistics Finland, sini.liukkonen@stat.fi

Alina Kerul, Statistics Iceland, Alina.Kerul@hagstofa.is

Arni Møller, Statistics Iceland, arni.moller@hagstofa.is

Jan Olav Rørhus, Statistics Norway, Jan.Rorhus@ssb.no

Andreas Poldahl, Statistics Sweden, Andreas.Poldahl@scb.se

The business statistics departments in the Nordic statistical offices have established harmonized databases in each NSI holding information at firm level. The databases are used for carrying out distributed micro data linking for analytical purposes by means of centrally developed syntax, run locally by each NSI. This approach allows for the design of harmonized, tailor-made statistical output across the Nordic countries for cross border analysis, without micro data leaving the NSIs.

The content of the database has gradually been enlarged due to new requests from policy makers or researchers. The flexible set-up has made it possible for the Nordic NSIs in a cost efficient way to address new emerging topics and consequently influence the development of business statistics internationally in terms of both organisation of harmonised data and cross national analysis and new statistical evidence supporting prioritised user needs.

In recent years, enterprise policy has focused on high growing enterprises and their potential job and value added creation but statistical evidence has not been available. In co-operation with Nordic Innovation, the Nordic NSIs developed definitions and methods to measure the fastest growing enterprises, the so-called scale-ups based on data available in the database. This work has set international standards for measuring high growth at firm level and is now the basis for a new OECD project on SMEs scaling up.

Keywords: Micro Data Linking, harmonized databases, scale-up enterprises, international comparisons

Session 4.4. NSIs v3.0: From producers to partners

When: Wednesday, August 24 at 10:30 - 11:25

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Marie Haldorson, Statistics Sweden, marie.haldorson@scb.se

Kristina Strandberg, Statistics Sweden, kristina.strandberg@scb.se

Johan Erikson, Statistics Sweden, johan.erikson@scb.se

The concepts of “Data Stewardship” and “Data Governance” are getting a lot of attention in the Official Statistical community. Depending on the national context there are different paths forward to strengthen official statistics as a strategic part of the national Data Ecosystem. All National Statistical Institutes share the same challenge; how to harness the potential from all kinds of data generated in society – and how to guard, grow and give it back to society as official statistics of high quality. For example, increasing use and re-use of our statistics as open data, fulfilling legal obligations regarding the Once Only Principle (reducing response burden for businesses), being able to provide new and timely statistics and sharing statistical knowledge and tools.

This paper describes Statistics Sweden's role as coordinator of the Swedish National Statistical System, NSS. The NSS is an important part of the national data ecosystem and an important rationale behind our efforts to strengthen Statistics Sweden’s data governance capability is to be able also to strengthen the NSS as a whole. More specifically the paper gives a concrete example on how to do this by sharing a Statistical Production Support, SPS, a knowledgebase and quality assurance hub based on a national version of the Generic Statistical Business Process Model (GSBPM).

The idea to share the SPS is not new, it was recommended in a previous Peer Review (2014) within the European Statistical System (ESS) already, that Statistics Sweden share our methods and tools with other statistical agencies responsible for official statistics. Since then, this has been incorporated to fulfil on of the Strategic Objectives of the Official Statistics of Sweden: "We do it better together". By sharing methods, tools, and processes, it is easier to secure cost efficient production of official statistics with quality that is fit for purpose.

Keywords: Data Ecosystem, Data Governance, National Statistical System, quality assurance, statistical production process, GSBPM, official statistics, national statistical institute, fit for purpose

Session 4.4. NSIs v3.0: From producers to partners

When: Wednesday, August 24 at 10:30 - 11:25

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Unni B. Grebstad, Statistics Norway, ugr@ssb.no

Anne Louisa Croos, Statistics Norway, alc@ssb.no

Svetlana Beyrer, Statistics Norway, svb@ssb.no

Over the last years different parties, typically decision makers in the public administration and data users like students and researchers, have expressed needs to disseminate official statistics on the Child Welfare Services (CWS) in Norway more frequently than Statistics Norway (SSB) has done so far. To meet these needs, would among other things imply a more automated data collection from the CWS offices located in the 356 municipalities in Norway. SSB is currently publishing the official statistics from the CWS as well as other KOSTRA-statistics (Municipality-State-Reporting) following this time schedule: 1) Unrevised figures are published in KOSTRA on 15 March every year, 2) Revised figures are published in KOSTRA on 15 June every year, 3) More detailed statistics are published every year at the end of June/beginning of July.

DigiBarnevern (DBV) is the name of a project that SSB has been heavily involved in since 2020 to better meet user needs for child welfare statistics. DBV works with shaping the new way of importing data more frequently from the CWS using a cloud solution.

The development processes use agile methodology. In short, this means that the tasks at hand and the problem solving are organized in so-called ‘sprints’, each lasting 14 days, where a scrum team with both IT and statistics competence have worked together to complete the goals of the sprints in collaboration with The Norwegian Directorate for Children, Youth and Family Affairs (Bufdir). Bufdir finances the project and is the owner of the data from the Child Welfare Services. This has probably enabled necessary resources to complete the DBV project.

The paper aims to highlight the benefits of working together in sprints and will provide valuable insight for future collaborations/processes.

Keywords: Child Welfare Services (CWS), frequent dataflow, municipalities, cloud computing, agile methodology

Session 4.4. NSIs v3.0: From producers to partners

When: Wednesday, August 24 at 10:30 - 11:25

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