The Proliferation of “Big Data” and Implications for Official Statistics and Statistical Agencies

Reimsbach-Kounatze, Christian

doi:10.1787/5js7t9wqzvg8-en

Cited by 17 publications

(12 citation statements)

References 14 publications

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“…The Australian Department of Education, Employment and Workplace Relations (DEEWR) has created the Internet Vacancy Index (IVI) based on new vacancies from four online recruitment websites. This complements the newspaper-based Skilled Vacancy Index (SVI) also created by the DEEWR (Reimsbach-Kounatze, 2015).…”

Section: Improving Policy Prediction and Nowcastingmentioning

confidence: 99%

Using digital technologies to improve the design and enforcement of public policies

2019

OECD Digital Economy Papers

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Section: Improving Policy Prediction and Nowcastingmentioning

confidence: 99%

Using digital technologies to improve the design and enforcement of public policies

2019

OECD Digital Economy Papers

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“…The introduction of drone deliveries has helped introduce a cheaper and more demand-responsive system, preventing stockouts at local facilities while at the same time minimising waste (which is particularly relevant in case of blood which has a short shelf life and must be kept refrigerated) (Rosen, 2017). The Rwandan authorities established supportive drone regulations.…”

Section: Drones For Humanitarian Aid and Development Projectsmentioning

confidence: 99%

“…Some countries are leading in providing e-services, others see the growth of large national "digital" sectors driven by private companies. A recent OECD report found that this generated considerable mismatches between the supply of and demand for ICT skills in general and for ICT specialist skills in particular (Reimsbach-Kounatze, 2015), which suggest that government authorities might increasingly have to bid against private firms for people with the required skills and could be forced to pay a premium to attract them to public service.…”

Section: Building Regulatory Capacity In Authoritiesmentioning

confidence: 99%

(Un)certain Skies?

2018

International Transport Forum Policy Papers

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What we didThis report investigates the role of drones as part of the future transport mix. It specifically addresses the issues policy makers face in engaging with the emerging private drone sector. Drones for recreational purposes are not part of this study.Drones are already deployed in the transport sector in surveying and monitoring the condition of infrastructure. They also promise to provide innovative services in freight delivery, passenger transport and disaster relief. With the sector developing at a rapid pace, regulators will want to create frameworks for drone use that allow innovation while ensuring positive overall outcomes.The potential impacts of large commercial drone fleets are as yet not fully understood. Assessment of the potential impact on aviation has begun but appraisal is rarely addressed from a cross-sectoral perspective.Freight drones for urban goods deliveries and, eventually, drones for passenger travel, may have both positive impacts (e.g. improved connectivity in remote regions, traffic congestion alleviation, reduced travel times) and negative impacts (e.g. safety, privacy, noise, energy consumption, land use and visual amenity concerns). We explore how some of these impacts could be anticipated and included in appraisal guidelines to support the underlying policy goals of efficient, safe, sustainable and equitable transport.The insights in this report build on expert interviews, a review of published research and a workshop with 37 international experts held in San Francisco in November 2017. Attendees included drone manufacturers, leaders of regulatory, humanitarian and economic organisations as well as representatives of companies that utilise drones as a central component of their businesses, or are planning to do so.

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“…One of the items in the European Code of Practice [7], is that NSIs should warn the public and policy makers when statistical results are being used inappropriately or are being misrepresented. As emphasized in [8,16], with big data it is easy to find spurious results, and there is a role for NSIs as statistical authorities to offer best practices for analysing big data.…”

Section: Google Trends For Nowcastingmentioning

confidence: 99%

``Re-make/Re-model'': Should big data change the modelling paradigm in official statistics?

Braaksma

Zeelenberg

2015

SJI

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Big data offers many opportunities for official statistics: for example increased resolution, better timeliness, and new statistical outputs. But there are also many challenges: uncontrolled changes in sources that threaten continuity, lack of identifiers that impedes linking to population frames, and data that refers only indirectly to phenomena of statistical interest. We discuss two approaches to deal with these challenges and opportunities. First, we may accept big data for what they are: an imperfect, yet timely, indicator of phenomena in society. These data exist and that's why they are interesting. Secondly, we may extend this approach by explicit modelling. New methods like machine-learning techniques can be considered alongside more traditional methods like Bayesian techniques. National statistical institutes have always been reluctant to use models, apart from specific cases like small-area estimates. Based on the experience at Statistics Netherlands we argue that NSIs should not be afraid to use models, provided that their use is documented and made transparent to users. Moreover, the primary purpose of an NSI is to describe society; we should refrain from making forecasts. The models used should therefore rely on actually observed data and they should be validated extensively.

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The Proliferation of “Big Data” and Implications for Official Statistics and Statistical Agencies

Cited by 17 publications

References 14 publications

Using digital technologies to improve the design and enforcement of public policies

Using digital technologies to improve the design and enforcement of public policies

(Un)certain Skies?

``Re-make/Re-model'': Should big data change the modelling paradigm in official statistics?

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