New evidence on intangibles, diffusion and productivity

Corrado, Carol; Criscuolo, Chiara; Haskel, Jonathan; Himbert, Alexander; Jona-Lasinio, Cecilia

doi:10.1787/de0378f3-en

Cited by 8 publications

(8 citation statements)

References 35 publications

(70 reference statements)

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“…Furthermore, the cloud variable is statistically significant in the majority of countries considered (Belgium, Denmark, Italy, Japan, Korea), losing significance in Switzerland and Israel only. 38 The link between ultra-fast broadband connections and AI is also positive, but to some extent weaker than the AI-cloud relation. 39 Using ultra-fast broadband connections is indeed positively linked with AI use in all countries considered (Belgium, France, Israel, Italy, Portugal), although significant in Belgium and France only.…”

Section: Factors Complementary To Ai Usementioning

confidence: 99%

A portrait of AI adopters across countries

2023

OECD Science, Technology and Industry Working Papers

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Working PapersOECD Working Papers should not be reported as representing the official views of the OECD or of its member countries. The opinions expressed and arguments employed are those of the authors. Working Papers describe preliminary results or research in progress by the author(s) and are published to stimulate discussion on a broad range of issues on which the OECD works. Comments on Working Papers are welcomed, and may be sent to Directorate for

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Section: Factors Complementary To Ai Usementioning

confidence: 99%

A portrait of AI adopters across countries

2023

OECD Science, Technology and Industry Working Papers

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“…Data about one consumer may be informative about other consumers, which can lead to too-low prices (Acemoglu et al, 2019[35]; Bergemann and Bonatti, 2019 [50]) and too-large collection of personal data (Choi, Jeon and Kim, 2019 [51]). This negative externality might help explain why consumers are rarely paid for sharing their personal data and are only compensated with free access to digital services (Acquisti, John and Loewenstein, 2013 [52]).…”

Section: Externalities Associated With Personal Datamentioning

confidence: 99%

Measuring the value of data and data flows

2022

OECD Digital Economy Papers

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Introduction 1.1 Why measure the value of data? 1.2 Outline 2 Data and the economy 2.1 What are data? 2.2 The rise of the data economy 2.3 Economic characteristics of data 2.4 Implications for the measurement of the value of data Key take-aways 3 Sales of data and data-intensive services 3.1 Data markets 3.2 Sales of data and data-intensive services 3.3 International trade in data services 3.4 Cross-border data flows underpinning international trade 3.5 Venture capital to big data firms Key take-aways 4 Recording data in macroeconomic statistics 4.1 Data in the System of National Accounts 4.2 Valuation of data 4.3 Evidence from experimental studies 4.4 Practical challenges for the sum-of-cost approach Key take-aways

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“…In addition, there is a risk that data may increase the likelihood of conglomerate mergers (mergers between firms that are neither competitors nor in a supply relationship) generating harm (OECD, 2020 [63]). For example, personal data collection in one market might be leveraged into market power in a related market, limiting the contestability of both markets (Condorelli and Padilla, 2019 [64]).…”

Section: Data Have Reshaped Competitive Dynamics Across the Oecdmentioning

confidence: 99%

Data shaping firms and markets

2022

OECD Digital Economy Papers

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This report analyses how firms use data, and how that use shapes markets. It presents policy lessons to encourage the more even use of data in the business population, which is necessary to realise the potential of data for growth and well-being. This report was drafted by Angela Attrey and James Mancini, under the guidance of Antonio Capobianco and Jeremy West, and the supervision of Audrey Plonk, Head of the OECD Digital Economy Policy Division. The report benefits from the input and research of focal points across the OECD Secretariat, including the Directorate for Science, Technology and Innovation (Sara Calligaris, Flavio Calvino, David Gierten, Simon Lange and Vincenzo Spiezia), the Centre for Entrepreneurship, SMEs, Regions and Cities (Marco Bianchini, Lucia Cusmano, Sandrine Kergroach and Lora Pissareva), the Directorate for Financial and Enterprise Affairs (Oliver Garrett-Jones and Iota Nassr) and the Economics Department (Lilas Demmou). The insights from participants of the virtual OECD Workshop "Data Shaping Firms and Markets", held on 11 May 2022, are gratefully acknowledged. Angela Gosmann and Mark Foss provided editorial support. This publication is a contribution to IOR 1.3.1.2.3 of the 2021-2022 Programme of Work and Budget of the Committee on Digital Economy Policy. This report was approved and declassified by the Committee on Digital Economy Policy on 27 September 2022 and prepared for publication by the OECD Secretariat.This publication is a contribution to Phase III of the OECD Going Digital project, which aims to provide policy makers with the tools they need to design and implement better data policies to promote growth and well-being.For more information, visit www.oecd.org/going-digital.

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New evidence on intangibles, diffusion and productivity

Cited by 8 publications

References 35 publications

A portrait of AI adopters across countries

A portrait of AI adopters across countries

Measuring the value of data and data flows

Data shaping firms and markets

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