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Researchers

Klaus Prettner

Professor of Macroeconomics, Vienna University of Economics and Business
Signed the letter · Academia · Austria

homepage · other · scholar

Professor of Macroeconomics at the Vienna University of Economics and Business (WU). Research on economic growth, inequality, demographic change, and the economic consequences of automation. Co-author, with David E. Bloom, of 'Automation and Its Macroeconomic Consequences: Theory, Evidence, and Social Impacts' (Academic Press, 2020). Author of work on automation and labor, including 'AI innovation and the labor share in European regions' (European Economic Review, 2025). Signed the wemustactnow.ai open letter.

AI-written Documented facts only, from the sources below.

35 works in the co-authorship map · 4,819 citations across them

Sources

  1. “a Professor of Macroeconomics at WU (Vienna University of Economics and Business)” — source
  2. Automation and Its Macroeconomic Consequences, by Klaus Prettner and David E. Bloom (Academic Press, 2020)
  3. AI innovation and the labor share in European regions
  4. “Signed the wemustactnow.ai open letter” — source

In the network

7 co-authors on the map · PageRank #5 of 400 · bridge #24 of 400 · 4 steps from Erik Brynjolfsson · cluster: Automation, growth and robot taxes.

Measured on this map only, which grows out of the letter's signatories; what these numbers mean. See Klaus Prettner on the map

Documented positions

Will AI actually boost productivity and growth? unknown

No documented evidence reviewed yet.

Will AI destroy more jobs than it creates? leans agree

Models technological unemployment from automation in search-and-matching frameworks and finds displacement pressure real.

Evidence

  1. Technological unemployment revisited: automation in a search and matching framework

Why researchers disagree on this · Who else says what

Will AI widen inequality? agrees

His macro models and empirical work find automation raises inequality and depresses the labor share without policy intervention.

Evidence

  1. Innovation, automation, and inequality: Policy challenges in the race against the machine
  2. AI innovation and the labor share in European regions

Why researchers disagree on this · Who else says what

Should governments act on AI now? leans agree

Studies optimal taxation of AI and policy challenges 'in the race against the machine' — policy action is his research premise.

Evidence

  1. Workers' Incentives and the Optimal Taxation of AI
  2. Innovation, automation, and inequality: Policy challenges in the race against the machine

Why researchers disagree on this · Who else says what

How fast will the impact arrive? unknown

No documented evidence reviewed yet.

Selected work

Writes with

David E. Bloom (11), Ana Lucia Abeliansky (4), Emanuel Gasteiger (4), Michael Kühn (4), Holger Strulik (3), Jamel Saadaoui (3), Jakub Growiec (2)

Co-authors on the map, by papers written together (7 of 7 shown).

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