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Data and Code For: Firm-Level Automation: Evidence from the Netherlands

Version
1
Resource Type
Dataset : program source code
Creator
  • Bessen, James (Boston University)
  • Goos, Maarten (Utrecht University)
  • Salomons, Anna (Utrecht University)
  • van den Berge, Wiljan (CPB Netherlands Bureau for Economic Policy Analysis)
Publication Date
2020-09-10
Description
  • Abstract


    In this paper, we use a Dutch firm-level survey on automation expenditures linked to administrative records covering the universe of firms in the Netherlands to consider firm-level automation over 2000-2016. While we do not observe the specific automation technology being adopted, ours is an omnibus measure allowing us to study automation across all private non-financial sectors of the economy.
    We first define automation events at the firm-level by exploiting the lumpy nature of automation investments. Next, we show that firms that have automation events experience higher employment growth and revenue growth than firms that do not have these events, consistent with findings for robotics. Using a descriptive event study at the firm level, however, we see that firms do save labor after investing in automation technology, while wages continue to rise. Importantly, these effects arise among both manufacturing and non-manufacturing firms, indicating that this is not specific to technologies like robotics.
Availability
Download
This study is freely available to the general public via web download.
Relations
  • Is version of
    DOI: 10.3886/E120789
Publications
  • Bessen, James, Maarten Goos, Anna Salomons, and Wiljan van den Berge. “Firm-Level Automation: Evidence from the Netherlands.” AEA Papers and Proceedings 110 (May 2020): 389–93. https://doi.org/10.1257/pandp.20201004.
    • ID: 10.1257/pandp.20201004 (DOI)

Update Metadata: 2020-09-10 | Issue Number: 1 | Registration Date: 2020-09-10

Bessen, James; Goos, Maarten; Salomons, Anna; van den Berge, Wiljan (2020): Data and Code For: Firm-Level Automation: Evidence from the Netherlands. Version: 1. ICPSR - Interuniversity Consortium for Political and Social Research. Dataset. https://doi.org/10.3886/E120789V1