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Cover page for working paper

Transforming Zambia’s Labour Force Survey using artificial intelligence

Working paper 12 Jun 2025 Sustainable Growth and State Effectiveness

This working paper evaluates the use of GPT-4 Turbo to classify open-ended responses from Zambia’s 2023 Labour Force Survey into standardised occupational and industry codes. The results show that GPT-4 Turbo significantly outperforms human enumerators in accuracy, offering potential efficiency gains of up to 130 working days annually for the Zambia Statistics Agency.

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Cover page for working paper

Authors

Ty Rossow cropped profile picture

Tyler Rossow

ZEL Data Analyst, Zambia, International Growth Centre
Tobias Edison profile picture

Tobias Edison

Data Engineer at Zambia Evidence Lab (ZEL), Zambia, International Growth Centre
Rory Hardie profile picture

Rory Hardie

Country Economist, Zambia, International Growth Centre

Harry Mayne

  • Rossow-et-al-Working-Paper-June-2025.pdf Download

    PDF document • 1.04 MB

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