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Better data, higher impact: improving agricultural data systems for societal change
[Correlated non-classical measurement errors, ‘second best’ policy inference, and the inverse size-productivity relationship in agriculture]

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  • Calogero Carletto

Abstract

The agricultural sector is undergoing a period of rapid transformation, driven by the powerful and interconnected impacts of climate change, demographic transitions and uneven economic growth around the world. For governments and the international community to navigate this period of upheaval to protect vulnerable populations and ensure positive societal change will require a similar degree of transformation within agricultural data systems. While technological innovation has resulted in substantive improvements in the availability, timeliness and overall quality of agricultural data, many technical and institutional challenges remain. This paper reviews recent developments in the agricultural data landscape, highlights existing constraints to further progress and argues for agricultural economists to take responsibility for building agricultural data systems equipped to respond to the diverse needs of a changing world.

Suggested Citation

  • Calogero Carletto, 2021. "Better data, higher impact: improving agricultural data systems for societal change [Correlated non-classical measurement errors, ‘second best’ policy inference, and the inverse size-productivity r," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 48(4), pages 719-740.
    • Handle: RePEc:oup:erevae:v:48:y:2021:i:4:p:719-740.
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    References listed on IDEAS

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    3. Holden, Stein T. & Makate, Clifton & Tione, Sarah, 2023. "Measurement Error and Farm Size: Do Nationally Representative Surveys Provide Reliable Estimates? ," CLTS Working Papers 7/23, Norwegian University of Life Sciences, Centre for Land Tenure Studies.

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