Everything under control: comparing machine learning and classical econometric impact assessment methods using FADN data

Machine learning (ML) methods have been proposed to improve the assessment of agricultural policies through enhanced causal inference. This study uses a simulation framework tailored to Farm Accountancy Data Network (FADN) data to scrutinize the performance of both ML and classical methods under div...

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Veröffentlicht in:	European review of agricultural economics 2024-12
Hauptverfasser:	Brignoli, P L, de Mey, Y, Gardebroek, C
Format:	Artikel
Sprache:	eng
Online-Zugang:	Volltext
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