Identifying Factor Productivity from Micro-data: The case of EU agriculture

Martin Petrick and Mathias Kloss ()

No 144, Factor Markets Working Papers from Centre for European Policy Studies

Abstract: The classical problem of agricultural productivity measurement has regained interest owing to recent price hikes in world food markets. At the same time, there is a new methodological debate on the appropriate identification strategies for addressing endogeneity and collinearity problems in production function estimation. We examine the plausibility of four established and innovative identification strategies for the case of agriculture and test a set of related estimators using farmlevel panel datasets from seven EU countries. The newly suggested control function and dynamic panel approaches provide attractive conceptual improvements over the received ‘within’ and duality models. Even so, empirical implementation of the conceptual sophistications built into these estimators does not always live up to expectations. This is particularly true for the dynamic panel estimator, which mostly failed to identify reasonable elasticities for the (quasi-) fixed factors. Less demanding proxy approaches represent an interesting alternative for agricultural applications. In our EU sample, we find very low shadow prices for labour, land and fixed capital across countries. The production elasticity of materials is high, so improving the availability of working capital is the most promising way to increase agricultural productivity.

Pages: 41 pages
Date: 2013-01
New Economics Papers: this item is included in nep-agr, nep-cwa, nep-eff and nep-eur
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Citations: View citations in EconPapers (10)

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Related works:
Working Paper: Identifying factor productivity from micro-data: the case of EU agriculture (2018)
Working Paper: Identifying factor productivity from micro-data: The case of EU agriculture (2018)
Working Paper: Identifying Factor Productivity from Micro-data: The case of EU agriculture (2013)
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