Abstract
This paper examines the impact of R&D on multifactor productivity in the U.S. agricultural sector over the 1910–1990 period. We use the Bennet–Bowley indicator to measure agricultural productivity based on a multiple output-multiple input technology. We demonstrate the relationship between the price dependent Bennet–Bowley indicator and the Luenberger productivity indicator which is constructed from directional distance functions without requiring price information. These performance measures are dual to the profit function which arguably makes them especially useful in the agricultural setting. We employ time-series techniques to investigate the effect of R&D on the pattern of productivity growth. We find that we cannot reject the presence of a cointegrating relationship between the two series and that productivity growth in the U.S. agriculture responds positively to R&D expenditure with a lag of between four and ten periods.
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Notes
Färe et al. (2007) provide a condition for \(\pounds^t\) to equal \(\pounds^{t+1}.\) It states that the distance function must be additively separable in inputs/outputs and time.
See Balk (2003), who attributed this index to Törnqvist.
This was first shown by Balk et al. (2008).
The quadratic form readily allows for the translation property of the directional distance function, see Chambers (2002).
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We would like to thank Steve Buccola, Ken Carlaw and the participants in the 2005 NZESG meetings at the University of Canterbury and the EWEPA conference in Brussels for their comments.
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Färe, R., Grosskopf, S. & Margaritis, D. U.S. productivity in agriculture and R&D. J Prod Anal 30, 7–12 (2008). https://doi.org/10.1007/s11123-008-0092-8
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DOI: https://doi.org/10.1007/s11123-008-0092-8