Knowledge accumulation in US agriculture: research and learning by doing
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Knowledge accumulation in US agriculture: research and learning by doing Sansi Yang
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C. Richard Shumway2
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© Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract We investigate the role of public research investment (R&D) and learning by doing (LBD) in improving productivity through an empirical examination of the US agricultural production sector. We construct a dual model and track R&D and LBD impacts on returns to scale, production cost, and input demand utilizing data for more than a century. A Bayesian approach is used to maintain regularity conditions implied by economic theory. We find that US agriculture shows significant evidence of increasing returns to scale when both R&D and LBD are included in the production process. R&D and LBD are complementary in reducing cost as an increase in one stock significantly strengthens the cost-reducing effect of the other. The direct impacts of R&D and LBD on scale economies, cost, and input demands are sensitive to choices of R&D lag structure, LBD proxy, LBD knowledge depreciation rate, and data period. But input demand price elasticities are highly robust across model specification. Keywords Cost function Input demand Knowledge accumulation Learning by doing Research investment R&D ●
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JEL classification D24 Q16 ●
1 Introduction Technical change has been the driving force for growth in US agriculture for many decades. Despite some evidence of a recent slowdown, US agriculture has experienced strong and sustained growth. Over the last 60 years, aggregate output grew at a rate of 1.49% per year, which was driven mainly by growth in total factor productivity (largely technical change) at an annual rate of 1.42% (Wang et al. 2015). Further, there is substantial evidence that accumulated knowledge is a significant source of technical change (Arrow 1962; Romer 1986; Adams 1990; Ruttan 2002; Ulku and Pamukcu 2015; Voyvoda and Yeldan 2015; Bretschger et al. 2017). One strand of the knowledge literature models is the creation of knowledge from research and development
* Sansi Yang [email protected] 1
School of Agricultural Economics and Rural Development, Renmin University of China, Beijing 100872, China
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School of Economic Sciences, Washington State University, Pullman, WA, USA
expenditures (R&D). A pioneering study by Romer (1986) modeled knowledge as a positive externality emanating from R&D. Knowledge gained from R&D expenditures has frequently been found to be a major contributor to productivity growth (Morrison and Siegel 1997; Wakelin 2001; Griffith et al. 2004; Ang and Madsen 2011; Yasar and Morrison Paul 2012; Doraszelski and Jaumandreu 2013; Kancs and Siliverstovs 2016). In the agricultural sector, the relationship between agricultural research expenditures and productivity growth has also been widely studied (Huffman and Evenson 2006; Onofri and Fulginiti 2008; Alston et al. 2010; Wang et al. 2012; Andersen 2015; Pardey et al. 2015; Khan et al. 2017). Another line of knowledge literature i
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