• This research incorporates vintages of R&D stocks in a global CGE model for improving projections of food security.• With current R&D intensity, productivity growth will not be sufficient to avoi... In this paper, the impact of public R&D investment on agricultural productivity and long-term food security via R&D driven endogenous technical change is analysed. The findings show that R&D growth...

Prague Economic Papers - impact factor journal of the University of Economics, Prague

The purpose of this chapter is to analyze the impact of public agricultural Research and Development (R&D) investments on agricultural productivity and long-term food security to derive policy recommendations. The methodological approach is based on the application of the state-of-the art Computable General Equilibrium (CGE) model to R&D. By endogenizing R&D in global CGE models, it is possible to assess the impact of different public R&D policies on the food availability and food access of food security. This study found that R&D investments bring positive effects on the food access dimension of food security, particularly in places such as Sub-Saharan Africa where prices are expected to grow significantly by 2050, as agricultural land becomes scarcer and more expensive. Doubling the R&D intensity would soften the land constraints and substantially decelerate food prices, thus preventing the deterioration of living standards of rural households and leading to a gain in daily caloric consumption. The impact of alternative agricultural R&D policies on the various dimensions of food security has not been analyzed using a CGE framework, which enables capturing both the benefits and costs from R&D investments. Modeling the dynamic accumulation of R&D stocks makes it possible to analyze the effects of R&D on food security over time.

The aim of the paper is to quantify endogenous factor-augmenting technical change driven by R&D investments in a panel of 11 OECD countries over 1987–2007. This paper contributes to the scant empirical evidence on the speed, sources and direction of technical change for various sectors and production factors. Assuming cost-minimization behavior, a CES framework is used to derive a system of equations that is estimated by a GMM system estimator. The estimated factor-augmenting technology parameters show that in most sectors, technical change was labor-augmenting and labor-saving. Statistically significant effects of manufacturing and services R&D were found on factor-augmenting technical change (with the highest R&D elasticities found in the high-tech manufacturing and transport, storage and communication sectors). Whereas ‘in-house’ R&D stimulates total factor productivity, R&D spilled over to other sectors has a capital-augmenting effect accompanied by a higher use of labor. The results of this study provide a starting point for incorporating endogenous factor-augmenting technical change in impact assessment models aimed at broad policy analysis including economic growth, food security or climate change.