A Bayesian statistical analysis of return to agricultural R&D investment in Latin America: Implications for food security

The world faces serious challenges in addressing food security highlighting the importance of agricultural productivity growth. Agricultural R&D investment has been the focus of several empirical works; however, the evidence concerning its returns in Latin America is limited. This study contributes to filling this gap by analyzing the rates of return to domestic and foreign agricultural research spending while discussing its speed of diffusion using Bayesian Dynamic Stochastic Production Frontier models. This approach also makes it possible to differentiate between Short-Run Technical Efficiency (SRTE) and Long-Run TE (LRTE). The results show that the average gap between SRTE and LRTE across countries is about 6% points implying that inefficiency in the production process is persistent over time. Furthermore, the findings show that the average benefit generated by each additional dollar spent in agricultural research over the 1981–2012 period, assuming a discount rate of 3%, ranges from $1.8:1 to $4.2:1, depending on the lag weight structure adopted, and this figure rises to between $6:1 and $19.5:1 when spillover benefits to other countries within the region are considered. The speed of technology diffusion is heterogeneous across countries, and the estimates confirm underinvestment in agricultural R&D. These results suggest that policies targeted to enhance food security need to incorporate significant investments in agricultural R&D. •This study presents a Bayesian analysis of return to agricultural R&D investment in Latin America.•Latin American countries have not yet reached their equilibrium value in terms of efficiency.•The Marginal Benefit Cost for foreign agricultural R&D varies between $6.8 to $34.8 with an average of $19.5•The Marginal Benefit Cost for domestic agricultural R&D ranges from $1.9 to $8.8, with an overall average of $3.6•Countries’ unobserved heterogeneity reflecting agroecological characteristics and time-invariant features also play a critical role in productivity gains.