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Innovation Complexity in AgTech: The case of Brazil, Kenya and the United States of America?
Economic Research Working Paper No.82
This paper illustrates successful policies and incentives that build on local innovation capabilities across three agricultural innovation hubs at different income levels and across different geographical regions. It makes the case for how countries highly complex innovation ecosystems, which refer to the diversity and sophistication of local innovators and the types of innovation they produce, tend to have more opportunities to shift their technological path to the frontier. The paper focuses on three agricultural hubs across different income levels and geography to illustrate how smart policies that focus on building local capabilities can help countries diversify and create their own agricultural technological paths. These hubs include: São Paulo in Brazil, Nairobi in Kenya and Colorado in the United States of America.
Publication year: 2024
Can we map innovation capabilities?
Economic Research Working Paper No.81
Recent years have witnessed a resurgence of industrial policies globally. Through various industrial policy instruments, governments make critical scientific and technological choices that shape innovation paths and resource allocations. Our paper explores innovation capabilities as essential drivers of competitive outcomes, spanning science, technology, and production domains. Based on the economic complexity literature, we propose a methodological framework to measure the innovation capabilities empirically, leveraging data on scientific publications, patents, and trade. Our findings highlight the multidimensional nature of innovation capabilities and underscore the importance of understanding both the specialization and quality of these capabilities. Our results are in line with the complexity literature, as we also find: (i) positive correlations between the innovation complexity and economic growth; and, (ii) the predictive power of existing innovation capabilities for fostering new ones. Based on these findings, we propose novel indicators informing innovation policymaking on the innovation potential across science, technology, and production fields of an ecosystem. We suggest that innovation policymaking needs to be informed by deeper insights into innovation capabilities that are crucial for long-term growth and competitiveness improvement.
Global Trends in Innovation Patterns: A Complexity Approach
Economic Research Working Paper No.80
Technological know-how in a country shapes its growth potential and competitiveness. Scientific publications, patents, and international trade data offer complementary insights into how ideas from science, technology, and production evolve, combine, and are transformed into capabilities. Analyzing their trajectories enables a more comprehensive and multifaceted understanding of the whole innovation process, from generating ideas to internationally commercializing products. We analyze the production patterns in these three domains, documenting the differences between advanced and emerging market economies. We find that future income, patenting, and publishing growth correlate with the economic complexity indices calculated from these domains. Capabilities embedded in the country also shape future diversification opportunities and make the innovation process path dependent. Lastly, we also show that diversification opportunities can be inferred across innovation domains.
Innovation Policies Under Economic Complexity
Economic Research Working Paper No.79
Recent geopolitical challenges have revived the implementation of industrial and innovation policies. Ongoing discussions focus on supporting cutting-edge industries and strategic technologies but hardly pay attention to their impact on economic growth. In light of this, we discuss the design of innovation policies to address current development challenges while considering the complex nature of productive activities. Our approach conceives economic development and technological progress as a process of accumulation and diversification of knowledge. This process is limited by the tacit nature of knowledge and by countries' binding constraints to growth. Consequently, effective innovation policies should be place-based and multidimensional, leveraging countries' existing capabilities and addressing countries' current problems. This contrasts policies that lead to economic efficiencies, such as copying other countries' solutions to problems that countries do not currently have.
Getting the innovation ecosystem ready for AI
An IP policy toolkit
As AI technologies evolve at an exponential pace there are many questions and challenges for IP and the IP system. The purpose of this IP policy toolkit is to provide policymakers with a framework to understand the state of play of AI innovation right now and to think about the future as AI becomes increasingly autonomous.