An expanded knowledge production function

IF 0.2 Q4 BUSINESS Revista Brasileira de Inovacao Pub Date : 2022-01-06 DOI:10.20396/rbi.v20i00.8661402
Pedro Henrique Batista de Barros, Adirson Maciel de Freitas Júnior
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Abstract

This paper uses a theoretical motivation for an Expanded Knowledge Production Function(EKPF) that encompasses both path dependence and spatial spillovers to search for evidences inBrazil using a Dynamic Spatial Panel Data approach. The purpose is to identify the determinantsof knowledge production in the 2005-2015 period as well as its temporal evolution, usinginnovation patents as proxies. Regarding its spatial distribution, we identified a North-Southdisparity for the knowledge production in Brazil, with Southeast and South producing alarge part of the country’s patents. Based on the EKPF, we confirmed the importance ofpath dependence and knowledge spillovers to explain the Brazilian innovation. In addition,population density, which generates Jacobian externalities and economies of agglomeration, isan important structural feature in the short run while the number of researchers in universitiesand an increased economic scale are essential to knowledge production in the long run.
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扩展的知识生产函数
本文利用包含路径依赖和空间溢出的扩展知识生产函数(EKPF)的理论动机,使用动态空间面板数据方法在巴西寻找证据。以创新专利为代表,研究2005-2015年知识生产的影响因素及其时间演化。在空间分布方面,我们发现巴西的知识生产存在南北差异,东南部和南部生产了大部分国家的专利。基于EKPF,我们证实了路径依赖和知识溢出在解释巴西创新中的重要性。此外,在短期内,产生雅可比外部性和集聚经济的人口密度是一个重要的结构特征,而在长期内,大学研究人员的数量和经济规模的增加对知识生产至关重要。
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发文量
19
审稿时长
2 weeks
期刊最新文献
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