Growth Through Inter-sectoral Knowledge Linkages

Cai, Jie; Li, Nan

doi:10.1093/restud/rdy062

Cited by 32 publications

(18 citation statements)

References 75 publications

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“…Jones, 2011; Bartelme and Gorodnichenko, 2015) as well as other types of linkages, e.g. those based on similarities in labor skills and technologies (Hausmann and Hidalgo, 2011;Ellison et al, 2010;Hanlon and Miscio, 2017;Cai and Li, 2018). Focusing on the relatively simple context of highly specialized agricultural economies, we provide clear-cut evidence that the composition of production can influence the growth process through various sorts of linkages.…”

Section: Introductionmentioning

confidence: 85%

Staple Products, Linkages, and Development: Evidence from Argentina

Droller¹,

Fiszbein²

2019

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We investigate how historical patterns of primary production influenced development across local economies in Argentina. Our identification strategy exploits exogenous variation in the composition of primary production induced by climatic features. We find that locations specializing in ranching had weaker linkages with other activities, higher concentration in land ownership, lower population density, and less immigration than cerealproducing areas. Over time, ranching localities continued to exhibit lower population density and they experienced relatively sluggish industrialization. Ultimately, ranching specialization had large negative effects on long-run levels of income per capita and human capital. Our findings show that early patterns of production can have a crucial influence on development patterns, providing suggestive support to the staple theory of economic growth.

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Section: Introductionmentioning

confidence: 85%

Staple Products, Linkages, and Development: Evidence from Argentina

Droller¹,

Fiszbein²

2019

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“…So-called 'main paths' in technological trajectory analysis (Hummon andDereian, 1989, Verspagen, 2007) could be particularly sensitive to the weights that are placed on, or empirically determined for, different layers or citation contexts. The multilayer framework may also conceptually aid traditional economic analyses (Cai and Li, 2019), for which it is possible, for example, to allow layers to differ in importance when constructing proxy network variables that attempt to capture an abstract concept.…”

Section: Future Workmentioning

confidence: 99%

Multilayer patent citation networks: A comprehensive analytical framework for studying explicit technological relationships

Higham,

Contisciani,

De Bacco

2022

Preprint

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The use of patent citation networks as research tools is becoming increasingly commonplace in the field of innovation studies. However, these networks rarely consider the contexts in which these citations are generated and are generally restricted to a single jurisdiction. Here, we propose and explore the use of a multilayer network framework that can naturally incorporate citation metadata and stretch across jurisdictions, allowing for a complete view of the global technological landscape that is accessible through patent data. Taking a conservative approach that links citation network layers through triadic patent families, we first observe that these layers contain complementary, rather than redundant, information about technological relationships. To probe the nature of this complementarity, we extract network communities from both the multilayer network and analogous single-layer networks, then directly compare their technological composition with established technological similarity networks. We find that while technologies are more splintered across communities in the multilayer case, the extracted communities match much more closely the established networks. We conclude that by capturing citation context, a multilayer representation of patent citation networks is, conceptually and empirically, better able to capture the significant nuance that exists in real technological relationships when compared to traditional, single-layer approaches. We suggest future avenues of research that take advantage of novel computational tools designed for use with multilayer networks.

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“…First, our focus is on innovation and knowledge diffusion. Second, besides the factor demand linkages, this paper also simultaneously consider the intrinsic interconnections of technologies embodied in different sectors, which turns out to be significant and relevant when studying innovation and diffusion (Cai and Li 2017). Related to the current work, Cai and Li 2016 study knowledge spillovers across sectors within a country and how trade costs affect the distribution of endogenous knowledge accumulation across sectors.…”

Section: Introductionmentioning

confidence: 98%

Knowledge Diffusion, Trade, and Innovation across Countries and Sectors

Cai

Santacreu

2022

American Economic Journal: Macroeconomics

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This paper provides a unified framework for quantifying the cross-country and cross-sector interactions among trade, innovation, and knowledge diffusion. This framework is used to study the effect of trade liberalization in an endogenous growth model in which comparative advantage and the stock of knowledge are determined by innovation and diffusion. The model is calibrated to match observed cross-country and cross-sector heterogeneity in production, innovation efficiency, and knowledge spillovers. The counterfactual analysis shows that a reduction in trade costs induces a reallocation of R&D and comparative advantage across sectors. Heterogeneous knowledge diffusion amplifies the specialization effects of trade-induced R&D reallocation, becoming an important source of welfare. (JEL F12, F14, O33, O34, O41)

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Growth Through Inter-sectoral Knowledge Linkages

Cited by 32 publications

References 75 publications

Staple Products, Linkages, and Development: Evidence from Argentina

Staple Products, Linkages, and Development: Evidence from Argentina

Multilayer patent citation networks: A comprehensive analytical framework for studying explicit technological relationships

Knowledge Diffusion, Trade, and Innovation across Countries and Sectors

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